Miracle-dz/UniFAR-FTUs huggingface dataset:
In silico approaches to evaluate the molecular properties of organophosphate compounds to inhibit acetylcholinesterase activity in housefly

Organophosphate compounds (OPC) have become the primary choice as insecticides and are widely used across the world. Additionally, OPCs were also commonly used as a chemical warfare agent that triggers a great challenge to public safety. Exposure of OPCs to human causes immediate excitation of cholinergic neurotransmission through transient elevation of synaptic acetylcholine (ACh) levels and accumulations. Likewise, prolonged exposure of OPCs can affect the processes in immune response, carbohydrate metabolism, cardiovascular toxicity, and several others. Studies revealed that the toxicity of OPCs was provoked by inhibition of acetylcholinesterase (AChE). Therefore, combined in silico approaches – pharmacophore-based 3D-QSAR model; docking and Molecular Dynamics (MD) – were used to assess the precise and comprehensive effects of series of known OP-derived compounds together with its −log LD50 values. The selected five-featured pharmacophore model – AAHHR.61 – displayed the highest correlation (R2 = .9166), cross-validated coefficient (Q2 = .8221), F = 63.2, Pearson-R = . 9615 with low RMSE = . 2621 values obtained using five component PLS factors. Subsequently, the well-validated model was then used as a 3D query to search novel OPCs using a high-throughput virtual screening technique. Simultaneously, the docking studies predicted the binding pose of the most active OPC in the MdAChE binding pocket. Additionally, the stability of docking was verified using MD simulation. The results revealed that OP22 and predicted lead compounds bound tightly to S315 of MdAChE through potential hydrogen bond interaction over time. Overall, this study might provide valuable insight into binding mode of OPCs and hit compounds to inhibit AChE in housefly.
Throughput-save ratio optimization in wireless powered communication systems

This paper deals with the idea of wireless energy harvesting and energy transfer used to establish communication between devices in a wireless network. Wireless energy harvesting and transfer has proved to be very advantageous in areas like WSN in which this technique not only improve the nodes lifetime but also makes the communication eco-friendly. A protocol namely save-then-transmit is used to accomplish the communication between the nodes in which some part of the time slot is devoted for energy harvesting and transfer with remaining part used for data transfer. Two models TCM-EH-ET and TRCM-EH-ET have been considered in which the nodes have no source of energy and they only get energy by natural means i.e. they harvest energy for recharging their batteries from the environment. An energy co-operation scheme is given, parameters involved in energy harvesting and transfer, i.e. energy transfer rate and save-ratio are optimized to maximize the overall throughput of the communication network. The proposed scheme is simulated on MATLAB R2013a, simulation results shows that the throughput of system with given energy cooperation scheme are better than the scheme without energy transfer and energy transfer with half save-ratio.
Social Discrimination and Health Care: A Multidimensional Framework of Experiences among a Low-Income Multiethnic Sample

ABSTRACT The study aims to describe the perceived discriminatory health care treatment experiences and its impact on care among minority urban-dwelling adults. Semistructured qualitative interviews (N = 51) were conducted with patients from community-based health care settings, and systematic, grounded theory approach was used. Three distinct themes emerged: (a) the sources of discriminatory experiences, (b) its impact on health care, and (c) the provider/organization recommendations to address discriminatory practices. The study highlights the relevance of perceived discrimination in avoidance of health care services, nonadherence to treatment, and adverse health-related sequelae by low-income urban-dwelling adults with little access to health care.
Cytogenetic localization of cancer-related genes in the rat and comparative mapping studies in human and mouse

The rat is an important model organism in biomedical research, and several well-characterized rat cancer model systems exist. To facilitate detailed analysis of these models, it is useful to know the regional location of known cancer-related genes. In this report, 14 cancer-related genes have been sublocalized by fluorescence in situ hybridization. The mapped genes include three oncogenes (Fyn, Mas1, and Vav1), a tyrosine kinase gene (Syk), a tumor-associated antigen gene (Cd24), a growth factor receptor gene (Igf2r), the gene for an activator of c-fos/c-jun transcription factors (Apex), a transcription factor gene (Egr3), and several genes involved in steroid hormone metabolism and signaling (Esr2, Pgr, Cbg, Cyp17, and Cyp19). The remaining gene (Map1a) is involved in microtubule assembly.
A Case for Conservative Management: Characterizing the Natural History of Radiographically Diagnosed Rathke Cleft Cysts.

