Miracle-dz/UniFAR-FTUs huggingface dataset:
Phylogenetic and Evolutionary Genomic Analysis of Listeria monocytogenes Clinical Strains in the Framework of Foodborne Listeriosis Risk Assessment

Listeria monocytogenes is one of the most important foodborne pathogens responsible for listeriosis, a severe disease with symptoms ranging from septicemia, meningoencephalitis, and abortion. Given the strong impact of listeriosis on human health and the difficulty of controlling L. monocytogenes along the food production chain, listeriosis has become a priority subjected to molecular surveillance in European Union/European Economic Area since 2007. From 2018, surveillance is based on whole-genome sequence using the core genome multilocus sequence type. The complete sequences of 132 clinical strains were used to define the evolutionary relatedness among subtypes of L. monocytogenes isolated in Italy from 2010 to 2016, allowing the identification of clades and/or clusters associated with outbreaks or sporadic cases of listeriosis. All the strains analyzed are clustered in lineages I and II, and the majority of the strains were classified as lineage II. A probable epidemic entrance in different years for every clade and cluster from each different region was defined. The persistence of the same specific clonal complexes of L. monocytogenes has been found over long periods; this may be related to the fact that some strains are able to survive better than others in a food production environment. Phylogenic studies, using whole-genome sequence data, are able to identify the emergence of highly persistent pathogenic variants, contributing to improving the hazard characterization of L. monocytogenes.
A Transcriptomic Study Reveals That Fish Vibriosis Due to the Zoonotic Pathogen Vibrio vulnificus Is an Acute Inflammatory Disease in Which Erythrocytes May Play an Important Role

Vibrio vulnificus is a marine zoonotic pathogen associated with fish farms that is considered a biomarker of climate change. Zoonotic strains trigger a rapid death of their susceptible hosts (fish or humans) by septicemia that has been linked to a cytokine storm in mice. Therefore, we hypothesize that V. vulnificus also causes fish death by triggering a cytokine storm in which red blood cells (RBCs), as nucleated cells in fish, could play an active role. To do it, we used the eel immersion infection model and then analyzed the transcriptome in RBCs, white BCs, and whole blood using an eel-specific microarray platform. Our results demonstrate that V. vulnificus triggers an acute but atypical inflammatory response that occurs in two main phases. The early phase (3 h post-infection [hpi]) is characterized by the upregulation of several genes for proinflammatory cytokines related to the mucosal immune response (il17a/f1 and il20) along with genes for antiviral cytokines (il12β) and antiviral factors (ifna and ifnc). In contrast, the late phase (12 hpi) is based on the upregulation of genes for typical inflammatory cytokines (il1β), endothelial destruction (mmp9 and hyal2), and, interestingly, genes related to an RNA-based immune response (sidt1). Functional assays revealed significant proteolytic and hemolytic activity in serum at 12 hpi that would explain the hemorrhages characteristic of this septicemia in fish. As expected, we found evidence that RBCs are transcriptionally active and contribute to this atypical immune response, especially in the short term. Based on a selected set of marker genes, we propose here an in vivo RT-qPCR assay that allows detection of early sepsis caused by V. vulnificus. Finally, we develop a model of sepsis that could serve as a basis for understanding sepsis caused by V. vulnificus not only in fish but also in humans.
Major Vault Protein (MVP) Associated With BRAF V600E Mutation Is an Immune Microenvironment-Related Biomarker Promoting the Progression of Papillary Thyroid Cancer via MAPK/ERK and PI3K/AKT Pathways

