Miracle-dz/UniFAR-FTUs huggingface dataset:
A Seeded Search for the Modularisation of Sequential Software Versions

Software module clustering is the process of partitioning the structure of the software system using low-level dependencies in the source code in order to understand and improve the system’s structure. A software clustering tool, Munch, was used to modularise sequential source code software check-ins to assess the degree of major changes. It uses a searchbased software engineering technique. This paper employs a seeding technique, based on results from previous modularisations, to speed up the process and reduce the running time. In order to evaluate the efficiency of the modularisation we conducted a number of experiments on our uniquely large and comprehensive real-world dataset. The results of the experiments present strong evidence to support the seeding strategy. Keywords clustering; modularisation; refactoring; seeding; time-series; fitness function; EVM; EVMD.
Genome-wide association study of exercise behavior in Dutch and American adults.

INTRODUCTION The objective of this study was to identify genetic variants that are associated with adult leisure time exercise behavior using genome-wide association (GWA) in two independent samples. METHODS Exercise behavior was measured in 1644 unrelated Dutch and 978 unrelated American adults of European ancestry with detailed questions about type, frequency, and duration of exercise. Individuals were classified into regular exercisers or nonexercisers using a threshold of 4 MET·h (metabolic equivalents-hours per week). GWA analyses of ∼1.6 million observed and imputed Single Nucleotide Polymorphism (SNP) were conducted in both samples independently using logistic regression in SNPTEST, including sex, age, and body mass index as covariates. A meta-analysis of the results was performed using the weighted inverse variance method in METAL. RESULTS Thirty-seven novel SNPs in the PAPSS2 gene and in two intergenic regions on chromosomes 2q33.1 and 18p11.32 were associated with exercise participation (pooled P values <1.0 × 10(-5)). Previously reported associations (ACE, CASR, CYP19A1, DRD2, LEPR, and MC4R genes) or linkage findings (2p22.3, 4q28, 4q31.21 7p13, 9q31, 11p15, 13q22, 15q13, 18q12.2, 18q21.1, 19p13.3, and 20q12) were not replicated, although suggestive evidence was found for association to rs12405556 in the LEPR gene (pooled P value 9.7 × 10(-4); American sample, P value 9.8 × 10(-5)) and for association to rs8036270 in the GABRG3 gene (pooled P value 4.6 × 10(-5)) in the linkage region 15q12-13. CONCLUSIONS The heritability of leisure time exercise behavior is likely to be accounted for by many genetic variants with small effect size. These can be detected by GWA as was shown here for the PAPSS2 gene, but larger samples with genome-wide genotypes and high-quality exercise data are needed for further progress.
Enhanced solubility of piperine using hydrophilic carrier-based potent solid dispersion systems

Abstract Context: Piperine alkaloid, an important constituent of black pepper, exhibits numerous therapeutic properties, whereas its usage as a drug is limited due to its poor solubility in aqueous medium, which leads to poor bioavailability. Objective: Herein, a new method has been developed to improve the solubility of this drug based on the development of solid dispersions with improved dissolution rate using hydrophilic carriers such as sorbitol (Sor), polyethylene glycol (PEG) and polyvinyl pyrrolidone K30 (PVP) by solvent method. Physical mixtures of piperine and carriers were also prepared for comparison. Methods: The physicochemical properties of the prepared solid dispersions were examined using SEM, TEM, DSC, XRD and FT-IR. In vitro dissolution profile of the solid dispersions was recorded and compared with that of the pure piperine and physical mixtures. The effect of these carriers on the aqueous solubility of piperine has been investigated. Results: The solid dispersions of piperine with Sor, PEG and PVP exhibited superior performance for the dissolution of piperine with a drug release of 70%, 76% and 89%, respectively after 2 h compared to physical mixtures and pure piperine, which could be due to its transformation from crystalline to amorphous form as well as the attachment of hydrophilic carriers to the surface of poorly water-soluble piperine. Conclusion: Results suggest that the piperine solid dispersions prepared with improved in vitro release exhibit potential advantage in delivering poorly water-soluble piperine as an oral supplement.
Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks

This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.
Modelling of micro pollutant emissions to water and evaluation of reduction measures

The reduction of micro pollutant emissions into surface waters is one important target of the European water policy. For a number of micro pollutants the municipal wastewater system is the dominant input pathway. For those pollutants the emissions via combined sewer overflows, storm water outlets and waste water treatment plants were quantified. The model MoRE (Modelling of Regionalized Emissions) considering a number of further pathways (point and diffuse sources) was used to create an overall picture of the given emissions. The resulting loads were subsequently used to calculate average concentrations in the receiving water bodies. Based on these results, hot spots of pollution and needs for measures were identified. A set of individual measures and combinations of measures were implemented into the MoRE system to assess their reduction potential. The results clearly highlight that a combination of preventive and end-of-pipe measures is necessary to achieve and maintain a good chemical status in line with the Water Framework Directive.
Prevalence of Dementia in the United States: The Aging, Demographics, and Memory Study

