Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Generation of Capability Leaks' Exploits for Android Applications

The capability leak of Android applications is one kind of serious vulnerability. It causes other apps to leverage its functions to achieve their illegal goals. In this paper, we propose a tool which can automatically generate capability leaks' exploits of Android applications with path-sensitive symbolic execution-based static analysis and test. It can aid in reducing false positives of vulnerability analysis and help engineers find bugs. We utilize control flow graph (CFG) reduction and call graph (CG) search optimization to optimize symbolic execution, which make our tool applicable for practical apps. By applying our tool to 439 popular applications of the Wandoujia (a famous app market in China) in 2017, we found 2239 capability leaks of 16 kinds of permissions. And the average analysis time was 4 minutes per app. A demo video can be found at the website https://youtu.be/dXFMNZWxEc0
Evolutionary trade-offs between baseline and plastic gene expression in two congeneric oyster species

Organismal responses to environmental stresses are a determinant of the effect of climate change. These can occur through the regulation of gene expression, involving genetic adaptation and plastic changes as evolutionary strategy. Heat shock protein (hsp) family genes are extensively expanded and play important roles in thermal adaptation in oysters. We investigated expression of all heat-responsive hsps in two allopatric congeneric oyster species, Crassostrea gigas and C. angulata, which are respectively distributed along the northern and southern coasts of China, using common garden and reciprocal transplant experiments. Our results showed that hsps in C. gigas have evolved higher basal levels of expression under ambient conditions at each field site, with lower expression plasticity in response to heat stress in comparison to C. angulata, which exhibited lower baseline expression but higher expression plasticity. This pattern was fixed regardless of environmental disturbance, potentially implying genetic assimilation. Our findings indicate divergent adaptive strategies with underlying evolutionary trade-offs between genetic adaptation and plasticity at the molecular level in two oyster congeners in the face of rapid climate change.
Communication barriers in maternity care of allophone migrants: Experiences of women, healthcare professionals, and intercultural interpreters

Abstract Aim To describe communication barriers faced by allophone migrant women in maternity care provision from the perspectives of migrant women, healthcare professionals, and intercultural interpreters. Background Perinatal health inequality of migrant women hinges on barriers to services, with a major barrier being language. Their care is often also perceived as demanding due to conflicting values or complex situations. Potentially divergent perceptions of users and providers may hinder efficient communication. Design Qualitative explorative study. Methods A convenience sample of 36 participants was recruited in the German speaking region of Switzerland. The sample consisted of four Albanian and six Tigrinya speaking women, 22 healthcare professionals and four intercultural interpreters (March–June 2016) who participated in three focus group discussions and seven semi‐structured interviews. Audio recordings of the discussions and interviews were transcribed and thematically analysed. Results The analysis revealed three main themes: the challenge of understanding each other's world, communication breakdowns and imposed health services. Without interpretation communication was reduced to a bare minimum and thus insufficient to adequately inform women about treatment and address their expectations and needs. Conclusion A primary step in dismantling barriers is guaranteed intercultural interpreting services. Additionally, healthcare professionals need to continuously develop and reflect on their transcultural communication. Institutions must enable professionals to respond flexibly to allophone women's needs and to offer care options that are safe and in accordance to their cultural values. Impact Our results give the foundation of tenable care of allophonic women and emphasize the importance of linguistic understanding in care quality.
Gut Microbiota and Colonization Resistance against Bacterial Enteric Infection

