Miracle-dz/UniFAR-FTUs huggingface dataset:
Collagen V haploinsufficiency in a murine model of classic Ehlers–Danlos syndrome is associated with deficient structural and mechanical healing in tendons

Classic Ehlers–Danlos syndrome (EDS) patients suffer from connective tissue hyperelasticity, joint instability, skin hyperextensibility, tissue fragility, and poor wound healing due to heterozygous mutations in COL5a1 or COL5a2 genes. This study investigated the roles of collagen V in establishing structure and function in uninjured patellar tendons as well as in the injury response using a Col5a1+/− mouse, a model for classic EDS. These analyses were done comparing tendons from a classic EDS model (Col5a1+/−) with wild‐type controls. Tendons were subjected to mechanical testing, histological, and fibril analysis before injury as well as 3 and 6 weeks after injury. We found that Col5a1+/− tendons demonstrated diminished recovery of mechanical competency after injury as compared to normal wild‐type tendons, which recovered their pre‐injury values by 6 weeks post injury. Additionally, the Col5a1+/−tendons demonstrated altered fibril morphology and diameter distributions compared to the wild‐type tendons. This study indicates that collagen V plays an important role in regulating collagen fibrillogenesis and the associated recovery of mechanical integrity in tendons after injury. In addition, the dysregulation with decreased collagen V expression in EDS is associated with a diminished injury response. The results presented herein have the potential to direct future targeted therapeutics for classic EDS patients. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2707–2715, 2017.
Acousto-Optic Q-Switched Fiber Laser-Based Intra-Cavity Photoacoustic Spectroscopy for Trace Gas Detection

We proposed a new method for gas detection in photoacoustic spectroscopy based on acousto-optic Q-switched fiber laser by merging a transmission PAS cell (resonant frequency f0 = 5.3 kHz) inside the fiber laser cavity. The Q-switching was achieved by an acousto-optic modulator, achieving a peak pulse power of ~679 mW in the case of the acousto-optic modulation signal with an optimized duty ratio of 10%. We used a custom-made fiber Bragg grating with a central wavelength of 1530.37 nm (the absorption peak of C2H2) to select the laser wavelength. The system achieved a linear response (R2 = 0.9941) in a concentration range from 400 to 7000 ppmv, and the minimum detection limit compared to that of a conventional intensity modulation system was enhanced by 94.2 times.
Configurative Method Engineering - On the Applicability of Reference Modeling Mechanisms in Method Engineering

The aim of this paper is to discuss the applicability of reference modeling adaptation mechanisms in method engineering. Reference models are generic conceptual models that formalize state-of-the-art knowledge of a certain domain. Adaptation mechanisms can assist to tailor reference models to specific business or project needs. (Situational) Method engineering is concerned with the preparation of methods that fit the characteristics of a situation. Due to the similar requirements, it seems feasible to investigate to what extent the existing mechanisms of reference modeling have already been reflected in the context of method engineering. The result of a literature review points out that the mechanism of configuration has not been sufficiently considered yet. We suggest transferring the concept of reference model configuration to the domain of method engineering. This approach is supported by an example case utilizing the H2 toolset in which a method is configured according to project specific needs.
A Semi-Automatic Numerical Algorithm for Turing Patterns Formation in a Reaction-Diffusion Model

The Turing pattern formation is modeled by reaction-diffusion (RD) type partial differential equations, and it plays a crucial role in ecological studies. Big data analytics and suitable frameworks to manage and predict structures and configurations are mandatory. The processing and resolution procedures of mathematical models relies upon numerical schemes, and concurrently upon the related automated algorithms. Starting from a RD model for vegetation patterns, we propose a semi-automatic algorithm based on a smart numerical criterion for observing ecological reliable results. Numerical experiments are carried out in the case of spot’s formations.
Effect of Acoustic Noise on Optimal SynRM Design Regions

