Miracle-dz/UniFAR-FTUs huggingface dataset:
Tag-Protector: An Effective and Dynamic Detection of Illegal Memory Accesses through Compile Time Code Instrumentation

Programming languages permitting immediate memory accesses through pointers often result in applications having memory-related errors, which may lead to unpredictable failures and security vulnerabilities. A lightweight solution is presented in this paper to tackle such illegal memory accesses dynamically in C/C++ based applications. We propose a new and effective method of instrumenting an application’s source code at compile time in order to detect illegal spatial and temporal memory accesses. It is based on creating tags to be coupled with each memory allocation and then placing additional tag checking instructions for each access made to the memory. The proposed solution is evaluated by instrumenting applications from the BugBench benchmark suite and publicly available benchmark software, run-time intrusion prevention evaluator (RIPE), detecting all the bugs successfully. The performance and memory overheads are further analyzed by instrumenting and executing real-world applications from various renowned benchmark suites. In addition, the proposed solution is also tested to analyze the performance overhead for multithreaded applications in multicore environments. Overall our technique can detect a wide range of memory bugs and attacks with reduced performance overhead and higher detection rate as compared to the similar existing countermeasures when tested under the same experimental setup.
The Impact of Using Many Jargon Words, while Communicating with the Organization Employees

For an organization in order to ensure that it is running smoothly, and its goals are being met to the best of the organization ability, there must be a solid communication between the management and employees involved. Therefore, communication is supposed to be effective and efficient when it is being used in the organization. Management should ensure that there are less jargon words that are being used in the daily communication with the employees in order to avoid miscommunication that may be detrimental to organizational success. This is also to make sure that communication is still serving its purpose in the organization, of information or ideas sharing. In situations where insufficient communication occurs, it tends to hamper the effective and efficient communication, as a result it leads employees to being demoralized and having a high employee turnover, relationships between employees and employers being tarnished, wastage of organizational resources and as well as negatively impact the organization productivity. Employees should be treated with care as they form a very integral component of the organization. In this paper, the impact of using many jargon words, while communicating with the organization employees is being investigated.
Does empathy predict altruism in the wild?

ABSTRACT Why do people act altruistically? One theory is that empathy is a driver of morality. Experimental studies of this are often confined to laboratory settings, which often lack ecological validity. In the present study we investigated whether empathy traits predict if people will act altruistically in a real-world setting, “in the wild”. We staged a situation in public that was designed to elicit helping, and subsequently measured empathic traits in those who either stopped to help or walked past and did not help. Results show that a higher number of empathic traits are a significant and positive predictor for altruistic behavior in a real-life situation. This supports the theory that the act of doing good is correlated with empathy.
The Impact of Agricultural Exports on Economic Growth in Nigeria

VERTER NAHANGA, BECVAŘOVA VĚRA. 2016. The Impact of Agricultural Exports on Economic Growth in Nigeria. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 64(2): 691–700. Agriculture is the backbone of Nigeria’s socioeconomic development. This paper investigates the impact of agricultural exports on economic growth in Nigeria using OLS regression, Granger causality, Impulse Response Function and Variance Decomposition approaches. Both the OLS regression and Granger causality results support the hypothesis that agricultural exports- led economic growth in Nigeria. The results, however, show an inverse relationship between the agricultural degree of openness and economic growth in the country. Impulse Response Function results fl uctuate and reveal an upward and downward shocks from agricultural export to economic growth in the country. The Variance Decomposition results also show that a shock to agricultural exports can contribute to the fl uctuation in the variance of economic growth in the long run. For Nigeria to experience a favourable trade balance in agricultural trade, domestic processing industries should be encouraged while imports of agricultural commodities that the country could process cheaply should be discouraged. Undoubtedly, this measure could drastically reduce the country’s overreliance on food imports and increase the rate of agricultural production for self-suffi ciency, exports and its contribution to the economic growth in the country.
Three Algorithms for Interface Synthesis: A Comparative Study

A temporal interface for a system component is a finite automaton that specifies the legal sequences of input events. We evaluate and compare three different algorithms for automatically extracting the temporal interface from the transition graph of a component: (1) a game algorithm that computes the interface as a representation of the most general environment strategy to avoid a safety violation; (2) a learning algorithm that repeatedly queries the component to construct the minimal interface automaton; and (3) a CEGAR algorithm that iteratively refines an abstract interface hypothesis by adding relevant state information from the component. Since algorithms (2) and (3) have been published in different software contexts, for comparison purposes, we present the three algorithms in a uniform finite-state setting. We furthermore extend the three algorithms to construct maximally permissive interface automata, which accept all legal input sequences. While the three algorithms have similar worst-case complexities, their actual running times differ greatly depending on the component whose interface is computed. On the theoretical side, we provide families of components that exhibit exponential differences in the performance of the three algorithms. On the practical side, we evaluate the three algorithms experimentally on a variety of real world examples. Not surprisingly, the experimental evaluation confirms the theoretical expectation: learning performs best if the minimal interface automaton is small; CEGAR performs best if only few component variables are needed to prove an interface hypothesis safe and permissive; and the direct (game) algorithm outperforms both approaches if neither is the case.
Application of Gaussian mixture model on defect detection of print fabric

