bluuebunny/crossref_metadata_2025 huggingface dataset:
Gut Microbiome and Symptom Burden in Obese and Non-Obese Women Receiving Chemotherapy for Breast Cancer
Authors: Cherwin Catherine H. , Hoang Jemmie , Roberts Emily K. , Mangalam Ashutosh
Published: February 2025

Purpose: Obese women with breast cancer experience high symptom burden, poor quality of life, and increased mortality compared to non-obese women with breast cancer. Obesity-related changes to the bacteria of the gut, the GI microbiome, may be one such mechanism for these differences in outcomes. The purpose of this work is to report symptom burden and GI microbiome composition between obese and non-obese women with breast cancer to identify potential microbial influences for symptom severity. Methods: 59 women with breast cancer (26 obese, 33 non-obese) provided symptom reports using the Memorial Symptom Assessment Scale and stool samples for 16S analysis one week after receiving chemotherapy. Symptom reports were summarized and examined for differences based on obesity. Fecal microbiome analysis was compared between groups using alpha-diversity (Shannon index), beta-diversity (Principal Coordinate Analysis with weighted UniFrac distances), and LASSO analysis of abundance of bacterial species. Results: While symptom burden was high, it did not differ based on obesity status. Alpha- and beta-diversity did not find significant differences based on obesity, but LASSO analysis identified eight bacteria to be significantly enriched in obese participants: Collinsella aerofacien, Prevotella 7, Coprobacillus cateniformis, Ruminococcus torques group, Agathobacter, Frisingicoccus, Roseburia inulinivorans, and Monoglobus pectinilyticus. Conclusions: Identifying biologic mechanisms driving symptoms is necessary for the development of therapies to reduce cancer-related symptom burden. While obesity may alter the GI microbiome and influence symptom burden in women with breast cancer, these effects may be outweighed by the effects of chemotherapy on the gut.
Adherence to intervention components: The key to success? Analysis on health-related outcomes of the AgeWell.de intervention to preserve cognition
Authors: Wittmann Felix G , Pabst Alexander , Zülke Andrea , Luppa Melanie , Cardona Maria I , Boekholt Melanie , Fankhänel Thomas , Weise Solveig , Kosilek Robert Philipp , Sanftenberg Linda , Brettschneider Christian , Döhring Juliane , Williamson Martin , Wiese Birgitt , Thyrian Jochen René , Hoffmann Wolfgang , Gensichen Jochen , König Hans-Helmut , Kaduszkiewicz Hanna , Frese Thomas , Riedel-Heller Steffi G
Published: February 2025

Background

The aim of the study was to analyze the impact of adherence to the intervention components on the effectiveness of AgeWell.de, a multi-domain lifestyle intervention against cognitive decline, on function in everyday activities, quality of life, depressiveness and social isolation.

Objective

Studying the effect of adherence on health-related outcomes.

Methods

Participants were aged 60–77 years at baseline and at risk (Cardiovascular Risk Factors, Ageing and Dementia Score (CAIDE) ≥9). Adherence to the components nutrition, enhancement of physical and social activities and cognitive training was analyzed in two ways, first continual within the intervention group (n = 378, mean age = 69.1 years, 52.7% female) and second as dichotomous split (75% adherence) and in reference to the control group (received infomaterial and regular health advice; n = 441, mean age = 69 years, 53% female). Generalized linear regression models were then run on the health outcomes functioning in everyday activities, quality of life, depressive symptoms, and social inclusion.

Results

Health-related quality of life and depressiveness were improved in participants with better adherence to nutritional counselling and enhancement of physical and social activities. Better adherence to social activities was relevant for function in everyday activities. Effects of high adherence to cognitive training was found for improvements in depressiveness when comparing it to the control group. No effect was found on social inclusion when considering the particular components.

Conclusions

The extent of adherence to most components influenced health-related outcomes such as health-related quality of life and depressiveness. With this study, the effectiveness of AgeWell.de can be understood in greater depth.

Trial Registration

German Clinical Trial Register (DRKS; ID: DRKS00013555).
Application of image reconstruction algorithm combining FCN and Pix2Pix in visual communication design
Authors: Zhao Man
Published: February 2025