Papillary thyroid cancer (PTC) is the most common malignancy of the endocrine system, with an increase in incidence frequency. Major vault protein (MVP) is the main structural protein of the vault complex that has already been investigated in specific cancers. Yet the underlying biological functions and molecular mechanisms of MVP in PTC still remain considerably uncharacterized. Comprehensive analyses are predicated on several public datasets and local RNA-Seq cohort. Clinically, we found that MVP was upregulated in human PTC than in non-cancerous thyroid tissue and was correlated with vital clinicopathological parameters in PTC patients. MVP expression was associated with BRAF V600E, RAS, TERT, and RET status, and it was correlated with worse progression-free survival in PTC patients. Functionally, enrichment analysis provided new clues for the close relationship between MVP with cancer-related signaling pathways and the immune microenvironment in PTC. In PTC with high MVP expression, we found CD8+ T cells, regulatory T cells, and follicular helper T cells have a higher infiltration level. Intriguingly, MVP expression was positively correlated with multiple distinct phases of the anti-cancer immunity cycle. MVP knockdown significantly suppressed cell viability and colony formation, and promoted apoptosis. In addition, downregulated MVP markedly inhibited the migration and invasion potential of PTC cells. The rescue experiments showed that MVP could reverse the level of cell survival and migration. Mechanistically, MVP exerts its oncogenic function in PTC cells through activating PI3K/AKT/mTOR and MAPK/ERK pathways. These results point out that MVP is a reliable biomarker related to the immune microenvironment and provide a basis for elucidating the oncogenic roles of MVP in PTC progression.
Equivalent homogeneous model of D31-mode longitudinal piezoelectric transducers

This article focuses on modelling of D31-mode longitudinal piezoelectric transducers. A simple equivalent one-dimensional homogeneous model of D31-mode longitudinal piezoelectric transducers is proposed in this article. Homogeneous properties of the model are derived by a simple analytical mixing method based on the operation principle of D31-mode longitudinal piezoelectric transducers. Compared with other models in the literature, the proposed homogeneous model can consider passive layers in D31-mode longitudinal piezoelectric transducers for more accurate predictions in either static or dynamic behaviour. The proposed model is validated by a three-dimensional finite element model. Besides, based on the homogeneous model and borrowing the network theory, an exact equivalent circuit is formulated. A more straightforward form of the equivalent circuit can further facilitate analysis and modelling of D31-mode longitudinal piezoelectric transducers. Also, the proposed homogeneous model is wrapped into a transfer matrix form. The formulated transfer matrix of D31-mode longitudinal piezoelectric transducers can be used with the transfer matrix method to facilitate the calculations, when D31-mode longitudinal piezoelectric transducers are connected with numerous mediums in the operation direction. The effectiveness of the equivalent circuit and the transfer matrix is also verified.
Short-circuit capability of SiC power MOSFETs

The short-circuit capability of Si power devices, defined in terms of a critical energy density, is the product of the heat capacity in the heat generation region and the rise in temperature. However, for SiC power devices, the heat generation region is significantly smaller than that for Si power devices, because the drift-region thickness is about 10 times less in SiC power devices. Therefore, formulae used for Si devices are not directly applicable to SiC devices. In this study, analytical formulae are derived for the short-circuit capability of a SiC power device, and its ambient-temperature dependence, based on the thermal diffusion equation. The calculated results are found to be in good agreement with those of direct measurements.
Frame-To-Frame Rotation Estimation under Uncertain Feature Positions for Visual Odometry Frame-To-Frame Rotation Estimation under Uncertain Feature Positions for Visual Odometry Bild-zu-Bild Rotationsschätzung unter Unsicheren Featurepositionen für Visuelle Odometrie

Relative pose estimation of two camera views is a fundamental problem in computer vision. While many algorithms to solve this problem have been proposed, almost all struggle with purely rotational motion given no additional information. Kneip et al . proposed the normal epipolar constraint (NEC) that allows for rotation estimation independent of the translation. However, their approach is highly dependent on accurate feature positions in both frames. This work presents the novel probabilistic normal epipolar constraint (PNEC) for relative pose estimation. The PNEC overcomes the NEC limitation by accounting for anisotropic and inhomogeneous uncertainties in the feature positions in the target frame. To this end, a novel objective function, along with an efﬁcient optimization scheme, is derived that effectively estimates the rotation while maintaining real-time performance. Experiments on synthetic data demonstrate that the novel PNEC improves upon the original NEC and yields more accurate rotation estimates. Furthermore, this thesis shows the integration of the PNEC into a state-of-the-art monocular rotation-only odometry system. This new PNEC visual odometry consistently achieves improved results for the real-world KITTI dataset. performance for real-world data in an odometry setting. We discuss the performance of the PNEC in Ch. 5 and present potential future work based on the experimental results. This thesis concludes with a summarization of the work presented (see Ch. 6).
Lock on Form Development of Active Transportation Safety Performance Functions in California Development of Active Transportation Safety Performance Functions in California Final Technical Report

