Showing papers by "Ben-Gurion University of the Negev published in 2018"

Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection.

Abstract: Neural networks have become an increasingly popular solution for network intrusion detection systems (NIDS). Their capability of learning complex patterns and behaviors make them a suitable solution for differentiating between normal traffic and network attacks. However, a drawback of neural networks is the amount of resources needed to train them. Many network gateways and routers devices, which could potentially host an NIDS, simply do not have the memory or processing power to train and sometimes even execute such models. More importantly, the existing neural network solutions are trained in a supervised manner. Meaning that an expert must label the network traffic and update the model manually from time to time. In this paper, we present Kitsune: a plug and play NIDS which can learn to detect attacks on the local network, without supervision, and in an efficient online manner. Kitsune's core algorithm (KitNET) uses an ensemble of neural networks called autoencoders to collectively differentiate between normal and abnormal traffic patterns. KitNET is supported by a feature extraction framework which efficiently tracks the patterns of every network channel. Our evaluations show that Kitsune can detect various attacks with a performance comparable to offline anomaly detectors, even on a Raspberry PI. This demonstrates that Kitsune can be a practical and economic NIDS.

Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics.

Abstract: Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes.

N-BaIoT—Network-Based Detection of IoT Botnet Attacks Using Deep Autoencoders

Abstract: The proliferation of IoT devices that can be more easily compromised than desktop computers has led to an increase in IoT-based botnet attacks. To mitigate this threat, there is a need for new methods that detect attacks launched from compromised IoT devices and that differentiate between hours- and milliseconds-long IoT-based attacks. In this article, we propose a novel network-based anomaly detection method for the IoT called N-BaIoT that extracts behavior snapshots of the network and uses deep autoencoders to detect anomalous network traffic from compromised IoT devices. To evaluate our method, we infected nine commercial IoT devices in our lab with two widely known IoT-based botnets, Mirai and BASHLITE. The evaluation results demonstrated our proposed methods ability to accurately and instantly detect the attacks as they were being launched from the compromised IoT devices that were part of a botnet.

Laser-Induced Graphene by Multiple Lasing: Toward Electronics on Cloth, Paper, and Food

Abstract: A simple and facile method for obtaining patterned graphene under ambient conditions on the surface of diverse materials ranging from renewable precursors such as food, cloth, paper, and cardboard to high-performance polymers like Kevlar or even on natural coal would be highly desirable. Here, we report a method of using multiple pulsed-laser scribing to convert a wide range of substrates into laser-induced graphene (LIG). With the increased versatility of the multiple lase process, highly conductive patterns can be achieved on the surface of a diverse number of substrates in ambient atmosphere. The use of a defocus method results in multiple lases in a single pass of the laser, further simplifying the procedure. This method can be implemented without increasing processing times when compared with laser induction of graphene on polyimide (Kapton) substrates as previously reported. In fact, any carbon precursor that can be converted into amorphous carbon can be converted into graphene using this multiple l...

Human Ageing Genomic Resources: new and updated databases.

Abstract: In spite of a growing body of research and data, human ageing remains a poorly understood process. Over 10 years ago we developed the Human Ageing Genomic Resources (HAGR), a collection of databases and tools for studying the biology and genetics of ageing. Here, we present HAGR's main functionalities, highlighting new additions and improvements. HAGR consists of six core databases: (i) the GenAge database of ageing-related genes, in turn composed of a dataset of >300 human ageing-related genes and a dataset with >2000 genes associated with ageing or longevity in model organisms; (ii) the AnAge database of animal ageing and longevity, featuring >4000 species; (iii) the GenDR database with >200 genes associated with the life-extending effects of dietary restriction; (iv) the LongevityMap database of human genetic association studies of longevity with >500 entries; (v) the DrugAge database with >400 ageing or longevity-associated drugs or compounds; (vi) the CellAge database with >200 genes associated with cell senescence. All our databases are manually curated by experts and regularly updated to ensure a high quality data. Cross-links across our databases and to external resources help researchers locate and integrate relevant information. HAGR is freely available online (http://genomics.senescence.info/).