This study addresses the limitations of traditional image reconstruction techniques in handling complex textures and fine details, which often result in poor image quality due to detail fidelity bottlenecks. An innovative image reconstruction framework is proposed by combining the global feature extraction capabilities of fully convolutional networks (FCNs) with the detail optimization advantages of the Pix2Pix generative adversarial network. The FCN’s fully convolutional architecture effectively captures the macro-structure of images, providing a solid foundation for reconstruction. The Pix2Pix network then generates preliminary results through adversarial learning, significantly enhancing image realism and texture naturalness. The performance of the proposed FCN-Pix2Pix framework was evaluated using the high-standard DIV2K dataset, which includes a variety of complex scenes. Compared to enhanced deep super-resolution network (EDSR) and super-resolution generative adversarial network (SRGAN), the FCN-Pix2Pix combination outperformed both in detail preservation and structural similarity. Specifically, the FCN-Pix2Pix model improved the peak signal-to-noise ratio (PSNR) by 3.2 and 4.0, and the structural similarity index (SSIM) by 0.03 and 0.06, respectively. The results demonstrate the significant advantages of this approach in maintaining image details and structural integrity. In conclusion, the integration of FCN and Pix2Pix not only addresses the challenges of image reconstruction in complex textured scenes but also significantly enhances image detail richness and texture quality, providing a reliable and efficient solution for high-quality image reconstruction in visual communication design.
Knowledge of strategic trade act 2010 and technology transfer among researchers in Malaysia
Authors: Badrul Hisham Amirah 'Aisha , Mohamed Yusof Nor Ashikin , Salleh Siti Hasliah , Saimy Intan Sazrina
Published: February 2025

The transfer of dual-use technologies, which can be used for both civilian and military applications, has become a critical issue for national and international security. In response, the Strategic Trade Act 2010 (STA 2010) was enacted in Malaysia to regulate the export, transit, and transshipment of strategic items, including dual-use goods and technologies. However, despite its importance, researchers in Malaysia’s Higher Learning Institutions exhibit lack of awareness and understanding of the Act, potentially placing national security at risk through unintended breaches of export control regulations. This study aims to evaluate the knowledge and awareness of the STA 2010 among researchers in Malaysia, focusing specifically on their understanding of tangible and intangible technology transfers (ITT) and the associated risks of dual-use items. Questionnaires were distributed to a purposive sample of researchers, and the data were analyzed using the Rasch Measurement Model to assess levels of knowledge. The results indicate a significant knowledge gap among the research community, with most respondents demonstrating insufficient awareness of STA 2010 provisions, despite the Act being in place for over a decade. These findings highlight the urgent need for targeted educational programs and outreach initiatives to improve compliance and mitigate potential risks. Policymakers and key stakeholders must strengthen efforts to raise awareness and ensure researchers are adequately informed about the legal frameworks governing dual-use technology transfers, thus safeguarding both national and international security.
Viral Justice: TikTok Activism, Misinformation, and the Fight for Social Change in Southeast Asia
Authors: Jalli Nuurrianti
Published: February 2025

This study examines the use of TikTok as a platform for youth activism in Southeast Asia, focusing on Indonesia, Malaysia, and the Philippines. Through a mixed-methods approach that includes qualitative content analysis, semi-structured interviews, systematic fact-checking, and digital trace data, the research explores how activists leverage TikTok’s unique features to promote social justice and mobilize political participation amid democratic backslidings. The findings reveal that activists skillfully adapt to TikTok’s attention economy, using strategies like trend-jacking and meme creation to reach broad audiences. However, they also face significant challenges, including rampant harassment and the precarious nature of algorithmic visibility. The study highlights the complexities of digital activism, where the pursuit of virality can sometimes undermine the depth of political movements. While the research counters the prevalent narrative that digital activism is rife with misinformation, it underscores the importance of maintaining accuracy to protect credibility. The study concludes by calling for further research on integrating online activism with offline organizing and exploring how platform governance can be reformed to better support activists. The insights from this study contribute to a deeper understanding of TikTok’s role in contemporary social movements and the challenges faced by youth activists in the digital age.
Delayed Postoperative Ambulation Results in a Significant Increase in 90-Day Mortality in Surgically Treated Hip Fractures
Authors: Wood Robert S. , Vergun Maddie , Herrera Elizabeth , Krumrey Jacqueline
Published: February 2025

Introduction

Hip fractures in individuals aged 65 and older present a significant burden to patients, families, and health care systems. These fractures lead to increased morbidity, loss of autonomy in Activities of Daily Living (ADLs), prolonged hospitalization, and heightened mortality rates. Despite existing knowledge, there is a need for high-quality studies to understand mid- to long-term outcomes and the impact of postoperative variables on mortality.

Methods

This retrospective matched case-control study analyzed patients who underwent operative management for hip fractures between August 1, 2021, and August 1, 2023, at a single Level II trauma center. Cases were defined as patients who expired between postoperative day 1 and ninety, while controls were patients alive at postoperative day 90. Cases and controls were matched by sex and age at the time of surgery. Patients over age 60, who underwent surgical treatment of a femoral neck or intertrochanteric fracture after receiving a preoperative block and were able to ambulate prior to their injury included. Cases and controls were matched based upon patient demographics including comorbidities. Major matched comorbidities were diabetes mellitus, hypertension, Chronic Obstructive Pulmonary Disease, and Coronary Artery Disease. A logistic regression was used to measure the association between in-hospital mobility and 90-day mortality.

Results

The 90-day mortality rate was 9.5% (16/169). The mean age of participants was 85.7 years, with 62.5% female. No significant differences were found in hospital length of stay or operative time. However, 37.5% of cases were discharged on hospice compared to 3.1% of controls. Only 6.3% of cases ambulated in the hospital compared to 53.1% of controls ( P-value <.001). Logistic regression indicated that the odds of death were 17 times higher in patients who did not walk during their hospital stay (OR: 17.0, 95% CI: 2.91-326.0, P-value: 0.01).

