Miracle-dz/UniFAR-FTUs huggingface dataset:
Lifestyle-Related Factors Contributing to Decline in Knee Extension Strength among Elderly Women: A Cross-Sectional and Longitudinal Cohort Study

This cross-sectional and 4-year longitudinal cohort study aimed to clarify how various lifestyle-related variables affect knee extension strength in elderly Japanese women. The participants were community-dwelling women (n = 575) living in the Itabashi Ward of Tokyo, Japan aged 75–85 years at baseline (in 2008) who returned for a follow-up examination 4 years later (in 2012). Maximum isometric knee extension strength in the dominant leg was measured during comprehensive medical check-ups at baseline and follow-up. Interviews with participants included questions on their history of 11 diseases and lifestyle-related factors such as physical activity as well as dietary, smoking, and drinking habits. Cross-sectional and longitudinal analyses yielded inconsistent results regarding the associations between lifestyle-related factors and knee extension strength. While going out more frequently and regular physical exercise positively affected baseline knee extension strength, they did not affect knee extension strength in the longitudinal analysis. The longitudinal analysis revealed that more frequent intake of soy products or green and yellow vegetables at baseline decreased age-related knee extension strength decline. The inconsistent results from the cross-sectional and longitudinal analyses indicate that conducting both types of analyses is crucial for researching this type of subject. The present study demonstrates that the age-related decline in muscle strength is lower in those who frequently eat soy products or green and yellow vegetables. Thus, recommending higher intake of soy products, and green and yellow vegetables for the elderly might help maintain their muscle health.
Long-term CAPD patients are volume expanded and display more severe left ventricular hypertrophy than haemodialysis patients.

BACKGROUND Whether hypertension and left ventricular hypertrophy (LVH) are more prevalent in CAPD than in haemodialysis (HD) patients is still under discussion. METHODS To examine this problem we compared a group of 51 CAPD patients, with a group of 201 HD patients. The evaluation included the measurement of atrial natriuretic peptide (atrial natriuretic factor (ANF)), taken as indicator of volume status, and echocardiographic measurements. RESULTS CAPD patients were older, had been treated for a shorter time, and had lower serum albumin and phosphate than HD patients. Plasma ANF was higher (P<0.01) in CAPD (median 33.8 pmol/l (interquartile range 18.2-63.0)) than in HD patients (22.7 pmol/l (14.9-38.7)). Similarly, the left atrial volume was substantially higher (P<0.0001) in CAPD patients (49+/-22 ml) than in HD patients (37+/-17 ml), while the left ventricular end-diastolic diameter was similar in the two groups (CAPD 51+/-7 mm; HD 50+/-7 mm). Furthermore, left ventricular hypertrophy was more severe (P<0.0001) in CAPD (157+/-37 g/m(2)) than in HD patients (133+/-39 g/m(2)). The proportion of CAPD patients requiring antihypertensive drugs was markedly higher than that of HD patients (65 vs 38% P<0.001). Multivariate modelling showed that volume expansion and pressure load as well as serum albumin were independent predictors of left ventricular mass. CONCLUSIONS Left ventricular hypertrophy is more severe in long-term CAPD patients than in HD patients. This finding is associated with evidence of more pronounced volume expansion, hypertension, and hypoalbuminaemia. Volume and pressure load along with factors associated with hypoalbuminaemia may aggravate LVH in uraemic patients on CAPD.
The Relationship Between Fish Assemblages and the Helminth Communities of a Prey Fish, in a Group of Small Shallow Lakes

Abstract Galaxias maculatus (small puyen) is an abundant native fish distributed in lakes and rivers of the Patagonia, and it is the frequent prey of other fishes, fish-eating birds, and mammals. Previous studies have shown that it is parasitized by 33 metazoan species and that the richness and composition of the parasite communities vary between lakes. The aim of the present work was to analyze the relationship between the composition of fish assemblages and the helminth component community structure of G. maculatus. Ten environmentally similar, small, shallow lakes, belonging to the Nahuel Huapi Lake basin, were chosen because of the differences in the native fish assemblages. Parasite community structure in G. maculatus varied according to the fish assemblage of each lake. The presence of the piscivorous fish Percichthys trucha regularly produced variations in the composition and richness at the component and infracommunity levels, as well as the percentage of autogenic parasite species in G. maculatus.
A Novel Phenylalanine-Based Targeting Signal Directs Telencephalin to Neuronal Dendrites

