SEBI, the Securities and Exchange Board of India, performs various functions to protect investors, regulate the market, and promote development. Its protective function includes prohibiting insider trading and price rigging, and promoting fair practices. Its regulatory function involves establishing

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Function-based thinking in Missouri Schoolwide Positive Behavior Support, emphasizing data-based decision-making, mission clarity, and effective teaching practices. Understand how behavior is related to the environment and how environmental interventions play a key role in shaping expected behaviors

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This lecture delves into the essential aspects of renal function tests, exploring the functional units of the kidney, the role of nephrons in maintaining homeostasis, and the intricate processes of filtration, reabsorption, and secretion within the renal tubules. Key topics include the hormonal and

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The production function is a vital mathematical equation that determines the relationship between factors of production and the quantity of output. This function plays a crucial role in optimizing production efficiency by assisting in decision-making related to input levels, output quantities, and c

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Acoramidis, a next-generation TTR stabilizer, shows promising results in improving cardiac function and promoting regression in Transthyretin Amyloid Cardiomyopathy. The ATTRibute-CM Cardiac Magnetic Resonance Substudy evaluated changes in cardiac structure, function, and amyloid burden after treatm

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Dive into function templates and generic programming in C++, exploring how to create reusable code for multiple data types. Learn about generic function templates, class templates, and how to declare function templates efficiently. Enhance your understanding of type-independent patterns and how to i

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Renal function tests are essential for diagnosing and monitoring kidney health. These tests assess functions like glomerular filtration, tubular reabsorption, and endocrine functions of the kidneys. Common indicators include serum urea, creatinine levels, and more. It's crucial to evaluate renal fun

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Approximation algorithms aim to find near-optimal solutions for optimization problems, with the performance ratio indicating how close the algorithm's solution is to the optimal solution. The terminology used in approximation algorithms includes P (optimization problem), C (approximation algorithm),

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Delve into the fascinating world of the particle-on-a-ring approximation in chemistry, exploring concepts like quantum quantization of energy levels, De Broglie approach, Schrödinger equation, and its relevance to the electronic structure of molecules. Discover how confining particles to a ring lea

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Batch reinforcement learning decouples data collection and optimization, making it data-efficient and stable. It is contrasted with online reinforcement learning, highlighting the benefits of using a fixed set of experience to optimize policies. Applications of batch RL include medical treatment opt

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In RISC-V function calls, the decision to place variables in caller-saved or callee-saved registers depends on various factors such as recursion and variable usage within the function. Additionally, understanding how function arguments are passed and stored is crucial for efficient program execution

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The Gamma function is a versatile mathematical function that generalizes the factorial function to non-integer and complex values. It has various integral definitions such as the Euler-integral form. The proof of the factorial property of the Gamma function is demonstrated through analytical continu

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Exploring learning-based low-rank approximations and linear sketches in matrices, including techniques like dimensionality reduction, regression, and streaming algorithms. Discusses the use of random matrices, sparse matrices, and the concept of low-rank approximation through singular value decompos

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Grigory Yaroslavtsev and collaborators present an improved approximation for the Directed Spanner Problem, exploring the concept of k-Spanner in directed graphs. The research delves into finding the sparsest k-spanner, preserving distances and discussing applications, including simulating synchroniz

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Structural components subjected to multi-axial cyclic loading can be analyzed for low-cycle fatigue using notch approximation. By transforming elastic response into an elastoplastic state, the computation time is reduced, and fatigue evaluation is done based on the Smith-Watson-Topper model. Strain-

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Electrons in solids obey Fermi-Dirac statistics, governed by the Fermi-Dirac distribution function. This function describes the probability of electron occupation in available energy states, with the Fermi level representing a crucial parameter in analyzing semiconductor behavior. At different tempe

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The nervous system is a complex network divided into the central nervous system (CNS) and peripheral nervous system (PNS). Neuroglia, or supporting cells, play vital roles in maintaining the health and function of neurons. Neurons, the fundamental units of the nervous system, vary in structure and f

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This paper proposes a method for dimensionality reduction based on functional approximation using Gaussian basis functions. Nonlinear Gauss weights are utilized to train a least squares support vector machine (LS-SVM) model, with further variable selection using forward-backward methodology. The met

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This piece discusses approximation algorithms for stochastic optimization problems, focusing on modeling uncertainty in inputs, adapting to stochastic predictions, and exploring different optimization themes. It covers topics such as weakening the adversary in online stochastic optimization, two-sta

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Explore the cutting-edge approaches in contention resolution schemes through submodular function maximization, multilinear relaxation, and stochastic probing. Understand constraints and relaxations involved, with a focus on balanced CRSs and approximation algorithms for maximizing weight functions.