From Surface ZrO2 Coating to Bulk Zr Doping by High Temperature Annealing of Nickel-Rich Lithiated Oxides and Their Enhanced Electrochemical Performance in Lithium Ion Batteries

Abstract: One of the major hurdles of Ni-rich cathode materials Li1+x(NixCozMnz)wO2, y > 0.5 for lithium-ion batteries is their low cycling stability especially for compositions with Ni ≥ 60%, which suffer from severe capacity fading and impedance increase during cycling at elevated temperatures (e.g., 45 °C). Two promising surface and structural modifications of these materials to alleviate the above drawback are (1) coatings by electrochemically inert inorganic compounds (e.g., ZrO2) or (2) lattice doping by cations like Zr4+, Al3+, Mg2+, etc. This paper demonstrates the enhanced electrochemical behavior of Ni-rich material LiNi0.8Co0.1Mn0.1O2 (NCM811) coated with a thin ZrO2 layer. The coating is produced by an easy and scalable wet chemical approach followed by annealing the material at ≥700 °C under oxygen that results in Zr doping. It is established that some ZrO2 remains even after annealing at ≥800 °C as a surface layer on NCM811. The main finding of this work is the enhanced cycling stability and lower impedance of the coated/doped NCM811 that can be attributed to a synergetic effect of the ZrO2 coating in combination with a zirconium doping.

Crop pests and predators exhibit inconsistent responses to surrounding landscape composition

Abstract: The idea that noncrop habitat enhances pest control and represents a win-win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win-win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies.

Millimeter Wave Communication: A Comprehensive Survey

Abstract: Millimeter wave (mmWave) communication has raised increasing attentions from both academia and industry due to its exceptional advantages. Compared with existing wireless communication techniques, such as WiFi and 4G, mmWave communications adopt much higher carrier frequencies and thus come with advantages including huge bandwidth, narrow beam, high transmission quality, and strong detection ability. These advantages can well address difficult situations caused by recent popular applications using wireless technologies. For example, mmWave communications can significantly alleviate the skyrocketing traffic demand of wireless communication from video streaming. Meanwhile, mmWave communications have several natural disadvantages, e.g., severe signal attenuation, easily blocked by obstacles, and small coverage, due to its short wavelengths. Hence, the major challenge is how to overcome its shortcomings while fully utilizing its advantages. In this paper, we present a taxonomy based on the layered model and give an extensive review on mmWave communications. Specially, we divide existing efforts into four categories that investigate: physical layer, medium access control (MAC) layer, network layer, and cross layer optimization, respectively. First, we present an overview of some technical details in physical layer. Second, we summarize available literature in MAC layer that pertains to protocols and scheduling schemes. Third, we make an in-depth survey of related research work in network layer, providing brain storming and methodology for enhancing the capacity and coverage of mmWave networks. Fourth, we analyze available research work related to cross layer allocation/optimization for mmWave communications. Fifth, we make a review of mmWave applications to illustrate how mmWave technology can be employed to satisfy other services. At the end of each section described above, we point out the inadequacy of existing work and identify the future work. Sixth, we present some available resources for mmWave communications, including related books about mmWave, commonly used mmWave frequencies, existing protocols based on mmWave, and experimental platforms. Finally, we have a simple summary and point out several promising future research directions.

Concussion, microvascular injury, and early tauopathy in young athletes after impact head injury and an impact concussion mouse model.

