Miracle-dz/UniFAR-FTUs huggingface dataset:
Tertiary Vascular Accesses: Which One do You Control?

Introduction: Vascular access for hemodialysis of choice remains the Arteriovenous Fistulas (AVF) of the Upper Limb, the creation of Lower Limb (LL) arteriovenous fistula is an alternative to the depletion of vascular access sites to the upper limb. The most used surgical technique is the transposition of the femoral vein; recent and poorly known technique. Material and methods: Through two clinical observations, we report our experience in the creation of exotic vascular approaches (AVF-LL). Discussion: The complete exhaustion of the veins of both upper limbs and the presence of venous disease occlusive central veins is a major problem in the creation of FAV upper limb, the most commonly used alternative to the lower limb is the transposition of the femoral vein described for the first time in 2000 by Jackson. Conclusion: The depletion of vascular sites is a delicate problem, hence the interest of knowing how to use the tertiary vascular approaches, particularly fistulas of the lower limb.
The financial benefits of eLearning

In the pioneering days of eLeaming, many institutions suffered from significant levels of investment in eLearning initiatives that brought poor returns. Increasingly, eLeaming projects are required to justify the budgets they request from decision-makers. However, the benefits of eLearning in tertiary education tend to be less quantitatively obvious than the financial gains that corporate training through eLeaming can realise. This paper examines the issues faced by tertiary educators when comparing their eLeaming activities with those of corporate trainers, and suggests ways in which specific Learning projects, both courses and elements within courses, might be justified using CBA (cost-benefit analysis) and ROI(return on investment). The approach suggests ways in which the financially intangible aspects of improved learning and institutional reputation might be considered when justifying eLeaming expenditure.
Veri(cid:12)cation of memory access for deep learning compilers

The succeed of deep learning recently leads to the emergence of many deep-learning-specialized accelerators that are designed as a distributed system with shared hierarchical memory. On the software side, compilers must take into account this complexity and ensure that the generated assembly program is correct. In this paper, we tackle the problem of verifying memory accesses or data transfers in an assembly program generated by our deep learning compiler, and report some preliminary results. Given an assembly program generated by the compiler from a source program, and a correct assembly simulator, we (cid:12)rst run the simulator to simulate the execution of the assembly program in order to generate a sequence of data transfers. We then verify the sequence of data transfers against a correct sequence that is generated directly from the source program. We propose a novel data structure, called address tensor, that can capture both information of input data from the source program and addresses in the assembly program. Address tensors are very convenient to correctly generate a sequence of data transfers from the source program.They are also (cid:13)exible enough to adapt to new data transfer strategies in the compiler. Our veri(cid:12)cation has been using during the development of the compiler, which helps us quickly (cid:12)nd bugs and validate generated assembly programs.
Basic Study on Detection of Outer Boundary of Arterial Wall Using Its Longitudinal Motion

The longitudinal motion of the arterial wall can be observed in a B-mode image obtained by recent ultrasonic diagnostic equipment. In this study, the longitudinal displacement was quantitatively estimated by the block matching of RF echoes using cross correlation. However, the estimated longitudinal displacement is discrete depending on the spacing between two ultrasound beams of about 0.1 mm. Such an accuracy is not sufficient for tracking the region of interest (ROI) in the arterial wall. Therefore, the spacing of 0.1 mm is reduced using the interpolation of measured RF echoes to improve the tracking of the ROI in the displacement estimation. In this study, the optimum parameter in the interpolation was investigated. The spatial distribution of longitudinal displacements along the arterial radial direction was estimated using the optimum parameter. There were significant differences between the longitudinal displacements in the arterial wall and those in the region considered to be tissue outside the arterial wall. These results show the possibility of using this method to identify the outer boundary of the adventitia, which has not been achieved by conventional ultrasonic imaging.
An Assessment of the Environmental Impacts of Transgenic Triploid Populus tomentosa in Field Condition

