Miracle-dz/UniFAR-FTUs huggingface dataset:
An Approach to Concurrent Java Programs Debugging and Run-Time Analysis

With increasing power of today’s computers, the Java programming language is more and more chosen by developers as the implementation language of various types of software. The wide range of applications also include concurrent multithreaded programs. However, programming, analyzing and testing concurrent programs is a problem of a higher order than programming and testing classic sequential programs, even if they are implemented at a high level of abstraction that Java provides. The purpose of this work is to describe an approach to concurrent Java programs debugging and run-time analysis done by means of a simulator of a subset of the JVM functionality and a converter of Java source code. The tested program can be deterministicly traced (just one thread at once) at run-time and the relationships of various entities can be observed and analyzed. As a consequence, the programmer can find potential bugs concerning concurrency issues in a shorter time than when using standard debugging and tracing techniques, usually inefficient for concurrent programs. This paper first summarizes some requirements that a tool implementing this approach should meet, then it presents work related to concurrent programs testing and analysis, done worldwide. Subsequently, it discusses an invented state-space model of concurrent Java programs and a controller based on it, executing the tested program. Finally, it shows how Java programs are transformed in order to use the controller. Chapter 6 concludes the document. Copies of this report are available on http://www.kiv. zcu.cz/publications/ or by surface mail on request sent to the following address: University of West Bohemia in Pilsen Department of Computer Science and Engineering Univerzitni 8 30614 Pilsen Czech Republic Copyright c ©2003 University of West Bohemia in Pilsen, Czech Republic
Weighted Vest Use to Improve Movement Control during Walking in Children with Autism

ABSTRACT Weighted vests (WV) are used to influence behavior through sensory integration in children with autism spectrum disorder (ASD). However, WV effects on motor ability during walking are not well understood in this population despite the growing acceptance that motor impairment is a prominent feature of ASD. This study aimed to evaluate the effects of a WV (15% body mass) on spatial–temporal parameters and the control of the center of mass and the hip, knee, and ankle joints in children with ASD during walking using group and single-subject analyses. Eight male children (11 ± 4 yr, 1.45 ± 0.25 m, 55.28 ± 26.20 kg) with ASD walked overground with and without a WV while three-dimensional kinematic data were obtained. A two-way ANOVA and a model statistic technique (&agr; = 0.05) were used to test for group and single-subject differences, respectively, for stride length, stride time, and smoothness of the center of mass and hip, knee, and ankle joint rotations. At the group level, stride length decreased (P = 0.018) in response to the WV perturbation, although no other differences were detected for any other variable. At the single-subject level, numerous differences (P < 0.05) were detected for each variable, although the differences detected were unique to each individual. WV use can alter gross movement function and body control during walking in some children with ASD. We suggest researchers and clinicians interested in evaluating WV use as a therapeutic modality to mitigate motor impairment in children with ASD proceed at the individual level to reveal individual responses to a WV intervention.
Genetic algorithms for uncapacitated network design

In this thesis, we address the problem of obtaining a "near optimal" solution to the uncapacitated network design problem. In the uncapacitated network design problem, each arc of a network has a fixed design cost for construction and a variable routing cost for routing each unit of flow. For each pair i,j of nodes, there is a demand of one unit of flow from i to j, and flow may only be sent on constructed arcs. We develop a genetic algorithm for solving the uncapacitated network design problem. It starts with a population of individuals and the population evolves by iterations. Each iteration of this genetic algorithm has steps called parental selection, crossover and immigration. We also define termination criteria for determining when the population has converged. The implementation of our genetic algorithm is tested for different problem sizes and several instances in each problem size. The computational results are compared to that of the dual ascent method with drop-add heuristic for the same problem instances. Extensive graphical analysis is performed on the results. We observe that our genetic algorithm is an efficient solution technique to solve uncapacitated network design problems, but is dominated by the dual ascent method with drop-add heuristic. Thesis Supervisor: James B. Orlin Title: Professor To my brother Krishnan
Evaluation of the BAI using ADP in African American Females

Objectives The aim of this study was to determine the agreement between body adiposity index (BAI) and body fat percentage using air displacement plethysmography (ADP) in African American females. Methods Seventy-two African American females (28.9 ± 10.2 yr) participated in the study. Pearson’s correlation coefficients were calculated to determine the relationships among waist circumference, hip circumference (HC), BAI, body mass index (BMI), and %BFADP. Bland–Altman plots were generated to analyze agreement between BAI and %BFADP. Results BAI and BMI were highly correlated with each other and %BFADP. BAI was more accurate in African American females within the normal BMI category but underestimated more in overweight and obese categories. However, the number of false-negative results when evaluating obesity was the same for BAI and BMI within this sample, which suggests their value as a clinical tool may be similar. HC was correlated with %BFADP. However, waist circumference correlated stronger than HC in the obese group. Conclusion The strong correlations of BAI and BMI to body fat percent were similar to previous studies in other races/ethnicities and methods. BAI underestimates body fat percent more with increasing levels of adiposity possibly because of the accumulation of fat in areas not captured by an HC measure.
SURFACE RECONSTRUCTION FROM POINT CLOUD USING LEVEL SET METHOD AND ADAPTIVE GRID

