Miracle-dz/UniFAR-FTUs huggingface dataset:
Sequence Dependent Elasticity of DNA

The DNA contained in every living cell not only stores the genetic information; it functions in a complex molecular network that can condense, transcribe, replicate and repair genes. The essential role played by the sequence dependent structure and deformability of DNA in these basic processes of life, has received increasing attention over the past years. The present work aims at better understanding sequence dependent elasticity of double stranded DNA elasticity, across biologically relevant length scales. A theoretical description is developed that makes is possible to relate structural, biochemical and biophysical experiments and simulation. It is based on the rigid base–pair chain (rbc) model which captures all basic deformation modes on the scale of individual base–pair (bp) steps. Existing microscopic parametrizations of the rbc model rely on indirect methods. A way to relate them to biochemical experiments is provided by the indirect readout mechanism, where DNA elasticity determines protein–DNA complexation affinities. By correlating theoretical affinity predictions with in vitro measurements in a well–studied test case, different parameter sets were evaluated. As a result a new, hybrid parameter set is proposed which greatly reduces prediction errors. Indirect readout occurs mostly at particular binding subsites in a complex. A statistical marker is developed which localizes indirect readout subsites, by detecting elastically optimized sub-sequences. By a systematic coarse–graining of the rbc to the well–characterized worm–like chain (wlc) model, a quantitative connection between microscopic and kbp scale elasticity is established. The general helical rbc geometry is mapped to an effective, linear ‘on-axis’ version, yielding the full set of wlc elastic parameters for any given sequence repeat. In the random sequence case, structural variability adds conformational fluctuations which are correlated by sequence continuity. The sequence disorder correction to entropic elasticity in the rbc model is shown to coincide with the conformational correction. The results show remarkable overall agreement of the coarse–grained with the mesoscale wlc parameters, lending support to the model and to the microscopic parameter sets. A continuum version of the rbc is formulated as Brownian motion on the rigid motion group. Analytic expressions for angular correlation functions and moments of the end–to–end distance distribution are given. In an equivalent Lagrangian approach, conserved quantities along, and the linear response around, a general equilibrium shape are explored.
Can You Answer This? - Exploring Zero-Shot QA Generalization Capabilities in Large Language Models (Student Abstract)

The buzz around Transformer-based language models (TLM) such as BERT, RoBERTa, etc. is well-founded owing to their impressive results on an array of tasks. However, when applied to areas needing specialized knowledge (closed-domain), such as medical, finance, etc. their performance takes drastic hits, sometimes more than their older recurrent/convolutional counterparts. In this paper, we explore zero-shot capabilities of large LMs for extractive QA. Our objective is to examine performance change in the face of domain drift i.e. when the target domain data is vastly different in semantic and statistical properties from the source domain and attempt to explain the subsequent behavior. To this end, we present two studies in this paper while planning further experiments later down the road. Our findings indicate flaws in the current generation of TLM limiting their performance on closed-domain tasks.
Quercetin 3-O-Glucuronide from Aglianico Vine Leaves: A Selective Sustainable Recovery and Accumulation Monitoring

In recent years, as part of sustainable development policies, the revaluation of end-of-life products has become more and more widespread. In terms of sustainability, in a scenario of circular economy food sustainability aims, inter alia, at making an effective re-use of natural resources as a starting point for the obtainment of high added-value products. With the aim of promoting the valorization of the wine sector wastes, the present study took into account the leaves of Vitis vinifera L. cv. Aglianico from the Campania Region (Italy). The use of deep eutectic solvents as a greener alternative to the most common organic solvents, joint to ultrasound-assisted maceration, and LC-MS tools, allowed us to define for the first time a six-month quantitative variation of flavonol derivatives, and in particular of quercetin 3-O-glucuronide, based on the collection time and the leaf height on the grapevine. Results underlined that the influence of abiotic factors, such as exposure to sunlight, which is pivotal in the biosynthesis of such compounds, should be strictly considered for their full recovery.
Novel Dual Incretin Receptor Agonists in the Spectrum of Metabolic Diseases with a Focus on Tirzepatide: Real Game-Changers or Great Expectations? A Narrative Review

