Miracle-dz/UniFAR-FTUs huggingface dataset:
FunProbe: Probing Functions from Binary Code through Probabilistic Analysis

Current function identification techniques have been mostly focused on a specific set of binaries compiled for a specific CPU architecture. While recent deep-learning-based approaches theoretically can handle binaries from different architectures, they require significant computation resources for training and inference, making their use less practical. Furthermore, due to the lack of interpretability of such models, it is fundamentally difficult to gain insight from them. Hence, in this paper, we propose FunProbe, an efficient system for identifying functions from binaries using probabilistic inference. In particular, we identify 16 architecture-neutral hints for function identification, and devise an effective method to combine them in a probabilistic framework. We evaluate our tool on a large dataset consisting of 19,872 real-world binaries compiled for six major CPU architectures. The results are promising. FunProbe shows the best accuracy compared to five state-of-the-art tools we tested, while it takes only 6 seconds on average to analyze a single binary. Notably, FunProbe is 6× faster on average in identifying functions than XDA, a state-of-the-art deep-learning tool that leverages GPU in its inference phase.
Current Trends in OMICS (CTO)

Artificial intelligence (AI) has made significant strides in recent years toward resolving a wide range of biological issues, including a number of occurrences connected to cancer. Deep learning is an adaptable sector of AI that enables the automatic extraction of features. It is increasingly being used in various fields of cancer research, both scientific and clinical. In this study, several current applications of AI in oncology, including the situations in which deep learning has effectively addressed intractable disputes, are discussed. This study also discusses the challenges that need to be surmounted before such an application of AI may be implemented more broadly. Similarly, it brings to light resources and data sets that can assist in maximizing the potential of AI. Essential insights in oncology may be generated based on the development of novel methodologies and uses of AI, making it possible for substantial changes to be made to clinical practice.
Type 2 diabetes mellitus is associated with altered CD 8 + T and NK cell function in pulmonary tuberculosis

Type 2 diabetes mellitus (DM) is associated with expanded frequencies of mycobacterial antigen specific CD4 + Th1 and Th17 cells in individuals with active pulmonary tuberculosis (TB). No data are available on the role of CD8 + T and NK cells in TB with coincident DM. To identify the role of CD8 + T and NK cells in pulmonary TB with diabetes, we examined mycobacteria–specific immune responses in the whole blood of individuals with TB-DM and compared them with those without DM (TB-NDM). We found that TB-DM is characterized by elevated frequencies of mycobacterial antigen stimulated CD8 + T cells expressing Type 1 (IFN and IL-2) and Type 17 (IL-17F) cytokines. We also found that TB-DM is characterized by expanded frequencies of TB antigen stimulated NK cells expressing Type 1 (TNF-) and Type 17 (IL-17A and IL-17F) cytokines. In contrast, CD8 + T cells were associated with significantly diminished expression of the cytotoxic markers Perforin, Granzyme B and CD107a both at baseline and following antigen or anti-CD3 stimulation, while NK cells were associated with significantly decreased antigen stimulated expression of CD107a only. This was not associated with alterations in CD8 + T cell or NK cell numbers or subset distribution. Therefore, our data suggest that pulmonary tuberculosis complicated with type 2 DM is associated A cc ep te d A rt ic le This article is protected by copyright. All rights reserved. with an altered repertoire of cytokine producing and cytotoxic molecules expressing CD8 + T and NK cells, possibly contributing to increased pathology.
Osteopontin versus alpha-fetoprotein as a diagnostic marker for hepatocellular carcinoma: a meta-analysis

