Miracle-dz/UniFAR-FTUs huggingface dataset:
IDF-Autoware: Integrated Development Framework for ROS-Based Self-Driving Systems Using MATLAB/Simulink

This paper proposes an integrated development framework that enables co-simulation and operation of a Robot Operating System (ROS)-based self-driving system using MATLAB/Simulink (IDF-Autoware). The management of self-driving systems is becoming more complex as the development of self-driving technology progresses. One approach to the development of self-driving systems is the use of ROS; however, the system used in the automotive industry is typically designed using MATLAB/Simulink, which can simulate and evaluate the models used for self-driving. These models are incompatible with ROS-based systems. To allow the two to be used in tandem, it is necessary to rewrite the C++ code and incorporate them into the ROS-based system, which makes development inefficient. Therefore, the proposed framework allows models created using MATLAB/Simulink to be used in a ROS-based self-driving system, thereby improving development efficiency. Furthermore, our evaluations of the proposed framework demonstrated its practical potential.
Parametric Estimation of Volterra Kernel for the Dynamic Response of an Offshore Structure Using Laguerre Polynomials

The behavior of a nonlinear dynamic system under arbitrary excitation can be represented by the Volterra series if the Volterra kernels of different orders are known. This study presents a methodology for a direct estimation of the Volterra kernel coefficients up to the second-order using prepared data obtained by running a time-domain analysis of the system of interest. To avoid potential problems during kernel estimation, the Volterra kernel is expanded into a polynomial series using the Laguerre polynomials, and the coefficients of the Laguerre polynomials are then estimated using a least-square method. A nonlinear oscillator with a quadratic stiffness term is introduced, and the methodology is applied to check the applicability and accuracy. The methodology is applied to a more realistic engineering problem of a simplified riser under irregular wave excitation.
Association Between Aldehyde dehydrogenase-2 Polymorphisms and Risk of Alzheimer's Disease and Parkinson's Disease: A Meta-Analysis Based on 5,315 Individuals

Objective: A number of studies have reported that aldehyde dehydrogenase-2 (ALDH2) polymorphisms maybe associated with the risk of Alzheimer's disease (AD) and Parkinson's disease (PD). However, the results of such studies are inconsistent. We therefore conducted a meta-analysis to clarify the association between ALDH2 polymorphisms and the risk of AD and PD. Methods: Five online databases were searched and the relevant studies were reviewed from inception through May 10, 2018. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were calculated in each genetic model of the general population and various subgroups. Furthermore, we simultaneously performed heterogeneity, cumulative, sensitivity, and publication bias analyses. Results: Overall, nine case-control studies involving 5,315 subjects were included in this meta-analysis. Potential associations were found between the ALDH2 rs671 G>A polymorphism and the risk of AD (A vs. G: OR = 1.46, 95%CI = 1.01–2.11, P = 0.05, I2 = 84.2%; AA vs. GG: OR = 2.22, 95%CI = 1.03–4.77, P = 0.04, I2 = 79.2%; AA vs. GG+GA: OR = 1.94, 95%CI = 1.03–3.64, P =0.04, I2 = 71.1%). In addition, some similar results were observed in other subgroups. Moreover, no significant association between ALDH2 polymorphisms and PD risk. Conclusions: In conclusion, our meta-analysis indicated that the ALDH2 rs671 G>A polymorphism plays an important role in AD development.
Transcriptional Reprogramming of Arabidopsis thaliana Defence Pathways by the Entomopathogen Beauveria bassiana Correlates With Resistance Against a Fungal Pathogen but Not Against Insects

