Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Estimation of Mean in Randomized Response Models ABSTRACT | FULL TEXT

The present investigation considers the problem of estimating the mean of a sensitive quantitative variable μA in a human population survey, using the scrambled response technique suggested by Ryu, Kim, Heo and Park (On stratified randomized response sampling, Model Assisted Statistics and Application 1(1), 31–36, 2005–2006). Specifically, using the prior estimate (or guessed mean) of the mean of a population, a family of estimators μ̂Ak is presented to estimate the population mean μA, and its properties are examined. The optimum value of the degree k(0 ≤ k ≤ 1) of the belief in the prior estimate depends, besides others, on the unknown population parameters, e.g. mean and variance, so the proposed family of estimators may have limited practical applications. In an attempt to overcome this problem, another estimator based on the estimated optimum value of k has been proposed. The proposed estimator has been compared with the Ryu et al. and Hussain and Shabbir (Improved estimation procedure for the mean of a sensitive variable using randomized response model, Pakistan Journal of Statistics 25(2), 205–220, 2009) estimators assuming simple random sampling with replacement.
Relevance of lung ultrasound in the diagnosis of acute respiratory failure: the BLUE protocol.

BACKGROUND This study assesses the potential of lung ultrasonography to diagnose acute respiratory failure. METHODS This observational study was conducted in university-affiliated teaching-hospital ICUs. We performed ultrasonography on consecutive patients admitted to the ICU with acute respiratory failure, comparing lung ultrasonography results on initial presentation with the final diagnosis by the ICU team. Uncertain diagnoses and rare causes (frequency<2%) were excluded. We included 260 dyspneic patients with a definite diagnosis. Three items were assessed: artifacts (horizontal A lines or vertical B lines indicating interstitial syndrome), lung sliding, and alveolar consolidation and/or pleural effusion. Combined with venous analysis, these items were grouped to assess ultrasound profiles. RESULTS Predominant A lines plus lung sliding indicated asthma (n=34) or COPD (n=49) with 89% sensitivity and 97% specificity. Multiple anterior diffuse B lines with lung sliding indicated pulmonary edema (n=64) with 97% sensitivity and 95% specificity. A normal anterior profile plus deep venous thrombosis indicated pulmonary embolism (n=21) with 81% sensitivity and 99% specificity. Anterior absent lung sliding plus A lines plus lung point indicated pneumothorax (n=9) with 81% sensitivity and 100% specificity. Anterior alveolar consolidations, anterior diffuse B lines with abolished lung sliding, anterior asymmetric interstitial patterns, posterior consolidations or effusions without anterior diffuse B lines indicated pneumonia (n=83) with 89% sensitivity and 94% specificity. The use of these profiles would have provided correct diagnoses in 90.5% of cases. CONCLUSIONS Lung ultrasound can help the clinician make a rapid diagnosis in patients with acute respiratory failure, thus meeting the priority objective of saving time.
Long‐Term Neuropsychological Outcome After Traumatic Brain Injury

Objective:To describe neuropsychological outcome 5 years after injury in persons with traumatic brain injury (TBI) who received inpatient medical rehabilitation. To determine the magnitude and pattern neuropsychological recovery from 1 year to 5 years after injury. Design:Longitudinal cohort study with inclusion based on the availability of neuropsychological data at 1 year and 5 years after injury. Setting:National Institute on Disability and Rehabilitation Research Traumatic Brain Injury Model Systems of Care. Participants:One hundred eighty-two persons with complicated mild to severe traumatic brain injury. Primary Outcome Measures:Digits Forward and Backward, Logical Memory I and II, Token Test, Controlled Oral Word Association Test, Symbol Digit Modalities Test, Trail Making Test, Rey Auditory Verbal Learning Test, Visual Form Discrimination, Block Design, Wisconsin Card Sorting Test, and Grooved Pegboard. Results:Significant variability in outcome was found 5 years after TBI, ranging from no measurable impairment to severe impairment on neuropsychological tests. Improvement from 1 year after injury to 5 years was also variable. Using the Reliable Change Index, 22.2% improved, 15.2% declined, and 62.6% were unchanged on test measures. Conclusions:Neuropsychological recovery after TBI is not uniform across individuals and neuropsychological domains. For a subset of persons with moderate to severe TBI, neuropsychological recovery may continue several years after injury with substantial recovery. For other persons, measurable impairment remains 5 years after injury. Improvement was most apparent on measures of cognitive speed, visuoconstruction, and verbal memory.
Modeling Chaotic Behavior of Chittagong Stock Indices

