Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum Mechanics/Molecular Mechanics Strategies for Docking Pose Refinement: Distinguishing between Binders and Decoys in Cytochrome c Peroxidase

We investigate the effect of systematically applying molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) to docked poses in an attempt to improve the correspondence between theoretical prediction and experimental observation. The proposed scheme involves running a short time scale MD simulation on a docked ligand pose (and any known structurally important crystal structure waters in the active site), followed by QM/MM minimization. Both of these steps are relatively fast for moderately sized ligands; longer time scale MD involving the protein is not found to improve the results. The final binding energy is given in terms of the QM/MM total energy, a van der Waals correction, and a term to account for desolvation effects. This methodology is first tested with a trypsin inhibitor, for which we establish the importance of running MD before reoptimizing with QM/MM. The method is then applied to cytochrome c peroxidase using a set of binders and decoys. In this example, the proposed methodology affords much better discrimination between binders and decoys than the traditional docking approach used. For both systems presented, application of this protocol results in a significantly better energetic ranking and a smaller root mean squared deviation from known crystallographic ligand poses. This work highlights the importance of including polarization effects through QM/MM and of sampling with MD to refine a set of initial docked poses.
A Novel DBSCAN-Based Defect Pattern Detection and Classification Framework for Wafer Bin Map

Defective die on a wafer map tend to cluster in distinguishable patterns, and such defect patterns can provide crucial information to identify equipment problems or process failures in the semiconductor manufacturing. Therefore, it is important to accurately and efficiently classify the defect patterns. In this paper, we propose a novel clustering-based defect pattern detection and classification framework for wafer bin map (WBM). The proposed framework has many advantages. Outlier detection and defect cluster pattern extraction can be done at the same time; arbitrarily shaped cluster patterns can be detected; and there is no need to specify the number of clusters in advance. Based on WBM property, the parameters used in the clustering algorithm are fixed so that parameter sensitivity can be avoided. Since the defect patterns are classified based on extracted features, no labeled data and no supervised classification training are needed and single-type patterns as well as mixed-type patterns can be found. Extensive experiments conducted on a real-world WM-811K dataset has shown the superiority of proposed framework. The proposed framework can also be used in a big data environment to accelerate performance.
A new method for resisting collision attack based on parallel random delay S-box

Collision Attack (CA) has posed a huge threat to the security of AES circuit. To protect sensitive information, it ’ s necessary to do research on defense strategy of CA. This letter proposes a new method to defense CA through the implementation of random delay based parallel S-box. It can destroy the consistency of the power consumption curves, confuse the judgment of the collision and the setting of the collision threshold to achieve the goal of resisting the CA. Compared to the well-known random mask method and other CA countermeasures, our strategy can defense CA without changing the AES round transformation architecture and bring extra resource overhead.
Genetic polymorphisms on heat-shock protein 70 gene and mitochondrial DNA d-loop variations: implications on selection for heat stress in indigenous chickens in Kenya