The gut microbiome is critical in providing resistance against colonization by exogenous microorganisms. The mechanisms via which the gut microbiota provide colonization resistance (CR) have not been fully elucidated, but they include secretion of antimicrobial products, nutrient competition, support of gut barrier integrity, and bacteriophage deployment. SUMMARY The gut microbiome is critical in providing resistance against colonization by exogenous microorganisms. The mechanisms via which the gut microbiota provide colonization resistance (CR) have not been fully elucidated, but they include secretion of antimicrobial products, nutrient competition, support of gut barrier integrity, and bacteriophage deployment. However, bacterial enteric infections are an important cause of disease globally, indicating that microbiota-mediated CR can be disturbed and become ineffective. Changes in microbiota composition, and potential subsequent disruption of CR, can be caused by various drugs, such as antibiotics, proton pump inhibitors, antidiabetics, and antipsychotics, thereby providing opportunities for exogenous pathogens to colonize the gut and ultimately cause infection. In addition, the most prevalent bacterial enteropathogens, including Clostridioides difficile, Salmonella enterica serovar Typhimurium, enterohemorrhagic Escherichia coli, Shigella flexneri, Campylobacter jejuni, Vibrio cholerae, Yersinia enterocolitica, and Listeria monocytogenes, can employ a wide array of mechanisms to overcome colonization resistance. This review aims to summarize current knowledge on how the gut microbiota can mediate colonization resistance against bacterial enteric infection and on how bacterial enteropathogens can overcome this resistance.
Distributed Discovery of Functional Dependencies

We address the problem of discovering functional dependencies from distributed big data. Existing (non-distributed) algorithms such as FastFDs focus on minimizing computation. However, distributed algorithms must also optimize data communication costs, especially in shared-nothing settings. We propose a distributed version of FastFDs that is communication-efficient and we experimentally show significant performance improvements over a straightforward distributed implementation.
Accumulation of glycinebetaine in rice plants that overexpress choline monooxygenase from spinach and evaluation of their tolerance to abiotic stress.

BACKGROUND AND AIMS Glycinebetaine (GB), a quaternary ammonium compound, is a very effective compatible solute. In higher plants, GB is synthesized from choline (Cho) via betaine aldehyde (BA). The first and second steps in the biosynthesis of GB are catalysed by choline monooxygenase (CMO) and by betaine aldehyde dehydrogenase (BADH), respectively. Rice (Oryza sativa), which has two genes for BADH, does not accumulate GB because it lacks a functional gene for CMO. Rice plants accumulate GB in the presence of exogenously applied BA, which leads to the development of a significant tolerance to salt, cold and heat stress. The goal in this study was to evaluate and to discuss the effects of endogenously accumulated GB in rice. METHODS Transgenic rice plants that overexpressed a gene for CMO from spinach (Spinacia oleracea) were produced by Agrobacterium-mediated transformation. After Southern and western blotting analysis, GB in rice leaves was quantified by (1)H-NMR spectroscopy and the tolerance of GB-accumulating plants to abiotic stress was investigated. KEY RESULTS Transgenic plants that had a single copy of the transgene and expressed spinach CMO accumulated GB at the level of 0.29-0.43 micromol g(-1) d. wt and had enhanced tolerance to salt stress and temperature stress in the seedling stage. CONCLUSIONS In the CMO-expressing rice plants, the localization of spinach CMO and of endogenous BADHs might be different and/or the catalytic activity of spinach CMO in rice plants might be lower than it is in spinach. These possibilities might explain the low levels of GB in the transgenic rice plants. It was concluded that CMO-expressing rice plants were not effective for accumulation of GB and improvement of productivity.
Optimal titer of anti‐HBs in blood components derived from donors with anti‐HBc

The ultimate strategy to cope with transfusion‐transmitted hepatitis B virus (HBV) infection caused by transfusion of blood from donors with historical HBV infection is to reject all donors having anti‐HBV core antigen (anti‐HBc). However, this strategy would result in a huge loss of blood donors and subsequent blood inventory collapse. On the other hand, anti‐HBc–positive blood is reportedly not infectious when containing more than 100 mIU/mL of anti‐HBV surface antigen (anti‐HBs).
An RBM Anomaly Detector for the Cloud

