Miracle-dz/UniFAR-FTUs huggingface dataset:
Repeatability analysis of hand movement recognition for control of robotic prosthesis based on sEMG data

Control methods based on surface electromyography (sEMG) obtained promising results for robotic hand prosthetics. However, control system robustness is still inadequate and does not allow the amputees to perform a vast number of movements useful for everyday life. Moreover, few studies analyzed the repeatability of sEMG classification of hand grasps. The main goals of this paper are, first, to explore repeatability in sEMG data and, second, to release a repeatability database with the recordings of the experiments. The data are recorded from 10 intact subjects repeating 7 grasps 12 times in 5 different days. The data were recorded twice a day (morning and afternoon), thus leading to 10 acquisitions for each subject. The data are publicly available on the Ninapro web page and follow protocols comparable with other publicly available data sets. The analysis for the repeatability is based on the comparison of movement classification accuracy in different data acquisitions and for different subjects. The analysis is performed using mean absolute valu, waveform length and discrete wavelet transform features and Random Forest and Kernel Regularized Least Squares classifiers. Four distinct setups are created. Each one consists of unique training and testing dataset and it gives different understanding in how much the accuracy classification of hand grasps changes with data acquired from different acquisitions. The inter-subject variability is remarkable, suggesting that specific characteristics of the subjects (e.g. size of arm, body hair, etc.) can affect repeatability as well as sEMG classification accuracy. In conclusion, the results described in this thesis can contribute to develop more robust control systems for hand prosthetics by exploiting previous data acquisitions, while the presented data can allow researchers worldwide to test repeatability effects in further analyses.
Preliminary fi ndings in Italian farms part of FADN dataset by the PLS-SEM

Galluzzo, N. (2018). Preliminary fi ndings in Italian farms part of FADN dataset by the PLS-SEM. Bulgarian Journal of Agricultural Science, 24(6), 927–932 In Italy there has been a signifi cant decrease of farms with the consequence to marginalize rural areas. By some fi nancial subsidies allocated throughout the Common Agricultural Policy there has been a partial reduction of socio-economic marginalization in Italian rural territories. The purpose of this research was to assess by a quantitative approach which variables have acted on the rurality, management of farms and features of different unit of production since 2005 to 2015 using the dataset published in the Farm Accountancy Data Network. Findings have pointed out the positive role of the specialization of farms in terms of cultivated areas and fi nancial subsidies allocated by the European Union throughout the Common Agricultural Policy and the Rural Development Plan. The Partial Least Square Structural Equation Modeling (PLS-SEM) has been useful in assessing the cause-effect relationships in different constructs or rather among all investigated variables and indicators. PLS-SEM has not been widely used in investigating some index of rurality and relationships among indicators and variables corroborating the pivotal role of this quantitive approach in estimating cause-effect relationships in a small sample of farms.
Inhibition of class I histone deacetylases abrogates TGF expression and development of fibrosis during chronic pancreatitis

1 TITLE PAGE Inhibition of class I histone deacetylases abrogates TGF expression and development of fibrosis during chronic pancreatitis Marta Bombardo, Rong Chen, Ermanno Malagola, Enrica Saponara, Andrew P. Hills, Rolf Graf and Sabrina Sonda Swiss Hepato-Pancreato-Biliary Center, Department of Visceral and Transplantation Surgery, University Hospital, Zurich, Switzerland (M.B., R.C., E.M, E.S., R.G., S.S.) Center for Integrative Human Physiology (ZIHP), University of Zurich, Switzerland (R.G., S.S.) School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, Australia (A.P.H., S.S.) This article has not been copyedited and formatted. The final version may differ from this version. Molecular Pharmacology Fast Forward. Published on June 7, 2018 as DOI: 10.1124/mol.117. 110924
Estimativa da composição química corporal de tourinhos Santa Gertrudes a partir da composição química e física das 9-10-11ª costelas

