Miracle-dz/UniFAR-FTUs huggingface dataset:
Editorial

This editorial is based on my experience of the reviewing process up to now for papers submitted to the Biomechanics section of the journal and its title could also be ‘How to avoid certain rejection of a paper submitted to a scientific journal’. The rejection rate of theBiomechanics section papers is currently around 60% and it is always a very difficult task to communicate such bad news to the authors of a rejected paper knowing that a lot of hardwork and effort went into its preparation. Although the reasons for rejection vary considerably between papers and scientific disciplines, there are some common characteristics that determine the quality of a manuscript and its contribution to the advancement of scientific knowledge. Based on some of the most frequent reasons for rejection, I try to describe below some important points to take into consideration when planning a paper for publication.
Guest Editorial

Speech Music Hearing department, KTH, arranged the Stockholm Music Performance Symposium, or STOMPS for short. The idea was to gather reseachers in the area of music performance, particularly those who have been working with and thus assembled experiences of the strengths and limitations of the KTH music performance grammar Director Musices. As performance research in Italy has been especially strong, the Stockholm Italian Cultural Institute “C. M. Lerici” generously financed the meeting. The invitation was accepted by 9 researchers from Austria, Germany, Italy, Spain, Sweden, The Netherlands, and the UK. Eight agreed to contribute to the STOMPS Proceedings and Marc Leman, Editor-in-Chief of this Journal offered to publish the Proceedings as the present special issue with me as Guest Editor. The articles cover a variety of aspects. W. Andrew Schloss considers the question what a music performance really is from the musician’s point of view. Reinhard Kopiez, Marc Bangert, Werner Goebl, and Eckart Altenmüller report on observations from a most unusual performance of a most unusual piece, Erik Satie’s composition Vexations, lasting for no less than 28 hours! Gerhard Widmer and Asmir Tobudic report on experiences from their work to analyse performances by means of an automatic learning strategy. Erik Lindström reviews his experiments that aims at identifying the effects on emotional expressivity of different musical melodic and harmonic contexts; and Sergio Canazza, Giovanni De Poli, Antonio Rodà, and Alvise Vidolin describe an abstract control space for expressive intentions in performance. The next three articles report on attempts to use the Director Musices program. This is described in the Appendix of the paper by Patrick Zanon and Giovanni De Poli, in various investigations. Johan Sundberg, Anders Friberg, and Roberto Bresin attempted to match a real performance of bars 1–20 of the second Adagio movement of W. A. Mozart’s Piano Sonata in F major, K 332, using a fixed constellation of performance rules. Patrick Zanon and Giovanni De Poli report on their attempts to reproduce a pianist’s expressive timing using time varying constellation of performance rules. Finally, Roberto Dillon presents his experiences by comparing two real performances and a Director Musices performance, using the audio signal as input. This STOMPS issue of the Journal of New Music Research thus demonstrates a strong research activity, a variety of approaches, and a wealth of information that can be derived from a scientific analysis of music performance.
PASID: Exploiting Indoor mmWave Deployments for Passive Intrusion Detection

As 5G deployments start to roll-out, indoor solutions are increasingly pressed towards delivering a similar user experience. Wi-Fi is the predominant technology of choice indoors and major vendors started addressing this need by incorporating the mmWave band to their products. In the near future, mmWave devices are expected to become pervasive, opening up new business opportunities to exploit their unique properties.In this paper, we present a novel PASsive Intrusion Detection system, namely PASID, leveraging on already deployed indoor mmWave communication systems. PASID is a software module that runs in off-the-shelf mmWave devices. It automatically models indoor environments in a passive manner by exploiting regular beamforming alignment procedures and detects intruders with a high accuracy. We model this problem analytically and show that for dynamic environments machine learning techniques are a cost-efficient solution to avoid false positives. PASID has been implemented in commercial off-the-shelf devices and deployed in an office environment for validation purposes. Our results show its intruder detection effectiveness (∼99% accuracy) and localization potential (∼ 2 meters range) together with its negligible energy increase cost (∼ 2%).
Occupational performance in the basic and instrumental daily activities of persons with low vision who received rehabilitation services

