Miracle-dz/UniFAR-FTUs huggingface dataset:
Prize-Collecting Steiner Tree and Forest in Planar Graphs

We obtain polynomial-time approximation-preserving reductions (up to a factor of 1 + \epsilon) from the prize-collecting Steiner tree and prize-collecting Steiner forest problems in planar graphs to the corresponding problems in graphs of bounded treewidth. We also give an exact algorithm for the prize-collecting Steiner tree problem that runs in polynomial time for graphs of bounded treewidth. This, combined with our reductions, yields a PTAS for the prize-collecting Steiner tree problem in planar graphs and generalizes the PTAS of Borradaile, Klein and Mathieu for the Steiner tree problem in planar graphs. Our results build upon the ideas of Borradaile, Klein and Mathieu and the work of Bateni, Hajiaghayi and Marx on a PTAS for the Steiner forest problem in planar graphs. Our main technical result is on the properties of primal-dual algorithms for Steiner tree and forest problems in general graphs when they are run with scaled up penalties.
Dollar Hegemony and China's Economy

This paper models the US dollar as a global currency and focuses on the effects of US money supply shock upon China's economy. The special roles of US dollar as a global currency and the special institutional arrangements of China are investigated. Given a positive US money supply shock, both the inflation and real GDP of China will be below their steady state levels in the medium term; while for the US there is no inflation pressure. Welfare calculation shows that a positive 10% US money supply shock will result in a positive 1.25% welfare gain for China, a positive 0.06% welfare gain for US, but a 0.21% welfare loss for the rest of the world. Given that the US dollar's hegemony is not weakened, the regime with liberalized capital accounts and an exchange rate peg to the US dollar for China is best for the Chinese households under the US money supply shock. However, when the US dollar is no longer the global reserve currency but instead a supranational reserve currency replaces it, then for China this regime is the worst kind of reform, no matter whether or not the dollar standard in international trade is maintained.
Building Analysis Environments : Beyond the Genome and the Web

Functional genomics is a relatively new field of molecular biology that studies how genomic information defines the functions of proteins in living organisms. The complexity of the domain that functional genomics examines and the amount of data this field produces demand that we adopt powerful computational techniques for data analysis. Advanced natural language processing (NLP) and data mining methods, enriched by ontologies that specify the domain’s semantics, seem to be a promising approach. However, interdisciplinary work will play a key role in this field’s development.
Discretisations of higher order and the theorems of Faà di Bruno and DeMoivre-Laplace

We study discrete functions on equidistant and non-equidistant infinitesimal grids. We consider its difference quotients of higher order and give conditions for their near-equality to the corresponding derivatives. Important tools are the formula of Faa di Bruno for higher order derivatives and a discrete version of it. As an application of such transitions from the discrete to the continuous we extend the DeMoivre-Laplace Theorem to higher order: n-th order difference quotients of the binomial probability distribution tend to the corresponding n-th order partial differential quotients of the Gaussian distribution.
The Affirmative “Yes”. Sexual Offense Based on Consent

The collective rape case that occurred in Spain during a 2016 famous festival placed the trial against its five aggressors on an unprecedented media and social scale in Spain. The court that ruled for sexual abuse and not for rape sparked a huge and prompt social rejection of the current legislation. To overcome revictimization and give voice to survivors, the consideration of consent has been raised. This new paradigm has deeply spread in society and social networks to the point that the Spanish government has expressed its interest in modifying the Criminal Code to base sexual crimes on consent. In our duty to provide scientific knowledge for this issue, this article frames the debate on sexual harassment and focuses on the crime against sexual freedom and the context under which consent can neither be asked for nor conceived. This article analyzes the aggravating crime factors while basing consent on the intention of the offender. Starting from international approaches, this article emphasizes the current social opportunity needed to create awareness and transform laws with the aim of legislating on affirmative “yes”. This approach contributes to the challenge of overcoming gender violence and to the study of masculinities and their influence on social transformation.
Accelerating Viola-Jones Facce Detection Algorithm on GPUs

