bluuebunny/crossref_metadata_2025 huggingface dataset:
Work Roles and Functions of Undergraduate Rehabilitation Services Alumni: A Pilot Study
Authors: Herbert James T. , Barrett Karen , Evenson Thomas , Jacob Charles J.
Published: December 2024

A modified Delphi procedure was used to identify frequency and perceived importance of professional roles and functions that undergraduate rehabilitation services alumni perform. After a series of focus groups with alumni to develop task statements and subsequent input by rehabilitation educators who teach in undergraduate rehabilitation services programs, a final list of 102 job task statements was identified. In an online survey, 179 respondents from 19 undergraduate programs indicated that providing emotional support to clients, writing client progress and summary notes, advocating for clients, conducting interviews with clients and/or family members to obtain background information, and identifying and securing community resources for clients are job tasks they perform frequently and perceive as very important to their work. Conversely, administrative duties associated with recruiting and hiring staff and other volunteers, preparing budget reports, securing funding to support agency or facility activities, assessing programs to ensure compliance for accreditation reviews and conducting hiring interviews of staff were seen as work tasks/functions performed less frequently and not particularly germane to their work roles. These findings may be useful to develop accreditation standards for undergraduate rehabilitation services training. Recommendations for future research are addressed.
Baseline Concussion Testing in High School Athletes: A Gap Between Policy and Practice
Authors: Swenson Allison K. , Nies Mary A. , Taylor Noelle , Maughan Dale
Published: December 2024

Background:Concussions are a significant concern in high school athletes. Implementation of effective baseline concussion testing procedures can aid athletic trainers and coaches with timely and accurate concussion diagnosis, as well as being used to develop a personalized treatment plan for postconcussion management.Objective:The purpose of this policy review was to (a) identify the gap between the current baseline concussion testing policy and practices in the high schools throughout the state, (b) highlight opinions that support the importance of and need for mandatory baseline concussion testing in high school athletes, and (c) identify potential revisions to the present policy to change how baseline concussion testing is done.Methods:A mixed-methods approach was applied, utilizing a Qualtrics survey to gather data from high school athletic directors in the state. The survey assessed current testing practices, perceived barriers, and potential benefits regarding baseline concussion testing.Thirty-three responses were received, revealing current testing practices, potential benefits, and perceived barriers of baseline concussion testing. While acknowledging the potential challenges, respondents recognized the overall benefits of baseline testing for athletes who are concussed.Conclusions:The findings of this project underscore the desire for standardized baseline concussion testing procedures in high school athletes and were used to recommend revisions to the current policy for testing in the state.Implications for Nursing:Revisions to the existing policy change have the potential to promote athlete safety, reduce the risk of long-term health consequences, and improve health outcomes for student athletes.
Investigation of Video Dispatching Methods on Multiple End Devices in the Context of the Rust Programming Language
Authors: Ermakov Sergey , Lyapunov Vladislav , Shefner Al'bert , Ahmedov Hadzhimurad , Kot Nikita
Published: December 2024

Abstract. The modern world is actively moving towards digitalization, which requires efficient distribution of video content on a variety of end devices. The problem is that different usage scenarios impose different requirements on security, quality, and latency when transmitting video. The aim of the study is to identify the most suitable protocols for video dispatching in educational and real-world applications using the Rust programming language, known for its security and performance. Protocols such as HTTPS (TCP), BitTorrent, HLS, WebRTC, SRT and DASH have been investigated and analyzed. The results show that HLS and DASH have advantages in adaptive streaming in a changing network environment, while SRT and WebRTC provide low latency and high reliability for applications requiring real-time operation. The practical significance of these findings is confirmed by successful integration into educational systems, which ensures stable work even with a change in workload. Discussion: in the future, it is recommended to explore the combined use of several protocols, such as HLS and SRT, to improve the overall efficiency and reliability of video data transmission, as well as integration with CDN to improve quality and reduce load.
Cleaning of Semi-Structured and Unstructured Earth Remote Sensing Data
Authors: Homonenko Anatoliy , Kirienko Andrey , Zlobin Sergey , Davydova Dayana
Published: December 2024

Abstract. The problem of processing semi-structured and unstructured Earth remote sensing (ERS) data obtained by various methods, including satellites and unmanned aerial vehicles, is touched upon. The purpose of the article is to study and implement algorithms for effective purification and preprocessing of semi-structured and unstructured Earth remote sensing data. The importance of cleaning these data from noise, artifacts and errors is emphasized in order to increase their accuracy and significance in applied scientific research and practical application. Key data preprocessing techniques are considered, including noise removal, distortion correction, classification, segmentation and standardization of data, reinforcing theoretical positions with practical examples in Python using libraries such as GDAL, OpenCV and scikit-image. Examples of detection of aerospace and transport objects using machine learning and deep learning are given, emphasizing the importance of accuracy, completeness and F1-Score metrics in assessing the quality of data purification. The practical significance of the study lies in evaluating the effectiveness of data purification methods used to restore images during remote sensing of the Earth.
BİLİM VE TEKNOLOJİ KARŞITLIĞINDA REAKSİYONER TUTUM
Authors: Sever Oğuzcan
Published: December 2024

