Miracle-dz/UniFAR-FTUs huggingface dataset:
Combining select neuropsychological assessment with blood-based biomarkers to detect mild Alzheimer's disease: a molecular neuropsychology approach.

BACKGROUND Current work has sought to establish a rapid and cost effective means of screening for Alzheimer's disease (AD) with the most recent findings showing utility of integrating blood-based biomarkers with cognitive measures. OBJECTIVE The current project sought to create a combined biomarker-cognitive profile to detect mild AD. METHODS Data was analyzed from 266 participants (129 AD cases [Early AD n = 93; Very Early AD n = 36]; 137 controls) enrolled in the Texas Alzheimer's Research and Care Consortium (TARCC). Non-fasting serum samples were collected from each participant and assayed via a multi-plex biomarker assay platform using electrochemiluminescence. Logistic Regression was utilized to detect early AD using two serum biomarkers (TNFα and IL7), demographic information (age), and one neuropsychological measure (Clock 4-point) as predictor variable. Disease severity was determined via Clinical Dementia Rating (CDR) scale global scores. RESULTS In the total sample (all levels of CDR scores), the combination of biomarkers, cognitive test score, and demographics yielded the obtained sensitivity (SN) of 0.94, specificity (SP) of 0.90, and an overall accuracy of 0.92. When examining early AD cases (i.e.m CDR = 0.5-1), the biomarker-cognitive profile yielded SN of 0.94, SP of 0.85, and an overall accuracy of 0.91. When restricted to very early AD cases (i.e., CDR = 0.5), the biomarker-cognitive profile yielded SN of 0.97 and SP of 0.72, with an overall accuracy of 0.91. CONCLUSIONS The combination of demographics, two biomarkers, and one cognitive test created a biomarker-cognitive profile that was highly accurate in detecting the presence of AD, even in the very early stages.
A limit theorem for "Quicksort"

Soit X n le nombre de comparaisons utilisees par la procedure Quicksort pour trier une liste de nombres distincts. Nous demontrons que (X n −E(X n ))/n converge faiblement vers une certaine variable aleatoire Y. La distribution de Y est le point fixe d'une contraction et peut etre calculee numeriquement part iteration
A modified design of PID controller for DC motor drives using Particle Swarm Optimization PSO

This paper presents the application of a new Particle swarm optimization technique for adjusting the gains of a PID speed controller adaptively to give the minimum integral absolute error between the speed demand and the output response, minimum settling time, and minimum overshoot for a separately excited dc drive. The new technique converts all objective functions to a single objective function by deriving a single aggregate objective function using specified or selected weighting factors. Since the optimal PID controller parameters are dependent on the selected weighting factors, the weighting factors was also treated as dynamic optimizing parameters within the Particle Swarm Optimization as a dual optimization and global selection of PID controller optimal parameters as well as best set of weighting factors. Computer simulations and experimental results show that the performance of the optimal PID controller is better than that of the traditional PID controller.
A lower bound on the mean-square error in random parameter estimation

A new lower bound on mean-square error in parameter estimation is presented. The bound is tighter than the Cramer-Rao and Bobrovsky-Zakai lower bounds. It requires no bias or regularity assumptions, it is computationally simple, and it can be applied to estimates of vector parameters or functions of the parameters.
Variable Mesh Adaptive Direct Search Algorithm Applied for Optimal Design of Electric Machines Based on FEA

Optimal design of electric machine based on finite element analysis (FEA) is characterized with the nonlinear magnetic saturation, which causes the much longer computation time for maintaining the high accuracy. In order to compensate the excessive computation time due to FEA and guarantee the reliable convergence to global optimum, variable mesh adaptive direct search (VMADS) is newly implemented with multi-start in this paper. Effectiveness of VMADS has been verified through a benchmark function. In particular, the proposed algorithm has been employed to optimal design of interior permanent magnet synchronous machine (IPMSM) for maximum torque per ampere (MTPA), of which design objective should be evaluated by FEA for better accuracy.
Different effects of physical exercise on cold pain sensitivity in fighter pilots with and without the history of acute in-flight neck pain attacks.