Populus tomentosa grow rapidly, but are salt susceptible. To quickly and efficiently gain new poplar breeds with better salt resistance, a DREB transcription factor derived from Atriplex hortensis was transformed into triploid Populus tomentosa by our lab, which significantly improved the salt tolerance of host plants. However, environmental impacts of transgenic plants must be assessed before large-scale cultivation in China. Here, we conducted a field trial of AhDREB1 transgenic and non-transgenic triploid Populus tomentosa to assess the impact of transgenic trees on rhizospheric soil microbial communities and allelopathic activity of leaves. No significant differences in the number of soil microbes present were detected between the transgenic lines and the non-transgenic controls. The allelopathic activity of leaves from both the transgenic and non-transgenic lines varied with sampling time, but did not differ significantly between the transgenic and non-transgenic lines. These results indicate that the impact on the environment of AhDREB1 transgenic P. tomentosa did not differ significantly from that of the non-transformed controls for the variables observed in this field trial. We also investigated the persistence of AhDREB1 genes in decomposing transgenic poplar leaf on the soil under natural conditions for five months, and our data indicated that fragments of the genetically modified DNA were not detectable in the field after more than two months. We used a triphenyl tetrazolium chloride test (TTC) (or pollen germination method) and hybridization to test the pollen viability and fertility, respectively, of the transgenic and non-transgenic trees and the results showed that the pollen viability of both the transgenic and non-transgenic trees was extremely low in 2016; the receptor plant may have been sterile.
A Unique Tidal Frequency to the Damage Induced Vibration of Planetary Gear System

Structures and dynamics of planetary gears are very different from fixed axis gears. Special attentions to fault diagnostics of planetary gear system need to be carefully studied. In this paper, a distinctive nature of damage induced vibration of planetary gear box, namely tidal frequency, considering fault transmission paths of planetary gear system is discussed and proposed. Artificial planetary sun gear fault is introduced to an experimental test rig, the proposed tidal frequency to planetary sun gear faults are demonstrated and it may be a promising feature for planetary gear system condition monitoring. Keywords-planetary gear system; fault diagnostic; tidal frequency
The Social Status Of Judo Athletes

The research aimed to determine the social status structure of male and female judo athletes. In order to determine the social status structure a total of 200 athletes (100 males and 100 females) were examined. To assess the social status, a model designed by Saksida and Petrovic as well as Appendix INST2 and questionnaire SSMIN (Boli, Popovic, Karanov & all 2015) were applied. All the data in this study were processed at the Multidisciplinary Research Center of the Faculty of Sport and Physical Education, University of Pristina, through the system of data processing software programs DRSAOFT developed by Popovic, D. (1980,1993) and Momirovic, K. & Popovic , D. (2003). The algorithm and program applied in this study are fully presented and the results of this program are analyzed. In order to determine the latent structure of social status of judo athletes, a method of component factor analysis was used. Using component analysis of variables for assessing the social status of judo athletes and applying Momirovic`s B6 criterion, three characteristic roots which can be considered statistically significant were obtained. The total percentage of the explained variability of the applied system of variables is 37.45%. By examining Table European Scientific Journal April 2016 /SPECIAL/ edition ISSN: 1857 – 7881 (Print) e ISSN 18577431 205 1, it can be seen that the first characteristic root extracts 18.75% of the explained variance, the second 10.21%, and the third only 8.45%.
Habitat persistence, habitat availability and the evolution of dispersal

Many organisms live in ephemeral habitats, making dispersal a vital element of life history. Here, we investigate how dispersal rate evolves in response to habitat persistence, mean habitat availability and landscape pattern. We show that dispersal rate is generally lowered by reduced habitat availability and by longer habitat persistence. However, for habitats that persist for an average of ten times the length of a generation, we show a clear non–monotonic relationship between habitat availability and dispersal rate. Some patterns of available habitat result in populations with dispersal polymorphisms. We explain these observations as a metapopulation effect, with the rate of evolution a function of both within–population and between–population selection pressures. Individuals in corridors evolve much lower dispersal rates than those in the mainland populations, especially within long, narrow corridors. We consider the implications of the results for conservation.
Social Support as a Stress-Buffer: A Multi-Method Investigation.

People exposed to stressful experiences should be less negatively affected if they receive higher rather than lower levels of social support. This proposition was tested by investigating the 'stress buffering. ' role of social support in a way that allowed comparison between conceptually different measures related to the construct of support. Results indicate that the quantity of helping behavior received and the number ol helpers in the support network are not the critical features of social support. support that is rated as satisfying, however, does provide effective assistance in coping with stress. The kinds of support received in different stress situations and the individual's ability to use this support are logical foci for further research. (Author/CS)
Pricing Patents for Licensing in Standard Setting Organisations: Making Sense of FRAND Commitments

We explore potential methods for assessing whether licensing terms for intellectual property declared essential within a standard setting organization can be considered fair, reasonable, and non-discriminatory (FRAND). We first consider extending Georgia-Pacific to a standard setting context. We then evaluate numeric proportionality, which is modelled after certain patent pool arrangements and which has been proposed in a pending FRAND antitrust suit. We then turn to two economic models with potential. The first—the efficient component-pricing rule (ECPR)—is based on the economic concept of market competition. The second—the Shapley value method—is based on cooperative game theory models and social concepts for a fair division of rents. Interestingly, these two distinct methods suggest a similar benchmark for evaluating FRAND licenses, but ones which might appeal differently to the courts and competition authorities in the US as compared to Europe. We find that under any approach, patents covering “essential” technologies with a greater contribution to the value of the standard and without close substitutes before the standard gets adopted should receive higher royalty payments after the adoption of the standard.
Addressing Imbalanced Classes Problem of Intrusion Detection System Using Weighted Extreme Learning Machine