Abstract: The mechanisms underpinning concussion, traumatic brain injury, and chronic traumatic encephalopathy, and the relationships between these disorders, are poorly understood. We examined post-mortem brains from teenage athletes in the acute-subacute period after mild closed-head impact injury and found astrocytosis, myelinated axonopathy, microvascular injury, perivascular neuroinflammation, and phosphorylated tau protein pathology. To investigate causal mechanisms, we developed a mouse model of lateral closed-head impact injury that uses momentum transfer to induce traumatic head acceleration. Unanaesthetized mice subjected to unilateral impact exhibited abrupt onset, transient course, and rapid resolution of a concussion-like syndrome characterized by altered arousal, contralateral hemiparesis, truncal ataxia, locomotor and balance impairments, and neurobehavioural deficits. Experimental impact injury was associated with axonopathy, blood-brain barrier disruption, astrocytosis, microgliosis (with activation of triggering receptor expressed on myeloid cells, TREM2), monocyte infiltration, and phosphorylated tauopathy in cerebral cortex ipsilateral and subjacent to impact. Phosphorylated tauopathy was detected in ipsilateral axons by 24 h, bilateral axons and soma by 2 weeks, and distant cortex bilaterally at 5.5 months post-injury. Impact pathologies co-localized with serum albumin extravasation in the brain that was diagnostically detectable in living mice by dynamic contrast-enhanced MRI. These pathologies were also accompanied by early, persistent, and bilateral impairment in axonal conduction velocity in the hippocampus and defective long-term potentiation of synaptic neurotransmission in the medial prefrontal cortex, brain regions distant from acute brain injury. Surprisingly, acute neurobehavioural deficits at the time of injury did not correlate with blood-brain barrier disruption, microgliosis, neuroinflammation, phosphorylated tauopathy, or electrophysiological dysfunction. Furthermore, concussion-like deficits were observed after impact injury, but not after blast exposure under experimental conditions matched for head kinematics. Computational modelling showed that impact injury generated focal point loading on the head and seven-fold greater peak shear stress in the brain compared to blast exposure. Moreover, intracerebral shear stress peaked before onset of gross head motion. By comparison, blast induced distributed force loading on the head and diffuse, lower magnitude shear stress in the brain. We conclude that force loading mechanics at the time of injury shape acute neurobehavioural responses, structural brain damage, and neuropathological sequelae triggered by neurotrauma. These results indicate that closed-head impact injuries, independent of concussive signs, can induce traumatic brain injury as well as early pathologies and functional sequelae associated with chronic traumatic encephalopathy. These results also shed light on the origins of concussion and relationship to traumatic brain injury and its aftermath.awx350media15713427811001.

Recurrent Implantation Failure-update overview on etiology, diagnosis, treatment and future directions

Abstract: Recurrent implantation failure (RIF) refers to cases in which women have had three failed in vitro fertilization (IVF) attempts with good quality embryos. The definition should also take advanced maternal age and embryo stage into consideration. The failure of embryo implantation can be a consequence of uterine, male, or embryo factors, or the specific type of IVF protocol. These cases should be investigated to determine the most likely etiologies of the condition, as this is a complex problem with several variables. There are multiple risk factors for recurrent implantation failure including advanced maternal age, smoking status of both parents, elevated body mass index, and stress levels. Immunological factors such as cytokine levels and presence of specific autoantibodies should be examined, as well as any infectious organisms in the uterus leading to chronic endometritis. Uterine pathologies such as polyps and myomas as well as congenital anatomical anomalies should be ruled out. Sperm analysis, pre-implantation genetic screening and endometrial receptivity should be considered and evaluated, and IVF protocols should be tailored to specific patients or patient populations. Treatment approaches should be directed toward individual patient cases. In addition, we suggest considering a new initial step in approach to patients with RIF, individualized planned activities to activate the brain's reward system in attempt to improve immunological balance in the body.

Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT: A Multicenter Study

Abstract: Objectives The study evaluated the automatic prediction of obstructive disease from myocardial perfusion imaging (MPI) by deep learning as compared with total perfusion deficit (TPD). Background Deep convolutional neural networks trained with a large multicenter population may provide improved prediction of per-patient and per-vessel coronary artery disease from single-photon emission computed tomography MPI. Methods A total of 1,638 patients (67% men) without known coronary artery disease, undergoing stress 99mTc-sestamibi or tetrofosmin MPI with new generation solid-state scanners in 9 different sites, with invasive coronary angiography performed within 6 months of MPI, were studied. Obstructive disease was defined as ≥70% narrowing of coronary arteries (≥50% for left main artery). Left ventricular myocardium was segmented using clinical nuclear cardiology software and verified by an expert reader. Stress TPD was computed using sex- and camera-specific normal limits. Deep learning was trained using raw and quantitative polar maps and evaluated for prediction of obstructive stenosis in a stratified 10-fold cross-validation procedure. Results A total of 1,018 (62%) patients and 1,797 of 4,914 (37%) arteries had obstructive disease. Area under the receiver-operating characteristic curve for disease prediction by deep learning was higher than for TPD (per patient: 0.80 vs. 0.78; per vessel: 0.76 vs. 0.73: p Conclusions Deep learning has the potential to improve automatic interpretation of MPI as compared with current clinical methods.