PURPOSE The cold pain sensitivity in fighter pilots was studied by using a cold pressor test. METHODS The pilots were divided into two groups: one group consisting of eight pilots (N = 8) who had experienced several acute in-flight neck pain attacks, and the control group (N = 8) who had not experienced these pain conditions under similar work and environment conditions. In each pilot cold pain thresholds and pain and unpleasantness responses to suprathreshold cold stimulations were recorded during repeated tests. The ratings of pain and unpleasantness responses to cold stimulations were evaluated by visual analog scales (VAS). The effect of exercise on cold pain sensitivity was tested in a separate experiment. Exercise was performed on a cycle ergometer at different workload levels (50-200 W). RESULTS In the control conditions (resting measures) of this study during repeated cold pressor tests, the average pain thresholds and pain or unpleasantness responses to suprathreshold cold stimulation were not different between groups. Physical exercise increased pain thresholds (P < 0.001) in pilots with a history of neck pain attacks but not in control group. Exercise induced a significant decrease in pain responses and unpleasantness responses to suprathreshold stimulation in both groups. This exercise effect was more marked both in pain intensity (P < 0.05) and unpleasantness responses (P < 0.01) in pilots with a history of neck pain attacks. Moreover, exercise more markedly (P < 0.05) decreased unpleasantness than pain intensity responses in both groups of pilots. CONCLUSIONS The results suggest that exercise stress-related analgesia mechanisms may be enhanced in pilots with a history of acute in-flight neck pain attacks. Moreover, sensory and nonsensory aspects of pain experience may be differentially influenced by exercise stress.
Visualization of neurogenesis in the central nervous system using nestin promoter‐GFP transgenic mice

Neurons are generated from neural progenitor cells not only during development but also in the mature brain. To develop an in vivo system for analyzing neurogenesis, we generated transgenic mice expressing green fluorescent protein (GFP) under the control of regulatory regions of the nestin gene. GFP fluorescence was observed in areas and during periods connected with neurogenesis, including embryonic neuroepithelium, neonatal cerebellum, and hippocampal dentate gyrus and rostral migratory pathway from the subventricular zone to the olfactory bulb in the adult. GFP-positive cells in the adult brain included immature neuronal cells expressing polysialylated NCAM. BrdU labeling experiments revealed that newly generated interneurons which migrated rostrally from the subventricular zone expressed GFP until they reached the olfactory bulb. These results indicate that nestin promoter-GFP transgenic mice can be utilized to visualize the regions of neurogenesis throughout the life of the animals and to follow the migration and differentiation of newly generated neurons.
Did you know? Modelling vision: computational science for understanding human visual perception

Human visual perception system is complex and involves a considerable portion of the brain's cortex. Hence, the wish to understand complex neuronal function is obvious, and the idea to model this by means of artificial neuronal networks might have been born at the time when first computational machines were constructed (Alan Turing, Intelligent machinery, 1948, h t t p: //www.npl.co.uk/about/history/notable-individuals/turing/intelligent-machinery) This article is protected by copyright. All rights reserved.
DAYLIGHT AND URBAN MORPHOLOGY : A MODEL FOR ANALYSING THE AVERAGE ANNUAL ILLUMINATION OF RESIDENTIAL HOUSING

Original scientific paper The model proposed in this paper is based on a multi-criteria analysis of annual daylight illumination relying on the interoperability of commercially available software tools. The daylight performance of different urban morphologies is investigated by simulating and measuring real weather conditions for a specified location on two types of 3D models. The first analysis is conducted on optimized 3D models of typical urban block morphology and the second analysis is conducted on a 3D model of an existing block extracted from the corpus of the city of Novi Sad. The results are processed according to the criteria of health factors such as the minimum daylight exposure value of 190 lx. The comparative analysis of the results showed that there is a difference between the different types of block morphologies regarding the illumination intensity for the interior spaces. The obtained values are presented in tabular form, graphic and 3D view.
Implementation of protocolized tight control and biological dose optimization in daily clinical practice: results of a pilot study