Failures are unavoidable in complex software systems, and the intrinsic characteristics of cloud systems amplify the problem. Predicting failures before their occurrence by detecting anomalies in system metrics is a viable solution to enable failure preventing or mitigating actions. The most promising approaches for predicting failures exploit statistical analysis or machine learning to reveal anomalies and their correlation with possible failures. Statistical analysis approaches result in far too many false positives, which severely hinder their practical applicability, while accurate machine learning approaches need extensive training with seeded faults, which is often impossible in operative cloud systems. In this paper, we propose EmBeD, Energy-Based anomaly Detection in the cloud, an approach to detect anomalies at runtime based on the free energy of a Restricted Boltzmann Machine (RBM) model. The free energy is a stochastic function that can be used to efficiently score anomalies for detecting outliers. EmBeD analyzes the system behavior from raw metric data, does not require extensive training with seeded faults, and classifies the relation of anomalous behaviors with future failures with very few false positives. The experimental results presented in this paper confirm that EmBeD can precisely predict failure-prone behavior without training with seeded faults, thus overcoming the main limitations of current approaches.
arcasHLA: high-resolution HLA typing from RNAseq

Motivation Human leukocyte antigen (HLA) locus makes up the major compatibility complex (MHC) and plays a critical role in host response to disease, including cancers and autoimmune disorders. In the clinical setting, HLA typing is necessary for determining tissue compatibility. Recent improvements in the quality and accessibility of next-generation sequencing have made HLA typing from standard short-read data practical. However, this task remains challenging given the high level of polymorphism and homology between the HLA genes. HLA typing from RNA sequencing is further complicated by post-transcriptional splicing and bias due to amplification. Results Here, we present arcasHLA: a fast and accurate in silico tool that infers HLA genotypes from RNA sequencing data. Our tool outperforms established tools on the gold-standard benchmark dataset for HLA typing in terms of both accuracy and speed, with an accuracy rate of 100% at two field precision for MHC class I genes, and over 99.7% for MHC class II. Importantly, arcasHLA takes as its input pre-aligned BAM files, and outputs three-field resolution for all HLA genes in less than 2 minutes. Finally, we discuss evaluate the performance of our tool on a new biological dataset of 447 single-end total RNA samples from nasopharyngeal swabs, and establish the applicability of arcasHLA in metatranscriptome studies. Availability arcasHLA is available at https://github.com/RabadanLab/arcasHLA.
Molten Metal Hazards Monitoring and Early Warning System Based on Convolutional Neural Network

In order to ensure the safety of molten metal operation and improve the efficiency of monitoring and early warning, molten metal hazards monitoring and early warning system is proposed based on convolutional neural network algorithm. The system utilizes image recognition technology such as behavior analysis, object detection and scene recognition. It consists of five functional modules: real-time monitoring, safety inspection, safety early warning, emergency rescue and information management. Equipped with AR helmet, the system demonstrates a wide potential for application in the field of safety management.
Fournier's Gangrene: 10-Year Experience of a Plastic Surgery and Burns Department at a Tertiary Hospital.

