bluuebunny/crossref_metadata_2025 huggingface dataset:
Stellar Flares, Superflares and Coronal Mass Ejections – Entering the Big Data Era
Authors: Vida Krisztián , Kővári Zsolt , Leitzinger Martin , Odert Petra , Oláh Katalin , Seli Bálint , Kriskovics Levente , Greimel Robert , Görgei Anna Mária
Published: June 2024

Flares, sometimes accompanied by coronal mass ejections (CMEs), are the result of sudden changes in the magnetic field of stars with high energy release through magnetic reconnection, which can be observed across a wide range of the electromagnetic spectrum from radio waves to the optical range to X-rays. In our review, we attempt to collect some fundamental new results, which can largely be linked to the Big data era that has arrived due to the expansion of space photometric observations of the last two decades. We list the different types of stars showing flare activity, their observation strategies, and discuss how their main stellar properties relate to the characteristics of the flares (or even CMEs) they emit. Our goal is to focus, without claiming to be complete, on those results that may in one way or another challenge the "standard" flare model based on the solar paradigm.
Quantifying the Cross-Sectoral Intersecting Discrepancies Within Multiple Groups Using Latent Class Analysis Towards Fairness
Authors: Yuan Yingfang , Chen Kefan , Rizvi Mehdi , Baillie Lynne , Pang Wei
Published: June 2024

The growing interest in fair AI development is evident. The ''Leave No One Behind'' initiative urges us to address multiple and intersecting forms of inequality in accessing services, resources, and opportunities, emphasising the significance of fairness in AI. This is particularly relevant as an increasing number of AI tools are applied to decision-making processes, such as resource allocation and service scheme development, across various sectors such as health, energy, and housing. Therefore, exploring joint inequalities in these sectors is significant and valuable for thoroughly understanding overall inequality and unfairness. This research introduces an innovative approach to quantify cross-sectoral intersecting discrepancies among user-defined groups using latent class analysis. These discrepancies can be used to approximate inequality and provide valuable insights to fairness issues. We validate our approach using both proprietary and public datasets, including EVENS and Census 2021 (England \& Wales) datasets, to examine cross-sectoral intersecting discrepancies among different ethnic groups. We also verify the reliability of the quantified discrepancy by conducting a correlation analysis with a government public metric. Our findings reveal significant discrepancies between minority ethnic groups, highlighting the need for targeted interventions in real-world AI applications. Additionally, we demonstrate how the proposed approach can be used to provide insights into the fairness of machine learning.
Anticancer Potential of Valencia Peanut (Arachis hypogaea L.) Skin Extract against Cervical Cancer Cells In Vitro and in Nude Mouse Xenograft Models
Authors: Jeeunngoi Jarckrit , Senawong Gulsiri , Jogloy Sanun , Prompipak Jeerati , Samankul Arunta , Utaiwat Suppawit , Woranam Khanutsanan , Sripa Banchob , Senawong Thanaset
Published: June 2024

Abstract: This study aimed at investigating the effects of Valencia KK4-type peanut skin ethanolic extract (KK4-PSE) in combination with cisplatin or 5-fluorouracil (5-FU) against HeLa cells in vitro and in xenograft models. MTT assay showed that KK4-PSE, cisplatin, and 5-FU suppressed proliferation of HeLa cells in a dose and time dependent manner. Drug interactions by Chou-Talalay method demonstrated that KK4-PSE enhanced antiproliferative activity of 5-FU against HeLa cells with combination index (CI) values of 0.49 (48 h) and 0.60 (72 h), indicating a synergistic effect, while KK4-PSE combined with cisplatin exhibited an additive effect (CI = 1.02) (72 h) and antagonistic effect at 24 and 48 h exposures (CI = 1.12 and 1.18, respectively). In nude mouse xenograft models, the combination of 5-FU and KK4-PSE markedly reduced HeLa tumor weights compared with control and single agent treatments. The combination of KK4-PSE and 5-FU achieved greater tumor growth inhibition than that of the KK4-PSE-cisplatin combination. KK4-PSE mitigated hepatotoxicity induced by both cisplatin and 5-FU in nude mice. The spleen hyaloserositis was significantly reduced in the combination treatment of 5-FU and KK4-PSE. These findings suggest a potential of KK4-PSE to inhibit cervical cancer cell growth while alleviating the toxicities of cisplatin and 5-FU.
High-Throughput Drug Stability Assessment via Biomimetic Metalloporphyrin Catalyzed Reactions Using Laser-Assisted Rapid Evaporative Ionization Mass Spectrometry (LA-REIMS)
Authors: Marton András , Mohácsi Zsombor Márton , Decsi Balázs , Csillag Balázs , Balogh Júlia , Schäffer Richárd , Karancsi Tamás , Balogh György Tibor
Published: June 2024