CONTEXT Rathke cleft cysts (RCCs) are benign embryonic remnants of the Rathke's pouch found in 13% to 33% of the general population. When symptomatic, they manifest themselves by compressing adjacent structures, causing pressure effects such as headache, visual disturbance, or pituitary hormone deficits. Most RCCs are asymptomatic, and their management remains controversial. Surgical resection has generally been indicated to treat symptomatic RCCs but carries the risk of complications. OBJECTIVE Our objective was to better characterize the outcomes for patients with presumed RCCs undergoing conservative management. DESIGN This was a retrospective cohort study. SETTING The setting was a pituitary program at a university medical center. PARTICIPANTS The participants were 75 patients with radiographically diagnosed RCCs. METHODS All brain magnetic resonance imaging (MRI) scans performed at the University of Virginia from 2006 through 2013 were searched for the words "Rathke cleft cyst," and pituitary clinic notes from 2007 to 2012 were reviewed for patients identified as probably having an RCC. Images for all patients were reviewed by the interpreting neuroradiologist, and those patients with at least 2 MRI scans were included. The dimensions of each cyst were assessed by the same neuroradiologist, and the volume of each cyst was analyzed as a function of the time from the first image obtained. RESULTS A total of 75 patients (4-76 years old) met our inclusion criteria. The length of follow-up was 1 to 126 months (median 24 months). In 43 patients (57%) no detectable change in the size of their cysts was seen, in 21 patients (28%) cysts increased in size, and in 11 patients (15%) cysts decreased in size. The predicted mean cyst growth rate was not significantly different from 0. CONCLUSION The increasingly prevalent use of brain imaging modalities such as MRI has resulted in an increase in the incidental discovery of pituitary lesions. Our study demonstrates that the majority of radiologically diagnosed RCCs remain unchanged or decrease in size over time. These results suggest that, in the absence of pressure symptoms, it is reasonable to manage patients with RCCs conservatively.
Calprotectin as a marker of inflammation in patients with early rheumatoid arthritis

Objectives Calprotectin is an inflammatory marker of interest in rheumatoid arthritis (RA). We evaluated whether the level of calprotectin was associated with disease activity, and if it was predictive of treatment response and radiographic progression in patients with early RA. Methods Plasma from disease-modifying antirheumatic drug (DMARD)-naïve patients with RA fulfilling 2010 American College of Rheumatology/European League Against Rheumatism classification criteria with symptom duration <2 years was analysed for calprotectin at baseline, and after 1, 3 and 12 months. All patients received treat-to-target therapy, as part of a randomised controlled strategy trial (ARCTIC). The association between calprotectin, erythrocyte sedimentation rate (ESR) and C reactive protein (CRP) and measures of disease activity were assessed by correlations. We used likelihood ratios and logistic regression models to assess the predictive value of the baseline inflammatory markers for treatment response and radiographic damage. Results 215 patients were included: 61% female, 82% anti-citrullinated peptide antibody positive, mean (SD) age 50.9 (13.7) years and median (25, 75 percentile) symptom duration 5.8 (2.8, 10.5) months. Calprotectin was significantly correlated with Clinical Disease Activity Index (r=0.32), ESR (r=0.50) and ultrasonography power Doppler (r=0.42) before treatment onset. After 12 months of treatment, calprotectin, but not ESR and CRP, was significantly correlated with power Doppler (r=0.27). Baseline levels of calprotectin, ESR and CRP were not predictive of treatment response, but high levels of calprotectin were associated with radiographic progression in multivariate models. Conclusions Calprotectin was correlated with inflammation assessed by ultrasound before and during DMARD treatment, and was also associated with radiographic progression. The data support that calprotectin may be of interest as an inflammatory marker when assessing disease activity in different stages of RA. Trial registration number NCT01205854; Post-results.
A FKSVM Model Based on Fisher Criterion for Text Classification

