The limited datatyping facilities in XML have prevented validating XML processors from supplying the rigorous type checking required in these situations. The result has been that individual applications writers have had to implement type checking in an ad hoc manner.

This specification addresses the need of both document authors and applications writers for a robust, extensible datatype system for XML which could be incorporated into XML processors.

As discussed below, these datatypes could be used in other XML-related standards as well. The [XML Schema Requirements] document spells out concrete requirements to be fulfilled by this specification, which state that the XML Schema Language must:.

This portion of the XML Schema Language discusses datatypes that can be used in an XML Schema. These datatypes can be specified for element content that would be specified as PCDATA and attribute values of various types in a DTD. It is the intention of this specification that it be usable outside of the context of XML Schemas for a wide range of other XML-related activities such as [XSL] and [RDF Schema].

The terminology used to describe XML Schema Datatypes is defined in the body of this specification. The terms defined in the following list are used in building those definitions and in describing the actions of a datatype processor:. This specification provides three different kinds of normative statements about schema components, their representations in XML and their contribution to the schema-validation of information items:.

This section describes the conceptual framework behind the type system defined in this specification. The framework has been influenced by the [ISO ] standard on language-independent datatypes as well as the datatypes for [SQL] and for programming languages such as Java.

The datatypes discussed in this specification are computer representations of well known abstract concepts such as integer and date. It is not the place of this specification to define these abstract concepts; many other publications provide excellent definitions. Each value in the value space of a datatype is denoted by one or more literals in its · lexical space ·.

The · value space · of a given datatype can be defined in one of the following ways:. For example, they always have the property of · cardinality · , some definition of equality and might be · ordered · , by which individual values within the · value space · can be compared to one another. The properties of · value space · s that are recognized by this specification are defined in Fundamental facets §2. In addition to its · value space · , each datatype also has a lexical space.

For example, "" and "1. The type system defined in this specification provides a mechanism for schema designers to control the set of values and the corresponding set of acceptable literals of those values for a datatype. While the datatypes defined in this specification have, for the most part, a single lexical representation i.

each value in the datatype's · value space · is denoted by a single literal in its · lexical space · , this is not always the case. The example in the previous section showed two literals for the datatype float which denote the same value. Similarly, there · may · be several literals for one of the date or time datatypes that denote the same value using different timezone indicators. Generally speaking, each facet characterizes a · value space · along independent axes or dimensions.

The facets of a datatype serve to distinguish those aspects of one datatype which differ from other datatypes. Rather than being defined solely in terms of a prose description the datatypes in this specification are defined in terms of the synthesis of facet values which together determine the · value space · and properties of the datatype.

Facets are of two types: fundamental facets that define the datatype and non-fundamental or constraining facets that constrain the permitted values of a datatype. All fundamental facets are fully described in Fundamental Facets §4. Constraining the · value space · consequently constrains the · lexical space ·. Adding · constraining facet · s to a · base type · is described in Derivation by restriction §4.

All constraining facets are fully described in Constraining Facets §4. It is useful to categorize the datatypes defined in this specification along various dimensions, forming a set of characterization dichotomies. The first distinction to be made is that between · atomic · , · list · and · union · datatypes. For example, a single token which · match · es Nmtoken from [XML 1. The · value space · of an · atomic · datatype is a set of "atomic" values, which for the purposes of this specification, are not further decomposable.

The · lexical space · of an · atomic · datatype is a set of literals whose internal structure is specific to the datatype in question. Several type systems such as the one described in [ISO ] treat · list · datatypes as special cases of the more general notions of aggregate or collection datatypes. The · value space · of a · list · datatype is a set of finite-length sequences of · atomic · values. The · lexical space · of a · list · datatype is a set of literals whose internal structure is a space-separated sequence of literals of the · atomic · datatype of the items in the · list ·.

A · list · datatype can be · derived · from an · atomic · datatype whose · lexical space · allows space such as string or anyURI or a · union · datatype any of whose {member type definitions} 's · lexical space · allows space.

In such a case, regardless of the input, list items will be separated at space boundaries. When a datatype is · derived · from a · list · datatype, the following · constraining facet · s apply:.

For each of · length · , · maxLength · and · minLength · , the unit of length is measured in number of list items. The value of · whiteSpace · is fixed to the value collapse. For · list · datatypes the · lexical space · is composed of space-separated literals of its · itemType ·. Hence, any · pattern · specified when a new datatype is · derived · from a · list · datatype is matched against each literal of the · list · datatype and not against the literals of the datatype that serves as its · itemType ·.

The canonical-lexical-representation for the · list · datatype is defined as the lexical form in which each item in the · list · has the canonical lexical representation of its · itemType ·. The · value space · and · lexical space · of a · union · datatype are the union of the · value space · s and · lexical space · s of its · memberTypes ·.

Currently, there are no · built-in · · union · datatypes. Any number greater than 1 of · atomic · or · list · · datatype · s can participate in a · union · type. During validation, an element or attribute's value is validated against the · memberTypes · in the order in which they appear in the definition until a match is found.

The evaluation order can be overridden with the use of xsi:type. The canonical-lexical-representation for a · union · datatype is defined as the lexical form in which the values have the canonical lexical representation of the appropriate · memberTypes ·.

