Miracle-dz/UniFAR-FTUs huggingface dataset:
A Sink-driven Approach to Detecting Exposed Component Vulnerabilities in Android Apps

Android apps could expose their components for cooperating with other apps. This convenience, however, makes apps susceptible to the exposed component vulnerability (ECV), in which a dangerous API (commonly known as sink) inside its component can be triggered by other (malicious) apps. In the prior works, detecting these ECVs use a set of sinks pertaining to the ECVs under detection. In this paper, we argue that a more comprehensive and effective approach should start by a systematic selection and classification of vulnerability-specific sinks (VSinks). The set of VSinks is much larger than those used in the previous works. Based on these VSinks, our sink-driven approach can detect different kinds of ECVs in an app in two steps. First, VSinks and their categories are identified through a typical forward reachability analysis. Second, based on each VSink's category, a corresponding detection method is used to identify the ECV via a customized backward dataflow analysis. We also design a semi-auto guided analysis and validation capability for system-only broadcast checking to remove some false positives. We implement our sink-driven approach in a tool called ECVDetector and evaluate it with the top 1K Android apps. Using ECVDetector we successfully identify a total of 49 vulnerable apps across all four ECV categories we have defined. To our knowledge, most of them are previously undisclosed, such as the very popular Go SMS Pro and Clean Master. Moreover, the performance of ECVDetector is high, requiring only 9.257 seconds on average to process each component.
Human Mu Opioid Receptor (OPRM1 A118G) polymorphism is associated with brain mu-opioid receptor binding potential in smokers

Evidence points to the endogenous opioid system, and the mu-opioid receptor (MOR) in particular, in mediating the rewarding effects of drugs of abuse, including nicotine. A single nucleotide polymorphism (SNP) in the human MOR gene (OPRM1 A118G) has been shown to alter receptor protein level in preclinical models and smoking behavior in humans. To clarify the underlying mechanisms for these associations, we conducted an in vivo investigation of the effects of OPRM1 A118G genotype on MOR binding potential (BPND or receptor availability). Twenty-two smokers prescreened for genotype (12 A/A, 10 */G) completed two [11C]carfentanil positron emission tomography (PET) imaging sessions following overnight abstinence and exposure to a nicotine-containing cigarette and a denicotinized cigarette. Independent of session, smokers homozygous for the wild-type OPRM1 A allele exhibited significantly higher levels of MOR BPND than smokers carrying the G allele in bilateral amygdala, left thalamus, and left anterior cingulate cortex. Among G allele carriers, the extent of subjective reward difference (denicotinized versus nicotine cigarette) was associated significantly with MOR BPND difference in right amygdala, caudate, anterior cingulate cortex, and thalamus. Future translational investigations can elucidate the role of MORs in nicotine addiction, which may lead to development of novel therapeutics.
Modification of Evolutionary Multiobjective Optimization Algorithms for Multiobjective Design of Fuzzy Rule-Based Classification Systems

We examine three methods for improving the ability of evolutionary multiobjective optimization (EMO) algorithms to find a variety of fuzzy rule-based classification systems with different tradeoffs with respect to their accuracy and complexity. The accuracy of each fuzzy rule-based classification system is measured by the number of correctly classified training patterns while its complexity is measured by the number of fuzzy rules and the total number of antecedent conditions. One method for improving the search ability of EMO algorithms is to remove overlapping rule sets in the three-dimensional objective space. Another method is to choose similar rule sets as parents for crossover operations. The other method is to bias the selection probability of parents toward rule sets with high accuracy. The effectiveness of each method is examined through computational experiments on benchmark data sets
Spatial/Frontal QRS-T Angle Predicts All-Cause Mortality and Cardiac Mortality: A Meta-Analysis