Stock market prediction is an important area of financial forecasting, which attracts great interest to stock buyers and sellers, stock investors, policy makers, applied researchers, and many others who are involved in the capital market. In this paper, a comparative study has been conducted to predict stock index values using soft computing models and time series model. Paying attention to the applied econometric noises because our considered series are time series, we predict Chittagong stock indices for the period from January 1, 2005 to May 5, 2011. We have used well-known models such as, the genetic algorithm (GA) model and the adaptive network fuzzy integrated system (ANFIS) model as soft computing forecasting models. Very widely used forecasting models in applied time series econometrics, namely, the generalized autoregressive conditional heteroscedastic (GARCH) model is considered as time series model. Our findings have revealed that the use of soft computing models is more successful than the considered time series model.
Predation of arthropods by southern bearded sakis (Chiropotes satanas) in Eastern Brazilian Amazonia

Bearded sakis are seed predators, but are also known to consume arthropods. This is the first detailed report of arthropod predation in southern bearded sakis (Chiropotes satanas). Two groups were monitored–one in continuous forest, and one on a small island–between January 2003 and February 2004. The arthropod prey included spiders and six insect orders. Island group members spent more time foraging for arthropods (3.8% vs. 2.6% of activity time) but ingested less prey (3.7% vs. 4.6% of feeding time). Arthropods accounted for a small proportion of feeding records in most months, but there were occasional sharp peaks due to the exploitation of temporary agglomerations of insects. In November, arthropods accounted for 26.6% and 14.2% of the feeding records of the mainland and island groups, respectively. The results suggest that bearded sakis actively seek arthropods as a dietary supplement, but that they represent a minor resource during most of the year, even under conditions of intense habitat fragmentation (island group). Am. J. Primatol. 68:209–215, 2006. © 2006 Wiley‐Liss, Inc.
Physics-Based Scoring of Protein-Ligand Complexes: Enrichment of Known Inhibitors in Large-Scale Virtual Screening

We demonstrate that using an all-atom molecular mechanics force field combined with an implicit solvent model for scoring protein-ligand complexes is a promising approach for improving inhibitor enrichment in the virtual screening of large compound databases. The rescoring method is evaluated by the extent to which known binders for nine diverse, therapeutically relevant enzymes are enriched against a background of approximately 100,000 drug-like decoys. The improvement in enrichment is most robust and dramatic within the top 1% of the ranked database, that is, the first thousand compounds; below the first few percent of the ranked database, there is little overall improvement. The improved early enrichment is likely due to the more realistic treatment of ligand and receptor desolvation in the rescoring procedure. We also present anecdotal but encouraging results assessing the ability of the rescoring method to predict specificity of inhibitors for structurally related proteins.
Bayesian CRLB for Joint AoA, AoD and Multipath Gain Estimation in Millimeter Wave Wireless Networks

In this paper, we present an analysis of the non- random and the Bayesian Cramer-Rao lower bound (CRLB) for the joint estimation of angle-of-arrival (AoA), angle-of-departure (AoD), and the multipath gain in the millimeter-wave (mmWave) wireless networks. Our analysis is applicable to multipath channels with Gaussian noise and independent path parameters. Numerical results based on uniform AoA and AoD in $[0,\pi)$, and Rician fading path gains, reveal that the Bayesian CRLB decreases monotonically with an increase in the Rice factor. Further, the CRLB obtained by using beam forming and combining code books generated by quantizing directly the domain of AoA and AoD was found to be lower than those obtained with other types of beam forming and combining code books.
[Functional anatomy of the basal ganglia].

