Miracle-dz/UniFAR-FTUs huggingface dataset:
Changing Their Mind About Confessing to Police: The Role of Contextual Factors in Crime Confession

This study aimed to investigate the offender’s decision making in crime confession during police interrogation. On the basis of a sample of 211 incarcerated offenders, the study showed that 21% of offenders changed their mind about confessing or not their crime following police interrogation. Logit regression indicated that contextual factors were associated with the offender’s final decision to confess after controlling for the offender’s initial decision. Multinomial regression further showed that offenders with a lengthy criminal record, advised by a lawyer, and facing drug-related charges characterized by weak police evidence were less likely to confess to the police, even when they initially planned to do so. Findings are discussed in light of the literature on crime confession.
Recognition and Elimination of Malicious Nodes in Vehicular Ad hoc Networks

A Vehicular Ad-Hoc Network, or VANET, is a form of Mobile ad-hoc network, to provide communications among nearby vehicles and between vehicles and nearby fixed equipment (Base Stations) via radio waves. These have similar characteristics as mobile ad hoc networks, often in the form of multi-hop networks. Due to the high mobility of nodes network topology changes occur frequently. All nodes share the same channel leading to congestion in very dense networks. One important property that characterizes VANETs is that they are self-organizing, self-creating, and self administering and decentralized systems. This paper proposes detection and elimination of misbehaving nodes in VANETs using mobile agents. Mobile agents are employed for each node, for the collection of information of neighbours and to find the route from source to the destination. To find the malicious nodes among the intermediate nodes, mobility and power ratio of the intermediate nodes are continuously monitored with the help of software agents. Some threshold value of mobility and power ratio for intermediate nodes are maintained at the source node. Based on comparing the monitored and threshold values of these factors, with probabilistic approach we are determining the nodes as malicious nodes. Once the intermediate node is determined as the malicious node, the alternate path is employed from source to the destination. To test the operative effectiveness and performance of the system some of the performance parameters evaluated are, Number of paths available, Number of routes involving misbehaving nodes, Number of misbehaving nodes, Time taken to detect misbehaving nodes.
A CMOS on-chip temperature sensor with −0.21°C 0.17 °C inaccuracy from −20 °C to 100 °C

An accurate, small, low-power CMOS temperature sensor for on-chip thermal monitoring is proposed. The temperature sensor utilizes the temperature characteristics of the threshold voltage of a MOS transistor to sense temperature and is quite linear over the in temperature range (-20C, 100°C). The threshold-based temperature sensors were designed in the ON Semiconductor 1P6M (Single Poly, 6 Metal) 180nm process with a 1.8V supply voltage. The die area of this circuit is only 14. 8μm×22. 2μm. It has low power consumption of about 1. 026μW at a 1% duty cycle. Measurement results show that a batch of 5 temperature sensors have a nonlinear error bounded of -0.21°C to +0.17°C with a one-point calibration and batch slope/curvature correction over the target operating temperature range (-20°C, 100°C).
Channel-Aware Distributed Medium Access Control

In this paper, we solve a fundamental problem: how to use distributed random access to achieve the performance of centralized schedulers. We consider wireless networks with arbitrary topologies and spatial traffic distributions, where users can receive traffic from or send traffic to different users and different communication links may interfere with each other. The channels are assumed heterogeneous, and the random channel gains of different links may have different distributions. To resolve the network contention in a distributed way, each frame is divided into contention and transmission periods. The contention period is used to resolve conflicts, while the transmission period is used to send payload in collision-free scenarios. We design a multistage channel-aware Aloha scheme for the contention period to enable users with relatively better channel states to have higher probabilities of contention success while assuring fairness among all users. We show analytically that the proposed scheme completely resolves network contention and achieves throughput close to that of centralized schedulers. Furthermore, the proposed scheme is robust to any uncertainty in channel estimation. Simulation results demonstrate that it significantly improves network performance while maintaining fairness among different users. The proposed random access approach can be applied to different wireless networks, such as cellular, sensor, and mobile ad hoc networks, to improve quality of service.
An Improved Algorithm for Diverse AdaBoostSVM

