bluuebunny/crossref_metadata_2025 huggingface dataset:
Assesing the knowledge, perception, and attitude of wildlife management students toward biodiversity conservation in Nigeria
Authors: Ajayi Omolola O. , Coker Oluwakayode M. , Agbon Zion
Published: January 2024

Despite intensified media campaigns and heightened emphasis on classroom instruction, recent international research has reported that young people are still failing to acknowledge biodiversity conservation as an issue of high priority. This study assessed students' knowledge, perception, and attitude toward biodiversity conservation in three Federal Universities offering Wildlife Management course in Southwestern Nigeria. A total of 159 respondents (15% sampling intensity) were surveyed using a structured questionnaire between July and December 2021. The findings revealed that most students had low knowledge of biodiversity conservation. This result is quite shocking given that they were enrolled in wildlife management courses. On the other hand, they had favorable attitudes and perceptions. The result further revealed that students in University of Ibadan had better attitude and perception. We concluded that there is a need to develop and teach programs and curricula that encourage and sustain the interests of wildlife students in biodiversity conservation.
Surveying the Effects of Aging a High C-Containing Co-Based Superalloy From the As-Cast and Solution Heat-Treated Conditions
Authors: Moffat James P. , Christofidou Katerina A. , Pek Ming En , Jones Nicholas G. , Jackson Paul , Stone Howard J.
Published: January 2024

The microstructure of the high carbon-containing cobalt-based superalloy, Co-101, has been studied in the as-cast state and following a variety of heat treatments. In the as-cast state both M7C3 and Mo-rich M23C6 carbides were observed in the interdendritic regions. After thermal exposure at temperatures between 1000 °C and 1250 °C for 1, 10, and 100 hours, the M7C3 interdendritic carbide network was observed to transform into a Mo-lean M23C6 carbide. These changes were rationalized with thermodynamic calculations. The carbide transformation liberated carbide-forming elements that resulted in the precipitation of intragranular carbides in the dendritic regions at temperatures below 1150 °C. These carbides in the cast-aged material preferentially formed at the dendrite peripheries early during exposure, leading to wide particle size distributions. Peak hardness in the cast-aged material was attained within the first 10 hours of exposure and softening was observed thereafter. After solution heat treating at 1250 °C for 10 hours, the microstructure of Co-101 comprised an M23C6 interdendritic carbide network and solid solution dendrites supersaturated with carbide-forming elements. Subsequent aging of this microstructure for 100 hours at 900 °C led to a high number density and narrow particle size distribution of intragranular carbides. The characteristics of these carbides in the solution-aged material resulted in greater hardness, which was retained for longer durations of exposure, than the cast-aged specimens.
Stein’s identities and the related topics: an instructive explanation on shrinkage, characterization, normal approximation and goodness-of-fit
Authors: Kubokawa Tatsuya
Published: January 2024

The Stein-type identities are widely recognized for their substantial utility and potency in deriving shrinkage estimators improving on crude estimators in normal, gamma, Poisson, and negative binomial distributions. Additionally, these identities serve to characterize these distributions themselves. The Stein identities are also used to demonstrate normal approximation. Moreover, they are instrumental in constructing statistical tests to assess the goodness-of-fit for normality, exponentiality, and Poissonity of distributions. This article offers an instructive and comprehensive explanation of the applications of Stein-type identities in the aforementioned contexts.
Investigation of thermomagnetic convective flow in vertical layers between water and kerosene based magnetic fluids
Authors: Rahman Md. Habibur , Hossain Md. Rakib , Mondal Sushmita , Rahman Hasibur
Published: January 2024

In this article, the convective flow in a vertical layer subjected to a consistent magnetic field with nonzero gravity condition is investigated. One side of the vertical walls is heated, while the opposite side is cooling. The magnetic field strength, field orientation angle, magnetization effect, and thermal deviation of vertical walls play important roles as controlling parameters on the flow stabilization. The goal of this investigation is to analyze the flow characteristics and find out the significant distinction between water and kerosene based magnetic fluids under the variation of thermal and magnetic effects. The numerical results are obtained by the pseudo-spectral Chebyshev expansion method. The properties of all instability modes caused by three major mechanisms, namely; thermomagnetic, thermogravitational and magneto-gravitational are analyzed. In the normal magnetic field, the wave speed responds faster, and it is recognized by a relatively small wave number in water based fluid than that in kerosene based fluid. In oblique magnetic field, the waves propagate faster in both kerosene and water based fluids with the field inclination angle increases, but they still propagate slower in kerosene based fluid comparatively in water based fluid. According to the linear or non-linear magnetization law, both upward and downward propagating waves in kerosene based fluid propagate slower, and they are recognized by greater wave numbers than that in water based fluid. It is found that the basic flow in water based fluid is much more stable than in kerosene based fluid.
Perspective/Commentary: The Transformation of STEMI Care with Thrombolysis in Paramedicine
Authors: Maria Sonja Jane
Published: January 2024

