bluuebunny/crossref_metadata_2025_split huggingface dataset:
Systematic identification of post-transcriptional regulatory modules
Authors: Khoroshkin Matvei , Buyan Andrey , Dodel Martin , Navickas Albertas , Yu Johnny , Trejo Fathima , Doty Anthony , Baratam Rithvik , Zhou Shaopu , Lee Sean B. , Joshi Tanvi , Garcia Kristle , Choi Benedict , Miglani Sohit , Subramanyam Vishvak , Modi Hailey , Carpenter Christopher , Markett Daniel , Corces M. Ryan , Mardakheh Faraz K. , Kulakovskiy Ivan V. , Goodarzi Hani 
Published: September 2024

AbstractIn our cells, a limited number of RNA binding proteins (RBPs) are responsible for all aspects of RNA metabolism across the entire transcriptome. To accomplish this, RBPs form regulatory units that act on specific target regulons. However, the landscape of RBP combinatorial interactions remains poorly explored. Here, we perform a systematic annotation of RBP combinatorial interactions via multimodal data integration. We build a large-scale map of RBP protein neighborhoods by generating in vivo proximity-dependent biotinylation datasets of 50 human RBPs. In parallel, we use CRISPR interference with single-cell readout to capture transcriptomic changes upon RBP knockdowns. By combining these physical and functional interaction readouts, along with the atlas of RBP mRNA targets from eCLIP assays, we generate an integrated map of functional RBP interactions. We then use this map to match RBPs to their context-specific functions and validate the predicted functions biochemically for four RBPs. This study provides a detailed map of RBP interactions and deconvolves them into distinct regulatory modules with annotated functions and target regulons. This multimodal and integrative framework provides a principled approach for studying post-transcriptional regulatory processes and enriches our understanding of their underlying mechanisms.
Preparation of silver nanowires with controlled parameters for conductive transparent electrodes
Authors: Salam Ahmed Abdel , Ebrahim Shaker , Soliman Moataz , Shokry Azza 
Published: September 2024

AbstractSilver nanowires (AgNWs) have excellent flexibility, unique optical transmittance and high conductivity. The polyol process is appropriate for preparing AgNWs due to its simplicity, effectiveness, low cost, and high yield. This work aims to investigate the effect of preparation parameters of the polyol process on the silver nanowires properties. The parameters include the controlling agent, molecular weight of the polyvinylpyrrolidone (PVP), the temperature, and the reducing agent. The amount of silver nanoparticles formed during preparation was used to determine the optimum preparation conditions. The transmission electron microscope (TEM) images showed minimal amount of Ag nanoparticles when using mixed molecular weight of PVP-40K, and PVP-1.3M at 150 °C with the assistance of copper chloride as a controlling agent. The prepared AgNWs had an average length of 3.7 µm and aspect ratio of 15.3. The fabricated electrodes were characterized using a scanning electron microscope (SEM) and four probe resistivity measurements. The electrical measurement of the AgNWs electrodes indicated that the surfactant thickness is a critical parameter in having low sheet resistance electrodes. Also, the optical transmission was affected by the amount of nanoparticles. The prepared electrode with high concentration of AgNWs and a minimal amount of nanoparticles exhibited 80% optical transmission.
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Authors: Manoharan Premkumar , Ravichandran Sowmya , Kavitha S. , Tengku Hashim Tengku Juhana , Alsoud Anas R. , Sin Tan Ching 
Published: September 2024

AbstractIn this paper, a new method is designed to effectively determine the parameters of proton exchange membrane fuel cells (PEMFCs), i.e., $${\xi }_{1}$$