In order to improve the training convergence speed and detection accuracy of Diverse AdaBoostSVM, an improved algorithm is proposed according to the asymmetry in face detection. In the algorithm, the weight of each weak learner, which represents importance of each weak learner, is determined by the error rate and the recognition capability of the weak learner for the face samples. The results of the experiments show that the proposed algorithm could improve the training convergence speed and the detection accuracy in face detection.
A Novel Computer Vision Method for Evaluating Deformations of Fibers Cross Section in False Twist Textured Yarns

(cid:3) Abstract — In recent five decades, textured yarns of polyester fiber produced by false twist method are the most important and mass-produced manmade fibers. There are many parameters of cross section which affect the physical and mechanical properties of textured yarns. These parameters are surface area, perimeter, equivalent diameter, large diameter, small diameter, convexity, stiffness, eccentricity, and hydraulic diameter. These parameters were evaluated by digital image processing techniques. To find trends between production criteria and evaluated parameters of cross section, three criteria of production line have been adjusted and different types of yarns were produced. These criteria are temperature, drafting ratio, and D/Y ratio. Finally the relations between production criteria and cross section parameters were considered. The results showed that the presented technique can recognize and measure the parameters of fiber cross section in acceptable accuracy. Also, the optimum condition of adjustments has been estimated from results of image analysis evaluation.
Examining The Undergraduate Construction Technology Students' Use Of Computer And Internet In UEW: A Structural Equation Modelling Approach

: - This paper empirically examines the the use of computer and Internet facilities among the undergraduate construction technology students in UEW, Ghana. The study was a cross-sectional survey of 499 respondents using structured questionnaire personally administered. A usable 358 questionnaire were returned, representing 71.7% response rate and analysed using Structural Equation Modelling approach. The findings indicate that the proposed model has high goodness-of-fit for student’s use of computer. It also found that access to Internet, classroom based learning with Internet and non-classroom based learning with Internet could be influenced by students’ computer use. Theoretically, the study fills the dearth of conceptual models in understanding the critical determinants that influence students’ computer use in the high educa tion level in developing country context. It provides important implications for educational management in higher education. This paper contributes to the body of knowledge in the area of computer application in education.
Human aided computer assessment for exhaustive search

Human-computer interaction has been proposed as a means for more effectively dealing with the challenges posed by information retrieval. However, within the hierarchy of information needs, certain kinds of needs are only poorly handled by existing techniques. Information needs requiring thoroughness (exhaustive research, information discovery) are not well served by existing models of human-computer information retrieval (HCIR). Information needs such as these are commonplace in legal, patent, medical and intelligence searches. In such applications, high recall with high precision is the primary consideration, and the standard model, which treats human interaction as a kind of post-processing filter, does not yield a system with desired characteristics. In this paper, we propose an alternative model of HCIR which yields systems whose properties are more closely aligned with the needs of the exhaustive research task, and describe an implementation of such a system, demonstrating its effectiveness over the standard model in a task that models real-world conditions.
A methodology for intelligent sensor measurement, validation, fusion, and fault detection for equipment monitoring and diagnostics

In equipment monitoring and diagnostics, it is very important to distinguish between a sensor failure and a system failure. In this paper, we develop a comprehensive methodology based on a hybrid system of AI and statistical techniques. The methodology is designed for monitoring complex equipment systems, which validates the sensor data, associates a degree of validity with each measurement, isolates faulty sensors, estimates the actual values despite faulty measurements, and detects incipient sensor failures. The methodology consists of four steps: redundancy creation, state prediction, sensor measurement validation and fusion, and fault detection through residue change detection. Through these four steps we use the information that can be obtained by looking at: information from a sensor individually, information from the sensor as part of a group of sensors, and the immediate history of the process that is being monitored. The advantage of this methodology is that it can detect multiple sensor failures, both abrupt as well as incipient. It can also detect subtle sensor failures such as drift in calibration and degradation of the sensor. The four-step methodology is applied to data from a gas turbine power plant.
THE EFFECT OF VITAMIN E SUPPLEMENTATION ON AN EXPERIMENTAL HAEMONCHUS CONTORTUS INFECTION IN DORSET LAMBS

