Miracle-dz/UniFAR-FTUs huggingface dataset:
N-dimensional quintic B-spline functions for solving n-dimensional partial differential equations

Abstract In continuation to what we started from developing the B-spline functions and putting them in n-dimensional to solve mathematical models in n-dimensions, we present in this article a new structure for the quintic B-spline collocation algorithm in n-dimensional. The quintic B-spline collocation algorithm is shown in three different formats: one, two, and three dimensional. These constructs are critical for solving mathematical models in different fields. The proposed method’s efficiency and accuracy are illustrated by their application to a few two- and three-dimensional test problems. We use other numerical methods available in the literature to make comparisons.
Confirmation and Description of the Larva of the Aquatic Dance Fly, Proclinopyga Melander (Diptera: Empididae: Clinocerinae)

Abstract. The larva of the aquatic dance fly genus Proclinopyga Melander is described for the first time. The larval association with adult stages was facilitated using COI mitochondrial DNA barcode sequences. The larvae of Proclinopyga are found in coarse substrates of riffles and other swift-flowing sections of streams and small rivers. The larvae infrequently occur in benthic samples collected from these habitat types, where they may co-occur with the larvae of other Empididae genera. The final instar larva is described and illustrated and a key to the larvae of genera of Clinocerinae of North America is updated.
Model Provenance Management in MLOps Pipeline

∗ Machine learning engineering is an important technology that has attracted the attention of academia and industry in the past two years. For AI to become a productivity of enterprises, it must be engineered to solve the problems of model development, deployment, management, prediction, and other lifecycle management, and MLOps system is the most concerned technology in the current machine learning engineering process. This paper starts from the training evolution process of intelligent computing models in machine learning engineering, focuses on the influence of data, training algorithms, and requirement indicators on the model evolution process, and gives the definition of Model Provenance and its evolutionary correlation elements. Based on the concept of model lineage, this paper designs a method to manage the model evolution process in the MLOps system and implements the related system.
Modelling Task Offloading Mobile Edge Computing

With the rapid growth of mobile devices (such as smart phones and IoT devices) and the upcoming 5G era, it has been considered that edge computing will play a significant role, which together with the Cloud server forms the Mobile Edge Computing (MEC) platform. In MEC, it is desired that the tasks originated from the mobile devices can be offloaded to run on the edge devices or on the cloud. Namely, when a mobile device deems that it can benefit from not running its task locally (in terms of reducing the execution time), it will make the offloading decision to run the task on the edge. But when the total number of tasks offloaded from the mobile devices to the edge exceeds the capacity of the edge, some tasks may be further offloaded from the edge to the cloud server. In this paper, we aim to model the task offloading behavior in MEC. The game theory is utilized to establish the model. The mixed strategy for each mobile device (i.e., the probability that a mobile device offloads its task) at the Nash Equilibrium is derived. Further, the makespan of all the tasks running on the MEC platform is modelled. The extensive experiments have been conducted and the results show that the offload game modelled in this paper works effectively.
MLPNeuzz: A Novel Neural Program Smoothing Method Based on Multi-Layer Perceptron

In recent years, using fuzzy methods to mine network security vulnerabilities has become a mainstream. Fuzzing is an effective vulnerability mining technology, which can find the potential vulnerability trigger point by traversing the program branch through some key algorithms. However, the traditional fuzzing methods exist some problems, such as redundant test cases, inefficient mutation strategy and so on. Therefore, a method combining machine learning with fuzzing has been proposed, which provides solutions to the above problems. Recently, someone proposes an effective fuzzer called NEUZZ, which uses a simple feedforward neural network (FNN) for neural program smoothing to model the branching behavior of the target program and improve the utilization of test cases. However, the traditional FNN model is easy to cause low learning efficiency and poor generalization ability and other problems. In order to solve these problems, a novel neural program smoothing method based on Multi-Layer Perceptron (MLP) is proposed in this paper, and we name the fuzzer as MLPNeuzz. MLPNeuzz can further collect edge coverage information and improve the smoothing effect of neural programs. In addition, we refine the original NEUZZ fuzzy method to make its fuzzy process more reasonable. Experiments on several real-world application programs show that the MLPNeuzz method proposed in this paper can achieve higher edge coverage than NEUZZ under the same time overhead.
Husbands' Plan to Participate in Birth Preparedness and Complication Readiness in Haramaya Health and Demographic Surveillance System Site, Eastern Ethiopia: A Community-Based Cross-Sectional Study