INTRODUCTION The cerebral cortex of mammals is massively interconnected with the basal ganglia. The manner in which the basal ganglia process information has been accepted since it was described in the 1980s. It is not a definitive model and many aspects of it still need clarification. DEVELOPMENT The corpus striatum (ST) forms the entrance to the basal ganglia circuit (BG) and receives numerous afferent fibres from the cerebral cortex. Similarly, the internal segment of the globus pallidus (GPi) and the substantia nigra pars reticulata (SNpr) form the main nuclei for exit from the circuit and have an inhibitory effect on the pre-motor neurones of the ventral lamina of the thalamus. Between the entrance nucleus and the exit structures are two parallel systems of projection known as the direct and indirect pathways. The direct pathway projects monosynaptically only on the Gpi/SNpr complex. The indirect pathway projects polysynaptically on to the GR/SNpr complex after passing through the external segment of the globus pallidus (Gpe) and subthalamic nucleus. Imbalance in the activity of these two circuits will lead to alterations in discharge from the Gpi/SNpr complex which will cause bradykinesia or hyperkinesia. The bradykinesia or akinesia would be caused by increased gabaergic inhibition of the thalamic premotor neurones as a result of excessive discharge of the Gpi/SNpr complex. CONCLUSION Current exploration of the electrophysiology of the basal ganglia and careful analysis of the clinical findings in lesions circumscribed to certain parts of the thalamus, subthalamus and internal globus pallidus in patients with Parkinson's disease, have led to the appearance of paradoxical effects, according to the current basal ganglia model.
Performance of Children with Traumatic Brain Injury on the Cognitive Assessment System

Children and adolescents with traumatic brain injury (TBI) were compared to a matched sample of neurologically normal children and adolescents on several measures of cognitive processing. Each of the children in the TBI group had experienced a closed head injury of moderate to severe magnitude. Participants in both the TBI (n = 22) and control (n = 22) groups ranged in age from 9 to 17 years and lived in the midwestern United States. They were all administered the Cognitive Assessment System (Naglieri & Das, 1997a). Children with TBI earned significantly lower scores in the domains of Planning and Attention than the matched control group. Within-group comparisons showed that the TBI group's Planning and Attention scores were significantly lower than their Simultaneous and Successive scores. The results are consistent with previous literature demonstrating poor performance on measures of attention and executive functions among children who have experienced TBI.
Neural Correlates of Biased Responses: The Negative Method Effect in the Rosenberg Self-Esteem Scale Is Associated with Right Amygdala Volume.

Self-esteem is a widely studied construct in psychology that is typically measured by the Rosenberg Self-Esteem Scale (RSES). However, a series of cross-sectional and longitudinal studies have suggested that a simple and widely used unidimensional factor model does not provide an adequate explanation of RSES responses due to method effects. To identify the neural correlates of the method effect, we sought to determine whether and how method effects were associated with the RSES and investigate the neural basis of these effects. Two hundred and eighty Chinese college students (130 males; mean age = 22.64 years) completed the RSES and underwent magnetic resonance imaging (MRI). Behaviorally, method effects were linked to both positively and negatively worded items in the RSES. Neurally, the right amygdala volume negatively correlated with the negative method factor, while the hippocampal volume positively correlated with the general self-esteem factor in the RSES. The neural dissociation between the general self-esteem factor and negative method factor suggests that there are different neural mechanisms underlying them. The amygdala is involved in modulating negative affectivity; therefore, the current study sheds light on the nature of method effects that are related to self-report with a mix of positively and negatively worded items.
AiX-Analytics: Analytics Tool at RWTH Aachen University

In this paper we present the AiX-Analytics prototype. The tool is a web-based prototype that visualizes usage statistics and analytics of the learning platform’s log data. The prototype has three parts: data management, RESTful application engine, and user interface(s). The data management receives, cleans, analyzes and aggregates the learning platform logs, and saves the derived results and analytics. The RESTful application engine is a Web API application that provides data and analytics to the front-end (UI). The user interface provides a set of visualizations, which interactively presents the learning data for different stakeholders in higher education scenarios. The user interface has two main aspects. The first is intended for the university’s administration and eLearning coordinators, in order to help in understanding how different faculties and institutes use the learning platform. The second aspect focuses on individual courses, where the teaching staff and students can take a look which modules, when, and how were used during the ongoing semester(s). The presented work is an ongoing research project at the Learning Technologies Research Group at RWTH Aachen University.
High-Sensitivity Cardiac Troponin Concentrations in Patients with Chest Discomfort: Is It the Heart or the Kidneys As Well?