Background A number of studies have assessed the predictive effect of QRS-T angles in various populations since the last decade. The objective of this meta-analysis was to evaluate the prognostic value of spatial/frontal QRS-T angle on all-cause death and cardiac death. Methods PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials were searched from their inception until June 5, 2014. Studies reporting the predictive effect of spatial/frontal QRS-T angle on all-cause/cardiac death in all populations were included. Relative risk (RR) was used as a measure of effect. Results Twenty-two studies enrolling 164,171 individuals were included. In the combined analysis in all populations, a wide spatial QRS-T angle was associated with an increase in all-cause death (maximum-adjusted RR: 1.40; 95% confidence interval [CI]: 1.32 to 1.48) and cardiac death (maximum-adjusted RR: 1.71; 95% CI: 1.54 to 1.90), a wide frontal QRS-T angle also predicted a higher rate of all-cause death (maximum-adjusted RR: 1.71; 95% CI: 1.54 to 1.90). Largely similar results were found using different methods of categorizing for QRS-T angles, and similar in subgroup populations such as general population, populations with suspected coronary heart disease or heart failure. Other stratified analyses and meta-analyses using unadjusted data also generated consistent findings. Conclusions Spatial QRS-T angle held promising prognostic value on all-cause death and cardiac death. Frontal QRS-T angle was also a promising predictor of all-cause death. Given the good predictive value of QRS-T angle, a combined stratification strategy in which QRS-T angle is of vital importance might be expected.
A Pharmacological Screening Approach for Discovery of Neuroprotective Compounds in Ischemic Stroke

With the availability and ease of small molecule production and design continuing to improve, robust, high-throughput methods for screening are increasingly necessary to find pharmacologically relevant compounds amongst the masses of potential candidates. Here, we demonstrate that a primary oxygen glucose deprivation assay in primary cortical neurons followed by secondary assays (i.e. post-treatment protocol in organotypic hippocampal slice cultures and cortical neurons) can be used as a robust screen to identify neuroprotective compounds with potential therapeutic efficacy. In our screen about 50% of the compounds in a library of pharmacologically active compounds displayed some degree of neuroprotective activity if tested in a pre-treatment toxicity assay but just a few of these compounds, including Carbenoxolone, remained active when tested in a post-treatment protocol. When further examined, Carbenoxolone also led to a significant reduction in infarction size and neuronal damage in the ischemic penumbra when administered six hours post middle cerebral artery occlusion in rats. Pharmacological testing of Carbenoxolone-related compounds, acting by inhibition of 11-β-hydroxysteroid dehydrogenase-1 (11β-HSD1), gave rise to similarly potent in vivo neuroprotection. This indicates that the increase of intracellular glucocorticoid levels mediated by 11β-HSD1 may be involved in the mechanism that exacerbates ischemic neuronal cell death, and inhibiting this enzyme could have potential therapeutic value for neuroprotective therapies in ischemic stroke and other neurodegenerative disorders associated with neuronal injury.
The walk is never random: subtle landscape effects shape gene flow in a continuous white‐tailed deer population in the Midwestern United States

One of the pervasive challenges in landscape genetics is detecting gene flow patterns within continuous populations of highly mobile wildlife. Understanding population genetic structure within a continuous population can give insights into social structure, movement across the landscape and contact between populations, which influence ecological interactions, reproductive dynamics or pathogen transmission. We investigated the genetic structure of a large population of deer spanning the area of Wisconsin and Illinois, USA, affected by chronic wasting disease. We combined multiscale investigation, landscape genetic techniques and spatial statistical modelling to address the complex questions of landscape factors influencing population structure. We sampled over 2000 deer and used spatial autocorrelation and a spatial principal components analysis to describe the population genetic structure. We evaluated landscape effects on this pattern using a spatial autoregressive model within a model selection framework to test alternative hypotheses about gene flow. We found high levels of genetic connectivity, with gradients of variation across the large continuous population of white‐tailed deer. At the fine scale, spatial clustering of related animals was correlated with the amount and arrangement of forested habitat. At the broader scale, impediments to dispersal were important to shaping genetic connectivity within the population. We found significant barrier effects of individual state and interstate highways and rivers. Our results offer an important understanding of deer biology and movement that will help inform the management of this species in an area where overabundance and disease spread are primary concerns.
Autonomous Forest Vehicles: Historic, envisioned, and state-of-the-art