Next, we distinguish between · primitive · and · derived · datatypes. For example, in this specification, float is a well-defined mathematical concept that cannot be defined in terms of other datatypes, while a integer is a special case of the more general datatype decimal. anySimpleType can be considered as the · base type · of all · primitive · datatypes. anySimpleType is considered to have an unconstrained lexical space and a · value space · consisting of the union of the · value space · s of all the · primitive · datatypes and the set of all lists of all members of the · value space · s of all the · primitive · datatypes.

The datatypes defined by this specification fall into both the · primitive · and · derived · categories. It is felt that a judiciously chosen set of · primitive · datatypes will serve the widest possible audience by providing a set of convenient datatypes that can be used as is, as well as providing a rich enough base from which the variety of datatypes needed by schema designers can be · derived ·.

In the example above, integer is · derived · from decimal. As described in more detail in XML Representation of Simple Type Definition Schema Components §4. base type s can be either · primitive · or · derived ·. A · list · datatype can be · derived · from another datatype its · itemType · by creating a · value space · that consists of a finite-length sequence of values of its · itemType ·.

One datatype can be · derived · from one or more datatypes by · union · ing their · value space · s and, consequently, their · lexical space · s. Conceptually there is no difference between the · built-in · · derived · datatypes included in this specification and the · user-derived · datatypes which will be created by individual schema designers. The · built-in · · derived · datatypes are those which are believed to be so common that if they were not defined in this specification many schema designers would end up "reinventing" them.

Furthermore, including these · derived · datatypes in this specification serves to demonstrate the mechanics and utility of the datatype generation facilities of this specification. Each built-in datatype in this specification both · primitive · and · derived · can be uniquely addressed via a URI Reference constructed as follows:.

Additionally, each facet definition element can be uniquely addressed via a URI constructed as follows:. Additionally, each facet usage in a built-in datatype definition can be uniquely addressed via a URI constructed as follows:.

For example, to address the usage of the maxInclusive facet in the definition of int, the URI is:. The · built-in · datatypes defined by this specification are designed to be used with the XML Schema definition language as well as other XML specifications. To facilitate usage within the XML Schema definition language, the · built-in · datatypes in this specification have the namespace name:.

To facilitate usage in specifications other than the XML Schema definition language, such as those that do not want to know anything about aspects of the XML Schema definition language other than the datatypes, each · built-in · datatype is also defined in the namespace whose URI is:.

This applies to both · built-in · · primitive · and · built-in · · derived · datatypes. Each · user-derived · datatype is also associated with a unique namespace.

However, · user-derived · datatypes do not come from the namespace defined by this specification; rather, they come from the namespace of the schema in which they are defined see XML Representation of Schemas in [XML Schema Part 1: Structures]. The · primitive · datatypes defined by this specification are described below. For each datatype, the · value space · and · lexical space · are defined, · constraining facet · s which apply to the datatype are listed and any datatypes · derived · from this datatype are specified.

The · value space · of string is the set of finite-length sequences of character s as defined in [XML 1. A character is an atomic unit of communication; it is not further specified except to note that every character has a corresponding Universal Character Set code point, which is an integer.

string has the following · constraining facets · :. The following · built-in · datatypes are · derived · from string :. An instance of a datatype that is defined as · boolean · can have the following legal literals {true, false, 1, 0}. boolean has the following · constraining facets · :. The · value space · of decimal is the set of numbers that can be obtained by multiplying an integer by a non-positive power of ten, i. Precision is not reflected in this value space; the number 2.

The · order-relation · on decimal is the order relation on real numbers, restricted to this subset. decimal has a lexical representation consisting of a finite-length sequence of decimal digits x x39 separated by a period as a decimal indicator. An optional leading sign is allowed. Leading and trailing zeroes are optional. If the fractional part is zero, the period and following zero es can be omitted. For example: The canonical representation for decimal is defined by prohibiting certain options from the Lexical representation §3.

The decimal point is required. Leading and trailing zeroes are prohibited subject to the following: there must be at least one digit to the right and to the left of the decimal point which may be a zero.

decimal has the following · constraining facets · :. The following · built-in · datatypes are · derived · from decimal :. In addition to the basic · value space · described above, the · value space · of float also contains the following three special values : positive and negative infinity and not-a-number NaN.

Positive infinity is greater than all other non-NaN values. NaN equals itself but is · incomparable · with neither greater than nor less than any other value in the · value space ·. A literal in the · lexical space · representing a decimal number d maps to the normalized value in the · value space · of float that is closest to d in the sense defined by [Clinger, WD ] ; if d is exactly halfway between two such values then the even value is chosen.

float values have a lexical representation consisting of a mantissa followed, optionally, by the character "E" or "e", followed by an exponent. The exponent · must · be an integer. The mantissa must be a decimal number. The representations for exponent and mantissa must follow the lexical rules for integer and decimal. If the "E" or "e" and the following exponent are omitted, an exponent value of 0 is assumed. The special values positive and negative infinity and not-a-number have lexical representations INF , -INF and NaN , respectively.

Lexical representations for zero may take a positive or negative sign. For example, -1E4, The canonical representation for float is defined by prohibiting certain options from the Lexical representation §3. Specifically, the exponent must be indicated by "E". If the exponent is zero, it must be indicated by "E0". Leading and trailing zeroes are prohibited subject to the following: number representations must be normalized such that there is a single digit which is non-zero to the left of the decimal point and at least a single digit to the right of the decimal point unless the value being represented is zero.

