Miracle-dz/UniFAR-FTUs huggingface dataset:
Prefrontal dysfunction in drug addiction: Cause or consequence?

With at least 15,3 million people suffering from illicit drug use disorders and many more alcohol and tobacco abusers, addiction is a worldwide problem that puts a great burden on society. Traditionally, research has focused on the reinforcing effects of drugs of abuse and the underlying neuronal mechanisms. The mesolimbic dopaminergic pathway is now generally accepted as the main target for drugs of abuse and their motivational value. Recently, however, the involvement of other brain areas in developing the addicted state has gained interest, especially the prefrontal cortex. This region is essential in inhibitory control processes which have been demonstrated to be dysfunctional in people suffering from addiction. The present report focuses on the dissimilarities between prefrontal cortex functioning of the addicted brain and healthy controls. Furthermore, this study discusses whether the abnormalities in prefrontal functioning exhibited by substance abusers are preexisting vulnerability traits which lead to addiction or, alternatively, are induced by repeated exposure to drugs of abuse. Accumulating evidence, particularly from animal studies, supports the latter hypothesis by demonstrating drug-induced structural alterations in the prefrontal cortex and drug-induced abnormal behavior associated with prefrontal regions. Nevertheless, some human studies have revealed individual differences which might predict the susceptibility for developing drug addiction. It is postulated that while underdeveloped prefrontal functioning may reflect a predisposition for drug taking and addiction, the drug-induced alterations are likely to facilitate the transitions from drug use to addiction.
defIned VehIculAr networks : ArchItectures , AlgorIthms And ApplIcAtIons

Vehicles have embedded software dedicated to diverse functionality ranging from driving assistance to entertainment. Vehicle manufacturers often need to perform updates on software installed on vehicles. Software updates can either be pushed by the manufacturer to install fixes, or be requested by vehicle owners to upgrade some functionality. We propose an architecture for distributing software updates on vehicles based on SDN and cloud computing. We show that using SDN, the emergent networking paradigm, which provides on-demand network programmability, adds substantial flexibility for deploying software updates on vehicles. We propose solutions for how vehicular networks can be modeled as connectivity graphs that can be used as input for the SDN architecture. After constructing graphs, we present an SDN-based solution where different frequency bands are assigned to different graph edges to improve the network performance.
SparkL Large-scale distributed data analytics for weakly-connected clusters

Systems for large-scale distributed data analytics have been studied extensively and deployed in many commercial production environments. However, most of these systems are deployed within data centers with strongly-connected networks and large bisection bandwidths, but emerging applications require more flexible scheduling methods to optimize overall system performance in spite of network constraints. For example, military use cases may require data and computation to occur thousands of miles apart, as data is generated from sensors in the field and computation occurs in data centers. At the same time, though these sensors are weakly connected to the data-centers, the data analytics may still need to take place in real-time for immediate decision making. After examining existing systems including Apache Spark and Hadoop MapReduce, we designed a novel orchestration framework to optimize these data analytics capabilities in weakly-connected networks. We present SparkL, a system that uses network topology and bandwidth constraints in a software-defined network (SDN) to optimally schedule data analytics jobs in weakly-connected clusters. Our system utilizes linear programming to calculate job assignments, taking into account bandwidth sharing across the network. We implemented a system consisting of a scheduler, an optimization engine, and computation and storage nodes. Our computation and storage nodes exist within an SDN, controlled and monitored by Unicorn and OpenFlow. In our experiments, SparkL can determine optimal bandwidth allocation and job assignments, which leads to decreases in overall job completion time. SparkL has the potential to be extended for use within Spark and other big data frameworks to orchestrate data analytics in large-scale, real-world applications. ACM Reference Format: Kristina Shia and Anushree Agrawal. 2018. SparkL: Large-scale distributed data analytics for weakly-connected clusters.
Examining the shared development of socialist political economics with Chinese characteristics

Purpose – The shared development concept is crucial for the construction of a socialist political economy with Chinese characteristics. The paper aims to discuss this issue. Design/methodology/approach – This is because shared development constitutes the logic thread of the socialist political economy with Chinese characteristics and the core for the formation and development of its whole system. Findings – China’s modernization is well underway and is following a unique path with its own characteristics, whereby shared development is undoubtedly one of its core values. Originality/value – In the new era, the development path under the concept of shared development of socialism with Chinese characteristics must adhere to the all-round development of human beings, promote social equity and justice via development, and embrace inclusive growth, specifically, pro-poor growth.
Conditional Adversarial Networks Assisted Road Extraction in Remote Sensing Imagery