Abstract The feasibility of using autonomous forest vehicles (which can be regarded as logical developments in the ongoing automation of forest machines), the systems that could be applied in them, their potential advantages and limitations (in the foreseeable future) are considered in this paper. The goals were to analyze: 1) the factors influencing the degree of automation in logging; 2) the technical principles that can be applied to autonomous forest machines, and 3) the feasibility of developing an autonomous path-tracking forest vehicle. A type of vehicle that is believed to have considerable commercial potential is an autonomous forwarder. The degree of automation is influenced by increased productivity, the machine operator as a bottle-neck, cost reduction, and environmental aspects. Technical principles that can be applied to autonomous forest vehicles are satellite navigation, wheel odometry, laser scanner, and radar. A new path-tracking algorithm has been developed to reduce deviations from the desired path by utilizing the driver’s steering commands. The presented system has demonstrated both possibilities and difficulties associated with autonomous forest machines. A field study has shown that it is quite possible for them to learn and track a path previously demonstrated by an operator with an accuracy of 0.1 m on flat ground and also to detect and avoid unexpected obstacles. Although the forest machine safely avoids obstacles, the study shows that further research in the field of obstacle avoidance is needed to optimize performance and ensure safe operation in a real forest environment.
Characterization of the Mouse and Human Monoacylglycerol O-Acyltransferase 1 (Mogat1) Promoter in Human Kidney Proximal Tubule and Rat Liver Cells

Monoacylglycerol acyltransferase 1 (Mogat1) catalyzes the conversion of monoacylglycerols (MAG) to diacylglycerols (DAG), the precursor of several physiologically important lipids such as phosphatidylcholine, phosphatidylethanolamine and triacylglycerol (TAG). Expression of Mogat1 is tissue restricted and it is highly expressed in the kidney, stomach and adipose tissue but minimally in the normal adult liver. To understand the transcriptional regulation of Mogat1, we characterized the mouse and human Mogat1 promoters in human kidney proximal tubule-2 (HK-2) cells. In-silico analysis revealed several peroxisome proliferator response element (PPRE) binding sites in the promoters of both human and mouse Mogat1. These sites responded to all three peroxisome proliferator activated receptor (PPAR) isoforms such that their respective agonist or antagonist activated or inhibited the expression of Mogat1. PPRE site mutagenesis revealed that sites located at -592 and -2518 are very effective in decreasing luciferase reporter gene activity. Chromatin immunoprecipitation (ChIP) assay using PPARα antibody further confirmed the occupancy of these sites by PPARα. While these assays revealed the core promoter elements necessary for Mogat1 expression, there are additional elements required to regulate its tissue specific expression. Chromosome conformation capture (3C) assay revealed additional cis-elements located ~10–15 kb upstream which interact with the core promoter. These chromosomal regions are responsive to both PPARα agonist and antagonist.
Probabilistic Kernel Combination for Hierarchical Object Categorization

Recognition of general visual categories requires a diverse set of feature types, but not all are equally relevant to individual categories; efficient recognition arises by learning the potentially sparse features for each class and understanding the relationship between features common to related classes. This paper describes hierarchical discriminative probabilistic techniques for learning visual object category models. Our method recovers a nested set of object categories with chosen kernel combinations for discrimination at each level of the tree. We use a Gaussian Process based framework, with a parameterized sparsity penalty to favor compact classification hierarchies. We exploit structural properties of Gaussian Processes in a multi-class setting to gain computational efficiency and employ evidence maximization to optimally infer kernel weights from training data. Experiments on benchmark datasets show that our hierarchical probabilistic kernel combination scheme offers a benefit in both computational efficiency and performance: we report a significant improvement in accuracy compared to the current best whole-image kernel combination schemes on Caltech 101, as well as a two order-ofmagnitude improvement in efficiency.
Detection and Characterization of Wolbachia Infections in Natural Populations of Aphids: Is the Hidden Diversity Fully Unraveled?