This paper investigates the rotor design optimization of synchronous reluctance machines (SynRMs) by using electromagnetic and structural finite-element simulations. Three conflicting objectives, i.e., average torque, torque ripple, and sound pressure level, were considered using a surrogate-based multi-objective approach. While the stator is fixed, the rotor flux barriers of a 33-slot 8-pole SynRM were geometrically varied to extract optimal design regions. These regions or constraints help decrease the computational time during the sampling procedure of a multiple-barrier design. Different numbers of flux barriers were studied and related to each other. Adding the sound pressure level was observed to affect previous results by spreading the Pareto front solutions across the design space.
Real time clustering of sensory data in wireless sensor networks

Data mining in wireless sensor networks (WSNs) is a new emerging research area. This paper investigates the problem of real time clustering of sensory data in WSNs. The objective is to cluster the data collected by sensor nodes in real time according to data similarity in a d-dimensional sensory data space. To perform in-network data clustering efficiently, a Hilbert Curves based mapping algorithm, HilbertMap, is proposed to convert a d-dimensional sensory data space into a two-dimensional area covered by a sensor network. Based on this mapping, a distributed algorithm for clustering sensory data, H-Cluster, is proposed. It guarantees that the communications for sensory data clustering mostly occur among geographically nearby sensor nodes and sensory data clustering is accomplished in in-network manner. Extensive simulation experiments were conducted using both real-world datasets and synthetic datasets to evaluate the algorithms. H-Cluster consistently achieves the lowest data loss rate, the highest energy efficiency, and the best clustering quality.
Association Between Cardiovascular Risk and Depressive Symptoms Among People With Serious Mental Illness

Abstract Depressive symptoms have debilitating effects on the physical health and functioning of people with serious mental illness. We examined change in depressive symptoms among overweight and obese adults with serious mental illness (n = 343) using data combined from two randomized trials comparing the 12-month In SHAPE program to a gym membership control condition. In SHAPE consists of a gym membership, weekly individual meetings with a fitness trainer, and instruction on healthy eating and nutrition. Depressive symptoms were measured at baseline, 3, 6, and 12 months. Change in depressive symptoms did not differ between groups, but depressive symptoms decreased over time across the entire sample (p = 0.045). At 12 months, reduced depressive symptoms were associated with clinically significant improved cardiorespiratory fitness (p = 0.030), 10% or more weight loss (p = 0.044), and cardiovascular risk reduction (p = 0.028) across both groups. Our findings suggest that participation in health promotion programs resulting in cardiovascular risk reduction may be associated with reduced depressive symptoms.
Full/half duplex based resource allocations for statistical quality of service provisioning in wireless relay networks

Integrating information theory with the principle of effective capacity, we propose the optimal resource allocation schemes for wireless full duplex and half duplex relay networks, respectively, to support the statistical quality-of-service (QoS) provisioning. In particular, we introduce a new control parameter, termed cancellation coefficient, to characterize the performance of full duplex relay transmission mode. For both amplitude-and-forward (AF) and decode-and-forward (DF) relay networks, we develop the dynamic hybrid resource allocation policies under full duplex and half duplex transmission modes to maximize the network throughput for the given delay QoS constraint measured by the QoS exponent. The numerical results obtained verify that our proposed resource allocation schemes can support diverse QoS requirements over wireless relay networks under full duplex and half duplex transmission modes. Our analysis indicates that the optimal effective capacity of perfect full duplex transmission mode is not the just twice as much as the optimal effective capacity of half duplex transmission mode. Our numerical analyses also show that the hybrid transmission mode can achieve better performance than just using full duplex or half duplex transmission mode alone.
ANALYSIS OF REPEATED STICKINESS MEASURES OF WHEAT DOUGH USING A TEXTURE ANALYZER

Stickiness of wheat dough using 51 international wheat genotypes was measured ten-times per sample using a texture analyzer and the improved Chen-Hoseney stickiness cell. Repeated measures analyses were carried out with the parameters adhesive force, adhesiveness, and stringiness of the force-time curves using the SAS MIXED procedure. The data revealed a high variability among observations from replicates of the same sample preparation. It is suggested to analyze a large (seven to ten) number of repeated measures per sample to account for the variation. Triplicate measures that result in reliable means with low standard errors for the particular lab conditions and test settings can be found by a repeated measure analysis.
Incremental GMMSD2 with applications to feature extraction

