Miracle-dz/UniFAR-FTUs huggingface dataset:
MPADE: An Improved Adaptive Multi-Population Differential Evolution Algorithm Based on JADE

JADE is an state-of-the-art adaptive differential evolution algorithm which implements “DE/current-to-pbest” as its mutation strategy, adapts its mutation factor and crossover rate, and uses an optional external archive to keep track of potential removed individuals in previous generations. This paper proposes MPADE, which extends JADE by using a multi-populated approach to solve high dimensional real-parameter optimization problems. This mechanism helps preventing the two well-known problems affecting the differential evolution algorithm performance, which are premature convergence and stagnation. The algorithm was tested using the benchmark functions in IEEE Congress on Evolutionary Computation 2014 test suite. MPADE was compared using Wilcoxon test to JADE algorithm and with other state-of-the-art algorithms that either use a multi-population approach or adapt their parameters. The experimental results show that the proposed new algorithm improves significantly its precursor and it is also suggested that other state-of-the-art algorithms could benefit from the multi-populated based approach.
Analysis on Sub-Synchronous Oscillation Associated with Wind Farms Based on Direct-Driven Wind Generators

Recently, several literatures reported that sub-synchronous oscillation (SSO) events occurred in wind farms based on direct-driven wind generators (DDWGs). This paper focuses on whether a wind farm consists of only DDWGs would bring an SSO. First, a small-signal model of the DDWG-based wind farm is proposed. Eigen-analysis indicates that there are natural modes with sub-synchronous frequency; however, their damping ratios are significantly large under specific control parameters. Further, the relationships between the sub-synchronous modes and the number of grid-connected DDWGs, the connecting reactance and the circuit topologies of the wind farm are analyzed. Taguchi's orthogonal array testing is also introduced to analyze the impact of the wind farm's stochastic operating conditions on the modes. Results show that if the DDWGs are well-tuned, the dynamics of the wind farm are similar to one DDWG, and the sub-synchronous modes have little correlation with those factors, thus SSO can hardly arise when the model of wind farm only includes DDWGs. Electromagnetic transient simulations are also carried out to prove the accuracy and efficiency of the results.
Subset selection in sparse matrices

In subset selection we search for the best linear predictor that involves a small subset of variables. From a computational complexity viewpoint, subset selection is NP-hard and few classes are known to be solvable in polynomial time. Using mainly tools from discrete geometry, we show that some sparsity conditions on the original data matrix allow us to solve the problem in polynomial time.
Active Semi-supervised Affinity Propagation Clustering Algorithm Based on Local Outlier Factor

Clustering algorithm can reveal the inherent properties and laws of data through the learning of unlabeled data. However, interference data exists in some fields of different data forms, and the clustering will reduce the credibility of clustering results without processing data. This paper puts forward a semi-supervised clustering algorithm based on outlier pruning (LOF-SAP). For the outlier in the data, the local outlier factor algorithm (LOF) is used to look for them and reduce the influence of the outliers in data structure. Then, semi-supervised clustering algorithms can help find better partitions of data in the presence of side information. And then side information that is pair-wise constraint obtained with active learning is embedded in the data similarity matrix. At the last through affinity propagation clustering algorithm, clustering results obtains. This method is compared with the traditional affinity propagation (AP) clustering algorithm and the AP clustering algorithm with pair-wise constraint, and the experiment is done by using UCI database. And the proposed method can achieve better clustering performance.
Comparative metagenomics of the gut microbiota in wild greylag geese (Anser anser) and ruddy shelducks (Tadorna ferruginea)

Gut microbiome contributes to host health by maintaining homeostasis, increasing digestive efficiency, and facilitating the development of immune system. Wild greylag geese (Anser anser) and ruddy shelducks (Tadorna ferruginea), migrating along the central Asian flyway, appear to be one of the most popular species in the rare birds rearing industries of China. However, the structure and function of the gut microbial communities associated with these two bird species remain poorly understood. Here, for the first time, we compared gut metagenomes from greylag geese to ruddy shelducks and investigated the similarities and differences between these two bird species in detail. Taxonomic classifications revealed the top three bacterial phyla, Firmicutes, Proteobacteria, and Fusobacteria, in both greylag geese and ruddy shelducks. Furthermore, between the two species, 12 bacterial genera were found to be more abundant in ruddy shelducks and 41 genera were significantly higher in greylag geese. A total of 613 genera (approximately 70%) were found to be present in both groups. Metabolic categories related to carbohydrate metabolism, metabolism of cofactors and vitamins, lipid metabolism, amino acid metabolism, and glycan biosynthesis and metabolism were significantly more abundant in ruddy shelducks, while greylag geese were enriched in nucleotide metabolism and energy metabolism. The herbivorous greylag geese gut microbiota harbored more carbohydrate‐active enzymes than omnivorous ruddy shelducks. In our study, a range of antibiotic resistance categories were also identified in the gut microbiota of greylag geese and ruddy shelducks. In addition to providing a better understanding of the composition and function of wild birds gut microbiome, this comparative study provides reference values of the artificial domestication of these birds.
Company Data in the Blockchain: A Juxtaposition of Technological Drivers and Potential Applications