Günümüz dünyası bilim ve teknolojinin tüm yaşamı dönüştüren ilerlemesine şahit olsa da bazı kuramcılar bu gelişimin insani değerlere zarar verdiklerini iddia ederler. Bilim ve teknoloji karşısındaki şüpheciliğin radikal karşıtlığa vardığı noktada söz konusu eleştirilerin kaynağını incelemek gerekir. Zira bu tepki modernitenin birçok uğrağını içine alan bir eleştiriye dönüşüp, bilim yanlısı- karşıtı gibi basit bir ikilik temelinde ele alınamaz. Modernite süreciyle birlikte ortaya çıkan yeni insan, doğa, bilim, politika konseptleri, yaşanan ekonomik, siyasal, sosyal sorunlar ve nihayetinde ortalama insanın gündelik algısında deneyimlenen krizler bu sürecin ciddi şekilde kritik edilmesi şart koşmaktadır. Özellikle çağımızda yaşanan tekno- bilimsel gelişmeler neticesinde yükselen ve birçok insan tarafından paylaşılan eleştirileri, radikal- marjinal bir tepki yahut karikatürize edilmiş bir kitlenin karşı çıkışı olarak okumak meselenin derinliği ve çok yönlülüğüne nüfuz edememeye sebep olmaktadır. Bu çalışma söz konusu reaksiyoner tutumun, salt bilime olan tepkiyle sınırlı kalmadığını, temelde modernlik, rasyonalite ve teknolojiyi de kapsayan geniş bir ölçekte konumlandığını ortaya koymayı amaçlamaktadır
Examining the relationship between remittances and financial development in Zimbabwe
Authors: Chiwira Oscar , Murindagomo Tinashe
Published: December 2024

This study examines the short-run and long-run relationships between remittances and economic growth in Zimbabwe from 1980 to 2022, using the autoregressive distributed lag (ARDL) bounds testing approach. To ensure the reliability, validity, and stability of the data, the study used the Jacque-Bera normality test, Breusch Godfrey serial LM test, and Bruesch-Pagan-Godfrey heteroskedasticity test together with a cumulative sum of recursive residuals and cumulative sum of recursive squares. The dependent variable in this study is domestic credit to the private sector as a percentage of GDP, and the independent personal remittances as a percentage of GDP, with the control variables per capita GDP growth, inflation, and gross fixed capital formation. The theoretical framework explores key perspectives, including the remittance-development optimist view, which posits that remittances can drive investment and economic progress; the supply-leading hypothesis, suggesting financial development as a precursor to economic growth; and the growth-led hypothesis, which sees economic development as a catalyst for financial development. The results from the ARDL test show no evidence of co-integration in the long run; however, in the short run, a significant positive effect on financial development is observed. This finding supported the complementarity theory and showed how remittances stimulate demand for financial services. Particularly problematic was the negative and statistically significant effect of inflation on financial development, which can potentially harm the performance of financial markets and slow down financial activities. The study suggests implementing targeted policies to limit parallel market activities and direct resources towards the formal sector.
AI IN ENGLISH LANGUAGE LEARNING: SAUDI LEARNERS’ PERSPECTIVES AND USAGE
Authors: Alqaed Mai Abdullah
Published: December 2024

Artificial intelligence (AI) is gaining wide attention in second language learning as a beneficial tool. The current research investigates EFL learners’ perceptions and usage of AI applications among 68 undergraduate English language major students. The aim is to enhance students’ awareness of valuable AI applications and involve them with AI applications to help them correct their English language errors and develop their English usage. The intervention involved guiding participants’ engagement with AI applications through specific prompts and analysing their errors into surface and linguistic categories. The objective of this approach is to raise participants’ awareness of recurrent errors in their English essays. Also, the study gathers participants’ perceptions before and after using the AI applications through pre- and post-questionnaires and focus group interviews. The participants’ responses are mainly positive, indicating AI holds the potential to significantly enhance their English language across a variety of skills. The results revealed positive engagement with AI applications, although participants expressed cautious usage due to concerns about overreliance and reliability of the information provided. The study recommends that AI can facilitate language learning through immediate feedback and productive interactions. Further research is needed to guide teachers and L2 learners to use AI while learning English ethically.
FROM QUANTITY TO QUALITY: EVALUATING SCIENTIFIC WORK OF TERTIARY SCHOOL TEACHERS AND RESEARCHERS
Authors: Izarova Iryna , Bediukh Oleksandr , Hartman Yuliia , Baklazhenko Yuliia
Published: December 2024