Background Partner involvement in maternal health services utilization remains a major public challenge in the developing world. Strategies of involving men in maternal health services are a critical and proven intervention for reducing maternal and neonatal mortality by ensuring safe delivery and reducing complications during childbirth. Moreover, the husbands' involvement during pregnancy helps their spouses to make timely decisions and avoid maternal delays, especially first and second delays. Although birth and complication readiness have been studied in developing countries such as Ethiopia, almost all previous researchers were focused primarily on women participants. Therefore, we aimed to investigate factors associated with husband involvement in birth preparedness and complication readiness plan in Haramaya Health and Demographic Surveillance site, Eastern Ethiopia. Methods A community-based cross-sectional study was conducted from March 1 to 30, 2020 among men whose wives were pregnant in Haramaya Health and Demographic Surveillance (HDSS) site in Eastern Ethiopia. The calculated sample size was 653, however while contacting 653 husbands only 630 had given the full interview, hence 630 respondents were remained in the analysis. Participants were approached through a systematic sampling technique. Data were collected using a pre-tested structured questionnaire through a face-to-face interview, and entered into Epidata version 3.1 and analyzed using SPSS version 22 (IBM SPSS Statistics, 2013). The prevalence was reported using proportion with 95% Confidence Interval (CI) and summary measures. Predictors were assessed using a multivariable logistic regression analysis model and reported using an adjusted odds ratio (AOR) with 95%CI. Statistical significance was declared at p < 0.05. Results Overall, the prevalence of the husband's plan to participate in birth preparedness and complication readiness was 59.6% (95%CI:56–64%). In the final model of multivariable analysis, predictors like husband's knowledge of birth preparedness and complication readiness [AOR = 4.18, 95%CI:2.05, 8.51], having a discussion with spouse on the place of delivery [AOR = 6.84, 95% CI: 4.17, 11.22], husband's knowledge of danger signs during labor and delivery [AOR = 3.19, 95 % CI: 1.52, 6.71], and making a postpartum plan[AOR = 2.30, 95 % CI: 1.38, 3.85] were factors statistically associated with husband's plan to participate in birth preparedness. Conclusions This study pointed out that two in every five husbands failed to plan birth preparedness and complication readiness. As a result, all stakeholders should emphasize male partners' education in terms of birth preparedness and complication readiness, as well as knowledge of danger signs during labor and delivery. They should also encourage male partners to discuss a place of delivery and have a postpartum plan in place to reduce potential complications related to labor and delivery.
d-Alanylation of Lipoteichoic Acids in Streptococcus suis Reduces Association With Leukocytes in Porcine Blood