Simple linear regressions to estimate empty body chemical composition of Santa Gertrudis young bulls were obtained, using the physical and chemical composition of the 9-10-11th ribs cut. Fifteen intact males, from nine to fifteen months of age and from 220 to 505 kg of liveweight, were kept confined. They were slaughtered after 18 hours without water and food, and six of them were slaughtered after adaptation period. The content of water, protein, lipid and ash were determined on the ribs cut and on the blood, hide, head + feet, visceras and carcass, and samples were obtained after quantitatively grinding and homogenizing the entire tissue. The physical composition of the ribs was determined by manual separation of bone, lean and fat. Empty body weight was closely related to hot carcass weight (r² = 0.99). Percent water and lipid of the 9-10-11th ribs cut were closely related to the empty body chemical composition, but not to the percent protein and ash, that can be calculated from their proportions on the empty body without fat. The physical composition of the ribs cut was a good estimator of the empty body composition, mainly for the equations using separable ribs fat to estimate the contents of water, ether extract and ash, but not protein content. Despite the good results with the ribs cut physical composition, chemical composition was a more efficient estimator of empty body chemical composition, because the coefficients of determination were higher and the standard errors were lower. As the percentage of water in empty body was closely related to the water percent on 9-10-11th ribs (r² = 0.95) and the percentages of ether extract and water in the empty body (r² = 0.94) were closely related each other, the water in the 9-10-11th ribs cut alone can be used to estimate empty body composition.
INFLUENCE OF THE EXTRACT OF BIOTIC ELICITOR ASPERGILLUS NIGER ON THE PRODUCTION OF FURANOCOUMARINS IN CALLUS CULTURES OF RUTA GRAVEOLENS L

The study was performed in the laboratory of plant cell and tissue culture, Department of Biology, College of Education for Pure Sciences, University of Diyala. The aim of this study was to investigate the influence of the extract of biotic elicitor Aspergillus niger at different concentrations (0.0, 1.0, 1.5, 2.0 ml L-1) on the production of furanocoumarins in callus cultures of Ruta graveolens L. , after the cultures were growing for 30 days on Murashige and Skoog (1962) (MS) medium supplemented with 2.0 mg L-1 2, 4-Dichlorophenoxy acetic acid (2,4-D) combined with 0.5 mg L-1 (Kin), the effect of the extract of A.niger on the production of Psoralen, Xanthotoxin and Bergapten was studied. Using Fast Liquid Chromatographic Column (FLCC) Technique, data showed the presence of the above three mentioned furanocoumarins in callus culture when compared with the standard samples. Psoralen, Xanthotoxin and Bergapten recorded their highest concentrations when the extract of the fungus A.niger was added to the growth medium at the concentration of 2.0 ml L-1, which reached 2.387 mg g -1, 0.537 mg g1 and 6.606 mg g-1 respectively compared with the controls which were 0.913 mg g-1, 0.244 mg g-1 and 3.983 mg g-1 respectively. The results indicate that plant tissue culture is constant and continuous source for the plant secondary metabolites such as Psoralen, Xanthotoxin and Bergapten and can serve as a suitable alternative for field plants.
Modelling IoT Systems with UML: A Case Study for Monitoring and Predicting Power Consumption

Software Engineering has evolved to meet the growing complexity of current systems and the resources of the Unified Modeling Language (UML) enable the modeling of such systems in different views. The Internet of Things (IoT) paradigm appears with very peculiar characteristics such as the heterogeneity of its physical and virtual components that must be integrated. Designing systems of this nature is a challenge and modeling using UML is consolidating itself as a resource to overcome this challenge. The objective of this work is to present some proposals for UML extensions already available in the literature, to represent IoT systems. Then, we present a case study with those models for representing a small energy monitoring system with artificial intelligence for power consumption forecast.
Mg@C74 isomers: Calculated relative concentrations and comparison with Ca@C74

Computations for two C74‐based endohedrals, Mg@C74 and Ca@C74, are presented. A set of four different C74 cages is considered, namely one isomer with isolated pentagons and three with pentagon–pentagon junctions. However, the endohedral based on the cage with isolated pentagons is the most important species in both systems. Special interest is paid to the Gibbs‐energy based evaluations of the production abundances for different metallofullerenes including saturated metal pressures into consideration. The predicted amount of Mg@C74 is about 5 orders of magnitude smaller than that of Ca@C74 for temperatures 1500–2000 K. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Towards a Systematic Approach to Sync Factual Data across Wikipedia, Wikidata and External Data Sources