Text classification is the process of automatically assigning a given document to its previous category. It is widely used in artificial intelligence and natural language processing. In this paper, we propose a new classification model named FKSVM in order to improve the accuracy of text classification. According to the model, firstly, we use the TF-IDF algorithm to calculate the weight of features, and then the feature vectors are sorted according to the value of T calculated by Anova and T-test. Secondly, the number of features that can produce the optimal classification performance is selected according to the Fisher criterion function. Finally, the KSVM classifier is used to classify which is the combination of SVM and KNN. The algorithm calculates the distance between the sample and the optimal hyperplane of SVM. If the distance is larger than the pre given threshold, the sample will be classified by SVM. Otherwise, the KNN classifier will be used. The experiment results indicate that the average accuracy of FKSVM model is up to 88.83%, while that of KNN is 83.20%, SVM is 84.73% and KSVM is 85.56%.
Assessment of Nonmotor Fluctuations Using a Diary in Advanced Parkinson's disease.

BACKGROUND Since previous studies aimed to study nonmotor symptom (NMS) fluctuations in direct conjunction with motor oscillations, there are no data available on the temporal context of NMS fluctuations and motor oscillations in advanced Parkinson's disease (PD). OBJECTIVE To evaluate circadian patterns and temporal connections of NMS and motor fluctuations in PD. METHODS 15 controls, 17 non-fluctuating and 15 fluctuating PD patients completed two diaries by rating 4 key psychiatric (anxiety, depressive mood, inner restlessness, concentration/attention deficits), fatigue and 4 autonomic NMS (excessive sweating, sialorrhea, bladder urgency, dizziness) absent or present and motor function (Off, On with/without dyskinesia, and asleep) for every hour for 5 consecutive days. RESULTS NMS Off state hours (hours with NMS rated as present) were less frequent compared to motor Off state hours and NMS On-Off-switches were less prevalent compared to those of the motor state. Off time and number of On-Off-switches of psychiatric NMS were moderately correlated with motor Off time and number of motor On-Off switches on the individual patient level. Changes in NMS state occurred largely independent of changes in motor states with concordance rates of only 26-43% of all NMS changes for psychiatric and 7-17% for autonomic NMS. In controls and non-fluctuating PD patients, there were no NMS state switches in concordance to motor state switches. CONCLUSION We provide first data on the temporal context of NMS fluctuations showing similar frequencies of psychiatric NMS Off, fatigue Off and motor Off times as well as their On-Off-fluctuations, but low concordance rates of NMS with motor On-Off-state switches. We found no evidence for NMS fluctuations in non-fluctuating PD patients. Our data implicate similar fluctuation patterns of mood NMS and motor function without close timing and/or different kinetics.
A proposed framework for biometrie electronic voting system

In this modern age of digitization, Bangladesh Election Commission (EC) still uses manual system during election for vote casting. Recently, it is considering to introduce Electronic Voting Machine (EVM) in parliamentary elections though EVM is not entirely automated and has many limitations. In this work, we have designed an automated biometric voting system with a convenient user interface and integrated database system containing all voters' information. Casted votes will be counted automatically at the end of the voting process and result will be generated centrally with less time. Therefore, the proposed system will improve the voting management of Bangladesh by ceasing fraudulent activities, corruptions, ensuring security, transparency, fairness, accuracy and keeping backup trails of voting process.
Redox Sensing by Fe2+ in Bacterial Fur Family Metalloregulators.