The article is dedicated to analyzing modern approaches to evaluating the work of researchers in Europe, with a focus on qualitative indicators that serve as alternatives to traditional quantitative metrics. This research topic was selected in response to the growing number of discussions surrounding the challenges of evaluating scientific work, as well as the rise of initiatives being implemented by leading institutions and universities worldwide. The study examines the impact of initiatives such as the Leiden Manifesto, the San Francisco Declaration on Research Assessment (DORA) of 2012, the Hong Kong Principles, and the Open Science Career Evaluation Matrix (OS-CAM), as well as the European Research Area (ERA), on the development of new criteria for assessing scientific research. Special attention is given to the role of open science and inclusivity in evaluation processes. Additionally, examples of practices adopted by leading European universities and the potential for adapting these approaches in Ukraine are explored. The article emphasizes the importance and promise of qualitative evaluation of research activity, encouraging a shift away from conventional quantitative practices toward more meaningful and impactful assessment methods. The empirical method was employed to collect and analyze relevant information, forming the foundation of the research. An analytical method was also used to identify the strengths and weaknesses of the proposed evaluation practices. Furthermore, a comparative method was applied to investigate the differences between the suggested practices and to assess the effectiveness of each one. As a result of the study, global and national trends in the evaluation of researchers' work were identified, and recommendations were developed for implementing best practices of qualitative evaluation in Ukraine's academic sphere. The findings can be useful for Ukrainian higher education institutions when introducing internal evaluation practices for academic staff, as well as for central executive authorities responsible for shaping state education policy and initiating relevant legislative changes.
Identification of dynamics for machining systems
Authors: Petrakov Yuri , Okhrimenko Oleksandr , Sikailo Maksim
Published: December 2024

Cutting processes are carried out in an elastic machining system, which is multi-mass with negative and positive loop control with a delay in construed mathematical models. Its behavior during the cutting process is entirely determined by dynamic properties and an adequate parameters of mathematical model is necessary to control the process. The paper proposes a method for identifying such dynamic parameters of the machining system, which include natural vibration frequencies, vibration damping coefficients, and stiffness of the replacement model of single-mass system in the direction of the machine-CNC coordinate axes.
It is proposed to identify such parameters as a result of experimental modal analysis by impacting the elements of the tool and workpiece with an impact hammer and processing the impulse signal with a fast Fourier transform. It is proposed to adapt the results obtained to the adopted mathematical model of the machining system, presented in the form of two masses, each with two degrees of freedom, according to the equivalence of the spectrum signal power or its spectral density. The cutting force model in the form of a linearized dependence on the area of undeformed chips needs to be clarified by the coefficient using experimental oscillograms obtained during milling of a workpiece mounted on a dynamometer table. Based on the identified parameters of the machining system, a stability diagram was constructed in the “spindle speed – feed” coordinates and experiments were carried out under conditions in the zone of stable and unstable cutting. Evaluation of the roughness of the machined surface confirmed the correspondence to the location of the stability lobes diagram constructed using the identified parameters, which indicates the effectiveness of the proposed identification method.
Study of the possibility of using cavitation microcurrents in an ultrasonic scalpel for the glaucoma treatment
Authors: Sharhorodskyi Serhii , Luhovskyi Oleksandr
Published: December 2024

The development of new medical instruments for surgical treatment of glaucoma patients is an urgent scientific and applied task of modern mechanical engineering, since the number of visually impaired people in Ukraine due to glaucoma is growing every year.  The role of intraocular pressure (IOP) as a major risk factor in the pathogenesis of glaucoma development and progression has been proven. It has been established that in glaucoma the rate of aqueous humor secretion does not change, while the outflow resistance increases in the area of ​​the trabecular meshwork, which leads to an increase in IOP. A lot of evidence indicates that the resistance to the outflow of intraocular fluid is created in the area of ​​the inner wall of the trabecular meshwork. To date, the exact structural location and molecular nature of the creation of trabecular outflow resistance in the area of ​​the inner wall of the trabecular meshwork have not been precisely established and require further study. Today, the phenomenon of ultrasonic cavitation is widely used in technology, which occurs when high-intensity ultrasonic vibrations are introduced into a liquid and provides high-quality removal of contaminants from surfaces, disinfection, fine atomization, the formation of intense microcurrents, etc. Our work investigates changes in biomechanical reactions as a result of minimally invasive glaucoma surgery - expansion of physiological pathways for the outflow of intraocular fluid (trabecular apparatus, Schlemm's canal, etc.) using procedures using ultrasonic cavitation. By modernizing the phacoemulsifier, an ultrasonic glaucoma scalpel was created, which will allow cleaning the pores of the trabecular meshwork, restoring and maintaining its elasticity, reducing resistance to the outflow of ocular fluid, and reducing intraocular pressure. The use of such a tool will help ophthalmologists perform minimally invasive interventions aimed at normalizing the level of intraocular pressure in a less invasive and safer way, which will contribute to the prevention of progression and successful treatment of glaucoma. The development of the latest medical tools will make it possible to develop individual treatment strategies based on the specific needs and severity of the disease of each patient and create a perfect system of treatment for glaucoma patients.
Distribution of magnetic field strength along a wheel tooth depending on the shape of the inductor
Authors: Dubinina Olha , Medvedev Vadym
Published: December 2024