Conclusions

This study highlights the critical importance of early postoperative mobilization in reducing 90-day mortality in hip fracture patients. The findings reveal that patients who ambulated during hospital admission had significantly lower mortality rates. These results suggest that early mobilization could serve as a strong protective factor against early postoperative mortality.
Development and preliminary evaluation of a decision coach training module for nurses in Norway
Authors: Kienlin Simone , Nytrøen Kari , Kasper Jürgen , Stacey Dawn
Published: February 2025

Background

Shared decision-making (SDM) is a collaborative patient-centred process for arriving at informed healthcare decisions. Decision coaching can help support SDM when combined with patient decision aids. As part of a meta-curriculum “Ready for SDM” for training different healthcare professionals in SDM, we developed and pilot-tested a new module designed to train nurses as decision coaches. The study assessed nurses' perceptions of a decision coach training module, focusing on its feasibility, acceptability and its role in developing decision coaching capabilities.

Methods

We used a two-phase approach guided by the Knowledge-to-Action Framework. In the first phase, we developed a decision coach training module. The second phase involved preliminary testing, using a descriptive design with qualitative and quantitative methods. We recruited a convenience sample of participants from two hospitals. Participants completed questionnaires at the end of Part A (classroom training). The assessment was informed by Kirkpatrick’s first three levels of educational outcomes: reaction (acceptability), learning (self-reported attitudes, intentions and confidence) and behaviour (practical application of decision coaching). A post-hoc inquiry investigated low participation in Part B of the coach training. Qualitative data underwent content analysis and quantitative data were analysed using descriptive statistics.

Results

The development resulted in a decision coach training comprising a Part A (6 h) on SDM and decision coaching fundamentals and a Part B (1 h) which involved practical application of decision coaching in the participants’ own practice (audio recorded) with self-appraisal and individualised feedback. In preliminary testing with 19 nurses from seven clinical departments, 90% of participants rated Part A as acceptable and relevant to practice. Only one nurse completed Part B due to reluctance to audio record coaching sessions. The most reported perceived barrier was time constraints. Key perceived facilitators identified were interprofessional collaboration, management support and additional practical training.

Conclusion

Decision coach training was feasible to deliver in the classroom. Participants reported Part A as acceptable and relevant to their practice. The second part, including an audio recording component, proved unfeasible. Further research should explore alternative methods for skill assessment and feedback in clinical practice. The results from this study will inform further refinement of the Norwegian Ready for SDM meta-curriculum and implementation strategies, particularly regarding the practical training components.

Trial registration

Retrospectively registered (14.02.2023) at ISRCTN (ISRCTN44143097).
Targeting the fundamentals for tremors: the frequency and amplitude coding in essential tremor
Authors: Pan Ming-Kai
Published: February 2025

Essential tremor (ET) is one of the most common movement disorders with heterogeneous pathogenesis involving both genetic and environmental factors, which often results in variable therapeutic outcomes. Despite the diverse etiology, ET is defined by a core symptom of action tremor, an involuntary rhythmic movement that can be mathematically characterized by two parameters: tremor frequency and tremor amplitude. Recent advances in neural dynamics and clinical electrophysiology have provided valuable insights to explain how tremor frequency and amplitude are generated within the central nervous system. This review summarizes both animal and clinical evidence, encompassing the kinematic features of tremors, circuitry dynamics, and the neuronal coding mechanisms for the two parameters. Neural population coding within the olivocerebellum is implicated in determining tremor frequency, while the cerebellar circuitry synchrony and cerebellar-thalamo-cortical interactions play key roles in regulating tremor amplitude. Novel therapeutic strategies aimed at tuning tremor frequency and amplitude are also discussed. These neural dynamic approaches target the conserved mechanisms across ET patients with varying etiologies, offering the potential to develop universally effective therapies for ET.
Effect of early and later prone positioning on outcomes in invasively ventilated COVID-19 patients with acute respiratory distress syndrome: analysis of the prospective COVID-19 critical care consortium cohort study
Authors: Simpkin Andrew J. , McNicholas Bairbre A. , Hannon David , Bartlett Robert , Chiumello Davide , Dalton Heidi J. , Gibbons Kristen , White Nicole , Merson Laura , Fan Eddy , Panigada Mauro , Grasselli Giacomo , Motos Anna , Torres Antoni , Barbé Ferran , Ng Pauline Yeung , Fanning Jonathon P. , Nichol Alistair , Suen Jacky Y. , Bassi Gianluigi Li , Fraser John F. , Laffey John G. ,   on behalf of the COVID-19 Critical Care Consortium
Published: February 2025

Background

Prone positioning of patients with COVID-19 undergoing invasive mechanical ventilation (IMV) is widely used, but evidence of efficacy remains sparse. The COVID-19 Critical Care Consortium has generated one of the largest global datasets on the management and outcomes of critically ill COVID-19 patients. This prospective cohort study investigated the association between prone positioning and mortality and in particular focussed on timing of treatment.