In this paper, we propose a very efficient method which reconstructs the high resolution surface from a set of unorganized points. Our method is based on the level set method using adaptive grid. We start with the surface reconstruction model in [3] as the basic model. In [3], they introduced very fast and efficient method which is different from the previous methods using the level set method. Most existing methods[4][5] employed the time evolving process from an initial surface to point cloud. But in [3] they considered the surface reconstruction process as an elliptic problem in the narrow band including point cloud. So they could obtain very speedy method because they didn’t have to limit the time evolution step by CFL condition. However, they still have the weakness in the reconstruction of some concave shapes e.g. narrow opening because the result depends on how close the initial band and point data are. So they need enough resolution of computational domain to avoid that problem in the uniform grid. We resolve it using the adaptive grid[1][2] and implement more efficient redistancing algorithm than the existing one[6].
Benefits of 24-Week Exergame Intervention on Health-Related Quality of Life and Pain in Women with Fibromyalgia: A Single-Blind, Randomized Controlled Trial.

Objective: To evaluate the effects of 24-week exergame-based intervention on health-related quality of life (HRQoL) and pain in patients with fibromyalgia as well as to analyze the effectiveness of the intervention in subgroups of patients with different pain intensity levels. Design: Single-blinded, randomized controlled trial. Setting: University facilities Participants: Fifty-five women with fibromyalgia participated in the study. Intervention: The exercise group (EG) completed 24 weeks of exergames focused on mobility, postural control, upper and lower limbs coordination, aerobic fitness, and strength. A total of 120 minutes per week, divided into two sessions of 60 minutes, was completed. Main outcome measures: The Euroqol-5 Dimensions-5 Levels (EQ-5D-5L) was used to assess the HRQoL. In addition, pain intensity was measured using a visual analog scale (VAS). Results: Twenty-five out of 28 women allocated to the EG completed the intervention, which means an 89.29% of adherence. They were randomly divided into an exercise (age = 54.04 [8.45]) and a control group (52.72 [9.98]). Significant effects on the perceived health status and pain intensity (P < 0.05) were found. K-means clustering procedure revealed two groups with different response to the intervention. The respond group obtained significant effects of the exergame intervention in EQ-5D-5L, pain VAS, and VAS-EQ, compared with those who did not respond. Conclusions: Exergames could be a useful tool to improve perceived health status and pain intensity level in women with fibromyalgia with a reduced health-related quality of life.
Atlas-based algorithm for automatic anatomical measurements in the knee

Abstract. We present an algorithm for automatic anatomical measurements in tomographic datasets of the knee. The algorithm uses a set of atlases, each consisting of a knee image, surface segmentations of the bones, and locations of landmarks required by the anatomical metrics. A multistage volume-to-volume and surface-to-volume registration is performed to transfer the landmarks from the atlases to the target volume. Manual segmentation of the target volume is not required in this approach. Metrics were computed from the transferred landmarks of a best-matching atlas member (different for each bone), identified based on a mutual information criterion. Leave-one-out validation of the algorithm was performed on 24 scans of the knee obtained using extremity cone-beam computed tomography. Intraclass correlation (ICC) between the algorithm and the expert who generated atlas landmarks was above 0.95 for all metrics. This compares favorably to inter-reader ICC, which varied from 0.19 to 0.95, depending on the metric. Absolute agreement with the expert was also good, with median errors below 0.25 deg for measurements of tibial slope and static alignment, and below 0.2 mm for tibial tuberosity-trochlear groove distance and medial tibial depth. The automatic approach is anticipated to improve measurement workflow and mitigate the effects of operator experience and training on reliability of the metrics.
Pediatric red ear syndrome: A case report of an erythromelalgia type and review of the literature

Red ear syndrome has been reported in the literature to have similarities to erythromelalgia with auricular involvement; however, the distinction between the two is controversial. Red ear syndrome has previously been classified as idiopathic (primary) or secondary, with headaches being the most common association in the idiopathic or primary form. We present a case of pediatric red ear syndrome with hand and foot involvement that we believe represents auricular erythromelalgia. In this report, we propose a classification system to unify the diagnoses of red ear syndrome and erythromelalgia and review the literature on pediatric cases of red ear syndrome.
Raman Tweezers for small microplastics and nano-plastics identification in seawater.