The canonical representation for zero is 0. float has the following · constraining facets · :. In addition to the basic · value space · described above, the · value space · of double also contains the following three special values : positive and negative infinity and not-a-number NaN.

A literal in the · lexical space · representing a decimal number d maps to the normalized value in the · value space · of double that is closest to d ; if d is exactly halfway between two such values then the even value is chosen. This is the best approximation of d [Clinger, WD ] , [Gay, DM ] , which is more accurate than the mapping required by [IEEE ].

double values have a lexical representation consisting of a mantissa followed, optionally, by the character "E" or "e", followed by an exponent.

The canonical representation for double is defined by prohibiting certain options from the Lexical representation §3. double has the following · constraining facets · :. The · value space · of duration is a six-dimensional space where the coordinates designate the Gregorian year, month, day, hour, minute, and second components defined in § 5. These components are ordered in their significance by their order of appearance i.

as year, month, day, hour, minute, and second. The number of seconds can include decimal digits to arbitrary precision. The values of the Year, Month, Day, Hour and Minutes components are not restricted but allow an arbitrary unsigned integer, i. Similarly, the value of the Seconds component allows an arbitrary unsigned decimal. Following [ISO ] , at least one digit must follow the decimal point if it appears.

Thus, the lexical representation of duration does not follow the alternative format of § 5. An optional preceding minus sign '-' is allowed, to indicate a negative duration. If the sign is omitted a positive duration is indicated. See also ISO Date and Time Formats §D. For example, to indicate a duration of 1 year, 2 months, 3 days, 10 hours, and 30 minutes, one would write: P1Y2M3DT10H30M.

One could also indicate a duration of minus days as: -PD. Reduced precision and truncated representations of this format are allowed provided they conform to the following:. For example, PY, PM and P1Y2MT2H are all allowed; P0YM and P0YM0D are allowed. PM is not allowed although -PM is allowed. P1Y2MT is not allowed. In general, the · order-relation · on duration is a partial order since there is no determinate relationship between certain durations such as one month P1M and 30 days P30D.

These values for s cause the greatest deviations in the addition of dateTimes and durations. Addition of durations to time instants is defined in Adding durations to dateTimes §E. The following table shows the strongest relationship that can be determined between example durations.

Note that because of leap-seconds, a seconds field can vary from 59 to However, because of the way that addition is defined in Adding durations to dateTimes §E , they are still totally ordered. Implementations are free to optimize the computation of the ordering relationship. For example, the following table can be used to compare durations of a small number of months against days. In comparing duration values with minInclusive , minExclusive , maxInclusive and maxExclusive facet values indeterminate comparisons should be considered as "false".

Certain derived datatypes of durations can be guaranteed have a total order. For this, they must have fields from only one row in the list below and the time zone must either be required or prohibited. For example, a datatype could be defined to correspond to the [SQL] datatype Year-Month interval that required a four digit year field and a two digit month field but required all other fields to be unspecified.

This datatype could be defined as below and would have a total order. duration has the following · constraining facets · :. Each such object also has one decimal-valued method or computed property, timeOnTimeline, whose value is always a decimal number; the values are dimensioned in seconds, the integer 0 is T and the value of timeOnTimeline for other dateTime values is computed using the Gregorian algorithm as modified for leap-seconds.

The timeOnTimeline values form two related "timelines", one for timezoned values and one for non-timezoned values. Each timeline is a copy of the · value space · of decimal , with integers given units of seconds.

The · value space · of dateTime is closely related to the dates and times described in ISO For clarity, the text above specifies a particular origin point for the timeline. It should be noted, however, that schema processors need not expose the timeOnTimeline value to schema users, and there is no requirement that a timeline-based implementation use the particular origin described here in its internal representation. Other interpretations of the · value space · which lead to the same results i.

All timezoned times are Coordinated Universal Time UTC, sometimes called "Greenwich Mean Time". Other timezones indicated in lexical representations are converted to UTC during conversion of literals to values. The value of each numeric-valued property other than timeOnTimeline is limited to the maximum value within the interval determined by the next-higher property. For example, the day value can never be 32, and cannot even be 29 for month 02 and year February The · lexical space · of dateTime consists of finite-length sequences of characters of the form: '-'?

yyyy '-' mm '-' dd 'T' hh ':' mm ':' ss '. For example, T noon on 10 October , Central Daylight Savings Time as well as Eastern Standard Time in the U. is TZ, five hours later than TZ. For further guidance on arithmetic with dateTime s and durations, see Adding durations to dateTimes §E. Except for trailing fractional zero digits in the seconds representation, '' time representations, and timezone for timezoned values , the mapping from literals to values is one-to-one.

Where there is more than one possible representation, the canonical representation is as follows:. Timezones are durations with integer-valued hour and minute properties with the hour magnitude limited to at most 14, and the minute magnitude limited to at most 59, except that if the hour magnitude is 14, the minute value must be 0 ; they may be both positive or both negative.

When a timezone is added to a UTC dateTime , the result is the date and time "in that timezone". dateTime value objects on either timeline are totally ordered by their timeOnTimeline values; between the two timelines, dateTime value objects are ordered by their timeOnTimeline values when their timeOnTimeline values differ by more than fourteen hours, with those whose difference is a duration of 14 hours or less being · incomparable ·.

In general, the · order-relation · on dateTime is a partial order since there is no determinate relationship between certain instants. For example, there is no determinate ordering between a T and b T Z. It is, however, possible for this range to expand or contract in the future, based on local laws. The following definition uses the notation S[year] to represent the year field of S, S[month] to represent the month field, and so on.

