Miracle-dz/UniFAR-FTUs huggingface dataset:
Infill Planks for Horse Stable Constructions : Thoughts about Kick Resistance Determination and Alternative Material Development Zusammenfassung

In the context of animal welfare, namely reducing the risk of injury to horses kept in boxes, and to prevent compensation claims in the case of injury, infill planks in horse stables have to be resistant to powerful kicks. Because of the common practice of designing infill planks without considering the individual properties of the wood species used, this paper aims to describe the current situation of horse kick load determination, give an overview of possibilities to determine the kick resistance of infill planks and provide ideas for alternative wood species and engineered wood products to replace tropical timbers as plank material. The objective of this effort is to form a basis on which the strength of infill plank can be tested, respectively, impact resistant materials can be developed in future. As a result of the presented findings from impact bending tests on real-dimensioned infill planks, a suitable test set-up for impact bending test is proposed, and mechanical properties of laminated bamboo lumber, a popular plank material, are given. In this context, shock resistance according to DIN 52189 was found to be a useful guide when screening high impact resistant alternative wood species.
Extracellular Accumulation of Mannosylerythritol Lipids by a Strain of Candida antarctica

A yeast strain, isolated from the exudate of a tree, accumulated biosurfactants abundantly when grown on soybean oil as the sole carbon source. The biosurfactants were found to be a mixture of 4 mannosylerythritol lipids, including two new mannosylerythritol lipids as major components. The major components, which amounted to about 80% of the total lipids, were determined to be 4-O-(di-O-acetyl-di-O-alkanoyl-β-d-mannopyranosyl)-erythritol and 4-O-(mono-O-acetyl-di-O-alkanoyl-β-d-mannopyranosyl)-erythritol. The yeast strain was identified as Candida antarctica (Goto et al.) Kurtzman et al.
PVTOL Aerial Manipulators with a Rigid or an Elastic Joint: Analysis, Control, and Comparison

In this paper we present the dynamic Lagrangian modeling, system analysis, and nonlinear control of a robot constituted by a planar-vtol (PVTOL) underactuated aerial vehicle equipped with a rigid-or an elastic-joint arm, which constitutes an aerial manipulator. For the design of the aerial manipulator, we first consider generic offsets between the center of mass (CoM) of the PVTOL, and the attachment point of the joint-arm. Later we consider a model in which these two points are the coinciding. It turns out to be that the choice of this attachment point is significantly affecting the capabilities of the platform. Furthermore, in both cases we consider the rigid-and elastic-joint arm configurations. For each of the resulting four cases we formally assess the presence of exact linearizing and differentially flat outputs and the possibility of using the dynamic feedback linearization (DFL) controller. Later we formalize an optimal control problem exploiting the differential flatness property of the systems, which is applied, as an illustrative example, to the aerial throwing task. Finally we provide extensive and realistic simulation results for comparisons between different robot models in different robotic tasks such as aerial grasping and aerial throwing, and a discussion on the applicability of computationally simpler controllers for the coinciding-point models to generic-point ones. Further exhaustive simulations on the trajectory tracking and the high-speed arm swinging capabilities are provided in a technical attachment.
The Impact of Spiritual Wellbeing and Coping Strategies on Patients with Generalized Anxiety Disorder

The present study aimed to investigate the spiritual wellbeing and coping strategies of participants with generalized anxiety disorder (GAD). This study included 40 participants with GAD, all meeting the diagnostic criteria of the DSM IVTR. The Spiritual Wellness Inventory and the Coping Strategies Questionnaire were used as measuring tools. The data were analyzed by descriptive statistics, linear and stepwise regression, and Sobel ztest of mediation analysis. The stepwise regression analysis showed that out of 13 dimensions of spiritual wellness, only three dimensions (i.e., concept of hereafter, mystery, and meaning) significantly predicted GAD symptoms in negative direction. The mediational analysis showed that active practical and religious coping strategies did not mediate between the relationship of spiritual wellness and symptoms of GAD. Keyword: spiritual wellbeing, coping strategies, Generalized Anxiety Disorder, me-
Posterior Parietal Hypoperfusion in Differentiation of Alzheimer ’ s Disease , Frontotemporal Dementia and Vascular Cognitive Impairment