This paper addresses one of the largest and most complex data curation workﬂows in existence: Wikipedia and Wikidata, with a high number of users and curators adding factual information from exter-nal sources via a non-systematic Wiki workﬂow to Wikipedia’s infoboxes and Wikidata items. We present high-level analyses of the current state, the challenges and limitations in this workﬂow and supplement it with a quantitative and semantic analysis of the resulting data spaces by deploying DBpedia’s integration and extraction capabilities. Based on an analysis of millions of references from Wikipedia infoboxes in diﬀerent languages, we can ﬁnd the most important sources which can be used to enrich other knowledge bases with information of better quality. An initial tool is presented, the GlobalFactSync browser, as a prototype to discuss further measures to develop a more systematic approach for data curation in the WikiVerse.
Anti-nutritional properties and organic acids composition of seven varieties cassava (Manihot esculenta Crantz) consumed in Côte d’Ivoire

In Côte d'Ivoire, new varieties cassava (Manihot esculenta Crantz) are produced and consumed by populations. The aim of this research work was to study the anti-nutritional and antioxidant properties, organic acids of seven varieties cassava (Agbablé 3, Bondoukou 4, Bonoua 2, Boufouh 3, Boufouh 4, Soclopouopo 3 and Totoba 2) to better value them. Thus, phytate contents varied from 50.34±0.03 (Bondoukou 4) to 60.36±0.04 mg/100g (Soclopouopo 3), those of tannins contents from 0.046±0.014 (Agbablé 3) to 0.054 ± 0.014 (Bondoukou 4). The flavonoid contents range from 0.62 ± 0.02 (Agbablé 3) to 3.01 ± 0.01 mg / 100 g (Bonfouh 3). Total polyphenols ranged from 51.24±1.79 (Totoba 2) to 81.12±1.97 mg/100 g (Bondoukou 4). Oxalates contents varied from 5.1±1 (Agbablé 3) to 5.6±1.5 (Bondoukou 4). Anti-oxidant power varied from 0.06 (Agbable 3, Bondoukou 4, Bonfouh 3) to 0.08 (Boufouh 4). Most abundant organic acids are carboxylic acids ranging from 122.5±2.04 (Boufouh 3) to 147.65±0.61 μg/100g (Bonoua 2) and benzoic acids from 80.11±0.17 (Boufouh 3) at 126.15±0.98 (Bondoukou 4). Agbablé 3 variety has low contents of tannins, flavonoids, total phenolols and oxidizing power. Bondoukou 4 and Bonoua 2 varieties respectively had low contents of phytates and total polyphenols.
Discrimination of moldy wheat using terahertz imaging combined with multivariate classification

Terahertz (THz) imaging was employed to develop a novel method for discriminating wheat of varying states of moldiness. Spectral data, in the range of 0.2–1.6 THz, were extracted from regions of interest (ROIs) in the THz images. Principal component analysis (PCA) was used to evaluate the spectral data and determine the cluster trend. Six optimal frequencies were selected by implementing PCA directly for each image's ROI. Classification models for moldy wheat identification were established using the support vector machine (SVM) method, a partial least-squares regression analysis, and the back propagation neural network method. The models developed from these methods were based on the full and optimal frequencies, using the top three principal components as input variables. The PCA-SVM method achieved a prediction accuracy of over 95%, and was implemented at every pixel in the images to visually demonstrate the moldy wheat classification method. Our results indicate that THz imaging combined with chemometric algorithms is efficient and practical for the discrimination of moldy wheat.
Preventive Factors of Postpartum Depression in Adult Mothers: A Systematic Review of Randomized Controlled Trials