The Viola-Jones face detection algorithm represents a class of parallel algorithms that both memory accesses and work distributions are irregular, thereby hard to obtain high performance on GPUs. Furthermore, conventional GPU programming wisdom usually guides us on how to optimize data parallel workloads with regular inputs and outputs. While how to efficiently write task-level parallelism programs with irregular workloads have not much material to reference. In this paper, we present an OpenCL-implementation of Viola-Jones face detection algorithm with high performance on both NVIDIA and AMD GPUs through five main techniques: warp size work granularity, persistent threads, Uberkernel, local and global queues. We also demonstrate the high performance of our implementation by comparing it with a well-optimized CPU version from OpenCV library. Experiment results show that the speedup reaches up to 5.193 ~35.08 times (16.91 on average) and 5.85 ~32.641 times (17.535 on average) on AMD and NVIDIA GPU respectively.
Early qualitative risk assessment of the emerging zoonotic potential of animal diseases

Most new human infections are of animal origin, but there is rarely sufficient evidence to make a risk assessment of the zoonotic potential of emerging animal diseases. An algorithm for early qualitative public health risk assessment has been developed to guide risk management Most newly emerging human infections of global importance are of animal origin,1w1 but early accurate predictions of zoonotic risk of emerging animal diseases are difficult, as shown by the epidemic of bovine spongiform encephalopathy and variant Creutzfeldt-Jakob disease in the United Kingdom.w2 Miscalculation, delays, or poor risk communication can result in failure to protect the public's health and undermine public trust,2 but overreaction can waste resources and even harm the economy of countries, as in the case of suspected plague in India.3 The public are increasingly anxious to understand the basis on which a government's decisions on risk management are taken,w3 but scientists and government may be reluctant to engage with the public at an early stage because of the fear of provoking a public scare. However, since the BSE epidemic, it has been accepted that the criteria used and the evidence considered in risk assessments should be open and explicit.4w4 w5 In this article we describe and illustrate such an approach, one that explicitly distinguishes evidence of lack of zoonotic potential from lack of evidence. The algorithm, endorsed by the UK government's Zoonoses Groupw6 and by the National Expert Panel on New and Emerging Infection,w7 is being used by the Human and Animal Infections and Risk Surveillance Group of the Health Protection Agency.5 The algorithm (figure) is used to categorise the evidence of zoonotic potential into four levels (box 1) by considering three key stages in the transmission of zoonoses: Template for qualitative risk assessment …
Design and Optimization of VPN Security Gateway

The VPN security gateway provides authentication, confidentiality, and key management. It checks the security policy database (SPD) so as to deal with the inbound and outbound packets. To optimize the performance of the VPN gateway, we have done the relative works in two aspects. On the one hand, we apply the theory of machine learning to the configuration of security policy database (SPD). And the scheme based on the ID3 decision tree is presented. On the other hand, we apply elliptic curve cryptography (ECC) to the key exchange and design the fast algorithms. Smaller keys can be used in ECC than in other public-key systems, but with equivalent levels of security. With our optimization efforts, the efficiency of the VPN security gateway is enhanced greatly.
Discrete Mobile User Tracking Algorithm via Velocity Estimation for Microcellular Urban Environment

A novel discrete tracking algorithm for mobile user based on velocity estimation in microcellular urban environment is proposed in this paper. By partitioning the mobile path and defining each partition as a state, the proposed algorithm tracks the mobile user based on hidden Markov model (HMM). The short-time Fourier analysis of the received signal strength is employed to estimate the mobile speed. Based on averaged received power (local mean), pathless, velocity estimation and using dynamic programming technique, the proposed algorithm predicts the next state of the mobile user. The proposed tracking algorithm shows good ability to predict user mobility behavior in urban area with multipath fading and shadowing phenomena.
Reachability in K3,3-free and K5-free Graphs is in Unambiguous Logspace