Gastrointestinal parasitism in sheep, particularly lambs, results in substantial economic losses to producers worldwide. Nutritional status has been shown to play an important role in host immune response to parasitic infections. The objective of this study was to investigate the effect of vitamin E supplementation on an artificial Haemonchus contortus (H. contortus) infection in immature lambs. Twenty Dorset lambs were stratified into two treatment groups according to parasite susceptibility. Worm-free lambs, 28 to 32 weeks of age, were supplemented with vitamin E (d-α-tocopherol) for twelve weeks following the recommendations of the National Research Council for minimal daily requirement (VE5; 5.3 IU/kg body weight (BW)/day (d), n=10) or optimal immune function (VE10; 10 IU/kg BW/d, n = 10). Five weeks after initiation of vitamin E supplementation, lambs were infected with 10,000 H. contortus L3 larvae. Samples were taken weekly for determination of fecal egg counts (FEC), packed cell volume (PCV), and serum α-tocopherol. After six weeks of infection, the lambs were humanely slaughtered for the determination of tissue vitamin E content, worm burden and histologic evaluation of the abomasum. Increased dietary vitamin E supplementation had no effect on liver (P=0.08), muscle (P=0.62), or lymph node (P=0.38) α-tocopherol content. There was no effect of treatment on FEC or PCV, however there was a 49% reduction in total abomasal worm burden (P=0.002) in the VE10 group. These results indicate that elevated levels of vitamin E supplementation had a beneficial effect on the abomasal worm burden; however, there was no treatment effect on PCV or FEC.
Post-Traumatic Stress Disorder Symptoms Among Children of Kathmandu 1 Year After the 2015 Earthquake in Nepal

Abstract Objective The 2015 earthquake in Nepal affected the country in terms of economy, and by causing damage and stress reactions. This study aimed to estimate the prevalence and determine individual child- and family-level predictors of post-traumatic stress disorder (PTSD) symptoms. Methods A community-based cross-sectional study was carried out in Kathmandu district 15 months after the earthquake. Multistage cluster sampling was adopted to collect 800 earthquake-affected children aged 7-16 years and a face-to-face interview was conducted. Trauma exposure questionnaire and Child PTSD Symptoms Scale were used for assessment of the level of exposure and PTSD symptoms. Multilevel generalized linear regression analysis was used to explore individual and family-level predictors. Results Among the children, 51% had moderate-to-severe PTSD symptoms. Children of school age (adjusted odds ratio=2.83 [1.45-5.49]), those attending lower-secondary school (2.26 [1.21-4.21]), those having a higher exposure to the severity of the earthquake, and those with low psychosocial acuity [1.70 (1.10-2.60)] were more likely to have more severe PTSD symptoms compared with those who were adolescents and in higher-secondary school, whereas children from a family living in an urban (0.33 [0.19-0.59]) setting and following Hindu religion (0.31 [0.16-0.60]) were less likely to have PTSD symptoms compared with children from suburban areas and those following Buddhist religion. Conclusion PTSD symptoms were prevalent among children of Nepal more than a year following the earthquake. Family-level indicators cannot be excluded when studying children’s trauma reactions. (Disaster Med Public Health Preparedness. 2018;12:486–492)
Modelling and Analysis of Network Security - An Algebraic Approach