Streptococcus suis (S. suis) is a common swine pathogen but also poses a threat to human health in causing meningitis and severe cases of streptococcal toxic shock-like syndrome (STSLS). Therefore, it is crucial to understand how S. suis interacts with the host immune system during bacteremia. As S. suis has the ability to introduce d-alanine into its lipoteichoic acids (LTAs), we investigated the working hypothesis that cell wall modification by LTA d-alanylation influences the interaction of S. suis with porcine blood immune cells. We created an isogenic mutant of S. suis strain 10 by in-frame deletion of the d-alanine d-alanyl carrier ligase (DltA). d-alanylation of LTAs was associated with reduced phagocytosis of S. suis by porcine granulocytes, reduced deposition of complement factor C3 on the bacterial surface, increased hydrophobicity of streptococci, and increased resistance to cationic antimicrobial peptides (CAMPs). At the same time, survival of S. suis was not significantly increased by LTA d-alanylation in whole blood of conventional piglets with specific IgG. However, we found a distinct cytokine pattern as IL-1β but not tumor necrosis factor (TNF)-α levels were significantly reduced in blood infected with the ΔdltA mutant. In contrast to TNF-α, activation and secretion of IL-1β are inflammasome-dependent, suggesting a possible influence of LTA d-alanylation on inflammasome regulation. Especially in the absence of specific antibodies, the association of S. suis with porcine monocytes was reduced by d-alanylation of its LTAs. This dltA-dependent phenotype was also observed with a non-encapsulated dltA double mutant indicating that it is independent of capsular polysaccharides. High antibody levels caused high levels of S. suis—monocyte—association followed by inflammatory cell death and strong production of both IL-1β and TNF-α, while the influence of LTA d-alanylation of the streptococci became less visible. In summary, the results of this study expand previous findings on d-alanylation of LTAs in S. suis and suggest that this pathogen specifically modulates association with blood leukocytes through this modification of its surface.
Diversity in Phenotypes Associated With Host Persistence and Systemic Virulence in Streptococcus sanguinis Strains

Streptococcus sanguinis is a pioneer commensal species of dental biofilms, abundant in different oral sites and commonly associated with opportunist cardiovascular infections. In this study, we addressed intra-species functional diversity to better understand the S. sanguinis commensal and pathogenic lifestyles. Multiple phenotypes were screened in nine strains isolated from dental biofilms or from the bloodstream to identify conserved and strain-specific functions involved in biofilm formation and/or persistence in oral and cardiovascular tissues. Strain phenotypes of biofilm maturation were independent of biofilm initiation phenotypes, and significantly influenced by human saliva and by aggregation mediated by sucrose-derived exopolysaccharides (EPS). The production of H2O2 was conserved in most strains, and consistent with variations in extracellular DNA (eDNA) production observed in few strains. The diversity in complement C3b deposition correlated with the rates of opsonophagocytosis by human PMN and was influenced by culture medium and sucrose-derived EPS in a strain-specific fashion. Differences in C3b deposition correlated with strain binding to recognition proteins of the classical pathway, C1q and serum amyloid protein (SAP). Importantly, differences in strain invasiveness into primary human coronary artery endothelial cells (HCAEC) were significantly associated with C3b binding, and in a lesser extent, with binding to host glycoproteins (such as fibrinogen, plasminogen, fibronectin, and collagen). Thus, by identifying conserved and strain-specific phenotypes involved in host persistence and systemic virulence, this study indicates potential new functions involved in systemic virulence and highlights the need of including a wider panel of strains in molecular studies to understand S. sanguinis biology.
Modeling Potential Impacts of Climate Change on the Distribution of Wooly Wolf (Canis lupus chanco)

The Central Asian wolves form a cohort within the wolf-dog clade known as the wooly wolf (Canis lupus chanco). These wolves are poorly studied and their current extent and distribution remain unknown. Apex predators already existing at higher elevations like wooly wolves can be severely affected by climate change because of the absence of suitable refuge. Concomitantly, in the era of Anthropocene, the change in land use land cover (LULC) is rapidly increasing. Even the most adaptable species occurring in human-dominated landscapes may fail to survive under the combined impact of both climate change and human pressure. We collected 3,776 presence locations of the wooly wolf across its range from published literature and compiled 39 predictor variables for species distribution modeling, which included anthropogenic factors, climatic, vegetation, and topographic features. We predicted the change in their distribution under different anthropogenic factors, climate change, and land-use land-cover change scenarios. Wolf showed affinity toward areas with low to moderately warm temperatures and higher precipitations. It showed negative relationships with forests and farmlands. Our future projections showed an expansion of wolf distribution and habitat suitability under the combined effects of future climate and LULC change. Myanmar and Russia had the introduction of high and medium suitability areas for the wooly wolf in future scenarios. Uzbekistan and Kazakhstan showed the consistent loss in high suitability areas while Mongolia and Bhutan had the largest gain in high suitability areas. The study holds great significance for the protection and management of this species and also provides opportunities to explore the impact on associated species.
Association Between Left Ventricular Geometry and Renal Outcomes in Patients With Chronic Kidney Disease: Findings From Korean Cohort Study for Outcomes in Patients With Chronic Kidney Disease Study