ξ
1

, $${\xi }_{2}$$

ξ
2

, $${\xi }_{3}$$

ξ
3

, $${\xi }_{4}$$

ξ
4

, $${R}_{\text{C}}$$

R
C

, $$\lambda$$
λ
, and $$b$$
b
. The fuel cells (FCs) involve multiple variable quantities with complex non-linear behaviours, demanding accurate modelling to ensure optimal operation. An accurate model of these FCs is essential to evaluate their performance accurately. Furthermore, the design of the FCs significantly impacts simulation studies, which are crucial for various technological applications. This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. In order to validate the proposed algorithm, a number of experiments using various datasets were conducted and compared the outcomes with different state-of-the-art algorithms. The outcomes indicate that the proposed GOOSE algorithm not only produced promising results but also exhibited superior performance in comparison to other similar algorithms. This approach demonstrates the ability of the GOOSE algorithm to simulate complex systems and enhances the robustness and adaptability of the simulation tool by integrating essential behaviours into the computational framework. The proposed strategy facilitates the development of more accurate and effective advancements in the utilization of FCs.
Cannabidiol and fluorinated derivative anti-cancer properties against glioblastoma multiforme cell lines, and synergy with imidazotetrazine agents
Authors: Brookes Alice , Kindon Nicholas , Scurr David J. , Alexander Morgan R. , Gershkovich Pavel , Bradshaw Tracey D. 
Published: September 2024

Abstract
Background
Glioblastoma multiforme (GBM) is an aggressive cancer with poor prognosis, partly due to resistance to the standard chemotherapy treatment, temozolomide (TMZ). Phytocannabinoid cannabidiol (CBD) has exhibited anti-cancer effects against GBM, however, CBD’s ability to overcome common resistance mechanisms to TMZ have not yet been investigated. 4’-Fluoro-cannabidiol (4’-F-CBD, or HUF-101/PECS-101) is a derivative of CBD, that exhibits increased activity compared to CBD during in vivo behavioural studies.

Methods
This anti-cancer activity of cannabinoids against GBM cells sensitive to and representing major resistance mechanisms to TMZ was investigated. Cannabinoids were also studied in combination with imidazotetrazine agents, and advanced mass spectrometry with the 3D OrbiSIMS was used to investigate the mechanism of action of CBD.

Results
CBD and 4’-F-CBD were found to overcome two major resistance mechanisms (methylguanine DNA-methyltransferase (MGMT) overexpression and DNA mismatch repair (MMR)-deficiency). Synergistic responses were observed when cells were exposed to cannabinoids and imidazotetrazine agents. Synergy increased with T25 and 4’-F-CBD. 3D OrbiSIMS analysis highlighted the presence of methylated-DNA, a previously unknown anti-cancer mechanism of action of CBD.

Conclusions
This work demonstrates the anti-cancer activity of 4’-F-CBD and the synergy of cannabinoids with imidazotetrazine agents for the first time and expands understanding of CBD mechanism of action.
A Preliminary Examination of a Novel Telepractice Screening Protocol for Poststroke Aphasia
Authors: Teti Selina D. , Murray Laura L. , Orange J. B. , Roberts Angela C. , Sedzro Mawukoenya Theresa 
Published: September 2024

Background:
The delivery of telepractice interventions for people with poststroke aphasia has been found effective and feasible compared to traditional, in-person interventions; however, telepractice assessments, particularly screening protocols, which may foster convenient access to aphasia diagnostic services, have received limited examination within the aphasia literature. Therefore, the purpose of this study was to examine a novel telepractice screening protocol for people with poststroke aphasia that assesses both language and extralinguistic cognitive abilities via both performance-based and patient-reported measures.

Method:
Twenty-one participants with previously diagnosed poststroke aphasia completed the telepractice administration of the Frenchay Aphasia Screening Test (FAST), the Aphasia Impact Questionnaire-21 (AIQ-21), the Oxford Cognitive Screen (OCS), and the Cognitive-Communication Checklist for Acquired Brain Injury (CCCABI). Care partners of the participants completed the Communicative Effectiveness Index (CETI). After the telepractice session, each participant completed a feasibility questionnaire to rate their overall experience.

Results:

All participants screened as having aphasia. Pearson correlation analyses yielded a strong positive relationship between OCS and FAST scores (
r
= .74), a strong relationship between OCS and CCCABI scores (
r
= −.71), and a moderate relationship between FAST and AIQ-21 scores (
r
= −.35). Moderate relationships were noted between the performance-based measures and the CETI (
r
= .30). The overall feasibility of telepractice administration was rated positively by each participant. No significant relationships were found between the feasibility responses and participant characteristics.