The research is aimed at determining the optimal shape of the inductor for processing the teeth of a large-sized gear wheel by magnetic pulse processing. The work studies the distribution of the magnetic field strength along the area of ​​the wheel tooth, depending on the type of inductor. This is necessary in order to predict the distribution of changes in the metal structure caused by MIO and their effect on the wear resistance of the wheel. The main task of the research is to establish the dependence of the magnetic field strength indicators on the shape and length of the inductor. Identifying the need for the presence or absence of a core.
Two types of inductors were considered: the first involute shape is worn on the wheel tooth, the second is located in the cavity between the wheel teeth. The calculation of the magnetic field strength distribution was carried out using the ANSYS Maxwel software package.
As a result of the research, it was found that the most effective for conducting magnetic pulse processing is the inductor of the first type, which is worn on the wheel tooth. The average values ​​of the magnetic field strength are 330-380 kA/m, which is sufficient for structural changes in the surface layer of the metal over the entire area of ​​the working surface of the tooth. The inductor of the second type, the length of which corresponds to the width of the gear crown, is ineffective. Since the magnitude of the magnetic field strength generated by it in the working area of ​​the wheel reaches only 29-67 kA/m and does not lead to structural changes in the surface layer of the metal. Increasing the length, as well as using cores of round and triangular shapes, did not give significant changes in the magnitude of the strength. It was also determined that the use of a shortened inductor of the second type is promising. In further studies of the optimal length of the inductor, it is recommended to study the direction and find out whether it is possible to process the gear wheel by stepwise movement of the inductor along the working surface of the tooth.
EFL students’ perceptions toward the use of electronic written feedback in academic writing classes
Authors: Putri Yohanna Amanda , Hadiyanto Anita Kurniawati , Mali Yustinus Calvin Gai
Published: December 2024

Feedback is one of the essential things for students to help them improve and develop their writing skills. Nowadays, the kinds of feedback are varied; a form that has often been used since the pandemic is electronic written feedback. This study aims to find out the students' perceptions toward the use of electronic written feedback. This study was conducted in the English Language Education Program at a private university in Salatiga. This study included 34 students registered in an Academic Writing class during the even semester 2023. The data for this study were gathered from semi-structured interviews and questionnaires. Both thematic analysis and statistical analysis were used to analyze the data from the interview and questionnaires. The findings revealed that the students’ attitudes toward electronic feedback were positive. Moreover, this study found weaknesses and strengths in using written feedback electronically. Practical recommendations for maximizing the potential of the electronic written feedback and directions for future research are also presented in this paper.
Improving English as a foreign language learners’ vocabulary and reading comprehension through crossword-assisted teaching
Authors: Yang Yu-Chi
Published: December 2024

Numerous studies have demonstrated the effectiveness of crossword-assisted teaching for English as a foreign language (EFL) instruction. The present study evaluated the effectiveness of this technique in the Chinese-speaking EFL environment. Two cohorts of junior college students participated in this study. Both groups completed a vocabulary and reading skill pretest, which revealed no significant differences between the groups. For convenience, a larger cohort of 34 students was designated as the experimental group, and a smaller cohort of 32 students was designated as the control group. During the study, crossword-solving tasks and quizzes were integrated into the instruction provided to the experimental group, whereas traditional lecture-based instruction was provided to the control group. After the study, both groups underwent the same posttest. The experimental group significantly outperformed the control group in both vocabulary knowledge and reading comprehension. Additionally, the experimental group students’ responses to a learning attitudes questionnaire indicated their favorable perceptions of the use of crosswords in instruction. Therefore, this study verified the effectiveness of crossword puzzles in a non-Western linguistic learning environment, reinforcing the value of crosswords for EFL teaching.
Analyzing the development of university English students’ speaking fluency
Authors: Aziez Feisal , Nita Alfia , Istikharoh Lutfi , Sotlikova Rimajon
Published: December 2024

The development of speaking fluency is a critical aspect of English language learning, particularly for non-native speakers. This study investigates the progress of university English learners in improving their speaking fluency, focusing on two key measures: the length of silent pauses and the use of pause fillers. A quantitative approach was employed, utilizing a pre-experimental design with 61 second-year students from two private universities, one in Indonesia and one in Uzbekistan. These students were enrolled in a speaking course at their respective universities, and the study served as an evaluative measure for the course. Data were collected through speaking tasks administered at the beginning and end of the course, where students delivered five-minute monologues on topics related to professional communication, specifically the creation of a startup company. The findings revealed a significant reduction in silent pauses, indicating an improvement in fluency, while the use of pause fillers showed minimal change.
Teaching English grammar for ESP learners: An exploration of content based instruction
Authors: Romadhon Romadhon
Published: December 2024