Methods

We investigated the incidence, demographic profile, management and outcomes of proned patients undergoing IMV for COVID-19 in the study. We compared outcomes between patients prone positioned within 48 h of IMV to those (i) never proned, and (ii) proned only after 48 h.

Results

3131 patients had data on prone positioning, 1482 (47%) were never proned, 1034 (33%) were proned within 48 h and 615 (20%) were proned only after 48 h of commencement of IMV. 28-day (hazard ratio 0.82, 95% confidence interval [CI] 0.68, 0.98, p = 0.03) and 90-day (hazard ratio 0.81, 95% CI 0.68, 0.96, p = 0.02) mortality risks were lower in those patients proned within 48 h of IMV compared to those never proned. However, there was no evidence for a statistically significant association between prone positioning after 48 h with 28-day (hazard ratio 0.93, 95% CI 0.75, 1.14, p = 0.47) or 90-day mortality (hazard ratio 0.95, 95% CI 0.78, 1.16, p = 0.59).

Conclusions

Prone positioning is associated with improved outcomes in patients with COVID-19, but timing matters. We found no association between later proning and patient outcome.
Cannabinoid spoilage, metabolism and cannabidiol(CBD) conversion to Tetrahydrocannabinol(THC) mechanisms with energetic parameters
Authors: Henriques Alwyn
Published: February 2025

Chemical redox mechanisms and thermodynamic parameters of the Cannabinoids Δ9-Tetrahydrocannabinol (THC) and cannabidiol (CBD) were determined theoretically and using activated complex theory then compared to physical experimentations of chemical spoilage by Pholsiri T et al. and intramolecular conversion of CBD to thc by Daniels. R. et al. Thermodynamic parameters were derived from activated complex theory using standard bond enthalpy data from the elments of Physical Chemistry by Atkins ((Atkins, Elements of Physical Chemistry, 2001)). Situations where psychotropic cannabinoids found in CBD based products were also understood due to the parameters that drive the reduction process of conversion to THC. The metabolism process of cannabinoids has been detailed from consumption to excretion with mechanistic support to deactivation and glucuronidation in order to have a cannabis standard established.
Supporting Multilingual Science Learners
Authors: Svoboda Julia
Published: February 2025

This installment of Current Insights showcases recent research on how to equitably support multilingual learners in science classrooms.
Charge transfer caused anomalies of physical properties of KV2Se2O
Authors: Zhuang Haoyu , Bai Jianli , Cheng Jingwen , Li Xiangfei , Meng Ying , Wang Luyao , Zhang Qinghua , Shen X. , Wang Yumei , Chen Genfu , Yu Richeng
Published: February 2025

Persistent efforts have been devoted to unraveling the fundamental mechanism behind superconductivity. In the pursuit of novel unconventional superconductors, layered transition metal compounds have emerged as promising candidates. In this work, transmission electron microscopy, electron energy-loss spectroscopy (EELS), and first-principles calculations are used to investigate the underlying causes of the anomalies of the susceptibility and resistivity of KV2Se2O. No evidence of either long-range or short-range ordered structural phase transition related to CDW is observed. However, our findings reveal a variation in the electronic configuration of vanadium occurring at low temperatures, which is supported by EELS spectra and Bader charge analysis. The change in electronic configuration may elucidate the anomalies of physical properties.
A Witch's Guide to the Underground
Authors: Brown Shelina
Published: February 2025

This chapter investigates the midcentury Anglo-American fascination with the witch archetype, linking it to the concurrent rise of the sixties counterculture and second-wave feminism. The surge in interest in Wiccan practices and women's empowerment at this time led to a proliferation of spell books and guides across the Global North. Louise Huebner's influential Wiccan incantation records met this demand, offering a pathway to self-actualization for aspiring witches through connection with an ancient, divine feminine. Scholar Justyna Sempuch interprets this popularization as an "herstorical fantasy," a means of renegotiating women's roles in patriarchal society. The chapter also explores how female vocalists such as Stevie Nicks, with her Wiccan anthem "Rhiannon" (1976), embodied and projected the witch archetype, influencing subsequent generations of Wiccan-inspired indie rock artists. By adopting this symbolic stance, women artists of the sixties critiqued patriarchy within popular music cultures, employing essentialist notions of the numinous feminine for gender-based cultural resistance.
Transcriptional regulation of autophagy in skeletal muscle stem cells
Authors: Gopal Krishnan Priya D. , Lee Wen Xing , Goh Kah Yong , Choy Sze Mun , Turqueza Lewin Raymarc Roldan , Lim Zhuo Han , Tang Hong-Wen
Published: February 2025