This is a logical explanation of the process. Actual implementations are free to optimize as long as they produce the same results. Normalize P and Q. That is, if there is a timezone present, but it is not Z, convert it to Z using the addition operation defined in Adding durations to dateTimes §E. If P and Q either both have a time zone or both do not have a time zone, compare P and Q field by field from the year field down to the second field, and return a result as soon as it can be determined.

That is:. Certain derived types from dateTime can be guaranteed have a total order. To do so, they must require that a specific set of fields are always specified, and that remaining fields if any are always unspecified. For example, the date datatype without time zone is defined to contain exactly year, month, and day. Thus dates without time zone have a total order among themselves.

dateTime has the following · constraining facets · :. The · value space · of time is the space of time of day values as defined in § 5.

Specifically, it is a set of zero-duration daily time instances. Since the lexical representation allows an optional time zone indicator, time values are partially ordered because it may not be able to determine the order of two values one of which has a time zone and the other does not. The order relation on time values is the Order relation on dateTime §3.

See also Adding durations to dateTimes §E. Pairs of time values with or without time zone indicators are totally ordered. The lexical representation for time is the left truncated lexical representation for dateTime : hh:mm:ss. sss with optional following time zone indicator. For example, to indicate pm for Eastern Standard Time which is 5 hours behind Coordinated Universal Time UTC , one would write: The canonical representation for time is defined by prohibiting certain options from the Lexical representation §3.

Specifically, either the time zone must be omitted or, if present, the time zone must be Coordinated Universal Time UTC indicated by a "Z". Additionally, the canonical representation for midnight is time has the following · constraining facets · :. For nontimezoned values, the top-open intervals disjointly cover the nontimezoned timeline, one per day. For timezoned values, the intervals begin at every minute and therefore overlap. A "date object" is an object with year, month, and day properties just like those of dateTime objects, plus an optional timezone-valued timezone property.

As with values of dateTime timezones are a special case of durations. Just as a dateTime object corresponds to a point on one of the timelines, a date object corresponds to an interval on one of the two timelines as just described. Timezoned date values track the starting moment of their day, as determined by their timezone; said timezone is generally recoverable for canonical representations. This "timezone normalization" which follows automatically from the definition of the date · value space · is explained more in Lexical representation §3.

For the following discussion, let the "date portion" of a dateTime or date object be an object similar to a dateTime or date object, with similar year, month, and day properties, but no others, having the same value for these properties as the original dateTime or date object. The · lexical space · of date consists of finite-length sequences of characters of the form: '-'?

yyyy '-' mm '-' dd zzzzzz? where the date and optional timezone are represented exactly the same way as they are for dateTime. The first moment of the interval is that represented by: '-' yyyy '-' mm '-' dd 'T' zzzzzz? and the least upper bound of the interval is the timeline point represented noncanonically by: '-' yyyy '-' mm '-' dd 'T' zzzzzz?

Given a member of the date · value space · , the date portion of the canonical representation the entire representation for nontimezoned values, and all but the timezone representation for timezoned values is always the date portion of the dateTime canonical representation of the interval midpoint the dateTime representation, truncated on the right to eliminate 'T' and all following characters.

For timezoned values, append the canonical representation of the · recoverable timezone ·. The · value space · of gYearMonth is the set of Gregorian calendar months as defined in § 5. Specifically, it is a set of one-month long, non-periodic instances e. Since the lexical representation allows an optional time zone indicator, gYearMonth values are partially ordered because it may not be possible to unequivocally determine the order of two values one of which has a time zone and the other does not.

If gYearMonth values are considered as periods of time, the order relation on gYearMonth values is the order relation on their starting instants. This is discussed in Order relation on dateTime §3. Pairs of gYearMonth values with or without time zone indicators are totally ordered. The lexical representation for gYearMonth is the reduced right truncated lexical representation for dateTime : CCYY-MM.

No left truncation is allowed. An optional following time zone qualifier is allowed. To accommodate year values outside the range from to , additional digits can be added to the left of this representation and a preceding "-" sign is allowed.

For example, to indicate the month of May , one would write: gYearMonth has the following · constraining facets · :. The · value space · of gYear is the set of Gregorian calendar years as defined in § 5. Specifically, it is a set of one-year long, non-periodic instances e. lexical to represent the whole year , independent of how many months and days this year has. Since the lexical representation allows an optional time zone indicator, gYear values are partially ordered because it may not be possible to unequivocally determine the order of two values one of which has a time zone and the other does not.

If gYear values are considered as periods of time, the order relation on gYear values is the order relation on their starting instants.

Pairs of gYear values with or without time zone indicators are totally ordered. The lexical representation for gYear is the reduced right truncated lexical representation for dateTime : CCYY.

An optional following time zone qualifier is allowed as for dateTime. For example, to indicate , one would write: gYear has the following · constraining facets · :. Arbitrary recurring dates are not supported by this datatype. The · value space · of gMonthDay is the set of calendar dates , as defined in § 3 of [ISO ]. Specifically, it is a set of one-day long, annually periodic instances. Since the lexical representation allows an optional time zone indicator, gMonthDay values are partially ordered because it may not be possible to unequivocally determine the order of two values one of which has a time zone and the other does not.

