Miracle-dz/UniFAR-FTUs huggingface dataset:
A 4-approximation for scheduling on a single machine with general cost function

We consider a single machine scheduling problem that seeks to minimize a generalized cost function: given a subset of jobs we must order them so as to minimize $\sum f_j(C_j)$, where $C_j$ is the completion time of job $j$ and $f_j$ is a job-dependent cost function. This problem has received a considerably amount of attention lately, partly because it generalizes a large number of sequencing problems while still allowing constant approximation guarantees. In a recent paper, Cheung and Shmoys provided a primal-dual algorithm for the problem and claimed that is a 2-approximation. In this paper we show that their analysis cannot yield an approximation guarantee better than $4$. We then cast their algorithm as a local ratio algorithm and show that in fact it has an approximation ratio of $4$. Additionally, we consider a more general problem where jobs has release dates and can be preempted. For this version we give a $4\kappa$-approximation algorithm where $\kappa$ is the number of distinct release dates.
Minimal Solvers for Relative Pose with a Single Unknown Radial Distortion

In this paper, we study the problems of estimating relative pose between two cameras in the presence of radial distortion. Specifically, we consider minimal problems where one of the cameras has no or known radial distortion. There are three useful cases for this setup with a single unknown distortion: (i) fundamental matrix estimation where the two cameras are uncalibrated, (ii) essential matrix estimation for a partially calibrated camera pair, (iii) essential matrix estimation for one calibrated camera and one camera with unknown focal length. We study the parameterization of these three problems and derive fast polynomial solvers based on Gröbner basis methods. We demonstrate the numerical stability of the solvers on synthetic data. The minimal solvers have also been applied to real imagery with convincing results.
Phase Variation of Ag43 Is Independent of the Oxidation State of OxyR

ABSTRACT OxyR is a DNA binding protein that differentially regulates a cell's response to hydrogen peroxide-mediated oxidative stress. We previously reported that the reduced form of OxyR is sufficient for repression of transcription of agn43 from unmethylated template DNA, which is essential for deoxyadenosine methylase (Dam)- and OxyR-dependent phase variation of agn43. Here we provide evidence that the oxidized form of OxyR [OxyR(ox)] also represses agn43 transcription. In vivo, we found that exogenous addition of hydrogen peroxide, sufficient to oxidize OxyR, did not affect the expression of agn43. OxyR(ox) repressed in vitro transcription but only from an unmethylated agn43 template. The −10 sequence of the promoter and three Dam target sequences were protected in an in vitro DNase I footprint assay by OxyR(ox). Furthermore, OxyR(ox) bound to the agn43 regulatory region DNA with an affinity similar to that for the regulatory regions of katG and oxyS, which are activated by OxyR(ox), indicating that binding at agn43 can occur at biologically relevant concentrations. OxyR-dependent regulation of Ag43 expression is therefore unusual in firstly that OxyR binding at agn43 is dependent on the methylation state of Dam target sequences in its binding site and secondly that OxyR-dependent repression appears to be independent of hydrogen-peroxide mediated oxidative stress and the oxidation state of OxyR.
Natural Orifice Transluminal Endoscopic Surgery-Assisted Laparoscopic Transvesical Bladder Diverticulectomy: Feasibility Study, Points of Technique, and Case Series with Medium-Term Follow-Up.

OBJECTIVES To demonstrate the feasibility of our novel natural orifice transluminal endoscopic surgery (NOTES)-assisted approach with medium-term follow-up. PATIENTS AND METHODS From March 2012, we included all patients who presented to our clinic with symptomatic or complicated retentive bladder diverticula secondary to long-standing infravesical obstruction. After managing the primary cause, we proceeded in all cases to our novel NOTES-assisted approach. We followed up the patients with abdominal ultrasonography at 6 weeks and 12 months postoperatively. Success was determined as subjective relief of the symptoms and objective disappearance of the diverticula in postoperative retrograde cystogram (RGC). RESULTS Between March 2012 and August 2014, eight diverticula were treated using our new technique. The surgery was uneventful. The mean operative time was 134.25 ± 44.92 minutes. Blood loss was minimal (>50 mL). Retrograde cystography was performed on the 10th postoperative day. The introduction of the needle holder through the urethral natural orifice (NOTES) facilitated a more optimal direction of the needle holder for suturing the bladder wall due to its parallel position in relation to the trigone and posterolateral walls. This renders this step easier compared with suturing the bladder wall through the transvesical laparoscopic ports. One case had a grade IIIa complication according to the Clavien-Dindo classification of surgical complications. The study is limited by the small number of cases. CONCLUSION Laparoscopic transvesical bladder diverticulectomy is a promising and safe procedure with good outcomes. Using the urethra (NOTES assisted) as an extra access to the bladder facilitates diverticular traction and bladder suturing without the need for extra ports. This technique can also be applied together with the novel T-laparoendoscopic single-site surgery approach.
An Improved Kernel Density Estimation Approach for Moving Objects Detection