Background: Several studies have reported that osteopontin (OPN) is a promising marker for the diagnosis of hepatocellular carcinoma (HCC); however, some studies emerged with conflicting results. Therefore, we provide a systematic review to evaluate the diagnostic performance of OPN for HCC. Methods: Studies that investigated the diagnostic value of OPN and alpha-fetoprotein (AFP) in HCC were collected from PubMed and Embase. Sensitivity, specificity, and other parameters about the diagnostic accuracy of serum OPN and AFP in HCC were pooled using STATA 12.0 software. The summary receiver operating characteristic curve (sROC) and other parameters were used to summarize the overall test performance. Results: Twelve studies were included in our meta-analysis. Pooled sensitivity, specificity, and diagnostic odds ratio were 0.813 (95% CI: 0.671–0.902), 0.874 (95% CI: 0.778–0.932), and 30.047 (95% CI: 8.845–102.067) for OPN; 0.639 (95% CI: 0.538–0.729), 0.959 (95% CI: 0.909–0.982), and 41.518 (95% CI: 13.688–125.929) for AFP; and 0.856 (95% CI: 0.760–0.918), 0.738 (95% CI: 0.630–0.823), and 16.718 (95% CI: 7.950–35.156) for OPN + AFP, respectively. The area under the sROC for OPN, AFP, and OPN + AFP was 0.91, 0.88, and 0.85, respectively. For diagnosis of early HCC, pooled sensitivity of serum OPN, AFP, and OPN + AFP was 0.493 (95% CI: 0.422–0.563), 0.517 (95% CI: 0.446–0.587), and 0.732 (95% CI: 0.666–0.791), respectively. Conclusions: OPN is a comparable marker to AFP for the diagnosis of HCC, and the sensitivity of OPN was higher than that of AFP. A combination of AFP and OPN can elevate the sensitivity of diagnosis for early HCC.
Adherence and patients’ experiences with the use of oral anticancer agents

Abstract A rapidly growing number of oral anticancer agents has become available in oncology and hematology. Though these introductions have several benefits, medication adherence is an issue of concern. Little is known about the factors influencing adherence to treatment with oral anticancer agents in daily practice. Material and methods. In this observational, multicenter study including 216 patients, carried out between October 2010 and March 2012, the use of oral anticancer drugs was assessed by means of a telephonic pill count, a questionnaire and a review of the patient's medical file and pharmacy medication records. Parameters collected were patients’ demographics, treatment characteristics, beliefs and attitude towards disease and medicines, self-reported adherence, side effects, quality of life and satisfaction about information. Patients off treatment filled out a questionnaire about the reasons for discontinuation. Optimal adherence was defined as ≥ 95%–≤ 105%. Results. The mean adherence rate (AR) (n = 177) was 99.1% with 20.3% of patients having a sub-optimal AR (< 95%, > 105%) consisting both of under- and over-adherence. Multivariate analyses showed that being on a cyclic dosing regimen (rather than a continuous regimen), not living alone and being highly educated increased the chances of optimal adherence (ORs = 4.88, 4.59 and 2.53, respectively). In addition, optimal adherence was found to be less common in patients reporting treatment control (OR = 0.77). One third of 79 patients off treatment reported their experienced side effects as one of the reasons for discontinuation. Discussion. Although most patients are fully adherent to oral anticancer agents, there is a substantial number tending to non-adherence. Patients living alone and those on a continuous dosing regimen are most likely to adhere sub-optimally. Interventions to improve adherence should specifically address these patients and be tailored to the needs of the individual patient.
Haptics to improve task performance in people with disabilities : A review of previous studies and a guide to future research with children with disabilities View project Teleoperation View project

Percutaneous needle insertion is amongst the most prevalent clinical procedures. The effectiveness of needlebase interventions heavily relies on needle targeting accuracy. However, the needle interacts with the surrounding tissue during insertion and deflects away from its intended trajectory. To overcome this problem, a significant research effort has been made towards developing robotic systems to automatically steer beveltipped needles percutaneously, which is a comprehensive and challenging control problem. A flexible needle inserted in soft tissue is an under-actuated system with nonholonomic constraints. Closed-loop feedback control of needle in tissue is challenging due to measurement errors, unmodelled dynamics created by tissue heterogeneity, and motion of targets within the tissue. In this paper, we review recent progress made in each of the complementary components that constitute a closed-loop needle steering system, including modelling needle-tissue interaction, sensing needle deflection, controlling needle trajectory, and hardware implementation.
Development of Character Assessment Instruments for Student