SIGNIFICANCE Iron is required for growth and is often redox active under cytosolic conditions. As a result of its facile redox chemistry, iron homeostasis is intricately involved with oxidative stress. Bacterial adaptation to iron limitation and oxidative stress often involves ferric uptake regulator (Fur) proteins: a diverse set of divalent cation-dependent, DNA-binding proteins that vary widely in both metal selectivity and sensitivity to metal-catalyzed oxidation. Recent Advances: Bacteria contain two Fur family metalloregulators that use ferrous iron (Fe2+) as their cofactor, Fur and PerR. Fur functions to regulate iron homeostasis in response to changes in intracellular levels of Fe2+. PerR also binds Fe2+, which enables metal-catalyzed protein oxidation as a mechanism for sensing hydrogen peroxide (H2O2). CRITICAL ISSUES To effectively regulate iron homeostasis, Fur has an Fe2+ affinity tuned to monitor the labile iron pool of the cell and may be under selective pressure to minimize iron oxidation, which would otherwise lead to an inappropriate increase in iron uptake under oxidative stress conditions. Conversely, Fe2+ is bound more tightly to PerR but exhibits high H2O2 reactivity, which enables a rapid induction of peroxide stress genes. FUTURE DIRECTIONS The features that determine the disparate reactivity of these proteins with oxidants are still poorly understood. A controlled, comparative analysis of the affinities of Fur/PerR proteins for their metal cofactors and their rate of reactivity with H2O2, combined with structure/function analyses, will be needed to define the molecular mechanisms that have facilitated this divergence of function between these two paralogous regulators.
The complete mitochondrial genome sequence of Hemibagrus sp. (Siluriformes: Bagridae)

Abstract At present, the phylogenetic and taxonomic positions of Bagridae and Siluriformes have long been unclear. In this paper, we sequenced and annotated the complete mitogenome of Hemibagrus sp. The total length was 16,529 bp, and was typically consist of 37 genes, including 13 protein-coding genes, 2 rRNAs, 22 tRNA, a light-strand replication origin (OL) and a single large control region (CR). Except for eight tRNA and ND6 genes, all other mitochondrial genes were encoded on the heavy strand (H-strand). The gene content, organization and arrangement were identical to that of a typical bony fish. The overall base composition was 26.5%, 26.8%, 31.7% and 15.0% for T, C, A and G, respectively, with a slight bias on AT content (58.2%). This information could not only contribute to provide useful molecular data for the species identification, but also to further taxonomic and phylogenetic studies of Hemibagrus and Bagridae.
Analytical Methods to Distinguish the Positive and Negative Spectra of Mineral and Environmental Elements Using Deep Ablation Laser-Induced Breakdown Spectroscopy (LIBS)

Environments affect mineral surfaces, and the surface contamination or alteration can provide potential information to understanding their regional environments. However, when investigating mineral surfaces, mineral and environmental elements appear mixed in data. This makes it difficult to determine their atomic compositions independently. In this research, we developed four analytical methods to distinguish mineral and environmental elements into positive and negative spectra based on depth profiling data using laser-induced breakdown spectroscopy (LIBS). The principle of the methods is to utilize how intensity varied with depth for creating a new spectrum. The methods were applied to five mineral samples exposed to four environmental conditions including seawater, crude oil, sulfuric acid, and air as control. The proposed methods are then validated by applying the resultant spectra to principal component analysis and data were classified by the environmental conditions and atomic compositions of mineral. By applying the methods, the atomic information of minerals and environmental conditions were successfully inferred in the resultant spectrum.
Nonrandomized Comparison of Open Flank versus Laparoscopic Nephrectomy in 249 Patients with Benign Renal Disease