Moving object detection based on monitoring video system is often a challenging problem. Specially to moni- tor traffic at both day and night, in different weather and illumination conditions and with changeable background. Kernel Density Estimation (KDE) model is an effective approach to judge background and foreground, however, typical KDE uses fixed parameters, such as bandwidths, threshold, etc. This paper proposes a detection algorithm based on an Im- proved Kernel Density Estimation (IKDE) model. The proper bandwidths, adaptive background sample learning array, and adaptive threshold, and an improved sample updating method for sample learning array are discussed as the funda- mentals of the IKDE model. Furthermore, an algorithm for restraining light field disturbance at night in video scene is proposed. Video image series are evaluated through the algorithm, and moving object detection is conducted in three dif- ferent scenes. Results show that the algorithm can help to achieve a promising high accuracy and robustness for detecting moving objects.
Combining Research and Pedagogy in the Development of a Crosslinguistic Grammar Resource

This paper describes how a graduate course in multilingual grammar engineering has been used to inform the development of the LinGO Grammar Matrix. When the course was first taught (in 2004), the Grammar Matrix consisted only of the cross-linguistic core grammar. Over time, the lab instructions for the students in the course sparked the development of extensions to the Matrix providing ‘libraries’ of analyses of crosslinguistically variable phenomena. At the same time, the students’ course work has provided valuable feedback both in error checking of the core grammar and refinement of the libraries. Based on the experience of teaching this class for four years, I suggest that grammar engineering courses present a rich opportunity for the combination of pedagogy and research. Involving even beginning grammar engineers in on-going investigations can be rewarding for all involved.
An Empirical Analysis of Constructing Non-restrictive NP Modifiers to Express Semantic Relations

It is not a rare phenomenon for human written text to use non-restrictive NP modifiers to express essential pieces of information or support the situation presented in the main proposition containing the NP, for example, "Private Eye, which couldn't afford the libel payment, had been threatened with closure. " (from Wall Street Journal) Yet no previous research in NLG investigates this in detail. This paper describes corpus analysis and a psycholinguistic experiment regarding the acceptability of using non-restrictive NP modifiers to express semantic relations that might normally be signalled by 'because' and 'then'. The experiment tests several relevant factors and enables us to accept or reject a number of hypotheses. The results are incorporated into an NLG system based on a Genetic Algorithm.
Computed Tomography of Virally Induced Canine Brain Tumors: A Preliminary Report

Seven neonatal dogs were inoculated intracerebrally with Avian Sarcoma Virus (ASV) and studied by computed tomography (CT) for intracranial tumors. The tumor yield was five anaplastic astrocytomas and two sarcomas, with an average latency of 57 days. Computed tomography accurately detected all tumors over 5 mm in diameter and predicted the size of the tumors within 3 mm. The intensity of contrast enhancement was directly related to the dose of Conray-60°. The area of enhancement on the CT scan correlated precisely with tumor permeability as determined histologically with horseradish peroxidase (HRP). Edema seen in CT scans correlated well with edema present in histological sections. Peritumoral edema was impermeable to both Conray-60° and HRP. The ASV-induced canine brain tumor model appears well suited for future CT studies.
Second Language Listening - Investigating Self-supporting Needs

In most of the ESL classrooms in Sri Lanka among four basic language skills, Listening Comprehension (LC) is almost neglected due to many practical reasons; in some classrooms LC is conducted; but the achievement rate is not satisfactory; to recognize part of the solution for this problem, the primary objective of this investigation was to recognize the peculiar listening comprehension (LC) issues encountered by the Tamil medium first year undergraduates in the Faculty of Arts during transactional listening and suggest feasible and effective recommendations for the stakeholders based on classroom investigation. In order to accomplish this objective, 27 Tamil medium ESL first year listeners were randomly selected as sample population in the Faculty of Arts and a classroom investigation employing an intervention programme for one complete semester was conducted; the intervention programme incorporated some specially selected LC texts/activities, participant observation and verbal report. Having employed qualitative methodology with the questionnaire, participant observation and retrospective report, this study, at the end, found out that the ESL listeners' comprehension level progressed dramatically when training was provided with specially selected texts with appropriate support needs to match our listeners' requirements.
An Unexpected Crisis