This study aims to develop instruments for evaluating the character of Vocational High School students as well as knowing the validity of the instrument items, and the instrument reliability of the experts and practitioners. The type of research used is research and development (R&D), the research model used is Four-D (4D). The 4D model consists of four stages of research namely define, design, develop, and disseminate. Analysis of the data used is to test the validity of manual book product content with the Lawshe CVR and CVI formulas. Tests carried out by 5 experts or experts who are competent in the field of Counseling and Psychological Guidance. The results of the study based on content validity analysis are the CVR values per item obtained between +1 to 0 (CVR> 0). Furthermore, the results of the Lawshe CVI analysis obtained a score of 0.97 greater than 0 (0.97> 0). Based on the analysis of these data means the value of the validity of the instrument content is high and for the reliability results obtained at 0.78> 0.60 thus all items of the questionnaire are declared reliable
GREEN SYNTHESIS AND ANTIBACTERIAL ACTIVITIES OF SILVER NANOPARTICLES

Silver ions and silver compounds have been known to have strong antibacterial activities. Using silver nanoparticles lead to an increase in number of particles per unit area thus, antibacterial effects can be maximized. In this study, silver nanoparticles were prepared by treating a solution of AgNO3 dissolved in deionized water with Vitamin C rich fruits (Guava, grape and tomato) as reducing agent. The factors that affect the synthesis of silver nanoparticles (reaction time, temperature and concentration of silver nitrate) were investigated. The nanoparticles were characterized by UV-vis spectrophotometer, X-ray diffraction and Fourier transform infrared (FT-IR). A suitable condition for silver nanoparticle synthesis is using 0.001M silver nitrate and guava extract at 60 °C for 8 hours. The UV-vis spectrophotometer show peak located of silver nanoparticles at 420 nm. X-ray diffraction analysis also showed functional structure and pattern of silver nanoparticles. The FT-IR spectra indicated the role of different functional groups of reducing agent and silver nanoparticles. Antibacterial activities of the prepared nanoparticles against Gram-positive (S. aureus) and Gram-negative (E. coli, P. aeruginosa and S. typhimurium) were evaluated by disc diffusion method. At concentration of 5µg/ml, silver nanoparticles have better antibacterial activities than that of AgNO3. However, at concentrations of 20, 50 and 200 µg/ml, the antibacterial activities of silver nanoparticles and AgNO3 were relatively close to each other.
Factors Associated with Antihypertensive Medication Non-Adherence: A Cross-Sectional Study Among Lebanese Hypertensive Adults and

Background: Poor adherence to antihypertensives is associated with negative outcome of the disease as well as loss of health-care resources. Addressing the epidemic of poor adherence requires identifying factors associated with this behaviour. The aim of this study is to describe adherence to antihypertensive medication among Lebanese hypertensive patients and to evaluate the association between socio-economic, patient- and conditions-related factors and non-adherence. Methods: A cross-sectional study was carried out on adherence to antihypertensive medications covering all governorates of Lebanon. This study was conducted between February 2018 and January 2019 on a random sample of 1497 hypertensive patients. A face-to-face questionnaire was used to assess adherence to antihypertensive medication and its determinants according to the ﬁ ve World Health Organization (WHO) main categories. Logistic regression analysis was performed to test the adjusted association between the multiple exposure factors, and drug adherence data were collected by trained interviewers. Results: Adherence to antihypertensive medications was reported by 1253 (83.7%) of the patients. After multivariate analysis, patients who tried to control their stress level (OR = 0.77, 95% CI [0.38 – 0.95]), those who had normal BP readings (OR =0.49, 95% CI [0.18 – 0.97]), and those who believed in the effectiveness of their treatment (OR = 0.31, 95% CI [0.14 – 0.76]) had a signi ﬁ cantly lower chance to exhibit non-adherence to their treatment. However, older patients (OR= 1.87, 95% CI [1.23 – 2.21]), divorced/separated patients (OR= 2.14, 95% CI [1.31 – 5.48]), married (OR=1.96, 95% CI [1.27 – 3.90]), widowed (OR=2.11, 95% CI [1.62 – 6.50]), obese patients (OR = 1.76, 95% CI [1.21 – 1.94]), and patients who smoked hookah and cigarettes (OR = 2.62, 95% CI [1.17 – 6.76]) were more likely to exhibit non-adherence. Conclusion: Our study highlights the in ﬂ uence of factors such as old age, marital status, BMI and high level of emotional stress on non-adherence to medication in hypertensive patients. These determinants should be incorporated into adherence improving strategies. therapeutic conti- nuum. Patient satisfaction, acceptability, quality of life, compliance, persistence and their role in developing new therapeutic modalities and compounds to optimize clinical outcomes for existing disease
symptom burden and self-management in persons with chronic obstructive pulmonary disease