The potential of Blockchain technology has long been recognized outside the financial sector. Wherever data need to be stored and kept decentralized, tamper-resistant, and realtime-capable without involving a trusted intermediary, applications based on Blockchain technology promise to create opportunities for innovations of cross-company processes. In the presented paper, the technical possibilities of Blockchains are analyzed and classified according to their suitability to address specific challenges. This makes it possible to identify those technological drivers that are particularly promising for applicability in a corporate context. This includes, for example, tamper-resistance and security from forgery, which can be achieved without intermediaries with the help of data encryption methods using hash functions. Another technological capability of Blockchains is to provide a high degree of data security, which can be realized using public-key cryptography. The technological drivers will be juxtaposed with data as typically generated in manufacturing companies (orders and order confirmations, production data, quality-related data, etc.). Subsequently, the prerequisites that these data must meet with regard to storage capacity and transferability will be identified. By linking the results to the identified technological drivers and functions it becomes possible to determine what types of company data have the potential to be successfully stored and managed in a Blockchain.
Increased complications in geriatric patients with a fracture of the hip whose postoperative weight‐bearing is restricted: AN ANALYSIS OF 4918 PATIENTS

Aims The aims of this study were to evaluate the incidence of postoperatively restricted weight‐bearing and its association with outcome in patients who undergo surgery for a fracture of the hip. Patients and Methods Patient aged > 60 years undergoing surgery for a hip fracture were identified in the 2016 National Surgical Quality Improvement Program (NSQIP) Hip Fracture Targeted Procedure Dataset. Analysis of the effect of restricted weight‐bearing on adverse events, delirium, infection, transfusion, length of stay, return to the operating theatre, readmission and mortality within 30 days postoperatively were assessed. Multivariate regression analysis was used to adjust for confounding demographic, comorbid and procedural characteristics. Results Of the 4918 patients who met inclusion criteria, 3668 (63.53%) were allowed to weight‐bear as tolerated postoperatively. Controlling for patient and procedural factors, multivariate odds of any adverse event, major adverse event, delirium, infection, transfusion, length of stay ≥ 75th percentile (six days) and mortality within 30 days were all higher in patients with weight‐bearing restrictions. Notably, there were no differences for thromboembolic events, return to the operating theatre or readmission within 30 days between the groups. Conclusion Elderly patients with a fracture of the hip with postoperative weight‐bearing restrictions have a significantly greater risk of developing most adverse events compared with those who are encouraged to weight‐bear as tolerated. These findings emphasize the importance of immediate weight‐bearing as tolerated to optimize the outcome in these frail patients; however nearly 25% of surgeons fail to meet this evidence‐based guideline.
Electrical-Thermal Co-Simulation for LFBGA

To verify the interaction of non-uniform power joule heat and temperature on chip, the electrical-thermal co- simulation is applied for low-profile fine-pitch ball grid array(LFBGA). Based on ANSYS Siwave, the power dissipation is simulated firstly. Similarly, temperature is simulated in ANSYS Icepak. By using the data interface between Siwave and Icepak, the two-way coupling can be accomplished. Thermal resistance is used to estimate the heat dissipation capability. According to comparing the results, the non-uniform joule heat and temperature are rising simultaneously.
Stochastic bipartite consensus of discrete-time multi-agent systems with random link failure over signed graph

This paper investigates the stochastic bipartite consensus problem for discrete-time multi-agent systems in the presence of antagonistic interactions, noise and random link failure. First of all, we define mean square bipartite consensus and almost sure bipartite consensus for multi-agent systems with the help of stochastic theory, matrix theory and algebraic graph theory. Second, we design a cooperative protocol for stochastic bipartite consensus based on the neighbors' information on signed directed graph. Third, for the case that communication graph Gm has a directed spanning tree and is structurally balanced, stochastic bipartite consensus can be achieved for discrete-time multi-agent systems. Finally, an example is given to support our result.
Time-Varying SAR Interference Suppression Based on Delay-Doppler Iterative Decomposition Algorithm