Background High-sensitivity cardiac troponins (hs-cTn) are the preferred biomarkers to detect myocardial injury, making them promising risk-stratifying tools for patients with symptoms of chest pain. However, circulating hs-cTn are also elevated in other conditions like renal dysfunction, complicating appropriate interpretation of low-level hs-cTn concentrations. Methods A cross-sectional analysis was performed in 1864 patients with symptoms of chest discomfort from the cardiology outpatient department who underwent cardiac computed tomographic angiography (CCTA). Serum samples were analyzed using hs-cTnT and hs-cTnI assays. Renal function was measured by the estimated glomerular filtration rate (eGFR), established from serum creatinine and cystatin C. On follow-up, the incidence of adverse events was assessed. Results Median hs-cTnT and hs-cTnI concentrations were 7.2(5.8–9.2) ng/L and 2.6(1.8–4.1) ng/L, respectively. Multivariable regression analysis revealed that both assay results were more strongly associated with eGFR (hs-cTnT:stβ:-0.290;hs-cTnI:stβ:-0.222) than with cardiac imaging parameters, such as coronary calcium score, CCTA plaque severity score and left ventricular mass (all p<0.01). Furthermore, survival analysis indicated lower relative risks in patients with normal compared to reduced renal function for hs-cTnT [HR(95%CI), 1.02(1.00–1.03) compared to 1.07(1.05–1.09)] and hs-cTnI [1.01(1.00–1.01) compared to 1.02(1.01–1.02)] (all p<0.001). Conclusion In patients with chest discomfort, we identified an independent influence of renal function on hs-cTn concentrations besides CAD, that affected the association of hs-cTn concentrations with adverse events. Estimating renal function is therefore warranted when interpreting baseline hs-cTn concentrations.
An SFS Berger check prediction ALU and its application to self-checking processor designs

A strongly fault secure (SFS) ALU design based on the Berger check prediction (BCP) technique is presented. The fault and error models of a large class of VLSI ALU designs are discussed. The proposed design is proved to be fault-secure and self-testing with respect to any single fault in the ALU part. The proposed BCP ALU is proved to be SFS with any design of BCP circuit. Consequently, a self-checking processor whose data path is encoded entirely in a Berger code can be achieved. An efficient self-checking processor can then be designed. >
Imaging of structural changes in endothelial cells and thrombus formation at the site of FeCl(3)-induced injuries in mice cremasteric arteries.

AIM We investigated thrombus formation at the site of functional injury to endothelial cells by FeCl(3). METHODS After preparation of cremasteric arteries of mice, controlled endothelial injury was induced by application of FeCl(3). Endothelial cells were rendered fluorescent by addition of FITC (fluorescein isothiocyanate)-labeled isolectin B4. Circulating platelets and leukocytes were made fluorescent by rhodamine 6G. Three-dimensional (3D) growth of thrombi was visualized in real time. Effects of aspirin and clopidogrel pre-treatments on the growth of thrombi were investigated in vivo as well as in an ex vivo flow chamber system. RESULTS Endothelial cells were tightly bound to each other to protect local thrombus formation. Platelets started to adhere to endothelial cells when FeCl(3) was applied. Three-dimensional growth of thrombi, which takes 10.6+/-7.5 minutes for complete occlusion in control, can be visualized with our imaging system. Aspirin pre-treatment at the dose tested did not influence either endothelial injury or platelet thrombus growth, while clopidogrel pretreatment significantly inhibited 3D growth and prolonged occlusion time up to 64.6+/-25.3 minutes (100 mg/kg). A similar inhibiting effect of clopidogrel was reproduced in ex vivo flow chamber experiments. CONCLUSIONS We have developed an in vivo system to detect thrombus formation after functional damage to the endothelium.
Location Privacy Protection Method based on Variable-Order Markov Prediction Model