Background: Climate change resulting in heat stress, is one of the most challenging environmental conditions affecting poultry. Studying thermotolerance is crucial in the prevention of heat stress in chickens because it may lead to the identification of genetic lines that can withstand adverse effects of heat stress. This study aimed at investigating polymorphisms in heat shock protein 70 (HSP70) gene in indigenous chicken ecotypes. We also analyzed the mitochondrial DNA (mtDNA) D-loop of indigenous chickens to assess their origins and genetic diversity. Methods: We collected samples From Turkana basin, Mt. Elgon catchment, Lake Victoria basin and Lamu chicken ecotypes in Kenya. Genomic DNA was extracted from 280 chicken samples. The first 360 bp region of HSP70 and the first 760 bp region of the mtDNA were then amplified via PCR. These were later sequenced using Sanger ABI 3730 method. Results: We reveal through a detailed analysis of the HSP70 gene fragment in 20 indigenous chickens the presence of three HSP70 haplotypes (GC, AC, and AG) and 28 mtDNA haplotypes. Phylogenetic analysis of HSP70 revealed the presence of the ancestral haplotype GC which dominated in Turkana basin ecotype. The 28 mtDNA haplotypes clustered in haplogroups A, B, C, D, E and I. Haplogroup E which has never been reported in commercial chickens dominated in Turkana basin ecotype indicating no admixture with commercial chickens. mtDNA haplogroups were shown to have originated from various parts of South and Southeast Asia. Lack of population structure in indigenous chicken ecotypes could be an indication of genetic admixture. The mtDNA nucleotide and haplotype diversity indices were low for Turkana basin ecotype and high for Lamu ecotype. High HSP70 nucleotide diversity indices were recorded in Turkana basin ecotype, while low values were recorded in Lamu ecotype. Most of the mtDNA genetic variations occurred within individuals for the three hierarchical categories considered while most variations in HSP70 gene occurred within populations. Conclusions: This is the first study to analyze the HSP70 polymorphisms in indigenous chickens in Africa and results obtained should pave the way for further in-depth studies on heat stress.
Temporal trends of alcohol and drug use among Inuit of Northern Quebec, Canada

Background Alcohol and drug use is a serious health problem for many indigenous populations across Canada, including Inuit. The literature on substance use in these populations is too sparse to devise public health interventions. Objective The present article portrays alcohol and drug use among Inuit living in Nunavik (Northern Quebec) between the 1990s and 2000s, and identifies socio-demographic characteristics related to substance use. Design The Santé Québec Health Survey (1992) and the Nunavik Inuit Health Survey Qanuippitaa (2004) served as databases for this empirical work. Statistical comparisons were made of substance use variables in the 2 samples. Proportions were compared by chi-square tests (p≤0.05) with benchmarking of statistics for all of Quebec and, when available, all of Canada. Results Alcohol and drug use among Inuit increased significantly between 1992 and 2004, particularly among young adults. Alcohol users consumed significantly more alcohol per drinking episode than other Canadians in both time periods. Considerable cannabis use was widespread. In 2004, no significant differences in frequencies of heavy drinking episodes were observed by gender, with 60% of drug users consuming alcohol on a regular basis. Conclusions As in other populations from North America, this study profiles the increase in substance use among Inuit from Nunavik in the first part of the last 20 years. We observed distinct substance use patterns among them in comparison to other Canadians. Such findings, if replicated in the coming years, emphasize the need for major, culturally-relevant public health interventions in this population.
A PIC-MCC Simulation of the High-Voltage Interruption Ability of a Vacuum Interrupter

In order to determine the ultimate high voltage interruption ability of a vacuum interrupter, a PIC-MCC (particle in cell - Monte Carlo collision) computer simulation was utilized under the following conditions. Residual charged and neutral particles at current zero were arranged between the electrodes. This was the initial condition. These particle conditions were obtained from extrapolated values of experimental data. Secondary electron emission and self-sputtering effects due to ion bombardment were also considered for this simulation. From the result of a simulation on a 168 kV/25 kA 40 mm diameter one-break interrupter, the breaking ability was found to be influenced most by the initial neutral particle density. The charged particle density and the secondary electron emission coefficient were found to have less effect on the breaking capability. Consequently, it is estimated that the self-sputtering coefficient by ion bombardment is one of the most important parameters of metal vapor supply
Optoelectronic waveforms generation: PCSS characterization and genetic algorithm

This paper proposes a contribution to optoelectronic ultra-wideband transient waveforms generation. It describes a genetic algorithm (GA) development, a Photoconductive Semiconductor Switch (PCSS) characterization and optimization modeling. The genetic algorithm enables generation of arbitrary transient waveforms from specific spectral conditions. Experimental measurements have been carried out with an optoelectronic bench which generates high-voltage pulses (few kV peak). Measurements lead to an Agilent Advance Design System (ADS) modeling predicting PCSS response to an optical impulsion at 1064nm.
A Digital Polar Transmitter With DC–DC Converter Supporting 256-QAM WLAN and 40-MHz LTE-A Carrier Aggregation