A new approach based on improved Gaussian mixture model was developed to detect defects on print fabric. Considering the detection accuracy is not high by using the conventional Gaussian mixture model based method,fully utilizes the characteristic of strong correlation among print fabric image pixels,this paper proposed a defect detection algorithm with self-adaptive partition block modeling. Experimental results indicate that by using the proposed method, the detection success rate can reach 94%. Furthermore,the proposed method can effectively handle problems in the detection process on nonuniform illumination and noise,and it is suitable for the defect detection of print fabrics.
Using Sift Algorithm Identifying An Abandoned Object By Moving Camera

Detection of suspicious items is one of the most important applications in Visual Surveillance. To find out those suspicious items the static objects were detected in a scene using a moving camera which detects a slight color variation, light variation and climatic changes but failed to detect the particular abandoned object. To deal with this detection problem we propose a system, which can detect only those suspicious object by using “SIFT ALGORITHM” which remove alarms in flat areas. Keyword: Abandoned object detection, geometric and photometric alignment, video matching.
Buccal telomere length and its associations with cortisol, heart rate variability, heart rate, and blood pressure responses to an acute social evaluative stressor in college students

Abstract Objective: Understanding the relationship between stress and telomere length (a marker of cellular aging) is of great interest for reducing aging-related disease and death. One important aspect of acute stress exposure that may underlie detrimental effects on health is physiological reactivity to the stressor. Methods: This study tested the relationship between buccal telomere length and physiological reactivity (salivary cortisol reactivity and total output, heart rate (HR) variability, blood pressure, and HR) to an acute psychosocial stressor in a sample of 77 (53% male) healthy young adults. Results: Consistent with predictions, greater reductions in HR variability (HRV) in response to a stressor and greater cortisol output during the study session were associated with shorter relative buccal telomere length (i.e. greater cellular aging). However, the relationship between cortisol output and buccal telomere length became non-significant when adjusting for medication use. Contrary to past findings and study hypotheses, associations between cortisol, blood pressure, and HR reactivity and relative buccal telomere length were not significant. Overall, these findings may indicate there are limited and mixed associations between stress reactivity and telomere length across physiological systems.
Concurrent nonindependent fixed‐ratio schedules of alcohol self‐administration: Effects of schedule size on choice

Choice behavior was studied under concurrent nonindependent fixed‐ratio fixed‐ratio (nFR) schedules of reinforcement, as these schedules result in frequent changeover responses. With these schedules, responses on either operandum count toward the completion of the ratio requirements of both schedules. Five monkeys were subjects, and two pairs of liquid reinforcers were concurrently available: 16% (w/v) and 0% ethanol or 16% and 8% ethanol. For each pair of reinforcers, the nFR sizes were systematically altered across sessions while keeping the schedule size equal for both liquids. Responding varied as a function of reinforcer pair and nFR size. With the 16% and 0% pair, higher response rates were maintained by 16% and were an inverted U‐shape function of nFR size. With 16% and 8%, a greater number of responses initially occurred on the schedule that delivered 8% ethanol. However, as nFR size increased, preference reversed such that responses that delivered 16% ethanol were greater. When the nFR size was subsequently decreased, preference reverted back to 8%. Number of responses emitted per delivery was a dependent variable and, in behavioral economic terms, was the price paid for each liquid delivery. With 16% and 0%, changeover responses initially increased and then decreased as schedule size became larger. In contrast, with the 16% and 8% pair, changeover responses increased directly with schedule size. Responding under nFR schedules is sensitive to differences in reinforcer magnitude and demonstrates that relative reinforcing effects can change as a function of schedule size.
Fixed-Rate Transmission Over Fading Interference Channels Using Point-to-Point Gaussian Codes