Muscle stem cells (MuSCs) are essential for the regenerative capabilities of skeletal muscles. MuSCs are maintained in a quiescent state, but, when activated, can undergo proliferation and differentiation into myocytes, which fuse and mature to generate muscle fibers. The maintenance of MuSC quiescence and MuSC activation are processes that are tightly regulated by autophagy, a conserved degradation system that removes unessential or dysfunctional cellular components via lysosomes. Both the upregulation and downregulation of autophagy have been linked to impaired muscle regeneration, causing myopathies such as cancer cachexia, sarcopenia and Duchenne muscular dystrophy. In this Review, we highlight the importance of autophagy in regulating MuSC activity during muscle regeneration. Additionally, we summarize recent studies that link the transcriptional dysregulation of autophagy to muscle atrophy, emphasizing the dominant roles that transcription factors play in myogenic programs. Deciphering and understanding the roles of these transcription factors in the regulation of autophagy during myogenesis could advance the development of regenerative medicine.
Potential ER tubular lumen-sensing intrinsically disordered regions
Authors: Yorimitsu Tomohiro , Sato Ken
Published: February 2025

Intrinsically disordered regions (IDRs) are known to sense the positive membrane curvature of vesicles and tubules. However, whether IDRs can sense the negative curvature of their luminal surfaces remains elusive. Here, we show that IDRs direct specific localization to ER tubules. In Saccharomyces cerevisiae, Sed4 interacts with Sec16 at the ER exit site (ERES) to promote ER export. Upon loss of this interaction, Sed4 failed to assemble at the ERES but was enriched in the ER tubules in a luminal region-dependent manner. Fusion of the Sed4 luminal region with Sec12 and Sec22, which localize throughout the ER, resulted in their enrichment in the tubules. The luminal regions of Sed4 or its homologs, predicted to be IDRs, localized to tubules when translocated alone into the ER lumen. The lumen-imported IDRs derived from cytosol-localizing Sec16 and Atg13 also exhibited tubule localization. Furthermore, Sed4 constructs with the luminal region replaced by these IDRs were concentrated at the ERES. Collectively, we suggest that the IDRs may sense the properties of the tubule lumen, such as its surface, and facilitate Sed4 assembly at the ERES.
Assessing the students’ evaluations of educational quality (SEEQ) questionnaire in Oman higher education
Authors: Al Kalbani Muna
Published: February 2025

Background Student Evaluation of Education Quality (SEEQ) is a widely used tool for assessing educational quality. This local data study examined the SEEQ’s psychometric properties in Omani education, specifically its validity and reliability. This local data study examined the SEEQ’s psychometric properties in Omani education, specifically its validity and reliability. Methods This was quantitative research to assess educational quality from the students’ viewpoint. The study was conducted at Muscat College from January to March 2024.Simple randomization implemented at the course level helped to choose the participants. All students registered in the specified courses were asked to take part after a random sample of the courses Muscat College offers throughout the study term was chosen. Five hundred fifty students completed the survey. AMOS was used to conduct confirmatory factor analysis (CFA), and PSS was used to evaluate the internal consistency (IBM Corp., 2024a, 2024b). Results CFA of the SEEQ indicated that the eight -factor solution best fit the data. Results also showed that the SEEQ has overall good-to-excellent reliability. The adapted scale was psychometrically sound, proving SEEQ’s applicability Conclusions This study proposes using SEEQ to measure Oman’s education quality.
The comparison of totally ultrasound-guided versus fluoroscopy-guided shockwave lithotripsy in renal stone treatment: a systematic review and meta-analysis
Authors: Sihotang Retta Catherina , Rasyid Nur , Birowo Ponco , Situmorang Gerhard Reinaldi , Atmoko Widi
Published: February 2025

Extracorporeal shock wave lithotripsy (SWL) has been a well-known therapy since years ago, especially for renal stones less than 20 mm. This study compared the effectiveness of totally ultrasound-guided (US-guided) and fluoroscopy-guided (FS-guided) SWL in treating renal and ureteral stones. A protocol has been registered in PROSPERO databases for systematic reviews. A systematic literature search was conducted in five online databases (PubMed, ScienceDirect, EMBASE, ProQuest, and Scopus). We included all available articles that compared the effectiveness and safety of US-SWL to FS-SWL. A risk of bias assessment was done using Risk of Bias (Rob) Tools for randomized interventional studies and Risk of bias in non-randomized studies interventions (ROBINS-I) Tools for Non-randomized studies. The primary outcome was the stone-free rate, and the secondary outcome was the complication rate. Subgroup analyses were performed for adult and pediatric groups. A comprehensive literature search identified seven comparative articles that matched the criteria: two randomized trials and six retrospective cohort studies comprising 1,255 patients (609 using US-SWL). The results revealed a significant difference in overall stone-free rates between US-guided and FS-guided SWL RR 0.76(95% CI; 0.61-0.95, p=0.02) and in adults RR 0.76(95% CI; 0.60-0.96), but not children groups RR 0.68(95% CI; 0.24-1.88). US-SWL might be favourable due to the radiation-free procedure and real-time presentation. Complication rates were low, and no life-threatening complications were reported. In conclusion, US-guided SWL is more effective than FS-guided SWL for treating renal stones, with a low incidence of complications. Further randomized controlled trials with larger populations are needed to explore the comparison more accurately.
FEDECOM: Enabling cross-border energy exchange by federating energy communities
Authors: Lennard Zia
Published: February 2025