The entomopathogenic fungus Beauveria bassiana can adopt an endophytic lifestyle by colonising a wide array of plant species. Beauveria-colonised plants can show enhanced resistance against insects and plant pathogens alike. However, little is known about the molecular and physiological mechanisms that govern such interactions. Here, we assessed the effects of two B. bassiana strains (BG11, FRh2) on the growth of Arabidopsis thaliana and its resistance against two herbivore species and a phytopathogen. Plant responses were studied on the transcriptomic and metabolic level using microarrays and by measuring changes in defence-related phytohormones and glucosinolates (GLSs). Root inoculation with B. bassiana BG11 significantly increased plant growth, while FRh2 had no such effect. Both Beauveria strains decreased leaf lesion area caused by the phytopathogen Sclerotinia sclerotiorum but did not affect population growth of the aphid Myzus persicae or the growth of Plutella xylostella caterpillars. Microarray analyses of leaves from endophyte-inoculated A. thaliana provided evidence for transcriptional reprogramming of plant defence pathways, with strain-specific changes in the expression of genes related to pathogenesis, phytoalexin, jasmonic (JA), and salicylic acid (SA) signalling pathways. However, B. bassiana colonisation did not result in higher concentrations of JA and SA or major changes in leaf GLS profiles. We conclude that the endophyte B. bassiana induces plant defence responses and hypothesise that these contribute to enhanced resistance against S. sclerotiorum.
Interactions of Transition Metal Dichalcogenide Nanosheets With Mucin: Quartz Crystal Microbalance With Dissipation, Surface Plasmon Resonance, and Spectroscopic Probing

Ultrathin 2-dimensional transition metal dichalcogenides (TMDs) have become a class of high-potential materials in biomedicine due to their intriguing properties. They have been applied to solve biomedical challenges, such as biosensing, bioimaging, drug delivery, and cancer therapy. However, studies of the interactions between these materials and biomolecules are insufficient. Mucous tissue serves as a barrier to foreign hazardous substances and a gel layer for substance exchange. The main organic matter of mucous tissue is mucin, so it was selected as a model biomolecule to study its interactions with six different TMD nanosheets (NSs), including single-layered (SL), few-layered (FL), and small few-layered (SFL) MoS2 and WS2 NSs, using quartz crystal microbalance (QCM) with a dissipation monitor (QCM-D) and surface plasmon resonance (SPR). Additionally, UV absorption, fluorescence, and circular dichroism (CD) spectroscopy were applied to investigate the mechanism of the interactions and to study the conformational change of mucin. We found that the TMD NSs could adsorb on the mucin layer and affect its viscoelasticity. The results indicated that the SL WS2 NSs exhibited the highest initial absorption rate and the maximum absorption amount, while the SL MoS2 NSs exhibited the highest initial desorption rate. During the adsorption, the viscoelasticity variations of the mucin layer caused by the WS2 nanosheets were weaker than those caused by the MoS2 nanosheets. Furthermore, the conformational changes of mucin caused by the SL MoS2, SL WS2, and SFL MoS2 NSs were higher than those resulting from other TMD NSs. These findings provide important information on the interactions between TMD NSs and mucin and provide useful insights into the interfacial behavior of TMD NSs before they enter tissues.
Highly Saline Water Desalination Using Direct Contact Membrane Distillation (DCMD): Experimental and Simulation Study

The path for water molecules transported across a membrane in real porous membranes has been considered to be a constant factor in the membrane distillation (MD) process (i.e., constant tortuosity); as such, its effect on membrane performance at various operating conditions has been ignored by researchers. Therefore, a simultaneous heat and mass transfer model throughout the direct contact membrane distillation (DCMD) module was developed in this study by taking into account the hypothetical path across the membrane as a variable factor within the operating conditions because it exhibits the changes to the mass transfer resistance across the membrane under the DCMD run. The DCMD process was described by the developed model using a system of nonlinear equations and solved numerically by MATLAB software. The performance of the poly-tetra-fluoroethylene (PTFE) membrane was examined to treat 200 g/L NaCl saline at various operating conditions. The simulation results in the present work showed that the hypothetical proposed path across the membrane has a variable value and was affected by changing the feed temperature and feed concentration. The results estimated by the developed model showed an excellent conformity with the experimental results. The salt rejection remained high (greater than 99.9%) in all cases. The temperature polarization coefficient for the DCMD ranged between 0.88 and 0.967, and the gain output ratio (GOR) was 0.893. The maximum thermal efficiency of the system was 84.5%.
Entrepreneurial alertness: a systematic literature review