If gMonthDay values are considered as periods of time, in an arbitrary leap year, the order relation on gMonthDay values is the order relation on their starting instants. Pairs of gMonthDay values with or without time zone indicators are totally ordered. The lexical representation for gMonthDay is the left truncated lexical representation for date : --MM-DD. An optional following time zone qualifier is allowed as for date. No preceding sign is allowed. No other formats are allowed. This datatype can be used to represent a specific day in a month.

To say, for example, that my birthday occurs on the 14th of September ever year. gMonthDay has the following · constraining facets · :. Arbitrary recurring days are not supported by this datatype. The · value space · of gDay is the space of a set of calendar dates as defined in § 3 of [ISO ].

Specifically, it is a set of one-day long, monthly periodic instances. This datatype can be used to represent a specific day of the month. To say, for example, that I get my paycheck on the 15th of each month. Since the lexical representation allows an optional time zone indicator, gDay values are partially ordered because it may not be possible to unequivocally determine the order of two values one of which has a time zone and the other does not.

If gDay values are considered as periods of time, in an arbitrary month that has 31 days, the order relation on gDay values is the order relation on their starting instants. Pairs of gDay values with or without time zone indicators are totally ordered. The lexical representation for gDay is the left truncated lexical representation for date : DD. gDay has the following · constraining facets · :. The · value space · of gMonth is the space of a set of calendar months as defined in § 3 of [ISO ].

Specifically, it is a set of one-month long, yearly periodic instances. This datatype can be used to represent a specific month. To say, for example, that Thanksgiving falls in the month of November. Since the lexical representation allows an optional time zone indicator, gMonth values are partially ordered because it may not be possible to unequivocally determine the order of two values one of which has a time zone and the other does not. If gMonth values are considered as periods of time, the order relation on gMonth is the order relation on their starting instants.

Pairs of gMonth values with or without time zone indicators are totally ordered. The lexical representation for gMonth is the left and right truncated lexical representation for date : --MM. gMonth has the following · constraining facets · :. The · value space · of hexBinary is the set of finite-length sequences of binary octets. hexBinary has a lexical representation where each binary octet is encoded as a character tuple, consisting of two hexadecimal digits [a-fA-F] representing the octet code.

For example, "0FB7" is a hex encoding for the bit integer whose binary representation is The canonical representation for hexBinary is defined by prohibiting certain options from the Lexical Representation §3. Specifically, the lower case hexadecimal digits [a-f] are not allowed. hexBinary has the following · constraining facets · :. The · value space · of base64Binary is the set of finite-length sequences of binary octets. For base64Binary data the entire binary stream is encoded using the Base64 Alphabet in [RFC ].

The lexical forms of base64Binary values are limited to the 65 characters of the Base64 Alphabet defined in [RFC ] , i. No other characters are allowed. For compatibility with older mail gateways, [RFC ] suggests that base64 data should have lines limited to at most 76 characters in length.

This line-length limitation is not mandated in the lexical forms of base64Binary data and must not be enforced by XML Schema processors. The lexical space of base64Binary is given by the following grammar the notation is that used in [XML 1.

Note that this grammar requires the number of non-whitespace characters in the lexical form to be a multiple of four, and for equals signs to appear only at the end of the lexical form; strings which do not meet these constraints are not legal lexical forms of base64Binary because they cannot successfully be decoded by base64 decoders.

The canonical lexical form of a base64Binary data value is the base64 encoding of the value which matches the Canonical-base64Binary production in the following grammar:. The length of a base64Binary value is the number of octets it contains. These could include anxiety, depression, trauma, grief, shame, self-esteem and relationship conflicts. My goal is to support and strengthen your relationship with yourself and your other relationships.

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Services offered, education and credentials vary by type of mental health professional. Each professional in Nova Scotia then may specialize in certain areas, such as depression, marriage counseling, or anxiety. Although many mental health providers are not licensed to prescribe medication, they may coordinate with a provider who can.

Both in-person and online therapy sessions are available from most psychologists. How to find a specialist? You can refine your search using the filters on this page. There are several categories you can filter by to find mental health professionals with the experience you are looking for. You may want to filter for CBT Psychologists in Nova Scotia, or Child Psychologists in Nova Scotia. Many find it useful to use filters to view only psychologists that have experience working with certain issues, like Nova Scotia psychologists specializing in EMDR.

What method of therapy is right for me? When it comes to treatment methods, there's no 'right way. Psychologists in Nova Scotia specialize in therapeutic approaches such as CBT, EMDR, and Interpersonal Therapy IPT , among others. kannada quotes ಪದೇ ಪದೇ ನೋಡುವಾಸೆ ನಿನ್ನ … ಎಷ್ಟು ನೋಡಿದರೂ ಸಾಲದು ಚಿನ್ನ.. ನಿನ್ನ ಸೌಂದರ್ಯವನ್ನ Here Are Some Sweet Love Quotes For Husbands. Until we do. We have 9 wallpapers about Sad malayalam quotes like Sad Love Quotes in Kannada Language Sad Kavanagalu - Whykol Kannada, Sad Kavanagalu in Kannada information systems definition ict Kannada: [noun] the major Dravidian language of Karnataka, southern India.