The prevalence of metabolic diseases including type 2 diabetes (T2D), obesity and non-alcoholic fatty liver disease (NAFLD) increases globally. This highlights an unmet need for identifying optimal therapies for the management of these conditions. Tirzepatide is a novel dual incretin receptor agonist (twincretin) that activates both glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) receptors. The aim of this narrative review was to examine the impact of novel twincretins, focusing on tirzepatide, on the management of a wide spectrum of metabolic diseases. Data from preclinical and clinical trials have shown that twincretins significantly reduce blood glucose levels in T2D, and tirzepatide is the first agent of this class that has been approved for the management of T2D. Additionally, the beneficial impact of tirzepatide on weight reduction has been corroborated in several studies, showing that this agent can achieve substantial and sustained weight loss in obese patients with or without T2D. Data also suggest that tirzepatide could be a promising drug for hepatic steatosis reduction in individuals with NAFLD. The remarkable effects of tirzepatide on glycaemic control, weight loss and liver-related outcomes have posed new research questions that are likely to lead to further advancements in the treatment of T2D, obesity and related metabolic disorders.
Presence of Pleural Effusion in the Assessment of Remote Dielectric Sensing

Background: The remote dielectric sensing (ReDS) system is a recently introduced non-invasive technology used to easily estimate the degree of lung fluid volume without any expert techniques. In the previous literature, ReDS values had a moderate correlation with invasively measured pulmonary artery wedge pressure (PAWP), the gold standard for representing left heart preload. Considering the mechanism of ReDS technology, ReDS values may be inappropriately elevated in the presence of pleural effusion (PE), and the ability of the ReDS system to estimate PAWP may decrease in such a situation. Methods: In-hospital patients with cardiovascular diseases underwent computed tomography, and the presence of pleural effusion (PE) was evaluated. The measurement of ReDS values using the ReDS system and the measurement of PAWP using invasive right heart catheterization were also performed simultaneously. The impact of the presence of PE on the relationship between the ReDS values and PAWP was evaluated. Results: A total of 59 patients (79 years, 30 male) were included. The median ReDS value was 25% (IQR: 22%, 30%) and the median PAWP level was 13 (IQR: 10, 18) mmHg. Of these patients, 11 had PE. PAWP was not significantly different between the two groups, whereas the ReDS values in the PE group were significantly higher than in the no-PE group. The impact of the presence of PE on the ReDS values was significant, with a beta value of 6.61 (95% confidence interval: 4.80–8.42, p < 0.001) upon adjusting for the levels of PAWP. Conclusions: We should pay attention to interpreting ReDS values when assessing the degree of pulmonary congestion in patients with PE, because ReDS values may be inappropriately elevated in this cohort.
Effect of Si Contents on the Properties of Ti15Mo7ZrxSi Alloys

The main purpose of this research is to evaluate the mechanical characteristics and biocompatibility of two novel titanium alloys, Ti15Mo7ZrxSi (x = 0, 0.5, 0.75, 1). These samples had already undergone grinding, polishing, cutting, and chipping. Electrochemical, metallographic, three-point bending, and microhardness studies were conducted on the studied materials to determine their corrosion behavior, microstructure, Young’s modulus, and hardness. The first investigations revealed that both samples had biphasic and dendritic structures, elastic moduli that were between the highest and minimum values achieved by around 20 GPa, and favorable behavior when in contact with physiological fluids at ambient temperature. Ti15Mo7Zr0.5Si and Ti15Mo7Zr0.75Si, the research samples, had greater corrosion potentials, reduced corrosion rates, and therefore higher corrosion resistance, as well as modulus of elasticity values that were comparable to and closer to those of human bone. The results of this investigation indicate that both alloys exhibit favorable corrosion behavior, great biocompatibility, Young’s modulus results lower than those of conventional alloys used in biomedical implants, and hardness values higher than commercially pure titanium.
The Relationship between the Source of Dietary Animal Fats and Proteins and the Gut Microbiota Condition and Obesity in Humans

