Miracle-dz/UniFAR-FTUs huggingface dataset:
An Improved Approach for Confirmatory Phase III Population Pharmacokinetic Analysis

In contrast to the traditional extensive exploratory approach, the authors propose a confirmatory approach to phase III population pharmacokinetics for regulatory submissions. In their approach, they recommend a prespecified primary analysis based on phase I/II data and phase III study design. Their approach also incorporates several specific sensitivity analyses to evaluate the robustness of the conclusions. According to statistical rationale, this approach eliminates certain biases that may occur in the estimated covariate effects, thereby precluding potentially unnecessary dosing adjustments and allowing for more accurate assessments of ambiguity in the results. Because exploration is vastly reduced, the analysis time is also substantially shortened. The proposed analyses are relatively easy to implement, although careful and prospective planning is required. Applications of the approach are provided, including 2 phase III analyses for regulatory submissions. Differences between the proposed approach and the commonly used extensive exploratory analyses submitted to regulatory agencies were small and consistent with practical expectations.
Impact of Poisson synaptic inputs with a changing rate on weak-signal processing

We explore the response of a single Hodgkin-Huxley neuron to a local field potential input, which is modeled as a subthreshold harmonic signal, plus synaptic inputs from independent Poisson processes. The synaptic input rate is periodically modulated with the same frequency as the signal. The neural behavior depends remarkably on the signal frequency. The neuron is more sensitive to the signals with frequencies ranging from 30 to 65 Hz and can produce regular output spikes with a low variability. Increasing the mean synaptic input rate can improve the detection of the subthreshold signal. These results further verify that noise can play a constructive role in signal processing of neurons.
PriMo: coupled prisms for intuitive surface modeling

We present a new method for 3D shape modeling that achieves intuitive and robust deformations by emulating physically plausible surface behavior inspired by thin shells and plates. The surface mesh is embedded in a layer of volumetric prisms, which are coupled through non-linear, elastic forces. To deform the mesh, prisms are rigidly transformed to satisfy user constraints while minimizing the elastic energy. The rigidity of the prisms prevents degenerations even under extreme deformations, making the method numerically stable. For the underlying geometric optimization we employ both local and global shape matching techniques. Our modeling framework allows for the specification of various geometrically intuitive parameters that provide control over the physical surface behavior. While computationally more involved than previous methods, our approach significantly improves robustness and simplifies user interaction for large, complex deformations.
Serglycin Is the Major Secreted Proteoglycan in Macrophages and Has a Role in the Regulation of Macrophage Tumor Necrosis Factor-α Secretion in Response to Lipopolysaccharide*

It has recently been shown that serglycin is essential for maturation of mast cell secretory granules. However, serglycin is expressed also by other cell types, and in this study we addressed the role of serglycin in macrophages. Adherent cells were prepared from murine peritoneal cell populations and from spleens, and analyzed for proteoglycan synthesis by biosynthetic labeling with [35S]sulfate. Conditioned media from serglycin–/– peritoneal macrophages and adherent spleen cells displayed a 65–80% reduction of 35S-labeled proteoglycans, compared with corresponding material from serglycin+/+ cells, indicating that serglycin is the dominant secretory proteoglycan in macrophages of these origins. In contrast, the levels of intracellular proteoglycans were similar in serglycin+/+ and serglycin–/– cells, suggesting that serglycin is not stored intracellularly to a major extent in macrophages. This is in contrast to mast cells, in which serglycin is predominantly stored intracellularly. Transmission electron microscopy revealed that the absence of serglycin did not cause any major morphological effects on peritoneal macrophages, in contrast to dramatic defects in intracellular storage vesicles in peritoneal mast cells. Several secretory products were not found to be affected by the lack of serglycin. However, the secretion of tumor necrosis factor-α in response to lipopolysaccharide stimulation was markedly higher in serglycin–/– cultures than in those of serglycin+/+. The present report thus demonstrates that serglycin is the major proteoglycan secreted by peritoneal macrophages and suggests that the macrophage serglycin may have a role in regulating secretion of tumor necrosis factor-α.
Polymorphisms in Long Noncoding RNA H19 Contribute to the Protective Effects of Coal Workers’ Pneumoconiosis in a Chinese Population