This paper investigates transmission schemes for fixed-rate communications over a Rayleigh block-fading interference channel. There are two source-destination pairs where each source, in the presence of a short-term power constraint, intends to communicate with its dedicated destination at a fixed data rate. It encodes its messages using a point-to-point Gaussian codebook. The two users' transmissions can be conducted orthogonally or non-orthogonally. In the latter case, each destination performs either direct decoding by treating the interference as noise, or successive interference cancellation (SIC) to recover its desired message. For each scheme, we seek solutions of a power control problem to efficiently assign power to the sources such that the codewords can be successfully decoded at destinations. However, because of the random nature of fading, the power control problem for some channel realizations may not have any feasible solution and the transmission will be in outage. Thus, for each transmission scheme, we first compute a lower bound and an upper bound on the outage probability. Next, we use these results to find an outer bound and an inner bound on the ϵ -outage achievable rate region, i.e., the rate region in which the outage probability is below a certain value ϵ.
Effect of Post-Cure on Mechanical Properties of CF/Epoxy Composites(Special Issue on Composite Materials)

This paper presents the effect of post-cure on mechanical properties of CF/Epoxy composites. At first, the shrinkage strain and the mechanical properties such as Vickers hardness of resin, transverse modulus and strength are measured for carbon/epoxy unidirectional laminates after four-hour thermal treatment (post-cure process) at temperatures ranging from 70°C to 200°C. Then, the effect of post-cure temperature on transverse cracking behavior in a cross-ply laminate is experimentally investigated. The change in the residual stress due to post-cure is also estimated for the cross-ply laminate. Finally, the fracture surfaces of transverse cracks are observed using the scanning electron microcopy (SEM) to reveal the effect of post-cure on fracture behavior. It is found that the unidirectional laminate shrinks in only the transverse direction after the post-cure process. The hardness of the resin increases with increasing post-cure temperature below 150°C while transverse modulus and strength are independent of post-cure temperature below 150°C. Transverse cracking in post-cured cross-ply specimens initiates at lower stresses than the critical stresses in virgin specimens. The transverse crack density is predicted by a Weibull's probabilistic failure model. It is deduced from SEM observation of fracture surfaces that the fiber/resin interface is weakened by thermal treatment that may lead to reduction in the transverse strength at 200°C.
The hierarchical high-speed neural network image classification algorithm for video surveillance systems

This article introduces a new fast model of a deep convolutional neural network that allows efficient low resolution image processing during the real-time video analysis with no need of a special high-performance computing devices. The architecture of the proposed neural network consists of the effective combination of fully connected and separable convolutional layers, normalization layers, and pooling, which can significantly reduce the number of computational operations and consequently, the speed of image processing.
Pattern and Process in the Comparative Study of Convergent Evolution*

Understanding processes that have shaped broad-scale biodiversity patterns is a fundamental goal in evolutionary biology. The development of phylogenetic comparative methods has yielded a tool kit for analyzing contemporary patterns by explicitly modeling processes of change in the past, providing neontologists tools for asking questions previously accessible only for select taxa via the fossil record or laboratory experimentation. The comparative approach, however, differs operationally from alternative approaches to studying convergence in that, for studies of only extant species, convergence must be inferred using evolutionary process models rather than being directly measured. As a result, investigation of evolutionary pattern and process cannot be decoupled in comparative studies of convergence, even though such a decoupling could in theory guard against adaptationist bias. Assumptions about evolutionary process underlying comparative tools can shape the inference of convergent pattern in sometimes profound ways and can color interpretation of such patterns. We discuss these issues and other limitations common to most phylogenetic comparative approaches and suggest ways that they can be avoided in practice. We conclude by promoting a multipronged approach to studying convergence that integrates comparative methods with complementary tests of evolutionary mechanisms and includes ecological and biogeographical perspectives. Carefully employed, the comparative method remains a powerful tool for enriching our understanding of convergence in macroevolution, especially for investigation of why convergence occurs in some settings but not others.
Strategies for Palliative Care in Advanced Colorectal Cancer

Palliative care has appropriately been receiving increased attention in recent years. From the surgeon’s standpoint, therapy is considered palliative when resection of all known tumor sites is no longer possible or advisable. Since a cure, as commonly defined, is not possible, the goal of treatment and eventually the success of therapy becomes judged by the control of symptoms and alleviation of suffering. Providing optimal palliative care for the patient with advanced colorectal cancer is a complex and challenging process. The process of providing palliative care may be a departure from the traditional surgical satisfaction derived from the complete excision of a malignancy, but surgeons achieving excellence in palliative care will likely find this a rewarding endeavor.
DAIS: a real-time data attack isolation system for commercial database applications