Game theory has been applied to investigate network security. But different security scenarios were often modeled via different types of games and analyzed in an ad-hoc manner. In this paper, we propose an algebraic approach for modeling and analyzing uniformly several types of network security games. This approach is based on a probabilistic extension of the value-passing Calculus of Communicating Systems (CCS), which is a common formal language for modeling concurrent systems. Our approach gives a uniform security model for different security scenarios. We present then a uniform algorithm for computing the Nash equilibria strategies on this security model. In a nutshell, the algorithm first generates a network state transition graph for our security model, then simplifies this transition graph through graph-theoretic abstraction and bisimulation minimization. Then, a backward induction method, which is only applicable to finite tree models, can be used to compute all the Nash equilibria strategies of the (possibly infinite) security models. This algorithm is implemented and can be tuned smoothly for computing its social optimal strategies, and its termination and correctness are proved. The effectiveness and efficiency of this approach are demonstrated with two detailed examples from the field of network security.
Bone Marrow-Derived Stem Cell Populations Are Differentially Regulated by Thyroid or/and Ovarian Hormone Loss

Bone marrow-derived stem cells (BMDSCs) play an essential role in organ repair and regeneration. The molecular mechanisms by which hormones control BMDSCs proliferation and differentiation are unclear. Our aim in this study was to investigate how a lack of ovarian or/and thyroid hormones affects stem cell number in bone marrow lineage. To examine the effect of thyroid or/and ovarian hormones on the proliferative activity of BMDSCs, we removed the thyroid or/and the ovaries of adult female rats. An absence of ovarian and thyroid hormones was confirmed by Pap staining and Thyroid Stimulating Hormone (TSH) measurement, respectively. To obtain the stem cells from the bone marrow, we punctured the iliac crest, and aspirated and isolated cells by using a density gradient. Specific markers were used by cytometry to identify the different BMDSCs types: endothelial progenitor cells (EPCs), precursor B cells/pro-B cells, and mesenchymal stem cells (MSCs). Interestingly, our results showed that hypothyroidism caused a significant increase in the percentage of EPCs, whereas a lack of ovarian hormones significantly increased the precursor B cells/pro-B cells. Moreover, the removal of both glands led to increased MSCs. In conclusion, both ovarian and thyroid hormones appear to have key and diverse roles in regulating the proliferation of cells populations of the bone marrow.
Mutations in N-acetylglucosamine (O-GlcNAc) transferase in patients with X-linked intellectual disability

N-Acetylglucosamine (O-GlcNAc) transferase (OGT) regulates protein O-GlcNAcylation, an essential and dynamic post-translational modification. The O-GlcNAc modification is present on numerous nuclear and cytosolic proteins and has been implicated in essential cellular functions such as signaling and gene expression. Accordingly, altered levels of protein O-GlcNAcylation have been associated with developmental defects and neurodegeneration. However, mutations in the OGT gene have not yet been functionally confirmed in humans. Here, we report on two hemizygous mutations in OGT in individuals with X-linked intellectual disability (XLID) and dysmorphic features: one missense mutation (p.Arg284Pro) and one mutation leading to a splicing defect (c.463–6T>G). Both mutations reside in the tetratricopeptide repeats of OGT that are essential for substrate recognition. We observed slightly reduced levels of OGT protein and reduced levels of its opposing enzyme O-GlcNAcase in both patient-derived fibroblasts, but global O-GlcNAc levels appeared to be unaffected. Our data suggest that mutant cells attempt to maintain global O-GlcNAcylation by down-regulating O-GlcNAcase expression. We also found that the c.463–6T>G mutation leads to aberrant mRNA splicing, but no stable truncated protein was detected in the corresponding patient-derived fibroblasts. Recombinant OGT bearing the p.Arg284Pro mutation was prone to unfolding and exhibited reduced glycosylation activity against a complex array of glycosylation substrates and proteolytic processing of the transcription factor host cell factor 1, which is also encoded by an XLID-associated gene. We conclude that defects in O-GlcNAc homeostasis and host cell factor 1 proteolysis may play roles in mediation of XLID in individuals with OGT mutations.
On the context dependence of emotion displays: Perceptions of gold medalists’ expressions of pride