The main issues of the Intrusion Detection Systems (IDS) are in the sensitivity of these systems toward the errors, the inconsistent and inequitable ways in which the evaluation processes of these systems were often performed. Most of the previous efforts concerned with improving the overall accuracy of these models via increasing the detection rate and decreasing the false alarm which is an important issue. Machine Learning (ML) algorithms can classify all or most of the records of the minor classes to one of the main classes with negligible impact on performance. The riskiness of the threats caused by the small classes and the shortcoming of the previous efforts were used to address this issue, in addition to the need for improving the performance of the IDSs were the motivations for this work. In this paper, stratified sampling method and different cost-function schemes were consolidated with Extreme Learning Machine (ELM) method with Kernels, Activation Functions to build competitive ID solutions that improved the performance of these systems and reduced the occurrence of the accuracy paradox problem. The main experiments were performed using the UNB ISCX2012 dataset. The experimental results of the UNB ISCX2012 dataset showed that ELM models with polynomial function outperform other models in overall accuracy, recall, and F-score. Also, it competed with traditional model in Normal, DoS and SSH classes.
Estimation of Genetic Parameters for Four Reproduction Component Traits in Two Chinese Indigenous Pig Breeds

The reproduction component traits are important components of sow efficiency. The objective of this study was to evaluate the phenotypic and genetic parameters of four reproduction component traits (age at puberty (AP), preweaning number dead (PND), weaning to service interval (WSI), and intra-individual SD in litter size (IISDLS)) of sows in two Chinese indigenous pig breeds. Available reproductive records including 22,591 piglets born from 2,054 litters by 574 Jiangquhai sows and 464 Meishan sows were used in this investigation. A set of mixed models and restricted maximum likelihood methodology were used for the multiple trait analyses of these traits. The results showed that the estimates of heritabilities (±standard error) for AP, PND, WSI and IISDLS were 0.40±0.05, 0.06±0.03, 0.20±0.02 and 0.09±0.03 in Jiangquhai sows, and 0.35±0.06, 0.0±50.03, 0.18±0.03 and 0.10±0.04 in Meishan sows, respectively. There was moderate genetic correlation between AP and WSI, while there were low genetic correlations between the other pairwise traits. The genetic correlations were positive for most of the pairwise traits, except for the one between AP and IISDLS. The results indicated that all traits except for AP were difficult to make genetic improvement by traditional selection methods due to low heritabilities and the favorable improvement of AP might result in unfavorable changes of IISDLS due to the trend of genetic antagonism.
Dark halo mass function in a prescribed spherical host perturbation - Press-Schechter theory with statistical constraints

Here proposed a modification of the Press‐Schechter theory a llowing for the presence of a host density perturbation ‐ host halo or void. The perturbation is accounted as statistical constraints in a form of linear functionals of the random overdensity field. Deviation of the background density within perturbation is interpreted in a pseudo-cosmological sense. Resulting mass function of sub-haloes depends on the perturbation parameters: its mean overdensity, spatial scale, and spatial momenta of higher orders. Applications of the theory to superclusters, voids and bias problem are briefly observed. In its pres ent form, the theory can describe the clustering properties of sub-haloes inside a non-viria lized host only. Possible fix of this drawback is also discussed.
Simultaneous Occurrence of the Braess and Emission Paradoxes

Braess’ paradox is well-known and examined. However, the emission paradox is not. Without considering the emission paradox, the road network improvement that mitigates congestion may increase harmful vehicular emissions. In this paper, we analytically examine the occurrence of the emission paradox and the simultaneous occurrence of Braess’ and emission paradoxes in the classical Braess’ network. We ascertain that the occurrence of the emission paradox depends on the demand for travel, the parameters of link performance functions as well as link emission factors. We also find that Braess’ and emission paradoxes do not always occur at the same time, and that the emission paradox is more likely to occur than the Braess paradox in some networks. More importantly, we discover that under some conditions of parameters in link performance functions, the emission paradox does occur but Braess’ paradox does not. This implies that road network design for mitigating congestion alone may not be able to avoid the increase in vehicular emissions. A more comprehensive view of road network design considering both congestion and emissions simultaneously is necessary to avoid the occurrence of the emission paradox.
Knowledge-Based Learning through Feature Generation