Conclusions:
Overall, the telepractice screening protocol yielded an effective and feasible way to identify poststroke aphasia. Similar to in-person administration of screening measures, it was more difficult to identify milder levels of aphasia severity. Future research should examine whether this telescreening protocol can identify poststroke aphasia within the broader stroke population.
Protein hydrogels for biomedical applications
Authors: Wang Xinyi , Hou Yue , Lu Xiong , Xie Chaoming , Jiang Yanan 
Published: September 2024

AbstractHydrogels, characterised as highly hydrophilic three‐dimensional polymer networks, have gained increasing attention due to their unique physicochemical properties, finding applications in various fields. Natural polymer hydrogels exhibit higher biocompatibility and biodegradability compared to traditional synthetic polymer hydrogels. Proteins, being the principal materials of natural polymer hydrogels, bear numerous modifiable functional groups. The resultant hydrogel possesses responsiveness, adjustable degradability, and underway as an excellent biomaterial. Seven common raw materials used to construct protein hydrogels are introduced. In terms of comparing natural polymer hydrogels with traditional synthetic polymer hydrogels, the authors conduct a detailed analysis and comparison, highlighting the advantages of natural polymer hydrogels in terms of biocompatibility and biodegradability, and summarising their characteristics. The authors also address the limitations of various protein hydrogels and list existing strengthening cross‐linking strategies, proposing new insights to overcome the application limits of protein hydrogels. Additionally, the applications of protein hydrogels in drug delivery, biosensing, bio‐inks and tissue engineering are discussed. The authors conclude by summarising the current challenges faced by protein hydrogels and prospecting its future development.
Diagnostik und Therapie der kardialen Sarkoidose
Authors: Chatzantonis Grigorios , Meier Claudia , Yilmaz Ali 
Published: September 2024

ZusammenfassungDie Sarkoidose ist eine entzündliche Erkrankung unklarer Genese, die durch eine Granulombildung gekennzeichnet ist. Sie kann prinzipiell jedes Organ befallen. Da eine kardiale Sarkoidose eine wesentliche Bedeutung für die Morbidität und Letalität hat, ist deren frühzeitige Diagnose von entscheidender therapeutischer und prognostischer Bedeutung. Dieser Beitrag erläutert die wichtigsten Punkte und Pitfalls in der Diagnostik und Therapie der kardialen Sarkoidose.
The Study of Calcium Chloride Effect on Silver Nanoparticles Capping with Roselle Extract Granule against Aggregatibacter actinomycetemcomitans
Authors: Chaiwong Thanaphoom , Yiemwattana Ichaya , Nathamtong Sasitharee , Prayoonwong Tipruthai , Yuakyong Suttimas , Wacharanad Sirorat 
Published: September 2024

Abstract
Objectives The primary aim of this research is to investigate the influence of calcium chloride on the synthesis of silver nanoparticles coated with roselle extract and enclosed within alginate and calcium chloride (SNP-Ro-CaCl2) beads, designated as SNP-Ro-CaCl2 beads. Additionally, the study aims to assess their antimicrobial activity.
Materials and Methods For the preparation of SNP-Ro-CaCl2 beads, SNPs and alginate gel were mixed, followed by dropping in three different concentrations of CaCl2 solution (1%, 3%, and 5% w/v). The morphological structure of the SNP-Ro-CaCl2 beads was analyzed using a stereoscope and scanning electron microscope (SEM). Over a period of 14 days, the release of SNPs was monitored using ultraviolet-visible (UV-Vis) spectroscopy. Additionally, the activity against Aggregatibacter actinomycetemcomitans was evaluated using the disk diffusion technique.
Statistical Analysis The data for this experiment were analyzed using one-way analysis of variance (ANOVA) and Scheffe's method.
Results The results revealed that varying concentrations of calcium chloride had distinct crosslinking effects on alginate, resulting in different voids and porosity within the SNP-Ro-CaCl2 beads. In the SNP-Ro-1% CaCl2 beads, the inner element exhibited higher porosity, facilitating faster activation and greater efficiency in releasing SNPs. Regarding activity against A. actinomycetemcomitans after 14 days, SNP-Ro-1% CaCl2 beads showed a larger inhibition zone diameter compared to other concentrations, while no statistically significant difference in the inhibition zone diameter was observed between SNP-Ro-3% CaCl2 and SNP-Ro-5% CaCl2 beads. Additionally, it was observed that the antimicrobial effectiveness diminished after 17 days through testing of the lifetimes of the three concentrations.
Conclusions This study developed a method for depositing SNP-Ro into alginate gel and crosslinking it with CaCl2 to produce small beads for the sustained release of SNP-Ro in periodontal lesions. Consequently, the SNP-Ro-CaCl2 beads have the potential to be developed as adjunctive locally delivered antimicrobial agents in periodontal therapy.
Equality of access to minority language assessments and interventions in immersion education
Authors: Nic Aindriú Sinéad 
Published: September 2024