Objectives: To assess the effects of education, guideline development, and individualized treatment advice on rheumatologist adherence to tight control-based treatment and biological dose optimization in rheumatoid arthritis (RA), psoriatic arthritis (PsA), and spondyloarthropathy (SpA) patients. Method: This pilot study, among two rheumatologists and two specialized nurses in a general hospital, combined education, feedback, local guideline development, and individualized treatment advice. Outcomes (baseline and 1 year post-intervention) were the percentage of patients with a Disease Activity Score in 28 joints (DAS28) or Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) measured during the visit, mean DAS28/BASDAI, and the percentage of patients using a reduced biological dose. DAS28 outcomes only applied to RA and PsA patients, BASDAI outcomes only applied to SpA patients whereas outcomes on biological dose applied to all patients. Results: A total of 232 patients (67% RA, 15% PsA, 18% SpA; 58% female, mean age 56 ± 15 years) were included in the study. The percentage of DAS28 and BASDAI measurements performed increased after the intervention [DAS28 15–51%, odds ratio (OR) 3.3, 95% confidence interval (CI) 2.1–5.5; BASDAI 23–50%, OR 2.2, 95% CI 1.0–5.5], with mean DAS28 and BASDAI scores remaining similar (DAS28: mean difference 0.1, 95% CI −0.3 to 0.5; BASDAI: mean difference 0.03, 95% CI −1.8 to 1.9). Use of a reduced biological dose increased from 10% to 61% (OR 3.9, 95% CI 2.4–6.5). Conclusions: A multicomponent intervention strategy aimed at rheumatologists can lead to improved adherence to tight control-based treatment and a reduction in the use of biologicals in RA, SpA, and PsA patients.
Evidence of hemoglobin dissociation

Bovine carbonmonoxy hemoglobin investigated with light scattering studies is found to dissociate from its native tetramer structure into dimers and monomers. The values of the hydrated tetramer radius, RT = 32.1 Å, and the fractional dissociation vs pH, have been obtained at different ionic strengths from the autocorrelation function of the scattered light.
Incoherent Ray Tracing without Acceleration Structures

Recently, a new family of dynamic ray tracing algorithms, called divide-and-conquer ray tracing, has been introduced. This approach partitions the primitives on-the-ﬂy during ray traversal, which eliminates the need for an acceleration structure. We present a new ray traversal method based on this principle, which efﬁciently handles incoherent rays, and takes advantage of the SSE and AVX instruction sets of the CPU. Our algorithm offers notable performance improvements over similar existing solutions, and it is competitive with powerful static ray tracers. Categories and Subject Descriptors (according to ACM CCS) : I.3. 7 [Computer Graphics]: Three-Dimensional Graphics and Realism—Raytracing
A novel piezoelectric ZnO nanogenerator on flexible metal alloy substrate

In this paper, we report a novel piezoelectric ZnO nanogenerator on flexible metal alloy substrate (Phynox alloy) for energy harvesting and sensing applications. The vertically aligned ZnO nanowires are sandwiched between Au electrodes. The aligned growth of ZnO nanowires have been successfully synthesized on Au coated metal alloy substrate by hydrothermal method at low temperature (95±1 °C). The as-synthesized vertically aligned ZnO nanowires were characterized using FE-SEM. Further, PMMA is spin coated over the aligned ZnO nanowires for the purpose of their long term stability. The fabricated nanogenerator is of size 30mm × 6mm. From energy harvesting point of view, the response of the nanogenerator due to finger tip impacts ranges from 0.9 V to 1.4V. Also for sensing application, the maximum output voltage response of the nanogenerator is found to be 2.86V due to stainless steel (SS) ball impact and 0.92 V due to plastic ball impact.
Simplified Rat Lung Transplantation by Using a Modified Cuff Technique