The H19 is a kind of long noncoding RNA, which has been implicated in multiple biological functions. However, the associations between genetic variants in H19 and susceptibility of coal workers’ pneumoconiosis (CWP) have been seldom reported. In the present study, three potential polymorphisms (rs2067051, rs217727, and rs2839702) in H19 were genotyped in a case-control study including 703 CWP cases and 705 controls. We found that individuals with the H19 rs2067051 CT/TT genotypes showed a decreased risk of CWP compared with those with the CC genotype (adjusted OR = 0.64, 95%CI = 0.49–0.83, p = 0.001). Further stratified analyses revealed that the associations between variant genotypes of rs2067051 and the risk of CWP were more prominent in subjects of non-smokers (adjusted OR = 0.55, 95%CI = 0.39–0.79, p = 0.001) and CWP patients with Stage I (adjusted OR = 0.63, 95%CI = 0.46–0.86, p = 0.004). Additionally, the protective effects of H19 rs2067051 were also evident in coal miners both with dust exposure years <25 years (adjusted OR = 0.63, 95%CI = 0.42–0.95, p = 0.026) and ≥25 years (adjusted OR = 0.57, 95%CI = 0.40–0.80, p = 0.001). Our results indicated that rs2067051 in the H19 gene is correlated with a deceased risk of CWP in a Chinese population, which may be a potential genetic marker for prevention and intervention of CWP. Further functional studies are warranted to validate our findings.
Adjuvant imatinib for gastrointestinal stromal tumors: the current situation and problems

Abstract Objective. To review the current situation and find out the current problems of adjuvant imatinib for gastrointestinal stromal tumors (GISTs). Methods. Searching for articles and records about imatinib for GISTs, especially adjuvant imatinib for GISTs, on MEDLINE, EMBASE and international conference on gastrointestinal. Results. GISTs are derived from mesenchymal cells of the gastrointestinal tract. The standard treatment for primary GISTs is to resect the tumor together with the negative margins completely without tumor rupture and spillage. Conventional chemotherapy and radiotherapy is ineffective for advanced GISTs. The introduction of imatinib has dramatically changed the natural history of advanced GISTs. Imatinib is generally safe and effective with doses of 400, 600 or 800 mg daily, and has become the standard drug in the treatment for patients with advanced GISTs. Furthermore, most of the toxicity of imatinib is minimal and manageable, almost no treatment-related deaths have been reported. Therefore, adjuvant imatinib therapy is safe and seems to improve recurrence-free survival after the resection of primary GISTs. Conclusions. Although U.S Food and Drug Administration and European Medicines Agency have approved the use of adjuvant imatinib for GISTs postoperatively, a series of questions about the use of adjuvant imatinib still exist, such as the impact of adjuvant imatinib on overall survival, the optimal dose, the best duration of treatment and the most suitable patients. Doctors and patients should weigh the pros (the decrease of relapse) and cons (drug toxicity and drug costs), especially in terms of the benefit of overall survival.
Exploring the effect of depressive symptoms and ageing on metamemory in an Italian adult sample

The current study aimed to investigate the effect of depression and age-related factors on metamemory measures in an Italian adult sample. Fifty-eight healthy participants were recruited in Northern Italy and were, respectively, assigned to the following groups: Young (20–30 years old), old (60–70 years old), and Very Old (71–84 years old). Participants were administered a battery of tests, including a word recall task, self-referent mnestic efficiency scales, general beliefs about memory, and depression measures. General beliefs about memory, self-efficacy, and beliefs about the control of personal memory were predicted by age, education, depression, and mnestic and cognitive efficiency. Finally, age-related differences were found in metamemory measures: the accuracy of mnestic control processes is thought to be lower by very old adults than by old and young individuals.
The effect of Hispanic accents on employment decisions