Abstract
In the Republic of Ireland (RoI), Irish is recognised as the first official language of the state. The public has
the right to conduct all business with the state solely through the medium of Irish if they wish. The reality, however, is that
many government bodies only provide services in English. This article discusses the language used for assessments and
interventions for students with special educational needs (SEN) in Irish-medium (IM) primary and post-primary schools in the RoI.
A mixed methods study was conducted, with teachers from schools (n = 56) completing an online questionnaire at
first and then teachers (n = 32) undertaking semi-structured interviews. The findings suggest that students in IM
schools are not being afforded access to services in Irish and many challenges exist for these schools when meeting the SEN of
students. Recommendations are made around how to strengthen educational policy and practice to enable IM teachers meet the needs
of all students.
Parametric approximations of fast close encounters of the planar three-body problem as arcs of a focus-focus dynamics
Authors: Guzzo Massimiliano 
Published: September 2024

Abstract
A gravitational close encounter of a small body with a planet may produce a substantial change of its orbital parameters which can be studied using the circular restricted three-body problem. In this paper we provide parametric representations of the fast close encounters with the secondary body of the planar CRTBP as arcs of non-linear focus-focus dynamics. The result is the consequence of a remarkable factorisation of the Birkhoff normal forms of the Hamiltonian of the problem represented with the Levi–Civita regularisation. The parameterisations are computed using two different sequences of Birkhoff normalisations of given order N. For each value of N, the Birkhoff normalisations and the parameters of the focus-focus dynamics are represented by polynomials whose coefficients can be computed iteratively with a computer algebra system; no quadratures, such as those needed to compute action-angle variables of resonant normal forms, are needed. We also provide some numerical demonstrations of the method for values of the mass parameter representative of the Sun–Earth and the Sun–Jupiter cases.
Joint Optimization of Probabilistic Shaping and Geometric Shaping for Faster-than-Nyquist Signaling
Authors: Kang Weimin 
Published: September 2024

Abstract
We propose a joint optimization algorithm of probabilistic shaping and geometric shaping for faster-than-Nyquist (FTN) signaling. The theoretical analysis and bit error performance both represent that the FTN probabilistic-geometric shaping method is superior to the conventional Nyquist regular QAM system. When spectral efficiency (SE) is 3.077 bits/s/Hz, the proposed 16QAM FTN probabilistic-geometric shaping scheme can obtain 1.65 dB theoretical gain compared to the conventional Nyquist regular 16QAM system, while the simulation gain is 2.90 dB with spectral efficiency at 3.077 bits/s/Hz. The proposed 16QAM FTN probabilistic-geometric shaping scheme can obtain 1.63 dB theoretical gain compared to the conventional FTN regular 16QAM system, while the simulation gain is 3.28 dB with spectral efficiency at 3.282 bits/s/Hz. Therefore, the proposed method is reliable, which can be regarded as a potential scheme for the 6G communications.
Design and Implementation of TDMA Scheduling Based on BRKGA
Authors: Xiaoying Shuai , Yuxia Yin 
Published: September 2024

Abstract
Messages in wireless Ad hoc networks may require intermediate multi-hop forwarding from the source to the target node. To find an optimum contend-free time slots scheduling solution in Ad hoc, a TDMA (Time Division Multiple Access) scheduling scheme based on BRKGA (Biased Random-key GA) is proposed. The algorithm divides the population of generation k into elite group and rest group. The elite solutions are copied directly to the next generation. One parent from the elite group and another parent from the rest population are randomly selected to crossover a new solution. The worst Pm solutions of the population of generation k are replaced by the mutants. The simulation results demonstrate that the TDMA based on BRKGA exhibits better performance in terms of lower frame length and higher channel utilization.
Plaid Fabric Image Retrieval Based on Wavelet Transform and SIFT Features
Authors: Zhao Pengyu , Liu Yuan , Zhang Xiaoting 
Published: September 2024