The relationship between gut microbiota and obesity is well documented in humans and animal models. Dietary factors can change the intestinal microbiota composition and influence obesity development. However, knowledge of how diet, metabolism, and intestinal microbiota interact and modulate energy metabolism and obesity development is still limited. Epidemiological studies show a link between consuming dietary proteins and fats from specific sources and obesity. Animal studies confirm that proteins and fats of different origins differ in their ability to prevent or induce obesity. Protein sources, such as meat, dairy products, vegetables, pulses, and seafood, vary in their amino acid composition. In addition, the type and level of other factors, such as fatty acids or persistent organic pollutants, vary depending on the source of dietary protein. All these factors can modulate the intestinal microbiota composition and, thus, may influence obesity development. This review summarizes selected evidence of how proteins and fats of different origins affect energy efficiency, obesity development, and intestinal microbiota, linking protein and fat-dependent changes in the intestinal microbiota with obesity.
B-DSPA: A Blockchain-Based Dynamically Scalable Privacy-Preserving Authentication Scheme in Vehicular Ad Hoc Networks

The big data of Internet of Vehicles contributes to the development of intelligent transportation. Privacy protection in vehicular ad hoc networks (VANETs) is the core factor to improve user and vehicle participation. This article proposes a novel blockchain-based dynamic extensible privacy protection and message authentication scheme for VANETs. It minimizes the computation cost of message authentication based on an elliptic curve and message batch verification. Based on the Chinese remainder theorem, this scheme protects transmitted message security by adaptively and dynamically responding to vehicles and roadside units accessing the VANET. It offers a smart contract-based forensics and tracing solution from the accident vehicle. In addition, strict security proof and analysis that the scheme meets the security requirements for the VANET. It evaluates the efficiency of the scheme, and the results show its practicality.
A cost-effective solution to estimate fuel consumption and greenhouse gas emissions for motorcycles: a case study

ABSTRACT The lack of country-specific data related to the real-world fuel consumption (FC) of motor vehicles is a significant impediment to the inventory of greenhouse gas (GHG) emissions in the transport sector in Vietnam. This study aims to develop a cost-effective solution for estimating the on-road FC of motorcycles (MC) to overcome this lack. An Artificial Neural Network (ANN)-based model (R2 >0.85 and MAPE < 20%) was developed to predict the MC’s instant FC rate (FRinst) based on the experimental data that were continuously collected using the data logger installed directly on the test MC. The developed ANN-based model was utilized to estimate FRinst according to the real-world driving characteristics that were collected using the Global positioning system (GPS) device. The discrepancy between the estimated and measured FC (in terms of liters per kilometer) was only 6.8%. Consequently, the proposed approach could help improve the consumed fuel-based GHG emission inventory in the transport sector.
Testing of modified curvature-rotation correction for k-ω SST model

Using eddy viscosity models (EVM) for solving Reynolds Averaged Navier-Stokes (RANS) equations is the most popular and economical way of turbulent flow computations up to date. However this approach, while being very convenient, is not flawless. For example, for accurate prediction of rotating flows and flows with significant streamline curvature (turbine rotors, various vortices etc.) special corrections must be used along with EVM to account for effects of these factors on turbulence. Current work presents the results of testing of the recently suggested modification of the Menter-Smirnov rotation and curvature correction for SST model. A range of internal and external flows is considered: flow in a plane rotating channel, flow in a channel with 180° turn, airfoil tip vortex and 3D boundary layer with the streamwise vortices produced by vortex generators. It is shown that the modified correction results in better prediction than the original version for the three dimensional vortex flows and gives virtually the same results for the 2D boundary layer flows.
Microbial Communities in Gynecological Cancers and Their Association with Tumor Somatic Variation