The FEDECOM project (Federated-system approach for flexible and interoperable energy communities) is a European Union-funded project aimed at fostering the integration and flexibility of local energy systems by demonstrating the potential of cross-border energy exchange by energy sector coupling through a federation of energy communities. The project seeks to provide economic benefits, improve grid stability and reliability, and contribute to the decarbonisation of the energy system. FEDECOM combines direct and indirect electrification strategies to leverage synergies and offers a cloud-based platform for managing local energy systems, including power, gas, thermal energy, industry, and mobility sectors. This paper discusses FEDECOM’s approach to energy management at multiple pilot sites, seeking to optimize resource use, enhance grid stability, and promote sustainable energy practices. It presents an overview of the FEDECOM project's goals, structure, pilot sites, and technical innovations, including peer-to-peer trading, semantic data modeling, and a novel platform architecture.
The Prediction and Evaluation of Manufacturing Technology innovation based on Machine Learning and Big Data Analysis
Authors: Yang Fang
Published: February 2025

A data anomaly detection method was designed based on chemical manufacturing and oil refining units. Massive data storage and calculation are used in the cloud computing framework for petrochemical enterprises, refineries, and other large enterprises. The massive data is segmented based on the modified time series method, and the anomaly analysis is carried out. Thus, the abnormal data of the chemical manufacturing and oil refining units can be monitored. The practice proves that the algorithm proposed in this paper is a feasible, simple and effective data correction scheme.
Application Research Of Improved Particle Swarm Computing Intelligent Algorithm In Track And Field Training Target Optimization
Authors: Wang Chao
Published: February 2025

This paper studies the influence of the athlete's state and wind direction on the Javelin flight trajectory. The process of plane throwing is analyzed theoretically. An accurate javelin flight mathematical model is established. Using the modified particle swarm optimization method, the paper finds a way to make the Javelin longer distance. This algorithm makes it portable and adaptive. Then, the entropy weight method is used to evaluate the weight of each factor. The experiment shows that this method can reflect the actual Javelin flying condition well, and its prediction effect is in accord with the demand of engineering applications.
Research on Modelling Architectural Heritage of Third-line Construction based on Hierarchical Analysis and Data Fusion using Rat Swarm tuned Artificial Neural Network
Authors: Liu Yanlong , Liang Xuan , Yu Rong , Li Jie
Published: February 2025

This study explores the novel use of Artificial Neural Networks (ANNs) with Rat Swarm Optimization (ANN-RSO) to model the architectural legacy of third-line construction projects. A multi-layered, combined approach to thoroughly assess and protect valuable historical buildings is constructed by the study through the application of hierarchical analysis and data fusion tools. The approach makes use of ANN-RSO power to maximize the analysis and understanding of a variety of data sets, from historical and cultural relevance to structural details and material compositions. Through the systematic division of complicated data into digestible layers, hierarchical analysis improves the neural network's power by concentrating on distinct aspects at various levels. Data fusion combines different data kinds at the same time, such as verbal descriptions, architectural plans, and photographic proof, to create a rich, consistent database that feeds into the neural network. By fine-tuning the ANN parameters, the RSO approach greatly increases the model's efficiency and accuracy in predicting and modeling architectural features. This study provides a standard for the use of modern computational techniques in the protection of cultural heritage in addition to showcasing the potential of ANN-RSO in architectural heritage modeling. The results show that these technologically advanced models can be essential resources for architectural historians and preservationists working on reconstruction projects, giving them a better understanding of the past and more precise reconstructions of historical buildings.
Hybrid Data Publishing Based on Differential Privacy
Authors: Wang Tao , Sun Kaining , Yin Rui , Zhang Teng , Zhang Longjun
Published: February 2025

The advent of the information and intelligence era has led to explosive growth of data. The author proposes a hybrid data model based on differential privacy. The main content of this model is based on the study of differential privacy, processing the data through a noise mechanism, using the calculation of tuple attribute differences and noise addition, and finally constructing a mixed data model based on differential privacy through experiments. The experimental results indicate that: as the value of k increases, the clustering results tend to be optimal, verifying that clustering the original data can reduce noise addition. However, ICMD-DP anonymizes the original dataset, resulting in much higher information loss than DCKPDP and prototype algorithms.  A mixed data model based on differential privacy enables better clustering performance of the original dataset, thereby utilizing differential privacy to better protect the data.
Application of Intelligent Robot in the Intelligent Recommendation of Mobile Application Content
Authors: Zhou Ping , Duan Bowei , Liu Feilong , Jing Xin , Lei Yan , Li Xijing
Published: February 2025

