bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fear learning induces synaptic potentiation between engram neurons in the rat lateral amygdala
Authors: Abatis Marios , Perin Rodrigo , Niu Ruifang , van den Burg Erwin , Hegoburu Chloe , Kim Ryang , Okamura Michiko , Bito Haruhiko , Markram Henry , Stoop Ron 
Published: June 2024

AbstractThe lateral amygdala (LA) encodes fear memories by potentiating sensory inputs associated with threats and, in the process, recruits 10–30% of its neurons per fear memory engram. However, how the local network within the LA processes this information and whether it also plays a role in storing it are still largely unknown. Here, using ex vivo 12-patch-clamp and in vivo 32-electrode electrophysiological recordings in the LA of fear-conditioned rats, in combination with activity-dependent fluorescent and optogenetic tagging and recall, we identified a sparsely connected network between principal LA neurons that is organized in clusters. Fear conditioning specifically causes potentiation of synaptic connections between learning-recruited neurons. These findings of synaptic plasticity in an autoassociative excitatory network of the LA may suggest a basic principle through which a small number of pyramidal neurons could encode a large number of memories.
The human ATAD5 has evolved unique structural elements to function exclusively as a PCNA unloader
Authors: Wang Feng , He Qing , Yao Nina Y. , O’Donnell Michael E. , Li Huilin 
Published: June 2024

AbstractHumans have three different proliferating cell nuclear antigen (PCNA) clamp-loading complexes: RFC and CTF18-RFC load PCNA onto DNA, but ATAD5-RFC can only unload PCNA from DNA. The underlying structural basis of ATAD5-RFC unloading is unknown. We show here that ATAD5 has two unique locking loops that appear to tie the complex into a rigid structure, and together with a domain that plugs the DNA-binding chamber, prevent conformation changes required for DNA binding, likely explaining why ATAD5-RFC is exclusively a PCNA unloader. These features are conserved in the yeast PCNA unloader Elg1-RFC. We observe intermediates in which PCNA bound to ATAD5-RFC exists as a closed planar ring, a cracked spiral or a gapped spiral. Surprisingly, ATAD5-RFC can open a PCNA gap between PCNA protomers 2 and 3, different from the PCNA protomers 1 and 3 gap observed in all previously characterized clamp loaders.
Sentiment analysis of the Hamas-Israel war on YouTube comments using deep learning
Authors: Liyih Ashagrew , Anagaw Shegaw , Yibeyin Minichel , Tehone Yitayal 
Published: June 2024

Abstract
Sentiment analysis aims to classify text based on the opinion or mentality expressed in a situation, which can be positive, negative, or neutral. Therefore, in the world, a lot of opinions are available on various social media sites, which must be gathered and analyzed to assess the general public’s opinion. Finding and monitoring comments, as well as manually extracting the information contained in them, is a difficult task due to the vast diversity of ideas on YouTube. Identifying public opinion on war topics is crucial for offering insights to opposing sides based on popular opinion and emotions about the ongoing war. To address the gap, we build a model on YouTube comment sentiment analysis of the Hamas-Israel war to determine public opinion. In this study, we address the gaps by developing a deep learning-based approach for sentiment analysis. We have collected 24,360 comments from popular YouTube News Channels including BBC, WION, Aljazeera, and others about the Hamas-Israel War using YouTube API and Google spreadsheet and labeled them by linguistic experts into three classes: positive, negative, and neutral. Then, textual comments were preprocessed using natural language processing (NLP) techniques, and features were extracted using Word2vec, FastText, and GloVe. Moreover, we have used the SMOTE data balancing technique and used different data splits, but the 80/20 train-test split ratio has the highest accuracy. For classification model building, commonly used classification algorithms LSTM, Bi-LSTM, GRU, and Hybrid of CNN and Bi-LSTM were applied, and their performance is compared. As a result, the Hybrid of CNN and Bi-LSTM with Word2vec achieved the highest performance with 95.73% accuracy for comments classifications.
Investigation of antifungal and antibacterial potential of green extracts of propolis
Authors: Jenny Jeslin Cheruvathoor , Kuś Piotr Marek , Szweda Piotr 
Published: June 2024