It is an utmost importance to characterize drug candidates as early in the development pipeline as possible. Appropriate application of the emerging high throughput analytical techniques unlocks the opportunities to obtain experimental data for in vitro absorption, distribution, metabolism and elimination (ADME) profiling of large compound libraries which is crucial for selection of lead compounds. In an usual scenario, only one drug candidate will be selected from thousands of early compounds based on several stability and screening results. A high to medium throughput screening approaches could significantly accelerates the subsequent research and production phases. Traditionally, the analysis of metabolic stability assays heavily relies on high throughput LC-MS/MS techniques to meet with the lead profiling demands. In this study presented an innovative experimental approach that can offer a refreshing alternative. Laser Assisted Rapid Evaporative Ionization Mass Spectrometry (LA-REIMS) is a quick and efficient method for characterizing complex biological samples without laborious sample preparation and chemical separation. Therefore, using an automated LA-REIMS well plate reader as fast as 8 seconds per sample, we assessed the oxidative metabolic stability of active agents using biomimetic metalloporphyrin-based oxidative model reactions at various pH for commercially available drug substances and compared stability measurements with traditional HPLC-DAD-MS results.
Green Synthesis of CuO Nanoparticles from Macroalgae Ulva lactuca and Gracilaria verrucosa
Authors: Marmiroli Marta , Villani Marco , Scarponi Paolina , Carlo Silvia , Pagano Luca , Sinisi Valentina , Lazzarini Laura , Pavlicevic Milica , Marmiroli Nelson
Published: June 2024

Macroalgae seaweeds such as Ulva lactuca and Gracilaria verrucosa cause problems on the Northern Coast of the Italian Adriatic Sea because their overabundance hinders the growth of cultivated clams, Rudatapes philippinarum. This study focused on the green synthesis of CuO nanoparticles from U. lactuca and G. verrucosa. The biosynthesized CuO NPs were successfully characterized using FTIR, XRD, HRTEM/EDX, and zeta potential. Nanoparticles from the two different algae species are essentially identical, with the same physical characteristics and almost the same antimicrobial activities. We have not investigated the cause of this identity, but it seems likely to arise from the reaction of Cu with the same algae metabolites in both species. The study demonstrates that it is possible to obtain useful products from these macroalgae through a green synthesis approach and that they should be considered as not just a cause of environmental and economic damage but also as a potential source of income.
IC Regimen: Delaying Resistance to Lorlatinib in ALK Driven Cancers Using Repurposed Itraconazole and Cilostazol
Authors: KAST RICHARD E.
Published: June 2024

This paper presents data supporting the IC Regimen for potentiating the effectiveness of lorlatinib in treating ALK positive cancers, and specifically non-small cell lung cancer. Lorlatinib is an effective treatment for ALK driven non-small cell lung cancer and other ALK driven cancers. Lorlatinib inhibits ALK kinase and achieves good brain tissue levels, a common site for metastases in lung cancers. However, resistance to lorlatinib usually supervenes and the cancer awakens and starts growing again, resistant to lorlatinib. This paper analyses data indicating that adding two common generic drugs, itraconazole and cilostazol, to lorlatinib treatment may delay resistance development. Itraconazole is marketed worldwide as a generic antifungal drug that also inhibits Hedgehog signaling, CYP3A4, and the p-gp efflux pump. Cilostazol is a generic anti-thrombosis, phosphodiesterase 3 inhibiting drug that carries minimal bleeding risk. Cilostazol may enhance lorlatinib by deprivation of trophic growth factors supplied by platelets. Itraconazole may enhance lorlatinib effectiveness by reducing or stopping a Hedgehog centered amplifying feedback loop with ALK kinase. The combination of metastatic non-small cell lung cancer being a low-survival disease and the general safety itraconazole plus cilostazol augmentation, make a clinical trial of this trio worthwhile.
The Driving Force of Natural Selection: Maximizing Entropy Production Rates
Authors: Wang Linbo
Published: June 2024

Although evolutionary theory has yet to furnish a comprehensive rationale for the underlying mechanism of natural selection, it is pertinent to note that the phenomenon transcends the confines of biological systems, exhibiting analogous patterns in physical systems as well. Specifically, isolated and closed systems tend to evolve towards states of progressively increasing entropy. In scenarios where multiple paths for entropy increase are accessible, such systems tend to favor combinations of paths that exhibit the most rapid entropy increase rates. Among the various processes in nature, life activities constitute a salient means of achieving entropy increase. Genetic variation within organisms generates individuals that vary in their rates of entropy increase. As these organisms interact, compete and combine, they form diverse combinations of entropy-increasing pathways. Nature, in turn, selects among these combinations, favoring those that culminate in the fastest entropy increase, thereby propelling the evolution of life. Essentially, the evolution of life is an ongoing exploration of diverse combinations of pathways that maximize entropy increase across various energy pools. Amidst continuous genetic variation and the selective pressure imposed by nature for maximum entropy production rates, information accumulates, leading to a corresponding acceleration in the rate of entropy increase. This natural selection, which favors maximizing the entropy at the fastest possible rate, serves as the ultimate driving force for the origin and evolution of life.
Results of Tendon Transfers in Radial Nerve Palsies: A New Evaluation Protocol
Authors: Reina Micaela , Odella Simonetta , Magnani Mauro , Locatelli Francesco , Clemente Alice , Macrì Martina , Tos Pierluigi
Published: June 2024