Encouraging individuals to indulge in active transportation, involving walking and bicycling, brings with it a societal obligation to protect commuters as they engage in these modes of travel. Investigating the factors impacting non-motorist safety on roadways is essential in this regard. The most popular method is to develop the safety performance function (SPF). The project is dedicated to the active transportation-oriented SPF development in California, which can not only illustrate the significant influential factors, but also paves the way for other activities such as accurate identification of hot spots of active transportation, countermeasure treatment selection, benefit-cost analysis, etc. The active transportation-related SPFs were developed for the micro-level, county-level, and traffic analysis zone-level crash counts, respectively.
APLIKASI MODEL COX PROPORTIONAL HAZARD (Application of Cox Proportional Hazard Model on The Case of Typoid Fever)

A common problem found in survival data is the presence of censored data. The length of hospitalization of Typhoid fever patients until declared cured is one of example of this data. Here, we use Cox regression model to analysis this data. Partial likelihood is one of the methods of estimating parameters for Cox regression model. In many cases of censored data, two objects (patients) have the same length of hospitalization (ties). Therefore, to estimate the parameters of the model must use the right method. Here we used partial likelihood Breslow, Efron, and Exact methods. The study was motivated by how the three methods performed for Cox regression model. The data used for the implementation of these methods is length of hospitalization of Typhoid fever patients at Mekar Sari Hospital-Bekasi in 2020. Based on AIC criteria, we found that exact method is the best model (minimum AIC) for parameter estimation of Cox regression model. Referring to the Cox regression model by using a significance level of 10%, there are five predictor variables that affects the length of patient hospitalization. The five variables are age, vomiting, dirty tongue, hemoglobin, and leukocyte.
IBM @ TREC Clinical Trials Track 2021

Although clinical trials are crucial to the advancement of medical science, many clinical trials fail because they do not meet recruitment targets. This problem engenders a need for automated systems that can match patients to ongoing trials. The potential benefits of such systems are twofold: first, they would allow for the systematic study of new treatments through completed clinical trials and second, they could improve or even save the lives of patients for whom existing treatments are ineffective. We participate in the TREC Clinical Trials (CT) Track, for which the aim is to match synthetic 5-10 sentence patient descriptions with clinical trials from ClinicalTrials.gov, a clinical trials repository that includes all clinical trials in the United States. Our system uses BM25 and semantic textual similarity (STS) models to retrieve two thousand candidates from hundreds of thousands of clinical trials. We then proceed to rerank those trials using neural reranking models with BERT-based encoders and novel attention mechanisms. In addition to training our models on an existing related corpus [Koopman and Zuccon, 2016], we leverage data from MIMIC-III to generate a larger training corpus. In the end, we found that our BM25-based ranker utilizing a Lucene index outperformed our neural models, likely due to a lack of high-quality training data.
Hyperverlet: A Symplectic Hypersolver for Hamiltonian Systems

Hamiltonian systems represent an important class of dynamical systems such as pendulums, molecular dynamics, and cosmic systems. The choice of solvers is significant to the accuracy when simulating Hamiltonian systems, where symplectic solvers show great significance. Recent advances in neural network-based hypersolvers, though achieve competitive results, still lack the symplecity necessary for reliable simulations, especially over long time horizons. To alleviate this, we introduce Hyperverlet, a new hypersolver composing the traditional, symplectic velocity Verlet and symplectic neural network-based solvers. More specifically, we propose a parameterization of symplectic neural networks and prove that hyperbolic tangent is r-finite expanding the set of allowable activation functions for symplectic neural networks, improving the accuracy. Extensive experiments on a spring-mass and a pendulum system justify the design choices and suggest that Hyperverlet outperforms both traditional solvers and hypersolvers.
Phytochemical screening and free radical scavenging Activity of “ Amrutha Mahabala Kashayam ”- an ethnobotanical formulation