AbstractPropolis extracts have been used in traditional medicines since ages due to its advantageous complex chemical composition. However, the antibacterial and antifungal activity of poplar propolis extracts prepared in Natural Deep Eutectic Solvent (NADES) are seldom studied. This study investigates suitable alternate for ethanol as a solvent for extraction for Polish poplar propolis. It also attempts to identify suitable extraction condition for the efficient transfer of compounds from propolis to the solvents. The extraction efficiency of NADES extracts was assessed in terms of total phenolic content, antioxidant activity and antimicrobial activity. The chemical composition of the extracts was analysed using UHPLC-DAD-QqTOF-MS. Four extracts, prepared in Propylene Glycol, Choline Chloride:Propylene Glycol (1:3), Choline Chloride:Propylene Glycol (1:4) and Choline Chloride:Glycerol (1:2), demonstrated activity and properties similar to ethanolic extract and extraction at 50 °C was found the most suitable for propolis. HPLC analysis confirmed that the chemical cocktail extracted by these solvents from propolis were identical with minor variations in their concentration as compared to its ethanolic extract. Thus, extracts of propolis at 50 °C in Propylene Glycol, Choline Chloride:Propylene Glycol (1:3) and Choline Chloride:Propylene Glycol (1:4) can be alternates for ethanolic extracts.
Ingestion of amoxicillin–clavulanic acid at therapeutic concentration during blood meal impacts Aedes aegypti microbiota and dengue virus transmission
Authors: Garcia--Van Smévoorde Margot , Calvez Elodie , Quétel Isaure , Dollin Christelle , Breurec Sébastien , Vega-Rúa Anubis 
Published: June 2024

AbstractDengue virus (DENV), mainly transmitted by Aedes aegypti mosquitoes, is the most prevalent arbovirus worldwide, representing a public health problem in tropical and subtropical countries. In these areas, antibiotic consumption rises which may impact both mosquito microbiota and dengue transmission. Here, we assessed how the ingestion by Ae. aegypti of therapeutic concentrations of amoxicillin–clavulanic Acid association (Amox/Clav), a broad-spectrum antibiotic used to treat febrile symptoms worldwide, impacted its microbiota. We also evaluated whether simultaneous ingestion of antibiotic and DENV impacted Ae. aegypti ability to transmit this virus. We found that Amox/Clav ingestion impacted microbiota composition in Ae. aegypti and we confirmed such impact in field-collected mosquitoes. Furthermore, we observed that Amox/Clav ingestion enhanced DENV dissemination and transmission by this mosquito at 21 days post-DENV exposure. These findings increase our understanding of factors linked to human hosts that may influence dengue transmission dynamics in regions with mass-drug administration programs.
Emergence of input selective recurrent dynamics via information transfer maximization
Authors: Kanemura Itsuki , Kitano Katsunori 
Published: June 2024

AbstractNetwork structures of the brain have wiring patterns specialized for specific functions. These patterns are partially determined genetically or evolutionarily based on the type of task or stimulus. These wiring patterns are important in information processing; however, their organizational principles are not fully understood. This study frames the maximization of information transmission alongside the reduction of maintenance costs as a multi-objective optimization challenge, utilizing information theory and evolutionary computing algorithms with an emphasis on the visual system. The goal is to understand the underlying principles of circuit formation by exploring the patterns of wiring and information processing. The study demonstrates that efficient information transmission necessitates sparse circuits with internal modular structures featuring distinct wiring patterns. Significant trade-offs underscore the necessity of balance in wiring pattern development. The dynamics of effective circuits exhibit moderate flexibility in response to stimuli, in line with observations from prior visual system studies. Maximizing information transfer may allow for the self-organization of information processing functions similar to actual biological circuits, without being limited by modality. This study offers insights into neuroscience and the potential to improve reservoir computing performance.
Health literacy and mental health: a national cross-sectional inquiry
Authors: Haeri-Mehrizi Aliasghar , Mohammadi Samira , Rafifar Shahram , Sadighi Jila , Kermani Ramin Mozaffari , Rostami Rahele , Hashemi Akram , Tavousi Mahmoud , Montazeri Ali 
Published: June 2024