Detecting Cyber Attacks in Industrial Control Systems Using Convolutional Neural Networks

Abstract: This paper presents a study on detecting cyber attacks on industrial control systems (ICS) using convolutional neural networks. The study was performed on a Secure Water Treatment testbed (SWaT) dataset, which represents a scaled-down version of a real-world industrial water treatment plant. We suggest a method for anomaly detection based on measuring the statistical deviation of the predicted value from the observed value. We applied the proposed method by using a variety of deep neural network architectures including different variants of convolutional and recurrent networks. The test dataset included 36 different cyber attacks. The proposed method successfully detected 31 attacks with three false positives thus improving on previous research based on this dataset. The results of the study show that 1D convolutional networks can be successfully used for anomaly detection in industrial control systems and outperform recurrent networks in this setting. The findings also suggest that 1D convolutional networks are effective at time series prediction tasks which are traditionally considered to be best solved using recurrent neural networks. This observation is a promising one, as 1D convolutional neural networks are simpler, smaller, and faster than the recurrent neural networks.

Dioxygen in Polyoxometalate Mediated Reactions

Abstract: In this review article, we consider the use of molecular oxygen in reactions mediated by polyoxometalates. Polyoxometalates are anionic metal oxide clusters of a variety of structures that are soluble in liquid phases and therefore amenable to homogeneous catalytic transformations. Often, they are active for electron transfer oxidations of a myriad of substrates and upon reduction can be reoxidized by molecular oxygen. For example, the phosphovanadomolybdate, H5PV2Mo10O40, can oxidize Pd(0) thereby enabling aerobic reactions catalyzed by Pd and H5PV2Mo10O40. In a similar vein, polyoxometalates can stabilize metal nanoparticles, leading to additional transformations. Furthermore, electron transfer oxidation of other substrates such as halides and sulfur-containing compounds is possible. More uniquely, H5PV2Mo10O40 and its analogues can mediate electron transfer-oxygen transfer reactions where oxygen atoms are transferred from the polyoxometalate to the substrate. This unique property has enabled correspond...

γδ T cells producing interleukin-17A regulate adipose regulatory T cell homeostasis and thermogenesis.

Abstract: γδ T cells are situated at barrier sites and guard the body from infection and damage. However, little is known about their roles outside of host defense in nonbarrier tissues. Here, we characterize a highly enriched tissue-resident population of γδ T cells in adipose tissue that regulate age-dependent regulatory T cell (Treg) expansion and control core body temperature in response to environmental fluctuations. Mechanistically, innate PLZF+ γδ T cells produced tumor necrosis factor and interleukin (IL) 17 A and determined PDGFRα+ and Pdpn+ stromal-cell production of IL-33 in adipose tissue. Mice lacking γδ T cells or IL-17A exhibited decreases in both ST2+ Treg cells and IL-33 abundance in visceral adipose tissue. Remarkably, these mice also lacked the ability to regulate core body temperature at thermoneutrality and after cold challenge. Together, these findings uncover important physiological roles for resident γδ T cells in adipose tissue immune homeostasis and body-temperature control.

Addressing global ruminant agricultural challenges through understanding the rumen microbiome: past, present and future

Abstract: The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security As the world population is predicted to reach approximately 97 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in "omic" data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies Advances in computational tools, high-throughput sequencing technologies and cultivation-independent "omics" approaches continue to revolutionize our understanding of the rumen microbiome This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges

chewBBACA: A complete suite for gene-by-gene schema creation and strain identification.