INTRODUCTION Fournier gangrene is a polymicrobial life threatening infection of perineal subcutaneous soft tissues with its point of origin in urologic, colorectal or skin diseases. Although more frequent in elderly and men, it can affect all genders and age groups. Perianal abscess, diabetes mellitus and Escherichia coli are the most frequent cause, predisposing comorbidity, and microorganism found in tissue culture analysis respectively. The objective of this study was to describe the experience of a Plastic Surgery Department of a tertiary Hospital in reconstructing Fournier's gangrene perineal defects and its detailed demography. MATERIAL AND METHODS The sample is composed of all patients with Fournier gangrene admitted in the Plastic Surgery and Burns Department. The authors retrospectively collected and analyzed demographic and clinical data during a period of 10 years including gender, age, length of stay, cause, number of debridements, predisposing factors, microbial culture results, surgical reconstructive techniques and its associated complications, additional surgical procedures and outcomes. RESULTS Fifteen patients were identified: 14 males (93%) and one female (7%); mean age was 66.9 years (range: 46 - 86); mean, length of stay was 46.8 days (range: 20 - 71 days) and mean number of debridements was 3.3 (range: 1 - 4). The most frequent predisposing factor was diabetes mellitus, the major cause was perianal (n = 2) and skin abscess (n = 2). Eight (53.3%) patients had no identifiable source of Fournier gangrene. Various types of reconstructive techniques were employed; and 5 additional surgical interventions (33.3%) were undertaken (one cystostomy, two orchidectomy, two ileostomy); six patients (40%) presented reconstructive technique complications with adequate final outcome. DISCUSSION In contrast with the literature, where Escherichia coli was the most frequently isolated agent, Staphylococcus aureus was the most frequent microorganism found in tissue biopsy/pus collection analysis. A higher than expected number of patients (n = 8) had no identifiable source of Fournier gangrene. This findings can be explained by the retrospective non-multicentre study limitation, with a potencial source of bias patients that were transferred from other hospitals in advanced stage, without point of origin of Fournier's gangrene identified. CONCLUSION Early recognition and extensive necrotic tissue debridement, along with prompt and adequate antimicrobial treatment, are the mainstay of Fournier gangrene management, thus reducing morbidity and mortality in these patients. Surgical reconstruction challenges derived from this condition should be addressed by specialized teams due to the risk of dysfunctional sequelae and conspicuous deformities. Taking in account the single-center and retrospective observational character of the present study, these premises require proper validation from a multicenter prospective study.
Synthesis of Phase Currents of Optimal form of Synchronous Motor with Permanent Magnets

This paper examines the methods of ensuring constant electromagnetic torque for a synchronous motor with permanent magnets (PMSM) during the rotation of a rotor with arbitrary form of phase EMF-s, as well as in the event of a power failure of any motor windings phase. The non-sinusoidal shape of the EMF can be a consequence of engine design features or technological causes. A method for the optimal configuration of the PMSM phase currents ensuring electromagnetic torque consistency with minimal electrical losses is offered. The proposed approach allows expanding the scope of vector control of a synchronous motor with permanent magnets increasing reliability and survivability of the engine.
Full-Reference Video Quality Assessment Using Deep 3D Convolutional Neural Networks

We present a novel framework called Deep Video QUality Evaluator (DeepVQUE) for full-reference video quality assessment (FRVQA) using deep 3D convolutional neural networks (3D ConvNets). DeepVQUE is a complementary framework to traditional handcrafted feature based methods in that it uses deep 3D ConvNet models for feature extraction. 3D ConvNets are capable of extracting spatio-temporal features of the video which are vital for video quality assessment (VQA). Most of the existing FRVQA approaches operate on spatial and temporal domains independently followed by pooling, and often ignore the crucial spatio-temporal relationship of intensities in natural videos. In this work, we pay special attention to the contribution of spatio-temporal dependencies in natural videos to quality assessment. Specifically, the proposed approach estimates the spatio-temporal quality of a video with respect to its pristine version by applying commonly used distance measures such as the l1 or the l2 norm to the volume-wise pristine and distorted 3D ConvNet features. Spatial quality is estimated using off-the-shelf full-reference image quality assessment (FRIQA) methods. Overall video quality is estimated using support vector regression (SVR) applied to the spatio-temporal and spatial quality estimates. Additionally, we illustrate the ability of the proposed approach to localize distortions in space and time.
A New Control Method Based on DTC and MPC to Reduce Torque Ripple in SRM

This paper proposes a new control strategy to reduce torque ripple in a switched reluctance motor (SRM). The flux linkage in this paper is related to model predictive flux control (MPFC). In addition, the torque hysteresis remained in the system is similar to direct torque control (DTC) and direct instantaneous torque control (DITC). The candidate voltage vectors (VVs) are selected from the torque hysteresis and the cost function is designed for the flux linkage minimization to select the best VV from candidate VVs. The advantages, as well as the improvement prospects for these methods, are discussed in details. Performance for torque ripple in steady state and the robustness in the transient state are evaluated in this paper under the simulation and experimental results, and also the possibility and some advice for model predictive control (MPC) applied to an SRM are indicated. The experimental result for the new method is carried out on a three-phase 12/8 poles SRM with the analysis of torque ripple compared to a DTC and DITC.
At‐line multi‐angle light scattering detector for faster process development in enveloped virus‐like particle purification