A digital polar transmitter is introduced using 9-b thermometer-coded uniform cells for wideband signal. By analyzing amplitude and phase paths impairment which causes both in-band and out-of-band distortions, a 960-MHz delay tuner is designed for precise amplitude and phase alignment. Furthermore, two digital pre-distortion algorithms for digital power amplifier (DPA) are implemented and compared. Importantly, an on-chip dc–dc converter is included for direct battery connection and output power control. Boosted cascode gate bias improves PA efficiency at low power region. The proposed design is fabricated using a 55-nm RF CMOS technology. This DPA including digital amplitude modulation (AM) filtering achieves peak power of +21.9 dBm with 41% drain efficiency in continuous-wave measurements. It achieves EVM of 2.9% with 20-MHz IEEE 802.11ac compliance of 256-QAM OFDM signal, and also achieves EVM of 4.5% (CC0)/4.8% (CC1) with 40-MHz LTE-A carrier aggregation compliance of 64-QAM OFDM signal.
A new approach to MRI brain images classification

The aim of this work is to present an automated method that assists diagnosis of normal and abnormal MR images. The diagnosis method consists of four stages, preprocessing of MR images, feature extraction, dimensionality reduction and classification. After histogram equalization of image, the features are extracted based on discrete wavelet transformation (DWT). Then the features are reduced using principal component analysis (PCA). In the last stage three classification methods, k-nearest neighbour (k-NN), parzen window and artificial neural network (ANN) are employed. Our work is the modification and extension of the previous studies on the diagnosis of brain diseases, while we obtain better classification rate with the less number of features and we also use larger and rather different database.
Completing Explorer Games with a Deep Reinforcement Learning Framework Based on Behavior Angle Navigation

In cognitive electronic warfare, when a typical combat vehicle, such as an unmanned combat air vehicle (UCAV), uses radar sensors to explore an unknown space, the target-searching fails due to an inefficient servoing/tracking system. Thus, to solve this problem, we developed an autonomous reasoning search method that can generate efficient decision-making actions and guide the UCAV as early as possible to the target area. For high-dimensional continuous action space, the UCAV’s maneuvering strategies are subject to certain physical constraints. We first record the path histories of the UCAV as a sample set of supervised experiments and then construct a grid cell network using long short-term memory (LSTM) to generate a new displacement prediction to replace the target location estimation. Finally, we enable a variety of continuous-control-based deep reinforcement learning algorithms to output optimal/sub-optimal decision-making actions. All these tasks are performed in a three-dimensional target-searching simulator, i.e., the Explorer game. Please note that we use the behavior angle (BHA) for the first time as the main factor of the reward-shaping of the deep reinforcement learning framework and successfully make the trained UCAV achieve a 99.96% target destruction rate, i.e., the game win rate, in a 0.1 s operating cycle.
A novel single-stage high power factor electronic ballast for metal halide lamps free of acoustic resonance

This paper proposes a novel single-stage high-power-factor electronic ballast for metal halide lamps. By integrating two buck-boost typed power-factor-correction converters, a full-bridge inverter and a bidirectional buck converter, a single-stage electronic ballast with symmetrical circuit topology is derived. The circuit component count can be effectively reduced and circuit energy-conversion efficiency is improved. With a tactful control scheme, the proposed electronic ballast can output a low-frequency square-wave voltage to drive metal halide lamps. The problematic phenomena of acoustic resonance can be eliminated. A high power factor at the input line is assured by operating the buck-boost converters in discontinuous conduction mode. The operation modes, design equations and design steps for the circuit parameters are proposed. A prototype circuit designed for a 70-W metal halide lamp was built and tested to verify the analytical predictions. Satisfactory performances are obtained from the experimental results.
Let Your CyberAlter Ego Share Information and Manage Spam