The generalized MMSD (GMMSD) is considered an efficient implementation of MMSD to extract discriminative information. However, a significant issue with the implementation of GMMSD is the complete recomputation of the training process when new training samples are presented. In this paper, we propose an alternative solution for feature extraction using the principles of GMMSD, which we call GMMSD2. GMMSD2 only requires the computation of centroid matrix, and it can overcome computational cost by applying efficient QR-updating techniques when new training samples are presented. Our experiments on FERET database demonstrate that incremental version of GMMSD2 eliminates the complete recomputation of the training process when new training samples are available, leading to significantly reduced computational cost.
TEXTURE ANALYSIS OF CANNED FISH

Comparaison des resultats de l'analyse sensorielle, des caracteristiques des courbes Brabender et des resultats donnes par l'Instron pour 3 especes de poissons en boite : maquereau, hareng, merlan bleu (ou poutassou)
Functionalization of liposomes: microscopical methods for preformulative screening

Abstract The development of smart delivery systems able to deliver and target a drug to the site of action is one of the major challenges in the field of pharmaceutical technology. The surface modification of nanocarriers, such as liposomes, is widely investigated either for increasing the blood circulation time (by pegylation) or for interacting with specific tissues or cells (by conjugation of a selective ligand as a monoclonal antibody, mAb). Microscopical analysis thereby is a useful approach to evaluate the morphology and the size owing to resolution and versatility in defining either surface modification or the architecture and the internal structure of liposomes. This contribution aims to connect the outputs obtained by transmission electron (TEM) and atomic force (AFM) microscopical techniques for identifying the modifications on the liposomal surface. To reach this objective, we prepared liposomes applying two different pegylation technologies and further modifying the surface by mAb conjugation. This work demonstrates the feasibility to apply the combined approach (TEM and AFM analysis) in the evaluation of the efficacy of a surface engineering process.
Robust kinase- and age-dependent dopaminergic and norepinephrine neurodegeneration in LRRK2 G2019S transgenic mice

Significance The lack of a robust transgenic mouse model of loss of dopamine (DA) neurons has greatly hindered the study of Parkinson’s disease caused by LRRK2 mutations. In this manuscript, we report the development of catecholaminergic neuron-specific Tet-inducible conditional transgenic LRRK2 G2019S and LRRK2 G2019S kinase-dead transgenic mice, and show that LRRK2-induced DA and norepinephrine neurodegeneration is kinase-dependent and can occur in a cell-autonomous manner. Moreover, these models reveal that α-synuclein pathology is LRRK2 kinase-dependent and that there are LRRK2 kinase-dependent defects in clathrin-dependent endocytic trafficking that accompany mutant LRRK2-mediated neurodegeneration. These LRRK2 models have the potential to advance our understanding of mutant LRRK2-mediated degeneration of DA neurons. Mutations in LRRK2 are known to be the most common genetic cause of sporadic and familial Parkinson’s disease (PD). Multiple lines of LRRK2 transgenic or knockin mice have been developed, yet none exhibit substantial dopamine (DA)-neuron degeneration. Here we develop human tyrosine hydroxylase (TH) promoter-controlled tetracycline-sensitive LRRK2 G2019S (GS) and LRRK2 G2019S kinase-dead (GS/DA) transgenic mice and show that LRRK2 GS expression leads to an age- and kinase-dependent cell-autonomous neurodegeneration of DA and norepinephrine (NE) neurons. Accompanying the loss of DA neurons are DA-dependent behavioral deficits and α-synuclein pathology that are also LRRK2 GS kinase-dependent. Transmission EM reveals that that there is an LRRK2 GS kinase-dependent significant reduction in synaptic vesicle number and a greater abundance of clathrin-coated vesicles in DA neurons. These transgenic mice indicate that LRRK2-induced DA and NE neurodegeneration is kinase-dependent and can occur in a cell-autonomous manner. Moreover, these mice provide a substantial advance in animal model development for LRRK2-associated PD and an important platform to investigate molecular mechanisms for how DA neurons degenerate as a result of expression of mutant LRRK2.
Estimating incident ultraviolet radiation exposure in the northern Gulf of Mexico during the Deepwater Horizon oil spill