Purpose – Despite the fact that Hispanics are the largest and fastest growing segment of the population and that 44 percent of Hispanics of 18 years of age and older speak English less than very well, research examining the impact of Spanish‐accented English on employment‐related decisions has been scarce. Therefore, the present study aimed to examine the effects of the accent (standard American English and Mexican Spanish) of a hypothetical job applicant on employment‐related judgments and hiring decisions.Design/methodology/approach – Participants made employment‐related decisions (i.e. job suitability ratings, likelihood of a promotion, and hiring decision) and judgments of personal attributes (i.e. perceived competence and warmth) of a hypothetical applicant for an entry‐level software engineering job. The accent of the applicant was manipulated using the matched‐guise technique.Findings – Results showed that compared to an applicant with a standard American‐English accent, one with a Mexican‐Spanish .
Towards Fast 3D Nanoparticle Localization for Studying Molecular Dynamics in Living Cells

Studying molecular dynamics is crucial for understanding b iological processes in living cells. In principle, this is achieved by attaching fluorescent particles to molecules of interest and their detection using fluorescence microscopy. These analysis require fast optical technique s with at least 20Hz frame rate and a resolution below the diffraction limit in all three spatial dimensions . Current approaches basically rely on determining the correlation between features of the particle’s 2D point spread function (PSF) and the focal distance to the center of the particle. However, they are still unsuitable f or the application to live cell imaging where the refractive index mismatch is present. This mismatch leads t o non-stationary optical properties of the particles on which the algorithms rely, necessitating a calibration p rocedure prior to every experiment. However, this is almost unfeasible to particles attached to living cells. We established a spinning disk confocal setup and employ Qua ntum dots (QD) as fluorescence particles. Corresponding models of the axial PSF features that define the di stance to the center of the particle are developed and analyzed in the presence of the refractive index mismatc h. We present this analysis as the base for the future development of a 3D localization technique applicab le to living cells.
Large-scale resting state network correlates of cognitive impairment in Parkinson's disease and related dopaminergic deficits

Cognitive impairment is a common non-motor feature of Parkinson's disease (PD). Understanding the neural mechanisms of this deficit is crucial for the development of efficient methods for treatment monitoring and augmentation of cognitive functions in PD patients. The current study aimed to investigate resting state fMRI correlates of cognitive impairment in PD from a large-scale network perspective, and to assess the impact of dopamine deficiency on these networks. Thirty PD patients with resting state fMRI were included from the Parkinson's Progression Marker Initiative (PPMI) database. Eighteen patients from this sample were also scanned with 123I-FP-CIT SPECT. A standardized neuropsychological battery was administered, evaluating verbal memory, visuospatial, and executive cognitive domains. Image preprocessing was performed using an SPM8-based workflow, obtaining time-series from 90 regions-of-interest (ROIs) defined from the AAL brain atlas. The Brain Connectivity Toolbox (BCT) was used to extract nodal strength from all ROIs, and modularity of the cognitive circuitry determined using the meta-analytical software Neurosynth. Brain-behavior covariance patterns between cognitive functions and nodal strength were estimated using Partial Least Squares. Extracted latent variable (LV) scores were matched with the performances in the three cognitive domains (memory, visuospatial, and executive) and striatal dopamine transporter binding ratios (SBR) using linear modeling. Finally, influence of nigrostriatal dopaminergic deficiency on the modularity of the “cognitive network” was analyzed. For the range of deficits studied, better executive performance was associated with increased dorsal fronto-parietal cortical processing and inhibited subcortical and primary sensory involvement. This profile was also characterized by a relative preservation of nigrostriatal dopaminergic function. The profile associated with better memory performance correlated with increased prefronto-limbic processing, and was not associated with presynaptic striatal dopamine uptake. SBR ratios were negatively correlated with modularity of the “cognitive network,” suggesting integrative effects of the preserved nigrostriatal dopamine system on this circuitry.
Robotics and Autonomous Systems a Survey of Bio-inspired Robotics Hands Implementation: New Directions in Dexterous Manipulation