Single photon emission computed tomography (SPECT) brain imaging adds diagnostic information in dementia. In this study we evaluate the role of bilateral posterior parietal hypoperfusion (BPPH) finding in (SPECT) with 99m Tc-HMPAO, in the early diagnosing of AD and the differentiation of AD from frontotemporal dementia (FTD) and vascular cognitive impairment (VCI). In this study 106 subjects, are included with a main complaint of memory impairment or for a check-up of their cognitive state. Each patient was injected with 555 MBq 99m Tc-HMPAO(Ceretec-Amersham). Semiquantitative rCBF analysis was done. The patients were followed up every 3 months which was our gold standard of diagnosis. 25 healthy subjects that were among the patients are included in the study as our control group. Our patients based on clinical diagnosis and SPECT were differentiated as following: 1-AD group fulfilled NINCDS-ADRDA criteria (36 patients, 13 men, 23 women), which was consisted of two subgroups:(a) Strongly suggestive of AD (SSAD): included 32 patients with a bilateral posterior parietal and medial temporal hypoperfusion with or without reduction at frontal region. 30 of them showed to be AD. (b) Suggestive of AD (SAD): included 4 patients with a bilateral posterior parietal and unilateral medial temporal hypoperfusion which showed to suffer from AD. (2) FTD group: consisted of 7 patients, 3 male and 4 female fulfilled Neary criteria, with a bilateral prefrontal, medial and lateral temporal perfusion reduction in SPECT. 3VCI group with two subgroups of: (a) Strongly suggestive of vascular cognitive impairment (SSVCI): contained 11 patients, 7 male and 4 female fulfilled NINCDS-AIREN criteria with focal or multifocal infarct defects in SPET. 4 of them had focal large infarcts seen in CT images too. 7 patients had multinfarct dementia (MID). (b) Suggestive of vascular cognitive impairment (SVCI): included 28 patients who had definitely abnormal blood flow pattern but not clearly categorized as mentioned in groups above. 24 of these patients were diagnosed as having vascular dementia. We observed that posterior parietal (PP) was the specific region affected in the early stage of AD and could help us in differentiating AD from other dementias. SPECT, with the perfusion patterns that mentioned had the specificity of 97% in the diagnosis of AD. 25% of the patients with AD were in mild stage of the disease. Also the specificity of 100% and 86% for diagnosing FTD and VCI were obtained respectively. We conclude that bilateral posterior parietal hypoperfusion may play a crucial role in early diagnosing of AD and differentiating it from frontotemporal and vascular cognitive impairment.
Drug resistance profiles of mutations in the RET kinase domain

Alterations in the tyrosine kinase enzyme RET are found in thyroid and lung cancer. While RET TK inhibitors (TKIs) are used to treat thyroid cancer and are in clinical trials for RET fusion‐positive non‐small cell lung cancer, the impact of mutations in the RET kinase domain on drug sensitivity is largely uncharacterized.
NS gene of influenza virus A/swine/IA/15/30 increases the replication rate of A/Puerto Rico/8/34 in MDCK and Vero cells

The reverse genetics (rg) technique has become an alternative approach to produce influenza virus vaccine strains in mammalian cells. The most frequently used genetic backbone for rg–derived viruses is from A/Puerto Rico/8/34 (H1N1) (PR8) virus which is currently approved for vaccine production. Previously, we reported that reassortant viruses with 6 internal genes from A/swine/IA/15/1930 (H1N1) (IA30) and HA and NA from A/chicken/Thailand/KU14/2004 (H5N1) replicated at higher titers than the corresponding PR8 reassortant. In this study, we aim to examine the IA30 genes that can enhance PR8 virus replication. Growth kinetics of PR8 viruses encoding PB2, PB1, PA, NP or NS of IA30 was compared to that of the wild type PR8 (PR8/WT) virus. The replication rate of PR8/IA30NS was significantly higher than the PR8/WT virus in both MDCK and Vero cells. Plaque analysis was also performed in MDCK cells infected with the PR8 viruses encoding IA30 NS or PB1 (PR8/IA30NS or PR8/IA30PB1). It produced significant larger plaque size in the monolayer of MDCK cells, suggesting that PR8/IA30NS could spread to bystander cells more efficiently than PR8/IA30PB1. Our results reveal the function of IA30 NS as a replication enhancer. We suggest the use of IA30 NS in combination with 5 internal genes of PR8 plus HA and NA of the circulating strain in a 5:1:2 reverse genetics system to produce high growth reassortants.
Learning a hyperplane classi fi er by minimizing an exact bound on the VC dimension 1