Abstract
This study presents a method for plaid fabric image retrieval that combines wavelet and SIFT features to address the challenges of accuracy and efficiency in fabric retrieval due to diverse fabric types. The process starts with cropping plaid fabric images and applying histogram equalization to improve brightness and contrast. Texture is enhanced using the Sobel operator, and the Haar wavelet transform extracts image high-frequency components in various directions. Wavelet features are then derived through histogram statistics. The SIFT algorithm is utilized to describe local features by capturing key points and directional information. A codebook aggregates these features from the fabric database, and VLAD encoding generates a vector for the image features, which is further reduced to 256 dimensions via PCA. A similarity-weighted fusion method combines the wavelet and SIFT features, achieving an mAP of 0.67 and an average retrieval time of 1.1 seconds per image. This method significantly enhances plaid fabric retrieval, aiding in fabric design and production.
Study on ECG Signal Classification and Athlete Health Analysis Based on Attention Mechanism
Authors: Zhu Dong , Zhu Haiyan 
Published: September 2024

Abstract
In the training and competition process of athletes, their bodies are subjected to various levels of load and stress. As an important diagnostic tool, ECG signals can provide deep insights into the cardiac function of athletes, including heart rate, rhythm, and changes in cardiac electrical activity. By conducting a thorough examination of ECG readings, we are able to quickly identify possible heart conditions or irregularities, which is essential for preserving the heart health of athletes. However, ECG signals are highly complex and multidimensional. To accurately classify these signals, it is necessary to select the most representative and discriminative features. However, this is not an easy task, and the selection of effective features remains a pressing issue. To address this problem, this paper proposes the CSNet classification network model. This framework eradicates disruptions in electrocardiogram signals, performs attribute extraction via a direct network configuration, and combines channel focus mechanisms and spatial focus mechanisms to enhance attribute representation and categorization capabilities. Furthermore, to retain the temporal information of ECG signals, we introduce the Gated Recurrent Unit (GRU), which helps to better capture temporal patterns and dependencies in the signals, thus enabling more accurate classification of ECG signals.
Bi-DAUnet: Leveraging BiFormer in a Unet-like Architecture for Building Damage Assessment
Authors: Dong Chao , Zhao Xi 
Published: September 2024

Abstract
In recent years, Convolutional Neural Networks (CNNs) have become an important research direction in the field of building damage assessment. Particularly, deep neural networks based on the U-shaped architecture and skip connections have achieved significant breakthroughs in the task of architectural damage assessment. Despite the impressive performance of CNNs, effectively capturing global and long-range semantic information remains a challenge due to the local nature of their convolutional operations. To address this issue, we propose a novel architectural damage assessment model called Bi-DAUnet, which adopts a BiFormer structure similar to U-Net. In this model, we employ a U-shaped encoder-decoder architecture based on BiFormer and combine it with skip connections to achieve global semantic feature learning. Specifically, we utilize a hierarchical BiFormer with a dual-layer routing attention mechanism as the encoder to extract contextual features of architectural images. In the symmetric decoder, a BiFormer Block is introduced to fuse shallow and deep features of the feature maps and learn the correlation between pixels at distant locations. Experimental results indicate that the U-shaped encoder-decoder network based on BiFormer achieves superior performance in the task of architectural damage assessment compared to fully convolutional methods.
Simulation Study of the Damage Effect of Typical Fragment on UAV Target
Authors: Cui Kaibo , Sun Haitao , Deng Huiyong 
Published: September 2024

Abstract
UAV poses a serious threat to ground troops and combat personnel in modern operations, and fighting against UAV is called an important task of air defense operations. Taking DJI UAV as the object, this article researches the typical blasting debris of the prefabricated damage effect of drone target through modeling simulation and simulation calculation, which is focused on damage simulation analysis of the drone battery, power plant, camera and other key components, and studies the damage condition of fragments in different direction and at different speeds, which can improve theoretical basis and reference for fighting against the drone and its swarm.