Simple Summary Bacteria are responsible for a wide range of human diseases including cancer. In our study we identified changes in the microbial communities of the female upper genital tract correlated with genomic variation in genes seen in gynecological cancers, endometrial and ovarian. This supports our hypothesis that differences in bacterial communities in the upper genital tract epithelium may lead to selection of specific genomic variation at the cellular level of these tissues that may predispose to their malignant transformation. Pathway analyses including correlated genes with changing microbiome may help understand how changing bacterial landscapes could lead to these cancers. Abstract There are strong correlations between the microbiome and human disease, including cancer. However, very little is known about potential mechanisms associated with malignant transformation in microbiome-associated gynecological cancer, except for HPV-induced cervical cancer. Our hypothesis is that differences in bacterial communities in upper genital tract epithelium may lead to selection of specific genomic variation at the cellular level of these tissues that may predispose to their malignant transformation. We first assessed differences in the taxonomic composition of microbial communities and genomic variation between gynecologic cancers and normal samples. Then, we performed a correlation analysis to assess whether differences in microbial communities selected for specific single nucleotide variation (SNV) between normal and gynecological cancers. We validated these results in independent datasets. This is a retrospective nested case-control study that used clinical and genomic information to perform all analyses. Our present study confirms a changing landscape in microbial communities as we progress into the upper genital tract, with more diversity in lower levels of the tract. Some of the different genomic variations between cancer and controls strongly correlated with the changing microbial communities. Pathway analyses including these correlated genes may help understand the basis for how changing bacterial landscapes may lead to these cancers. However, one of the most important implications of our findings is the possibility of cancer prevention in women at risk by detecting altered bacterial communities in the upper genital tract epithelium.
A method to improve the computational performance of nonlinear all—optical diffractive deep neural network model

Abstract To further improve the computational performance of the diffractive deep neural network (D2NN) model, we use the ReLU function to limit the phase parameters, which effectively solves the problem of vanishing gradient that occurs in the mitigation model. We add various commonly used nonlinear activation functions to the hidden layer of the model and establish the ReLU phase-limit nonlinear diffractive deep neural network (ReLU phase-limit N-D2NN) model. We evaluate the model by comparing the performance of various nonlinear activation functions, where confusion matrix and accuracy are used as evaluation methods. The numerical simulation results show that the model achieves better classification performance on the MNIST and Fashion-MNIST datasets, respectively. In particular, the highest classification performance is obtained by the ReLU phase-limit N-D2NN model, in which the hidden layer uses PReLU, with 98.38% and 90.14%, respectively. This paper provides a theoretical basis for applying the nonlinear D2NN systems in natural scenes.
Balloon Variant of Single Spoke Resonator

Z. Yao, R.E. Laxdal, V. Zvyagintsev, TRIUMF, Vancouver, B.C., Canada Abstract Spoke resonators have been widely proposed and optimized for various applications. Good performance has been demonstrated by many cold tests. Accompanying the great progress, the adverse impact of strong multipacting (MP) is also noted by recent test reports, consistent with modern 3D simulations. This paper will discuss MP behaviors in the single spoke resonator. In particular a phenomenological theory is developed to highlight the details of the geometry that affect MP. The analysis leads to an optimized geometry of a single spoke resonator defined here as the ‘balloon geometry’.
State feedback H2 optimal controllers under regulation constraints for descriptor systems

This paper is concerned with a non-standard multi-objective state feedback control problem for continuous descriptor systems. In this problem an output is to be regulated asymptotically with presence of an infinite-energy exo-system, while a desired H2 performance from a finite external disturbance to a tracking error has also to be satisfied. Thanks to the descriptor framework, not only unstable but also nonproper behaviors can be treated. A parametrization of all optimal dynamic and static controllers solving the proposed multi-objective control problem is given. Moreover, an application to the non-standard LQR problem is investigated. A numerical example shows the efficiency of the proposed results.
Employing GeoGebra in the teaching of mathematics: The teachers perspective

The purpose of this study was to investigate teachers’ perceptions about employing GeoGebra in the teaching and learning of mathematics. The study comprises four respondents who are currently enrolled in a mathematics education course at Universiti Kebangsaan Malaysia. The findings indicate a similar opinion among the respondents according to their experience, with regard to GeoGebra. All respondents agree that the software employs straightforward and comprehensible instructions in addition to offering accurate and simple information. They also agree that the software is user friendly. The respondents on the whole have positive opinions regarding the idea of employing GeoGebra in the teaching of mathematics.
Predicting rotation for ITER via studies of intrinsic torque and momentum transport in DIII-D