The VC dimension measures the complexity of a learning machine, and a low VC dimension leads to good generalization. While SVMs produce state-of-the-art learning performance, it is well known that the VC dimension of a SVM can be unbounded; despite good results in practice, there is no guarantee of good generalization. In this paper, we show how to learn a hyperplane classifier by minimizing an exact, or Θ bound on its VC dimension. The proposed approach, termed as the Minimal Complexity Machine (MCM), involves solving a simple linear programming problem. Experimental results show, that on a number of benchmark datasets, the proposed approach learns classifiers with error rates much less than conventional SVMs, while often using fewer support vectors. On many benchmark datasets, the number of support vectors is less than one-tenth the number used by SVMs, indicating that the MCM does indeed learn simpler representations. & 2014 Elsevier B.V. All rights reserved.
LLNL-PROC-579552 Improving Conservation for First-Order System Least Squares Finite-Element Methods

The first-order system least-squares (FOSLS) finite element method for solving partial differential equations has many advantages, including the construction of symmetric positive definite algebraic linear systems that can be solved efficiently with multilevel iterative solvers. However, one drawback of the method is the potential lack of conservation of certain properties. One such property is conservation of mass. This paper describes a strategy for achieving mass conservation for a FOSLS system by changing the minimization process to that of a constrained minimization problem. In addition, an overlapping Schwarz process is used to make this strategy more robust and not add too much computational overhead to solving the system.
Differences in Hearing Acuity among “Normal-Hearing” Young Adults Modulate the Neural Basis for Speech Comprehension

Abstract In this paper, we investigate how subtle differences in hearing acuity affect the neural systems supporting speech processing in young adults. Auditory sentence comprehension requires perceiving a complex acoustic signal and performing linguistic operations to extract the correct meaning. We used functional MRI to monitor human brain activity while adults aged 18–41 years listened to spoken sentences. The sentences varied in their level of syntactic processing demands, containing either a subject-relative or object-relative center-embedded clause. All participants self-reported normal hearing, confirmed by audiometric testing, with some variation within a clinically normal range. We found that participants showed activity related to sentence processing in a left-lateralized frontotemporal network. Although accuracy was generally high, participants still made some errors, which were associated with increased activity in bilateral cingulo-opercular and frontoparietal attention networks. A whole-brain regression analysis revealed that activity in a right anterior middle frontal gyrus (aMFG) component of the frontoparietal attention network was related to individual differences in hearing acuity, such that listeners with poorer hearing showed greater recruitment of this region when successfully understanding a sentence. The activity in right aMFGs for listeners with poor hearing did not differ as a function of sentence type, suggesting a general mechanism that is independent of linguistic processing demands. Our results suggest that even modest variations in hearing ability impact the systems supporting auditory speech comprehension, and that auditory sentence comprehension entails the coordination of a left perisylvian network that is sensitive to linguistic variation with an executive attention network that responds to acoustic challenge.
Diagnostic accuracy study of loop mediated isothermal amplification in the detection of Mycobacterium tuberculosis in Pakistan

The study has been conducted in Armed Forces Institute of Pathology, Rawalpindi Pakistan from 2015 to 2017. The study was done to determine the adequacy of Loop-mediated Isothermal Amplification for the detection of Mycobacterium tuberculosis. A cross sectional study was done on 72 clinical sputum samples taken from the patient suspected of tuberculosis using a novel technique LAMP targeting IS6110 gene sequence for the first time in Pakistan. Six primers recognizing eight distinct regions on the target sequence were employed. The assay was performed in total volume of 25 μl containing primers, DNA polymerase, Fluorescent dye and sample incubated at 65°C for 60 minutes along with positive and negative controls. LAMP amplicons were detected by their fluorescence under UV light and compared with gold standard MGIT culture system and smear microscopy. Out of 72 total samples 60(83.3%) were LAMP positive and 61(84.7%) were MGIT positive. Its specificity, sensitivity is 100% and 98.36% respectively with PPV 100% and NPV 91.6%. According to our study the LAMP assay is suggested to be a potential nucleic acid based diagnostic method for TB detection in developing countries.
TYMS 2R3R polymorphism and DPYD [IVS]14+1G>A gene mutation in Mexican colorectal cancer patients.