AbstractHealth literacy and mental health are among the most important issues in the modern health and era of public health. This study aimed to investigate the association between health literacy and mental health status. This was a national cross-sectional study that was conducted in Iran. A sample of literate individuals aged 18–65 was entered into the study using multistage sampling. The data were collected by the Health Literacy Instrument for Adults (HELIA) and the 12-item General Health Questionnaire (GHQ-12). Logistic regression and path analysis were used for data analysis. A total of 20,571 individuals completed the questionnaires. The mean(± SD) age of participants was 34.9(± 11.8) years old, 51% were female, and 38.1% had higher education. The mean(± SD) health literacy score was 68.3(± 15.2), and 29.8% of the respondents reported some mental health problems. Logistic regression analysis showed that limited health literacy was associated with poor mental health status (OR 2.560, 95% CI 2.396–2.735, P = 0.001). The path analysis showed that an increase in health literacy could reduce psychological and social dysfunction (the effect of health literacy on reducing psychological distress is more profound). It is recommended to carry out interventions that strengthen adult’s cognitive and communication skills to improve their ability to access and use health information to make healthy choices.
Cyber‐physical system model based on multi‐agent system
Authors: Ahmed Maqbol , Kazar Okba , Harous Saad 
Published: June 2024

AbstractIntegrating physical processes with computational components creates cyber‐physical systems (CPS) that seamlessly interact between the physical and digital worlds. The cyber‐physical system has become an interesting research area and an attractive application domain, especially in industry based on the big advantages of this new paradigm. All companies are trying to use this model to control the real industry sector by integrating the cyber system. Many solutions were proposed however, they were not entirely satisfactory. This research proposes a novel CPS model based on Multi‐Agent Systems (MAS). This model takes advantage of MAS's collaborative and distributed nature to improve CPS's performance and functionality. Therefore, this model offers a flexible and scalable approach to the development and management of intricate, and interwoven CPSs. The research focuses on developing a CPS model, that encompasses nine layers: the physical agent, security agent, computation agent, decision‐making agent, control agent, communication agent, resilience agent, maintenance agent, and application agent layer. The MAS framework is employed to overcome the challenges associated with CPS design, such as coordination, dependability, maintainability, robustness, security, control etc. The results of this exploration are significant in their contribution to the advancement of CPS modelling by utilising Multi‐Agent Systems.
Pro familia Berlin goes TikTok – ein Beispiel für zeitgemäße Sexuelle
Bildung
Authors: Ritter Andreas , Stephan Ringo 
Published: June 2024

ZusammenfassungSeit Winter 2021 betreibt pro familia Berlin einen eigenen TikTok-Kanal (https://www.tiktok.com/@profamilia_berlin). Der
Kanal weist mehr als 60 Videos zu sexualpädagogischen Themen auf. Er hat rund 35 000 Follower*innen sowie
knapp 400 000 Likes gesammelt. Videos über Penislügen und zum Kondomgebrauch sind mit mehreren Millionen
Views viral gegangen. Der vorliegende Praxisbeitrag beschreibt, wie der Kanal entstanden ist. Er
schildert zudem, welche Erfahrungen mit der Content-Produktion und den Publikumsreaktionen gesammelt
werden. Empfehlungen für sexualpädagogische Fachkräfte, die selbst auf TikTok aktiv werden möchten,
werden abgeleitet.
Sexuelle Gesundheit fördern durch eine dialogorientierte Kommunikation auf Social
Media – LIEBESLEBEN als ein Beispiel guter Praxis
Authors: Breuer Johannes , Lulei Verena 
Published: June 2024

