Miracle-dz/UniFAR-FTUs huggingface dataset:
Farnesoid X Receptor Agonists and Other Bile Acid Signaling Strategies for Treatment of Liver Disease

The intracellular nuclear receptor farnesoid X receptor (FXR) and the transmembrane G protein-coupled receptor 5 (TGR5) respond to bile acids (BAs) by activating transcriptional networks and/or signaling cascades. These cascades affect the expression of a great number of target genes relevant for BA, cholesterol, lipid and carbohydrate metabolism, as well as genes involved in inflammation, fibrosis and carcinogenesis. FXR activation in the liver tissue and beyond, such as the gut-liver axis, kidney and adipose tissue, plays a role in metabolic diseases. These BA receptors activators hold promise to become a new class of drugs to be used in the treatment of chronic liver disease, hepatocellular cancer and extrahepatic inflammatory and metabolic diseases. This review discusses the relevant BA receptors, the new drugs that target BA transport and signaling and their possible applications.
Data Centric Cache Measurement on the Intel ltanium 2 Processor

Processor speed continues to increase faster than the speed of access to main memory, making effective use of memory caches more important. Information about an application’s interaction with the cache is therefore critical to performance tuning. To be most useful, tools that measure this information should relate it to the source code level data structures in an application. We describe how to gather such information by using hardware performance counters to sample cache miss addresses, and present a new tool named Cache Scope that does this using the Intel Itanium 2 performance monitors. We present experimental results concerning Cache Scope’s accuracy and perturbation of cache behavior. We also describe a case study of using Cache Scope to tune two applications, achieving 24% and 19% reductions in running time.
Prediction-based failure management for supercomputers

The growing requirements of a diversity of applications necessitate the deployment of large and powerful computing systems and failures in these systems may cause severe damage in every aspect from loss of human lives to world economy. However, current fault tolerance techniques cannot meet the increasing requirements for reliability. Thus new solutions are urgently needed and research on proactive schemes is one of the directions that may offer better efficiency. This thesis proposes a novel proactive failure management framework. Its goal is to reduce the failure penalties and improve fault tolerance efficiency in supercomputers when running complex applications. The proposed proactive scheme builds on two core components: failure prediction and proactive failure recovery. More specifically, the failure prediction component is based on the assessment of system events and employs semi-Markov models to capture the dependencies between failures and other events for the forecasting of forthcoming failures. Furthermore, a two-level failure prediction strategy is described that not only estimates the future failure occurrence but also identifies the specific failure categories. Based on the accurate failure forecasting, a prediction-based coordinated checkpoint mechanism is designed to construct extra checkpoints just before each predicted failure occurrence so that the wasted computational time can be significantly reduced. Moreover, a theoretical model has been developed to assess the proactive scheme that enables calculation of the overall wasted computational time.The prediction component has been applied to industrial data from the IBM BlueGene/L system. Results of the failure prediction component show a great improvement of the prediction accuracy in comparison with three other well-known prediction approaches, and also demonstrate that the semi-Markov based predictor, which has achieved the precision of 87.41\% and the recall of 77.95\%, performs better than other predictors.
Sliding Mode with Time Delay Control for MIMO nonlinear Systems With unknown dynamics

In this paper, the control problem of Multi-Input Multi-Output (MIMO) nonlinear Systems with unknown dynamics is proposed. A novel method based on the Sliding Mode with Time Delay Control (SMTDC) is proposed by combining a Sliding Mode Control (SMC) with saturation (sat) function and Time Delay Control (TDC). This method (SMTDC), allows chattering reduction on control inputs and estimates the amounts of unknown or unmodeled nonlinear dynamics and unexpected uncertainties and cancels them. This algorithm was simulated on the model of the ANAT robot arm system to demonstrate the effectiveness of the proposed design method.
Microscale surgery on single axons.

OBJECTIVE The lack of meaningful axon regeneration after central nervous system damage and poor functional recovery after serious peripheral nervous system nerve injuries have been long-standing problems of substantial interest to both neurosurgeons and neurobiologists. As an alternative to strategies that seek to promote the regeneration of adult axons, our research group has taken advantage of advances in microtechnology to develop a paradigm of direct axon repair involving the substitution of damaged axon regions with healthy segments from donor axons. METHODS This repair methodology uses a novel combination of microtechnology, electrokinetic axon manipulation, and the well-established biological principle of cell fusion. These three fields of research have been integrated in a multidisciplinary approach to develop a solution for a significant clinical problem that currently has no specific treatment. RESULTS The findings reported here provide some initial proof of principle for the core technologies we intend to use for axon repair. Functional recovery from nerve damage of course is clinically challenging, and many obstacles would need to be overcome before such axon repair procedures can be contemplated for therapeutic use. We identify some of the clinical issues that must be addressed for microtechnology-assisted axon repair to transition from the realm of research into actual surgical settings. CONCLUSION It is hoped that each advance in axon repair technology will spur additional research to provide us with a comprehensive understanding on how best to pursue neurosurgical intervention at the microscale.
Analysis, Synthesis, and Retargeting of Facial Expressions