ಜೀವನದಲ್ಲಿ ಒಬ್ಬ ವ್ಯಕ್ತಿಯ ಆಗಮನ ಮತ್ತು ನಿರ್ಗಮನ ಆಕಸ್ಮಿಕವಾಗಿರುವುದಿಲ್ಲ. ಬಹಳ ಭಯ ಪಟ್ರೆ ಜೀವಿಸೋದಕ್ಕಾಗಲ್ಲ. ನೀನು ಬದುಕುತ್ತಿರುವ ಜೀವನ ಕೆಲವರಿಗೆ ಕನಸಾಗಿರುತ್ತದೆ,ಅಕೃತಜ್ಞನಾಗಬೇಡ. ಈ ಜೀವನವನ್ನು ಪ್ರೇರೇಪಿಸುವ ಸಂದೇಶಗಳು ನಿಮ್ಮ ಜೀವನದ ಎಷ್ಟೋ ಘಟನೆಗಳಿಗೆ ಹತ್ತಿರವಾಗಿರುತ್ತವೆ ಹಾಗು ಕೊಂಚ ಧೈರ್ಯವನ್ನು ತುಂಬುತ್ತವೆ. ಉತ್ತಮ ಮೋಟಿವೇಷನ್ quotes ಗಾಗಿ ಇಲ್ಲಿ ಕ್ಲಿಕ್ ಮಾಡಿ ಕ್ಲಿಕ್ ಮಾಡಿAbout Press Copyright Contact us Creators Advertise Developers Terms Press Copyright Contact us Creators Advertise Developers Terms combobox change event vba Definitions and Meaning of written word in English written word noun.

the written form of a word Examples "a craftsman of the written word" "while the spoken word stands for something, the written word stands for something that stands for something" guitar hero 2 songs download Quotes sad malayalam quote dialogue whykol.

Meaning of true friendship quotes in kannada in Random Posts. positive quotes on family; quotes about excuses; quotes about friendship ending;Nov 12, - Explore Ganesh Pandit's board "Kannada quote", followed by people on Pinterest. See more ideas about saving quotes, quotes, life quotes. a passage or expression that is quoted or cited. Synonyms : citation, quotation. a punctuation mark used to attribute the enclosed text to someone else. Synonyms : inverted …ದುಃಖ ಕ್ವೋಟ್ಸ, ಸದ್ ಕ್ವೋಟ್ಸ ಕನ್ನಡ ದಲ್ಲಿ.

Best Sad quotes in Kannada with images for whatsapp status, facebook and instagram. what names go with scarlett Enjoy reading and share 1 famous quotes about My Attitude Depends On Your Behaviour with everyone.

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Also see: Kannada to English Translation Our Apps are nice too! And more You can take these Quotes as a guide to build your life. These quotes will tell us the experiences of people. Each quote is an experience of a person. When you go through these quotes, you will come to understand that Nothing is Impossible in your life.

Best Quotes in Kannada: ಜೀವನ ಅನ್ನೋದು ಸೋಲು ಗೆಲುವಿನ ಆಟ, ಗೆದ್ದವನ Continue Reading 1quote - Meaning in Kannada, what is the meaning of quote in Kannada dictionary, pronunciation, synonyms, usage examples and definitions of quote in Kannada and English. title for boys A synonym is a word, morpheme, or phrase that means exactly or nearly the same as another word, morpheme, or phrase in a given language. For example, in the English language, the …Enjoy reading and share 1 famous quotes about My Attitude Depends On Your Behaviour with everyone.

None can teach you, none can make you spiritual. There is no other teacher but your own soul. ನಿಮ್ಮ ಸ್ವಂತ ಆತ್ಮವನ್ನು ಹೊರತುಪಡಿಸಿ ಬೇರೆ ಶಿಕ್ಷಕರು ಇಲ್ಲ. Tamil is also an official spoken language in. Translations in context of "HE WAS CALLED" in english-tamil.

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The Twist Palm Springs is a Desert Oasis Featuring the Best in Modern Architecture and Design. erpnext rest api example Love itself is a beautiful feeling. ಪ್ರೀತಿ ಎಂದರೆ ಭಾವನೆಗಳು, ವಾತ್ಸಲ್ಯ ಮತ್ತು ಇನ್ನೊಬ್ಬ ವ್ಯಕ್ತಿಯ ಮೇಲಿನ ಗೌರವ. ಪ್ರೀತಿ ಎಂದರೆ ಅರ್ಥಮಾಡಿಕೊಳ್ಳುವುದು ತುಂಬಾ ಕಷ್ಟ. ಪ್ರೀತಿಯೇ ಒಂದು …You can take these Quotes as a guide to build your life. Best Quotes in Kannada: ಜೀವನ ಅನ್ನೋದು ಸೋಲು ಗೆಲುವಿನ ಆಟ, ಗೆದ್ದವನ Continue Reading 1 docker for mac wireguard We is No.

Having students write essays is an antiquated way of teaching students something. the description is the meaning and history write-up for the name; separate search terms with spaces; search for an exact phrase by surrounding it with double quotes.

Premium a statement of the current market price of a security or commodity a short note recognizing a source of information or of a quoted passage Synonyms : acknowledgment, citation, cite, credit, mention, referenceMeaningful quotes in kannada friendship and actors. Synonyms : inverted comma, quotation mark. ಉದ್ಧರಣ ಚಿಹ್ನೆ, Meaningful quotes in kannada friendship and actors. Undeniably what matters the most is the way one treats others; your small gestures of love and generosity are what the world needs the most.

Thus, this day is a small reminder of the fact that love and kindness surpass every emotion and should be embraced to create a positive and constructive environment.