In this article, we have investigated preliminary phytochemical screening and antioxidant ability for the aqueous extract of “ Amrutha Mahabala Kashayam ” (AMK) an ethnobotanical formulation prescribed around Kuppam forest habitats in Andhra Pradesh, India. Quantitative estimation of phytoconstituents and DPPH, ABTS assay were performed for examining Antiradical scavenging potency. Results depicted aqueous extract of AMK possess High contents of phytochemical compounds (TPC, TFC, TF and TPA) and exert strong anti-radical scavenging capacity by scavenging 64.22 % of DPPH radicals and 58.24 of ABTS % radicals at 100 mg/mL and exhibited IC 50 values of DPPH and ABTS of the aqueous extract of AMK are 62.12±1.33 µg/ml and 72.62±2.03 µg/ml respectively. Our results reveals that, the AMK proves to be a potent Neutraceutical and provided a scientific base for a therapeutic ethno-pharmacological insight, authenticating their usages in folk medicine.
The Comparison of C4.5 and CART (Classification and Regression Tree) Algorithm in Classification of Occupation for Fresh Graduate

The problem that college students face is the difficulty of determining the appropriate field of work after they graduate from college. In this study, a classification of the field of work was carried out using the data mining method based on the alumni field of work data. The data on the field of work of alumni contained information such as gender, study program, practical work topics, types of practical work companies, final project topics, and year of graduation. The classification on the field of work carried out was divided into three types of experiments, namely experiments in eight target categories (STQA Engineer, Software and Mobile Application Developer, Web Developer, UI/UX Designer, Software and Business Analyst, Lecturer and Researcher, AI Engineer, DevOps and Cybersecurity Practitioner), three target categories (SQA, Programmer, Data Manager, and Analyst) and two target categories (Programmer and Non-Programmer). The data mining algorithms used to classify were C4.5 and CART (Classification and Regression Tree). The accuracy obtained using the C4.5 algorithm was 42% in the eight categories experiment, 58% in the three categories experiment, and 75% in the two categories experiment. In comparison, the accuracy obtained using the CART algorithm was 43% in the eight categories experiment, 61% in the three categories experiment, and 77% in the two categories experiment. Based on the experimental results, it can be concluded that the best algorithm to classify the fields of work based on alumni data from the two algorithms used is the CART algorithm, even though the difference is not too significant.
Isolation and Structural Elucidation of Compounds from Pleiocarpa bicarpellata and Their In Vitro Antiprotozoal Activity

Species of the genus Pleiocarpa are used in traditional medicine against fever and malaria. The present study focuses on the isolation and identification of bioactive compounds from P. bicarpellata extracts, and the evaluation of their antiprotozoal activity. Fractionation and isolation combined to LC-HRMS/MS-based dereplication provided 16 compounds: seven indole alkaloids, four indoline alkaloids, two secoiridoid glycosides, two iridoid glycosides, and one phenolic glucoside. One of the quaternary indole alkaloids (7) and one indoline alkaloid (15) have never been reported before. Their structures were elucidated by analysis of spectroscopic data, including 1D and 2D NMR experiments, UV, IR, and HRESIMS data. The absolute configurations were determined by comparison of the experimental and calculated ECD data. The extracts and isolated compounds were evaluated for their antiprotozoal activity towards Trypanosoma brucei rhodesiense, Trypanosoma cruzi, Leishmania donovani, and Plasmodium falciparum, as well as for their cytotoxicity against rat skeletal myoblast L6 cells. The dichloromethane/methanol (1:1) root extract showed strong activity against P. falciparum (IC50 value of 3.5 µg/mL). Among the compounds isolated, tubotaiwine (13) displayed the most significant antiplasmodial activity with an IC50 value of 8.5 µM and a selectivity index of 23.4. Therefore, P. bicarpallata extract can be considered as a source of indole alkaloids with antiplasmodial activity.
Effect of Genetics and Climate on Apple Sugars and Organic Acids Profiles