Abstract Recently, cognitive perspectives have garnered increasing attention in entrepreneurship alertness research. But the broader psychological basis of the alertness, which differentiates intrinsic and phasic aspects of alertness, has somehow been neglected, even though some entrepreneurship scholars have described alertness as the main cognitive capability of entrepreneurs in recognizing entrepreneurial opportunities. In this systematic review, the literature of entrepreneurial alertness has been critically examined. We categorize the previous works into five broad research themes: the alertness construct itself, its cognitive foundations, its operational measurement, the theoretical antecedents of alertness, and its consequences. We then identify two gaps where future research should direct greater efforts. First, past attention to the cognitive foundations of alertness has largely focused on its phasic aspects without exploration of the role of intrinsic alertness. The recent separate theorizing of opportunity creation/discovery has only begun to explore the potential of intrinsic alertness in opportunity spotting. Secondly, a lack of attention to establishing a clear definition of the alertness construct has hampered development of valid and robust measurement instruments, which may have confounded past efforts to empirically confirm the role of alertness in a range of theoretical models.
Reducing a Masked Implementation's Effective Security Order with Setup Manipulations And an Explanation Based on Externally-Amplified Couplings

Couplings are a type of physical default that can violate the independence assumption needed for the secure implementation of the masking countermeasure. Two recent works by De Cnudde et al. put forward qualitatively that couplings can cause information leakages of lower order than theoretically expected. However, the (quantitative) amplitude of these lower-order leakages (e.g., measured as the amplitude of a detection metric such as Welch’s T statistic) was usually lower than the one of the (theoretically expected) dth order leakages. So the actual security level of these implementations remained unaffected. In addition, in order to make the couplings visible, the authors sometimes needed to amplify them internally (e.g., by tweaking the placement and routing or iterating linear operations on the shares). In this paper, we first show that the amplitude of low-order leakages in masked implementations can be amplified externally, by tweaking side-channel measurement setups in a way that is under control of a power analysis adversary. Our experiments put forward that the “effective security order” of both hardware (FPGA) and software (ARM-32) implementations can be reduced, leading to concrete reductions of their security level. For this purpose, we move from the detection-based analyzes of previous works to attack-based evaluations, allowing to confirm the exploitability of the lower-order leakages that we amplify. We also provide a tentative explanation for these effects based on couplings, and describe a model that can be used to predict them in function of the measurement setup’s external resistor and implementation’s supply voltage. We posit that the effective security orders observed are mainly due to “externally-amplified couplings” that can be systematically exploited by actual adversaries.
An EEG/EMG/EOG-Based Multimodal Human-Machine Interface to Real-Time Control of a Soft Robot Hand

Brain-computer interface (BCI) technology shows potential for application to motor rehabilitation therapies that use neural plasticity to restore motor function and improve quality of life of stroke survivors. However, it is often difficult for BCI systems to provide the variety of control commands necessary for multi-task real-time control of soft robot naturally. In this study, a novel multimodal human-machine interface system (mHMI) is developed using combinations of electrooculography (EOG), electroencephalography (EEG), and electromyogram (EMG) to generate numerous control instructions. Moreover, we also explore subject acceptance of an affordable wearable soft robot to move basic hand actions during robot-assisted movement. Six healthy subjects separately perform left and right hand motor imagery, looking-left and looking-right eye movements, and different hand gestures in different modes to control a soft robot in a variety of actions. The results indicate that the number of mHMI control instructions is significantly greater than achievable with any individual mode. Furthermore, the mHMI can achieve an average classification accuracy of 93.83% with the average information transfer rate of 47.41 bits/min, which is entirely equivalent to a control speed of 17 actions per minute. The study is expected to construct a more user-friendly mHMI for real-time control of soft robot to help healthy or disabled persons perform basic hand movements in friendly and convenient way.
Secondary Students’ Identities in the Virtual Classroom

Though researchers have paid attention to the social aspect of students’ virtual and online learning, little attention has been paid to their identity. The present research intends to do so by studying students’ identities when learning high-level mathematics in the virtual classroom. Fourteen secondary school students participated in the research. Data were collected using interviews with the participants before and after participating in the virtual mathematics classroom. Data analysis was done using inductive and deductive content analysis, where the deductive analysis utilized the narrative framework developed by Sfard and Prusak. The research results indicated that the virtual identities of high-level mathematics students were impacted by three factors: the design of the virtual classroom, the teacher’s interactions with the student, and the personal characteristics of the student. In addition, the research results indicated that students’ identities, in terms of features and narratives, changed in the case of some students, but continued to be the same in the case of other students. The reasons behind the change or the absence of change were the three above factors and their interaction. It is concluded that the virtual course design needs to take into consideration the interaction aspect of students’ learning alongside factors that encourage their substantive learning.
Actual Evapotranspiration in the High Andean Grasslands: A Comparison of Measurement and Estimation Methods