Computer animated characters have recently gained popularity in many applications, including web pages, computer games, movies, and various human computer interface designs. In order to make these animated characters lively and convincing, they require sophisticated facial expressions and motions. Traditionally, these animations are produced entirely by skilled artists. Although the quality of manually produced animation remains the best, this process is slow and costly. Motion capture performance of actors and actresses is one technique that attempts to speed up this process. One problem with this technique is that the captured motion data can not be edited easily. In recent years, statistical techniques have been used to address this problem by learning the mapping between audio speech and facial motion. New facial motion can be synthesized for novel audio data by reusing the motion capture data. However, since facial expressions are not modeled in these approaches, the resulting facial animation is realistic, yet expressionless. This thesis takes an expressionless talking face and creates an expressive facial animation. This process consists of three parts: expression synthesis, blendshape retargeting, and head motion synthesis. Expression synthesis uses a factorization model to describe the interaction between facial expression and speech content underlying each particular facial appearance. A new facial expression can be applied to novel input video, while retaining the same speech content. Blendshape retargeting maps facial expressions onto a 3D face model using the framework of blendshape interpolation. Three methods of sampling the keyshapes, or the prototype shapes, from data are evaluated. In addition, the generality of blendshape retargeting is demonstrated in three different domains. Head motion synthesis uses audio pitch contours to derive new head motion. The global and local statistics of the pitch and the coherency of head motion are utilized to determine the optimal motion trajectory. Finally, expression synthesis, blendshape retargeting, and head motion synthesis are combined into a prototype system and demonstrated through an example.
Quinone-Based Polymers for Label-Free and Reagentless Electrochemical Immunosensors: Application to Proteins, Antibodies and Pesticides Detection

Polyquinone derivatives are widely recognized in the literature for their remarkable properties, their biocompatibility, simple synthesis, and easy bio-functionalization. We have shown that polyquinones present very stable electroactivity in neutral aqueous medium within the cathodic potential domain avoiding side oxidation of interfering species. Besides, they can act as immobilized redox transducers for probing biomolecular interactions in sensors. Our group has been working on devices based on such modified electrodes with a view to applications for proteins, antibodies and organic pollutants using a reagentless label-free electrochemical immunosensor format. Herein, these developments are briefly reviewed and put into perspective.
Elsevier Editorial System(tm) for Journal of Web Semantics Manuscript Draft Title: on Demand Creation of Focused Domain Models Using Top-down and Bottom-up Information Extraction On-demand Creation of Focused Domain Models Using Top-down and Bottom-up Information Extraction

We present a hybrid method for automated on-demand creation of conceptual models of domain-specific knowledge. Models are thereby created using a two-step process of Domain Definition and Domain Description. Domain Definition creates a conceptual base whereas in the Domain Description relationships are added to the conceptual model using a pattern-based relational-targeting Information Extraction algorithm. The two-step process has the advantage over traditional approaches to ontology learning that it provides conceptual grounding through a top-down extraction and over information extraction that the extraction operates on a conceptual level so that concept integrity and reference are guaranteed. At the core of the extraction algorithm is a novel measure for semantic overlap of relationships that allows the extraction of multiple intensionally similar relationships while disambiguating merely extensionally similar relationships. The envisioned use of the created models is primarily in Information Retrieval applications, but the models can also serve as starting points for formal ontologies in Knowledge Representation applications. We detail the techniques involved in domain definition and description as well as evaluate the outcomes in depth using qualitative and quantitative evaluation metrics. ABSTRACT We present a hybrid method for automated on-demand creation of conceptual models of domain-specific knowledge. Models are thereby created using a two-step process of Domain Definition and Domain Description. Domain Definition creates a conceptual base whereas in the Domain Description relationships are added to the conceptual model using a pattern-based relational-targeting Information Extraction algorithm that deploys a novel relational pertinence measure to disambiguate semantically overlapping types of relationships. The two-step process has the advantage over traditional approaches to ontology learning that it provides conceptual grounding through a top-down extraction and over information extraction that the extraction operates on a conceptual level so that concept integrity and reference are guaranteed. At the core of the extraction algorithm is a novel measure for semantic overlap of relationships that allows the extraction of multiple intensionally similar relationships while disambiguating merely extensionally similar relationships. The envisioned use of the created models is primarily in Information Retrieval applications, but the models can also serve as starting points for formal ontologies in Knowledge Representation applications. We detail the techniques involved in domain definition and description as well as evaluate the outcomes in depth using qualitative and quantitative evaluation metrics.
PREDICTION OF BREEDING VALUES FOR UNMEASURED TRAITS FROM MEASURED TRAITS