Abstract: Gene-by-gene approaches are becoming increasingly popular in bacterial genomic epidemiology and outbreak detection. However, there is a lack of open-source scalable software for schema definition and allele calling for these methodologies. The chewBBACA suite was designed to assist users in the creation and evaluation of novel whole-genome or core-genome gene-by-gene typing schemas and subsequent allele calling in bacterial strains of interest. chewBBACA performs the schema creation and allele calls on complete or draft genomes resulting from de novo assemblers. The chewBBACA software uses Python 3.4 or higher and can run on a laptop or in high performance clusters making it useful for both small laboratories and large reference centers. ChewBBACA is available at https://github.com/B-UMMI/chewBBACA.

Adolescent Tuning of Association Cortex in Human Structural Brain Networks.

Abstract: Motivated by prior data on local cortical shrinkage and intracortical myelination, we predicted age-related changes in topological organization of cortical structural networks during adolescence. We estimated structural correlation from magnetic resonance imaging measures of cortical thickness at 308 regions in a sample of N = 297 healthy participants, aged 14-24 years. We used a novel sliding-window analysis to measure age-related changes in network attributes globally, locally and in the context of several community partitions of the network. We found that the strength of structural correlation generally decreased as a function of age. Association cortical regions demonstrated a sharp decrease in nodal degree (hubness) from 14 years, reaching a minimum at approximately 19 years, and then levelling off or even slightly increasing until 24 years. Greater and more prolonged age-related changes in degree of cortical regions within the brain network were associated with faster rates of adolescent cortical myelination and shrinkage. The brain regions that demonstrated the greatest age-related changes were concentrated within prefrontal modules. We conclude that human adolescence is associated with biologically plausible changes in structural imaging markers of brain network organization, consistent with the concept of tuning or consolidating anatomical connectivity between frontal cortex and the rest of the connectome.

Sulfur-Doped Laser-Induced Porous Graphene Derived from Polysulfone-Class Polymers and Membranes

Abstract: Graphene based materials have profoundly impacted research in nanotechnology, and this has significantly advanced biomedical, electronics, energy, and environmental applications. Laser-induced graphene (LIG) is made photothermally and has enabled a rapid route for graphene layers on polyimide surfaces. However, polysulfone (PSU), poly(ether sulfone) (PES), and polyphenylsulfone (PPSU) are highly used in numerous applications including medical, energy, and water treatment and they are critical components of polymer membranes. Here we show LIG fabrication on PSU, PES, and PPSU resulting in conformal sulfur-doped porous graphene embedded in polymer dense films or porous substrates using reagent- and solvent-free methods in a single step. We demonstrate the applicability as flexible electrodes with enhanced electrocatalytic hydrogen peroxide generation, as antifouling surfaces and as antimicrobial hybrid membrane-LIG porous filters. The properties and surface morphology of the conductive PSU-, PES-, and PPSU-...

Association of Bariatric Surgery Using Laparoscopic Banding, Roux-en-Y Gastric Bypass, or Laparoscopic Sleeve Gastrectomy vs Usual Care Obesity Management With All-Cause Mortality.