Aim: To estimate the prevalence of Alzheimer’s disease (AD) and other dementias in the USA using a nationally representative sample. Methods: The Aging, Demographics, and Memory Study sample was composed of 856 individuals aged 71 years and older from the nationally representative Health and Retirement Study (HRS) who were evaluated for dementia using a comprehensive in-home assessment. An expert consensus panel used this information to assign a diagnosis of normal cognition, cognitive impairment but not demented, or dementia (and dementia subtype). Using sampling weights derived from the HRS, we estimated the national prevalence of dementia, AD and vascular dementia by age and gender. Results: The prevalence of dementia among individuals aged 71 and older was 13.9%, comprising about 3.4 million individuals in the USA in 2002. The corresponding values for AD were 9.7% and 2.4 million individuals. Dementia prevalence increased with age, from 5.0% of those aged 71–79 years to 37.4% of those aged 90 and older. Conclusions: Dementia prevalence estimates from this first nationally representative population-based study of dementia in the USA to include subjects from all regions of the country can provide essential information for effective planning for the impending healthcare needs of the large and increasing number of individuals at risk for dementia as our population ages.
Novel Feature Modelling the Prediction and Detection of sEMG Muscle Fatigue towards an Automated Wearable System

Surface Electromyography (sEMG) activity of the biceps muscle was recorded from ten subjects performing isometric contraction until fatigue. A novel feature (1D spectro_std) was used to extract the feature that modeled three classes of fatigue, which enabled the prediction and detection of fatigue. Initial results of class separation were encouraging, discriminating between the three classes of fatigue, a longitudinal classification on Non-Fatigue and Transition-to-Fatigue shows 81.58% correct classification with accuracy 0.74 of correct predictions while the longitudinal classification on Transition-to-Fatigue and Fatigue showed lower average correct classification of 66.51% with a positive classification accuracy 0.73 of correct prediction. Comparison of the 1D spectro_std with other sEMG fatigue features on the same dataset show a significant improvement in classification, where results show a significant 20.58% (p < 0.01) improvement when using the 1D spectro_std to classify Non-Fatigue and Transition-to-Fatigue. In classifying Transition-to-Fatigue and Fatigue results also show a significant improvement over the other features giving 8.14% (p < 0.05) on average of all compared features.
Estimating dominant runoff modes across the conterminous United States

Effective natural resource planning depends on understanding the prevalence of runoff generating processes. Within a specific area of interest, this demands reproducible, straightforward information that can complement available local data and can orient and guide stakeholders with diverse training and backgrounds. To address this demand within the contiguous United States (CONUS), we characterized and mapped the predominance of two primary runoff generating processes: infiltration‐excess and saturation‐excess runoff (IE vs. SE, respectively). Specifically, we constructed a gap‐filled grid of surficial saturated hydraulic conductivity using the Soil Survey Geographic and State Soil Geographic soils databases. We then compared surficial saturated hydraulic conductivity values with 1‐hr rainfall‐frequency estimates across a range of return intervals derived from CONUS‐scale random forest models. This assessment of the prevalence of IE versus SE runoff also incorporated a simple uncertainty analysis, as well as a case study of how the approach could be used to evaluate future alterations in runoff processes resulting from climate change. We found a low likelihood of IE runoff on undisturbed soils over much of CONUS for 1‐hr storms with return intervals <5 years. Conversely, IE runoff is most likely in the Central United States (i.e., Texas, Louisiana, Kansas, Missouri, Iowa, Nebraska, and Western South Dakota), and the relative predominance of runoff types is highly sensitive to the accuracy of the estimated soil properties. Leveraging publicly available data sets and reproducible workflows, our approach offers greater understanding of predominant runoff generating processes over a continental extent and expands the technical resources available to environmental planners, regulators, and modellers.
A novel time-frequency feature extraction for movie audio signals classification

Most of short time-frequency feature (TFF) extraction methods in the literature only consider scale and frequency of the selected atoms, which neglects the effect of expansion coefficient and time of the selected atoms. In order to classify movie audio signals better, an effective and flexible time-frequency feature extraction method using expansion coefficient, scale, time and frequency of the selected atoms is investigated in this work, which consists of four stages: signal decomposition, Wigner-Ville distribution, principal component extraction and clustering. The experimental results show that the proposed TFF is better than the traditional TFF, which can improve 6% in accuracy for classifying twenty kinds of movie audio signals. The best dimension number of the proposed TFF is 25.
Using Statutes-Based IR to Drive Legal CBR