Purpose: Self-management is crucial for effective COPD management. This study aimed at identifying associations between self-management and sociodemographic characteristics, clinical characteristics, and symptom burden in people with COPD. Patients and methods: In this cross-sectional study with 225 participants diagnosed with COPD grades II–IV, multiple linear regression analysis was conducted, using sociodemographic and clinical characteristics and symptom burden (COPD Assessment Test) as the independent variables and the eight self-management domains of the Health Education Impact Questionnaire (heiQ) as the outcome variables. Results: Higher symptom burden was significantly associated with worse scores in all self-management domains ( p , 0.003), except for self-monitoring and insight ( p = 0.012). Higher disease severity ( p = 0.004) and numbers of comorbidities ( p , 0.001) were associated with more emotional distress, and women scored higher than men on positive and active engagement in life ( p = 0.001). Higher score in pack-years smoking was associated with lower score in health-directed activities ( p = 0.006) and self-monitoring and insight ( p , 0.001), and participation in organized physical training was associated with higher score in health-directed activities ( p , 0.001). The final models explained 3.7%–31.7% of variance (adjusted R 2 ) across the eight heiQ scales. Conclusion: A notable finding of this study was that higher symptom burden was associated with worse scores in all self-management domains, except for self-monitoring and insight. In addition, sex, disease severity, comorbidity, pack-years smoking, and participation in organized physical training were associated with one or two self-management domains. The study contributes to improved understanding of self-management in COPD. However, the explained variance levels indicate that more research needs to be done to uncover what else explains self-management domains in COPD. global Initiative for Chronic Obstructive lung Disease; ICs, inhaled corticosteroids; laBa, long-acting β 2 -agonist; laMa, long-acting anticholinergic; lTOT, long-term oxygen therapy; mMRC, modified Medical Research Council; SABA, short-acting 2 -agonist; saMa, short-acting anticholinergic; Pr, pulmonary rehabilitation; PT, physical training.
Overexpressing lncrna SNHG16 inhibited hcc proliferation and chemoresistance by functionally sponging hsa-mir-93

Background: Long noncoding RNAs (lncRNAs) have been identified as prognostic biomarkers and functional regulators in human cancers. The present study aimed to determine the expressions and functions of an lncRNA, Small Nucleolar RNA Host Gene 16 ( SNHG16 ), in hepatocellular carcinoma (HCC). Patients and methods: SNHG16 expressions were tested by quantitative real-time PCR (qRT-PCR) in HCC cell lines, as well as 43 pairs of HCC tissues and pair-matched healthy hepatic tissues. It was overexpressed in Hep3B and HuH7 cells. The effects of SNHG16 overexpression in HCC in vitro proliferation, 5-fluorouracil (5-FU) chemoresistance, and in vivo tumor growth were tested. A potential microRNA (miRNA) sponge target of SNHG16 , hsa-miR-93, was tested by luciferase reporter assay and qRT-PCR. In addition, hsa-miR-93 was upregulated in SNHG16 -overexpressed HCC cells to examine its effect on SNHG16 -mediated cancer cell functional regulation in HCC. Results: SNHG16 levels were markedly downregulated in both HCC cell lines and HCC tissues. Lentivirus-mediated SNHG16 overexpression inhibited HCC cell proliferation, 5-FU chemoresistance, and in vivo tumor growth. Hsa-miR-93 was confirmed to be directly sponging on SNHG16 . Its upregulation in HCC cells reversed SNHG16 overexpression and induced tumor-suppressing effects in HCC cells. Conclusion: Our data demonstrate that SNHG16 plays a critical role in HCC development via functionally sponging hsa-miR-93.
EFFICIENT SURROGATE-BASED MULTI-OBJECTIVE OPTIMIZATION ALGORITHM WITH A NEW ADAPTIVE WEIGHT VECTOR GENERATION