We show that the reachability problem for directed graphs that are either K3,3-free or K5-free is in unambiguous log-space, UL∩ coUL. This significantly extends the result of Bourke, Tewari, and Vinodchandran that the reachability problem for directed planar graphs is in UL∩ coUL. Our algorithm decomposes the graphs into biconnected and triconnected components. This gives a tree structure on these components. The non-planar components are replaced by planar components that maintain the reachability properties. For K5-free graphs we also need a decomposition into 4-connected components. Thereby we provide a logspace reduction to the planar reachability problem. We show the same upper bound for computing distances in K3,3-free and K5-free directed graphs and for computing longest paths in K3,3-free and K5-free directed acyclic graphs.
Energy expenditure and walking speed in lower limb amputees: a cross sectional study.

BACKGROUND Energy expenditure and walking speed are generally recommended for use as measures of status and outcome for walking. The objective of this study was to measure the physiological cost index (PCI) and comfort walking speed (CWS) at three levels of lower limb amputation: transfemoral, transtibial and Syme level, and the relationship of these physiological variables to prosthetic ambulation supported with walking aids and stump length. MATERIAL AND METHODS This study was a prospective cross-sectional study.Eighty-nine individuals with lower limb amputation for reasons other than peripheral vascular disease (PVD) were recruited among patients at the Department of Prosthetics and Orthotics in University Clinical Center of Kosovo. PCI was assessed by five minutes of continuous indoor walking at CWS. RESULTS Significant differences were found in PCI (F=29.87, P < 0.001) and CWS (F=19.33, P < 0.001) among the three amputation groups. Prosthetic ambulation supported with crutches showed an important impact on PCI (F=35.1, P < 0.001) and CWS (F=28.42, P < 0.001). Stump length was associated with significantly increased PCI (r=0.53, P = 0.02) and reduced CWS (r=0.58, P = 0.004) in transfemoral amputees. CONCLUSIONS 1. A higher level of amputation is associated with less energy-efficient walking and with lower walking speed. 2. Prosthetic ambulation supported with crutches has significant impact on increasing of energy expenditure and decreasing walking speed. 3. Stump length is shown to have a major impact on PCI and CWS in transfemoral amputees.
Toward joint liability supply chains: Addressing the root causes of labor violations in international subcontracting networks.

On the morning of April 24, 2013, Rana Plaza, an eight-story building in Bangladesh that housed five garment factories, collapsed, killing at least 1,129 workers.1 The collapse was the most deadly disaster in the history of the global garment industry and, indeed, one of the worst industrial workplace disasters in history.2 Media coverage of the factory collapse and its aftermath fueled a longstanding campaign by a coalition of unions and NGOs to address what had become, well before this latest tragedy, a crisis in building and fire safety in Bangladesh.3 Under intense pressure, within a month of the Rana Plaza collapse, more than three dozen of the world’s largest apparel brands and retailers, including H&M, Inditex (owner of the Zara brand), Tesco, and
Investigative interviewing of suspects in Australia

In Australia the criminal justice system is largely the responsibility of the states (there are six) and territories (two), with each state and territory having its own police force, laws and justice system. The Commonwealth, in the form of the Australian Federal Police, which was established in 1979, only takes responsibility for a limited range of offences, including national and international operations, and peacekeeping (Fleming 2004). Surprisingly little primary research has been conducted in this country on investigative interviews with suspects. Instead, research has tended to focus on perceptions of the investigative process, with studies exploring the views of judges, prosecutors, defence lawyers, police officers, the public and even defendants (e.g. Dixon 2006; Moston and Fisher 2006; Kebbell et al. 2006). The reasons for this particular focus are complex, but centre on a deep-seated distrust (in both directions) between academics and police officers. This chapter will explore what we currently objectively know about investigative interviewing practices in Australia, with data mainly coming from a series of thorough (but narrowly focused) audit commissions, and also how the various players in the criminal justice system see the legislation, technology and operational practice of interviewing. It focuses on the investigative interviewing of suspects in criminal investigations, and thus excludes some interesting and innovative work on the interviewing of children who have witnessed criminal activity (e.g. Wilson and Powell 2001; Powell et al. 2002; Powell and Thomson 2003).
Topic Augmented Neural Response Generation with a Joint Attention Mechanism