Introduction The objective was to describe the occupational performance in basic and instrumental daily activities of persons living in the community who have received comprehensive interdisciplinary low vision rehabilitation services. Method The Mesure de l'impact de la déficience visuelle dans les activités quotidiennes (a measure of the impact of visual impairment in daily activities) was administered at home to 102 individuals who participated in a comprehensive low vision rehabilitation program. Performance in 16 near-vision activities was measured with the person's aids and strategies; nine more global tasks were questionnaire-based. Handicap scores were obtained by multiplying performance × importance ratings. Results Average performance was satisfactory or very satisfactory for 21/25 items, even if 92% of the participants had a moderate or severe visual impairment. A severe or total handicap was present in at least one activity for 79% of the subjects. The most handicapping activities required visual searches of finely printed information on a complex or visually crowded document, or shopping and mobility. Conclusion People with low vision who took part in a comprehensive rehabilitation program generally face no or slight handicap situations in their basic and instrumental daily activities. However, major handicap situations may remain in some important activities.
Hypothesis testing in smoothing spline models

Nonparametric regression models are often used to check or suggest a parametric model. Several methods have been proposed to test the hypothesis of a parametric regression function against an alternative smoothing spline model. Some tests such as the locally most powerful (LMP) test by Cox et al. (Cox, D., Koh, E., Wahba, G. and Yandell, B. (1988). Testing the (parametric) null model hypothesis in (semiparametric) partial and generalized spline models. Ann. Stat., 16, 113–119. ), the generalized maximum likelihood (GML) ratio test and the generalized cross validation (GCV) test by Wahba (Wahba, G. (1990). Spline models for observational data. CBMS-NSF Regional Conference Series in Applied Mathematics, SIAM. ) were developed from the corresponding Bayesian models. Their frequentist properties have not been studied. We conduct simulations to evaluate and compare finite sample performances. Simulation results show that the performances of these tests depend on the shape of the true function. The LMP and GML tests are more powerful for low frequency functions while the GCV test is more powerful for high frequency functions. For all test statistics, distributions under the null hypothesis are complicated. Computationally intensive Monte Carlo methods can be used to calculate null distributions. We also propose approximations to these null distributions and evaluate their performances by simulations. E-mail: yuedong@pstat.ucsb. edu E-mail: annaliu@pstat.ucsb. edu
Comparison of Differently Lined Paper on Letter Production Quality in First Graders

The purpose of this study was to examine handwriting production of first grade students using differently lined paper. Two groups of first grade students were assessed with the Minnesota Handwriting Assessment. The first group printed on a four-lined writing grid that included top, middle, base, and descender guidelines. The second group printed on double lined paper that provided middle and base guidelines only. There was no difference between groups for legibility, form, alignment, and space as measured by the Minnesota Handwriting Assessment. There was a statistical difference noted between the two groups for size, t(63) = –4.629, p < . 001. Examination of sizing errors showed that 55% of the students in the double-lined paper group used the middle guideline as a top guideline. The results suggest that for first grade students, the number of lines on writing paper has no effect on letter legibility but can influence size. Writing paper that has both a top and a bottom guideline may be optimal for first grade students for ensuring proper letter size when printing.
Spectrum of Anxiety Disorders Among Medical Students in a Nigerian Medical School: A Cross-Sectional Study With Standardized Screening Tools

