Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning agents based intelligent transport and routing systems for autonomous vehicles and their respective vehicle control systems based on model predictive control (MPC)

Our research primarily focuses on developing mechanisms to intelligently route autonomous vehicles in an urban area while managing to reduce traffic congestion. We propose an Intelligent Transportation System for Autonomous vehicles based on Multi-Agent paradigm. These agents observe traffic conditions over a period of time. Historical traffic information along with information of factors that affects traffic(like weather conditions) are used to develop a regression based learning algorithm that predicts time required to traverse a route for a given time-slot, which can be used to find out shortest path for a given source-destination pair, before beginning to travel. This estimated traverse time for every lane is communicated to the vehicles. Based on this information, the vehicles find out k shortest paths. Reservation based protocols are used to obtain a single path such that the overall congestion is minimized and the destination is reached in the shortest possible time. The shortest path obtained is then traversed with the help the vehicle control system with optimized fuel efficiency, ensuring vehicle stability and obstacle avoidance. To achieve this path trajectory, we used nonlinear Model Predictive control (MPC) approach based on bicycle model of vehicle dynamics. The main advantage of MPC is the fact that it allows the current time-slot to be optimized, while taking future time-slots into account. We further investigate the linear MPC strategies for Co-operative adaptive Cruise control which directly minimizes the fuel consumption.
The Epidemiology of UK University Football Injuries within the 2011-2012 Season

Although football is one of the most popular sports worldwide, there have been very few studies on injuries suffered at university level. The aim of this study was to collate a wide range of epidemiological findings representative of the injuries suffered by those who play football at this level; while also comparing those injuries suffered between males and females. An electronic retrospective questionnaire was completed by 183 British University level footballers (males n=99, females n=84) who had sustained an injury during the 2011-12 season. The dominant lower limb (ankle: 29.5%, knee: 19.7%) was found as the most common site of injury occurrence with sprains (36. 6%) and muscle strains (23%) reported as the most common types of injury. University players are most often exposed to risk of injury in the autumnal period (20%), whilst playing a competitive match (58.5%) on a grass surface (66.1%) and the severity of injury is high (44.8%). Males reported more groin/thigh and muscle strain injuries compared to females. This study provides a landscape of information in relation to UK university football injuries. There is a need for an injury surveillance initiative to be implemented prospectively involving team doctors and a database of players’ medical records. This, in combination with the results found in this study, will help produce a better evidence base of the epidemiology of injuries at this level which will pave the way for producing preventative strategies that aim to improve the safety of university football participation.
Handwritten Digit Recognition using Slope Detail Features

this paper, new features called Slope Detail (SD) features for handwritten digit recognition have been introduced. These features are based on shape analysis of the digit image and extract slant or slope information. They are effective in obtaining good recognition accuracies. When combined with commonly used features, Slope Detail features enhance the digit recognition accuracy. K- Nearest Neighbour (k-NN) and Support Vector Machine (SVM) algorithms have been used for classification purposes. The data sets used are the Semeion Data Set and United States Postal Service (USPS) Data Set. For the USPS Data Set an error rate of 1.3% was obtained, which has been found to be better than any reported error rate on the said data set. General Terms Histogram Features, OCR, Pattern Recognition, Artificial Intelligence.
Linear Multiuser MIMO Transceiver Design With Quality of Service and Per-Antenna Power Constraints

Joint design of linear multiuser multiple-input-multiple-output (MIMO) transceiver subject to different quality of service (QoS) constraints per user and with per-antenna or antenna group power constraints is considered. Solutions for two linear transceiver optimization problems are proposed, i.e., balancing the weighted signal-to-interference-plus-noise ratio (SINR) per data stream and balancing the weighted rate for each scheduled user with minimum rate requirements per user. The proposed joint transceiver optimization algorithms are compared to corresponding optimal nonlinear transmission methods as well as to generalized zero-forcing transmission solutions. Unlike the optimal nonlinear schemes, the optimization problems employed in the linear multiuser MIMO transceiver design are not convex in general. However, the proposed algorithms are shown to provide very efficient solutions despite of the fact that the global optimum cannot be guaranteed due to nonconvexity of the problems.
Bridging ICT and CS: educational standards for computer science in lower secondary education

Recently, the importance of computer science education in secondary schools has been coming more and more into focus. Students' interests and motivation to pursue a career in CS related fields are highly influenced by school. Also beliefs in the nature of CS are influenced, and necessary foundations in knowledge and skills are built. However, a major problem is the gap between information and communication technologies (ICT) and computer science (CS). Often pupils have only experiences in ICT, and therefore develop inadequate beliefs about CS. We propose educational standards for CS in lower high school in order to bridge ICT and CS.
Appendix A : A functional programming approach to hardware acceleration of algorithms