Apple is widely cultivated in temperate regions. The beneficial properties of apple for preventing several illnesses are widely known. Nevertheless, qualitative variables such as sweetness or sourness may influence consumer satisfaction; they are critical factors for fruit consumption and essential in plant breeding. In the present work, 155 apple accessions were assessed during five consecutive years (2014–2018). Four individual sugars and seven organic acids were analysed by HPLC. A mixed-effects model was fitted with accessions and the years’ climatic features as independent variables. A cluster analysis was applied on the mixed-effects model coefficients. Four groups were considered as optimum. Genetics seemed to have the strongest effect and showed clear differences between accession groups, while climate effects were strong only for certain compounds and had a more horizontal behaviour equally affecting the different accession groups. In fact, non-Spanish cultivars tended to concentrate, while autochthone accessions had a much wider spread. Individual sugars and acids concentrations correlated negatively with precipitation and positively with temperature range and solar radiation in all accession groups. The geographic region where the orchard is grown is thus very important in the resulting metabolites profiles. Moreover, apple genetics would also play a decisive role as highlighted in the cluster analysis.
Self-Determination in Marriage: Actor and Partner Effects of Spousal Autonomy on Relationship Maintenance Behaviors

Guided by self-determination theory, this study examined the dyadic effects of marital autonomy on relationship maintenance behaviors. Heterosexual married couples (N = 324 dyads) completed questionnaires assessing their need fulfillment of autonomy in marriage along with their enactment of relationship maintenance behaviors. Using multilevel modeling, actor-partner interdependence models were estimated to determine dyadic effects for husbands’ and wives’ autonomy on their own and their partners’ use of positivity, openness, assurances, social networks, and shared tasks. Parameter estimates revealed that husbands’ and wives’ autonomy produced equivalent positive actor and partner effects for the positivity, assurances, social networks, and shared tasks maintenance behaviors, and a positive actor effect for the openness maintenance behavior. These dyadic findings support the idea of mutuality of autonomy support in marriage.
Simulation and analysis of spatial audio reproduction and listening area effects

Loudspeaker-based spatial audio systems are often designed with the aim to create an auditory event or scene to a listener positioned in the optimal listening position. However, in real-world domestic listening environments, listeners can be distributed across the listening area. Any translational change from the central listening position will introduce artefacts which can be challenging to evaluate perceptually. Simulation of a loudspeaker system using non-individualised dynamic binaural synthesis is one solution to this problem. However, the validity in using such systems is not well proven. This thesis measures the limitations of using a non-individualised, dynamic binaural synthesis system to simulate the perception of loudspeaker-based panning methods across the listening area. The binaural simulation system was designed and verified in collaboration with BBC Research and Development. The equivalence of localisation errors caused by loudspeaker-based panning methods between in situ and binaural simulation was measured where it was found that localisation errors were equivalent to a +/-7 degrees boundary in 75% of the spatial audio reproduction systems tested. Results were then compared to a computation localisation model which was adapted to utilise head-rotations. The equivalence of human acuity to sound colouration between in situ and when using non-individualised binaural simulation was measured using colouration detection thresholds from five directions. It was shown that thresholds were equivalent within a +/-4dB equivalence boundary, supporting the use for simulating sound colourations caused by loudspeaker-based panning methods. The binaural system was finally applied to measure the perception of multi-loudspeaker induced colouration artefacts across the listening area. It was found that the central listening position had the lowest perceived colouration. It is also shown that the variation in perceived colouration across the listening area is larger for reverberant reproduction conditions.