BACKGROUND: Anxiety disorders among medical students constitute a global problem, and also reflect the mental state of the general population. There is paucity of data on the spectrum of such disorders among medical students in Nigeria.AIM: The study aims to determine the prevalence of anxiety disorders among medical students, and the effect of socio-demographic characteristics.METHODS: A total of 217 medical students from the second to the final years of study at Enugu State University of Science and Technology in south-east Nigeria were enrolled by simple random sampling. Five pretested, self- administered standardized questionnaires were used as screening tools for anxiety disorders. Data were analyzed using the Statistical Package for Social Sciences program (SPSS version 20). A p-value less than 0.05 was taken as statistically significant.RESULTS: Thirty one (14.3%) of the enrolled medical students fulfilled the screening criteria for anxiety disorders. Specifically, generalized anxiety disorder (GAD) was significantly related to gender (p =0.017) and the year of study (p =0.017). Post-traumatic stress disorder (PTSD) was significantly related to the year of study (p =0.037), and social anxiety disorder (SAD) to the year of study (p =0.003) and gender (p =0.04). Similarly, panic disorder was significantly related to the year of study (p =0.025) while specific phobia was significantly associated with marital status (p =0.003), parental monthly income (p =0.022) and student’s monthly allowance (p =0.002). Finally, obsessive-compulsive disorder was significantly related to marital status (p =0.034) and year of study (p =0.028). CONCLUSION: Medical students in Nigeria are prone to a spectrum of anxiety disorders. This susceptibility is influenced by socio-demographic characteristics.
Molecular identification of gold nanoparticles synthesizing bacteria through in silico methods

Classifying individual bacterial through traditional methods is stagnant, which require lot of consultation and efforts. DNA sequencing can provide more definitive taxonomic classification than culture based approaches for many organisms. While providing less time consuming and labour intensive. Molecular characterization technology is now widely used for wide range of bacterial species. We have used blastn, Cluster W, MEGA6.0 software to identify species of bacterial isolates on the basis of 16S rrna gene and then homology searching has been done through Cluster W. Phylogenetic relationship established through MEGA 6.0 software. We have identified Bacillus thuringiensis strain GBI-3 with a noble trait such as to synthesize Gold nanoparticles.
The evolution of social norms in conflict resolution

In her classic essay ‘Collective Action and the Evolution of Social Norms’, Nobel laureate Elinor Ostrom (2000) made a major contribution to our understanding of human institutions. She developed the ‘Indiana School’s’ Institutional Analysis and Development (IAD) Framework at Indiana University’s Workshop on Political Theory and Policy Analysis. Her work has broad application to law and conflict resolution. We are currently undergoing a wave of privatization of justice in the United States. Companies are imposing mandatory or adhesive arbitration clauses on employees (Baker, 2004) and consumers (Demaine & Hensler, 2004) that preclude them from joining class actions or resorting to the public justice system to enforce laws on discrimination or consumer protection (Bingham, 2004; Sternlight, 2005). The result is undermining the enforcement of public law. This essay endeavors a brief application of Ostrom’s work to these private justice systems. It examines collective action and social norms in formal legal institutions and informal ones for managing conflict that have evolved outside the justice system. It introduces dispute system design (DSD) in the context of IAD. It applies IAD to examples of these systems. It concludes with issues, collective action and the development of social norms, for managing conflict in dispute resolution systems that have emerged in certain industries. Ostrom’s work can help us address collective action problems in these private justice systems.
Different management modalities in chronic osteomyelitis of long bones following open fractures: A case series

Chronic osteomyletis is one of the most dreaded complication of 0pen fractures and a surgeons nightmare. Eradication of COM requires aggressive surgical excision combined with effective antibiotic treatment and reconstructive procedures. The goal of therapy in such patients is to restore the functional anatomy of the limb. Depending on our experience and the type of infected nonunion we individualize a modality of management for the patient and the type of nonunion. The various modalities used were Corticotomy and lengthening using Ilizarov or LRS, Customized antibiotic rod implantation, Membrane osteosynthesis, Resection and endoprosthesis and Papineau technique. We followed up these patients till the radiological and clinical union occured and eradication of infection. The outcomes were based on bony union, functional outcome based on range of motion and occupational rehabilitation with eradication of infection at the last follow up. We publish our series of such cases and review of literature with representative cases.
The VEGFA gene and anterior cruciate ligament rupture risk in the Caucasian population