Recently, significant advances have been made in ROBOTICS, ARTIFICIAL INTELLIGENCE and other COGNITIVE related fields, allowing to make much sophisticated biomimetic robotics systems. In addition, enormous number of robots have been designed and assembled, explicitly realize biological oriented behaviors. Towards much skill behaviors and adequate grasping abilities (i.e. ARTICULATION and DEXTEROUS MANIPULATION), a new phase of dexterous hands have been developed recently with biomimetically oriented and bio-inspired functionalities. In this respect, this manuscript brings a detailed survey of biomimetic based dexterous robotics multi-fingered hands. The aim of this survey, is to find out the state of the art on dexterous robotics end-effectors, known in literature as (ROBOTIC HANDS) or (DEXTEROUS MULTI-FINGERED) robot hands. Hence, this review finds such biomimetic approaches using a framework that permits for a common description of biological and technical based hand manipulation behavior. In particular, the manuscript focuses on a number of developments that have been taking place over the past two decades, and some recent developments related to this biomimetic field of research. In conclusions, the study found that, there are rich research efforts in terms of KINEMATICS, DYNAMICS, MODELING and CONTROL methodologies. The survey is also indicating that, the topic of biomimetic inspired robotics systems make significant contributions to robotics hand design, in four main directions for future research. First, they provide a genuine world test of models of biologically inspired hand designs and dexterous manipulation behaviors. Second, they provide novel manipulation articulations and mechanisms available for industrial and domestic uses, most notably in the field of human like hand design and real world applications. Third, this survey has also indicated that, there are quite large number of attempts to acquire biologically inspired hands. These attempts were almost successful, where they exposed more novel ideas for further developments. Such inspirations were directed towards a number of topics related (HAND MECHANICS AND DESIGN), (HAND TACTILE SENSING), (HAND FORCE SENSING), (HAND SOFT ACTUATION) and (HAND CONFIGURATION AND TOPOLOGY). FOURTH, in terms of employing AI related sciences and cognitive thinking, it was also found that, rare and exceptional research attempts were directed towards the employment of biologically inspired thinking, i.e. (AI, BRAIN AND COGNITIVE SCIENCES) for hand upper control and towards much sophisticated dexterous movements. Throughout the study, it has been found there are number of efforts in terms of mechanics and hand designs, tactical sensing, however, for hand soft actuation, it seems this area of research …
Measurement and evaluation in education and psychology.

Measurement And Evaluation In Education Evaluation . Creating valid and reliable assessments is critical to accurately measuring educational data. Evaluating the information gathered, however, is equally important to the effective use of the information for instruction. In education, evaluation is the process of using the measurements gathered in the assessments. Teachers use this information to judge the relationship between what was intended by the instruction and what was learned.
Trace Selection For Compiling Large C Application Programs To Microcode

Microcode optimization techniques such as code scheduling and resource allocation can benefit significantly by reducing uncertainties in program control flow. A trace selection algorithm with profiling information reduces the uncertainties in program control flow by identifying sequences of frequently invoked basic blocks as traces. These traces are treated as sequential codes for optimization purposes. Optimization based on traces is especially useful when the code size is large and the control structure is complicated enough to defeat hand optimizations. However, most of the experimental results reported to date are based on small benchmarks with simple control structures. For different trace selection algorithms, we report the distribution of control transfers categorized according to their potential impact on the microcode optimizations. The experimental results are based on ten C application programs which exhibit large code size and complicated control structure. The measured data for each program is accumulated across a large number of input files to ensure the reliability of the result. All experiments are performed automatically using our IMPACT C compiler which contains integrated profiling and analysis tools.
Combining Syntactic and Semantic Features by SVM for Unrestricted Coreference Resolution

The paper presents a system for the CoNLL-2011 share task of coreference resolution. The system composes of two components: one for mentions detection and another one for their coreference resolution. For mentions detection, we adopted a number of heuristic rules from syntactic parse tree perspective. For coreference resolution, we apply SVM by exploiting multiple syntactic and semantic features. The experiments on the CoNLL-2011 corpus show that our rule-based mention identification system obtains a recall of 87.69%, and the best result of the SVM-based coreference resolution system is an average F-score 50.92% of the MUC, B-CUBED and CEAFE metrics.
Knowledge or Gaming?: Cognitive Modelling Based on Multiple-Attempt Response