Machine learning algorithms have difficulties to generalize over a small set of examples. Humans can perform such a task by exploiting vast amount of background knowledge they possess. One method for enhancing learning algorithms with external knowledge is through feature generation. In this paper, we introduce a new algorithm for generating features based on a collection of auxiliary datasets. We assume that, in addition to the training set, we have access to additional datasets. Unlike the transfer learning setup, we do not assume that the auxiliary datasets represent learning tasks that are similar to our original one. The algorithm finds features that are common to the training set and the auxiliary datasets. Based on these features and examples from the auxiliary datasets, it induces predictors for new features from the auxiliary datasets. The induced predictors are then added to the original training set as generated features. Our method was tested on a variety of learning tasks, including text classification and medical prediction, and showed a significant improvement over using just the given features.
Local nematic susceptibility in stressed BaFe 2 As 2 from NMR electric field gradient measurements

The electric field gradient (EFG) tensor at the $^{75}$As site couples to the orbital occupations of the As p-orbitals and is a sensitive probe of local nematicity in BaFe$_2$As$_2$. We use nuclear magnetic resonance to measure the nuclear quadrupolar splittings and find that the EFG asymmetry responds linearly to the presence of a strain field in the paramagnetic phase. We extract the nematic susceptibility from the slope of this linear response as a function of temperature and find that it diverges near the structural transition in agreement with other measures of the bulk nematic susceptibility. Our work establishes an alternative method to extract the nematic susceptibility which, in contrast to transport methods, can be extended inside the superconducting state.
5 Animal Models of Parkinson’s Disease

: Parkinson’s disease (PD) is a heterogenous disease with a varying age of onset, symptoms, and rate of progression. This heterogeneity requires the use of a variety of animal models to study different aspects of the disease. Neurotoxin-based approaches include exposure of rodents or non-human primates to 6-OHDA, MPTP, and agrochemicals such as the pesticide rotenone, the herbicide paraquat, and the fungicide maneb. Acute exposure to neurotoxins induces motor deficits and rapid nigro-striatal dopaminergic cell death by disrupting mitochondrial function and/or increasing oxidative stress, while chronic administration of neurotoxins induces progressive models which can include alpha-synuclein ( α -synuclein) aggregates. Genetic-based approaches to model Parkinson’s disease include transgenic models and viral vector-mediated models based on genes linked to monogenic Parkinson’s disease, including SNCA, LRRK2, UCH-L1, PRKN, PINK1, and and DJ-1, as well as manipulation of dopaminergic transcription factors. SNCA mutations, overexpression, and introduction of α -synuclein preformed fibrils induce toxic protein aggregates and variable nigro-striatal neurodegeneration and motor deficits, depending on the specific model. Species, genetic background of a Disease strain, and environment affect the display of symptoms and neurodegenerative hallmarks of animal models. These models can be combined to study the interplay between genetics and environment and untangle the heterogeneity and mechanisms underlying Parkinson’s disease. In this chapter, we discuss the strengths and limitations of mouse, rat, and non-human primate models of Parkinson’s disease.
Fuzzy Logic techniques for Interpreting and Evaluating Pedagogy of Teacher Behavior and Capability to Transform Knowledge into Practice

Current literature and common practices suggest that there is no consistent method available to interpret and evaluate the performance of a teacher. Due to its inherent vagueness and uncertainty, this research work aims to analyze the effectiveness of teacher depending upon various factors influencing quality of teacher using fuzzy logic. The first part studies various factors of professional behavior, interpersonal behavior and personal behavior of the teachers from student’s perspective to impart quality education. In the second part, fuzzy inference mechanism as suggested by Mamdani is designed and developed to decide the possible quality of performance of teacher from student’s point of view. The paper concludes by observing that the proposed fuzzy logic based interpretation of comprehensive quality of performance of teacher is consistent with those judged by the experts in the field and can be used to predict the possible quality of teachers Keywords-Teacher behavior; Teacher evaluation; Academic development; Students achievement; Fuzzy Logic; Chi-Square
Klinisch-psychologische Interventionen beim Hypertoniker

Psychosocial Interventions in hypertensives. Psychosocial risk factors such as depression, anxiety, stress, socioeconomic factors and personality traits, including their impact on lifestyle-behavior, will be discussed in regard to the development and maintenance of arterial hypertension. Based on these factors, potential benefits and efficacy of the progressive muscle relaxation and slow breathing technique will be evaluated and motivational aspects of lifestylechange will be discussed. J Hypertonie 2016; 20 (2): 35–9.