Millions of barrels of oil were released into the Gulf of Mexico following the 2010 explosion of the Deepwater Horizon oil rig. Polycyclic aromatic hydrocarbons (PAHs) are toxic components of crude oil, which may become more toxic in the presence of ultraviolet (UV) radiation, a phenomenon known as photo‐induced toxicity. The Deepwater Horizon spill impacted offshore and estuarine sites, where biota may be co‐exposed to UV and PAHs. Penetration of UV into the water column is affected by site‐specific factors. Therefore, measurements and/or estimations of UV are necessary when one is assessing the risk to biota posed by photo‐induced toxicity. We describe how estimates of incident UV were determined for the area impacted by the Deepwater Horizon oil spill, using monitoring data from radiometers near the spill, in conjunction with reference spectra characterizing the composition of solar radiation. Furthermore, we provide UV attenuation coefficients for both near‐ and offshore sites in the Gulf of Mexico. These estimates are specific to the time and location of the spill, and fall within the range of intensities utilized during photo‐induced toxicity tests performed in support of the Deepwater Horizon Natural Resource Damage Assessment (NRDA). These data further validate the methodologies and findings of phototoxicity tests included in the Deepwater Horizon NRDA, while underscoring the importance of considering UV exposure when assessing possible risks following oil spills. Environ Toxicol Chem 2018;37:1679–1687. © 2018 SETAC
Haze as key CMP output parameter

In silicon wafer manufacturing, the Haze parameter is commonly used to characterize the finishing surface quality [1]. For oxide planarization, the usual CMP output parameters are removal rate, non uniformity and defectivity, like scratches or remaining particles, while Haze values, although directly available on the standard defect metrology tool, are not usually exploited. Understanding and characterization of the impact of process variations on wafer surface conditions and identifying potential surface damage become critical for smaller device size. In this work we propose a correlation between key CMP input parameters and post-CMP surface quality through Haze measurements on TEOS wafers. As Haze can be influenced by film thickness, it was measured on several oxide thickness pre CMP and compared to polished wafers targeting the same thickness, using different consumable set. Influence of pad type, slurry pH, abrasive size and type (colloidal, fumed) was investigated. Process parameters impact (polish time, applied pressure, platen speed) on surface quality was also estimated. Finally, acid versus alkaline post-CMP cleaning influence on Haze values was quantified. Relation of these parameters to surface quality is verified also by AFM measurements and is discussed in order to propose Haze as key CMP output parameter in an advanced CMP process.
A Stereological Study of Synapse Number in the Epileptic Human Hippocampus

Hippocampal sclerosis is the most frequent pathology encountered in resected mesial temporal structures from patients with intractable temporal lobe epilepsy (TLE). Here, we have used stereological methods to compare the overall density of synapses and neurons between non-sclerotic and sclerotic hippocampal tissue obtained by surgical resection from patients with TLE. Specifically, we examined the possible changes in the subiculum and CA1, regions that seem to be critical for the development and/or maintenance of seizures in these patients. We found a remarkable decrease in synaptic and neuronal density in the sclerotic CA1, and while the subiculum from the sclerotic hippocampus did not display changes in synaptic density, the neuronal density was higher. Since the subiculum from the sclerotic hippocampus displays a significant increase in neuronal density, as well as a various other neurochemical changes, we propose that the apparently normal subiculum from the sclerotic hippocampus suffers profound alterations in neuronal circuits at both the molecular and synaptic level that are likely to be critical for the development or maintenance of seizure activity.
A Walnut-Enriched Diet Affects Gut Microbiome in Healthy Caucasian Subjects: A Randomized, Controlled Trial