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ನಿನ್ನನ್ನು ಒಂದೊಂದು ನಿಮಿಷನು ಯೋಚನೆ ಮಾಡಿಸುತ್ತೆ" 2 " ನೀನು ಬಡವನಾಗಿ ಹುಟ್ಟಿದ್ದರೆ ಅದು ನಿನ್ನ ತಪ್ಪಲ್ಲ. ಆದರೆ ನೀನು ಬಡವನನಾಗಿ ಸತ್ತರೆ, ಅದು ಕಂಡಿತ ನಿನ್ನದೆ ತಪ್ಪು" 3 "ಗುರಿ ಇಟ್ಟುಕೊಂಡು ಸಾಗುವವರು ಸಾದಕರು ಆಗುತ್ತಾರೆಕೇವಲ ಅಸೆಗಳನ್ನು ಇಟ್ಡುಕೊಂಡವರುಸಾಮನ್ಯರಾಗಿ ಉಳಿಯುತ್ತಾರೆ" best dog park near me now Quote — ಪದದ ಅರ್ಥ Meaning , ವ್ಯಾಖ್ಯಾನ Definition , ವಿವರಣೆ Explanation ಮತ್ತು Meanings of Quote in Kannada.

A federal appeals court struck a major blow against the Consumer Financial Protection Bureau with a finding that its funding mechanism is unconstitutional. The decision is likely to be challenged, setting up a major fight for the future of the top U. consumer-finance watchdog. As set up under the Dodd-Frank Act, the CFPB is funded by the Federal Reserve rather than congressional appropriations. But Republicans have chafed at what they view as anti-business practices and a lack of oversight.

The structure has been the target of legal challenges before. Democratic Sen. Elizabeth Warren, who oversaw the CFPB's creation , responded to the ruling on Twitter, writing that "extreme right-wing judges are throwing into question every rule the CFPB enforces to protect consumers and businesses alike. Republican Sen. Cynthia Lummis, meanwhile, said the CFPB "needs the same Congressional oversight as every other government agency. The CFPB is expected to challenge the ruling, though it has yet to confirm that.

To that point, the CFPB issued new guidance to credit-reporting agencies Thursday about omitting what it called "junk data" from credit reports. The CFPB has faced several challenges to its existence over its 11 years in business. In , the Supreme Court ruled that restrictions on when its leader can be removed were unconstitutional, but rejected a plea to strike down the agency as a whole. The most significant fear from progressive lawmakers and consumer groups is that the CFPB could see its resources chopped if left to the whims of Congress.

Public Interest Research Group. The new court decision comes as the CFPB, under Biden-appointed director Rohit Chopra , has taken a more aggressive stance toward the financial industry than his Trump administration predecessors. Chopra has also promised scrutiny over the way large technology companies are expanding into financial services. But the agency is also taking up initiatives with fintech industry support, including finally setting up open-banking rules to guide data-sharing between financial institutions and tech companies.

What the ruling means for the fintech industry remains to be seen. While regulators and companies can occasionally come into conflict, the agencies also serve an important role in providing rules of the road and certainty for business models.

His decisions on major cryptocurrency cases have quoted "The Big Lebowski," "SNL," and "Dr. The ways Zia Faruqui right has weighed on cases that have come before him can give lawyers clues as to what legal frameworks will pass muster. Veronica Irwin vronirwin is a San Francisco-based reporter at Protocol covering fintech.

Previously she was at the San Francisco Examiner, covering tech from a hyper-local angle. Before that, her byline was featured in SF Weekly, The Nation, Techworker, Ms. Magazine and The Frisc. One hundred percent electronic. The author is Magistrate Judge Zia Faruqui. His rulings have made smart references to "The Big Lebowski," "Dr.

Strangelove," and "SNL" parodies of the McLaughlin Group. Rather, before taking the judge position Faruqui was one of a group of prosecutors in the U. There, Faruqui prosecuted cases that involved terrorism, child pornography, and weapons proliferation. But the ways Faruqui has weighed on cases that have come before him can give lawyers clues as to what legal frameworks will pass muster. Crypto lawyers have drawn on his prior decisions in the context of the Tornado Cash sanctions, for example.

Faruqui spoke with Protocol about the power of his position, and what people in crypto should understand about the law.

There was another prosecutor, Christopher Brown — you know, the other Chris Brown — and he had taken an interest in this when we were both working on financial crime in the Washington, D. Our U. attorney at the time, Jessie Liu, had this idea of using financial investigations in a way that was not limited to just white collar crime, or even narcotics cases, but also for cyber investigations, to national security investigations, and in civil cases.

A lot of what we were investigating was related to following the money and so she wanted us to be this multidisciplinary unit. But I have to say, we started with the goal of wanting to make T-shirts, and we never did that while I was there.

Your decisions have also gotten a lot of attention. We're public servants! And in order for the public to have faith and trust us, they need to understand what it is that we're doing and what we're saying.

Humor is one way, not using a lot of legalese is another way. But I think there are many judges who are trying to make the judiciary more accessible, and so people can see the work that we're doing and understand what we're doing and then make their own opinions about if it's right or wrong.

But at least, if it's understandable, then there's still some trust in the framework even if you don't agree with how our decisions are stated.

We are ambassadors for the judiciary to the people in our courtroom — it's a very frightening proposition being in court if you've been federally charged, and people have perceptions of what they think can happen there in terms of fairness or unfairness. But then it goes far beyond that.