Our understanding of the fate and distribution of micro- and nano- plastics in the marine environ-ment is limited by the intrinsic difficulties of the techniques currently used for the detection, quanti-fication and chemical identification of small particles in liquid (light scattering, vibrational spectros-copies, optical and electron microscopies). Here we introduce Raman Tweezers (RTs), namely op-tical tweezers combined with Raman spectroscopy, as an analytical tool for the study of micro- and nano-plastics in sea water. We show optical trapping and chemical identification of sub-20 µm plastics, down to the 50 nm range. Analysis at the single particle level allows us to unambiguously discriminate plastics from organic matter and mineral sediments, overcoming the capacities of standard Raman spectroscopy in liquid, intrinsically limited to ensemble measurements. Being a microscopy technique, RTs also permits to assess the size and shapes of particles (beads, frag-ments, fibres), with spatial resolution only limited by diffraction. Applications are shown on both model particles and naturally aged environmental samples, made of common plastic pollutants, in-cluding polyethylene, polypropylene, nylon and polystyrene, also in presence of a thin eco-corona. Coupled to suitable extraction and concentration protocols, RTs have the potential to strongly im-pact future research on micro and nanoplastics environmental pollution, and enable the understand-ing of the fragmentation processes on a multi-scale level of aged polymers.
Handwritten English character recognition by combining SVM classifier

paper we reviewed the importance of the pattern classification and its application. The paper describes the process of character recognition using the Multi Class SVM classifier. The problem of recognition of English handwritten characters is still an active area of research. The support vector machine(SVM) is new learning machine with very good generalization ability. Recent results in pattern recognition have shown SVM (Support vector classifier) often have superior recognition rates in comparison to the other classification methods. The input data is English handwritten characters. The approach works in two steps. 1. Feature extraction module. 2. SVM classifier module. The recognition of SVM with Gaussian kernel with statistical feature is 98 % and with structural and statistical feature is 99.9%.
Minimal prevalence of Huntington’s disease in the South of Brazil and instability of the expanded CAG tract during intergenerational transmissions

Abstract Huntington’s disease (HD) is due to dominant expansions of the CAG repeat of the HTT gene. Meiotic instability of the (CAG)n might impact the disorder frequency. We report on HD minimal prevalence in Rio Grande do Sul (RS) state, Brazil, and on intergenerational instability of the (CAG)n in HD families. Symptomatic and at-risk subjects from 179 HD families were ascertained between 2013 and 2016. Clinical, molecular and family history data were obtained. Expanded (CAG)n length differences between parent and child (delta-expanded-(CAG)n) were calculated. Effect of parental age on the (CAG)n instability upon transmission was inferred by correlating delta-expanded-(CAG)n between siblings to their age differences. HD minimal prevalence in RS state was estimated as 1.85:100,000 inhabitants. Alleles with (CAG)27-35 were found on 21/384 non-disease associated chromosomes (5.5%); among 253 expanded alleles, four (1.6%) were within reduced penetrance range with (CAG)36-39. In 32 direct transmissions, mean instability was larger among paternal than maternal transmissions. In direct transmissions and in 51 sibling pairs, parental age at the time of child birth were not correlated with delta-expanded-(CAG)n. Briefly, HD prevalence in RS state was lower than those reported for European populations. Expanded (CAG)n transmissions were unstable and not associated to parental age.
Stochastic simulation algorithms for computational systems biology: Exact, approximate, and hybrid methods

Nowadays, mathematical modeling is playing a key role in many different research fields. In the context of system biology, mathematical models and their associated computer simulations constitute essential tools of investigation. Among the others, they provide a way to systematically analyze systems perturbations, develop hypotheses to guide the design of new experimental tests, and ultimately assess the suitability of specific molecules as novel therapeutic targets. To these purposes, stochastic simulation algorithms (SSAs) have been introduced for numerically simulating the time evolution of a well‐stirred chemically reacting system by taking proper account of the randomness inherent in such a system. In this work, we review the main SSAs that have been introduced in the context of exact, approximate, and hybrid stochastic simulation. Specifically, we will introduce the direct method (DM), the first reaction method (FRM), the next reaction method (NRM) and the rejection‐based SSA (RSSA) in the area of exact stochastic simulation. We will then present the τ‐leaping method and the chemical Langevin method in the area of approximate stochastic simulation and an implementation of the hybrid RSSA (HRSSA) in the context of hybrid stochastic‐deterministic simulation. Finally, we will consider the model of the sphingolipid metabolism to provide an example of application of SSA to computational system biology by exemplifying how different simulation strategies may unveil different insights into the investigated biological phenomenon.
Integrated Environmental Assessment and Management