In this paper, we narrow down the task for conditional adversarial networks focusing on solving the binary segmentation problem for road extraction on remote sensing imagery. We constrain the objective of the generator of a conditional adversarial network to make it suitable to produce binary road predictions in an effective way. We evaluate our approach on the SpaceNet Roads dataset and our method shows promising results compared to standard segmentation models. Our best pixel level precision score on test set is 76.9%. This paper shows that adversarial networks with detailed images as input and binary mask as output can be optimized with certain adaption and optimization tweaks, showing potentials in solving computer vision problems.
Effect of Tag Anchor Location on Retention / Survival through Molt in Male Snow Crabs Chionoecetes opilio

Science Branch. Department of Fisheries and Oceans P.O. Box 5667. St. John's, Newfoundland AIC 5XI. Canada Effect of Tag Anchor Location on Retention/Survival through Molt in Male Snow Crabs Chionoecetes opilio Abstract.A laboratory study showed that when small male snow crabs are tagged with the anchor of a t-bar tag inserted into the dorsal musculature, tag retention and survival through the first molt are excellent; when the tag anchor is situated in the basal leg musculature, animals die while molting. When recaptures were obtained from larger, field-tagged animals, it was noted that some animals which had molted had been tagged in the leg musculature. Dissections were performed on 43 animals which molted and 89 animals which did not molt to determine tag anchor placement. Four general locations were noted: dorsal musculature, basal leg musculature, loose in the body cavity, and attached internally to carapace. Relative tag retention/survival associated with molting was estimated for the different tag anchor locations by comparing the proportions of tags in each location among animals which molted and among those which did not. Animals with anchors in the leg musculature appeared to survive and retain the tag through a molt as well as those tagged in the dorsal musculature and those with the tag attached to the inside of the carapace. Animals with anchors loose in the body cavity appeared to have worse tag retention/survival than those tagged in the dorsal musculature. The hypothesis that tag placement does not affect retention/survival through molt was tested by fitting hierarchical loglinear models and testing for a significant interaction between molt status (i.e., did or did not molt) and tag anchor location. No statistically significant effect was found, but it still seems prudent to try to place tag anchors into the dorsal musculature.
Research on 3D virtual high performance multimodal mesh simplification and display system

: In order to achieve a smooth three-dimensional display effect, this paper studies the triangle mesh simplification algorithm, mesh simplification of the three-dimensional model. Based on the typical virtual reality HMD HTC VIVE, a three-dimensional display system of automobile model is designed. Users can experience the realistic 3D effect on the client side and perform basic interactive operation.
The Relationship between Market Orientation, Learning Orientation and Organizational Performance in the Development of New Products

This theoretic essay has the objective to revise the relationship and explore literary reflections between the orientation of learning and organizational development for the market in light of new products. This orientation is for learning and development of organizational fulfillment or performance in light of the development of new products. Undoubtedly this is an analysis of the relationship between these three favorable pillars, resulting in the creation of propositions that will either benefit or cause difficulties in the development of new products (DNP). To put into practice the proposed objective, suggested propositions were elaborated in studies of each fundamental pillar in relationship with the DNP to take note the manner in which the same were tackled in the past until now and how they are treated in literature today. Market orientation is the capacity of the business to generate and dissimulate information concerning the very market obtaining the answers to the questions. Learning attained promotes the development of skills and encourages competition thus giving incentive, instigating curiosity to improve performance furthermore forming critical reflections on the organizational presumptions. The organizational performance is relational to the application of the available resources to obtain the objectives. In some way, these foundational pillars are connected and directly or indirectly influence the development of new products (DNP). The pillars are approached in constructed proposition with literary base where their relationships are discussed. In tackling these propositions in light of literary investigations, positive and negative affirmatives were concluded.
Multi-body Dynamics : Spline Joint

This project is heavily based on Lee’s work[1]. The essential contribution of spline joint is introducing approximation methods in SE(3) to the joint space. It can also be considered as a general way of defining minimum joint coordinates. Such methods are helpful for simulating the complex human joints like the thumb. The extension to 2-DOF spline joints and its application to the thumb modeling are explored in this project.
The influence of shelf information on consumers ’ wine choice

Prior research on consumer choice of wine has focused on information on the bottle itself, such as brand, region, grape variety and awards. We add to this stream of research by considering information on the shelf, such as short descriptions of the taste of the wine and ratings by independent agencies. Participants chose wines from two different simulated retail shelves, one containing photographs of real wine bottles and one containing graphics of simulated wine bottles. The greatest increase in choice probability was generated by star ratings followed by numerical ratings, and then by taste descriptions. Implications for retailers and future research are discussed.
AIS Electronic Library (AISeL)