289 Henderson (1977, 1984) described a method for prediction of breeding values for traits not in the model for records. This method may be practical for animal or sire models for the case when no measurements can be obtained on any animals for some traits to be evaluated. The least squares equations are augmented with A -1®ON1 rather than with A -1®OOl where A is the numerator relationship and 00 and ON are the genetic covariance matrices for measured and for all traits. This method can be used for each unmeasured trait or simultaneously for measured and all unmeasured traits. An option in the MTDFRUN module of the Multiple Trait Derivative Free REML (MTDFREML) program of Boldman et al. (1993) is to obtain solutions for breeding values and their prediction error variances. However, the preparation program (MTDFPREP) must be tricked to set-up equation numbers for breeding values of the unmeasured traits. Adding dummy records for the unmeasured traits but with missing records for the measured traits for dummy animals to the data file of animals with measured traits but with missing unmeasurable traits will result in the needed equations. At least two dummy records are needed to avoid a divide by zero error in calculating the sample standard deviation. The dummy records need to be associated with a level of at least one f! Xed factor. The dummy animals also must be added to the pedigree file with unknown sires and dams before running the program to obtain the inverse of the numerator relationship matrix (MTDFNRM). In the program to obtain solutions to the multiple trait mixed model equations (MTDFRUN), the full genetic (co)vaiiance matrix, ON' for both measured and unmeasured traits is needed. The residual (co)variance matrix must have zero covariances between pairs of measured and unmeasured traits but the variance of the unmeasured trait must not be zero. This procedure provides direct solutions for breeding values of unmeasured traits based on mixed model predictions of breeding values of the measured traits and also allows calculation of standard errors of prediction for the solutions directly from elements of the inverse of the augmented coefficient matrix. For example, this procedure can be used to predict breeding values of bulls (which have tenderness measurements) for the correlated trait of tenderness as a steer or heifer which cannot be measured on the bull. Conference on Applied Statistics in Agriculture Kansas State University New Prairie Press https://newprairiepress.org/agstatconference/1994/proceedings/22 290 Kansas State University
Antenna diversity for a narrow-band successive-cancellation multiuser detector

The performance of a successive-cancellation multiuser detector (SC-MUD) for narrow-band signals operating in the Rayleigh-fading channel is shown to deteriorate severely unless very large power margins at the receiver are maintained. To mitigate this deterioration, antenna diversity is applied and adapted to the SC-MUD. In each detection stage, the best signal for detection and the corresponding combining weights are determined jointly. Two criteria for selecting the best signal based on maximizing the signal-to-noise-plus-interference ratio and maximizing the minimum distance-to-noise ratio, respectively, are proposed and evaluated. For signal combining, zero forcing and minimum mean square error (mmse) combining are considered. The obtained results show that the SC-MUD with mmse combining performs close to maximum likelihood joint detection while keeping a much lower computational complexity when the number of users is less than the number of receive antennas. The effect of channel-estimation errors is investigated for orthogonal training sequences and shown to result in a minor degradation compared to perfect estimation.
Site-specific insertion of three structural gene cassettes in transposon Tn7

Transposon Tn7 has been known to carry genes for resistance to trimethoprim and spectinomycin. A poorly expressed streptothricin resistance gene, identical to the sat gene found in transposons Tn1825 and Tn1826, was localized between the two mentioned genes in Tn7. The surroundings of all three resistance genes indicated site-specific insertion of genetic cassettes.
Brane Solitons and Hypercomplex Structures

The investigation of strings and M-theory involves the understanding of various BPS solitons which in a certain approximation can be thought of as solutions of ten- and eleven-dimensional supergravity theories. These solitons have a brane or a intersecting brane interpretation, saturate a bound and are associated with parallel spinors with respect to a connection of the spin bundle of spacetime. A class of intersecting brane configurations is examined and it is shown that the geometry of spacetime is hyper-K\"ahler with torsion. A relation between these hyper-K\"ahler geometries with torsion and quaternionic calibrations is also demonstrated.
Knowledge, attitude and experience of menopause.