In order to bring a new perspective of human-computer interaction to TV program hosts, increase program highlights, and promote the integration and development of new technologies and new media, the authors propose the application of intelligent robots in mobile application content intelligent recommendation. Designed and implemented an artificial intelligence virtual assisted hosting robot system, including overall system design, knowledge base design, and robot interaction control system implementation. A "smart investment advisory model" has been established based on multidimensional calculations and analysis of project areas, investment amounts, and on-site attention. The results showed that the final system did not recommend the 6th and 7th investors with the highest matching degree in the field, nor did it recommend the 8th investor with the highest matching degree in investment amount, nor did it recommend the 4th investor with the highest matching degree in communication. Instead, it selected the 1st investor by combining three factors, the entrepreneurs of this period ultimately followed Little A's advice and chose investor 1 as their entrepreneurial investor. In 46 investment recommendation applications, there were 6 times when Mr. A's investor selection suggestions were not the highest bidding investors on the program site. In these 6 times, 5 entrepreneurs followed Mr. A's suggestions, and his analysis received recognition from different entrepreneurial mentors multiple times, demonstrating the rationality of Mr. A's recommendations, with a recommendation adoption rate of 97.72% (45/46). The system has achieved intelligent data analysis and recommended reasonable investors for entrepreneurs, with a high recommendation adoption rate. The comprehensive application of technologies such as speech recognition, facial recognition, and natural language processing has achieved interactive functions for program hosting, ensuring consistency and fluency in program hosting. The practical application effect is good, promoting the application of artificial intelligence robots in television media.
Integrative Development of Research Travel and Cultural Heritage Protection based on 5G Communication and Mobile Base Station from the Perspective of Geography
Authors: Chen Yanyan
Published: February 2025

Energy efficiency is one of the important issues that must be taken into consideration at the beginning of 5G communication design; in this study, the base station energy consumption model is selected for subsequent network energy efficiency assessment. With the increasingly strict requirements for base station antennas, the design of base station antenna units has been put forward with higher requirements. This thesis tracks the latest research advances in 5G communication requirements and key technologies from various research organizations at home and abroad. The world cultural heritage research trip integrates cultural heritage with heritage tourism and youth heritage education in the present environment of the merger of culture and tourism. The interpretation and presentation of legacy, as exemplified by Mount Lushan World Geopark, serves to communicate to the general public the significance of heritage. According to this study, heritage education is an activity that management agencies, research institutes, and local community members arrange either alone or in collaboration with other tourism and educational institutions with the goal of raising public awareness of heritage and educating people about heritage through research excursions. This document outlines this idea and lists the organizers, research objectives, range of activities, and learning materials for cultural heritage research excursions. The optimized MIMO-D2D system model is demonstrated to be effective in Lushan World Geopark by the experimental findings. This report suggests five strategies and actions for cutting-edge study abroad programs and the preservation of China's intangible cultural heritage.
Research on Big Data Visualization Technology based on Multi-source Vibrational Data Acquisition
Authors: Ling Haojie , Wan Xiang , Gou Yi , Huang Yuan
Published: February 2025

In order to scientifically and reasonably monitor the soil environment of green spaces in urban residential areas, the layout and sampling methods of soil monitoring points for green spaces in residential areas were studied, including the selection of representative residential areas, determination of monitoring point sampling positions, and determination of the number of points. The author proposed a research on the layout and sampling of soil monitoring points for green spaces in urban residential areas based on multi-source data collection and big data visualization. By using multi-source big data visualization methods, representative residential areas of a certain city were selected to monitor heavy metals (cadmium, mercury, arsenic, lead, copper, chromium, zinc, and nickel) in the green soil of their residential areas. The study reveals variations in heavy metal concentrations in the soil across residential areas of differing building ages. To ensure thorough monitoring of soil environmental conditions in residential areas, it's recommended to include neighborhoods of varying building ages as monitoring sites. Our findings indicate that the choice of sampling locations within these areas does not substantially affect the heavy metal content in soil samples. Therefore, it's preferable to prioritize sampling from residential areas rather than focusing solely on large green spaces within them, There are differences in samples from different monitoring points within the same residential area, and at least 3-4 monitoring points should be set up in each residential area to represent the soil environmental conditions of that residential area. The application of multi-source big data has a positive effect and advantage on the distribution of urban soil monitoring points.
Intelligent Optimization and Recommendation System Design for Personalized Training Programs for Marathon Athletes based on Machine Learning
Authors: Guo LuXia
Published: February 2025