Radial nerve palsies present a challenging clinical scenario, often leading to substantial functional impairment. This study focuses on evaluating the outcomes of tendon transfer surgeries in patients with post-traumatic radial nerve injuries. The radial nerve, vital for upper limb movements, faces various etiologies such as trauma, compression, or idiopathy. Patients with radial nerve palsy encounter difficulties in daily activities, emphasizing the need for effective management strategies. The research introduces a novel evaluation protocol, aiming to comprehensively assess tendon transfer outcomes. This protocol incorporates functional movements of wrist and finger joints, encompassing both objective and subjective parameters. The retrospective study includes eleven patients treated between 2010 and 2022, with a minimum follow-up of one year post-surgery. Tendon transfers demonstrated positive results. The evaluation protocol covers a wide range of parameters, including wrist and finger mobility, thumb function, grip strength, and patient satisfaction. The results indicate successful restoration of motor function, with an average grip strength of 70% compared to the healthy arm. The proposed evaluation protocol facilitates standardized and reproducible assessment, minimizing subjective errors in clinical evaluations. Despite the study's limitations, such as a relatively small sample size, the findings underscore the effectiveness of tendon transfers in treating radial nerve palsies. The introduced evaluation scheme provides a comprehensive and reproducible approach to assess outcomes, contributing to the global standardization of tendon transfer assessments in radial nerve injuries.
Optimization of Quartz Sand Enhanced Coagulation for Sewage Treatment by Response Surface Methodology
Authors: Zhang Zhengan , Li Yepu , Liu Yongzhi , Li Yuying , Wang Zonghua , Wang Dayang , Yan Lu , Zhao Jiayin , Li B. Larry
Published: June 2024

In the process of sewage coagulation treatment, quartz sand is often used as a heavy medium to accelerate the settling rate of flocs, but it will adversely affect the removal efficiency of pollutants. The factors that affect the coagulation effect and can be controlled manually include the quartz sand dosage, coagulant dosage, sewage pH, stirring time, settling time, etc, their reasonable setting is critical to. This paper was to study the optimal conditions of quartz sand enhanced coagulation(QSEC), first, single-factor tests were conducted to preliminarily explore the optimal range of influencing factors, and then response surface methodology（RSM）tests were performed to accurately determine the optimums of significant factors. The results showed that the addition of quartz sand can’t improve the water quality of coagulation treatment, but it can significantly accelerate the coagulation settlement process, the quartz sand dosage, the coagulant dosage and sewage pH all impacted significantly on its coagulation effect, and existed inflection points. A model that could guide QSEC was obtained by RSM tests. The model optimization and experimental validation showed that the optimal QSEC conditions for treating domestic sewage were as follows: the polyaluminum chloride(PAC) dosage, cationic polyacrylamide(CPAM) dosage, the sewage pH, quartz sand dosage, stirring time and settling time were 0.97 g·L-1, 2.25 mg·L-1, 7.22, 2 g·L-1, 5 minutes and 30 minutes, respectively, and the turbidity of treated sewage was reduced to 1.15 NTU.
Risk Assessment of Compound Dry-Hot events for Maize in Liaoning Province
Authors: Wang Rui , Zhang Xiaoxuan , Cong Longpeng , Wang Yilin , Bai Xiaotian
Published: June 2024

Extreme climates such as droughts and hot extremes, may result in marked damage to crop yields and threaten regional and global food security. Maize is a major grain crop in Liaoning Province, severely affected by drought and hot events. The objective of this study is to advance an approach to estimate the risk of crop yield reduction under the compound dry-hot events (CDHE) in Liaoning Province. Results show that the ratio of stations experiencing compound dry-hot events during the twelfth leaf and maturity stage tended to increase on the time scale. On a spatial scale, the frequency of compound dry-hot events in central Liaoning Province was relatively low during the whole and various reproductive periods of maize. In addition to the twelfth leaf, western Liaoning Province is prone to compound dry-hot events. The high-risk area for the occurrence of the compound dry-hot events in maize is Chaoyang City, located in the western part of Liaoning Province, and the cities in the low-risk area account for about 64.3% of the total number of cities in Liaoning Province, mainly in the central and northern parts of Liaoning Province. Generally, this study emphasizes focusing on the impacts of compound dry-hot events on agricultural production and provides an index to assess the risk of compound dry-hot events on maize production.
Uncovering Financial Performance and Efficiency: A Glimpse into Indonesia's State-Owned Enterprises (SOEs) Construction Industry Debt and Financial Risk
Authors: Wibowo Febrianto Arif , Satria Arif , Gaol Sahala Lumban , Indrawan Dikky
Published: June 2024

This study aims to evaluate the financial performance of SOEs in Indonesia and compare it with private companies using financial ratio analysis and efficiency analysis approaches. Four construction sector SOEs were evaluated, and five private companies were compared using financial data from 2015 to 2022. The financial ratio analysis used the Peterson (2013) approach, while the efficiency analysis employed the data envelopment analysis (DEA) approach and the paired t-test. The study results show that the financial ratio performance of state-owned companies is relatively poor, with low profitability, critical liquidity, and a high debt ratio. Debt, as a source of capital in financing construction projects, makes companies face a greater debt risk. This study validates that SOEs have lower efficiency compared to private companies.
Evaluating Coseismic Landslide Susceptibility Following the 2022 Luding Earthquake: A Comparative Analysis of Six Displacement Regression Models Integrating Epicentral and Seismogenic Fault Distances within the Permanent-Displacement Framework
Authors: Liu Tianhao , Zang Mingdong , Peng Jianbing , Xu Chong
Published: June 2024