Background: Postpartum Depression (PPD) is defined as major depressive disorder with peripartum onset. It is the most common mental illness that occurs after childbirth, affecting not only mother but also newborn. Considering the great impact PPD has, it is relevant to investigate the effectiveness of preventive interventions.Objective: This review investigates published literature of the last decade (2009-2019) regarding the topic of preventive factors of PPD in adult mothers.Methods: An electronic search was conducted by using PubMed, psycINFO and Google Scholar. The search term included a combination of postpartum depression, postnatal depression, predictor, prevention and risk factor. Inclusion criteria were: 1) randomized controlled trials (RCT) published in English or German language that deal with 2) adult pregnant or adult mothers (>18 years). Extraction of articles by two independent raters using predefined data fields, including study quality indicators.Results: The electronic search resulted in a total of 905 articles, whereby only 22 articles were relevant for this synthesis. The interventions were divided into five major topics, these being psychological, psychosocial, nutritional, medical, and exercise interventions. Significant preventive effects concerning PPD in adult mothers were found in psychological and psychosocial interventions. Nutritional, medical and exercise interventions did not have a significant preventive impact.Conclusion: Psychological and psychosocial interventions seem to be effective in the prevention of PPD. Consequently, preventive programs should include such components. Implications for future research might include the comparison of already existing prevention programs for PPD and the observation of their long-term effects.
Simultaneous Tracking of Multiple Moving Humans from a Robotic System

Tracking multiple people simultaneously in real-world environments is crucial for a wide variety of applications, including video surveillance and human-robot interaction. In this work, we present a method for tracking an unknown number of humans from a robotic platform. This is accomplished by using the robot's 2D Laser-Range Scanner sensor located at the feet height and a plain web camera. Since we employ two separate sensory modalities, we commence by providing a method to manually yet e ortlessly calibrate the sensory setup. The proposed tracking methodology is an iterative process which consists of a clustering and a tracking step. During the rst step, human centers are being produced from the fusion of sensory data via means of clustering. The developed clustering method is based on the introduced Human Evidence Grid (HEG) concept. HEG constitutes a 2D Cartesian occupancy grid, whose cells capture the occupancy evidence, i.e. a detected human face on the image plane occupies a number of cells, of the environment being monitored by the LRS scanner. The occupancy likelihood, that the HEG holds, is a result of a training process. Several training datasets were considered in order to robustly learn real-life con gurations among a human face and the corresponding LRS measurements that the detected face may produce. The potential of the developed methodology is explored by comparing it to an Euclidean approach which only considers LRS data. The results show that HEG clustering outperforms the Euclidean approach. As a second step, the produced cluster centers are subsequently being tracked by a Rao-Blackwellized Particle Filtering (RBPF) Multiple Target Tracker, where human appearance and disappearance are coded via a distribution that models the lifetime of each target. 3 Chapter 0 Several datasets were captured in order to test the proposed approach in real-life scenarios. The results from a dataset, where three people are being monitored and tracked in the surveillance area, are presented and described in detail. Our experimental results demonstrate the e ectiveness of HEG clustering in handling temporary occlusions in the LRS area.
Dynamic Independent Component/Vector Analysis: Time-Variant Linear Mixtures Separable by Time-Invariant Beamformers

A novel extension of Independent Component and Independent Vector Analysis for blind extraction/separation of one or several sources from time-varying mixtures is proposed. The mixtures are assumed to be separable source-by-source in series or in parallel based on a recently proposed mixing model that allows for the movements of the desired source while the separating beamformer is time-invariant. The popular FastICA algorithm is extended for these mixtures in one-unit, symmetric and block-deflation variants. The algorithms are derived within a unified framework so that they are applicable in the real-valued as well as complex-valued domains, and jointly to several mixtures, similar to Independent Vector Analysis. Performance analysis of the one-unit algorithm is provided; it shows its asymptotic efficiency under the given mixing and statistical models. Numerical simulations corroborate the validity of the analysis, confirm the usefulness of the algorithms in separation of moving sources, and show the superior speed of convergence and ability to separate super-Gaussian as well as sub-Gaussian signals.
The first report on the oribatid mites (Acari: Oribatida) in tundra of the Chunatundra Mountains on the Kola Peninsula, Russia