I do a lot of work with the Administrative Office of the Courts, our central body doing civic education and outreach to high schools, because I want college and high school students and law students to have an experience where they get a chance to talk to a judge. So my goal is certainly not just getting to one segment of the population, but it's making decisions accessible to whoever's interested in reading them. What has it felt like for you switching from that prosecutor role to magistrate judge?

Lawyers are trying to take different frameworks from one topic and apply them to another, and then convince you that that is or is not appropriate. Being a judge is very different because you're evaluating what the parties present to you as the applicable legal frameworks, and deciding how new, groundbreaking technology fits into legal frameworks that were written 10 or 15 years ago.

But that's not really a place where judges get involved in saying how it ought to be regulated. There was, famously, a judge in Florida that said cryptocurrency was not money because you couldn't put it underneath your bed, and that's what money is: something that is tangible.

So different people are going to have different decisions. And that's not just true for crypto, but also other areas of the law.

Your best-known crypto decisions strongly assert that crypto is traceable. One way people try to make it less traceable is with mixers, and Tornado Cash was sanctioned by OFAC not too long ago.

Do you think the legal reasoning was sound enough for similar sanctions to be applied to other mixers, or decentralized exchanges? I don't know. I think there's been some discussion that people may litigate some of these things, so I can't comment, because those frequently do come to our courthouse.

And I think there are certainly people opining on that, yes and no. So much of what judges do is that we rely on the parties that are before us to tell us what's right and what's wrong. And then, you know, obviously, they'll have different views, and we make a decision based on what people say in front of us. Are you aware that some legal analysis of the Tornado Cash sanctions references your recent decision in a cryptocurrency sanctions case? That's what good lawyers will always do.

Even legislators might look at that as they try to think about where the gaps are. As a prosecutor I had a case where we sued three Chinese banks to give us their bank records, and it had never been done before. Afterwards, Congress passed a new law, using the decisions from judges in this court and the D. circuit court, the court above us. So I'm sure people look at prior decisions and try to apply them in the ways that they want to.

Are there any misconceptions about how the law applies to crypto, or how your decisions should be interpreted, that you wish you could get across? One misconception is that the judges can't understand this technology — we can. People have these views in two extremes. The lawyer's fundamental job is to take super complex and technical things and boil them down to very easily digestible arguments for a judge, for a jury, or whoever it might be.

The financial technology transformation is driving competition, creating consumer choice, and shaping the future of finance. Hear from seven fintech leaders who are reshaping the future of finance, and join the inaugural Financial Technology Association Fintech Summit to learn more.

Financial technology is breaking down barriers to financial services and delivering value to consumers, small businesses, and the economy. Fintech puts American consumers at the center of their finances and helps them manage their money responsibly.

From payment apps to budgeting and investing tools and alternative credit options, fintech makes it easier for consumers to pay for their purchases and build better financial habits. Fintech also arms small businesses with the financial tools for success, including low-cost banking services, digital accounting services, and expanded access to capital. We advocate for modernized financial policies and regulations that allow fintech innovation to drive competition in the economy and expand consumer choice.

Spots are still available for this hybrid event, and you can RSVP here to save your seat. Join us as we discuss how to shape the future of finance.

In its broadest sense, Open Banking has created a secure and connected ecosystem that has led to an explosion of new and innovative solutions that benefit the customer, rapidly revolutionizing not just the banking industry but the way all companies do business.

Target benefits are delivered through speed, transparency, and security, and their impact can be seen across a diverse range of use cases. Sharing financial data across providers can enable a customer individual or business to have real-time access to multiple bank accounts across multiple institutions all in one platform, saving time and helping consumers get a more accurate picture of their own finances before taking on debt, providing a more reliable indication than most lending guidelines currently do.

Companies can also create carefully refined marketing profiles and therefore, finely tune their services to the specific need. Open Banking platforms like Klarna Kosma also provide a unique opportunity for businesses to overlay additional tools that add real value for users and deepen their customer relationships.

The increased transparency brought about by Open Banking brings a vast array of additional benefits, such as helping fraud detection companies better monitor customer accounts and identify problems much earlier. The list of new value-add solutions continues to grow.

The speed of business has never been faster than it is today. For small business owners, time is at a premium as they are wearing multiple hats every day. Macroeconomic challenges like inflation and supply chain issues are making successful money and cash flow management even more challenging. This presents a tremendous opportunity that innovation in fintech can solve by speeding up money movement, increasing access to capital, and making it easier to manage business operations in a central place.

Fintech offers innovative products and services where outdated practices and processes offer limited options. For example, fintech is enabling increased access to capital for business owners from diverse and varying backgrounds by leveraging alternative data to evaluate creditworthiness and risk models.

RFC Residents of other geographic areas in gray are included in the results reported for all adults, registered voters, and likely voters, but sample sizes for these less-populous areas are not large enough to report separately. What existing contractual obligations are those? The editors acknowledge the members of the XML Schema Working Group, the members of other W3C Working Groups, and industry experts in other forums who have contributed directly or indirectly to the process or content of creating this document. Did you also know that have a little brain in our guts? Note: A datatype which is · primitive · in this specification need not be a "primitive" datatype in any programming language used to implement this specification. Note: Because days in one calendar only rarely correspond to days in other calendars, values of this type do not, in general, have any straightforward or intuitive representation in terms of most other calendars.

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