Regular walnut consumption is associated with better health. We have previously shown that eight weeks of walnut consumption (43 g/day) significantly improves lipids in healthy subjects. In the same study, gut microbiome was evaluated. We included 194 healthy subjects (134 females, 63 ± 7 years, BMI 25.1 ± 4.0 kg/m2) in a randomized, controlled, prospective, cross-over study. Following a nut-free run-in period, subjects were randomized to two diet phases (eight weeks each); 96 subjects first followed a walnut-enriched diet (43 g/day) and then switched to a nut-free diet, while 98 subjects followed the diets in reverse order. While consuming the walnut-enriched diet, subjects were advised to either reduce fat or carbohydrates or both to account for the additional calories. Fecal samples were collected from 135 subjects at the end of the walnut-diet and the control-diet period for microbiome analyses. The 16S rRNA gene sequencing data was clustered with a 97% similarity into Operational Taxonomic Units (OTUs). UniFrac distances were used to determine diversity between groups. Differential abundance was evaluated using the Kruskal–Wallis rank sum test. All analyses were performed using Rhea. Generalized UniFrac distance shows that walnut consumption significantly affects microbiome composition and diversity. Multidimensional scaling (metric and non-metric) indicates dissimilarities of approximately 5% between walnut and control (p = 0.02). The abundance of Ruminococcaceae and Bifidobacteria increased significantly (p < 0.02) while Clostridium sp. cluster XIVa species (Blautia; Anaerostipes) decreased significantly (p < 0.05) during walnut consumption. The effect of walnut consumption on the microbiome only marginally depended on whether subjects replaced fat, carbohydrates or both while on walnuts. Daily intake of 43 g walnuts over eight weeks significantly affects the gut microbiome by enhancing probiotic- and butyric acid-producing species in healthy individuals. Further evaluation is required to establish whether these changes are preserved during longer walnut consumption and how these are linked to the observed changes in lipid metabolism.
Preschoolers Continually Adjust Their Epistemic Trust Based on an Informant's Ongoing Accuracy.

Children aged 4-7 years (N = 120) played four rounds of a find-the-sticker game. For each round, an informant looked into two cups and made a claim about which cup held a sticker. At the end of each round, children guessed the sticker's location, and then the sticker's actual location was revealed. For three of the rounds, the informant accurately reported the sticker's location. But critically, for one round-either Round 1, 2, or 3-she was inaccurate. Children continually adjusted their trust in the informant as they obtained more information about her accuracy. Relations between the informant's pattern of accuracy and children's trust were robust, neither mediated nor moderated by children inferences about her intent or traits.
Curcumin increases exosomal TCF21 thus suppressing exosome-induced lung cancer

Curcumin is a novel drug for lung cancer treatment. However, the mechanism underlying the anti-tumor effect of curcumin remains elusive. Previous evidences indicated that, the methylating transferase DNMT1 is downregulated by curcumin, and the transcription factor 21 (TCF21) is suppressed by DNMT1. We hereby attempt to elucidate the correlation between curcumin treatment and TCF21 expression. Exosomes derived from curcumin-pretreated H1299 cells were used to treat BEAS-2B cells, which induced proliferation, colony formation and migration of BEAS-2B cells. An increase in TCF21 expression in response to curcumin was also seen, as revealed by real-time PCR (RT-PCR) and western blot. Analysis using the GEO database (access #GSE21210) indicated that a positive correlation existed between TCF21 levels and lung cancer patient survival. TCF21 overexpression and knockdown was introduced to H1299 cells through lentiviral system, which led to suppression and promotion of tumor growth, respectively. We also demonstrated that DNMT1 expression was downregulated by curcumin. Therefore, curcumin exerts its anti-cancer function by downregulating DNMT1, thereby upregulating TCF21.
Online user behavior: A decade's perspective

Online user's behavior identification is to find the user's way of internet access. It is the way of searching behavior characteristics of users, and their goal of web access. The behavior varies as per requirement of user, facility provided by the application and users knowledge. Online user behavior study is helpful for businesses, for different applications, to provide security if user deviates from the normal way of behavior, etc. This paper presents the study of online user's behavior since 2008 to 2017. The methods are mentioned which are used by the existing systems to identify behavior of user, and also few methods are used to identify and separate normal and suspicious users.