Background The impact of left ventricular (LV) geometry on the renal outcomes in patients with chronic kidney disease (CKD) has not been established yet. We aimed to investigate the association of LV geometry with renal outcomes and all-cause mortality in patients with pre-dialysis CKD. Methods A total of 2,144 subjects from the Korean Cohort Study for Outcome in Patients With Chronic Kidney Disease (KNOW-CKD) were categorized by LV geometry, which was defined by LV mass index and relative wall thickness [normal geometry, concentric remodeling, eccentric hypertrophy (eLVH), and concentric hypertrophy (cLVH)]. Study outcomes were composite renal events [decline of kidney function (the first occurrence of > 50% decline of eGFR or doubling of serum creatinine from the baseline) and onset of ESRD (initiation of dialysis or kidney transplantation) during follow-up periods)] and all-cause mortality. Results Cox regression analysis revealed that eLVH [adjusted hazard ratio (HR) 1.498, 95% confidence interval (CI) 1.197–1.873] and cLVH (adjusted HR 1.289, 95% CI 1.011–1.643) were associated with increased risk of composite renal events, whereas concentric remodeling (adjusted HR 1.881, 95% CI 1.135–3.118) and cLVH (adjusted HR 2.216, 95% CI 1.341–3.664) were associated with increased risk of all-cause mortality. Sensitivity analyses confirmed that concentric remodeling (adjusted HR 1.993, 95% CI 1.197–3.368) and eLVH (adjusted HR 1.588, 95% CI 1.261–2.001) are independently associated with all-cause mortality and composite renal events, respectively. Conclusion In conclusion, we report that LV geometry is significantly associated with adverse renal outcomes and all-cause mortality in patients with pre-dialysis CKD. Echocardiographic determination of LV geometry may help the early identification for the patients with high risk of CKD progression.
SAM: A Unified Self-Adaptive Multicompartmental Spiking Neuron Model for Learning With Working Memory

Working memory is a fundamental feature of biological brains for perception, cognition, and learning. In addition, learning with working memory, which has been show in conventional artificial intelligence systems through recurrent neural networks, is instrumental to advanced cognitive intelligence. However, it is hard to endow a simple neuron model with working memory, and to understand the biological mechanisms that have resulted in such a powerful ability at the neuronal level. This article presents a novel self-adaptive multicompartment spiking neuron model, referred to as SAM, for spike-based learning with working memory. SAM integrates four major biological principles including sparse coding, dendritic non-linearity, intrinsic self-adaptive dynamics, and spike-driven learning. We first describe SAM’s design and explore the impacts of critical parameters on its biological dynamics. We then use SAM to build spiking networks to accomplish several different tasks including supervised learning of the MNIST dataset using sequential spatiotemporal encoding, noisy spike pattern classification, sparse coding during pattern classification, spatiotemporal feature detection, meta-learning with working memory applied to a navigation task and the MNIST classification task, and working memory for spatiotemporal learning. Our experimental results highlight the energy efficiency and robustness of SAM in these wide range of challenging tasks. The effects of SAM model variations on its working memory are also explored, hoping to offer insight into the biological mechanisms underlying working memory in the brain. The SAM model is the first attempt to integrate the capabilities of spike-driven learning and working memory in a unified single neuron with multiple timescale dynamics. The competitive performance of SAM could potentially contribute to the development of efficient adaptive neuromorphic computing systems for various applications from robotics to edge computing.
Regional Analysis of Virtual Water Flow in View of Crop Consumption