Abstract: Importance Bariatric surgery is an effective and safe approach for weight loss and short-term improvement in metabolic disorders such as diabetes. However, studies have been limited in most settings by lack of a nonsurgical group, losses to follow-up, missing data, and small sample sizes in clinical trials and observational studies. Objective To assess the association of 3 common types of bariatric surgery compared with nonsurgical treatment with mortality and other clinical outcomes among obese patients. Design, Setting, and Participants Retrospective cohort study in a large Israeli integrated health fund covering 54% of Israeli citizens with less than 1% turnover of members annually. Obese adult patients who underwent bariatric surgery between January 1, 2005, and December 31, 2014, were selected and compared with obese nonsurgical patients matched on age, sex, body mass index (BMI), and diabetes, with a final follow-up date of December 31, 2015. A total of 33 540 patients were included in this study. Exposures Bariatric surgery (laparoscopic banding, Roux-en-Y gastric bypass, or laparoscopic sleeve gastrectomy) or usual care obesity management only (provided by a primary care physician and which may include dietary counseling and behavior modification). Main Outcomes and Measures The primary outcome, all-cause mortality, matched and adjusted for BMI prior to surgery, age, sex, socioeconomic status, diabetes, hyperlipidemia, hypertension, cardiovascular disease, and smoking. Results The study population included 8385 patients who underwent bariatric surgery (median age, 46 [IQR, 37-54] years; 5490 [65.5%] women; baseline median BMI, 40.6 [IQR, 38.5-43.7]; laparoscopic banding [n = 3635], gastric bypass [n = 1388], laparoscopic sleeve gastrectomy [n = 3362], and 25 155 nonsurgical matched patients (median age, 46 [IQR, 37-54] years; 16 470 [65.5%] women; baseline median BMI, 40.5 [IQR, 37.0-43.5]). The availability of follow-up data was 100% for all-cause mortality. There were 105 deaths (1.3%) among surgical patients during a median follow-up of 4.3 (IQR, 2.8-6.6) years (including 61 [1.7%] who underwent laparoscopic banding, 18 [1.3%] gastric bypass, and 26 [0.8%] sleeve gastrectomy), and 583 deaths (2.3%) among nonsurgical patients during a median follow-up of 4.0 (IQR, 2.6-6.2) years. The absolute difference was 2.51 (95% CI, 1.86-3.15) fewer deaths/1000 person-years in the surgical vs nonsurgical group. Adjusted hazard ratios (HRs) for mortality among nonsurgical vs surgical patients were 2.02 (95% CI, 1.63-2.52) for the entire study population; by surgical type, HRs were 2.01 (95% CI, 1.50-2.69) for laparoscopic banding, 2.65 (95% CI, 1.55-4.52) for gastric bypass, and 1.60 (95% CI, 1.02-2.51) for laparoscopic sleeve gastrectomy. Conclusions and Relevance Among obese patients in a large integrated health fund in Israel, bariatric surgery using laparoscopic banding, gastric bypass, or laparoscopic sleeve gastrectomy, compared with usual care nonsurgical obesity management, was associated with lower all-cause mortality over a median follow-up of approximately 4.5 years. The evidence of this association adds to the limited literature describing beneficial outcomes of these 3 types of bariatric surgery compared with usual care obesity management alone.

On the effect of shot-peening on fatigue resistance of AlSi10Mg specimens fabricated by additive manufacturing using selective laser melting (AM-SLM)

Abstract: The effect on fatigue resistance of additively manufactured (AM) AlSi10Mg specimens fabricated by selective laser melting (SLM) following surface treatment by shot-peening was investigated. Specimen surface was shot-peened with either steel or ceramic balls. Nano-indentation measurements revealed that shot-peening caused surface hardening, with the hardness profile from the surface to the interior of the bulk disappearing 50 μm below the surface. Surfaces polished before shot-peening or following removal of about 25–30 μm from the surface after shot-peening by either mechanical or electrolytic polishing showed improved fatigue resistance and fatigue limit. Fractography of broken specimens demonstrated that for shot-peened specimens, the site of fatigue crack initiation was deeper than that for specimens that had not undergone shot-peening. The fracture area of AM-SLM AlSi10Mg specimens before and after shot-peening displayed a ductile fracture with relatively deep dimples. In contrast to AM specimens, the final fracture area of die-cast samples exhibited a brittle fracture surface, containing numerous cleavage facets and micro-cracks.

Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development.