This study examined two instructional methods of grammar teaching for polytechnic students: the traditional method of translation and memorization and Content-Based Instruction (CBI). By involving first-year students majoring in Cyber Security, this study measured the impact of each method using pre- and post-tests focusing on key grammar topics integrated into IT content. The results showed that students in the CBI class outperformed those in the conventional class, wherein 53.34% of the former group attained converted grades of A and B while only 26.67% achieved similar grades in the latter. The students’ feedback collected through questionnaires indicated that they preferred CBI because it was more relevant and applicable to reality, thus motivating them and making the grammar understandable in context. CBI was effective in ESP settings because it combined language skills with subject matter, but it necessitated instructors to handle both language teaching and content area. The current study highlighted that CBI could be a more meaningful grammar instruction for providing better learner outcomes in technical fields.
A panoramic view of a structured how to write for publication course: College students’ views and tips
Authors: Erbay Çetinkaya Şakire
Published: December 2024

Despite the privileged status of writing in academia, satisfying outputs are still low, and thus lack of knowledge about the nature of academic writing and publishing is attempted to be compensated in how to write for publication courses. Responding to the existing calls to conduct writing-related studies going far beyond diagnosing well-established writing challenges, the current case study seeks to probe 8 MA candidates’ experiences, needs, wishes, and suggestions in a structured how-to-write for publication course through open-ended questionnaires and student diaries at the MA Applied Linguistics program of a large-size state university in Türkiye. The qualitative data of the current study were triangulated with an open-ended questionnaire in the form of participant self-reports and student diaries. The findings show that such writing interventions were valued for adding up to graduate candidates and socializing their writing. However, MA candidates needed to be supported with negotiated workshops as such extensions could help them apply writing theory and find the audience. The insights are provided, and the findings are discussed to suggest implications for both research and educational policy.
Integrative systematics with structural monophyly and ancestral signatures: Chionoloma (Bryophyta)
Authors: Zander Richard
Published: December 2024

The moss genus Chionoloma (Pottiaceae, Bryophyta), recently presented in a molecular analysis as a massive genus inflated by the synonymy of several heretofore accepted genera, is deframed and reformatted to internally define minimally monophyletic genera. This resurrects from the molecular synonymy of the genera Oxystegus and Pseudosymblepharis. Morphologically determined evolutionary relationships of species are combined with molecular signatures of ancestral species to devise an integrated evolutionary classification for the group. The methods include second-order morphological Markov chains, Shannon–Turing sequential Bayes statistical support, and multi-node molecular evidence of ancestry. This study is based on data and revisionary results from the original studies by other authors and from the study of herbarium specimens of authentic material. The reframing of this portmanteau genus directly affects the apprehension of biodiversity and rescues two genera from epistemological extinction.
Recipe Based Anomaly Detection with Adaptable Learning: Implications on Sustainable Smart Manufacturing
Authors: Lee Junhee , Jang Jaeseok , Tang Qing , Jung Hail
Published: December 2024

The advent of Industry 4.0 has significantly transformed the manufacturing sector, bringing advancements in quality control efficiency, environmental sustainability, and production development. These changes have led to development of intelligent technologies such as artificial intelligence(AI). However, implementing AI solutions in manufacturing processes still faces challenges in many aspects, particularly in handling irregular datasets influenced by diverse manufacturing settings. Especially in the field of injection molding, quality inspection often occurs at the batch level rather than per individual data, providing only the overall defective ratio of the batch production instead of each labeling result. These issues limit the general application of AI and data-driven decision making. To address these limitations and promote sustainable manufacturing, this study proposes a novel anomaly detection framework for a specific manufacturing process. For Recipe-Based Learning, we first apply K-Means to separate injection molding data into specific-setting based recipes to secure data normality. Then, autoencoders for anomaly detection are trained with normal data from each recipe. With taking control of the nature of the dataset, this data-driven AI approach resulted in predicting 61 defective products compared to the existing 41 defects. Meanwhile, the integrated model without considering the change of settings only predicted 2 defects which imply a poor and distorted quality inspection. For Adaptable Learning focused on new inputs with unseen settings, we apply KL-Divergence to find the closest trained recipe data and its model. In this case, it also exceeded the predictivity compared to the integrated and additionally trained models. This leads to continuous prediction without further training, which successfully expands the data-driven AI approach considering the change of settings. In the aspect of smart factory in the injection molding field, such improvement of continuous quality inspection with the proper application of AI can first enhance the productivity throughout the advancement of data-driven decision making. Furthermore, it is expected to efficiently reduce such environmental waste and computational cost, ensuring the overall sustainable manufacturing.
Outcomes of Broader Genomic Profiling in Metastatic Colorectal Cancer: a Portuguese Cohort Study
Authors: Roque Ricardo , Santos Rita , Santos Luis Guilherme , Coelho Rita , Fernandes Isabel , Varela Cunha Gonçalo , Gonçalves Marta , Fraga Teresa , Paulo Judy , Bonito Nuno
Published: December 2024