ZusammenfassungPrävention und Gesundheitsförderung im Bereich der sexuellen Gesundheit profitieren von einer
Kommunikation auf Social Media. Der vorliegende Praxisbeitrag beschreibt daher, wie die Bundeszentrale
für gesundheitliche Aufklärung (BZgA) ihre komplexe Intervention LIEBESLEBEN (www.liebesleben.de) in Sozialen Medien umsetzt. Dabei wird
konkret die Arbeit mit Instagram anhand der Prävention von Chlamydien sowie dem Schutz vor
Konversionsbehandlungen erläutert. LIEBESLEBEN dient der Förderung sexueller Gesundheit sowie der
Prävention von HIV und anderen sexuell übertragbaren Infektionen und soll zur Sprachfähigkeit über
Sexualität befähigen sowie die (Selbst-)Akzeptanz geschlechtlicher und sexueller Vielfalt fördern.
Perspectives on policing education and careers: insights from undergraduate students of China’s police academies
Authors: Wang Jianxin , Jiang Feng , Fang Xin 
Published: June 2024

AbstractThis study delves into the perspectives of Chinese police academy undergraduate students concerning their education and career paths within police academies. Employing a qualitative research design, in-depth interviews were conducted with undergraduate students from a leading police academy in China. The focus of the interviews centered on unraveling the cognitive transitions experienced by undergraduate students during their academy tenure, encompassing their perceptions of the police community and adherence to rigorous police discipline. The analysis revealed a profound transformation in undergraduate students, evolving from high-school graduates into aspiring law enforcement officers, manifesting in both behavioral and psychological dimensions. Undergraduate students developed a strong sense of identity with the police community and embraced the principles of police discipline, aligning themselves closely with these foundational concepts. Notably, robust collectivism was observed among undergraduate students. While showcasing a high level of enthusiasm for academic pursuits, concerns regarding potential challenges in their future policing roles were also articulated. This exploration establishes connections with the Social Cognitive Career Theory, shedding light on the dynamic cognitive processes and identity development experienced by police academy undergraduate students as they navigate their educational and career trajectories.
Different levels of co-construction in dialogue
Authors: Létourneau Alain 
Published: June 2024

Abstract
A completed research-action project on Climate change adaptation at the regional level (Memphremagog, Québec,
Canada) is revisited here, which requires first to briefly recall what is the CCA program, and the project’s context, goals, and
characteristics. The aim of the paper is to clarify issues of co-construction in dialogue, implementing a way to analytically
distinguish phases of co-construction at the level of the research team’s effort along the project, by following important
dialogue episodes. Stemming out of this dialogue analysis, another contribution of this work is to propose a better picture of the
internal relationship between three important components of the normative dimension of such projects: pursued values, processual
values, and the prescriptions that were required to actualize these values.
Nonlinear Multimodal Interference as Ultrafast Photonic Device for Dual-Wavelength Domain-Wall Dark Pulse Generation
Authors: Wang 王 Shan 珊 , Song 宋 Bo-Le 博乐 , Dou 窦 Xin-He 鑫河 , Qiao 乔 Fei-Hong 飞鸿 , Li 李 Xiang 响 , Wang 王 Jin-Bo 锦波 , Lv 吕 Zhi-Guo 志国 
Published: June 2024

Abstract
In comparison to bright pulses, better stability that is not susceptible to loss makes dark pulses accessible for applications in such fields as signal processing, optics sensing, and quantum communication. Here we investigate the dual-wavelength domain-wall dark pulse generation in a graded-index multimode fiber (GIMF) based anomalous dispersion single-mode fiber (SMF) laser. By optimizing intra-cavity nonlinearity and pulse polarization, the mode-locked states can evolve each other between bright pulses, dark pulses, and bright-dark pulse pairs. The evolution mechanism among them may be relevant to the coherent mode superposition, spectral filtering, and mode selection in SMF-GIMF-SMF hybrid-fiber modulation devices that affect the pulse formation and evolution in temporal, frequency, and space domains. These results provide a valuable reference for promoting further development of nonlinear optics and ultrafast optics, in which ultrafast photonic devices, with low cost, simple manufacture as well as wide adaptability, as novel pulsed generation technique, play a vital role.
Enhancing traditional grading in introductory physics courses
Authors: Kanchanapusakit Wittaya , Tanalikhit Pattarapon 
Published: June 2024