OBJECTIVE To determine the knowledge and attitude of women towards menopause and to investigate the symptoms experienced by postmenopausal women. DESIGN It was a cross sectional survey based on sample of convenience. PLACE AND DURATION OF STUDY Study was conducted at out patient department of Isra university hospital from 1st January 2005 to 31st December 2006. METHODS Total 863 women of age 42 to 80 years were interviewed in office of out patient department. A semi structured questionnaire was used to collect data. Data analysis done by computer software statistical program for social sciences (SPSS) version 11.0. RESULTS Mean age of respondents was 55.05, Menopause was natural in 727 (84.24%) women and 136 (15.75%) had surgical menopause. 680 (78.79%) women had little knowledge about menopause, while 137 (15.8%) women knew about effects and symptom of menopause. 680 (78.79%) women considered menopause as a natural process, while 183 (21.2%) perceived it as a disease, 720 (83.42%) women were happy about cessation of menses and they did not want to have menses again, while 143 (16.57%) women wanted to have menses again. These women were of age 45 to 58 years and 85 (59.4%) were uneducated. Frequently reported symptoms were Backache in 653 (75.66%), body aches, 576 (66.74%) and Insomnia in 544 (63.44%) women. Vasomotor symptoms (Hot Flushes and Night Sweats) were reported by 513 (59.4%) and 390 (45.19%) respectively. Short loss of memory was reported by 536 (62.10%) women. 318 (36.84%) women were bothered by menopausal symptoms but only 275 (31.86%) has consulted doctor. 649 (75.20%) women were not taking any medicine for symptoms, 08 (0.926%) were taking Herbs, 10 (1.15%) were on HRT and 196 (22.71%) women were taking analgesics and Ca supplements off and on. Hypertension and Diabetes Mellitus was present in 180 (20.85%), 215 (24.9%) women respectively. CONCLUSION Majority of our women were unaware of menopausal symptoms and its health effects. Most of them considered it as a natural process of aging, though bothered by symptoms but did not go for consultation due to lack of awareness and poverty.
IT Implementation Contract Design: Analytical and Experimental Investigation of IT Value, Learning, and Contract Structure

This article analytically and experimentally investigates how firms can best capture the business value of information technology (IT) investments through IT contract design. Using a small sample of outsourcing contracts for enterprise information technology (EIT) projects in several industries—coupled with reviews of contracts used by a major enterprise software maker—the authors determine the common provisions and structural characteristics of EIT contracts. The authors use these characteristics to develop an analytical model of optimal contract design with principal–agent techniques. The model captures a set of key characteristics of EIT contracts, including a staged, multiperiod project structure; learning; probabilistic binary outcomes; variable fee structures; possibly risk-averse agents; and implementation risks. The model characterizes conditions under which multistage contracts enable clients to create and capture greater project value than single-stage projects, and how project staging enables f.
Deliberation scheduling strategies for adaptive mission planning in real-time environments

We are developing the Multi-Agent Self-Adaptive Cooperative Intelligent Real-Time Control Architecture (MASA-CIRCA) to address high-stakes, mission-critical, hazardous domains. [5, 6]. MASA-CIRCA is a domain-independent architecture for intelligent, self-adaptive autonomous control systems that can be applied to hard real-time, mission-critical applications. MASA-CIRCA includes a Controller Synthesis Module (CSM) that can automatically synthesize reactive controllers for environments that include timed discrete dynamics. In order to best tailor its behavior to the current context, MASA-CIRCA will sequence through a number of different controllers, one for each phase of the mission (see Figure 1).
Double‐Diffusive Layering in the Canada Basin: An Explanation of Along‐Layer Temperature and Salinity Gradients

Double-diffusive mixing gives rise to layered structures in the Arctic Ocean: layers within a double-diffusive staircase overlying deeper layers associated with thermohaline intrusions. These layers exhibit well-defined lateral temperature and salinity gradients. Gradients in salinity along individual layers change sign with depth, while along-layer gradients in temperature remain the same sign with depth. A theoretical formalism is put forward to explain these features in terms of vertical divergences of double-diffusive fluxes; temperature and salinity gradients along layers are set by the depth-dependent ratio of double-diffusive heat to salt fluxes. Examination of fine structure in temperature and salinity profiles reveals how the net flux ratio depends upon whether the layer is part of an evolving thermohaline intrusion or a staircase. The physical framework in context with observations of varying along-layer gradients in temperature and salinity provides evidence for thermohaline intrusions evolving to a staircase and describes the parameters that dictate this process. Results bring new understanding to heat and salt transport in the Arctic Ocean as well as the physics of double-diffusive layering in the world's oceans. Plain Language Summary A type of ocean mixing process, double-diffusive convection, gives rise to layers in the Arctic Ocean that may be characterized by their differing temperature and salinity properties. The properties and physics of these layers are key to understanding how heat is transported vertically and laterally in the Arctic Ocean. A theoretical formalism is put forward to explain distinct features of the layers that are characterized in the observations. The physical framework in context with observations brings new understanding to how the layers evolve and how they relate to heat and salt transport in the Arctic Ocean.