This research focuses on developing an innovative machine learning-based intelligent optimization and recommendation system for marathon runners' personalized training schemes. The system aims to provide accurate and dynamically adjusted training guidance for athletes through real-time monitoring, training effect evaluation and intelligent recommendation. First, the system uses advanced wearable technology to achieve real-time monitoring of multiple physiological and athletic data during athlete training, including but not limited to heart rate variability, lactate threshold, and gait analysis. This data forms the basis of a personalized training program. Secondly, the support vector machine (SVM) algorithm is used to evaluate the training effect of the collected data. Finally, the system combines individual characteristics and the historical performance of athletes and generates personalized training plans through optimization strategies such as support vector machines. This process not only considers the short-term training goals but also considers the long-term sports career planning. Through algorithm modeling and computer simulation, it is found that the system can realize the continuous optimization of the training scheme in the process of continuous iteration. The intelligent system significantly improves athletes' training efficiency and competition performance compared to traditional training methods. This study provides a new perspective and practice path for intellectualization in sports training.
The Medical Testing Equipment Management System based on Artificial Intelligence
Authors: Pei Hongli , Sun Lei , Guo Wentao
Published: February 2025

This study focuses on developing a medical testing equipment management system based on artificial intelligence. The system integrates advanced sensor technology to monitor patient's physiological characteristics data in real-time, such as heart rate, blood pressure, body temperature, etc. and processes the data through a differential entropy analysis algorithm to extract key health indicators. Then, this study constructed a deep learning neural network model to predict the changing trend of patient health status and optimized the configuration and use of medical detection equipment accordingly. This paper proposes a feature extraction method based on neural network model, which can effectively identify abnormal patterns in physiological signals and provide high-quality input data for subsequent prediction models. Simulation results show that the proposed neural network model has high accuracy and practicability in predicting patients' health status. The model can assist healthcare workers in identifying potential health risks in time to improve treatment results and patients' quality of life.
Monitoring and Three-dimensional Numerical Analysis of Rock and Soil Deformation during Construction
Authors: Wu Jun
Published: February 2025

In order to solve the problem of large monitoring errors in settlement deformation in construction engineering, the author proposes rock and soil deformation monitoring and three-dimensional numerical analysis under construction. The author proposes a settlement and deformation monitoring method for pile foundation construction in green building engineering. By setting settlement deformation monitoring points and setting the frequency of pile foundation contour monitoring, a contour line tracking edge monitoring model is constructed to obtain monitoring results, and longitudinal contour correction is used to correct monitoring errors, thus achieving settlement deformation monitoring. The experimental results show that compared with the traditional symmetrical settlement deformation monitoring group and the traditional compression observation settlement deformation monitoring group, the monitoring error obtained by the contour line tracking settlement deformation monitoring group designed by the author is controlled below 1.1. The author's monitoring method has better results, higher accuracy, and smaller errors, and has practical application value.
The Income Allocation Mechanism of Trusted Dual Contribution Data Assets Based on Blockchain Technology
Authors: Chen Qianhui , Ding Weibin , Shen Huaqiang
Published: February 2025

In order to solve the problem of researching the distribution of returns on trustworthy "dual contribution" data assets, the authors propose a research on the distribution mechanism of returns on trustworthy "dual contribution" data assets based on blockchain technology. Integrate and apply various levels in the blockchain system. In this model, a node authorization control mechanism is added in the network layer, which can be customized in the consensus layer, and the data query efficiency can be improved through the optimization of the structure and the establishment of the index, so that the data can be managed intelligently in the intelligent contract layer, and encrypts information with customizable encryption algorithms at the transaction layer. In simpler terms, the new data asset management model utilizing blockchain technology has made on-chain data queries 2.25 times faster compared to conventional models. The benefit distribution mechanism model of blockchain is more conducive to internal cooperation than the traditional model.
Design and Development of Memory Pixel Architecture for Sobel Edge Detection
Authors: Yellamraju Sri Chakrapani , Nandanavanam Venkateswara Rao , Maddu Kamaraju
Published: February 2025

Memory is a fundamental hardware structure used in various electronic and multi-media products. The design and development of large-size memory architectures have become increasingly complex due to the growing demands of high-resolution image processing applications. This research work aims to design a specialized memory architecture module for Sobel edge detection, an essential technique in image processing. The proposed architecture (memory pixel size) consists of memory unit, comprising rows and columns, is determined by the image resolution. For effective Sobel edge detection, the image pixels must be stored in memory, and read operations are performed to access a 3x3 matrix of nine pixels. A critical consideration in developing this memory architecture is power dissipation, which is mitigated through the application of Clock Gating techniques. The proposed pixel memory architecture is implemented using MATLAB and Xilinx ISE software with Verilog HDL. The image pixel memory is developed using Block RAMs (BRAMs) and registers, and the 3x3 pixel matrix required for the Sobel edge detector is generated. Simulation, synthesis, and power analysis are conducted for the image pixel memory across source images with various resolutions, including 10x40, 10x20, 128x128, 320x240, and 512x512. The results indicate reduced power dissipation from 30% to 40% due to Clock Gating. This work demonstrates the effectiveness of the proposed memory architecture in reducing power consumption while maintaining performance. Future work aims to further enhance the performance of image pixel memory by decreasing the number of registers and improving pixel access times. Such module will provide a more efficient and scalable solution for high-resolution image processing applications.