Social and political theory in the twentieth century envisioned the flourishing of both democracy and the information economy. But while the digital revolution has promoted freedom of expression and freedom of information, it has had mixed effects on the freedom of the press. Throughout the advanced democratic world –more acutely in some countries than in others –the rise of digital communications has undermined the financial condition and economic independence of the press. New media have not, as of yet, offset losses in more traditional media. With its high dependence on advertising revenue, American journalism has been especially vulnerable to stress. In the late twentieth century, observers expected the news media in Europe to evolve in an American direction; instead American journalism has been moving in a more European direction –more partisan and less financially secure –though public policy in the United States shows no signs of adjusting to the new realities.
Understanding younger and older adults' perceptions of humanoid robots: effects of facial appearance and task

Although humanoid robots are being designed to assist people in various tasks, there remain gaps in our understanding of the perceptions that humanoid faces evoke in the user. Understanding user perceptions would help design robots that are better suited for the target user group. Younger and older adults’ preferences for robot appearance were assessed out of three levels of human-likeness. In general, people perceived a mixed human-robot appearance less favorably compared to highly human and highly robotic appearances. Additionally the nature of task also influenced people’s overall perceptions of robots. Robots were most positively evaluated for assistance with chores and less positively for personal care and decision-making. Moreover, task and robot humanness had an interactive effect on people’s likability, trust, and perceived usefulness toward robots. Age-related differences in preferences of robot humanness were also observed. Older adults showed a higher inclination toward human-looking appearance of robots whereas younger adults’ preferences were more distributed across the levels of humanness. An appearance with mixed human-robot features was more likely to be rejected by older adults than by younger adults, and the difference was most striking for a decision-making task. Besides the humanness of the robot face, perceptions of robot appearances were also influenced by factors such as robot gender, specific facial features/aesthetics, expressiveness, perceived personality, and perceived capability. Future studies should measure the relative weight of these different factors in the formation of perceptions, both at a global level and at a task-specific level.
Stability and predictability of the classification of mild cognitive impairment as assessed by episodic memory test performance over time

This study aimed to address the criteria and the stability of the classification of MCI. The Foresight Challenge cohort of 157 community-dwelling volunteers was assessed on 3 visits at 2-year intervals with episodic, semantic and working memory tests. Subjective memory complaints were assessed with the CAMDEX. Of the cohort, 2% had dementia and 31% were classified with MCI at visit 3, 43% with stable impairment from Time 1. Thirteen percent of those with objective memory impairment at Time 1 or 2 improved to control status by Time 3. Episodic memory tests were predictive for MCI at all timepoints, as were tests for praxis and Graded Naming, while at Time 3 spatial span lost predictive value, but processing speed became predictive. Decline in processing speed was seen in control and MCI groups, while memory performance and MMSE decline occurred only in the MCI group. The use of combined memory test scores gave better sensitivity to MCI than single tests. Subjective memory complaints were positive for 79% of the MCI group and 62.5% of controls. These findings would suggest consideration of modification of current MCI criteria. Our chief acknowledgement is to the individuals who volunteered to participate in the study. We acknowledge the support of Professor David Smith and Elizabeth King at OPTIMA and are grateful to the research nurses for administering the baseline screening tests. This work was supported by grants from the Medical Research Council, The Norman Collisson Foundation and The Clore Duffield Foundation.
Artificial Neural Network : A Brief Overview

Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. Neural networks, have remarkable ability to derive meaning from complicated or imprecise data, can be used to extract patterns and detect trends that are too complex to be noticed by either humans or other computer techniques. A trained neural network can be thought of as an "expert" in the category of information it has been given to analyze. This expert can then be used to provide projections given new situations of interest and answer "what if" questions. so in this paper we tried to introduce a brief overview of ANN to help researchers in their way throw ANN.
AggFlow: Scalable and Efficient Network Address Virtualization on Software Defined Networking

In this paper, we propose AggFlow, a new address virtualization scheme for high scalability and resource efficiency. AggFlow is intended to provide complete address virtualization while incurring low overhead for physical switches and the control channel. To reduce overhead of address virtualization, we propose mapping-less address virtualization. We additionally introduce hop-by-hop-based forwarding, which aggregates flow rules installed in physical switches. This leads to efficient use of ternary content addressable memory and bandwidth of the control channel. Our evaluation using Mininet with simple linear and tree topologies, the flow table size of the core switch is reduced up to 1/16 for both topologies, and the control channel traffic decreases by 51% and 29% respectively. Furthermore, we measure the overhead incurred from AggFlow. Compared to OpenVirteX, AggFlow increases control plane delay by 0.1 ms, only 0.4% increase of CPU usage, and no change of throughput for UDP traffic.
Augmented reality sandbox: a platform for educative experiences