Each day cybercrime attacks are getting more frequent, dangerous and sophisticated. In 2016 the FBI’s Internet Crime Complaint Center received 1,408,849 complaints and a reported loss of $4.63 billion. The concept of cybercrime is complex, and as such the drive to overcome the problem is very difficult. However, the continual escalation of cybercrimes can have a negative impact on businesses and by extension the economies of countries. As a result, it is imperative that measures be identified to overcome the problem. Hence, this study seeks to propose a research model which can be used to evaluate the significance of cybercrime in deterring the use of e-banking in the financial sector. It is hoped that the proposed research model will influence other researchers to conduct empirical research in their context.
Extended Abstract : Type-Directed Program Repair

PROBLEM AND MOTIVATION Programmers working in modern object-oriented languages often need to compose several large, complicated libraries together with in-house code while developing enterprise software. As these libraries evolve, legacy code that depends on deprecated declarations sometimes breaks. Many different transformations can break legacy code. For example, changing the name or signature of a function, changing the type hierarchy, or removing a deprecated declaration will leave behind expressions that are well-formed, but ill-typed. While such code will still reflect the programmer’s intent, it will no longer compile, and will need correction.
Special Section on Image Media Quality Pyramid Predictive Attention Network for Medical Image Segmentation

In this paper, we propose a Pyramid Predictive Attention Network (PPAN) for medical image segmentation. In the medical field, the size of dataset generally restricts the performance of deep CNN and deploying the trained network with gross parameters into the terminal device with limitedmemory is an expectation. Our teamaims to the future homemedical diagnosis and search for lightweight medical image segmentation network. Therefore, we designed PPAN mainly made of Xception blocks which are modified from DeepLab v3+ and consist of separable depthwise convolutions to speed up the computation and reduce the parameters. Meanwhile, by utilizing pyramid predictions from each dimension stage will guide the network more accessible to optimize the training process towards the final segmentation target without degrading the performance. IoU metric is used for the evaluation on the test dataset. We compared our designed network performance with the current state of the art segmentation networks on our RGB tongue dataset which was captured by the developed TIAS system for tongue diagnosis. Our designed network reduced 80 percentage parameters compared to the most widely used U-Net in medical image segmentation and achieved similar or better performance. Any terminal with limited storage which is needed a segment of RGB image can refer to our designed PPAN. key words: PPAN, CNN, predictive, separable, IoU, segmentation, medical
Does Aid for Trade Diversify the Export Structure of Recipient Countries ?

The importance of aid for trade as a tool for facilitating trade, economic growth, and social development has received attention since the concept was introduced in 2005. While one of the main targets of aid for trade is export diversification, reflecting the fact that the exports of many developing countries are concentrated in a small range of items, there have not been many efforts to measure the effect of aid for trade on export structure. This study, therefore, attempts to trace the relationship between aid for trade and 133 aid recipients’ export structure between 1996 and 2013. Using the Herfindahl–Hirschman Index (HHI) to measure the degree of export concentration, the findings suggest that, total aid for trade has reduced the concentration level in the short-run. In the long-run, on the other hand, aid for trade has had no significant effect on export structure of recipient countries. Only aid for building productive capacity, which is one of the three categories of aid for trade, contributes to lower concentration. Yet, this change is not caused by an increase in export diversity but by the redistribution of shares of existing products of a similar sophistication level.
ESTIMATION OF LOW CLOUD BASE HEIGHTS AT NIGHT FROM SATELLITE INFRARED AND SURFACE TEMPERATURE DATA

A nighttime low cloud image product that highlights areas of the lowest cloud base heights has been developed by combining brightness temperature data from the Geostationary Operational Environmental SateZZite (GOES) Imager InfraRed (fR) bands centered at 3.9 Jlm and 10.7 Jlm, with hourly temperatures from surface observing sites and offshore marine buoys. A dependent data sample collected during the Summer of 1997 showed a fairly strong correlation between the surface minus cloud top IR temperature differences versus measured cloud base heights. Histogram analysis indicated that a temperature difference of less than 4 °C related to a > 50% probability of ceilings below 1000 ft above ground level, the threshold for Instrument Flight Rules (fFR). Using the Man-computer Interactive Data Analysis System (McIDAS) software, an experimental Low Cloud Base (LCE) image product was developed that highlights regions of likely IFR ceilings. The image product is routinely available from GOES8 and GOES-l0 hourly at night for six regions in the Continental United States via a Web site (orbit-net.nesdis.noaa.govlaradlfpdtlfog.html). Validation of the LCB product for two separate periods resulted in Probabilities of Detection of 67% and 72% and False Alarm Rates of 6% and 11 %. Some regional variation was observed that could be related to the frequency of multi-layered overcast conditions. The biggest factor leading to under-detection of IFR ceilings by the GOES LCB is the presence of overlying clouds, including thin cirrus contamination. Although further improvements are planned, the prototype GOES LCB product shows potential for use as guidance for aviation meteorologists over both continental and marine areas.
English 2-1-2019 Directions for the future of technology in pronunciation research and teaching