The aim of this proposal is to develop methods and tools to enable large scale acceleration of algorithms using reconfigurable hardware (Field Programmable Gate Arrays, FPGAs). FPGAs currently contain resources other than just a fabric of computing elements; examples include fast carry chains, embedded DSP circuits that run much faster than the reconfigurable fabric, and embedded processors. These additional resources make FPGAs into very powerful computing platforms, but also demand sophisticated methods if they are to be efficiently exploited. Previous knowledge from the design of algorithmic blocks (such as fast binary adders) for implementation on full custom hardware is not simply transferrable to these augmented FPGAs. A new approach is needed, and we propose one based on functional programming and search. The application areas that we aim to support demand fast data-paths, as distinct from more control oriented computations. They are medium scale cryptography (which demands Montgomery multiplication and exponentiation), large scale correlators and convolvers for astronomy and, finally, fully homomorphic encryption (FHE), which (currently) demands arithmetic on millions of bits, and which, if successfully made practical, will enable secure cloud computing. The proposed research is distinguished from current approaches by:
Financial Development , Property Rights , and Growth 1

This paper investigates how different legal frameworks not only affect the amount of external financing available, but also the allocation of resources among different types of assets. Using a simple model, we show that a firm will get less financing, and thus invest less, in a weaker legal environment. But weaker property rights also lead to an asset allocation effect with firms investing less in intangible assets. Empirically, these two effects appear to be equally important drivers of growth in sectoral value added for a large number of countries. Using individual firm data, we also show that weaker legal frameworks are associated with relatively more fixed assets, but less long-term financing for a given amount of fixed assets. JEL Classifications: G31, G32, K10, O34, and O4 1 The authors are grateful to Sudipto Dasgupta, Enrico Perotti, Sheridan Titman, participants at seminars at Korea University and UADE, Argentina and the Third Annual Conference on Financial Market Development in Emerging and Transition Economies, Hong Kong, June 28-30, 2001 for their comments. The views expressed in this paper are those of the authors and do not necessarily represent those of the World Bank.
Molecular diversity of heparan sulfate.

Heparan sulfate (HS) appeared early in metazoan evolution. As such, many of the structural motifs (variably sulfated disaccharide subunits) that characterize HS (and heparin) were established early on and have been preserved in modern organisms. Thus, many of the biological functions associated with HS either occurred early in evolution or have depended on the subsequent evolution of the protein ligands that bind to the polysaccharide. Today, we know of literally hundreds of heparin-binding proteins, and many interactions have profound consequences in vertebrate and invertebrate physiology. This Perspective aims to provide an overview of HS structure, function, and biosynthesis and to set the stage for discussing the relationship between structure and function of these fascinating molecules and how altered HS biosynthesis and catabolism can lead to human disorders.
Learning Against Non-Stationary Opponents in Double Auctions

Energy markets are emerging around the world. In this context, the PowerTAC competition has gained attention for being a realistic and powerful simulation platform that can be used to perform robust research on retail energy markets. Agent in this complex environment typically use different strategies throughout their interaction, changing from one to another depending on diverse factors, for example, to adapt to population needs and to keep the competitors guessing. This poses a problem for learning algorithms as most of them are not capable of handling changing strategies. The previous champion of the PowerTAC competition is no exception, and is not capable of adapting quickly to non-stationary opponents, potentially impacting its performance. This paper introduces DriftER, an algorithm that learns a model of the opponent and keeps track of its errorrate. When the error-rate increases for several timesteps, the opponent has most likely changed strategy and the agent should learn a new model. Results in the PowerTAC simulator show that DriftER is capable of detecting switches in the opponent faster than an existing state of the art algorithms against switching (non-stationary) opponents obtaining better results in terms of profit and accuracy.
Reactive Oxygen Species and Nitric Oxide in Cutaneous Leishmaniasis

Cutaneous leishmaniasis affects millions of people around the world. Several species of Leishmania infect mouse strains, and murine models closely reproduce the cutaneous lesions caused by the parasite in humans. Mouse models have enabled studies on the pathogenesis and effector mechanisms of host resistance to infection. Here, we review the role of nitric oxide (NO), reactive oxygen species (ROS), and peroxynitrite (ONOO−) in the control of parasites by macrophages, which are both the host cells and the effector cells. We also discuss the role of neutrophil-derived oxygen and nitrogen reactive species during infection with Leishmania. We emphasize the role of these cells in the outcome of leishmaniasis early after infection, before the adaptive Th-cell immune response.
Mental Health and Academic Success in College