Coseismic landslides have the potential to cause catastrophic disasters. Thus, it is of crucial importance to conduct a comprehensive regional assessment of susceptibility to coseismic landslides. This study rigorously interprets 13,759 coseismic landslides triggered by the 2022 Luding earthquake within the seismic zone. Employing the Newmark method, we systematically assess the susceptibility to coseismic landslides through the application of six distinct displacement regression models. The efficacy of these models is validated against the actual landslide inventory using the area under the curve. A hazard map of coseismic landslides is generated based on the displacement regression model with the highest degree of fit. The results show that Moxi Town, Detuo Town, the flanks of the Daduhe River, Wandonghe River, Hailuogou River, and Yanzigou River are high susceptibility areas for coseismic landslides. The study explores factors influencing model fit, revealing that the inclusion of both epicentral distance and the distance to seismogenic fault and in displacement prediction enhances model performance. Nevertheless, in close proximity to fault zones, the distance to seismogenic fault exerts a more significant influence on the spatial distribution density of coseismic landslides compared to the epicentral distance. Conversely, in regions situated further from fault zones, the epicentral distance has a greater impact on the spatial distribution density of coseismic landslides compared to the distance to seismogenic fault. These findings contribute to a nuanced understanding of coseismic landslide susceptibility and offer valuable insights for future Newmark method-based coseismic landslide displacement calculations.
A Review of the Metaverse and Its Implications for Urban Environments: Ethical, Social, and Economic Considerations
Authors: Tiwari Alok
Published: June 2024

The present study provided a comprehensive overview of the current state of research on the Urban Metaverse, focusing on its integration into urban planning and design, as well as the ethical, social, and economic implications in urban settings. This study aims to evaluate the present standing and scope of the metaverse in the context of urban planning and city design; investigate the obstacles and remedies in integrating metaverse components into urban spaces; and explore the ethical, social, and economic ramifications of the metaverse in urban settings. The methodology involved a qualitative investigation of the relevant literature using academic databases and a review of thirty-two selected studies published between 2022 and 2024. The findings emphasise the changing nature of interpersonal relationships, potential alienation from physical spaces, and ethical implications of technology-driven urban changes. The study also highlights the potential opportunities and challenges associated with incorporating the metaverse into urban environments and offers strategies to address these challenges, including the formulation of data protection regulations, expansion of infrastructure, and ensuring equal access for all residents. The implications of the findings underscore the necessity of regulatory frameworks, technological investments, ethical considerations, and inclusive governance structures to ensure inclusive and sustainable urban development in the emerging era of the metaverse.
Entropy Generation Analysis for Combustible Third Grade Fluid Flow through a Slant Channel
Authors: Thosago Kgomotshwana Frans , Rundora Lazarus , Adesanya Samuel Olumide
Published: June 2024

This paper addresses the mixed convective flow and heat transfer in combustible third grade fluid through a slant channel that is filled with a permeable materials. The fluid layer in contact with the lower plate is exposed to convective heating with the ambient while at the upper plate, a constant heat flux is experienced. We employ the spectral quasilinearisation method (SQLM) to the coupled nonlinear flow governing equations. Fluid velocity and temperature profiles, local entropy generation and irreversibility ratio are computed and analysed quantitatively and qualitatively. A residual error analysis demonstrated high accuracy and convergence of the numerical method. The results on flow and thermal effects, entropy generation rate and Bejan number revealed fascinating manifestations that have profound implications in design of thermo-mechanical systems. In particular, the results of the thermal analysis are pertinent to optimal designs of systems that achieve efficient energy utilization.
Validity of Current Smartwatches for Triathlon Training: How Accurate Are Heart Rate, Distance, and Swimming Readings?
Authors: Jacko Tobias , Bartsch Julia , von Diecken Carlo , Ueberschär Olaf
Published: June 2024

Smartwatches are one of the most relevant fitness trends of the past two decades, and they collect increasing amounts of health and movement data. The accuracy of these data may be questionable and requires further investigation. Therefore, the aim of the present study is to validate smartwatches for use in triathlon training. Ten different smartwatches were tested for accuracy in measuring heart rate, distance (via global navigation satellite systems, GNSS), swim stroke rates and the number of swim laps in a 50 m Olympic-size pool. The optical heart rate measurement function of each smartwatch was compared to that of a chest strap. Thirty participants (15 females, 15 males) ran five 3-minute intervals on a motorised treadmill to evaluate the accuracy of the heart rate measurements. Moreover, for each smartwatch, running und cycling distance tracking was tested over six runs of 4,000 m on a 400 m tartan stadium track, six hilly outdoor runs over 3.4 km, and four repetitions of a 36.8 km road bike course, respectively. Three swimming protocols ranging from 200 m to 400 m were performed in triplicate in a 50 m Olympic-size pool, evaluating tracked distance and detected number of strokes. The mean absolute percentage errors (MAPEs) for the average heart rate measurements varied between 3.1% and 8.3%, with the coefficient of determination ranging from 0.22 to 0.79. MAPE results ranged from 0.8% to 12.1% for the 4,000 m run on the 400 m track, from 0.2% to 7.5% for the 3.4 km outdoor run, and from 0.0% to 4.2% for the 36.8 km bike ride. For the swimming tests, in contrast, the deviations from the true distance varied greatly, starting at a 0.0% MAPE for the 400 m freestyle and reaching 91.7% for the 200 m medley with style changes every 25 m. In summary, for some of the smartwatches, the measurement results deviated substantially from the true values. Measurements taken while road cycling over longer distances with only a few curves were in relative terms more accurate than for outdoor runs and even more accurate than for the 400 m track. In the swimming exercises, the accuracy of the measured distances was severely deteriorated by the medley changes among the majority of the smartwatches. Altogether, the results of this study should help in assessing the accuracy and thus suitability of smartwatches for general triathlon training.
Low Frequency Raman Spectroscopy on Amorphous Poly(Ether Ether Ketone) (PEEK)
Authors: Numata Tomoko , Ishikawa Naomoto , Shimada Toshihiro , Gordon Keith C , Yamaguchi Makoto
Published: June 2024