Actual evapotranspiration (ETa) explains the exchange of water and energy between soil, land surface and atmosphere. Despite its importance, it remains difficult to measure directly. Grasslands represent a widespread ecosystem for which further assessment of the measurement and estimation of ETa is needed. Thus, the objective of this study was to compare measurements and estimations of ETa in a mountain grassland ecosystem made using different approaches. The study was conducted in the Zhurucay Ecohydrological Observatory, located in the high Andes of Ecuador between 3500 and 3900 m a.s. l. The study area is a representative site of the paramo ecosystem, in which the vegetation mainly consists of tussock grasslands. ETa was measured or estimated using the following methods: eddy-covariance (EC), volumetric lysimeters (Lys), water balance (WB), energy balance (EB), the calibrated Penman-Monteith equation (PMCal), and two hydrological models (the Probability Distribution Model (PDM) and the Hydrologiska Byrans Vattenbalansavdelning model (HBV-light)). During one year, precipitation (P) accumulated to 1094 mm while ETa (measured with EC) accumulated to 622 mm (with ETa/P = 0.57). On a daily basis, the EC method measured average ETa rates of 1.7 mm/day. The best daily estimates according to percentage bias (pbias), normalized root mean square error (nRMSE), Pearson’s correlation coefficient (r) and the volumetric coefficient (ve) came from the HBV-light model, followed by the PMCal and the PDM (pbias: -2 to -20 %, nRMSE: 12–15 %, r: 0.7–0.9, and ve: 0.7–0.8). On the other hand, the WB, EB, and Lys estimates showed a poor performance (pbias: -10 to -19 %, nRMSE: 25–93 %, r: -0.4 to 0.5, and ve: -0.5 to 0.7). As the methods used in this study are of different types (hydrological, micrometeorological and analytical), their suitability and applications are discussed in terms of their costs, temporal resolution and accuracy. This study identifies low-cost and easy-to-implement alternatives to EC measurements, such as hydrological models and the calibrated Penman-Monteith equation. This study also allows us to provide an increment of progress on the accurate closure of the water balance in grasslands.
Transient Receptor Potential Melastatin 8 (TRPM8)-Based Mechanisms Underlie Both the Cold Temperature-Induced Inflammatory Reactions and the Synergistic Effect of Cigarette Smoke in Human Bronchial Epithelial (16HBE) Cells

Transient receptor potential melastatin 8 (TRPM8) is a major receptor of cold environment. Recently, we found that cigarette smoke extract (CSE) upregulated TRPM8 mRNA and protein expression in bronchial tissues that made them more sensitive to cold stimuli. In our present study, we found that cold temperature (18°C)-induced activation of TRPM8 in 16HBE (human bronchial epithelial) cells facilitated Ca2+ influx and subsequently led to the increased expression of interleukin (IL)-6, IL-8, and tumor necrosis factor (TNF)-α via the upregulation of p-extracellular signal-regulated kinase (ERK) and the activation of NF-κB. In addition, 16HBE cells that co-stimulated with 18°C and CSE were used to explore the synergistic effect of CSE on cold temperature-induced inflammatory cytokine production as well as the possible involved signaling pathway. RT-PCR and western blot analysis revealed that CSE upregulated TRPM8 mRNA and protein level in 16HBE cells. Ca2+ imaging, western blot, and luciferase assay showed more robust increase in intracellular Ca2+ and promoted phosphorylated ERK, P38, and NF-κB activity, respectively, in 16HBE cells co-stimulated with CSE and cold temperature, and such alteration was attenuated by TRPM8 short hairpin RNA (shRNA) transfection and BCTC pretreatment. Furthermore, enhanced levels of IL-6, IL-8, and TNF-α showed by enzyme-linked immunosorbent assay (ELISA) were reduced by specific inhibitors of ERK and NF-κB. Collectively, our results suggest that mitogen-activated protein kinase (MAPK)/NF-κB signaling is involved in TRPM8-mediated cold temperature-induced inflammatory cytokine expression. In addition, CSE synergistically amplifies cold temperature-induced inflammatory factors release via upregulating TRPM8 expression and enhancing MAPK/NF-κB signaling pathway.
Functional Expression of Gloeobacter Rhodopsin in PSI-Less Synechocystis sp. PCC6803