Abstract Mental health problems represent a potentially important but relatively unexplored factor in explaining human capital accumulation during college. We conduct the first study, to our knowledge, of how mental health predicts academic success during college in a random longitudinal sample of students. We find that depression is a significant predictor of lower GPA and higher probability of dropping out, particularly among students who also have a positive screen for an anxiety disorder. In within-person estimates using our longitudinal sample, we find again that co-occurring depression and anxiety are associated with lower GPA, and we find that symptoms of eating disorders are also associated with lower GPA. This descriptive study suggests potentially large economic returns from programs to prevent and treat mental health problems among college students, and highlights the policy relevance of evaluating the impact of such programs on academic outcomes using randomized trials.
RADIO FREQUENCY IDENTIFICATION (RFID) BASED ATTENDANCE SYSTEM WITH AUTOMATIC DOOR UNIT

Radio-frequency identification (RFID) is a technology that uses radio waves to transfer data from an electronic tag, called RFID tag or label, attached to an object, through a reader for the purpose of identifying and tracking the object. RFID technology which is a matured technology that has been widely deployed by various organizations as part of their automation systems. In this study, an RFID based system has been built in order to produce a time-attendance management system. This system consists of two main parts which include: the hardware and the software. The hardware consists of the motor unit and the RFID reader. The RFID reader, which is a low-frequency reader (125 kHz), is connected to the host computer via a serial to USB converter cable. The Time-Attendance System GUI was developed using visual basic.Net. The Time-Attendance Management System provides the functionalities of the overall system such as displaying live ID tags transactions, registering ID, deleting ID, recording attendance and other minor functions. This interface was installed in the host computer.
Good Neighbourliness in a Sustainable European Internal Electricity Market: A Tale of Communities and Uncommunautaire Thinking

The internal energy market is much like the ‘normal’ internal market so that the degree of completion is measured by economic interpenetration. This means that the more business is done across the border, the more the market has transformed from a national market to the internal market. This is coupled to a desire to come to a sustainable, i.e. more environmentally friendly and secure, energy production and supply. The objectives of market integration and sustainability lead to increasing interconnections between national energy systems and the corresponding need to take into account the effects of national policies on neighbouring countries. This contribution will examine how the principle of good neighbourliness can already be identified - albeit embryonically - in current EU sustainable energy policy. It also investigates whether and how this principle can form a useful framework to come to a sustainable European internal electricity market. It starts, however, by first identifying what this principle may entail with the use of similar concepts in small communities and how this may be contrasted when the communities become less relevant and neighbourliness is operationalised in a hierarchical setting.
Transferring Boosted Detectors Towards Viewpoint and Scene Adaptiveness

In object detection, disparities in distributions between the training samples and the test ones are often inevitable, resulting in degraded performance for application scenarios. In this paper, we focus on the disparities caused by viewpoint and scene changes and propose an efficient solution to these particular cases by adapting generic detectors, assuming boosting style. A pretrained boosting-style detector encodes a priori knowledge in the form of selected features and weak classifier weighting. Towards adaptiveness, the selected features are shifted to the most discriminative locations and scales to compensate for the possible appearance variations. Moreover, the weighting coefficients are further adapted with covariate boost, which maximally utilizes the related training data to enrich the limited new examples. Extensive experiments validate the proposed adaptation mechanism towards viewpoint and scene adaptiveness and show encouraging improvement on detection accuracy over state-of-the-art methods.
Water Decoction of Coptidis Rhizoma Prevents Oxidative Damage in Erythrocytes of Mice

Coptidis Rhizoma (Coptis chinensis) has been reported to have antioxidative effect on hemolysis of erythrocytes induced by acetylphenylhydrazine in mice and rats. However, the ability of Coptidis Rhizoma to protect structure and function of erythrocytes membrane and morphology of erythrocytes against oxidative damage remains unknown. In this study, we undertook a characterization of antioxidative activity in erythrocytes membrane of Coptidis Rhizoma using an in vivo model of acetylphenylhydrazine-induced mice together with in vitro studies with 2,2-azo-bis (2-amidinopropane) dihydrochloride-induced erythrocytes for further morphology characterization. Acetylphenylhydrazine-induced mice were treated intragastrically with Coptidis Rhizoma at doses of 0.3, 0.6, and 1.2 g/kg per day for 3 days and at the dose of 0.6 and 1.2 g/kg it showed that there was an increasing trend in membranes cytoskeletal proteins of band I-IV, especially a significant upregulation in band II. Significant increase in phosphatidylserine and phosphatidylcholine content at the dose of 1.2 g/kg Coptidis Rhizoma was obsereved. At all doses of Coptidis Rhizoma, the declined membrane fluidity of acetylphenylhydrazine-induced mice was significantly increased. In addition, at the dose of 1.2 g/kg Coptidis Rhizoma treatment showed a significant increase in Ca2+/Mg2+-ATPase activity and there was an increasing trend in the activity of Na+/K+-ATPase. In vitro, Coptidis Rhizoma protected erythrocytes from 2,2-azo-bis (2-amidinopropane) dihydrochloride-induced hemolysis in a dose-dependent manner at concentrations of 0.25-1.5 mg/ml, and also significantly inhibited the 2,2-azo-bis (2-amidinopropane) dihydrochloride-induced morphological alterations in mice erythrocytes. These results demonstrate that Coptidis Rhizoma is capable of protecting erythrocytes against oxidative damage probably by acting as an antioxidant and maintaining membrane integrity.
European preferences for beef steak attributes