Low-frequency peaks in the Raman spectra of amorphous poly (ether ketone) (PEEK) are investigated. An amorphous sample with zero crystallinity, as confirmed by WAXRD, was used in this study. In a previous study, two peaks were observed in the low-frequency Raman spectra of crystallized samples. One of the peaks at 135 cm-1, disappeared for the amorphous sample. Furthermore, the peak at 50 cm-1 was observed for the first time in the crystallized sample. The peak at 50 cm-1, similar to the peak at 135 cm-1, disappeared in the amorphous state, and its intensity increased with increasing crystallinity. The origins of the two peaks were both associated with the Ph-CO-Ph-type intermolecular vibrational modes in the simulation. It was suggested that the Ph-CO-Ph vibrational mode observed in the low-frequency region of PEEK was strongly in-fluenced by the intermolecular order.
Analysis of the Uplink Spectral Characteristics Deploying IRS in 6G Multi-tier Network
Authors: Mahbub Mobasshir , Shubair Raed M.
Published: June 2024

The study employed simulation-based measurement approaches to evaluate and compare the performance of conventional networks to IRS-enhanced systems in terms of upstream spectral efficiency. The study discovered that applying IRS greatly improves coverage, or transmitting potency, for 6G services.
Advancements in the Application of CO2 Capture and 2 Utilization Technologies—a Comprehensive Review
Authors: Nwabueze Queendarlyn Adaobi , Leggett Smith
Published: June 2024

Addressing escalating energy demands and greenhouse gas emissions in the oil and gas industry has driven extensive efforts in carbon capture and utilization (CCU), focusing on power plants and industrial facilities. Utilizing CO2 as a primary feedstock for industrial fuels and petrochemical materials offers a favorable alternative to sequestration, with byproducts substituting traditional chemical feedstocks. This comprehensive review explores the current landscape of CO2 capture technologies, examining opportunities, economic viability, and efficiency challenges. It provides a detailed analysis of various CO2 utilization methods and the combined process of capture and utilization. The review highlights primary obstacles in planning, production, and widespread implementation, emphasizing the need for strategic integration of materials research, process performance, and cost-effectiveness to advance new technologies.
A Practical Roadmap to Learning from Demonstration for Robotic Manipulators in Manufacturing
Authors: Barekatain Alireza , Habibi Hamed , Voos Holger
Published: June 2024

This paper provides a structured and practical roadmap for practitioners to integrate Learning from Demonstration (LfD) into manufacturing tasks, with a specific focus on industrial manipulators. Motivated by the paradigm shift from mass production to mass customization, it is crucial to have an easy-to-follow roadmap for practitioners with moderate expertise, to transform existing robotic processes to customizable LfD-based solutions. To realize this transformation, we devise the key questions of "What to Demonstrate", "How to Demonstrate", "How to Learn", and "How to Refine".
To follow through these questions, our comprehensive guide offers a questionnaire-style approach, highlighting key steps from problem definition to solution refinement. The paper equips both researchers and industry professionals with actionable insights to deploy LfD-based solutions effectively. By tailoring the refinement criteria to manufacturing settings, the paper addresses related challenges and strategies for enhancing LfD performance in manufacturing contexts.
Rapid Response to the Legalization of Fentanyl Test Strips in Alabama: An Academic–Community Partnership
Authors: McCollum C. Greer , Ventrelli Greg , Gagnon Kelly W. , Loftis Ashley , Famurewa Abimbola , Wimberly Carie , Eaton Ellen
Published: June 2024

In June 2022, Alabama legalized fentanyl test strips (FTS). In response to this new opportunity to prevent overdoses, Project Linkage, Education, and Prevention (LEAP)—an academic–community partnership providing substance use prevention services—quickly purchased FTS and started distributing them in the Birmingham area. We describe how the Addiction Prevention Coalition, a substance use education and harm reduction provider, distributed 7300 FTS in the first year of legalization via Project LEAP and discuss its efforts to decrease substance use among young people. ( Am J Public Health. 2024;114(8):785–788. https://doi.org/10.2105/AJPH.2024.307681 )
Engaging School Champions in the Implementation of a Research Study in Historically Marginalized School Communities
Authors: Kenworthy LaMarca Tara , Campez-Pardo Mileini , Sauvigné Katheryn C. , Guevara Gabriela , Fleurime Rose May , Pulgaron Elizabeth R.
Published: June 2024