Abstract: While substantial effort has been invested in making robots more reliable, experience demonstrates that robots operating in unstructured environments are often challenged by frequent failures. Despite this, robots have not yet reached a level of design that allows effective management of faulty or unexpected behavior by untrained users. To understand why this may be the case, an in-depth literature review was done to explore when people perceive and resolve robot failures, how robots communicate failure, how failures influence people's perceptions and feelings toward robots, and how these effects can be mitigated. Fifty-two studies were identified relating to communicating failures and their causes, the influence of failures on human-robot interaction (HRI), and mitigating failures. Since little research has been done on these topics within the HRI community, insights from the fields of human computer interaction (HCI), human factors engineering, cognitive engineering and experimental psychology are presented and discussed. Based on the literature, we developed a model of information processing for robotic failures (Robot Failure Human Information Processing, RF-HIP), that guides the discussion of our findings. The model describes the way people perceive, process, and act on failures in human robot interaction. The model includes three main parts: (1) communicating failures, (2) perception and comprehension of failures, and (3) solving failures. Each part contains several stages, all influenced by contextual considerations and mitigation strategies. Several gaps in the literature have become evident as a result of this evaluation. More focus has been given to technical failures than interaction failures. Few studies focused on human errors, on communicating failures, or the cognitive, psychological, and social determinants that impact the design of mitigation strategies. By providing the stages of human information processing, RF-HIP can be used as a tool to promote the development of user-centered failure-handling strategies for HRIs.

A Serological Point-of-Care Test for the Detection of IgG Antibodies against Ebola Virus in Human Survivors

Abstract: Ebola virus disease causes widespread and highly fatal epidemics in human populations. Today, there is still great need for point-of-care tests for diagnosis, patient management and surveillance, both during and post outbreaks. We present a point-of-care test comprising an immunochromatographic strip and a smartphone reader, which detects and semiquantifies Ebola-specific antibodies in human survivors. We developed a Sudan virus glycoprotein monoplex platform and validated it using sera from 90 human survivors and 31 local noninfected controls. The performance of the glycoprotein monoplex was 100% sensitivity and 98% specificity compared to standard whole antigen enzyme-linked immunosorbent assay (ELISA), and it was validated with freshly collected patient samples in Uganda. Moreover, we constructed a multiplex test for simultaneous detection of antibodies against three recombinant Sudan virus proteins. A pilot study comprising 15 survivors and 5 noninfected controls demonstrated sensitivity and specifici...

Generic Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers

Abstract: In this paper, we present a black-box attack against API call based machine learning malware classifiers, focusing on generating adversarial sequences combining API calls and static features (e.g., printable strings) that will be misclassified by the classifier without affecting the malware functionality. We show that this attack is effective against many classifiers due to the transferability principle between RNN variants, feed forward DNNs, and traditional machine learning classifiers such as SVM. We also implement GADGET, a software framework to convert any malware binary to a binary undetected by malware classifiers, using the proposed attack, without access to the malware source code.

Antifungal Activity of Bacillus Species Against Fusarium and Analysis of the Potential Mechanisms Used in Biocontrol.

Abstract: Fusarium is a complex genus of ascomycete fungi that consists of plant pathogens of agricultural relevance. Controlling Fusarium infection in crops that leads to substantial yield losses is challenging. These economic losses along with environmental and human health concerns over the usage of chemicals in attaining disease control are shifting focus toward the use of biocontrol agents for effective control of phytopathogenic Fusarium spp. In the present study, an analysis of the plant-growth promoting (PGP) and biocontrol attributes of four bacilli (Bacillus simplex 30N-5, B. simplex 11, B. simplex 237, and B. subtilis 30VD-1) has been conducted. The production of cellulase, xylanase, pectinase, and chitinase in functional assays was studied, followed by in silico gene analysis of the PGP-related and biocontrol-associated genes. Of all the bacilli included in this study, B. subtilis 30VD-1 (30VD-1) demonstrated the most effective antagonism against Fusarium spp. under in vitro conditions. Additionally, 100 μg/ml of the crude 1-butanol extract of 30VD-1's cell-free culture filtrate caused about 40% inhibition in radial growth of Fusarium spp. Pea seed bacterization with 30VD-1 led to considerable reduction in wilt severity in plants with about 35% increase in dry plant biomass over uninoculated plants growing in Fusarium-infested soil. Phase contrast microscopy demonstrated distortions and abnormal swellings in F. oxysporum hyphae on co-culturing with 30VD-1. The results suggest a multivariate mode of antagonism of 30VD-1 against phytopathogenic Fusarium spp., by producing chitinase, volatiles, and other antifungal molecules, the characterization of which is underway.