ABSTRACT In spite of various claims for cross-cultural differences in the experience of pride, studies on the expression of pride have revealed few cross-cultural differences. Five studies using archival data from Olympic and national championships do show cross-cultural differences in the expression of pride and other positive emotions in pride-eliciting contexts, contingent on the social context of the expression, notably the in-group or out-group status of the audience. Chinese gold medalists were perceived to express less pride than American medalists when outperforming in-group competitors; when outperforming out-group members, however, no or smaller cross-cultural differences were observed. These findings are important because they indicate that cultural norms about emotion expression may be activated only in situations in which they serve a function in coordinating people's behaviour.
The Structure of a National Elite Network

This paper addresses a long-disputed issue: the degree of integration among political elites in the United States. This issue is examined through an investigation of the structure of an elite interaction network as revealed by recently developed procedures for network analysis. The data, taken from the American Leadership Study conducted by the Bureau of Applied Social Research in 1971 and 1972, consist of interviews with 545 leaders of major political, economic and social institutions. The study's wide institutional representation, sociometric data, and focus on major issues of the early 1970s make it virtually unique for examining elite integration.
Box Aggregation for Proposal Decimation: Last Mile of Object Detection

Regions-with-convolutional-neural-network (RCNN) is now a commonly employed object detection pipeline. Its main steps, i.e., proposal generation and convolutional neural network (CNN) feature extraction, have been intensively investigated. We focus on the last step of the system to aggregate thousands of scored box proposals into final object prediction, which we call proposal decimation. We show this step can be enhanced with a very simple box aggregation function by considering statistical properties of proposals with respect to ground truth objects. Our method is with extremely light-weight computation, while it yields an improvement of 3.7% in mAP on PASCAL VOC 2007 test. We explain why it works using some statistics in this paper.
Mutual Information Bounds via Adjacency Events

The mutual information between two jointly distributed random variables X and Y is a functional of the joint distribution PXY, which is sometimes difficult to handle or estimate. A coarser description of the statistical behavior of (X, Y) is given by the marginal distributions PX, PY and the adjacency relation induced by the joint distribution, where x and y are adjacent if P(x, y) > 0. We derive a lower bound on the mutual information in terms of these entities. The bound is obtained by viewing the channel from X to Y as a probability distribution on a set of possible actions, where an action determines the output for any possible input, and is independently drawn. We also provide an alternative proof based on convex optimization that yields a generally tighter bound. Finally, we derive an upper bound on the mutual information in terms of adjacency events between the action and the pair (X, Y), where in this case, an action a and a pair (x, y) are adjacent if y = a(x). As an example, we apply our bounds to the binary deletion channel and show that for the special case of an independent identically distributed input distribution and a range of deletion probabilities, our lower and upper bounds both outperform the best known bounds for the mutual information.
Evaluation of controlled prescriptions with a diagnosis of surgical intervention.

OBJECTIVE Drugs subject to control (DSC) are commonly used in the preoperative, per-operative and postoperative periods. In this study, details of DSC use, that are required to be prescribed to green prescriptions (GP) or red prescriptions (RP), for a surgical diagnosis were evaluated. MATERIAL AND METHODS Controlled drug prescriptions (CDP) between January to December 2009 were investigated in the archives of the Istanbul Local Health Authority. 660 CDPs indicating a surgical diagnosis were retrospectively evaluated and those prescribed by surgical departments (SD)were compared to those written by internal medicine departments (ID). RESULTS SD physicians prescribed 72.7% of CDPs and 89.5% of prescriptions were for GP, and 10.5% were for RP. The physicians of SD were found to prescribe more RP than ID physicians. Most of the CDPs were written for women (58.8%) and mostly in private hospitals (40.9%). Among all the physicians, orthopedic surgeons prescribed these drugs the most (20.9%). Tramadol was the most common drug found in CDPs (55.5%). CONCLUSION DSCs, which have difficult prescription procedures, are used frequently in surgical interventions. The study shows that not only SD physicians, but also ID physicians prefer CDP. The study provides important clues to the usage patterns of DSCs. Recently evolving health care systems including prescriptions should use these findings obtained from the study.