In this paper, we describe the implementation of an Augmented Reality Sandbox as a platform for educative experiences. Usually, the traditional Augmented Reality experiences, where the interface is a screen of a mobile devices, here the interface is real sand. It can form real landscapes where a virtual layer of information is displayed. We constructed the Sandbox from open source software and with accessible hardware. In this paper we discuss the special features of this installation, we evaluate the bottlenecks toward its implementation in real classrooms and the contents that can be teach together with the expected benefits.
Dissemination of the novel plasmid-mediated beta-lactamase CTX-1, which confers resistance to broad-spectrum cephalosporins, and its inhibition by beta-lactamase inhibitors

The novel beta-lactamase CTX-1 (pI 6.3) encoded on a transferable 84-kilobase plasmid was found in six different bacterial species. It was responsible for a significant decrease in susceptibility towards most penicillins and cephalosporins, except imipenem, temocillin, and cephalosporins which have a 7-alpha-methoxy substituent. Synergy between either ampicillin, piperacillin, cefotaxime, ceftazidime, or aztreonam and three beta-lactamase inhibitors (clavulanic acid, sulbactam, and YTR 830) was generally found for different strains harboring CTX-1. This enzyme may be related to or derived from the TEM enzyme, since an intragenic probe of the TEM-1 gene hybridized with a fragment of the plasmid carrying CTX-1.
The Challenge of Measuring Financial Impacts From Investments in Corporate Social Performance

There is a small, but positive, relationship between corporate social performance and company financial performance. However, research in this area has provided little guidance to managers on how they should measure the financial impacts of their CSP strategies. Commonly used market measures, such as share price, or accounting measures, such as return on equity, are impacted by a host of other variables. These metrics do not provide the necessary level of detail for managers who want to establish an optimal level of CSP investment for their company. Further, academic research has tended to overlook the mediation process between CSP and financial performance. This gap limits the practical application of research and leaves the question of causality unaddressed. The author reviews the research examining the business case for CSP from both the academic and practitioner literatures, and provide recommendations for managers interested in measuring the impacts of CSP investment on financial performance.
Visual monitoring of surface deformations on objects manipulated with a robotic hand

Nowadays dexterous manipulation of rigid objects using a robot hand can be achieved fairly well. However, grasping and manipulating deformable objects is still challenging as the force and tactile sensors which are commonly used in such applications can only provide local information about the deformation at the contact points. In this paper, a vision framework is proposed for 3D visually guided grasping and manipulation of deformable objects. This visual monitoring framework, which uses state-of-the-art computer vision methods, provides a robotic hand system with comprehensive monitoring of the deformable object that it manipulates as it tracks its deformation. Stereoscopic vision is used to detect and track in real time the deformation of non-rigid objects in three dimensions and within a complex environment. The technique is tested successfully in real robotic operation conditions using the Barrett hand. The actual object shape is rendered in the 3D virtual environment of the GraspIt! robotic simulator which also displays the hand configuration.
Cybercrime Profiling: Decision-Tree Induction, Examining Perceptions of Internet Risk and Cybercrime Victimisation

The Internet can be a double-edged sword. While offering a range of benefits, it also provides an opportunity for criminals to extend their work to areas previously unimagined. Every country faces the same challenges regarding the fight against cybercrime and how to effectively promote security for its citizens and organisations. The main aim of this study is to introduce and apply a data-mining technique (decision-tree) to cybercrime profiling. This paper also aims to draw attention to the growing number of cybercrime victims, and the relationship between online behaviour and computer victimisation. This study used secondhand data collected for a study was carried out using Jordan a s a case study to investigate whether or not individuals effectively protect themselves against cybercrime, and to examine how perception of law influences actions towards incidents of cybercrime. In Jordan, cybercafe's have become culturally acceptable alternatives for individuals wishing to access the Internet in private, away from the prying eyes of society.
Profile-based direct kernels for remote homology detection and fold recognition

MOTIVATION Protein remote homology detection is a central problem in computational biology. Supervised learning algorithms based on support vector machines are currently one of the most effective methods for remote homology detection. The performance of these methods depends on how the protein sequences are modeled and on the method used to compute the kernel function between them. RESULTS We introduce two classes of kernel functions that are constructed by combining sequence profiles with new and existing approaches for determining the similarity between pairs of protein sequences. These kernels are constructed directly from these explicit protein similarity measures and employ effective profile-to-profile scoring schemes for measuring the similarity between pairs of proteins. Experiments with remote homology detection and fold recognition problems show that these kernels are capable of producing results that are substantially better than those produced by all of the existing state-of-the-art SVM-based methods. In addition, the experiments show that these kernels, even when used in the absence of profiles, produce results that are better than those produced by existing non-profile-based schemes. AVAILABILITY The programs for computing the various kernel functions are available on request from the authors.