Almost all of us have multiple cyberspace identities, and these cyberalter egos are networked together to form a vast cyberspace social network. This network is distinct from the world-wideweb (WWW), which is being queried and mined to the tune of billions of dollars everyday, and until recently, has gone largely unexplored. Empirically, the cyberspace social networks have been found to possess many of the same complex features that characterize its real counterparts, including scalefree degree distributions, low diameter, and extensive connectivity. We show that these topological features make the latent networks particularly suitable for explorations and management via localonly messaging protocols. Cyberalter egos can communicate via their direct links (i.e., using only their own address books) and set up a highly decentralized and scalable message passing network that can allow large-scale sharing of information and data. As one particular example of such collaborative systems, we provide a design of a spam filtering system, and our large-scale simulations show that the system achieves a spam detection rate close to 100%, while the false positive rate is kept around zero. This system of letting cyberalter egos network among themselves has several advantages over other recent proposals for collaborative spam filtering: (i) It uses an already existing network, created by the same social dynamics that govern our daily lives, and no dedicated peerto-peer (P2P) systems or centralized server-based systems need be constructed; (ii) It utilizes a percolation search algorithm (which can be viewed as mimicking how rumor is spread in a social network) that makes the query-generated traffic scalable; (iii) The network has a built in trust system (just as in social networks) that can be used to thwart malicious attacks; and (iv) It can be implemented right now as a plugin to popular email programs, such as MS Outlook, Eudora, and Sendmail.
Explicit Space&#8211;Time Codes Achieving the Diversity&#8211;Multiplexing Gain Tradeoff

A recent result of Zheng and Tse states that over a quasi-static channel, there exists a fundamental tradeoff, referred to as the diversity-multiplexing gain (D-MG) tradeoff, between the spatial multiplexing gain and the diversity gain that can be simultaneously achieved by a space-time (ST) code. This tradeoff is precisely known in the case of independent and identically distributed (i.i.d.) Rayleigh fading, for Tgesnt+nr-1 where T is the number of time slots over which coding takes place and nt,nr are the number of transmit and receive antennas, respectively. For T<nt+nr-1, only upper and lower bounds on the D-MG tradeoff are available. In this paper, we present a complete solution to the problem of explicitly constructing D-MG optimal ST codes, i.e., codes that achieve the D-MG tradeoff for any number of receive antennas. We do this by showing that for the square minimum-delay case when T=nt=n, cyclic-division-algebra (CDA)-based ST codes having the nonvanishing determinant property are D-MG optimal. While constructions of such codes were previously known for restricted values of n, we provide here a construction for such codes that is valid for all n. For the rectangular, T>nt case, we present two general techniques for building D-MG-optimal rectangular ST codes from their square counterparts. A byproduct of our results establishes that the D-MG tradeoff for all Tgesnt is the same as that previously known to hold for Tgesnt+n r-1
A performance comparison of the Rete and TREAT algorithms for testing database rule conditions

The authors present the results of a simulation comparing the performance of the two most widely used production rule condition testing algorithms, Rete and TREAT, in the context of a database rule system. The results show that TREAT almost always outperforms Rete. TREAT requires less storage than Rete, and is less sensitive to optimization decisions than Rete. Based on these results, it is concluded that TREAT is the preferred algorithm for testing join conditions of database rules. Since Rete does outperform TREAT in some cases, this study suggests a next step which would be to develop a hybrid version of Rete and TREAT with an optimizer that would decide which strategy to use based on the rule definition and statistics about the data and update patterns. <<ETX>>
Diversity and size-structured persistence of tropical carnivores in a small, isolated protected area

Abstract Protected areas are critical to biodiversity conservation. Yet many protected areas around the world are very small, and population persistence can be compromised in small habitat patches, particularly for large species. But we do not know how small is too small for long-term population viability, or the degree to which habitat area effects vary with mammal body size, for most tropical species. Here, diversity and species occurrence were assessed in a small national park that has long been isolated from other forest patches. The two largest Bornean carnivores, the Sunda clouded leopard (Neofelis diardi) and sun bear (Helarctos malayanus), may be locally extinct, but 12 smaller carnivores appear to be persisting. The banded civet (Hemigalus derbyanus), the Malay civet (Viverra tangalunga) and the leopard cat (Prionailurus bengalensis) had relatively high occurrence rates and were found in all habitat types, though were more common in hill (banded civet) or lowland (common palm civet) forest (LF). Occurrence probabilities for all of these species and the common palm civet (Paradoxurus hermaphroditus) were lower in areas more accessible to humans. Detection rates and estimated diversity suggest that this park has a small carnivore assemblage equivalent to those of much larger areas. These are the first results demonstrating size-specific vulnerability to area effects in Southeast Asian carnivores.
Computation Efficiency and Robustness Improvement of Predictive Control for PMS Motors