Neurons sort out a variety of functional molecules to appropriate subcellular destinations. Telencephalin (TLCN; intercellular adhesion molecule-5) is a cell adhesion molecule specifically localized to somatodendritic membranes in the telencephalic neurons. Here, we established a new in vivo strategy to analyze neuronal sorting mechanisms by ectopic expression of molecules of interest in the cerebellar Purkinje cells of transgenic mice. By using this system, we identified a novel dendritic targeting determinant in the cytoplasmic tail region of TLCN. A full-length TLCN ectopically expressed in the Purkinje cells was localized exclusively to dendrites but not to axons. In contrast, a deletion of cytoplasmic C-terminal 12 amino acids (residues 901-912) or a point mutation of Phe905 to Ala abrogated the dendrite-specific targeting with appearance of the truncated and point-mutated TLCN in both axons and dendrites. Furthermore, an addition of the C-terminal 17 amino acids (residues 896-912) of TLCN to an unrelated molecule (CD8) was sufficient for its specific targeting to dendrites in several types of neurons. Because the C-terminal region of TLCN does not contain any canonical dendritic targeting sequences such as the tyrosine-based motif or the dileucine motif, this study suggests a novel mechanism of protein trafficking to the dendritic compartment of neurons.
2016 Ieee International Conference on Big Data (big Data) Deep Learning in the Automotive Industry: Applications and Tools

—Deep Learning refers to a set of machine learning techniques that utilize neural networks with many hidden layers for tasks, such as image classification, speech recognition, language understanding. Deep learning has been proven to be very effective in these domains and is pervasively used by many Internet services. In this paper, we describe different automotive uses cases for deep learning in particular in the domain of computer vision. We surveys the current state-of-the-art in libraries, tools and infrastructures (e. g. GPUs and clouds) for implementing, training and deploying deep neural networks. We particularly focus on convolutional neural networks and computer vision use cases, such as the visual inspection process in manufacturing plants and the analysis of social media data. To train neural networks, curated and labeled datasets are essential. In particular, both the availability and scope of such datasets is typically very limited. A main contribution of this paper is the creation of an automotive dataset, that allows us to learn and automatically recognize different vehicle properties. We describe an end-to-end deep learning application utilizing a mobile app for data collection and process support, and an Amazon-based cloud backend for storage and training. For training we evaluate the use of cloud and on-premises infrastructures (including multiple GPUs) in conjunction with different neural network architectures and frameworks. We assess both the training times as well as the accuracy of the classifier. Finally, we demonstrate the effectiveness of the trained classifier in a real world setting during manufacturing process. I. INTRODUCTION Machine learning and deep learning has many potential applications in the automotive domain both inside the vehicle , e. g. advanced driving assistance systems (ADAS), autonomous driving, and outside the vehicle, e. g. during development , manufacturing and sales & aftersales processes. Machine learning is an essential component for use cases, such as predictive maintenance of vehicles, personalized infotainment and location-based services, business process automation, supply chain and price optimization. A common challenge of these applications is the need for storage and processing of large volumes of data as well as the necessity to deal with unstructured data (videos, images, text), e. g. from camera-based sensors on the vehicle or machines in the manufacturing process. To effectively utilize this kind of data, new methods, such as deep learning, are required. Deep learning [1], [2] refers to a set of machine learning algorithms that utilize large neural networks with many hidden layers …
Investigation on cobalt‐oxide nanoparticles cyto‐genotoxicity and inflammatory response in two types of respiratory cells

