Miracle-dz/UniFAR-FTUs huggingface dataset:
A Semantic-Enhancement-Based Social Network User-Alignment Algorithm

User alignment can associate multiple social network accounts of the same user. It has important research implications. However, the same user has various behaviors and friends across different social networks. This will affect the accuracy of user alignment. In this paper, we aim to improve the accuracy of user alignment by reducing the semantic gap between the same user in different social networks. Therefore, we propose a semantically enhanced social network user alignment algorithm (SENUA). The algorithm performs user alignment based on user attributes, user-generated contents (UGCs), and user check-ins. The interference of local semantic noise can be reduced by mining the user’s semantic features for these three factors. In addition, we improve the algorithm’s adaptability to noise by multi-view graph-data augmentation. Too much similarity of non-aligned users can have a large negative impact on the user-alignment effect. Therefore, we optimize the embedding vectors based on multi-headed graph attention networks and multi-view contrastive learning. This can enhance the similar semantic features of the aligned users. Experimental results show that SENUA has an average improvement of 6.27% over the baseline method at hit-precision30. This shows that semantic enhancement can effectively improve user alignment.
Nonlinear pressure fields due to focused circular apertures

The use of high amplitude focused ultrasound fields is widespread in medical diagnosis and therapy but there has been relatively little work published that compares experimental measurements with appropriate theory for such systems. In this paper, comparisons are made between the measured continuous‐wave pressure field of a focused circular aperture operating at 2.25 MHz and a numerical solution of the nonlinear parabolic wave equation. The measurements were made in water using a 38‐mm diam plane circular transducer as the acoustic source with perspex lenses providing focusing, focal lengths of 440, 216, and 142 mm were examined. Results are presented for the amplitudes of the fundamental, second, and third harmonics along and across the acoustic axis of the source. In general, the agreement between experiment and theory is good.
Flavour Profile of Traditional Dry Sausage Prepared with Partial Substitution of NaCl with KCl

The effects of partial substitution of NaCl with 0%, 20%, 30% and 40% KCl on the physical characteristics, bacterial community and flavour profile of traditional dry sausage were investigated in this study. With the increase in KCl substitution ratio, the moisture content, astringency, bitterness and umami increased significantly, and the saltiness gradually decreased (p < 0.05). The high-throughput sequencing results showed that the dry sausages with KCl substitution had relatively high abundances of Staphylococcus. For volatile compounds, increasing the KCl substitution ratio reduced the formation of aldehydes, ketones and some alcohols, but promoted the formation of acids and esters (p < 0.05). Sensory evaluation and partial least square regression analysis showed that the dry sausages with 20% and 30% KCl were similar in overall physical and microbial properties, flavour profiles and sensory attributes, and the sausages with 40% KCl were characterized by taste defects. Overall, partial substitution of NaCl with 30% KCl could ensure the acceptable flavour and sensory attributes of dry sausages.
Oleuropein Attenuates Oxidative Stress in Human Trophoblast Cells

Olive-derived bioactive compound oleuropein was evaluated against damage induced by hydrogen peroxide in human trophoblast cells in vitro, by examining the changes in several markers implicated in oxidative stress interactions in the placenta. Trophoblast HTR-8/SVneo cells were preincubated with OLE at 10 and 100 µM and exposed to H2O2, as a model of oxidative stress. Protein and lipid peroxidation, as well as antioxidant enzymes’ activity, were determined spectrophotometrically, and DNA damage was evaluated by comet assay. iNOS protein expression was assessed by Western blot, while the mRNA expression of pro- and anti-apoptotic genes BAX and BCL2 and transcription factor NFE2L2, as well as cytokines IL-6 and TNF α were determined by qPCR. Oleuropein demonstrated cytoprotective effects against H2O2 in trophoblast cells by significantly improving the antioxidant status and preventing protein and lipid damage, as well as reducing the iNOS levels. OLE reduced the mRNA expression of IL-6 and TNF α, however, it did not influence the expression of NFE2L2 or the BAX/BCL2 ratio after H2O2 exposure. Oleuropein per se did not lead to any adverse effects in HTR-8/SVneo cells under the described conditions, confirming its safety in vitro. In conclusion, it significantly attenuated oxidative damage and restored antioxidant functioning, confirming its protective role in trophoblast.
A recipe for stability of finite-difference wave-equation computations