Background: Colorectal cancer (CRC) is the third most diagnosed cancer globally and the second leading cause of cancer-related deaths. Despite advancements, metastatic CRC (mCRC) has a five-year survival rate below 20%. Next-generation sequencing (NGS) is recommended nowadays to guide mCRC treatment, however its clinical utility when compared with traditional molecular testing in mCRC is debated due to limited survival improvement and cost-effectiveness concerns. Methods: This retrospective study included mCRC patients (≥18 years) treated at a single oncology center who underwent NGS during treatment planning. Tumour samples were analyzed using either a 52-gene Oncomine™ Focus Assay or a 500+ gene Oncomine™ Comprehensive Assay Plus. Variants were classified by clinical significance (ESMO ESCAT) and potential benefit (ESMO-MCBS and OncoKBTM). The Mann-Whitney and Chi square tests were used to compare characteristics of different groups, with significance at p<0.05. Results: Eighty-six metastatic colorectal cancer (mCRC) patients were analysed, all MMR proficient. Most cases (73.3%) underwent sequencing at diagnosis of metastatic disease, using primary tumour samples (74.4%) and a focused NGS assay (75.6%). A total of 206 somatic variants were detected in 86.0% of patients, 31.1% of which were classified as clinically significant, predominantly KRAS mutations (76.6%), with G12D and G12V variants as the most frequent. Among 33.7% RAS/BRAF wild-type patients, 65.5% received anti-EGFR therapies. Eleven patients (12.8%) had other actionable variants ESCAT level I-II, including four identified as TMB-high, four KRAS G12C, two BRAF V600E and one HER2 amplification. Four received therapies classified as OncoKbTM level 1-2 and ESMO-MCBS score 4, leading to disease control in three cases. Conclusions: NGS enables the detection of rare variants, supports personalized treatments, and expands therapeutic options. As new drugs emerge and genomic data integration improves, NGS is poised to enhance real-world mCRC management.
A Study on Practical Guidelines for Resilient Flight Operation Behavior Through Case Analysis Based on Integrated Safety Management System
Authors: No Hyun Woo , Cha Woo Chang
Published: December 2024

This study focuses on the phenomenon of recurring specific failures in the aviation industry, despite maintaining high safety levels through advanced technology and sophisticated safety management systems. To overcome the limitations of the current Safety-I centered reactive safety management approach, which only addresses surface-level causes and solutions of failures, this study proposes a new integrated approach combining Safety-I and Safety-II. To achieve this, we applied the HEAR (Human Error Analysis and Reduction) framework, which has been validated in the railway sector, to analyze three types of failure cases in aviation - FMS (Flight Management System) operation errors, turbulence-related accidents, and aircraft energy management issues. The analysis revealed that organizational factors (87.1%) were more significant causes of failures than individual/task factors (12.9%). Furthermore, by combining Safety-II methodologies such as AA LIT (American Airlines' Learning and Improvement Team) and FSF LAO (Flight Safety Foundation's Learning from All Operations), we developed specific methods to transform failure cases into resilient success cases. This study emphasizes strengthening safety managers' capabilities and establishing systematic training programs, proposing a paradigm shift in aviation safety management from 'failure prevention' to 'success expansion.' This integrated approach is expected to contribute to improving aviation safety culture and operational performance.
Protective Effects of Bifidobacterium Breve MCC1274 as a Novel Therapy for Alzheimer’s Disease
Authors: Abdelhamid Mona , Counts Scott E , Zhou Chunyu , Hida Hideki , Kim Jae-Il , Michikawa Makoto , Jung Cha-Gyun
Published: December 2024

Alzheimer’s disease (AD) is the most common form of dementia and is characterized by memory impairment that significantly interferes with daily life. Therapeutic options for AD that substantively modify disease progression remain a critical unmet need. In this regard, the gut microbiota is crucial in maintaining human health by regulating metabolism and immune responses, and increasing evidence suggests that probiotics, particularly beneficial bacteria, can enhance memory and cognitive functions. Recent studies have highlighted the positive effects of Bifidobacterium breve MCC1274 (B. breve MCC1274) on individuals with mild cognitive impairment (MCI) and schizophrenia. Additionally, oral supplementation with B. breve MCC1274 has been shown to effectively prevent memory decline in AppNL-G-F mice. In relation to Alzheimer’s pathology, oral supplementation with B. breve MCC1274 has been found to reduce amyloid-β (Aβ) accumulation and tau phosphorylation in both AppNL-G-F and wild-type (WT) mice. It also decreases microglial activation and increases levels of synaptic proteins.
In this review, we examine the beneficial effects of B. breve MCC1274 on AD, exploring potential mechanisms of action and how this probiotic strain may aid in preventing or treating the disease. Furthermore, we discuss the broader implications of B. breve MCC1274 for improving overall host health and provide insights into future research directions for this promising probiotic therapy.
Late Onset Myocarditis Following Immune Checkpoint Inhibitor Therapy: A Case Series with Literature Review
Authors: Muglu Harun , Sünger Erdem , Köylü Bahadır , Tunalı Didem , Erol Cengiz , Selcukbiricik Fatih , Bilici Ahmet , Olmez Omer Fatih
Published: December 2024