Narrow-band interference (NBI) and Wide-band interference (WBI) are critical issues for synthetic aperture radar (SAR), which degrades the imaging quality severely. Since some complex signals can be modeled as linear frequency modulated (LFM) signals within a short time, LFM-WBI and NBI are mainly discussed in this paper. Due to its excellent energy concentration and useful properties (i.e., auto-terms pass through the origin of Delay-Doppler plane while cross-terms are away from it), a novel nonparametric interference suppression method using Delay-Doppler iterative decomposition algorithm is proposed. This algorithm consists of three stages. First, we present signal synthesis method (SSM) from ambiguity function (AF) and cross ambiguity function (CAF) based on the matrix rearrangement and eigenvalue decomposition. Compared with traditional SSM from Wigner distribution (WD), the proposed SSM can synthesize a signal faster and more accurately. Then, based on unique properties in Delay-Doppler domain, a mask algorithm is applied for interference identification and extraction using Radon and its inverse transformation. Finally, a signal iterative decomposition algorithm (IDA) is utilized to subtract the largest interference from the received signal one by one. After that, a well-focused SAR imagery is obtained by conventional imaging methods. The simulation and measured data results demonstrate that the proposed algorithm not only suppresses interference efficiently but also preserves the useful information as much as possible.
AVIA: Automatic Vulnerability Impact Assessment on the Target System

Manual labor in information technologies becomes too much time-consuming and not effective with increasing complexity of computer systems. As a result, automation of all process in cyber security gains a popularity in recent years. Impact evaluation of disclosed security flaw on overall system can be a challenge under certain conditions. In this paper we designed a new method, which makes automatic vulnerability impact assessment and reduces manual vulnerability impact analysis with the help of binary analysis and public non-code text related vulnerability information.
Diffusion of Innovations and Personal Network

In this study, I examine the knowledge created by innovation adopters to reduce uncertainty associated with innovations in the process of innovation diffusion and analyze the hiring network. Specifically, first, I examine the knowledge that doctors create in the process of adopting new medicines in the ophthalmological field. Next, I examine the researcher network, which is the mother of knowledge creation. Doctors tend to have a strong connection with their home college and working hospitals. I also discovered the role of key personnel in forming doctor's networks. The findings of this study provide a theoretical and practical contribution not only to the diffusion of new drugs but also to the diffusion of new products in other areas.
Differential Effects of Salient Visual Events on Memory‐Guided Attention in Adults and Children

Both salient visual events and scene‐based memories can influence attention, but it is unclear how they interact in children and adults. In Experiment 1, children (N = 27; ages 7–12) were faster to discriminate targets when they appeared at the same versus different location as they had previously learned or as a salient visual event. In contrast, adults (N = 30; ages 18–31) responded faster only when cued by visual events. While Experiment 2 confirmed that adults (N = 27) can use memories to orient attention, Experiment 3 showed that, even in the absence of visual events, the effects of memories on attention were larger in children (N = 27) versus adults (N = 28). These findings suggest that memories may be a robust source of influence on children's attention.
Fault Detection for Networked Control Systems with Two-channel Packet Dropouts Using Delta Operator

This paper addresses the problem of fault detection for networked control systems (NCSs) with two-channel packet dropouts and time-varying delays via delta operator. Packet dropouts exist in both channels from sensors to controllers and from controllers to actuators, and utilize two independent Bernoulli random variables to represent it. Then the system with packet dropouts and time-varying delays is modeled as a networked switched system. A design scheme of fault detection filter is proposed under an arbitrary switching law. Furthermore, sufficient conditions that the switched system is exponentially stable in the mean-square sense are developed by means of linear matrix inequalities (LMI), Lyapunov-Krasovskii functional and average dwell-time (ADT) approach. The minimal $H_{\infty}$ disturbance attenuation level is also achieved. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.
Design and Analysis of A Novel Stator Permanent Magnet Linear Motor Drive Mechanical Press

– Eliminating any middle transmissions, mechanical press direct driven by permanent magnet linear motor (PMLM) can meet the demands of high speed, high efficiency and precise control. However, traditional PMLM drive press exists restrictive relation between power, cost and reliability. A novel stator permanent magnet linear motor (SPMLM) is proposed to directly drive mechanical press, the motor topology and mechanical press structure are introduced. Based on electromagnetic finite element analysis (FEA), longitudinal end effect of the SPMLM is weakened, and the force capability is optimized then the whole design parameters are determined. Thermal characteristic of the proposed press is analyzed to ensure the temperature raising is acceptable. The proposed SPMLM can be driven by the common vector control system, and the whole system is simulated through field-circuit coupling analysis, the results show the proposed press indicates favorable dynamic performance.
Spatial Mining of Web-Log to observe reachability of Website

The web sites are the virtual interface of an organization. the object of designing a web site is to reach to the maximum public. To evaluate the reachability of web site organization wants to look for the spread of the visitors reaching to the website the weblog contains. The IP address through which the location of the visitor can be trace the data mining techniques helps to visualize the patters in the system. in this paper k means clustering techniques is used to find the clusters of people, using the NASA website.
A Chinese cross-sectional study on depression and anxiety symptoms in patients with psoriasis vulgaris