Abstract
The evaluation in introductory physics courses follows a traditional approach where a letter grade, determined by the total score, is assigned to represent the student’s overall performance. To enhance the meaningfulness of these grades, we supplement them with individual thinking proficiency profiles for each student. These profiles are derived from subscores attributed to particular exam questions, organized by the corresponding thinking skills. We report the average thinking proficiency profiles of all students and compare the average profiles among students from different grade groups. The objective is to aid instructors in identifying areas that may require improvement in the learning process.
Designing edge states from fractional polarization insulators
Authors: Chan Wei Jie , Fu Pei-Hao , Ang L K , Ang Yee Sin 
Published: June 2024

Abstract
We theoretically investigated disconnected dispersive edge states in an anisotropic honeycomb lattice without chiral symmetry. When both mirror and chiral symmetries are present, this system is defined by a topological quantity known as fractional polarization (FP) term and exhibits a bulk band gap, classifying it as an FP insulator. While the FP insulator accommodates robust, flat topological edge states (TES), it also offers the potential to engineer these edge states by deliberately disrupting a critical symmetry that safeguards the underlying topology. These symmetry-breaking terms allow the edge states to become dispersive and generate differing configurations along the open boundaries. Furthermore, disconnected helical-like and chiral-like edge states analogous to TES seen in quantum spin and anomalous hall effect are achieved by the finite size effect, not possible from the symmetry-breaking terms alone. The demonstration of manipulating these edge states from a FP insulator can open up new avenues in constructing devices that utilize topological domain walls.
Insights into the compositional and temperature-mediated magnetic characteristics of chromium-doped ZnO nanoparticles
Authors: Rizwana Begum S , Anitha A G , Thirumurugan Arun , Chidhambaram N 
Published: June 2024

Abstract
This study explores the influence of chromium content and temperature on the magnetic characteristics of ZnO synthesized via the cost-effective coprecipitation approach. The host ZnO structure is not significantly changed by chromium doping, even at 5 wt.% of chromium concentration, according to x-ray diffraction studies. The Zn–O characteristic stretching vibration band at 480 cm−1 and the other functional group attached to the Cr-doped ZnO nanoparticles are confirmed by Fourier-transform infrared (FTIR) spectroscopy studies. Diffuse reflectance spectroscopy analysis shows the interaction between chromium ions and ZnO causes bandgap narrowing, and the observed optical bandgap values fall as chromium content increases in the host ZnO matrix. Point defects such as zinc interstitial, zinc vacancy, and oxygen vacancy that exist in the Cr-doped ZnO nanoparticles are inveterate through photoluminescence spectroscopy. Vibrating sample magnetometry investigations reveal weak ferromagnetic behavior at low applied fields and diamagnetic signatures dominating at high applied fields in the Cr-doped ZnO nanoparticles at 300 K. The magnetic characteristics are also tunable in terms of temperatures, which opens new avenues for fabricating dilute magnetic semiconductors with various applications.
Predicting long-term trends in physical properties from short-term molecular dynamics simulations using long short-term memory
Authors: Noda Kota , Shibuta Yasushi 
Published: June 2024

Abstract
This study proposes a novel long short-term memory (LSTM)-based model for predicting future physical properties based on partial data of molecular dynamics (MD) simulation. It extracts latent vectors from atomic coordinates of MD simulations using graph convolutional network, utilizes LSTM to learn temporal trends in latent vectors and make one-step-ahead predictions of physical properties through fully connected layers. Validating with MD simulations of Ni solid-liquid systems, the model achieved accurate one-step-ahead prediction for time variation of the potential energy during solidification and melting processes using residual connections. Recursive use of predicted values enabled long-term prediction from just the first 20 snapshots of the MD simulation. The prediction has captured the feature of potential energy bending at low temperatures, which represents completion of solidification, despite that the MD data in short time do not have such a bending characteristic. Remarkably, for long-time prediction over 900 ps, the computation time was reduced to 1/700th of a full MD simulation of the same duration. This approach has shown the potential to significantly reduce computational cost for prediction of physical properties by efficiently utilizing the data of MD simulation.