OBJECTIVE To examine the association between TYMS 2R3R polymorphism and DPYD [IVS]14+1G>A mutation by comparing healthy subjects with colorectal cancer (CRC) patients in the Mexican population. METHOD Genotyping of the 2R/3R was performed by polymerase chain reaction (PCR) and [IVS]14+1G>A mutation by real-time PCR analysis. RESULTS The observed frequencies of the TYMS 2R3R polymorphism and the -[IVS]14+1G>A mutation in DPYD did not indicate an increased risk for CRC (p>0.05). However we observed an association of the 2R/2R (OR 3.08, 95% CI 1.66-6.08, p=0.0017) and heterozygous (OR 1.98, 95% CI 1.32-2.97, p=0.0012) genotypes as risk factors when comparing controls and CRC patients that were also tobacco consumers. An association between the genotype and the disease was evident. The distribution of the 2R/2R genotype and hematological toxicity (adjusted OR 2.26, 95% CI 1.54-4.45, p=0.0259), heterozygous (2R/3R) with tumor stage III-IV (OR 1.81, 95% CI 1.11-2.94, p=0.020) and 2R/2R-2R/3R in non-chemotherapy response CRC patients with hematological (OR 2.3, 95% CI 1.21-4.4, p=0.014) and gastric toxicities (OR 3.11, 95% CI 1.18-8.2, p=0.035) confirmed that this factor may significantly contribute to the CRC susceptibility. CONCLUSION TYMS 2R3R polymorphism and the -[IVS]14+1G>A mutation in DPYD was not associated with susceptibility to CRC. However, the 2R/2R and 2R/3R genotypes of TYMS polymorphism could significantly contribute to hematological and gastric toxicity in CRC patients in this sample population.
INVESTIGATING THE RELATION BETWEEN PREVALENCE OF ASTHMATIC ALLERGY WITH THE CHARACTERISTICS OF THE ENVIRONMENT USING ASSOCIATION RULE MINING

The prevalence of allergic diseases has highly increased in recent decades due to contamination of the environment with the allergy stimuli. A common treat is identifying the allergy stimulus and, then, avoiding the patient to be exposed with it. There are, however, many unknown allergic diseases stimuli that are related to the characteristics of the living environment. In this paper, we focus on the effect of air pollution on asthmatic allergies and investigate the association between prevalence of such allergies with those characteristics of the environment that may affect the air pollution. For this, spatial association rule mining has been deployed to mine the association between spatial distribution of allergy prevalence and the air pollution parameters such as CO, SO2, NO2, PM10, PM2.5, and O3 (compiled by the air pollution monitoring stations) as well as living distance to parks and roads. The results for the case study (i.e., Tehran metropolitan area) indicates that distance to parks and roads as well as CO, NO2, PM10, and PM2.5 is related to the allergy prevalence in December (the most polluted month of the year in Tehran), while SO2 and O3 have no effect on that.
The next wave in selective breeding: implementing genomic selection in aquaculture

Advanced animal breeding in aquaculture has reached a tipping point where the commercial implementation of genomic selection to improve productivity and disease resistance is becoming reality. However, the success of practical implementation of genomic selection depends on the specific aquaculture species, production system and available phenotyping and genetic resources. Using the experience learned from commercial programs for pearl oysters and marine shrimp, we highlight current benefits and options in cost-effective high-throughput genotyping and phenotyping technologies for genomic selection applications relevant to aquaculture species, followed by discussion of some of the lessons learnt when dealing with its practical implementation, including what is needed to build adequate genotype resources for non-model species; confounded breeding objective verse trait measurements; complex traits and unknown interactions; multi-family breeding schemes; multi-stage selection schemes, and transition to a genomic selection breeding program incorporating minimisation of inbreeding.
lgorithmic strategies for full waveform inversion : 1 D experiments