ABSTRACT Previous studies have reported a higher incidence of depression and anxiety in psoriasis patients compared to the general population, which has important implications for assessment and treatment. In this study, we determined the frequency of depression and anxiety in Chinese patients with psoriasis and its relationship with disease severity and other demographic variables. The study included 208 Chinese patients with psoriasis vulgaris. The Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder scale (GAD-7) were used to screen for depression and anxiety. The Psoriasis Area and Severity Index (PASI) was used to assess the severity of psoriasis. Of the 208 patients included in the study, 29 patients (13.9%) were positive for moderate-to-severe depression (PHQ-9 ≥ 10) and 22 patients (10.6%) were positive for anxiety (GAD-7 ≥ 10) symptoms. Both positive stress reactors who perceived stress as an exacerbating factor of psoriasis and moderate-to-severe psoriasis were found to be positive predictors for the presence of moderate-to-severe depression or anxiety symptoms while longer duration and late onset age played a protective role. In the sample of Chinese patients with psoriasis there was a clinically significant prevalence of depression and anxiety. Our study suggests that Chinese psoriasis patients should be screened for psychiatric comorbidities.
Secure Computing for the Internet of Things and Network Edges: Protecting Communication in the Worldwide Network of Devices

The Internet of Things (IoT) is focused on architectures and protocols for the efficient interconnection of heterogeneous things, deployment of infrastructure, and creation of value-added services. The IoT has become an emerging technology, where more than 50 billion things will be connected to the Internet by 2020, and data in the network will grow by another 1,000 times. The framework of the IoT is the backbone for several applications, such as smart cities and smart homes, where most of the data move to the cloud for further evaluation because of the resource poverty of IoT devices.
Intranasal oxytocin in rhesus monkeys alters brain networks that detect social salience and reward

In primates, resting state functional neuroimaging (rsfcMRI) has identified several large‐scale, intrinsic brain networks, including the salience network (SN), which is involved in detecting stimulus salience. Intranasal oxytocin (IN‐OT) has been shown to modulate the salience and rewarding quality of social stimuli in mammals and numerous studies have shown that it can affect the functional connectivity between brain regions. Less is known, however, about how these effects unfold over time following IN‐OT administration. This study used rsfcMRI in anesthetized rhesus macaques to track temporal changes in the functional connectivity between brain regions involved in the SN, including the anterior cingulate cortex (ACC), anterior insula (AI), amygdala (amy), and ventral striatum (vstr), lasting 3 hr after IN‐OT or Placebo (saline) administration. We found significant temporal changes in the functional connectivity between all regions associated with treatment condition. IN‐OT increased the functional connectivity between AI_vstr, ACC_amy (right hemisphere), ACC_vstr (left hemisphere), and amy_vstr (right hemisphere), but reduced the functional connectivity between ACC_AI, and the AI_amygdala. These results suggest that IN‐OT may dampen salience detection in rhesus monkeys, consistent with previous findings of reduced social vigilance, while enhancing the connectivity between the SN and regions involved in processing reward.
Polypyrrole Hollow Nanosphere Intercalated Graphene-based Flexible Supercapacitor

Flexible supercapacitors are a significant class of energy storage devices for the wearable flexible electronic devices. In this study, a flexible electrode material for polypyrrole hollow nanospheres and reduced graphene oxide was prepared for flexible supercapacitor. The polypyrrole hollow nanospheres were prepared by emulsion polymerization and in-situ polymerization, and HI was used to reduce Graphene oxide (GO). The electrochemical performance of obtained electrode material was tested, which exhibits area specific capacitance of 381.54 mF/cm2 at 2 mA/cm2, and shows capacitance retention of 93.94% after 1000 GCD cycles, demonstrating the good cycle stability of electrode material of PPy/rGO. Furthermore, we assembled a simple symmetrical supercapacitor based on the prepared electrode material to assess its electrochemical performance and reliability in application. It has been shown that the assembled symmetrical supercapacitor can be used as a power supplier to lighten light-emitting diode (LED) light. These electrochemical results indicate that the prepared material is a suitable flexible supercapacitor electrode material.
The Study on Taiwan's High School Crisis Management Model

The purpose of this study was to construct a crisis management model specifically designed for high schools in Taiwan with intent to meet the actual needs of crisis management now in high school campus. The construction of such a model involves first integrating expert opinions on crisis management in high schools, then confirming priorities of crisis management items using Interpretive Structural Model(ISM) as a research tool, and finally combing quality management concepts of six sigma of Define(D), Measure(M), Analyze(A), Improve(I), and Control(C). A campus crisis management hierarchy was thus established and presented by means of diagrams in the current study. It is hoped by the researcher that when encountering major security incidents, school authority can draw explicit reference from the model proposed, and that actual needs of crisis management in high school campus can be met.