Recent decades have witnessed the rapid growth of intelligent tutoring systems (ITS), in which personalized adaptive techniques are successfully employed to improve the learning of each individual student. However, the problem of using cognitive analysis to distill the knowledge and gaming factor from students learning history is still underexplored. To this end, we propose a Knowledge Plus Gaming Response Model (KPGRM) based on multiple-attempt responses. Specifically, we first measure the explicit gaming factor in each multiple-attempt response. Next, we utilise collaborative filtering methods to infer the implicit gaming factor of one-attempt responses. Then we model student learning cognitively by considering both gaming and knowledge factors simultaneously based on a signal detection model. Extensive experiments on two real-world datasets prove that KPGRM can model student learning more effectively as well as obtain a more reasonable analysis.
Ensemble Classifiers for Medical Diagnosis of Knee Osteoarthritis Using Gait Data

Automated or semi-automated gait analysis systems are important in assisting physicians for diagnosis of various diseases. The objective of this study is to discuss ensemble methods for gait classification as a part of preliminary studies of designing a semi-automated diagnosis system. For this purpose gait data is collected from 110 sick subjects (having knee osteoarthritis (OA)) and 91 age-matched normal subjects. A set of multilayer perceptrons (MLPs) is trained by using joint angle and time-distance parameters of gait as features. Large dimensional feature vector is decomposed into feature subsets and the ones selected by gait expert are used to categorize subjects into two classes; healthy and patient. Ensemble of MLPs is built using these distinct feature subsets and diversification of classifiers is analyzed by cross-validation approach and confusion matrices. High diversifications observed in the confusion matrices suggested that using combining methods would help. Indeed, when a proper combining rule is applied to decomposed sets, more accurate results are obtained. The result suggests that ensemble of MLPs could be applied in the automated diagnosis of gait disorders in a clinical context
High Performance Network Storage Solution

The ideal network storage system is globally accessible always available, provides high performance and capacity for a large number of files and requires no manual management. This paper discusses the design, implementation and performance of “virtual hard drive system (VHD)” a system that attempts to approximate this idea in practice through a novel combination of features. VHD system consists of collection of “Masters” that cooperatively manages a pool of physical disks of nodes. To a “Node” this collection appears as a highly available block level storage system that provide large abstract container called virtual disk. A virtual disk is globally accessible to all nodes on the network. We have an initial “VHD system” prototype consist of 15 800MHz systems running Windows 2000 professional and Red Hat 5.0 connected 100Mbits/s.
Thrombolysis for Pulmonary Embolism and Venous Thrombosis: Is It Worthwhile?

Venous thromboembolism is a frequently occurring and potentially fatal disease characterized by short-term and long-term sequelae. Conventional treatment consists of heparin and vitamin K antagonists, but there is an ongoing controversy if more aggressive therapy, such as thrombolytic drugs, should be used in selected patients to achieve faster clot lysis in pursuit of better clinical outcome. A review of the literature shows that thrombolytic therapy is not recommended in the treatment of venous thrombosis. Although in deep vein thrombosis systemically administered and catheter-directed thrombolysis both offer advantages in improving vein patency and reducing the postthrombotic syndrome (PTS), prevention of severe PTS remains unproved while the bleeding risk is high. In pulmonary embolism (PE), thrombolytic therapy is generally recommended for patients with massive PE and hemodynamic instability, despite scarce and inconclusive evidence. There is no evidence that thrombolysis has a benefit over standard anticoagulant treatment in normotensive patients with acute PE, but more research is needed to better identify the subgroup of patients with nonmassive PE in whom the risk-benefit ratio is most favorable. Until this group is defined and the benefit of thrombolytic therapy is demonstrated, thrombolytic therapy should only be considered in patients with signs of massive PE and hemodynamic shock.