Miracle-dz/UniFAR-FTUs huggingface dataset:
Analyzing the impact of product configuration variations on advanced driver assistance systems with search

Due to the complexity of designing vehicle products and the inherent uncertainties in their operating environments, ensuring the safety of their Advanced Driver Assistance Systems (ADASs) becomes crucial. Especially, very minor changes to a vehicle design, for instance due to production errors or component degradation, might lead to failures of ADASs and, therefore, catastrophic consequences such as collision occurrences. Motivated by this, we propose a multi-objective search-based approach (employing NSGA-II) to find minimum changes to the configuration of a set of configurable parameters of a vehicle design, such that the collision probability is maximized, consequently leading to a reversal change in its safety. We conducted experiments, in a vehicle driving simulator, to evaluate the effectiveness of our approach. Results show that our approach with NSGA-II significantly outperforms the random search. Moreover, based on the detailed analyses of the results, we identify some parameters for which minor changes to their values lead the vehicle into collisions, and demonstrated the importance of studying the configuration of multiple parameters in a single search and the impact of their interactions on causing collisions.
GPU Accelerated Path Tracing of Massive Scenes

This article presents a solution to path tracing of massive scenes on multiple GPUs. Our approach analyzes the memory access pattern of a path tracer and defines how the scene data should be distributed across up to 16 GPUs with minimal effect on performance. The key concept is that the parts of the scene that have the highest amount of memory accesses are replicated on all GPUs. We propose two methods for maximizing the performance of path tracing when working with partially distributed scene data. Both methods work on the memory management level and therefore path tracer data structures do not have to be redesigned, making our approach applicable to other path tracers with only minor changes in their code. As a proof of concept, we have enhanced the open-source Blender Cycles path tracer. The approach was validated on scenes of sizes up to 169 GB. We show that only 1–5% of the scene data needs to be replicated to all machines for such large scenes. On smaller scenes we have verified that the performance is very close to rendering a fully replicated scene. In terms of scalability we have achieved a parallel efficiency of over 94% using up to 16 GPUs.
Distributed Secure Consensus for Second-Order Multi-Agent Systems under Replay Attacks

This paper is concerned with secure consensus of second-order discrete-time multi-agent systems under replay attacks. State information is transmitted over a communication network and each agent may be attacked by an adversary who is able to replay the state information sent from its neighbors maliciously. A consensus protocol based on distributed model predictive control is developed in the presence of replay attacks. The sufficient conditions for multi-agent systems to achieve secure consensus under replay attacks is derived. The effectiveness of the consensus protocol based on distributed model predictive control is illustrated through numerical examples.
Spinal Cord Injury Causes Reduction of Galanin and Gastrin Releasing Peptide mRNA Expression in the Spinal Ejaculation Generator of Male Rats

Spinal cord injury (SCI) in men is commonly associated with sexual dysfunction, including anejaculation, and chronic mid-thoracic contusion injury in male rats also impairs ejaculatory reflexes. Ejaculation is controlled by a spinal ejaculation generator consisting of a population of lumbar spinothalamic (LSt) neurons that control ejaculation through release of four neuropeptides including galanin and gastrin releasing peptide (GRP) onto lumbar and sacral autonomic and motor nuclei. It was recently demonstrated that spinal contusion injury in male rats caused reduction of GRP-immunoreactivity, but not galanin-immunoreactivity in LSt cells, indicative of reduced GRP peptide levels, but inconclusive results for galanin. The current study further tests the hypothesis that contusion injury causes a disruption of GRP and galanin mRNA in LSt cells. Male rats received mid-thoracic contusion injury and galanin and GRP mRNA were visualized 8 weeks later in the lumbar spinal cord using fluorescent in situ hybridization. Spinal cord injury significantly reduced GRP and galanin mRNA in LSt cells. Galanin expression was higher in LSt cells compared to GRP. However, expression of the two transcripts were positively correlated in LSt cells in both sham and SCI animals, suggesting that expression for the two neuropeptides may be co-regulated. Immunofluorescent visualization of galanin and GRP peptides demonstrated a significant reduction in GRP-immunoreactivity, but not galanin in LSt cells, confirming the previous observations. In conclusion, SCI reduced GRP and galanin expression in LSt cells with an apparent greater impact on GRP peptide levels. GRP and galanin are both essential for triggering ejaculation and thus such reduction may contribute to ejaculatory dysfunction following SCI in rats.
Advanced Second Language Learners of Mandarin Show Persistent Deficits for Lexical Tone Encoding in Picture-to-Word Form Matching