Community engagement in research improves uptake of health interventions and health outcomes among marginalized populations. Researchers from school-based health centers serving marginalized communities in Miami, Florida fostered community engagement in COVID-19 research and health education through collaboration with school staff and student “champions” from June 2021 to June 2023. Evaluations completed by champions assessed acceptability, feasibility, and recommendations for improvements. Overall satisfaction was high among champions. We elaborate on lessons learned and future directions for this type of research collaboration. ( Am J Public Health. 2024;114(8):789–793. https://doi.org/10.2105/AJPH.2024.307711 )
Conversion Birmingham Hip Resurfacing in Managing Post-traumatic Arthritis With Retained Femoral Hardware
Authors: Khan Shujaa T. , Pasqualini Ignacio , Mesko Nathan , McLaughlin John , Brooks Peter J. , Piuzzi Nicolas S.
Published: June 2024

Case:

A 70-year-old man with a year-long history of arthritic pain in his left hip presented to our clinic. He had a left intertrochanteric hip fracture 6 years ago, fixed with an open reduction internal fixation with a cephalomedullary nail. He underwent a conversion Birmingham Hip Resurfacing (BHR) with removal of the proximal helicoidal blade and retention of the intramedullary nail. At 7-year follow-up, the patient reported satisfactory clinical outcomes and excellent radiographic fixation.

Conclusion:

This case highlights using conversion BHR in patients with post-traumatic arthritis with retained femoral hardware as an alternative to conventional total hip arthroplasty.
Innovative Service Quality Boosts Patient Satisfaction
Authors: Firdaus Muhammad Zaqqi Zamroni , Cahyana Atikha Sidhi
Published: June 2024

This study examines factors affecting service quality, patient satisfaction, and loyalty at Puskesmas XYZ, using Structural Equation Modeling (SEM) on data from 108 respondents. The results pinpoint doctor-patient interaction as crucial for service quality (loading factor 0.732), satisfaction (0.692), and loyalty (0.758). Suggestions include improving queue management, proposing a web-based system for efficiency. Future research can expand service quality variables for broader impact assessment.
 
Highlight: 

Key Findings: Doctor interaction highly impacts patient loyalty and satisfaction.
Recommendation: Implement web-based queue management for improved healthcare service.
Future Research: Expand service quality variables for a broader patient assessment.

 
 
Keyword:  Service Quality, Patient Satisfaction, Loyalty, Structural Equation Modeling (SEM), Queue Management
BP neural network construction cost prediction model based on different optimization algorithms
Authors: Liu Qian , Yang Shujuan , Yu Dehu , Gai Tongtong
Published: June 2024

Aiming at the complexity of prefabricated construction project input cost estimation and the subjectivity and limitation of manual estimation, a method of cost prediction based on BP neural network is proposed. In this paper, 144 sets of assembled engineering data are selected and collected. By using the mapping relationship between construction cost and 11 cost impact indicators, the prediction results are compared and analyzed after training and prediction. The results show that BP neural network can effectively predict cost, but the convergence is slow and the fitting effect is not good. In this paper, three algorithms, Adam, SGD and Adadelta, are proposed to optimize the BP neural network respectively, and the prediction results are compared and analyzed. The maximum error of SGD-BP neural network prediction model is 6.56% and the minimum error is 0.91%, the maximum error of Adadelta-BP neural network prediction model is 17.10% and the minimum error is 0.82%, the Adam-BP neural network prediction model has a maximum error of 3.89% and a minimum error of 0.11%. From the error analysis, it can be seen that the prediction results of Adam-BP neural network prediction model are more accurate, with good generalization effect, providing more accurate assembly building construction cost reference data for decision makers to judge the feasibility of the project.
Prediction Model For Digital Image Tampering Using Customized Deep Neural Network Techniques
Authors: Saxena Sachin , Singh Archana , Tiwari Shailesh
Published: June 2024

Image tampering detection is a critical area of research, given the widespread use of manipulated images for deceptive purposes. Convolutional Neural Networks (CNNs) have shown significant potential in automating the identification of tampered images. This paper presents customized deep learning model to detect tampering class with comparative analysis of CNN architectures - ResNet50V2, InceptionNetV3, MobileNetV2, and the proposed CNN, for image tampering detection. The proposed approach encompasses a dataset comprising four distinct classes: copy-move, inpaint, splicing, and normal images. This study sheds light on the comparative strengths and weaknesses of these CNN architectures. The dataset encompasses the key tampered classes, offering a holistic assessment of each model's ability to identify various tampering techniques. The custom CNN architecture is specifically tailored for this task, aiming to evaluate its efficiency compared to the established CNNs. Metrics for training and evaluation are standardized to generate equitable comparisons, encompassing performance indicators such as accuracy, precision, recall, and F1-score.This research contributes the knowledge in the field of image tampering detection, offering a comprehensive evaluation of multiple CNN architectures. Additionally, the effectiveness of separable convolutional layers is explored in deep neural networks, showcasing their potential to enhance scalability and effectiveness across various tasks in machine learning and computer vision. The proposed model, designed with separable convolution layers, exhibits superior validation accuracy and training accuracy compared to the other models under evaluation. Notably, The proposed customized model achieved an impressive F1 score of 96%, highlighting its proficiency in accurately detecting tampered regions within images while minimizing false positives.
Harnessing Chemical Space Neural Networks to Systematically Annotate GPCR ligands
Authors: Jensen Emil , Hansson Frederik , Madsen Niklas Gesmar , Hansen Lea , Jakočiūnas Tadas , Lengger Bettina , Keasling Jay , Jensen Michael , Acevedo-Rocha Carlos
Published: June 2024