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Push beyond traditional NLP models like logistic regression and PCFG with approximation-aware training. Explore factor graphs, BP algorithm, and fancier models to improve predictions. Learn how to tweak algorithms, tune parameters, and build custom models for machine learning in NLP.

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Explore graphing techniques including stretching, shrinking, reflecting, symmetry, translations, and various types of functions such as the identity function, square function, cube function, square root function, cube root function, and absolute value function. Understand vertical and horizontal shi

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This collection of images and data discusses the importance of monitoring thyroid function after head and neck cancer treatment, specifically focusing on post-treatment thyroid function tests, audits of practices in head and neck units, thyroid function post laryngectomy, and the significance of det

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ACCEPT is an Approximate C Compiler framework that allows programmers to designate which parts of the code can be approximated for energy and performance trade-offs. It automatically determines the best approximation parameters, identifies safe approximation areas, and can utilize FPGA for hardware

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Regret-bounded vehicle routing problems aim to minimize client delays by considering client-centric views and bounded client regret measures. This involves measuring waiting times relative to shortest-path distances from the starting depot. Additive and multiplicative regret measures are used to add

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The genitourinary system comprises the urinary and reproductive organs, with the kidneys, ureters, bladder, and urethra playing crucial roles. Maintaining proper function involves factors like renal blood flow, glomerular filtration, tubular function, and urine flow. Nephrons are the functional unit

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This research explores regret-bounded vehicle routing problems (VRPs) where the focus is on minimizing client delays based on their distances from the starting depot. The study introduces a client-centric view to measure regret and devises algorithms for both additive and multiplicative regret-based

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Mitigating memory and bandwidth walls, this research extends rollback-free value prediction to GPUs, achieving up to 2x improvement in energy and performance while maintaining 10% quality degradation. Utilizing microarchitecturally-triggered approximation to predict missed loads, this work focuses o

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This research presents LP-Based Algorithms for the Capacitated Facility Location problem, aiming to choose facilities to open and assign clients to these facilities efficiently. It discusses solving the problem using metric costs, client and facility sets, capacities, and opening costs. The research

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Dive into the intricacies of memory management with Chapter 5 by Mooly Sagiv. Explore topics such as heap allocation, limitations of stack frames, currying functions, browser events in JavaScript, static scope for function arguments, result of function calls, closures, and more. Gain insights into m

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The content covers iterative root approximation using natural logarithm in solving equations. It explores finding roots by iterative formulas and demonstrates calculations to reach approximate values. The process involves selecting intervals to show correct values and ensuring continuity for accurat

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Explore the concepts of root finding, locating roots, stationary points, and iteration in numerical methods. Learn to determine roots, stationary points, and convergence/divergence types, as well as apply the Newton-Raphson method for function approximation.

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Exploring the concepts of C++ templates including type-independent patterns for working with various data types, generic class patterns, function templates, and their usage. The reading covers examples of function templates for finding maximum values in vectors and highlights the importance of clear

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The liver carries out essential metabolic, excretory, protective, synthetic, and storage functions in the body. Liver function tests play a crucial role in screening for liver dysfunction, recognizing patterns of liver disease, assessing patient prognosis, monitoring disease progression, and evaluat

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This research discusses hierarchy-based algorithms for minimizing makespan in scheduling problems with precedence and communication constraints. Various approximation techniques, open questions in scheduling theory, and QPTAS for different settings are explored, including the possibility of beating

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In this document, the authors from Huawei discuss the analysis of employing the ambiguity function for WLAN sensing sequence design. They delve into the ambiguity function's definition, analysis, and its comparison with the range-Doppler map. The document highlights the importance of ambiguity funct

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Explore the process of developing Function-Based Behavior Support Plans (BSP) using Functional Behavioral Assessment (FBA). Understand the concepts of function and functional behavior assessment, learn how FBA/BSP fits within a multi-tiered support system, and practice developing BSP for students. D

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Explore correlation clustering, a powerful clustering method using qualitative similarities. Learn about LP rounding techniques, approximation algorithms, NP-hardness, and practical applications like document deduplication. Discover insights from leading researchers and tutorials on theory and pract

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This research explores the use of quasi-interpolation techniques to approximate functions from scattered data points in high dimensions. It discusses the interpretation of Moving Least Squares (MLS) for direct pointwise approximation of differential operators, handling singularities, and improving a

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Explore characteristics and properties of good approximation operators, such as quasi-interpolation and Moving Least-Squares (MLS), for approximating functions with singularities and near boundaries. Learn about direct approximation of local functionals and high-order approximation methods for non-s

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