The aim of the present study was to analyse VEGFA rs699947, rs1570360, and rs2010963 polymorphisms with susceptibility to anterior cruciate ligament rupture (ACLR) in a Polish population. The study included 412 physically active Caucasian participants. The study group consisted of 222 individuals with surgically diagnosed primary ACLR qualified for ligament reconstruction (ACLR group). The control group consisted of 190 apparently healthy participants without any history of ACLR (CON group). Three polymorphisms within the VEGFA (rs699947, rs1570360, and rs2010963) gene were chosen for investigation due to their significance in the angiogenesis signalling pathway and previous associations with risk of ACLRs. Both single-locus and haplotype-based analyses were conducted. No significant differences in the allele and genotype frequency distributions were noted for the rs699947 and rs1570360 polymorphisms. In contrast, rs2010963 was associated with risk of ACLR in the codominant (p=0.047) and recessive model (p=0.017). In the latter, the CC genotype was overrepresented among individuals with ACL rupture (23.4% vs 14.2%, OR=1.85 [1.11-3.08]). Two VEGFA haplotypes were associated with ACLR under the additive (global score=11.39, p=0.022) and dominant model (global score=11.61, p=0.020). The [C;G;G] haplotype was underrepresented in the ACLR group (52.2% vs. 60.3%), whereas the [C;G;C] haplotype was overrepresented (2.9% vs 0.5%). The results obtained suggest a potential correlation between the VEGFA rs2010963 polymorphism and ACLR risk, suggesting that harbouring this specific C allele may be an unfavourable risk factor for a knee injury in Caucasian participants from Poland.
OntoC4S framework: constraint based framework for sequential pattern mining

Nowadays, data is everywhere and everyone can access it. This data is characterized by its diversiﬁcation and heterogeneity. So, as consequence, the challenge is to be able of getting useful information of all that data. The interdisciplinary ﬁeld of data mining appears as a computational process of extracting information from data and transform it into an understandable structure to be applied. Pattern mining is a subﬁeld inside data mining which tries to extract relevant knowledge in the form of patterns from datasets. The ﬁnal goal of these patterns is to be useful and to help the decision-making process. Constraints are an identiﬁed way of getting more interesting patterns and focusing on the pattern mining algorithms to the expectations of the users but until now their importance is very limited by the expression power of the tools used to deﬁne them. Ontologies were identiﬁed as a new possibility of representing knowledge in a more interesting way. In this work, we developed a ontology based framework for the sequential pattern mining process, the OntoC4S framework, to introduce domain knowledge speciﬁed by the user’s input. This framework is able to represent sequential and concurrent events, in order to deﬁne constraints over sequential data. The goal of this work is to enable the representation of more expressive constraints when compared with other constraints’ representation and to obtain a broader way of embody user knowledge while optimizing the current algorithms. The results show that the framework achieves the proposed goals while keeping the performance of unconstraint algorithms. This work is done within the D2PM project where a framework for guiding the pattern mining process is the goal to be accomplished.
Higher-order Behavioral Contracts for Distributed Components

Inspired by the Design by Contract paradigm, we intro- duce CONSUL, a contract system for distributed compo- nents. CONSUL monitors distributed components at run time with higher-order behavioral contracts. Contract monitoring is local to a component, and the component is treated as a black box. Thus it does not disturb the highly decoupled nature of distributed components and allows heterogeneous implementation languages and platforms without modifica- tions to a component’s code. We describe the design, seman- tics and properties of CONSUL (adapter transparency and correct blame), and show that its contracts can capture and enforce precise and useful properties of a variety of off-the- shelf components.
Phosphatase activities (ACP, ALP) in agroecosystem soils