People who grow up speaking a language without lexical tones typically find it difficult to master tonal languages after childhood. Accumulating research suggests that much of the challenge for these second language (L2) speakers has to do not with identification of the tones themselves, but with the bindings between tones and lexical units. The question that remains open is how much of these lexical binding problems are problems of encoding (incomplete knowledge of the tone-to-word relations) vs. retrieval (failure to access those relations in online processing). While recent work using lexical decision tasks suggests that both may play a role, one issue is that failure on a lexical decision task may reflect a lack of learner confidence about what is not a word, rather than non-native representation or processing of known words. Here we provide complementary evidence using a picture-phonology matching paradigm in Mandarin in which participants decide whether or not a spoken target matches a specific image, with concurrent event-related potential (ERP) recording to provide potential insight into differences in L1 and L2 tone processing strategies. As in the lexical decision case, we find that advanced L2 learners show a clear disadvantage in accurately identifying tone mismatched targets relative to vowel mismatched targets. We explore the contribution of incomplete/uncertain lexical knowledge to this performance disadvantage by examining individual data from an explicit tone knowledge post-test. Results suggest that explicit tone word knowledge and confidence explains some but not all of the errors in picture-phonology matching. Analysis of ERPs from correct trials shows some differences in the strength of L1 and L2 responses, but does not provide clear evidence toward differences in processing that could explain the L2 disadvantage for tones. In sum, these results converge with previous evidence from lexical decision tasks in showing that advanced L2 listeners continue to have difficulties with lexical tone recognition, and in suggesting that these difficulties reflect problems both in encoding lexical tone knowledge and in retrieving that knowledge in real time.
A 13-Gene Metabolic Prognostic Signature Is Associated With Clinical and Immune Features in Stomach Adenocarcinoma

Patients with advanced stomach adenocarcinoma (STAD) commonly show high mortality and poor prognosis. Increasing evidence has suggested that basic metabolic changes may promote the growth and aggressiveness of STAD; therefore, identification of metabolic prognostic signatures in STAD would be meaningful. An integrative analysis was performed with 407 samples from The Cancer Genome Atlas (TCGA) and 433 samples from Gene Expression Omnibus (GEO) to develop a metabolic prognostic signature associated with clinical and immune features in STAD using Cox regression analysis and least absolute shrinkage and selection operator (LASSO). The different proportions of immune cells and differentially expressed immune-related genes (DEIRGs) between high- and low-risk score groups based on the metabolic prognostic signature were evaluated to describe the association of cancer metabolism and immune response in STAD. A total of 883 metabolism-related genes in both TCGA and GEO databases were analyzed to obtain 184 differentially expressed metabolism-related genes (DEMRGs) between tumor and normal tissues. A 13-gene metabolic signature (GSTA2, POLD3, GLA, GGT5, DCK, CKMT2, ASAH1, OPLAH, ME1, ACYP1, NNMT, POLR1A, and RDH12) was constructed for prognostic prediction of STAD. Sixteen survival-related DEMRGs were significantly related to the overall survival of STAD and the immune landscape in the tumor microenvironment. Univariate and multiple Cox regression analyses and the nomogram proved that a metabolism-based prognostic risk score (MPRS) could be an independent risk factor. More importantly, the results were mutually verified using TCGA and GEO data. This study provided a metabolism-related gene signature for prognostic prediction of STAD and explored the association between metabolism and the immune microenvironment for future research, thereby furthering the understanding of the crosstalk between different molecular mechanisms in human STAD. Some prognosis-related metabolic pathways have been revealed, and the survival of STAD patients could be predicted by a risk model based on these pathways, which could serve as prognostic markers in clinical practice.
The Impact of Excluding Nonrandomized Studies From Systematic Reviews in Rare Diseases: “The Example of Meta-Analyses Evaluating the Efficacy and Safety of Enzyme Replacement Therapy in Patients With Mucopolysaccharidosis”