It would be fair to say that immune checkpoint inhibitor (ICI) therapy brought about a revolution in cancer treatment. However, it is important to note that ICI therapy can potentially lead to immune-related adverse events (irAEs), including myocarditis. While early-onset myocarditis is well-known, it is becoming increasingly recognized that late-onset cases may also occur. This case series presents four cases of late-onset ICI-associated myocarditis, which serve to underscore the importance of long-term surveillance for this potentially fatal complication. All patients presented with a variety of cardiac symptoms, including chest pain, shortness of breath, and arrhythmia. The diagnosis was confirmed through cardiac MRI and elevated cardiac biomarkers. Treatment involved immediate cessation of ICI therapy and initiation of high-dose corticosteroids. For patients with inadequate response, additional immunosuppressive agents were considered. This case series presents four cases of late-onset ICI-associated myocarditis, which highlights the importance of long-term surveillance for this potentially fatal complication. Further research is needed to establish optimal treatment strategies and long-term management for this complex condition.
The Dual Role of cGAS-STING Signaling in COVID-19: Implications for Therapy
Authors: di Flora Daniele Castro , Lara João Paulo Zanardini , Buzalaf Marília Afonso Rabelo
Published: December 2024

Since its emergence in late 2019, coronavirus disease 2019 (COVID-19) has rapidly become a global health crisis, with nearly 800 million confirmed cases and 7 million fatalities. The pandemic has had profound effects on public health systems and the global economy. The progression of COVID-19c involves a complex and intricated interplay between the SARS-CoV-2 virus and the host's immune response. The immune system employs both innate and adaptive mechanisms to combat infection. Innate immunity initiates the release of interferons (IFNs) and pro-inflammatory cytokines, while the adaptive immune response involves CD4+ Th lymphocytes, B lymphocytes, and CD8+ Tc cells. Pathogen-associated molecular patterns (PAMPS) and damage- associated molecular patterns (DAMPs) are recognized by pattern recognition receptors (PRRs), activating the cyclic guanosine monophosphate-adenosine monophosphate synthase-stimulator of interferon genes (cGAS-STING) signaling pathway, a crucial component of the innate immune response to SARS-CoV-2. This pathway plays a dual role during infection. In the early phase of infection, the virus can suppress cGAS-STING signaling to evade immune detection. However, in the late stages, activation of this pathway can lead to excessive inflammation and tissue damage, exacerbating disease severity. Modulating the cGAS-STING pathway, whether through agonists like dimeric amidobenzimidazole (diABZI) or inhibitors targeting viral proteins, such as 3CLpro, for example, offers a promising personalized therapeutic to control the immune response and reduce severe inflammation, improving clinical outcomes in patients with severe COVID-19.
Topoisomerase II Inhibitors in Lung Cancer: A Comprehensive Review of Etoposide's Role and Emerging Therapeutic Strategies
Authors: Jang Jung Yoon , Kim Donghwan , Im Eunok , Kim Nam Deuk
Published: December 2024

Topoisomerase II inhibitors, particularly etoposide, have long been integral to the treatment of lung cancer, especially small cell lung cancer. This review comprehensively examines the mechanisms of action of etoposide, its clinical efficacy, and its role in current lung cancer treatment regimens. Etoposide exerts its anticancer effects by inducing DNA strand breakages through inhibition of topoisomerase II, leading to cancer cell apoptosis. Despite their widespread use, challenges such as drug resistance, toxicity, and limited efficacy in non-small cell lung cancer have spurred ongoing research on combination therapies and novel drug formulations. Emerging therapeutic strategies include the integration of etoposide with immunotherapy, targeted therapies, and novel drug delivery systems aimed at enhancing the therapeutic window and overcoming drug resistance. This article aims to inform the development of more effective treatment strategies by providing a critical overview of the clinical applications of etoposide and exploring future directions for lung cancer therapy.
Bibliometric Analysis on the Application of Artificial Intelligence, Big Data and the Internet of Things in Traffic Management Systems in Latin America: Advances, Challenges and Opportunities
Authors: Rodriguez Baquero Laura Manuela , Quiroga Juliana Salazar , Angulo Mercedes Gaitan , Gómez Caicedo Melva Inés , Costa Leandro Vico , Ballesteros Vladimir , Alarcon Villamil Nelson Orlando
Published: December 2024