Drug-target interaction (DTI) databases comprise millions of manually curated data points, yet there are missed opportunities for repurposing established interaction networks to infer DTIs. To address this gap, we first collected DTIs on 128 unique G protein-coupled receptors across 187K molecules to establish an all-vs-all chemical space network. We next developed a chemical space neural network (CSNN), which operates on the graph structure of chemical space rather than on the graphs of compounds, to infer drug bioactivity classes with up to 98% accuracy. We combined this virtual library screen with a cost-efficient experimental platform to validate our predictions and discovered 14 novel DTIs in the process. Altogether, our platform integrates virtual library screening and experimental validation for fast and efficient coverage of missing DTIs.
Adaptive food price forecasts enhance public information during rapid economic changes
Authors: MacLachlan Matthew , Adjemian Michael , Etienne Xiaoli , Sweitzer Megan , Volpe Richard , Zeng Wendy
Published: June 2024

The advent of COVID-19 ended an era of stable US retail food prices that followed the world food price crisis of 2010-2012. Pandemic-related disruptions, avian influenza outbreaks, and the Russia-Ukraine war drove 2022 food-at-home inflation to its highest rate since 1974 (11.4%). In 2023, US Department of Agriculture (USDA) economists responded to these changes by updating food price forecasts with statistical learning protocols to select time-series models and prediction intervals to convey their uncertainty. We characterise the public good provided by these "adaptive" inflation forecasts and enhance them by continuously selecting exogenous variables, improving their precision and explanatory power. The all-items-less-food-and-energy ("core") index helps predict food prices until 2017; then, the money supply, wholesale-food prices, and food service wages help generate optimal forecasts. The strong relationships between food prices and other prices and the money supply indicate the sensitivity of food markets to macroeconomic forces and government policy choices.
Emerging Interest in Science during Early Childhood Period and Evaluating its Effectiveness
Authors: ASL Sowmya , R Neela Rani
Published: June 2024

The present study focused on fostering interest in science among underprivileged children belonging to government early childhood education centres in Telangana state, India. The research initiated with the development of seven science experiments, designing science kits for conducting these experiments, and training the teachers on how to conduct the experiments. When teachers conducted the science experiments with children aged 4 to 6 years, videos were carefully recorded. Video analysis was done through the Behavioural Observation Research Interactive Software (BORIS). For each experiment, ethogram was set with different behaviour codes, selected children as focal subjects, and extracted the data from the software. The results revealed that children showed keen interest in learning science experiments. They acquired basic science concepts and improved their vocabulary. Children not only gained hands-on experience but also nurtured intellectual curiosity and a scientific temper. This research also emphasized the significance of introducing science during the early years of childhood.
Cardiovascular health metrics and diabetic nephropathy: a nationally representative cross-sectional study
Authors: Mai Yanpei , Yan Si , Gong Liya
Published: June 2024

Background:
The pathogenesis of diabetic nephropathy is well-documented to be multifactorial. However, research available on the association between cardiovascular health and diabetic nephropathy is limited. Thus, this study aimed to investigate these potential associations and provide guidance for disease prevention.
Methods:
We applied Life's Essential 8 (LE8) identified by the American Heart Association, which integrates multiple health behaviors and health factors to measure cardiovascular health. This study covered 4,207 adults with diabetes from the National Health and Nutrition Examination Survey spanning 2007–2018. Weighted regression models assessed the estimated effect of LE8 score on the prevalence of diabetic nephropathy as well as their corresponding clinical indicators. Weighted restricted cubic spline models discussed the possible nonlinear dose-response relationships further. Subgroup analyses clarified the effects of other covariates on correlations.
Results:
After adjusting for all covariates, participants with moderate or high cardiovascular health showed a decreased prevalence of diabetic nephropathy (odds ratio [OR]:0.52; 95% confidence interval [CI]:0.42 ~ 0.63), and also a decrease in the urinary albumin-to-creatinine-ratio [UACR] (β:-0.83; 95% CI:-1.00~-0.65). The prevalence of diabetic nephropathy and the level of UACR tended to decrease linearly as the total LE8 score increased (P for nonlinear > 0.05). Subgroup analyses showed that the effects of increased overall LE8 score and the specific cardiovascular health construct varied across age and obesity strata.
Conclusions:
Elevated overall LE8 score was significantly associated with a lower prevalence of diabetic nephropathy in U.S. adults, and the effects of the specific cardiovascular health construct on diabetic nephropathy and their corresponding clinical indicators varied. In all, maintaining good cardiovascular health by refining LE8 metrics may help reduce the adverse effects.
Effect of In situ CO2 Mixing of Cement Paste on the Leachability of Hexavalent Chromium (Cr(VI))
Authors: Cho Kian , Kim Wonkyung , Moon Juhyuk , Cha Daniel , Park Junboum
Published: June 2024