Abstract At‐line static light scattering and fluorescence monitoring allows direct in‐process tracking of fluorescent virus‐like particles. We have demonstrated this by coupling at‐line multi‐angle light scattering and fluorescence detectors to the downstream processing of enveloped virus‐like particles. Since light scattering intensity is directly proportional to particle concentration, our strategy allowed a swift identification of product containing fractions and rapid process development. Virus‐like particles containing the Human Immunodeficiency Virus‐1 Gag protein fused to the Green Fluorescence protein were produced in Human Embryonic Kidney 293 cells by transient transfection. A single‐column anion‐exchange chromatography method was used for direct capture and purification. The majority of host‐cell protein impurities passed through the column without binding. Virus‐like particles bound to the column were eluted by linear or step salt gradients. Particles recovered in the step gradient purification were characterized by nanoparticle tracking analysis, size exclusion chromatography coupled to multi‐angle light scattering and fluorescence detectors and transmission electron microscopy. A total recovery of 66% for the fluorescent particles was obtained with a 50% yield in the main product peak. Virus‐like particles were concentrated 17‐fold to final a concentration of 4.45 × 1010 particles/mL. Simple buffers and operation make this process suitable for large scale purposes.
Preliminary evaluation of a self-management health app by people with cognitive impairment

Cognitive impairment is associated with increased risk of disability, increased health care costs and potential progression to dementia. An emerging approach to counteract the impact of cognitive impairment is to empower patients with the appropriate tools to effectively manage their own condition. In this work we evaluate the use of KeepWell, a self-management smartphone application developed to assist people with early cognitive impairment to live independently. KeepWell provides services such as reminders, surveys, and educational information that allows users to set physical goals and monitor their physical performance. Participants involved in the evaluation of adoption and usability consisted of individuals diagnosed with early cognitive impairment. A qualitative and quantitative analysis was conducted with 5 and 2 such individuals respectively. Data was codified using grounded theory and affinity diagramming. The findings from the work have resulted in the development of a set of recommendations for the design of self-management mobile applications.
Goal setting and control orientation of pregnant / parenting female adolescents in the GRADS program.

The Graduation, Reality, and Dual-role Skills (GRADS) home economics program helps at-risk pregnant/parenting teens graduate from high school, set life goals, and feel empowered. It was initiated in Ohio in 1980 and started in New Mexico in 1989. The authors investigated whether female GRADS students differed from nonpregnant/nonparenting female teens in terms of the types of goals they perceive to be most important, the tendency to set goals, and control orientation. Comparisons were made between 37 female GRADS students in the program for one year or more, 46 female GRADS students new to the program, and 68 nonpregnant/nonparenting female students from an English class. The data were collected during Fall 1992 from eight sites in New Mexico. Analysis of the data found the existence of significant differences regarding participants' most important goals, but no significant differences in goal orientation or locus of control among the three groups. GRADS students were highly concerned about interpersonal relationships, while the nonpregnant/nonparenting students were highly interested in personal concerns. Pregnant and/or parenting teens were more like their nonpregnant/nonparenting peers than different, with the differences in goals seeming to reflect different priorities.
An improved algorithm for three dimensional scene reconstruction

The three dimensional reconstruction (3D) technology is one of the most popular fields in computer vision. The technology can be used in science, education, medicine and archaeology. This paper mainly studies the reconstruction algorithm of 3D scene. We have sorted out the existing tools and algorithms in 3D scene reconstruction and provided improvement for the existing schemes. The quality of the depth image can be greatly improved by using a pass-through filter to reduce the noise of the sensor.