Artificial Intelligence, Big Data and the Internet of Things ( IoT ) have been in constant development within various fields of study for their application, especially within Traffic Management Systems and sustainable urban transport, the above was born with the need to reduce, mitigate and control large traffic flows, polluting emissions from vehicles, long travel times and traffic accidents that occur within cities, especially cities in underdeveloped countries, such as the Latin American zone. It is important to generate development strategies that consider a multidimensional and long-term perspective, the success of urban development requires strategic governance and the construction of public projects and the construction of the habitat as a public matter with social inclusion. Coordinated action is needed for environmental protection, territorial planning and public policies. Therefore, the purpose of this research is to analyze the implementation of Artificial Intelligence, Big Data and IoT within Traffic Management systems, specifically, within the Ibero-American zone, likewise, to examine the most effective artificial intelligence technologies and algorithms such as Predictive Models that provide traffic flows helping to have better control within the roads, these use Neural Networks to improve the statistical models used in these models, Machine Learning and Deep Learning among others, which have shown to have positive results in predicting demand and reducing vehicular congestion and accidents within cities and identify the challenges and limitations found in the implementation of these solutions within cities. For the above, a bibliographic review and a bibliometric analysis were carried out, which was performed using the Scopus database, supported by Bibliometrix and VOSviewer for bibliometrics, analyzing information on data, trends and characteristics of research publication, most preferred and productive journals, author, journal and productive countries, thematic evaluation and co-occurrence of words. The results show a low relevance of Ibero-America within the field of study despite having several investigations developed within it. The knowledge obtained in this research will be valuable for young researchers, industry professionals, transport policy makers and government entities in their search to identify solutions to road congestion.
Adaptive Learning Ability Enhancing of The Slow Sensor:A Machine Learning Approach
Authors: Xu Song , Chang Teng-Wen , Wu Yi-Sin
Published: December 2024

Slow sensors, widely used in industrial automation, environmental monitoring, and smart agriculture, face significant challenges in real-time data processing due to limitations such as bandwidth constraints, delayed response times, and low sampling rates. These issues, including data latency, sparsity, and noise, can hinder system performance and decision-making. However, integrating adaptive learning techniques, such as incremental and real-time learning algorithms, holds promise in enhancing the efficiency and reliability of slow sensor systems. Recent advancements in sensor technology, supported by machine learning and computational resources, have facilitated the development of intelligent sensor designs that optimize data acquisition and reduce computational burdens. This study explores the application of TinyML technology to slow sensors, enabling machine learning models to run efficiently on resource-constrained devices. Through a hybrid sensor design, combining hardware and senseware layers, the research aims to achieve real-time behavior perception using deep learning techniques. Two key experimental outcomes include the successful assembly of the slow sensor prototype and the deployment of a trained neural network within the system. Additionally, the study addresses challenges such as small sample sizes and data purification, both of which were critical to improving model performance and training efficiency. The findings underscore the potential of intelligent slow sensors and highlight the need for further exploration of their application in real-world scenarios, particularly in the realm of artificial intelligence integration. Future research will focus on refining sensor designs and evaluating the performance of slow sensors in specific application contexts.
From Leadership to Holdership: Psychoanalytic Insights for Thriving in the Digital Era
Authors: Sant'Anna Anderson de Souza , Oliveira Fátima Bayma de , Diniz Daniela Martins
Published: December 2024

This article discusses the concept of holdership as a human-centered alternative to traditional leadership approaches, particularly within the context of contemporary HR policies and practices. Holdership emphasizes collaboration, empowerment, autonomy, and personal growth, fostering psychological safety, trust, and innovation. By intersecting with Lacanian theory - specifically the discourse of the analyst and the concept of social ties - this article explores the role of relational dynamics and human subjectivity in organizational environments. The proposed framework highlights practical strategies for HR leaders to navigate the complexities of emergent work arrangements, including flexible, networked, and virtual structures. By integrating holdership principles with HR practices such as talent development, performance management, and knowledge creation processes, organizations can cultivate environments that promote creativity, adaptability, and sustainable growth. This research provides a theoretical and practical lens for organizations aiming to balance the de-subjectivizing forces of technology with the need for human potential as a source of competitive advantage.
Increasing Carbon Sequestration, Land Use Efficiency, and Building Decarbonization with Short Rotation Eucalyptus
Authors: Chilton Kate , Campoe Otávio Camargo , Allan Nicholas , Hinkle Hal
Published: December 2024

Global construction activity remains the least responsive large economic sector to the exigencies of global climate change. Focus has centered on operating emissions of buildings, while upfront embodied emissions in building materials remain unabated. Two of the most used building materials, steel and concrete, together produce more than 14 percent of total annual greenhouse gas emissions [1]. In contrast, softwood timber, another commonly used building material, can remove and store atmospheric carbon in buildings for decades. However, the upfront climate benefits of using structural-grade softwoods in durable building frames are limited due to the multi-decadal growth and harvest cycles. Here, we compare the use of fast-growing Brazilian Eucalyptus to a group of commonly used North American softwoods (spruce, pine, and fir) in a three-stage climate risk model that results in a novel Carbon Benefit Multiple, which quantifies the relative carbon removal benefits in a risk adjusted framework. The analysis shows that short rotation, high yield Eucalyptus is 2.7x to 4.6x better at removing atmospheric carbon than softwoods depending on various risk perception scenarios. The analysis indicates that building decarbonization can benefit by using fast growing and high yielding Eucalyptus species compared to traditionally used softwood species.