$EVWUDFW(cid:17) We present and discuss the use of Information Retrieval (IR) to drive Case-Based Reasoning (CBR) in legal case retrieval. This is a hybrid IR-CBR approach to legal text indexing and retrieval. Our approach is based on our intuitive model of how humans represent, recognize and retrieve concepts. We point out the different components and processes involved in this human mental conceptualization model. We suggest and use Statutes-Seeded Indexing and Retrieval (SSIR) as a simple and suitable technique that can be used as a front-end to legal CBR systems. We view the hybrid approach as a natural simplification to the intense and practically impossible to automate life-long human knowledge acquisition. This simplification, we hope, will make it applicable in areas of open-nature such as law. The different processes and components are modeled as a combinations of IR and CBR. The Open world is simplified as a narrow domain. Thus enabling us to intuitively assume that a subject domain has its limited set of concepts, represented using limited sets of terms, structures, and stereo-typical scenarios. We take advantage of law makers’ efforts put into writing the law to our advantage by using the created statutes as a seed for term extraction in the index and retrieval processes. We demonstrated how to practically use IR as a front end for CBR and obtain useful results in Bankruptcy Case Law. Our prototype system based on this model takes as input a natural language description of a novel situation (case text) and outputs a list of cases similar to the new case.
The Hot Serial Cereal Experiment for modeling wheat response to temperature: field experiments and AgMIP-Wheat multi-model simulations

The data set reported here includes the part of a Hot Serial Cereal Experiment (HSC) experiment recently used in the AgMIP-Wheat project to analyze the uncertainty of 30 wheat models and quantify their response to temperature. The HSC experiment was conducted in an open-field in a semiarid environment in the southwest USA. The data reported herewith include one hard red spring wheat cultivar (Yecora Rojo) sown approximately every six weeks from December to August for a two-year period for a total of 11 planting dates out of the 15 of the entire HSC experiment. The treatments were chosen to avoid any effect of frost on grain yields. On late fall, winter and early spring plantings temperature free-air controlled enhancement (T-FACE) apparatus utilizing infrared heaters with supplemental irrigation were used to increase air temperature by 1.3°C/2.7°C (day/night) with conditions equivalent to raising air temperature at constant relative humidity (i.e. as expected with global warming) during the whole crop growth cycle. Experimental data include local daily weather data, soil characteristics and initial conditions, detailed crop measurements taken at three growth stages during the growth cycle, and cultivar information. Simulations include both daily in-season and end-of-season results from 30 wheat models. Data access via doi 10.7910/DVN/M9ZT0F
MRO Procurement for Business Customers: A Longitudinal Case Study Analysis

Buero-Fuerrer is a company that decided to implement a modern e-procurement solution for B2B customers in the industry of office supplies. The company was looking for an e-commerce software solution for the seamless integration of the procurement process for its business customers. The main objective was the development of a customized software solution which would have a major impact on customer retention and the way procurement processes were handled. Buero-Fuerrer can be called as visionary regarding the consequent implementation of its e-strategy. What was originally seen as a challenge and “nice to have” venture is now the preferred sales channel and an absolute key to market success. Without an e-shop, Buero-Fuerrer would not have managed to become number one in the Swiss B2B stationary market.
Extended Kalman Filter for Real Time Indoor Localization by Fusing WiFi and Smartphone Inertial Sensors

Indoor localization systems using WiFi received signal strength (RSS) or pedestrian dead reckoning (PDR) both have their limitations, such as the RSS fluctuation and the accumulative error of PDR. To exploit their complementary strengths, most existing approaches fuse both systems by a particle filter. However, the particle filter is unsuitable for real time localization on resource-limited smartphones, since it is rather time-consuming and computationally expensive. On the other hand, the light computation fusion approaches including Kalman filter and its variants are inapplicable, since an explicit RSS-location measurement equation and the related noise statistics are unavailable. This paper proposes a novel data fusion framework by using an extended Kalman filter (EKF) to integrate WiFi localization with PDR. To make EKF applicable, we develop a measurement model based on kernel density estimation, which enables accurate WiFi localization and adaptive measurement noise statistics estimation. For the PDR system, we design another EKF based on quaternions for heading estimation by fusing gyroscopes and accelerometers. Experimental results show that the proposed EKF based data fusion approach achieves significant localization accuracy improvement over using WiFi localization or PDR systems alone. Compared with a particle filter, the proposed approach achieves comparable localization accuracy, while it incurs much less computational complexity.
Constructing sub-word units for spoken term detection