Nonrandomized studies are usually excluded from systematic reviews. This could lead to loss of a considerable amount of information on rare diseases. In this article, we explore the impact of excluding nonrandomized studies on the generalizability of meta-analyses results on mucopolysaccharidosis (MPS) disease. A comprehensive search of systematic reviews on MPS patients up to May 2020 was carried out (CRD42020191217). The primary endpoint was the rate of patients excluded from systematic reviews if only randomized studies were considered. Secondary outcomes included the differences in patient and study characteristics between randomized and nonrandomized studies, the methods used to combine data from studies with different designs, and the number of patients excluded from systematic reviews if case reports were not considered. More than 50% of the patients analyzed have been recruited in nonrandomized studies. Patient characteristics, duration of follow-up, and the clinical outcomes evaluated differ between the randomized and nonrandomized studies. There are feasible strategies to combine the data from different randomized and nonrandomized designs. The analyses suggest the relevance of including case reports in the systematic reviews, since the smaller the number of patients in the reference population, the larger the selection bias associated to excluding case reports. Our results recommend including nonrandomized studies in the systematic reviews of MPS to increase the representativeness of the results and to avoid a selection bias. The recommendations obtained from this study should be considered when conducting systematic reviews on rare diseases.
The Usefulness of Functional Near-Infrared Spectroscopy for the Assessment of Post-Stroke Depression

Background: Post-stroke depression (PSD) is the most common mood disorder following stroke and is also the main factor that limits the recovery and rehabilitation of patients with stroke. The prevalence of PSD is ~30%. Since there is no gold standard for the diagnosis and evaluation of PSD, it is important to raise awareness of PSD and to establish methods for its evaluation, early diagnosis, and treatment. In the field of psychiatry, functional near-infrared spectroscopy (fNIRS) has been used as a diagnostic tool for the measurement of oxygenated hemoglobin (oxy-Hb). This study aimed to assess whether fNIRS could be applied in the diagnosis and evaluation of PSD. Methods: We recruited 45 patients with stroke, who were admitted to Nagasaki Kita Hospital between May 2015 and April 2019. The 17-item Hamilton Rating Scale for Depression (HAMD17), which is considered to be a useful screening and evaluation tool for PSD, was used for the assessment of patients after stroke; moreover, oxy-Hb was measured in the pre-frontal cortex. The subjects were divided into two groups: the depressed group (n = 13) and the non-depressed group (n = 32). We evaluated the correlation between the oxy-Hb integral values and HAMD17 scores. Results: We investigated the relationship between the oxy-Hb integral values and HAMD17 total scores, and found a negative correlation between them (ρ = −0.331, P < 0.005). There was a significant difference in the oxy-Hb integral values during the activation task period between the depressed and non-depressed groups (3.16 ± 2.7 and 1.71 ± 2.4, respectively; P = 0.040). The results indicated that the patients of the depressed group showed lower oxy-Hb integral values and lower activation in the frontal lobe in comparison with the patients of the non-depressed group. Conclusion: The present study highlights that the measurement of oxy-Hb by using fNIRS is a useful methodology for the diagnosis of PSD in patients after stroke.
Genome-Wide Differential Expression Profiling of Pulmonary circRNAs Associated With Immune Reaction to Pasteurella multocida in Goats

