The document discusses concepts related to the generative lexicon theory and statistical semantics. It provides definitions and examples of key terms, such as the generative lexicon, word sense disambiguation, and the principle of compositionality. Examples are given to illustrate how statistical semantics can be used to analyze word usage patterns and determine word meanings.
برگزاری دوره های ایزو 10002 مدریت شکایت و رضایت مشتری همراه با گواهینامه معتبر بین المللی
استاندارد مدیریت رسیدگی به شکایات مشتری ISO 10002
استاندارد ISO 10002 بعنوان الگویی برای رسیدگی به شکایات مشتریان در سازمان ها اعم از تجاری و غیرتجاری به کار می رود. در واقع هدف راهنمایی دادن به سازمان ها، مشتریان و کلیه طرف های ذینفع می باشد. طیف وسیعی از سازمان ها می توانند از این استاندارد استفاده کنند و حتی در تجارت الکترونیک نیز می توان از آن بهره برد. سیستم مدیریت رسیدگی به شکایات مشتریان ساختاری متشکل از عناصر مرتبط به هم شامل خط مشی ها، روش های اجرایی، ساختار سازمانی، اهداف و فرایندها می باشد. برای اینکه عملکرد کلی سازمان اثربخش باشد باید این عناصر در تعامل با یکدیگر طرح ریزی و اجرا شوند.
خروجی اصلی این استاندارد اثربخش نمودن فرایند رسیدگی به شکایات مشتریان و نحوه برخورد سیستماتیک با شکایات در سازمان ها می باشد که در نهایت ارتقاء کیفیت عملکرد سازمان و جلب رضایت مشتریان را به دنبال خواهد داشت و نهایتاٌ منجر به یکپارچه سازی سازمان ها در نحوه تعامل با مشتریان و برخورد با شکایات آن ها بر طبق یک الگوی جهانی خواهد شد.
تشویق مشتری به ارائه بازخورد و حتی ابراز نارضایتی و شکایت می تواند فرصتی برای سازمان ایجاد کند تا با اهمیت دادن به خواست مشتریان و تلاش برای جلب رضایت آن ها وفاداری آنها را تضمین نماید و نهایتاٌ این امر منجر به افزایش کیفیت در سطح بازار و افزایش رقابت پذیری خواهد شد.
فواید بکارگیری استاندارد مدیریت رسیدگی به شکایات مشتری ISO 10002:
· افزایش توانایی سازمان در شناسایی و تحلیل علل ریشه ای نارضایتی و اقدام در جهت رفع نواقص
· ایجاد رویکرد مشتری مداری در پرسنل سازمان و افزایش مهارت های آنها در رابطه با مشتریان
· کسب بازار از طریق اهمیت دادن به مشتریان و ایجاد محیطی باز برای ابراز بازخوردهای آنها
· سازگاری استاندارد ایزو 10002 با استاندارد
explorar y descubrir el mundo que les rodea y su funcionamiento, los niños aprenden a comprender y valorar la naturaleza y la interdependencia de los seres vivos y su entorno. Y que mejor que este cuaderno de experimentos para potenciar esta inquietud.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
47. Statistical Semantics:#J
Statistical Semantics is the study of how the
statistical patterns of human word usage can be
used to figure out what people mean, at least to
a level sufficient for information access”(ACL
wiki)
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51. Principle of compositionality (Frege1892]
… the meaning of a complex expression is determined by
the meanings of its constituent expressions and the rules
used to combine them (wikipedia
73. ħăđƫ (1/3)
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Introduction to Generative Lexicon. Foundations of
SemanticsƩĺ´ē.
http://www.cs.brandeis.edu/~jamesp/classes/LING130/
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Generative Lexicon2. Ɛ:ğ†NJ̓:ŏÌƈ
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Automatic Acquisition of Ranked Qualia Structures from the
Web. ACL2007
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0. NLP2012.
! [Mitchell+08] Jeff Mitchell, Mirella Lapata.
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! [Socher+12] Richard Socher, Brody Huval, Christopher D.
Manning, Andrew Y. Ng.
Semantic Compositionality through Recursive Matrix-Vector
Spaces. EMNLP2012.
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76. ħăđƫ(3/3)
! [Cruys+13] Tim Van de Cruys, Thierry Poibeau, Anna Korhonen.
A Tensor-based Factorization Model of Semantic
Compositionality. NAACL2013.
! [Kalchbrenner+14] Nal Kalchbrenner, Edward Grefenstette, Phil
Blunsom.
A Convolutional Neural Network for Modelling Sentences.
ACL2014.
! [Zelier+14] Matthew D. Zeiler, Rob Fergus.
Visualizing and Understanding Convolutional Networks.
ECCV2014.
! [Tsubaki+13] Masashi Tsubaki, Kevin Duh, Masashi Shimbo,
Yuji Matsumoto.
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Prototype Projections and Neural Networks. EMNLP2013
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