Aphids are a serious threat to agriculture, despite being a rather small group of insects. The about 4,000 species worldwide engage in highly interesting and complex relationships with their microbial fauna. One of the key symbionts in arthropods is Wolbachia, an α-Proteobacterium implicated in many important biological processes and believed to be a potential tool for biological control. Aphids were thought not to harbour Wolbachia; however, current data suggest that its presence in aphids has been missed, probably due to the low titre of the infection and/or to the high divergence of the Wolbachia strains of aphids. The goal of the present study is to map the Wolbachia infection status of natural aphids populations, along with the characterization of the detected Wolbachia strains. Out of 425 samples from Spain, Portugal, Greece, Israel and Iran, 37 were found to be infected. Our results, based mainly on 16S rRNA gene sequencing, indicate the presence of two new Wolbachia supergroups prevailing in aphids, along with some strains belonging either to supergroup B or to supergroup A.
Two-compartment tumor metabolism

Previously, we proposed a new paradigm to explain the compartment-specific role of autophagy in tumor metabolism. In this model, autophagy and mitochondrial dysfunction in the tumor stroma promotes cellular catabolism, which results in the production of recycled nutrients. These chemical building blocks and high-energy “fuels” would then drive the anabolic growth of tumors, via autophagy resistance and oxidative mitochondrial metabolism in cancer cells. We have termed this new form of stromal-epithelial metabolic coupling: “two-compartment tumor metabolism. ” Here, we stringently tested this energy-transfer hypothesis, by genetically creating (1) constitutively autophagic fibroblasts, with mitochondrial dysfunction or (2) autophagy-resistant cancer cells, with increased mitochondrial function. Autophagic fibroblasts were generated by stably overexpressing key target genes that lead to AMP-kinase activation, such as DRAM and LKB1. Autophagy-resistant cancer cells were derived by overexpressing GOLPH3, which functionally promotes mitochondrial biogenesis. As predicted, DRAM and LKB1 overexpressing fibroblasts were constitutively autophagic and effectively promoted tumor growth. We validated that autophagic fibroblasts showed mitochondrial dysfunction, with increased production of mitochondrial fuels (L-lactate and ketone body accumulation). Conversely, GOLPH3 overexpressing breast cancer cells were autophagy-resistant, and showed signs of increased mitochondrial biogenesis and function, which resulted in increased tumor growth. Thus, autophagy in the tumor stroma and oxidative mitochondrial metabolism (OXPHOS) in cancer cells can both dramatically promote tumor growth, independently of tumor angiogenesis. For the first time, our current studies also link the DNA damage response in the tumor microenvironment with “Warburg-like” cancer metabolism, as DRAM is a DNA damage/repair target gene.
NFC mobile payments: Are we ready for them?

Near-field communication (NFC) mobile payments technology was prophesied to take the world by storm. Hence, merchants, stakeholders and banks in Norway have commenced plans to join the race of providing this technology to their consumers. Through adopting the Technology Acceptance and Change Management models as theoretical lenses, a qualitative survey was conducted in this study to gather users' insights regarding the perceived motivations and concerns towards NFC mobile payments in Norway. Specifically, this research focuses on user awareness and readiness to change, as well as, technology ease-of-use, usefulness, and trust. While earlier literature findings suggest a potential high market penetration and readiness of Norwegian users to adopt NFC payments, yet our results challenge these findings. Nonetheless, given a solid platform, improved security, and a proper NFC ecosystem, the potential users may consider switching from other payment methods to NFC payments in the future.
Salvage treatment with lenalidomide and dexamethasone in relapsed/refractory mantle cell lymphoma: clinical results and effects on microenvironment and neo-angiogenic biomarkers