It is important to identify virtual water for crop production (Pvw) and consumption (Cvw) and to analyse the virtual water flow among regions for a better understanding of water resource use. The estimation of virtual water flow in a basin or between regions of a basin can contribute to finding options for water‐saving strategies, such as changing cropping pattern and land use. The objective of this study was to analyse virtual water flow by using Pvw, Cvw and virtual water content (VWC). VWC of a product is the amount of fresh water required to produce the product, expressed as m3 t−1. The virtual water consumption rate in this study is defined as Cvw/Pvw, which indicates the extent of water shortage and self‐sufficiency of water use in a region. The Cvw and Pvw of 16 regions were computed and the virtual water flow in the Han and Nakdong River basins was analysed. The analysis indicated that a shift of rice cultivation between the upper and the lower regions of these basins can save between 503 and 752 Mm3 of VW in ideal conditions. Virtual water analysis can be useful for finding solutions to improve water productivity at basin level and to reduce pressure on local water resources. Copyright © 2016 John Wiley & Sons, Ltd.
Isobaric Tags for Relative and Absolute Quantitation Identification of Blood Proteins Relevant to Paroxetine Response in Patients With Major Depressive Disorder

Objectives Isobaric tags for relative and absolute quantitation (iTRAQ) is a proteomic investigation that could be utilized for rapid identification and quantification of proteins, which we would use to identify differentially expressed proteins in treatment responsive patients with major depressive disorder (MDD). Methods Six treatment responsive patients of MDD were recruited, and their peripheral blood mononuclear cell (PBMC) were collected before and after 4 weeks of paroxetine treatment. iTRAQ and Mascot search engine were used to detect differentially expressed proteins, which were then validated by Western blot. Results Two thousand one hundred and fifty three proteins were screened, and seven proteins showed differences of more than two-fold and 62 proteins with a differences of less than two-fold. Six proteins with commercially available antibodies were identified, and were validated by Western blot in 10 paroxetine responsive MDD patients. Putative hydroxypyruvate isomerase (HYI), eukaryotic translation initiation factor 4H (eIF4H), and RNA binding motif 8A (RBM8A) had statistically significant differences before and after treatment in the validation. Data are available via ProteomeXchange with identifier PXD028947. Conclusions By using iTRAQ and Western blot, we were able to identify HYI, eIF4H, and RAM8a to be the potential predictors of paroxetine treatment response in patients with MDD. This finding could help establish future individualized medicine.
Renal Function Mediates the Association Between Klotho and Congestive Heart Failure Among Middle-Aged and Older Individuals

Objective Using a newly released National Health and Nutrition Examination Survey (NHANES) data of serum Klotho, this study aimed to explore the relationship between Klotho and specific cardiovascular diseases (CVD), as well as the mediation effect of renal function, among middle-aged and older individuals within the general population. Methods This nationally representative cross-sectional study analyzed data from the 2007–2016 NHANES. A total of 13,765 participants, who aged 40 years or older, from the general population were examined. Klotho were divided into four groups based on median and interquartile range. The associations among Klotho (exposure), congestive heart failure (CHF; outcome), and renal function markers [estimated glomerular filtration rate (eGFR), blood urea nitrogen (BUN), uric acid (UA), and urine albumin-to-creatinine ratio (UACR); mediators] were investigated using mediation analysis. Results In comparison to the lowest quartile, Klotho in the highest quartile was independently associated with the prevalence of CHF (OR 0.59; 95% CI 0.46–0.77, p for trend = 0.001), but not with other individual CVDs. Klotho had a significant direct effect on the prevalence of CHF (all p < 0.001), while eGFR, BUN, UA, and UACR partly mediated the indirect effect of Klotho on the prevalence of CHF (all p < 0.05), explaining 19.51, 6.98, 13.93, and 0.71% of the association between Klotho and CHF, respectively. Additionally, restricted cubic spline regression demonstrated a linear association and negative correlation between Klotho level and CHF. Conclusion These findings suggest that Klotho is closely linked to CHF and renal function may be a key mediator of this association.