Finite‐difference solutions to the wave equation are pervasive in the modeling of seismic wave propagation (Kelly and Marfurt, 1990) and in seismic imaging (Bording and Lines, 1997). That is, they are useful for the forward problem (modeling) and the inverse problem (migration). In computational solutions to the wave equation, it is necessary to be aware of conditions for numerical stability. In this short note, we examine a convenient recipe for insuring stability in our finite‐difference solutions to the wave equation. The stability analysis for finite‐difference solutions of partial differential equations is handled using a method originally developed by Von Neumann and described by Press et al. (1986, p. 827–830).
CRISPR/Cas12a-Assisted Dual Visualized Detection of SARS-CoV-2 on Frozen Shrimps

Given the possibility that food contaminated with SARS-CoV-2 might become an infection source, there is an urgent need for us to develop a rapid and accurate nucleic acid detection method for SARS-CoV-2 in food to ensure food safety. Here, we propose a sensitive, specific, and reliable molecular detection method for SARS-CoV-2. It has a mechanism to control amplicon contamination. Swabs from spiked frozen shrimps were used as detection samples, which were processed by heating at 95 °C for 30 s. These preprocessed samples served as the templates for subsequent amplification. A colorimetric LAMP reaction was carried out to amplify both the SARS-CoV-2 target and the MS2 phage simultaneously in one tube. MS2 phage was detected by colorimetric LAMP as the internal control, while SARS-CoV-2 was detected with a CRISPR/Cas12a system. The fluorescence results could be visually detected with an ultraviolet lamp. Meanwhile, uracil was incorporated during the LAMP reaction to provide an amplicon contamination proof mechanism. This test could detect as low as 20 copies of SARS-CoV-2 in one reaction. Additionally, the detection could be finished in 45 min. The test only needs a heating block and an ultraviolet lamp, which shows the potential for field detection.
Microfluidic Gut-on-a-Chip: Fundamentals and Challenges

The human gut is responsible for food digestion and absorption. Recently, growing evidence has shown its vital role in the proper functioning of other organs. Advances in microfluidic technologies have made a significant impact on the biomedical field. Specifically, organ-on-a-chip technology (OoC), which has become a popular substitute for animal models, is capable of imitating complex systems in vitro and has been used to study pathology and pharmacology. Over the past decade, reviews published focused more on the applications and prospects of gut-on-a-chip (GOC) technology, but the challenges and solutions to these limitations were often overlooked. In this review, we cover the physiology of the human gut and review the engineering approaches of GOC. Fundamentals of GOC models including materials and fabrication, cell types, stimuli and gut microbiota are thoroughly reviewed. We discuss the present GOC model applications, challenges, possible solutions and prospects for the GOC models and technology.
Investigating the direct and indirect effects of a school-based leadership program for primary school students: Rationale and study protocol for the ‘Learning to Lead’ cluster randomised controlled trial

Background Leadership is a valuable skill that can be taught in school, and which may have benefits within and beyond the classroom. Learning to Lead (L2L) is a student-led, primary school-based leadership program whereby older ‘peer leaders’ deliver a fundamental movement skills (FMS) program to younger ‘peers’ within their own school. Aim The aims of the study are to determine the efficacy of a peer-led FMS intervention on: (i) peer leaders’ (aged 10 to 12 years) leadership effectiveness (primary outcome), leadership self-efficacy, well-being, and time on-task in the classroom; (ii) peers’ (aged 8 to 10 years) physical activity levels, actual and perceived FMS competency, cardiorespiratory fitness, muscular power, and executive functioning; and (iii) teachers’ (referred to as ‘school champions’) work-related stress and well-being. Method L2L will be evaluated using a two-arm parallel group cluster randomised controlled trial. Twenty schools located within a two-hour drive of the University of Newcastle, Australia will be recruited. We will recruit 80 students (40 peer leaders and 40 peers) from each school (N = 1,600). L2L will be implemented in three phases: Phase 1 –school champions’ training via a professional learning workshop; Phase 2 –school champions’ delivery of leadership lessons to the peer leaders; and Phase 3 –peer leaders’ delivery of the FMS program to their younger peers. The FMS program, consisting of 12 x 30-minute lessons, will be delivered over the course of one school term (10 weeks). Study outcomes will be assessed at baseline (between mid-March to June, Terms 1 and 2), intervention end (mid-August to September, Term 3), and follow-up (November to mid-December, Term 4. This trial was prospectively registered on the Australian New Zealand Clinical Trials Registry (ANZCTR); registration number: ACTRN12621000376842.
Carbohydrate, Lipid, and Apolipoprotein Biomarkers in Blood and Risk of Thyroid Cancer: Findings from the AMORIS Cohort