The approach of providing an oxygenic photosynthetic organism with a cyclic electron transfer system, i.e., a far-red light-driven proton pump, is widely proposed to maximize photosynthetic efficiency via expanding the absorption spectrum of photosynthetically active radiation. As a first step in this approach, Gloeobacter rhodopsin was expressed in a PSI-deletion strain of Synechocystis sp. PCC6803. Functional expression of Gloeobacter rhodopsin, in contrast to Proteorhodopsin, did not stimulate the rate of photoheterotrophic growth of this Synechocystis strain, analyzed with growth rate measurements and competition experiments. Nevertheless, analysis of oxygen uptake and—production rates of the Gloeobacter rhodopsin-expressing strains, relative to the ΔPSI control strain, confirm that the proton-pumping Gloeobacter rhodopsin provides the cells with additional capacity to generate proton motive force. Significantly, expression of the Gloeobacter rhodopsin did modulate levels of pigment formation in the transgenic strain.
OSlms: A Web Server to Evaluate the Prognostic Value of Genes in Leiomyosarcoma

The availability of transcriptome data and clinical annotation offers the opportunity to identify prognosis biomarkers in cancer. However, efficient online prognosis analysis tools are still lacking. Herein, we developed a user-friendly web server, namely Online consensus Survival analysis of leiomyosarcoma (OSlms), to centralize published gene expression data and clinical datasets of leiomyosarcoma (LMS) patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). OSlms comprises of a total of 268 samples from three independent datasets, and employs the Kaplan Meier survival plot with hazard ratio (HR) and log rank test to estimate the prognostic potency of genes of interests for LMS patients. Using OSlms, clinicians and basic researchers could determine the prognostic significance of genes of interests and get opportunities to identify novel potential important molecules for LMS. OSlms is free and publicly accessible at http://bioinfo.henu. edu.cn/LMS/LMSList.jsp.
Lameness in Beef Cattle: UK Farmers' Perceptions, Knowledge, Barriers, and Approaches to Treatment and Control

Lameness in the beef industry has received little attention in the UK, despite the fact that it is a well-recognised problem in the dairy industry. The aims of this study were to (i) compare UK beef farmers' estimates of lameness prevalence to that of researchers, (ii) explore beef farmers' attitudes towards lameness, and (iii) help identify farmer reported barriers to lameness control and treatment. Beef farmers (11 finishing units and 10 suckler farms) were recruited from England and Wales. Farmers were asked to estimate their lameness prevalence, before a researcher conducted locomotion scoring using a five point scale, and a Bland Altman analysis performed. Face to face interviews were also conducted using a semi structured interview script aimed at capturing information such as current approaches and protocols as well as their views of lameness importance. Interviews were recorded and transcribed. An inductive thematic analysis was performed. All but two farmers underestimated lameness prevalence on their farms when compared to the researcher. Farmers initially underestimated lameness prevalence compared to the researchers estimates, with a mean underestimate of 7% (95% CI 5–9%). This is an important barrier to lameness detection and treatment. Thematic analysis identified four major themes: (1). Perception of lameness prevalence, (2). Technical knowledge and skills, (3). Perception of the impact of lameness, and (4). Barriers to the treatment and control of lameness. This study highlights that some approaches to lameness treatment are likely to be causing harm, despite being done with the intention to help the animal. There were four key areas of concern identified: recognition of lameness, treatment approaches, the training provided to farmers and confusion over transport and slaughter options available to farmers. This suggests an urgent need for future work to quantify and address the problem, and to provide evidence to justify the role of prevention and potentially start to break down barriers to control and treatment of lameness.