This paper reports on the role of technology in state-of-the-art pronunciation research and instruction, and makes concrete suggestions for future developments. The point of departure for this contribution is that the goal of second language (L2) pronunciation research and teaching should be enhanced comprehensibility and intelligibility as opposed to native-likeness. Three main areas are covered here. We begin with a presentation of advanced uses of pronunciation technology in research with a special focus on the expertise required to carry out even small-scale investigations. Next, we discuss the nature of data in pronunciation research, pointing to ways in which future work can build on advances in corpus research and crowdsourcing. Finally, we consider how these insights pave the way for researchers and developers working to create researchinformed, computer-assisted pronunciation teaching resources. We conclude with predictions for future developments.
Establishing the Spillover of Pro-Environmental Behaviour Phenomenon Using Structural Equation Modelling Analysis

Positive spillover behaviour is defined as the constructive effects of an individual’s working life on their personal and family life. Employees working in organizations that are committed to environmental protection, and who are routinely performing environmentally related activities within their job responsibilities, could have their behaviour significantly affecting their general attitudes and norms toward the environment. This study proposed that these acquired attitude and norms will also be seen as relevant to the person’s social dimension outside the organization especially at home, since the responsibility of protecting the environment is equally important both while inside and outside the organization. Using the Structural Equation Modelling, the spillover of pro-environmental behaviour phenomenon has empirically been established. It is hope that the findings from this study could justify and thus encourage organizations to positively contribute to the core issue of environmental problem, which is the development of an environmentally responsible individual. Key-Words: spillover behavior, employee organizational identification, environmental management system
Feeder Realization for Quasi-lumped Multilayer Resonators with Low Q-factor DEJAN MILJANOVI

A novel feeder realization for a quasi-lumped multilayer resonator with low external Q-factor is proposed. The resonator is realized as a double-sided microstrip resonator with two quasi-lumped elements: a square spiral inductor and a microstrip patch capacitor. Each quasi-lumped element is printed on separate layer (the upper and the lower dielectric layers are separated by a common ground plane). In this paper, we propose two types of the input/output coupling structure. The resonator inductor is coupled by (1) coupled-lines or (2) saw-toothed structure. The saw-toothed coupling structure is used to increase coupling at the feed port, i.e. realize a lower external quality factor. The design methodology is exemplified by a second-order multilayer bandpass filter that is based on the proposed feeder realization. Key-Words: External Q-factor, multilayer resonator, double-sided microstrip, saw-toothed coupled structures
GENE EXPRESSION PROFILING IN BONE TISSUE OF OSTEOPOROTIC MICE

Ovaricetomized (OVX) animals represent an optimal model to investigate bone loss in osteoporosis. To further elucidate the underlying mechanisms of decreased bone formation and increased bone resorption following OVX, we conducted gene expression profiling experiments using bone samples of ovariectomized C57BL/6J mice. Following OVX, genes involved in immune response, cell cycle regulation, growth, apoptosis and bone resorption were upregulated, while genes that are important for regular cell processes, mitosis, metabolism of carbohydrates, extracellular matrix structure, angiogenesis, skeletal development and morphogenesis were downregulated. Among bone specific genes we observed upregulation of interleukin 7 (IL-7), IL-7 receptor and matrix metallopeptidase 8, while genes such as transforming growth factor-beta 3, procollagen type I and procollagen type VI exhibited marked decrease in expression. We also observed downregulation of two genes, parathyroid hormone receptor 1 and WD repeat domain 5, that are involved in skeletal development but were not previously reported to be altered in osteoporosis. We further performed gene set enrichment analysis (GSEA) in order to calculate enrichment of pathways specifically altered in murine bones following ovariectomy. In conclusion, OVX greatly influences expression of various genes involved in diverse biological processes confirming the notion that numerous pathways play an important role in pathophysiology of osteoporosis.