Simple Summary We performed a cohort study based on the Swedish Apolipoprotein-Related Mortality Risk (AMORIS) Cohort, including 561,388 individuals and with a follow-up of >30 years, to assess the associations of nine blood biomarkers of carbohydrate, lipid, and apolipoprotein metabolism with the subsequent risk of thyroid cancer. In brief, we found that increased blood levels of total cholesterol and HDL-C were associated with a lower risk of thyroid cancer and, as a group, patients with thyroid cancer had constantly lower levels of total cholesterol and HDL-C during the decades before diagnosis, compared to controls. We also found that, during the 10 years before diagnosis, patients with thyroid cancer demonstrated declining levels of lipid and apolipoprotein biomarkers, whereas controls demonstrated stable or increasing levels likely because of aging. Abstract Background: Previous studies have examined the link between blood metabolic biomarkers and risk of thyroid cancer, with inconclusive results. We performed a cohort study based on the Swedish Apolipoprotein-Related Mortality Risk (AMORIS) Cohort, including 561,388 individuals undergoing health examinations during 1985–1996 with a follow-up of >30 years. Methods: Newly diagnosed cases of thyroid cancer were identified from the Swedish Cancer Register. We assessed the associations of nine blood biomarkers of carbohydrate, lipid, and apolipoprotein metabolism measured at the time of health examinations with the subsequent risk of thyroid cancer and demonstrated the temporal trend of these biomarkers during the 30 years before diagnosis of thyroid cancer. Results: After multivariable adjustment, there was a lower risk of thyroid cancer, per standard deviation increase in total cholesterol (TC; HR 0.91; 95%CI 0.82–0.99) and HDL-C (HR 0.86; 95%CI 0.75–0.99). During the 20 to 30 years before diagnosis, patients with thyroid cancer, as a group, demonstrated constantly lower levels of TC and HDL-C, compared to controls. Further, patients with thyroid cancer demonstrated declining levels of these biomarkers during the ten years before diagnosis, whereas controls demonstrated stable or increasing levels. Conclusions: Taken together, we found blood levels of TC and HDL-C to be associated with the risk of thyroid cancer and that there was a declining level of metabolic biomarkers during the 10 years before diagnosis of thyroid cancer.
Towards Decoding Hepatotoxicity of Approved Drugs through Navigation of Multiverse and Consensus Chemical Spaces

Drug-induced liver injury (DILI) is the principal reason for failure in developing drug candidates. It is the most common reason to withdraw from the market after a drug has been approved for clinical use. In this context, data from animal models, liver function tests, and chemical properties could complement each other to understand DILI events better and prevent them. Since the chemical space concept improves decision-making drug design related to the prediction of structure–property relationships, side effects, and polypharmacology drug activity (uniquely mentioning the most recent advances), it is an attractive approach to combining different phenomena influencing DILI events (e.g., individual “chemical spaces”) and exploring all events simultaneously in an integrated analysis of the DILI-relevant chemical space. However, currently, no systematic methods allow the fusion of a collection of different chemical spaces to collect different types of data on a unique chemical space representation, namely “consensus chemical space. ” This study is the first report that implements data fusion to consider different criteria simultaneously to facilitate the analysis of DILI-related events. In particular, the study highlights the importance of analyzing together in vitro and chemical data (e.g., topology, bond order, atom types, presence of rings, ring sizes, and aromaticity of compounds encoded on RDKit fingerprints). These properties could be aimed at improving the understanding of DILI events.
AI-Driven Robust Kidney and Renal Mass Segmentation and Classification on 3D CT Images