∗ Abstract: Recently, the usage scenarios of location-based services are becoming increasingly complex. Attackers can reconstruct a user’s trajectory by collecting continuous query information issued during the user’s movement. However, existing location privacy protection studies usually focus on protecting the user’s current location and ignore the problem that the Spatio-temporal correlation contained in the user’s movement trajectory can lead to the disclosure of the user’s trajectory. To address this problem, we propose a continuous query privacy-preserving method based on location prediction. It constructs a user trajectory spanning tree and uses a variable-order Markov model to predict the user’s movement trend where the order of the Markov model dynamically depends on the length of the current user trajectory segment. It also selects and sends multiple dummy location queries with timestamps according to the probabilities of predicted locations through the k-anonymity technique, which not only ensures that the virtual location set can effectively anonymize the user’s next location but also further disrupts the temporal order of the user’s query trajectory, thereby enhancing privacy protection for the user. Our experiments on a benchmark dataset and a newly-created synthetic dataset show that our method significantly outperforms several existing methods in terms of confusion degree and average query processing time.
Synthesis and Antidiabetic Activity of 3,6,7‐Trisubstituted‐2‐(1H‐imidazol‐2‐ylsulfanyl)quinoxalines and Quinoxalin‐2‐yl isothioureas

Two series of 3,6,7‐trisubstituted‐2‐(1H‐imidazol‐2‐ylsulfanyl)‐quinoxalines 2a‐l and 2‐(quinoxalin‐2‐yl)‐isothioureas 3a‐l were prepared. All the test compounds 2a‐l and 3a‐l were screened in vitro, in a RIN5F cell‐based assay for glucose‐dependent insulinotropic activity. A significant concentration and glucose‐dependent insulin secretion effect was seen with compounds 2a‐l and the insulinotropic activity of compound 2l was found to be identical to that of the standard compound (6,7‐dichloro‐2‐trifluromethyl‐3‐(5‐methyl‐1,3,4‐thiadiazo‐2‐ylsulfanyl)‐quinoxaline (1)).
Synthesis of purine nucleosides using iodine as catalyst.

Iodine has been found to be an excellent catalyst for the synthesis of nucleosides, i.e., the reaction of 1-O-acetyl-2, 3, 5-tri-O-benzoyl-β-D-ribofuranose with various purines in the presence of iodine resulted in the formation of corresponding 9-β-D-ribonucleosides, and/or their isomers in good yields.
A Classification of Belarusian Regions upon Economic Development Using Cluster Analysis

One of the main goals of this paper work is to classify regions of Belarus based on six variables indicating economic development of these regions taken for a period of five years from 2000 to 2004. The research covers 71 regions including 64 administration districts and 7 largest towns located within their borders. The aim of this work is not to classify regions for every of these years in particular but to make a data pool for all five years of observation in order to get a proper understanding of processes and tendencies taking place in these regions due to changes in their economic activities. As nowadays there exist many methods and measures available for conducting a cluster analysis a special procedure is proposed to define a best classification for the given partitions for different methods and metrics. As a result, in the research a new approach is suggested to determine the quality of different classifications. It was also uncovered that a choice of software may cause different classification results and particularly the dissimilarity between R and SPSS is discussed concerning their clusterization features.
Supervised Models C 1 . 2 Multilayer perceptrons

This section introduces multilayer perceptrons, which are the most commonly used type of neural network. The popular backpropagation training algorithm is studied in detail. The momentum and adaptive step size techniques, which are used for accelerated training, are discussed. Other acceleration techniques are briefly referenced. Several implementation issues are then examined. The issue of generalization is studied next. Several measures to improve network generalization are discussed, including cross validation, choice of network size, network pruning, constructive algorithms and regularization. Recurrent networks are then studied, both in the fixed point mode, with the recurrent backpropagation algorithm, and in the sequential mode, with the unfolding in time algorithm. A reference is also made to time-delay neural networks. The section also includes brief mention of a large number of applications of multilayer perceptrons, with pointers to the bibliography.