Existing prescriptive guidance on the derivation of local water quality benchmarks (WQBs; e.g., guideline values, criteria, standards) for protecting aquatic ecosystems is limited to only 3 to 4 specific approaches. These approaches do not represent the full suite available for deriving local WQBs for multiple types of water quality–related issues. The general lack of guidance is inconsistent with the need for, and benefits of, local WQBs, and can constrain the appropriate selection and subsequent evaluation of derivation approaches. Consequently, the defensibility of local WQBs may not be commensurate with the nature of the issues for which they are derived. Moreover, where local WQBs are incorporated into regulatory requirements, the lack of guidance presents a potential risk to the derivation of appropriate WQBs and the achievement of desired environmental outcomes. This review addresses the deficiency in guidance by 1) defining local WQBs and outlining initial considerations for deciding if one is required; 2) summarizing the existing regulatory context; 3) summarizing existing guidance and identifying gaps; 4) describing strengths, weaknesses, and potential applications of a range of derivation approaches based on laboratory and/or field data; and 5) presenting a conceptual framework for appropriately selecting and evaluating a derivation approach to best suit the need. The guidance incorporates an existing set of guiding principles for deriving local WQBs and reinforces an existing categorization of site‐adapted and site‐specific WQBs. The conceptual framework recognizes the need to strike an appropriate balance between effort and ecological risk and, thus, embeds the concept of fit‐for‐purpose by considering both the significance of the issue being assessed and the extent to which the approach provides confidence that the ecosystem will be appropriately protected. The guidance can be used by industry, regulators, and others for both the a priori selection and the post hoc evaluation of appropriate approaches for deriving local WQBs. Integr Environ Assess Manag 2019;15:683–702. © The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC)
Evaluating the antibacterial and antibiofilm potential of sulphated polysaccharides extracted from green algae Chlamydomonas reinhardtii

In this study, antibacterial and antibiofilm potential of sulphated polysaccharides (SPs) extracted from Chlamydomonas reinhardtii (Cr) was evaluated against Neisseria mucosa, Escherichia coli, Streptococcus sp. and Bacillus subtilis.
Mandarin tone recognition in English speakers with normal hearing and with cochlear implants

Abstract Objective: Mandarin-speaking cochlear implant users have difficulty perceiving tonal changes in speech with current signal processing strategies. The purpose of this study was to evaluate whether English-speaking cochlear implant and normal hearing listeners can be trained to recognise closed-set Mandarin tones. The validity of using native-English speakers to evaluate Mandarin tone perception in cochlear implants was tested. Design: Two groups of native-English speaking participants were evaluated. All listeners were given training rounds and evaluation rounds in which their tonal identification was tested. The normal-hearing group was also tested with acoustic simulations of the traditional Continuous Interleaved Sampling (CIS) strategy. Study sample: Ten normal-hearing English speakers and seven cochlear implant listeners participated. Results: The normal-hearing group correctly identified unprocessed tones at 87% and CIS-processed tones at 58% on average. The cochlear implant listeners achieved 56% correct identification on average. Conclusions: This level of performance for native English speaking CI users was comparable to previous studies using native Mandarin-speaking CI listeners, which showed a mean of 59% in 19 CI users.
Microaneurysms segmentation with a U-Net based on recurrent residual convolutional neural network

Abstract. Microaneurysms (MAs) play an important role in the diagnosis of clinical diabetic retinopathy at the early stage. Annotation of MAs manually by experts is laborious and so it is essential to develop automatic segmentation methods. Automatic MA segmentation remains a challenging task mainly due to the low local contrast of the image and the small size of MAs. A deep learning-based method called U-Net has become one of the most popular methods for the medical image segmentation task. We propose an architecture for U-Net, named deep recurrent U-Net (DRU-Net), obtained by combining the deep residual model and recurrent convolutional operations into U-Net. In the MA segmentation task, DRU-Net can accumulate effective features much better than the typical U-Net. The proposed method is evaluated on two publicly available datasets: E-Ophtha and IDRiD. Our results show that the proposed DRU-Net achieves the best performance with 0.9999 accuracy value and 0.9943 area under curve (AUC) value on the E-Ophtha dataset. And on the IDRiD dataset, it has achieved 0.987 AUC value (to our knowledge, this is the first result of segmenting MAs on this dataset). Compared with other methods, such as U-Net, FCNN, and ResU-Net, our architecture (DRU-Net) achieves state-of-the-art performance.
Draft Genome Sequence of the Yeast Kodamaea ohmeri, a Symbiont of the Small Hive Beetle

Kodamaea ohmeri is a symbiont of the small hive beetle (SHB), which is a scavenger of honey bee colonies. The SHB causes absconding of the economically important honey bee (Apis mellifera) and deposits K. ohmeri in the honeycomb. We describe long-read sequencing and further analyses of the K. ohmeri genome. ABSTRACT Kodamaea ohmeri is a symbiont of the small hive beetle (SHB), which is a scavenger of honey bee colonies. The SHB causes absconding of the economically important honey bee (Apis mellifera) and deposits K. ohmeri in the honeycomb. We describe long-read sequencing and further analyses of the K. ohmeri genome.