Spoken term detection, especially of out-of-vocabulary (OOV) keywords, benefits from the use of sub-word systems. We experiment with different language-independent approaches to sub-word unit generation, generating both syllable-like and morpheme-like units, and demonstrate how the performance of syllable-like units can be improved by artificially increasing the number of unique units. The effect of unit choice is empirically evaluated using the eight languages from the 2016 IARPA BABEL evaluation.
FREE VIEWPOINT IMAGE SYNTHESIS USING UNCALIBRATED MULTIPLE MOVING CAMERAS

We propose a novel method to synthesize free-viewpoint images for a moving object, which is captured by uncalibrated multiple moving cameras. If multiple ﬁxed cameras are used for capturing a moving object, we must zoom out in order to capture the moving object within FOV of the cameras. Such zooming-out limits the resolution for the moving object in the captured images. In the proposed method, we use multiple moving cameras that capture the moving object in the center of the images with high resolution. For shape reconstruction of the object from the uncalibrated multiple moving camera images, two ﬁxed cameras are employed for determining Projective Grid Space, which de-ﬁnes a projective 3D coordinate in the object space. The coordinate in PGS can be related to every moving camera by fundamental matrices between the moving camera and the ﬁxed cameras. In the experiment that is performed for demonstrating the efﬁcacy of the proposed method, high resolution free-viewpoint images can be successfully synthesized by the proposed method.
Task and Motion Planning for Mobile Manipulators by Ioan Alexandru Şucan

Task and Motion Planning for Mobile Manipulators by Ioan Alexandru Şucan This thesis introduces new concepts and algorithms that can be used to solve the simultaneous task and motion planning (STAMP) problem. Given a set of actions a robot could perform, the STAMP problem asks for a sequence of actions that takes the robot to its goal and for motion plans that correspond to the actions in that sequence. This thesis shows how to solve the STAMP problem more efficiently and obtain more robust solutions, when compared to previous work. A solution to the STAMP problem is a prerequisite for most operations complex robots such as mobile manipulators are asked to perform. Solving the STAMP problem efficiently thus expands the range of capabilities for mobile manipulators, and the increased robustness of computed solutions can improve safety. A basic sub-problem of the STAMP problem is motion planning. This thesis generalizes KPIECE, a sampling-based motion planning algorithm designed specifically for planning in high-dimensional spaces. KPIECE offers computational advantages by employing projections from the searched space to lower-dimensional Euclidean spaces for estimating exploration coverage. This thesis further develops the original KPIECE algorithm by introducing a means to automatically generate projections to lower-dimensional Euclidean spaces. KPIECE and other state-of-the-art algorithms are implemented as part the Open Motion Planning Library (OMPL), and the practical applicability of KPIECE and OMPL is demonstrated on the PR2 hardware platform. To solve the STAMP problem, this thesis introduces the concept of a task motion multigraph (TMM), a data structure that can express the ability of mobile manipulators to perform specific tasks using different hardware components. The choice of hardware components determines the state space for motion planning. An algorithm that prioritizes the state spaces for motion planning using TMMs is presented and evaluated. Experimental results show that planning times are reduced by a factor of up to six and solution paths are shortened by a factor of up to four, when considering the available planning options. Finally, an algorithm that considers uncertainty at the task planning level based on generating Markov Decision Process (MDP) problems from TMMs is introduced.
A unified relay framework with both D-F and C-F relay nodes

Decode-and-forward (D-F) and compress-and-forward (C-F) are two fundamentally different relay strategies proposed by (Cover and El Gamal, 1979). Individually, either of them has been successfully generalized to multi-relay channels. In this paper, to allow each relay node the freedom of choosing either of the two strategies, we propose a unified framework, where both the D-F and C-F strategies can be employed simultaneously in the network. It turns out that, to fully incorporate the advantages of both the best known D-F and C-F strategies into a unified framework, the major challenge arises as follows: For the D-F relay nodes to fully utilize the help of the C-F relay nodes, decoding at the D-F relay nodes should not be conducted until all the blocks have been finished; However, in the multi-level D-F strategy, the upstream nodes have to decode prior to the downstream nodes in order to help, which makes simultaneous decoding at all the D-F relay nodes after all the blocks have been finished inapplicable. To tackle this problem, nested blocks combined with backward decoding are used in our framework, so that the D-F relay nodes at different levels can perform backward decoding at different frequencies. As such, the upstream D-F relay nodes can decode before the downstream D-F relay nodes, and the use of backward decoding at each D-F relay node ensures the full exploitation of the help of both the other D-F relay nodes and the C-F relay nodes. The achievable rates under our unified relay framework are found to combine both the best known D-F and C-F achievable rates and include them as special cases.