A choice experiment is used to evaluate how consumers in London, Frankfurt, and Paris value beef steaks with attributes such as: "hormone-free," "GM-free," farm-specific source verification, and domestic origin. The effect of various consumer characteristics on steak selection is also evaluated. Results suggest that European consumers are significantly heterogeneous in their preferences for beef steak attributes. French and German consumers have a higher willingness to pay to avoid genetically modified feed use than British consumers, while German and British consumers would pay more for growth hormone-free beef. French and German consumers are willing to pay for farm-specific source verification.
Clustered Causal Ordering

Causal arguments are ubiquitous in human reasoning about physical phenomena. Formalization and computer modeling of these arguments is a major goal of qualitative physics. Building causal qualitative models of rich domains like classical thermodynamics has proven to be difficult . The most accessible and widely agreed upon source of knowledge is found in textbooks, usually in the form of noncausal mathematical equations. Iwasaki and Simon's causal ordering procedure addresses this problem by attempting to extract causality directly from mathematical equations . This paper examines the causal ordering procedure from the point of view of qualitative process theory. We illustrate how causal ordering is dependent on the choice of exogenous variables which in turn requires consideration of the many ways in which a system can interact with its surroundings . In other words, it suffers from environmental instability . This paper shows how directly influenced quantities can be used to find environmentally stable causal clusters. Because of their stability, causal clusters can be studied in isolation and used as building blocks in a broad range of environments . We demonstrate our ideas in the domain of thermodynamics by uncovering the causality of the Ideal Gas Law and Joule's temperature-internal energy relation .
Intersegmental Coordination in the Kinematics of Prehension Movements of Macaques

The most popular model to explain how prehensile movements are organized assumes that they comprise two “components”, the reaching component encoding information regarding the object’s spatial location and the grasping component encoding information on the object’s intrinsic properties such as size and shape. Comparative kinematic studies on grasping behavior in the humans and in macaques have been carried out to investigate the similarities and differences existing across the two species. Although these studies seem to favor the hypothesis that macaques and humans share a number of kinematic features it remains unclear how the reaching and grasping components are coordinated during prehension movements in free-ranging macaque monkeys. Twelve hours of video footage was filmed of the monkeys as they snatched food items from one another (i.e., snatching) or collect them in the absence of competitors (i.e., unconstrained). The video samples were analyzed frame-by-frame using digitization techniques developed to perform two-dimensional post-hoc kinematic analyses of the two types of actions. The results indicate that only for the snatching condition when the reaching variability increased there was an increase in the amplitude of maximum grip aperture. Besides, the start of a break-point along the deceleration phase of the velocity profile correlated with the time at which maximum grip aperture occurred. These findings suggest that macaques can spatially and temporally couple the reaching and the grasping components when there is pressure to act quickly. They offer a substantial contribution to the debate about the nature of how prehensile actions are programmed.
Investigation of the Interaction between the Large and Small Subunits of Potato ADP-Glucose Pyrophosphorylase

ADP-glucose pyrophosphorylase (AGPase), a key allosteric enzyme involved in higher plant starch biosynthesis, is composed of pairs of large (LS) and small subunits (SS). Current evidence indicates that the two subunit types play distinct roles in enzyme function. Recently the heterotetrameric structure of potato AGPase has been modeled. In the current study, we have applied the molecular mechanics generalized born surface area (MM-GBSA) method and identified critical amino acids of the potato AGPase LS and SS subunits that interact with each other during the native heterotetrameric structure formation. We have further shown the role of the LS amino acids in subunit-subunit interaction by yeast two-hybrid, bacterial complementation assay and native gel. Comparison of the computational results with the experiments has indicated that the backbone energy contribution (rather than the side chain energies) of the interface residues is more important in identifying critical residues. We have found that lateral interaction of the LS-SS is much stronger than the longitudinal one, and it is mainly mediated by hydrophobic interactions. This study will not only enhance our understanding of the interaction between the SS and the LS of AGPase, but will also enable us to engineer proteins to obtain better assembled variants of AGPase which can be used for the improvement of plant yield.