The increasing use of cobalt oxide (Co3O4) nanoparticles (NPs) in several applications and the suggested genotoxic potential of Co‐oxide highlight the importance of evaluating Co3O4 NPs toxicity. Cyto‐genotoxic and inflammatory effects induced by Co3O4 NPs were investigated in human alveolar (A549), and bronchial (BEAS‐2B) cells exposed to 1–40 µg ml–1. The physicochemical properties of tested NPs were analysed by transmission electron microscopy (TEM) and dynamic light scattering (DLS). Cytotoxicity was studied to analyze cell viability (WST1 test) and membrane damage (LDH assay), direct/oxidative DNA damage was assessed by the Formamido‐pyrimidine glycosylase (Fpg)‐modified comet assay and inflammation by interleukin (IL)‐6, IL‐8 and tumor necrosis factor‐alpha (TNF‐α) release (ELISA). In A549 cells, no cytotoxicity was found, whereas BEAS‐2B cells showed a viability reduction at 40 µg ml–1 and early membrane damage at 1, 5 and 40 µg ml–1. In A549 cells, direct and oxidative DNA damage at 20 and 40 µg ml–1 were detected without any effects on cytokine release. In BEAS‐2B cells, significant direct DNA damage at 40 µg ml–1 and significant oxidative DNA damage with a peak at 5 µg ml–1, that was associated with increased TNF‐α release at 1 µg ml–1 after 2 h and increased IL‐8 release at 20 µg ml–1 after 24 h, were detected. The findings show in the transformed alveolar cells no cytotoxicity and genotoxic/oxidative effects at 20 and 40 µg ml–1. In normal bronchial cells, moderate cytotoxicity, direct DNA damage only at the highest concentration and significant oxidative‐inflammatory effects at lower concentrations were detected. The findings confirm the genotoxic‐oxidative potential of Co3O4 NPs and show greater sensitivity of BEAS‐2B cells to cytotoxic and oxidative‐inflammatory effects suggesting the use of different cell lines and multiple end‐points to elucidate Co3O4 NPs toxicity. Copyright © 2015 John Wiley & Sons, Ltd.
Characterization of Zeolite in Zeolite-Geopolymer Hybrid Bulk Materials Derived from Kaolinitic Clays

Zeolite-geopolymer hybrid materials have been formed when kaolin was used as a starting material. Their characteristics are of interest because they can have a wide pore size distribution with micro- and meso-pores due to the zeolite and geopolymer, respectively. In this study, Zeolite-geopolymer hybrid bulk materials were fabricated using four kinds of kaolinitic clays (a halloysite and three kinds of kaolinite). The kaolinitic clays were first calcined at 700 °C for 3 h to transform into the amorphous aluminosilicate phases. Alkali-activation treatment of the metakaolin yielded bulk materials with different amounts and types of zeolite and different compressive strength. This study investigated the effects of the initial kaolinitic clays on the amount and types of zeolite in the resultant geopolymers as well as the strength of the bulk materials. The kaolinitic clays and their metakaolin were characterized by XRD analysis, chemical composition, crystallite size, 29Si and 27Al MAS NMR analysis, and specific surface area measurements. The correlation between the amount of zeolite formed and the compressive strength of the resultant hybrid bulk materials, previously reported by other researchers was not positively observed. In the studied systems, the effects of Si/Al and crystalline size were observed. When the atomic ratio of Si/Al in the starting kaolinitic clays increased, the compressive strength of the hybrid bulk materials increased. The crystallite size of the zeolite in the hybrid bulk materials increased with decreasing compressive strength of the hybrid bulk materials.
On the stability of plan costs and the costs of plan stability

Predicate selectivity estimates are subject to considerable run-time variation relative to their compile-time estimates, often leading to poor plan choices that cause inflated response times. We present here a parametrized family of plan generation and selection algorithms that replace, whenever feasible, the optimizer's solely cost-conscious choice with an alternative plan that is (a) guaranteed to be near-optimal in the absence of selectivity estimation errors, and (b) likely to deliver comparatively stable performance in the presence of arbitrary errors. These algorithms have been implemented within the PostgreSQL optimizer, and their performance evaluated on a rich spectrum of TPC-H and TPC-DS-based query templates in a variety of database environments. Our experimental results indicate that it is indeed possible to identify robust plan choices that substantially curtail the adverse effects of erroneous selectivity estimates. In fact, the plan selection quality provided by our algorithms is often competitive with those obtained through apriori knowledge of the plan search and optimality spaces. The additional computational overheads incurred by the replacement approach are miniscule in comparison to the expected savings in query execution times. We also demonstrate that with appropriate parameter choices, it is feasible to directly produce anorexic plan diagrams, a potent objective in query optimizer design.
Reoperations for Persistent or Recurrent Primary Hyperparathyroidism: Results of a Retrospective Cohort Study at a Tertiary Referral Center