Most engineering design optimization problems are complex and expensive multi-objective optimization problems with multiple constraints. This paper proposes an improved surrogate-based multi-objective optimization algorithm (SBMO) using an adaptive weight vector generation method to address them. The main idea of the improved SBMO is to update the weight vectors of sub-problems adaptively according to the shape of the current Pareto front (PF) at each iteration while using SBMO to obtain Pareto optimal solutions. First, the improved SBMO decomposes a multi-objective optimization problem into a set of single-objective optimization sub-problems and builds surrogate models for each objective. Second, solutions are obtained by solving the acquisition problems for the sub-problems under the inﬁll-sampling criteria. Third, all the solutions obtained will be evaluated and used to update the surrogate models to share the search information. At each iteration, the improved SBMO will divide the topology of the current PF evenly and select random points between the segment points. Well-distributed weight vectors will be generated based on the random points. This weight vector generation method can signiﬁcantly improve the distribution of Pareto optimal solutions. The studies on benchmark test instances and aerodynamic design optimization of an airfoil indicate that the improved SBMO can obtain Pareto optimal solutions with better distribution than SBMO in a small number of sample points, and offers great potential to solve an expensive multi-objective optimization problem.
The Wages of Repression ∗

Incidents of government repression vary in which individuals are targeted. Building on a conceptual distinction between targeted repression (against opposition group members) and mass repression (against citizens broadly), I develop a framework that explains why regimes use both types of repression in combination. Targeted and mass repression have distinct eﬀects on civilians’ incentives to support an opposition. Citizens trade oﬀ ideological beneﬁts from challenging the regime and material beneﬁts from participating in the economy. Targeted repression decreases the beneﬁt of challenging the regime, activating security concerns. Mass repression aﬀects individuals’ material wellbeing, improving opportunities for participants in the economy. These participation and material wellbeing mechanisms make targeted and mass repression jointly optimal for the regime. By identifying distinct logics for targeted and mass repression, I show in some cases, targeted and mass repression are complements, meaning it is optimal for governments to employ more of both types of repression simultaneously.
The MapReduce snowy slope: where is it heading?

—The MapReduce (MR) paradigm represents a mile-stone in the ﬁeld of large-scale data analysis, even though most of its fundamental aspects have been already studied thoroughly in the last 3 decades by the database community. In this report, we will highlight the design trade-offs made by MR to achieve better horizontal scalability, at the price of lower efﬁciency compared to a parallel database. We will then describe some recent large-scale systems for BigData processing – by addressing some of the characteristic MR trade-offs, they represent its natural evolution for speciﬁc use-cases (e
Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis.

BACKGROUND Histologic grade in breast cancer provides clinically important prognostic information. However, 30%-60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profiles of breast cancers and whether such profiles could be used to improve histologic grading. METHODS We analyzed microarray data from 189 invasive breast carcinomas and from three published gene expression datasets from breast carcinomas. We identified differentially expressed genes in a training set of 64 estrogen receptor (ER)-positive tumor samples by comparing expression profiles between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to define the gene expression grade index. Data from 597 independent tumors were used to evaluate the association between relapse-free survival and the gene expression grade index in a Kaplan-Meier analysis. All statistical tests were two-sided. RESULTS We identified 97 genes in our training set that were associated with histologic grade; most of these genes were involved in cell cycle regulation and proliferation. In validation datasets, the gene expression grade index was strongly associated with histologic grade 1 and 3 status; however, among histologic grade 2 tumors, the index spanned the values for histologic grade 1-3 tumors. Among patients with histologic grade 2 tumors, a high gene expression grade index was associated with a higher risk of recurrence than a low gene expression grade index (hazard ratio = 3.61, 95% confidence interval = 2.25 to 5.78; P < .001, log-rank test). CONCLUSIONS Gene expression grade index appeared to reclassify patients with histologic grade 2 tumors into two groups with high versus low risks of recurrence. This approach may improve the accuracy of tumor grading and thus its prognostic value.