Mizuta's cuff technique in rat lung transplantation (LT) model has some disadvantages, such as twisting of blood vessels or bronchus and being time-consuming, which complicate procedures for anastomosis. This study was performed to investigate the advantage of using a simplified cuff technique in LT. The anastomosis time was compared in two groups. In group I, Mizuta'scuff technique was performed in 50 rat orthotopic left lung transplants. In group II, a simple modified cuff technique was performed in 48 rat orthotopic left lung transplants. The successful rate of the new technique for anastomosis was 100%. No twist of vessels or bronchus and no bleeding or air leakage were observed in group II. The anastomosis time of group II was significantly less than for group I (11.2 ± 2.1 min vs. 18.1 ± 3.6 min, mean ± SD, p <. 01). This simple modified cuff technique led to less anastomosis time and avoided potential complications induced by the cuff-tail technique. It has been verified to be a safe, simple, and reproducible technique that can provide us with a more precise assessment in the rat LT model.
IIHS head restraint ratings and insurance injury claim rates

ABSTRACT Objectives: The Insurance Institute for Highway Safety (IIHS) rates front seat/head restraint designs using a combination of static and dynamic measurements following RCAR-IIWPG procedures. The purpose of this study was to determine whether vehicles with better IIHS-rated seats/head restraints had lower injury risk in rear-end collisions and how the effect of better rated seats interacted with driver gender and age. Methods: The presence of an associated insurance injury claim was determined for rear-impact crashes using 2001–2014 model year cars and SUVs. Logistic regression was used to compare injury risk for vehicles with good, acceptable, and marginal IIHS-rated seats/head restraints with poor-rated seats/head restraints. Analyses were run by gender and driver age and also by the rate of more severe injury claims. Results: Injury rates were 11.2% lower for vehicles with seats/head restraints rated good compared to vehicles with seats/head restraints rated poor. The percentage reduction for good- versus poor-rated seats was greater for females (12.7%) than males (8.9%). Comparing good- with poor-rated seats, driver ages 15–24 had the largest reduction at 19.8%, followed by 10.7% for driver ages 45–64 and 10.4% for driver ages 25–44. Conclusions: Seats/head restraints with better IIHS ratings are associated with lower injury rates in rear-impact collisions than seats rated poor. The reductions in injury rates were strongest for females and for young-to–middle-age drivers. The strong reductions in injury rates for these groups are encouraging given their high initial injury rates.
DTC-SVM control strategy for induction machine based on indirect matrix converter in flywheel energy storage system

Flywheel energy storage system (FESS) improves the quality of the power transmitted to the grid by wind generators. Presently, FESSs, containing back to back converter and a direct torque control (DTC) that controlled induction machine (IM), are mainly considered for this kind of application. This paper investigates a low-speed FESS with DTC_SVM control strategy for an IM based on indirect matrix converter (IMC). In this system, DTC-SVM increase efficiency of the energy storage system and facilitate the active power output of the wind farm by providing situation to shift quickly and repeatedly between motoring and generating operation modes in induction machine. The space vector modulation (SVM) strategy in indirect matrix converter provides full control of both the output voltage vector and the instantaneous input current displacement angle. The reference power of the FESS that used as the input of the system can be obtained by calculating the active power of wind farm and the target power. The model of the system is simulated in SIMULINK/MATLAB software for different FESS operations such as: charge, discharge and standby modes. The results of simulation show effectiveness of the proposed strategy.
Exploration of 3D Activity Cliffs on the Basis of Compound Binding Modes and Comparison of 2D and 3D Cliffs