Early intervention in kidney cancer helps to improve survival rates. Abdominal computed tomography (CT) is often used to diagnose renal masses. In clinical practice, the manual segmentation and quantification of organs and tumors are expensive and time-consuming. Artificial intelligence (AI) has shown a significant advantage in assisting cancer diagnosis. To reduce the workload of manual segmentation and avoid unnecessary biopsies or surgeries, in this paper, we propose a novel end-to-end AI-driven automatic kidney and renal mass diagnosis framework to identify the abnormal areas of the kidney and diagnose the histological subtypes of renal cell carcinoma (RCC). The proposed framework first segments the kidney and renal mass regions by a 3D deep learning architecture (Res-UNet), followed by a dual-path classification network utilizing local and global features for the subtype prediction of the most common RCCs: clear cell, chromophobe, oncocytoma, papillary, and other RCC subtypes. To improve the robustness of the proposed framework on the dataset collected from various institutions, a weakly supervised learning schema is proposed to leverage the domain gap between various vendors via very few CT slice annotations. Our proposed diagnosis system can accurately segment the kidney and renal mass regions and predict tumor subtypes, outperforming existing methods on the KiTs19 dataset. Furthermore, cross-dataset validation results demonstrate the robustness of datasets collected from different institutions trained via the weakly supervised learning schema.
Application of Teeth in Toxicological Analysis of Decomposed Cadavers Using a Carbamazepine-Administered Rat Model

In a regular autopsy, blood and organs are used to quantify drug and toxicant concentrations; however, specimens such as blood cannot be collected from highly decomposed corpses, making the quantification of drug and toxicants impossible. This study aimed to estimate the blood carbamazepine (CBZ) concentration from teeth, a part of the human body that is best preserved after death. We sampled teeth and blood of rats administered CBZ. The correlation between the tooth and serum CBZ concentrations was analyzed. Rats were euthanized after CBZ administration and kept at 22 °C for 0 to 15 days before sampling the teeth and measuring the CBZ concentration. Undecalcified, fresh, frozen sections of rat teeth were prepared, and CBZ localization was evaluated. CBZ concentrations in both teeth and cardiac blood peaked at 60 min after administration and increased in a dose-dependent manner. CBZ concentration in teeth did not substantially change after death, with high CBZ distribution being observed in the pulp cavity. The tooth and serum CBZ concentrations were highly correlated, suggesting that the measurement of toxicant concentration in sampled teeth would allow for the estimation of blood toxicant concentration in highly decomposed corpses.
Genetic Divergence and Connectivity among Gene Pools of Polyprion americanus

Simple Summary The wreckfish Polyprion americanus is a long-living grouper distributed anti-tropically. Three regional gene pools have been described so far in this species, i.e., the Atlantic North, the Atlantic Southwest, and the Indo-Pacific Ocean. This study addresses the interspecific divergence within the genus Polyprion spp. as well as the intrapopulation structure of P. americanus from the Atlantic North, by analyzing mitochondrial DNA and nuclear DNA gene markers on a comprehensive sampling effort. A highly divergent gene pool from South Africa was conspicuously intermediate between P. americanus and P. oxygeneios, which suggests its putative hybrid origin between those species. The inclusion of the South Africa pool produced a very high nuclear DNA divergence among Polyprion spp. populations which contrasts with the large genetic homogeneity of the Atlantic North stock. Inferred significant migration rates suggest a longitudinal connectivity pattern which strengthens the bi-directional migratory hypothesis in the Atlantic North gene pool. Abstract Three regional gene pools of Polyprion americanus have been described so far, i.e., the North Atlantic, the Southwest Atlantic, and the Indo-Pacific Ocean. However, there is taxonomic uncertainty about the Southeast Atlantic population and there is suspicion on the existence of a third species of Polyprion in that area. Additionally, prior studies have shown a lack of genetic structuring in the Atlantic North. Nonetheless, a more conspicuous characterization of intensity, periodicity, and direction of migration are needed to properly understand the wreckfish connectivity pattern in the North Atlantic population. This study addresses the interspecific concerns highlighted above as well as the intrapopulation structure of P. americanus from the Atlantic North, using the mitochondrial DNA Cytochrome Oxidase I gene and nuclear DNA microsatellite markers on a comprehensive sampling effort. The highly divergent gene pool from South Africa was characterized by the specific Mitochondrial DNA PamCOI.Saf haplotype. Its molecular composition and phylogenetic status were conspicuously intermediate between P. americanus and P. oxygeneios, which suggests its putative hybrid origin between those species. Microsatellite variation exhibited a high differentiation (24%) among four putative Polyprion spp. gene pools which contrasts with the large genetic homogeneity within the Atlantic North stock (FSC = 0.002). The significant migration rates inferred upon Bayesian algorithms suggest a longitudinal bi-directional connectivity pattern which strengthens the migratory hypothesis previously suggested on demographic data in the Atlantic North gene pool.
GRPAFusion: A Gradient Residual and Pyramid Attention-Based Multiscale Network for Multimodal Image Fusion