Pasteurella multocida is a highly versatile pathogen that infects a wide range of animals, including goats, causing pneumonia and hemorrhagic septicemia. Circular RNA (circRNA) is a type of non-coding RNA that plays an important role in regulating cellular metabolism. However, whether and how circRNA is involved in regulating immune responses in the goat lung has not been reported. Thus, this study was designed to examine the function of circRNA in goats infected with Pasteurella multocida. Goats were assigned into one of two groups: an uninfected control group (CK) and an infected group challenged with P. multocida. Compared with the CK group, which remained healthy, the infected goats showed clinical signs of infection, including depression, cough, nasal discharge, and dyspnea, along with elevated body temperature and lesions in the lung. Whole-transcriptome sequencing and small RNA sequencing were then performed using lung samples from goats from each group. A total of 138 circRNA, 56 microRNAs (miRNA), and 2,673 messenger RNA (mRNA) molecules were significantly differentially expressed in the P. multocida-infected group compared with the CK group. Randomly selected differentially expressed circRNA, miRNA, and mRNA molecules (n = 5 per group) were then validated by quantitative reverse-transcriptase polymerase chain reaction analysis. Gene ontology (GO) analysis of the source genes indicated that six immune-related terms were enriched among the differentially expressed cirRNA molecules, including inflammatory response, immune effector process, cell activation involved in immune response, cytokine-mediated signaling pathway, response to endogenous stimulus, and immune response. The corresponding circRNA molecules were then selected for construction of a competitive endogenous RNA network to identify networks that may be involved in the immune response to P. multocida infection. The results indicated that P. multocida HN01 may cause pneumonia and stimulate an immune response in goats via regulation of circRNA expression. This study presents the first comprehensive circRNA profile in response to P. multocida infection in goats, thus, providing a basis for understanding the function of circRNA in the host immune response to P. multocida infection.
Differential Organic Carbon Mineralization Responses to Soil Moisture in Three Different Soil Orders Under Mixed Forested System

Soil microbial respiration is one of the largest sources of carbon (C) emissions to the atmosphere in terrestrial ecosystems, which is strongly dependent on multiple environmental variables including soil moisture. Soil moisture content is strongly dependent on soil texture, and the combined effects of texture and moisture on microbial respiration are complex and less explored. Therefore, this study examines the effects of soil moisture on the mineralization of soil organic C Soil organic carbon in three different soils, Ultisol, Alfisol and Vertisol, collected from mixed forests of Georgia, Missouri, and Texas, United States , respectively. A laboratory microcosm experiment was conducted for 90 days under different moisture regimes. Soil respiration was measured weekly, and destructive harvests were conducted at 1, 15, 60, and 90 days after incubation to determine extractable organic C (EOC), phospholipid fatty acid based microbial community, and C-acquiring hydrolytic extracellular enzyme activities (EEA). The highest cumulative respiration in Ultisol was observed at 50% water holding capacity (WHC), in Alfisol at 100% water holding capacity, and in Vertisol at 175% WHC. The trends in Extractable Organic Carbon were opposite to that of cumulative microbial respiration as the moisture levels showing the highest respiration showed the lowest EOC concentration in all soil types. Also, extracellular enzyme activities increased with increase in soil moisture in all soils, however, respiration and EEA showed a decoupled relationship in Ultisol and Alfisol soils. Soil moisture differences did not influence microbial community composition.
Comprehensive Analysis of Peripheral Exosomal circRNAs in Large Artery Atherosclerotic Stroke

Exosomes are crucial vehicles in intercellular communication. Circular RNAs (circRNAs), novel endogenous noncoding RNAs, play diverse roles in ischemic stroke. Recently, the abundance and stability of circRNAs in exosomes have been identified. However, a comprehensive analysis of exosomal circRNAs in large artery atherosclerotic (LAA) stroke has not yet been reported. We performed RNA sequencing (RNA-Seq) to comprehensively identify differentially expressed (DE) exosomal circRNAs in five paired LAA and normal controls. Further, quantitative real-time PCR (qRT-PCR) was used to verify the RNA-Seq results in a cohort of stroke patients (32 versus 32). RNA-Seq identified a total of 462 circRNAs in peripheral exosomes; there were 25 DE circRNAs among them. Additionally, circRNA competing endogenous RNA (ceRNA) network and translatable analysis revealed the potential functions of the exosomal circRNAs in LAA progression. Two ceRNA pathways involving 5 circRNAs, 2 miRNAs, and 3 mRNAs were confirmed by qRT-PCR. In the validation cohort, receiver operating characteristic (ROC) curve analysis identified two circRNAs as possible novel biomarkers, and a logistic model combining two and four circRNAs increased the area under the curve compared with the individual circRNAs. Here, we show for the first time the comprehensive expression of exosomal circRNAs, which displayed the potential diagnostic and biological function in LAA stroke.
The Community Health Worker (CHW) Common Indicators Project: Engaging CHWs in Measurement to Sustain the Profession