Experiments at the DIII-D tokamak have used dimensionless parameter scans to investigate the dependencies of intrinsic torque and momentum transport in order to inform a prediction of the rotation profile in ITER. Measurements of intrinsic torque profiles and momentum confinement time in dimensionless parameter scans of normalized gyroradius and collisionality are used to predict the amount of intrinsic rotation in the pedestal of ITER. Additional scans of Te/Ti and safety factor are used to determine the accuracy of momentum flux predictions of the quasi-linear gyrokinetic code TGLF. In these scans, applications of modulated torque are used to measure the incremental momentum diffusivity, and results are consistent with the E×B shear suppression of turbulent transport. These incremental transport measurements are also compared with the TGLF results. In order to form a prediction of the rotation profile for ITER, the pedestal prediction is used as a boundary condition to a simulation that uses TGLF to det.
PERKEMBANGAN PEMBELAJARAN BERDIFERENSIASI DALAM KURIKULUM MERDEKA PADA PENDIDIKAN ANAK USIA DINI

Sistem drilling yang diterapkan disekolah melalui metode hafalan terlalu menuntut anak agar dapat membaca, menulis dan berhitung dengan cepat sehingga anak merasa terkekang tanpa merasakan kebebasan dalam belajar. Pembelajaran berdiferensiasi sangat menghargai keragaman kemampuan anak dan memberi kebebasan anak dalam proses belajar. Hal tersebut dapat diimplementasikan dengan kurikulum merdeka di jenjang PAUD yang memiliki sistem merdeka bermain. Penelitian ini menggunakan metode studi pustaka dengan mengumpulkan literatur yang terkait dengan topik penelitian. Sumber data dalam penelitian ini berasal dari jurnal, conference, review, laporan, buku, dan lain sebagainya yang bersifat informatif. Hasil penelitian menunjukan bahwa: 1) pembelajaran berdiferensiasi pada pendidikan anak usia dini memiliki tiga elemen penting yaitu konten, proses dan produk yang dikembangkan oleh Pendidik. Tiga elemen ini membantu proses pembelajaran dengan cara pendidik menyiapkan perangkat pembelajaran, dengan menyesuaikan minat anak dan sesuai profil belajar peserta didik; 2) Konsep pembelajaran berdiferensiasi sesuai dengan karakteristik pembelajaran dalam kurikulum merdeka dan bervalue modern. Dimana karakteristiknya bertumpu pada pengembangan karakter individu dan berpusat padaanak. 3) Prinsip pembelajaran berdiferensiasi mengupayakan fungsi pendidik berjalan secara optimal dalam memfasilitasi peserta didik baik sebelum, sedang dan sesudah pembelajaran. 4) diketahui pembelajaran berdiferensiasi dapat diimplementasikan pada pendidikan anak usia dini, dimana konsep, karakteristik, dan prinsip pembelajarannya bersesuaian dengan gagasan kurikulum merdeka. Selain itu, tantangan pembelajaran berdiferensiasi ialah menitikberatkan pada peran pendidik, sehingga mengharuskan tenaga pendidik memiliki kompetensi yang memadai.
Estimating the Number of Block Boundaries from Diagonal Blockwise Matrices Without Penalization

In computational biology, numerous recent studies have been dedicated to the analysis of the chromatin structure within the cell by two‐dimensional segmentation methods. Motivated by this application, we consider the problem of retrieving the diagonal blocks in a matrix of observations. The theoretical properties of the least squares estimators of both the boundaries and the number of blocks are investigated. More precisely, the contribution of the paper is to establish the consistency of these estimators. A surprising consequence of our results is that, contrary to the one‐dimensional case, a penalty is not needed for retrieving the true number of diagonal blocks. Finally, the results are illustrated on synthetic data.