Traditional database security mechanisms are very limited in defending successful data attacks. Authorized but malicious transactions can make a database useless by impairing its integrity and availability. The paper presents the design of a real-time data attack isolation system, denoted DAIS. DAIS isolates likely suspicious actions before a definite determination of intrusion is reported. In this way, the database can be immunized from many malicious transactions. DAIS is a COTS-DBMS-specific implementation of a general isolation algorithm that was developed previously (P. Liu et al., 2000). The design of the first DAIS prototype, which is for Oracle Server 8.1. 6, is discussed. DAIS uses triggers and transaction profiles to keep track of the items read and written by transactions, isolates attacks by rewriting user SQL statements, and is transparent to end users. The DAIS design is very general. In addition to Oracle, it can be easily adapted to support many other database application platforms such as Microsoft SQL Server, Sybase, and Informix.
Excitation conditions for signed regressor least mean squares adaptation

The stability of the signed regressor variant of least-mean-square (LMS) adaptation is found to be heavily dependent on the characteristics of the input sequence. Averaging theory is used to derive a persistence of excitation condition that guarantees exponential stability of the signed regressor algorithm. Failure to meet this condition (which is not equivalent to persistent excitation for LMS) can result in exponential instability, even with the use of leakage. This persistence of excitation condition is interpreted in both deterministic and stochastic settings. >
Erythritol is a pentose-phosphate pathway metabolite and associated with adiposity gain in young adults

Significance The prevention of weight gain in adulthood is a public health challenge, particularly given the difficulty of losing weight. Data on freshmen were collected at the beginning and end of the academic year, and baseline blood samples were studied to find markers of incident weight gain. A metabolite, erythritol, was elevated at the beginning of the year in freshmen who went on to gain weight, fat, and abdominal fat compared with freshmen with stable weight. Erythritol is a sugar substitute low-calorie sweetener, and prior studies claimed no endogenous synthesis. We report a previously unrecognized metabolism of glucose to erythritol, and given the association between erythritol and weight gain, research is needed to understand whether and how this pathway contributes to weight gain risk. Metabolomic markers associated with incident central adiposity gain were investigated in young adults. In a 9-mo prospective study of university freshmen (n = 264). Blood samples and anthropometry measurements were collected in the first 3 d on campus and at the end of the year. Plasma from individuals was pooled by phenotype [incident central adiposity, stable adiposity, baseline hemoglobin A1c (HbA1c) > 5.05%, HbA1c < 4.92%] and assayed using GC-MS, chromatograms were analyzed using MetaboliteDetector software, and normalized metabolite levels were compared using Welch’s t test. Assays were repeated using freshly prepared pools, and statistically significant metabolites were quantified in a targeted GC-MS approach. Isotope tracer studies were performed to determine if the potential marker was an endogenous human metabolite in men and in whole blood. Participants with incident central adiposity gain had statistically significantly higher blood erythritol [P < 0.001, false discovery rate (FDR) = 0.0435], and the targeted assay revealed 15-fold [95% confidence interval (CI): 13.27, 16.25] higher blood erythritol compared with participants with stable adiposity. Participants with baseline HbA1c > 5.05% had 21-fold (95% CI: 19.84, 21.41) higher blood erythritol compared with participants with lower HbA1c (P < 0.001, FDR = 0.00016). Erythritol was shown to be synthesized endogenously from glucose via the pentose-phosphate pathway (PPP) in stable isotope-assisted ex vivo blood incubation experiments and through in vivo conversion of erythritol to erythronate in stable isotope-assisted dried blood spot experiments. Therefore, endogenous production of erythritol from glucose may contribute to the association between erythritol and obesity observed in young adults.
MetaFraud: A Meta-Learning Framework for Detecting Financial Fraud

Financial fraud can have serious ramifications for the long-term sustainability of an organization, as well as adverse effects on its employees and investors, and on the economy as a whole. Several of the largest bankruptcies in U.S. history involved firms that engaged in major fraud. Accordingly, there has been considerable emphasis on the development of automated approaches for detecting financial fraud. However, most methods have yielded performance results that are less than ideal. In consequence, financial fraud detection continues as an important challenge for business intelligence technologies. In light of the need for more robust identification methods, we use a design science approach to develop MetaFraud, a novel meta-learning framework for enhanced financial fraud detection. To evaluate the proposed framework, a series of experiments are conducted on a test bed encompassing thousands of legitimate and fraudulent firms. The results reveal that each component of the framework significantly contributes to its overall effectiveness. Additional experiments demonstrate the effectiveness of the meta-learning framework over state-of-the-art financial fraud detection methods. Moreover, the MetaFraud framework generates confidence scores associated with each prediction that can facilitate unprecedented financial fraud detection performance and serve as a useful decision-making aid. The results have important implications for several stakeholder groups, including compliance officers, investors, audit firms, and regulators.