The aim of this research was to obtain initial data on the fauna and abundance of the oribatid mites from the main types of the mountain tundra habitats of the Chunatundra Mountains. Four plots, including two lichen tundra plots, one dwarf shrub tundra plot and one sphagnum bog in the belt of mountain tundra were investigated. Multidimensional scaling and discriminant function analysis were used to identify trends in the fauna and abundance of oribatid species through the explored plots. A total of 70 species and one subspecies from 37 genera and 24 families were found during the course of this investigation. Nine species, one subspecies, one genus and one family of oribatid mites have been added to the fauna of the Kola Peninsula. The families Brachychthoniidae, Oppiidae and Suctobelbidae are the most diverse in the discovered local fauna. According to literature data, the first two families are characteristic of the low tundra communities, the third family is more common for the boreal zone. The discovered oribatid fauna is similar to the fauna of other tundra sites of the Kola Peninsula studied previously and is significantly different to the local oribatid mite faunae of the Scandinavian Peninsula. The abundance of the adult oribatid mites reached 39 080 ind. /m2 in the lichen tundra and 56 200 ind. /m2 in the dwarf shrub tundra. The minimum abundance of oribatid mites, 18 640 ind. /m2 was found in the sphagnum bog. Differences in the oribatid mite complexes of lichen tundra, dwarf shrub tundra and the sphagnum bog were found. The species Carabodes labyrinthicus, Nothrus borussicus, Sellnickochthonius immaculatus, Mycobates sarekensis, and Tectocepheus velatus were associated with the lichen tundra habitats. Nanhermannia sellnicki, Chamobates borealis and a few species of Oppiella and Suctobelbella were associated with the dwarf shrub tundra. Mucronothrus nasalis, Limnozetes ciliatus, Platynothrus peltifer, Trimalaconothrus foveolatus, Limnozetes cf. rugosus, and Trimalaconothrus maior are most characteristic of the sphagnum bog. The family Suctobelbidae was represented by a large number of species, while the families Ceratozetidae and Camisiidae were much less diverse. The low diversity of Ceratozetidae, a high diversity of Suctobelbidae and relatively high abundance of oribatid mites in the explored tundra habitats may be explained by an ambivalent nature of the oribatid community, which combines boreal and arctic features due to marine climate. Also, this result may be a feature of a local mountain tundra which is surrounded by the underlying belts of the mountain forests that are a source of the increasingly diversity of species.
Adaptive Retrieval Time-Related Data Model for Tracking Factors Affecting Diabetes

In the last four decades several dozens of representing time-oriented data/knowledge bases have been presented. Some of these representations violate First Normal Form (1NF) by using Non-First Normal Form (N1NF) prototypes and temporal nested representations, while others simulated the concepts of temporal data with relational data representation without violating 1NF. In this article, a new interval-based knowledge representational data model with an optimized retrieval techniques are employed for modeling and optimality retrieve a biomedical time-varying data (factors/observations that affect the diabetes). The used time-related data model is more compact to represent time-varying data with less memory (capacity) storage with respect to the main representations in the literature, but which is as expressive as those representations (a transformation algorithms show that data represented in this model can be transferred to/from the representations in the literature with zero percent loss of information). A new data structure is defined with the optimal retrieval techniques to prove some basic properties of the used time-model and to ensure that the time-model is an extension and reduction of the main representations in the literature, namely TQuel and BCDM. The expressive power, reducibility, and easy implementation of the proposed model, especially for the legacy systems, are considered as advantages of the proposed model. Keywords—Diabetes database; time-data model; diabetes observations; valid-time data; knowledge-based data
The adsorption of SO2 on TiO2 anatase nanoparticles: a density functional theory study

First-principles calculations have been carried out to investigate the adsorption properties of SO2 molecules on nitrogen-doped TiO2 anatase nanoparticles using the density functional theory method to fully exploit the gas-sensing capabilities of TiO2 particles. For this purpose, we have mainly studied the adsorption of the SO2 molecule on the dangling oxygen atom and doped nitrogen atom sites of the TiO2 nanoparticles because these sites are more active than other sites in the adsorption processes. The complex systems consisting of the SO2 molecule positioned toward the undoped and nitrogen-doped nanoparticles have been relaxed geometrically. The results presented include structural parameters such as bond lengths and bond angles and energetics of the systems such as adsorption energies. The electronic structure and its variations resulting from the adsorption process, including the density of states, molecular orbitals, and the charge transfer, are discussed. We found that the adsorption of the SO2 mole.