High computational burden and model dependence of the conventional model predictive control of permanent magnet synchronous motors are regarded as the two shortcomings of this attractive control scheme. A new method is proposed in this paper to overcome the mentioned drawbacks. The method evaluates a cost function for only three admissible inverter voltage vectors in each sampling period for a two-level inverter without deteriorating motor performance. Furthermore, the prediction of the torque for the next sampling period(s) is achieved without using the motor parameters. The proposed finite control set predictive control is evaluated through the simulation and experimental tests for a permanent magnet synchronous motor. In addition, the motor performance under the proposed control is compared with those under two other predictive control methods. The results show that parameter mismatch does not affect the prediction of the torque under the proposed control method, thus resulting in improved robustness of the motor drive system against motor parameter variations.
Reversible out-of-plane spin texture in a two-dimensional ferroelectric material for persistent spin helix

Although spin-orbit coupling (SOC) in ferroelectrics contributes to the manipulation of the electron spin by an electric field, it also breaks the spin rotation symmetry resulting in the decay of spin polarization. Here, we showed that the [110] Dresselhaus model in the two-dimensional ferroelectrics with in-plane ferroelectricity can host a persistent spin helix and render the spin lifetime infinite. Taking a ${\mathrm{WO}}_{2}{\mathrm{Cl}}_{2}$ monolayer as an example, we demonstrated from first principles that SOC leads to a sizable [110] Dresselhaus-type band splitting near the conduction-band minimum accompanied by an out-of-plane Dresselhaus-type spin texture which is decisive for a long spin lifetime. More interestingly, such a spin texture can be reversed by switching the ferroelectric polarization, suggesting the fully electrically controllable persistent spin helix. Our findings uncover the possibility of an electrically controllable persistent spin helix in ferroelectrics, offering a promising platform for novel spintronics applications.
CHA2DS2-VASc score can guide the screening of atrial fibrillation - cross-sectional study in a geriatric ward

Purpose: Atrial fibrillation (AF) is an increasingly common rhythm disorder and an important risk factor of ischemic stroke, heart failure, hospitalization, and cardiovascular mortality. Its diagnosis, however, is often delayed because of silent character of the arrhythmia. The aim of the study was to identify independent determinants of AF in patients of the geriatric ward, so as to be able to propose a strategy for screening of this arrhythmia. Methods: Cross-sectional cohort study of patients admitted to the department of geriatrics was conducted. The prevalence of AF and its health correlates (including AF recognized risk factors) was assessed. Relative risks were calculated and multivariable logistic regression analysis model was built. The predictive performance was evaluated using receiver-operating characteristic (ROC) curve analysis. Results: There were 416 patients hospitalized in the study period and 98 (23.6%) presented with AF. The independent predictors with top 3 strongest association with AF were congestive heart failure (OR 5.43; 95%CI 3.14–9.39; P<0.001), age of 75+years (OR 4.0; 95% CI 1.43–11.2; P=0.008), and previous history of stroke or transient ischemic attack (OR 2.1; 95% CI 1.06–4.13; P=0.03). ROC analysis showed CHA2DS2-VASc scale significance as a screening tool for AF (ROC-AUC 0.75; 0.7–0.8; P<0.001), with the value of 4 or more as the best cut-off point. Conclusions: Based on CHA2DS2-VASc score the intensity of surveillance for AF at a primary prevention population level could be probably guided, but it requires further research.