Activity cliffs are formed by pairs or groups of structurally similar compounds having large differences in potency and are focal points of structure-activity relationship (SAR) analysis. The choice of molecular representations is a critically important aspect of activity cliffs analysis. Thus far, activity cliffs have predominantly been defined on the basis of molecular graph or fingerprint representations. Herein we introduce 3D activity cliffs derived from comparisons of experimentally determined compound binding modes. The analysis of 3D activity cliffs is generally applicable to target proteins for which structures of multiple ligand complexes are available. For two popular targets, β-secretase 1 (BACE1) and factor Xa (FXa), public domain X-ray structures with bound inhibitors were collected. Crystallographic binding modes of inhibitors were systematically compared using a 3D similarity method taking conformational, positional, and atomic property differences into account. In addition, standard 2D similarity relationships were also determined. SAR information associated with individual compounds substantially changed when either bioactive conformations or 2D molecular graphs were used for similarity evaluation. 3D activity cliffs were identified for BACE1 and FXa inhibitor sets and systematically compared to 2D cliffs. It was found that less than 40% of 3D activity cliffs were conserved when 2D similarity was applied. The limited conservation of 3D and 2D cliffs provides further evidence for the strong molecule representation dependence of activity cliffs. Moreover, 3D cliffs represent a new class of activity cliffs that convey SAR information in ways that differ from graph-based similarity measures. In cases where sufficient structural information is available, the comparison of 3D and 2D cliffs is expected to aid in SAR analysis and mapping of critical binding determinants.
Geographic Diffusion of Information and Stock Returns

This study outlines a new disclosure-based approach for predicting a firm’s future earnings using information that is geographically distributed within the United States. Using this approach, we show that firm earnings can be predicted using the past earnings of firms in a given firm’s economically-connected states. However, we find that equity analysts and institutional investors do not fully incorporate this value-relevant information into their earnings forecasts and trades, respectively. A Long−Short trading strategy that exploits the slow diffusion of geographic information earns an annual, abnormal risk-adjusted return of about 9%.
Characteristics Description of Potential User Segments on the E-Commerce Website oriented to Precision Marketing

In the increasingly competitive environment between e-commerce companies, for more accurate implementation of marketing strategies, e-commerce websites often choose to subdivide the consumer market of the enterprise to identify site users’ characteristics to find their needs. In this paper, we subdivide consumer market from the four dimensions of behavior, geography, demography and psychology and propose a model to describe the characteristics of potential user market segments. Based on the web log data and user transaction data, a classification algorithm is used to analyze user behavior data in Web log to find the potential user segments and the user's descriptive characteristics in user transaction data are clustered to obtain the distribution of consumer characteristics under various product categories, then we use the product categories in e-commerce website as an intermediary to give every single potential user in potential user market segments the descriptive characteristics, which can provide data support for the realization of precision marketing. The proposed model is applied to the actual data of a certain insurance e-commerce platform, and based on the results, we gain some implications for marketing of the e-commerce website.
Using Process Mining to Measure the Expected Costs of Business Processes

Process mining is a means to extract hidden information from the event logs accumulated by the information systems that drive increasingly complex business processes, potentially improving their manageability. Traditional process mining is used mainly to extract a useful description of how an enterprise’s processes actually work (as versus how they are documented to work), usually presented in the form of a flowchart. To the best of our best knowledge, previous process mining techniques have not used available information on duration and frequency of portions of a business process. We propose a method that combines process mining with Bayes’ Theorem to augment a mined model with probabilities information. This additional information increases the value of the mined model and can be used not only in making predictions, but also in making decisions. Together with activity-based costing that assigns some cost to each activity in a process, our process mining technique can measure the expected costs of different stages in the process to support improvement of the underlying processes. We apply our approach to a chip probing process of a semiconductor firm in Taiwan. Our results confirm that the proposed approach could improve company decisions regarding their internal supply chain management.
Immune Response to Cryptococcus neoformans Soluble Polysaccharide

Chromium chloride was used as a coupling agent for the conjugation of purified cryptococcal polysaccharide to sheep erythrocytes. Sensitized erythrocytes were used in a passive hemagglutination (PHA) assay for antibody to cryptococcal polysaccharide and a passive hemagglutination inhibition (PHI) assay for antigen. The PHA assay was more sensitive than complement fixation, agglutination, or precipitation tests for antibody. The PHI assay could detect submicrogram quantities of soluble polysaccharide. Antigen or antibody could be detected in serum or spinal fluid from seven of eight patients with cryptococcosis. Tests for antigen or antibody