Objectives: We report the results from a nonrandomized comparison of open flank versus laparoscopic nephrectomy in patients with benign renal disease. Methods: From January 1993 to December 1997, 249 nephrectomies for benign renal disease were performed at our institution. There were 118 patients in the open flank nephrectomy group (median age 58.5, range 8–89 years) and 131 patients in the laparoscopic nephrectomy group (median age 40, range 16–73 years). Clinical parameters such as operative times, blood loss, transfusion rates, conversion and complication rates, start of oral intake, analgesic consumption, duration of hospitalization and convalescence and short–term mortality were compared among both groups. Results: Median operative time in the open flank nephrectomy group was 90 (range 30–240) min and also 90 (range 41–210) min in the laparoscopic nephrectomy group. In the laparoscopy group 8 patients were converted to open surgery (6.1%). There were 27 complications (20.6%) in the laparoscopic nephrectomy group compared to 30 complications (25.4%) in the open flank nephrectomy group. Postoperatively, patients in the laparoscopic nephrectomy group required less morphine sulfate equivalent (12 vs. 20 mg) for pain control and they had a shorter hospital stay (4 vs. 10 days) and convalescence (24 vs. 36 days). The postoperative parameters are given as medians and reached statistically significant differences in favor of laparoscopic nephrectomy. Conclusions: Laparoscopic nephrectomy results in a significantly briefer postoperative course when compared to open flank nephrectomy. As a matter of fact laparoscopy in urology is still a center–related procedure and even in these centers only a minority of urologists practice laparoscopy. However, in experienced centers the laparoscopic technique should be offered to patients with benign renal disease who are scheduled for elective nephrectomy.
Auction based energy trading in transactive energy market with active participation of prosumers and consumers

This paper proposes a Transactive Energy Market (TEM) platform for Peer-to-Peer (P2P) energy trading among prosumers and consumers in the Transactive environment. Prosumers with excess energy participate in the market as seller and consumers play a buyer role and communicate with each other to maximize their welfare, which is the difference between their benefit and cost. The proposed platform is an hour-ahead market, where market subscribers join to trade energy for the next hour. Market clearing is performed using auction approach and a double auction with average mechanism is applied to determine allocation and price of energy. In this platform, market subscribers pay a Subscription Charge (SC) for utilizing the distribution network and this charge is used as a price signal to reduce the possibility of overload in the network's lines. Power Transfer Distributed Factor (PTDF) is used to calculate SC by incorporating network topology and the distributed nature of prosumers and consumers. Simulation results on a simple IEEE 13 node distribution network with 10 subscribers (5 buyers and 5 sellers) demonstrate the efficacy of the proposed TEM platform and market clearing mechanism.
On Simple Back-Off in Unreliable Radio Networks

In this paper, we study local and global broadcast in the dual graph model, which describes communication in a radio network with both reliable and unreliable links. Existing work proved that efficient solutions to these problems are impossible in the dual graph model under standard assumptions. In real networks, however, simple back-off strategies tend to perform well for solving these basic communication tasks. We address this apparent paradox by introducing a new set of constraints to the dual graph model that better generalize the slow/fast fading behavior common in real networks. We prove that in the context of these new constraints, simple back-off strategies now provide efficient solutions to local and global broadcast in the dual graph model. We also precisely characterize how this efficiency degrades as the new constraints are reduced down to non-existent, and prove new lower bounds that establish this degradation as near optimal for a large class of natural algorithms. We conclude with a preliminary investigation of the performance of these strategies when we include additional generality to the model. These results provide theoretical foundations for the practical observation that simple back-off algorithms tend to work well even amid the complicated link dynamics of real radio networks.
Nonlinear Metric Learning through Geodesic Polylinear Interpolation (ML-GPI)

In this paper, we propose a nonlinear distance metric learning scheme based on the fusion of component linear metrics. Instead of merging displacements at each data point, our model calculates the velocities induced by the component transformations, via a geodesic interpolation on a Lie transfor- mation group. Such velocities are later summed up to produce a global transformation that is guaranteed to be diffeomorphic. Consequently, pair-wise distances computed this way conform to a smooth and spatially varying metric, which can greatly benefit k-NN classification. Experiments on synthetic and real datasets demonstrate the effectiveness of our model.