We consider incorporating topic information as prior knowledge into the sequence to sequence (Seq2Seq) network structure with attention mechanism for response generation in chatbots. To this end, we propose a topic augmented joint attention based Seq2Seq (TAJA-Seq2Seq) model. In TAJA-Seq2Seq, information from input posts and information from topics related to the posts are simultaneously embedded into vector spaces by a content encoder and a topic encoder respectively. The two kinds of information interact with each other and help calibrate weights of each other in the joint attention mechanism in TAJA2Seq2Seq, and jointly determine the generation of responses in decoding. The model simulates how people behave in conversation and can generate well-focused and informative responses with the help of topic information. Empirical study on large scale human judged generation results show that our model outperforms Seq2Seq with attention on both response quality and diversity.
Bandwidth-Efficient Distributed Estimation in Inhomogeneous Wireless Sensor Networks

This paper presents a distributed estimation scheme (DES) along with the bit allocation algorithm, which minimizes the total required bandwidth while ensuing a given average estimation mean-squared error (MSE). The DES comprises of a probabilistic Lloyd-Max quantization rule, and a best linear unbiased estimation (BLUE). Since the optimum bit allocation problem does not have a closed form, we present a suboptimal solution utilizing the alternating minimization (AM) algorithm. Finally, simulation results are provided to show the effectiveness of the proposed DES along with the bit allocation algorithm.
An Environmentally Extended Input-Output Analysis to Support Sustainable Use of Forest Resources

The use of environmentally extended input-output analysis was demonstrated for quantifying the overall sustainability impacts of forest industries in the Finnish economy in 2005. Direct greenhouse gas emission, land use, employment and import impacts of economic sectors were transformed into impact intensities of products. The intensities were used to construct a final demand based emission inventory demonstrating the relative importance of export, investment and consumption activities in causing environmental and social impacts. The calculations were presented using an aggregated input-ouput table, which makes it possible to repeat the calculations using standard spreadsheet software. Therefore the study can be used as an accessible primer to the use of input-output methods in sustainability assessment.
Insuring Sensitive Processes through Process Mining

Any system, company or complex task is composed by processes, i.e., sequences of actions performed in some established order. Some of these processes are considered sensitive for the role they play within the system, or for the sensitive data they manage. In such cases, the trust in this processes is desirable, requiring their verification, monitoring, auditing, but also the possibility of being insured by a third party. In this approach we propose a schema for insuring sensitive process based on the use of formal models and Process Mining techniques (i.e. process management techniques that allows for the analysis of processes based on event logs). The experimental results presented show that this new approach could be useful in the context of insurance and analysis of processes.
Fuzzy Subset Dependencies

The fuzzy relational databases which use the special types of constraints, called dependencies, as a semantic tool for expressing properties of the data like a classical relational databases. Fuzzy functional dependencies(ffd) and fuzzy multivalued dependencies(fmvd) are the most common types of dependencies. Similar to classical relational database, a full utilization of fuzzy multivalued dependencies in the design of fuzzy relational databases requires that fuzzy embedded multivalued dependencies(fEmvd) and fuzzy subset dependencies(fsd). These multivalued dependencies hold in a projection of a relation but not necessarily in the relation itself. The main object of this paper is to extend the concept of Embedded Multivalued Dependency (EMVD) and Subset Dependency (SD) to fuzzy relational database.
Following Devil's Footprints: Cross-Platform Analysis of Potentially Harmful Libraries on Android and iOS