Background Parathyroid reoperations are challenging and achieving a cure requires multidisciplinary treatment team cooperation. The aims of this study were to summarize our experience in revision surgery for persistent (pHPT) or recurrent primary hyperparathyroidism (rHPT) and to explore factors underlying failure to cure at initial surgery. Material/Methods This was a retrospective cohort study of patients who underwent reoperations for pHPT or rHPT at a tertiary referral center. The database of parathyroid surgery was searched for eligible patients (treated in the years 2000–2012). The primary outcome was the cure rate. All the patients were followed-up for at least 12 months postoperatively. Factors underlying failure to cure at initial surgery were reviewed based on hospital records. Results The study group comprised 88 patients (69 women, 19 men) operated on for persistent (n=57) or recurrent disease (n=31), who underwent 98 reoperations, including 26 (2.4%) patients first operated on at our institution, and 72 (81.8%) patients operated on elsewhere, but referred for revision surgery. A long-term cure was achieved in 83/88 patients (94.3%). The mean post-reoperation follow-up was 91.7 (12–176) months. Missed hyperfunctioning parathyroid gland was found on reoperation in eutopic position in 49 (55.5%) patients, and in ectopic position in 39 (44.3%) patients, including 20 (22.7%) cases of cervical ectopy and 19 (21.6%) cases of mediastinal ectopy. Conclusions Multidisciplinary treatment team cooperation at a tertiary referral center, consisting of an accurate preoperative localization, expertise in parathyroid re-explorations, and correct use of intraoperative adjuncts, contribute to the high success rate of parathyroid reoperations.
Biomechanical Perspectives on Concussion in Sport

Concussions can occur in any sport. Often, clinical and biomechanical research efforts are disconnected. This review paper analyzes current concussion issues in sports from a biomechanical perspective and is geared toward Sports Med professionals. Overarching themes of this review include the biomechanics of the brain during head impact, role of protective equipment, potential population-based differences in concussion tolerance, potential intervention strategies to reduce the incidence of injury, and common biomechanical misconceptions.
Falls in institutionalized older adults: risks, consequences and antecedents.

Objective: To analyze the occurrence of falls in institutionalized elderly addressing the risks, consequences and antecedents. Method: Cross-sectional study carried out with 45 older adults in Long-Term Care Facilities for the Older adult in João Pessoa, Brazil, in June and July 2016. A socio-demographic questionnaire and the Berg Balance Scale were applied, classifying as risk of fall scores lower than 45. Descriptive statistics and tests were conducted: independent t-test, Anova (Tukey), Chi-square, Mann Whitney. Statistically significance was p <0.05. Data were processed in SPSS version 19.0. Results: A total of 66.7% (30) falls occurred, 20% (9) of them in the external area, with 66.7% (30) of the participants having hypertension as a previous disease and, as consequence, the fracture was highlighted with 11.2% (5). The Berg Scale had different scores when compared to the falls suffered by the elderly and previous diseases influenced the occurrence of falls (p <0.05). Conclusion: It is necessary to implement public financing policies or partnerships that allow environments adaptations aiming at reducing the risks of falls. Objetivo: Analisar a ocorrência de quedas em idosos institucionalizados quanto aos riscos, consequências e antecedentes. Método: Estudo transversal, realizado com 45 idosos em Instituições de Longa Permanência para Idosos em João Pessoa/PB, Brasil, em junho e julho de 2016. Aplicou-se questionário sociodemográfico e Escala de Equilíbrio de Berg classificando risco de quedas quando escore inferior a 45. Realizou-se estatística descritiva e testes: t independente, Anova (Tukey), Qui-quadrado, Mann Whitney. Considerado significativamente estatístico p < 0,05 e processados no SPSS versão 19.0. Resultados: As quedas ocorreram em 66,7% (30), sendo 20% (9) na área externa, 66,7% (30) com doença prévia hipertensão e como consequência destacou-se fratura com 11,2% (5). A Escala de Berg avaliou pontuações diferentes (p < 0,05) quando comparadas às quedas sofridas pelos idosos, e as doenças prévias influenciaram ocorrência de quedas (p < 0,05). Conclusão: Necessita-se implementar políticas públicas de financiamento ou parcerias que possibilitem adaptação dos ambientes visando a redução dos riscos de quedas.
A Phylogenetic Analysis of the Genus Fragaria (Strawberry) Using Intron-Containing Sequence from the ADH-1 Gene