Full-waveform seismic inversion, i.e., the iterative minimization of the misfit between observed seismic data and synthetic data obtained by a numerical solution of the wave equation provides a systematic, flexible, general mechanism for reconstructing earth models from observed ground motion. However, many difficulties arise for highly resolved models and the associated large-dimensional parameter spaces and high-frequency sources. First, the least-squares datamisfit functional suffers from spurious local minima, which necessitates an accurate initial guess for the smooth background model. Second, total variation regularization methods that are used to resolve sharp interfaces create significant numerical difficulties because of their nonlinearity and neardegeneracy. Third, bound constraints on continuous model parameters present considerable difficulty for commonly used active-set or interior-point methods for inequality constraints because of the infinite-dimensional nature of the parameters. Finally, common gradient-based optimization methods have difficulties scaling to the many model parameters that result when the continuous parameter fields are discretized. We have developed an optimization strategy that incorporates several techniques address these four difficulties, including grid, frequency, and time-window continuation; primal-dual methods for treating bound inequality constraints and total variation regularization; and inexact matrixfree Newton-Krylov optimization. Using this approach, several computations were performed effectively for a 1D setting with synthetic observations.
Directed Graph Evolution from Euler-Lagrange Dynamics

In this paper, we develop a variational principle from the von Neumann entropy for directed graph evolution. We minimise the change of entropy over time to investigate how directed networks evolve under the Euler-Lagrange equation. We commence from our recent work in which we show how to compute the approximate von Neumann entropy for a directed graph based on simple in and out degree statistics. To formulate our variational principle we commence by computing the directed graph entropy difference between different time epochs. This is controlled by the ratios of the in-degree and out-degrees at the two nodes forming a directed edge. It also reveals how the entropy change is related to correlations between the changes in-degree ratio and in-degree, and their initial values. We conduct synthetic experiments with three widely studied complex network models, namely Erdos-Renyi random graphs, Watts-Strogatz small-world networks, and Barabasi-Albert scale-free networks, to simulate the in-degree and out-degree distribution. Our model effectively captures the directed structural transitions in the dynamic network models. We also apply the method to the real-world financial networks. These networks reflect stock price correlations on the New York Stock Exchange(NYSE) and can be used to characterise stable and unstable trading periods. Our model not only effectively captures how the directed network structure evolves with time, but also allows us to detect periods of anomalous network behaviour.
Phase Locking States of Bidirectionally Coupled Spiking Neural Networks

Macroscopic oscillations of different brain regions show phase relations that are persistent across time [5]. Termed as communication through coherence, such phase locking is believed to be implicated in a number of cognitive functions [7]. This suggests that there are mechanisms taking place at the cellular level that influence the network’s dynamic and structure macroscopic firing patterns. The question is then to identify the biological properties of neurons that permit such motifs to arise. Unfortunately, there is not yet a method for studying macroscopic phase locking, and one of the central issues we face in mathematical neuroscience is to bring about a clear understanding of the synaptic mechanisms responsible for its emergence.
DETECTING SUBVERSION ON TWITTER

Twitter is a dominant platform enabling millions of users to self-organize and communicate. Its popularity has attracted spammers seeking to capitalize on its infrastructure and user base. Indeed, Twitter has useful features that enable users to discover and comment on trending topics. Spammers can undermine the integrity of these features and exploit high-traffic topics, detracting from otherwise valuable discussions. In general, forged Twitter accounts negatively impact the user experience and must be dealt with. In this paper, we examine existing methods for detecting unwanted activity on Twitter and present a state-of-the-art system for identifying Twitter spammers. We gathered an appropriate dataset using Twitter’s APIs. Synthesizing ideas from the literature, we proposed options to improve our system’s performance. We specified certain metrics (“features”), calculated on gathered data, that assist in the classification of user accounts. The metrics fall into three primary categories: profilebased features, Tweet-based features, and network-based features. Despite having insufficient resources and data to draw strong conclusions at the time of writing, we expect to finish our research in the near future.