It is reported recently that legitimate libraries are repackaged for propagating malware. An in-depth analysis of such potentially-harmful libraries (PhaLibs), however, has never been done before, due to the challenges in identifying those libraries whose code can be unavailable online (e.g., removed from the public repositories, spreading underground, etc.). Particularly, for an iOS app, the library it integrates cannot be trivially recovered from its binary code and cannot be analyzed by any publicly available anti-virus (AV) systems. In this paper, we report the first systematic study on PhaLibs across Android and iOS, based upon a key observation that many iOS libraries have Android versions that can potentially be used to understand their behaviors and the relations between the libraries on both sides. To this end, we utilize a methodology that first clusters similar packages from a large number of popular Android apps to identify libraries, and strategically analyze them using AV systems to find PhaLibs. Those libraries are then used to search for their iOS counterparts within Apple apps based upon the invariant features shared cross platforms. On each discovered iOS PhaLib, our approach further identifies its suspicious behaviors that also appear on its Android version and uses the AV system on the Android side to confirm that it is indeed potentially harmful. Running our methodology on 1.3 million Android apps and 140,000 popular iOS apps downloaded from 8 markets, we discovered 117 PhaLibs with 1008 variations on Android and 23 PhaLibs with 706 variations on iOS. Altogether, the Android PhaLibs is found to infect 6.84% of Google Play apps and the iOS libraries are embedded within thousands of iOS apps, 2.94% among those from the official Apple App Store. Looking into the behaviors of the PhaLibs, not only do we discover the recently reported suspicious iOS libraries such as mobiSage, but also their Android counterparts and 6 other back-door libraries never known before. Those libraries are found to contain risky behaviors such as reading from their host apps' keychain, stealthily recording audio and video and even attempting to make phone calls. Our research shows that most Android-side harmful behaviors have been preserved on their corresponding iOS libraries, and further identifies new evidence about libraries repackaging for harmful code propagations on both sides.
To rank or to classify? Annotating stress for reliable PTSD profiling

In this paper we profile the stress responses of patients diagnosed with post-traumatic stress disorder (PTSD) to individual events in the game-based PTSD stress inoculation and exposure virtual environment StartleMart. Thirteen veterans suffering from PTSD play the game while we record their skin conductance. Game logs are used to identify individual events, and continuous decomposition analysis is applied to the skin conductance signals to derive event-related stress responses. The extracted skin conductance features from this analysis are used to profile each individual player in terms of stress response. We observe a large degree of variation across the 13 veterans which further validates the idiosyncratic nature of PTSD physiological manifestations. Further to game data and skin conductance signals we ask PTSD patients to indicate the most stressful event experienced (class-based annotation) and also compare the stress level of all events in a pairwise preference manner (rank-based annotation). We compare the two annotation stress schemes by correlating the self-reports to individual event-based stress manifestations. The self-reports collected through class-based annotation exhibit no correlation to physiological responses, whereas, the pairwise preferences yield significant correlations to all skin conductance features extracted via continuous decomposition analysis. The core findings of the paper suggest that reporting of stress preferences across events yields more reliable data that capture aspects of the stress experienced and that features extracted from skin conductance via continuous decomposition analysis offer appropriate predictors of stress manifestation across PTSD patients.
The Role of Pathogen-Secreted Proteins in Fungal Vascular Wilt Diseases

A limited number of fungi can cause wilting disease in plants through colonization of the vascular system, the most well-known being Verticillium dahliae and Fusarium oxysporum. Like all pathogenic microorganisms, vascular wilt fungi secrete proteins during host colonization. Whole-genome sequencing and proteomics screens have identified many of these proteins, including small, usually cysteine-rich proteins, necrosis-inducing proteins and enzymes. Gene deletion experiments have provided evidence that some of these proteins are required for pathogenicity, while the role of other secreted proteins remains enigmatic. On the other hand, the plant immune system can recognize some secreted proteins or their actions, resulting in disease resistance. We give an overview of proteins currently known to be secreted by vascular wilt fungi and discuss their role in pathogenicity and plant immunity.