Despite progress in documenting the outcomes of Community Health Worker interventions, the lack of standardized measures to assess CHW practice has made it difficult for programs to conduct reliable evaluations, and impossible to aggregate data across programs and regions, impeding commitment to sustainable, long-term financing of CHW programs. In addition, while CHWs have sometimes been involved as data collectors, they have seldom been engaged as full partners in all stages of evaluation and research. This manuscript details the current work being done by the CI Project, demonstrating how CHWs are able to contribute to the integrity, sustainability, and viability of CHW programs through the collaborative development and adoption of a set of common process and outcome constructs and indicators for CHW practice and CHW program implementation.
Genome-Wide Identification of Powdery Mildew Resistance in Common Bean (Phaseolus vulgaris L.)

Genome-wide association studies (GWAS) have been utilized to detect genetic variations related to several agronomic traits and disease resistance in common bean. However, its application in the powdery mildew (PM) disease to identify candidate genes and their location in the common bean genome has not been fully addressed. Single-nucleotide polymorphism (SNP) genotyping with a BeadChip containing 5398 SNPs was used to detect genetic variations related to PM disease resistance in a panel of 211 genotypes grown under two field conditions for two consecutive years. Significant SNPs identified on chromosomes Pv04 and Pv10 were repeatable, ensuring the phenotypic data’s reliability and the causal relationship. A cluster of resistance genes was revealed on the Pv04 of the common bean genome, coiled-coil-nucleotide-binding site–leucine-rich repeat (CC-NBS-LRR, CNL), and Toll/interleukin-1 receptor-nucleotide-binding site–leucine-rich repeat type (TIR-NBS-LRR, TNL)-like resistance genes were identified. Furthermore, two resistance genes, Phavu_010G1320001g and Phavu_010G136800g, were also identified on Pv10. Further sequence analysis showed that these genes were homologs to the disease-resistance protein (RLM1A-like) and the putative disease-resistance protein (At4g11170.1) in Arabidopsis. Significant SNPs related to two LRR receptor-like kinases (RLK) were only identified on Pv11 in 2018. Many genes encoding the auxin-responsive protein, TIFY10A protein, growth-regulating factor five-like, ubiquitin-like protein, and cell wall RBR3-like protein related to PM disease resistance were identified nearby significant SNPs. These results suggested that the resistance to PM pathogen involves a network of many genes constitutively co-expressed.
Untargeted Proteomics-Based Approach to Investigate Unintended Changes in Genetically Modified Maize for Environmental Risk Assessment Purpose

Profiling technologies, such as proteomics, allow the simultaneous measurement and comparison of thousands of plant components without prior knowledge of their identity. The combination of these non-targeted methods facilitates a more comprehensive approach than targeted methods and thus provides additional opportunities to identify genotypic changes resulting from genetic modification, including new allergens or toxins. The purpose of this study was to investigate unintended changes in GM Bt maize grown in South Africa. In the present study, we used bi-dimensional gel electrophoresis based on fluorescence staining, coupled with mass spectrometry in order to compare the proteome of the field-grown transgenic hybrid (MON810) and its near-isogenic counterpart. Proteomic data showed that energy metabolism and redox homeostasis were unequally modulated in GM Bt and non-GM maize variety samples. In addition, a potential allergenic protein—pathogenesis related protein −1 has been identified in our sample set. Our data shows that the GM variety is not substantially equivalent to its non-transgenic near-isogenic variety and further studies should be conducted in order to address the biological relevance and the potential risks of such changes. These finding highlight the suitability of unbiased profiling approaches to complement current GMO risk assessment practices worldwide.