In situ CO2 mixing technology is a potential technology for permanently sequestering CO2 during concrete manufacturing processes. Although it has been approved as a promising carbon capture and utilisation (CCU) method, its effect on the leachability of heavy metals from cementitious compounds has not yet been studied. This study focuses on the effect of in situ CO2 mixing of cement paste on the leaching of hexavalent chromium (Cr(VI)). The tank leaching test of the CO2 mixing cement specimen resulted in a Cr(VI) cumulative leaching of 0.614 mg/m2 in 28 d, which is ten times lower than that of the control mixing specimens. The results in thermogravimetric analysis indicated that a relatively significant amount of CrO42- is immobilised as CaCrO4 during the CO2-mixing, and a higher Cr-O extension is observed in the Fourier transform infrared spectra. Furthermore, a portion of the monocarboaluminate is inferred from microstructural analyses to incorporate CrO42- ions. These results demonstrate that in situ CO2 mixing is beneficial not only in reducing CO2 emissions, but also in controlling the leaching of toxic substances.
Influence of bacterial infection on human sperm
Authors: Sadeek Yousry Khalaf , Abdelghany Tarek , Gadel-Rab Aii Gamal , Mohamed Eman Hassan
Published: June 2024

Background
Invasion of bacteria in to the male reproductive system associated with decrease sperm function, leading to impair fertilizing ability, the human body harbors trillions of microbes, and their influence on human health has been explored in many parts of the human body, there is a general agreement on the negative impact of some pathogenic bacterial species on semen parameters, including sperm counts, motility, morphology, and sperm Deoxyribonucleic acid (DNA) integrity. The Aim of this study was to evaluate the impacts of microbial infection on human sperm parameters and sperm functions. This work included 186 semen specimen from sub fertile men unselected couples consulting infertility clinic center. All semen samples examined bacteriologically, also semen and sperm quality, evaluated according to world Health organization guideline (WHO,2010).
Results
from the 186 patients investigated for infertility, 65 (34.94%) of studied semen specimens were infected with bacteria of different species. The bacterial strains were identified as Enterococcus Fecails, staphylococcus haemolyticyus, Escherichia coli, Micrococcus lylae and Serratia Marcescens. Infected semen sub fertile men had negative impact on sperm quality (count, motility, sperm progressive, vitality and normality. Moreover, high Reactive oxygen species (ROS) with decrease sperm function which include Acrosin activity (A.A) and Hypo-osmotic swelling test (HOST) were noticed in infected sub fertile men in comparison to non-infected sub fertile men but non-significant.
Conclusion
Infected semen has negative impact on sperm parameters and sperm function this lead to impair fertilizing ability of human sperm.
Processing Feature Recognition Based on Improved YOLOv5 Algorithm
Authors: Miao Liqin , Li Jialong , Feng Xin , Tang Zhengwei , Liang Huaidan
Published: June 2024

Processing feature recognition technology can effectively integrate CAD and CAPP systems, thus realizing the effective interoperability of design information and manufacturing information. Classical processing feature recognition technology does not have the ability to learn, recognition efficiency is low and the accuracy of the recognition results can not be guaranteed, while the deep neural network technology not only has the ability to learn, and noise resistance can improve the accuracy of the recognition, therefore, the proposed deep learning-based processing feature classification and recognition technology, the use of multi-angle downscaling to capture the processing features of the processing features of the image method to create a processing feature dataset, and the deep neural network model through the YOLOv5 improved deep neural network model to train the dataset, and use the machining feature classifier to classify the processed part model and output the machining feature results. The machining feature recognition process is verified with typical parts as an example by combining with UG platform, which provides a new idea for machining feature recognition technology.
Methods to characterize Microplastics: Case study on freshwater fishes from a tropical lagoon in Colombia
Authors: Rojas-Luna René A. , Oquendo-Ruiz Luisa , GARCÍA-ALZATE CARLOS A , Arana Victoria A. , García-Alzate Roberto , Trilleras Jorge
Published: June 2024

We studied the prevalence, abundance and physical and chemical characteristics of microplastics (MPs) in fishes in the Luruaco lagoon, Colombia. Four samplings were carried out where fish were captured with trawl nets. Each individual was assessed for total weight, total and standard length, and then a uroventral cut was made to extract stomach and intestine (GIT). Each structure was weighed, measured and deposited in glass jars with filtered KOH solution. The abundance of MPs and frequency of occurrence were assessed. A principal component analysis (PCA) was used to describe the variation of the species dataset (%FO, proportion of MPs and their diet). Seven species were recorded and 271 individuals examined: Microplastics were identified in all species, and 1157 particles were found in their GIT, with a prevalence of 87.5% of MPs. Mugil liza and Andinoacara latifrons had the highest proportion of MPs. The highest %FO was found in cichlid species. Four typologies and 13 colors of MPs were analyzed; fibers and color blue were predominant. A direct relationship was observed between the type of diet and the proportion and %FO of MPs.