Soil phosphatases play a major role in the mineralization processes of organic phosphorus substrates. Enzymes in soils originate from animal, plant and microbial sources and the resulting soil biological activity includes the metabolic processes of all these organisms. The activity of soil phosphatases can be influenced by numerous factors and soil properties and farming systems play a key role among them. The research adds to the growing knowledge on soil phosphatases in their interactions with specific soil characteristics at nine sites in the Czech Republic with common soil types. The results show correlations and linear equations between phosphatase activity and soil characteristics. The trials were also conducted at experimental locations and farms in Uppland (Sweden) with eutric cambisol soil type. The results also demonstrate the correlation between acid and/or alkaline phosphatase and several soil characteristics. At the experimental plots were also studied the effect of different farming systems (conventional farming without animal husbandry, organic farming with animal husbandry, organic without animal husbandry with standard soil cultivation, and organic agricultural system without animal husbandry with minimum soil management). The research is also concentrated toward acid phosphatase activity linked to cultivated plants. The evaluation was carried out on the root systems of both the chosen species and cereal varieties and also in nutrient medium on which crops were planted under conditions of changing pH and phosphorus supply. The results show that the acid phosphatase activity in the root system of various species and cereal cultivars is negatively correlated with increasing pH and available phosphorus level in the nutrient medium. Attention was also paid to acid phosphatase and alkaline phosphatase active colonies of bacteria, isolated from soils. The activity of acid phosphatase and other soil properties were compared with the number of bacteria belonging to the genus Micrococcus. Numerous correlations were described but the results didn't show any correlation between phosphatase active colonies of bacteria and acid and alkaline phosphatase activity in the investigated soils. This is probably due to the production of phosphatates by organisms other than bacteria.
Real-time Driving Context Understanding using Deep Grid Net: A
Granular Approach

Numerous self-driving cars algorithms rely on grid maps for motion planning, obstacles avoidance, or environment perception. Obtained from fused sensory information, the occupancy grids (OGs) are nowadays among the most popular solutions used in series production in the automotive industry. In this paper, we extend Deep Grid Net (DGN) [18], a deep learning (DL) system designed for understanding the context in which an autonomous car is driving. We consider this paper a granular approach to DGN method due to the improvements added to the original research [18]. DGN incorporates a learned driving environment representation based on OGs obtained from raw real-world Lidar data and constructed on top of the Dempster-Shafer (DS) theory. Our system is able to predict in real-time if the vehicle is driving on the highway, on county roads, inside a city, in parking lots or is stuck in a traffic jam. The predicted driving context is further used for switching between different autonomous driving strategies implemented within EB robinos, Elektrobit’s Autonomous Driving (AD) software platform. We propose a neuroevolutionary approach to search the optimal hyperparameters set of DGN. Genetic algorithms (GAs) were selected due to their demonstrated capabilities to evolve deep neural networks with improved accuracy and processing speed. The performance of the proposed deep network has been evaluated against similar competing driving context estimation classifiers.
Analysis of Structural Breaks in Inflation, Exchange Rate, Interest Rate and Horticultural Exports in Kenya

The main objective of this study was to identify the major structural breaks associated with horticultural exports in Kenya using time series variables. To achieve this objective of the study, monthly secondary data was sourced from Central Bank of Kenya. The sample period was 2005 to 2018. The variables that were used are exchange rate, interest rate, inflation and horticultural exports. Structural breaks were tested by application of Clemente-Montannes-Reyes with both Additive and Innovative outlier unit root test to allow for multiple breaks. Results indicated that some of the variables had significant structural breaks while some recorded some insignificant structural breaks. The structural breaks were also variable specific and were associated with key changes in both policy and international economic episodes. This shows that Kenya’s horticultural exports are affected by both domestic and international events and there is need by policy makers to factor in the effects of structural breaks in designing export policies. Citation: Kiprono S (2019) Analysis of Structural Breaks in Inflation, Exchange Rate, Interest Rate and Horticultural Exports in Kenya. J Glob Econ 7: 334.