Background Preclinical studies have highlighted the activity of lenalidomide in mantle cell lymphoma and its anti-proliferative synergy with dexamethasone. Design and Methods In this prospective, multicenter, phase II study, patients with relapsed/refractory mantle cell lymphoma who were not eligible for, or had relapsed after, intensive treatments received lenalidomide 25 mg/day (days 1–21 of each 28-day cycle) and dexamethasone (40 mg/day on days 1, 8, 15, and 22) for up to 12 months. Results The primary end-points, overall and complete response rates, were achieved by 17 of 33 (52%; 95% confidence interval [CI], 35–68%) and 8 of 33 patients (24%; 95% CI, 13–41%), respectively, by the end of treatment. Fifteen patients (45%) discontinued treatment prematurely, 13 due to lack of response. The median progression-free and overall survival were 12 months (95% CI, 5–19 months) and 20 months (95% CI, 12 months to not estimable), respectively. Treatment resulted in a significant increase in microvessel density (P=0.033) and non-significant increases in macrophage and natural killer cell counts, while serum levels of neoangiogenic factors did not change significantly. Grade 3/4 adverse events were neutropenia (53%), leukopenia (25%), thrombocytopenia (22%), infections (12%), and febrile neutropenia (12%). Conclusions These results confirm a favorable safety and activity profile of lenalidomide in relapsed/refractory mantle cell lymphoma. The contribution of dexamethasone in achieving these results is unclear because of its possible detrimental effect on the immune activation generated by lenalidomide and a higher risk of developing infectious complications. (clinicaltrials.gov identifier: NCT00786851).
From traditional Ayurvedic medicine to modern medicine: identification of therapeutic targets for suppression of inflammation and cancer

Cancer is a hyperproliferative disorder that involves transformation, dysregulation of apoptosis, proliferation, invasion, angiogenesis and metastasis. Extensive research during the last 30 years has revealed much about the biology of cancer. Drugs used to treat most cancers are those that can block cell signalling, including growth factor signalling (e.g., epidermal growth factor); prostaglandin production (e.g., COX-2); inflammation (e.g., inflammatory cytokines: NF-κB, TNF, IL-1, IL-6, chemokines); drug resistance gene products (e.g., multi-drug resistance); cell cycle proteins (e.g., cyclin D1 and cyclin E); angiogenesis (e.g., vascular endothelial growth factor); invasion (e.g., matrix metalloproteinases); antiapoptosis (e.g., bcl-2, bcl-XL, XIAP, survivin, FLIP); and cellular proliferation (e.g., c-myc, AP-1, growth factors). Numerous reports have suggested that Ayurvedic plants and their components mediate their effects by modulating several of these recently identified therapeutic targets. However, Ayurvedic medicine requires rediscovery in light of our current knowledge of allopathic (modern) medicine. The focus of this review is to elucidate the Ayurvedic concept of cancer, including its classification, causes, pathogenesis and prevention; surgical removal of tumours; herbal remedies; dietary modifications; and spiritual treatments.
Bioenergetic Aspects of Halophilism

SUMMARY Examinination of microbial diversity in environments of increasing salt concentrations indicates that certain types of dissimilatory metabolism do not occur at the highest salinities. Examples are methanogenesis for H2 + CO2 or from acetate, dissimilatory sulfate reduction with oxidation of acetate, and autotrophic nitrification. Occurrence of the different metabolic types is correlated with the free-energy change associated with the dissimilatory reactions. Life at high salt concentrations is energetically expensive. Most bacteria and also the methanogenic archaea produce high intracellular concentrations of organic osmotic solutes at a high energetic cost. All halophilic microorganisms expend large amounts of energy to maintain steep gradients of NA+ and K+ concentrations across their cytoplasmic membrane. The energetic cost of salt adaptation probably dictates what types of metabolism can support life at the highest salt concentrations. Use of KCl as an intracellular solute, while requiring far-reaching adaptations of the intracellular machinery, is energetically more favorable than production of organic-compatible solutes. This may explain why the anaerobic halophilic fermentative bacteria (order Haloanaerobiales) use this strategy and also why halophilic homoacetogenic bacteria that produce acetate from H2 + CO2 exist whereas methanogens that use the same substrates in a reaction with a similar free-energy yield do not.
Handover keying and its uses

Mobile nodes must authenticate themselves in order to use network services. When mobile nodes roam into a new cell, they must re-authenticate to the new layer 2 and 3 devices. This re-authentication process can take as long as two seconds, which is unacceptable for applications such as voice over IP. In this article we present several recently developed authentication protocols that can reduce the reauthentication delay. Both intra-domain and inter-domain handover scenarios are discussed. We mainly focus on two protocols - 802.11r and EAP Re-authentication protocol for handover keying. These two protocols use security key hierarchies to avoid full authentication. An application of these protocols is presented for the control and provisioning of a wireless access-point network.