The genus Fragaria encompasses species at ploidy levels ranging from diploid to decaploid. The cultivated strawberry, Fragaria×ananassa, and its two immediate progenitors, F. chiloensis and F. virginiana, are octoploids. To elucidate the ancestries of these octoploid species, we performed a phylogenetic analysis using intron-containing sequences of the nuclear ADH-1 gene from 39 germplasm accessions representing nineteen Fragaria species and one outgroup species, Dasiphora fruticosa. All trees from Maximum Parsimony and Maximum Likelihood analyses showed two major clades, Clade A and Clade B. Each of the sampled octoploids contributed alleles to both major clades. All octoploid-derived alleles in Clade A clustered with alleles of diploid F. vesca, with the exception of one octoploid allele that clustered with the alleles of diploid F. mandshurica. All octoploid-derived alleles in clade B clustered with the alleles of only one diploid species, F. iinumae. When gaps encoded as binary characters were included in the Maximum Parsimony analysis, tree resolution was improved with the addition of six nodes, and the bootstrap support was generally higher, rising above the 50% threshold for an additional nine branches. These results, coupled with the congruence of the sequence data and the coded gap data, validate and encourage the employment of sequence sets containing gaps for phylogenetic analysis. Our phylogenetic conclusions, based upon sequence data from the ADH-1 gene located on F. vesca linkage group II, complement and generally agree with those obtained from analyses of protein-encoding genes GBSSI-2 and DHAR located on F. vesca linkage groups V and VII, respectively, but differ from a previous study that utilized rDNA sequences and did not detect the ancestral role of F. iinumae.
Efficient Community Detection Using Power Graph Analysis Special Theme : large-scale data processing in social networks

Understanding the structure of complex networks and uncovering the properties of their constituents has been for many decades at the center of study of several fundamental sciences, such as discrete mathematics and graph theory. Especially during the previous decade, we have witnessed an explosion in complex network data, with two cornerstone paradigms being the biological networks and the social networks. The large scale, but also the complexity, of these types of networks constitutes the need for efficient graph mining algorithms. In both examples, one of the most important tasks is to identify closely connected network components comprising nodes that share similar properties. In the case of biological networks, this could mean the identification of proteins that bind together to carry their biological function, while in the social networks, this can be seen as the identification of communities. Motivated by this analogy, we adapt the Power Graph Analysis methodology, for the first time to the best of our knowledge, to the field of community mining. The model was introduced in bioinformatics research and in this work is adapted to the problem of community detection in complex networks. The advances in the field of community mining allow us to experiment with widely accepted benchmark data sets, and our results show that the suggested methodology performs favorably against state of the art methods for the same task, especially in networks with large number of nodes. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Copyright 20XX ACM X-XXXXX-XX-X/XX/XX . $10.00.
Dependence of pinning on domain wall spin structure and notch geometry

In this work, we present a systematic investigation of the domain wall spin structure and notch geometries on the pinning field strength. We observed that for transverse domain wall, pinning is strongly dependent on the transversely varying energy profile of the wall. Domain walls are pinned at notches only when the notch provides a barrier to the higher energy component of the domain wall. For all notch shapes investigated, we observed that when the notch height/nanowire width > 0.3, the depinning field reaches a maximum and remains constant. We also note that the pinning of a domain wall at a notch is markedly sensitive to the angle of the notch with respect to the domain wall.