Multimodal image fusion aims to retain valid information from different modalities, remove redundant information to highlight critical targets, and maintain rich texture details in the fused image. However, current image fusion networks only use simple convolutional layers to extract features, ignoring global dependencies and channel contexts. This paper proposes GRPAFusion, a multimodal image fusion framework based on gradient residual and pyramid attention. The framework uses multiscale gradient residual blocks to extract multiscale structural features and multigranularity detail features from the source image. The depth features from different modalities were adaptively corrected for inter-channel responses using a pyramid split attention module to generate high-quality fused images. Experimental results on public datasets indicated that GRPAFusion outperforms the current fusion methods in subjective and objective evaluations.
IONIZATION OF NEUTRAL ATOMS WITH OUTER 2p AND 3p ELECTRONS BY ELECTRON AND PROTON IMPACT.

The Born approximation is used to calculate cross sections for the ionization by electron and proton impact of all neutral atomic systems in the sequences boron to neon and aluminium to argon. Possible exchange between the incident and atomic electrons is approximately taken into account using the Ochkur approximation to the exchange amplitude. In the cases where experimental data exist for comparison there is agreement at high energies to within about a factor of 2, a discrepancy which may be partly explained by the simple approximation made to the true wave function of the ejected electron.
Measurement and contouring of micro-scale objects through integrated transillumination in a flexible fiber probe system

High-resolution measurement and contouring of objects with micro-scale sizes have been two of the research challenges in many areas, such as nondestructive testing and imaging, imaging of artifacts in MEMS, and lab-on-chip devices, as well as in biomedical imaging. In this context, we use a transillumination incorporated fiber probe imaging system to enable imaging of the targeted object in a single shot. It also enables positioning of the probe system to the region of interest for further fine analysis, thereby reducing the long scanning time faced by conventional approaches. The capability of the developed probe is illustrated using standard USAF resolution chart and fluorescent microspheres as test targets. The probe system has axial and lateral resolutions of about 16 μm and 144 lp/mm, respectively. This proposed probe scheme can potentially be employed as a viable diagnostic imaging methodology.
Confidence interval for random‐effects calibration curves with left‐censored data

The presence of left censoring in environmental and engineering applications complicates tests of hypotheses and interval estimation. First, we construct a confidence interval (CI) for a true concentration using nonlinear mixed‐effects regression models for analysis of interlaboratory calibration data with left censoring. Next, we impute the unobserved left‐censored data with randomly simulated value. Finally, we compute the coverage probability via simulation and show that our methodology achieves the nominal level. We illustrate our methodology with a real‐life example. Copyright © 2008 John Wiley & Sons, Ltd.
IoT in Water Quality Monitoring—Are We Really Here?

The Internet of Things (IoT) has become widespread. Mainly used in industry, it already penetrates into every sphere of private life. It is often associated with complex sensors and very complicated technology. IoT in life sciences has gained a lot of importance because it allows one to minimize the costs associated with field research, expeditions, and the transport of the many sensors necessary for physical and chemical measurements. In the literature, we can find many sensational ideas regarding the use of remote collection of environmental research. However, can we fully say that IoT is well established in the natural sciences?