The integration of thrombolysis into paramedicine practice has brought about a significant paradigm shift in the treatment and prognosis of patients with STEMI (ST-Elevation Myocardial Infarction). This innovative approach has led to a notable increase in patient survival rates, demonstrating its effectiveness. A crucial aspect of this transformative change is the noteworthy reduction in “door-to-needle” time, a critical benchmark in STEMI management. As we delve deeper into examining this shift, it becomes increasingly evident that its impact extends beyond the immediate and convenient on-scene medical intervention. Instead, it fundamentally alters the trajectory of patient outcomes, highlighting the evolving role of paramedicine within the realm of medical care.
The Euclidean Programme
Authors: Paseau A. C. , Wrigley Wesley
Published: January 2024

The Euclidean Programme embodies a traditional sort of epistemological foundationalism, according to which knowledge – especially mathematical knowledge – is obtained by deduction from self-evident axioms or first principles. Epistemologists have examined foundationalism extensively, but neglected its historically dominant Euclidean form. By contrast, this book offers a detailed examination of Euclidean foundationalism, which, following Lakatos, the authors call the Euclidean Programme. The book rationally reconstructs the programme's key principles, showing it to be an epistemological interpretation of the axiomatic method. It then compares the reconstructed programme with select historical sources: Euclid's Elements, Aristotle's Posterior Analytics, Descartes's Discourse on Method, Pascal's On the Geometric Mind and a twentieth-century account of axiomatisation. The second half of the book philosophically assesses the programme, exploring whether various areas of contemporary mathematics conform to it. The book concludes by outlining a replacement for the Euclidean Programme.
Is central line type an independent risk factor of central line-associated bloodstream infection in a neonatal intensive care unit population? Experiences at a pediatric hospital in South Texas
Authors: Durant Danielle J. , Fallwell Nancy , Martinez Lesley , Guerrazzi-Young Claudia
Published: January 2024

Background:

Central line-associated bloodstream infection (CLABSI) causes significant harm in neonatal intensive care unit (NICU) patients. However, data regarding risk factors and prevention strategies for CLABSI in NICU patients is limited.

Objective:

To examine risk factors for CLABSI in a NICU population, with particular interest in central line type and site placement.

Design:

Retrospective case–control study.

Setting:

NICU (Level IV, 67 bed) at a pediatric hospital in South Texas.

Participants:

All central line insertions and subsequent CLABSI cases were extracted from the EHR for NICU admissions occurring from January 1, 2018, to November 3, 2022 (N= 1,356), along with potential CLABSI risk factors.

Methods:

Central line insertions resulting in CLABSI (N= 35) were compared to instances without CLABSI (N= 1,321) using bivariate and multivariate analysis, with propensity score matching.

Results:

Multivariate risk factors include implantable device (odds ratio [OR] = 14.5,P< .001), neck site placement (OR = 7.2,P< .001), and device dwell time (OR = 5.6,P= .001), as well as years 2021 (OR = 5.1,P= .017) and 2022 (OR = 5.9,P= .011). This indicates the odds of contracting CLABSI are 14.5 times higher when an implantable central line is used compared to the reference category (PICC devices). When cases are paired with matched controls, likelihood of CLABSI is 7.1% higher in patients with an implantable device than in similar patients with other central lines (p= 0.034).

Conclusions:

Implantable central lines are an independent risk factor for CLABSI in NICU patients at this facility.
A qualitative study evaluating barriers and enablers to improving antimicrobial use for the management of bacteriuria in hospitalized adults
Authors: Black Emily K. , MacLean Dianne , Bell Madison , Neville Heather L. , Kits Olga , Ramsey Tasha D. , Sketris Ingrid , Johnston Lynn
Published: January 2024

Objective:

The objective of this study was to explore barriers and enablers to improving the management of bacteriuria in hospitalized adults.

Design:

Qualitative study.

Setting:

Nova Scotia, Canada.

Participants:

Nurses, physicians, and pharmacists involved in the assessment, diagnosis, and treatment of bacteriuria in hospitalized patients.

Methods:

Focus groups (FGs) were completed between May and July 2019. FG discussions were facilitated using an interview guide that consisted of open-ended questions coded to the theoretical domains framework (TDF) v2. Discussions were transcribed verbatim then independently coded to the TDFv2 by two members of the research team and compared. Thematic analysis was used to identify themes.

Results:

Thirty-three healthcare providers from five hospitals participated (15 pharmacists, 11 nurses, and 7 physicians). The use of antibiotics for the treatment of asymptomatic bacteriuria (ASB) was the main issue identified. Subthemes that related to management of ASB included: “diagnostic uncertainty,” difficulty “ignoring positive urine cultures,” “organizational challenges,” and “how people learn.” Barriers and/or enablers to improving the management of bacteriuria were mapped to 12 theoretical domains within these subthemes. Barriers and enablers identified by participants that were most extensively discussed related to the domains of environmental context and resources, belief about capabilities, social/professional role and identity, and social influences.

Conclusions:

Healthcare providers highlighted barriers and recognized enablers that may improve delivery of care to patients with bacteriuria. A wide range of barriers at the individual and organization level to address diagnostic challenges and improve workload should be considered to improve management of bacteriuria.
The rationale and recommendations for inclusion of screening for benign paroxysmal positional vertigo in falls clinics
Authors: Metz Dean , Bryce Kate
Published: January 2024

Background

There have been many studies linking falls and benign paroxysmal positional vertigo. This article collates those studies, and demonstrates how a community falls service fast-tracked patients with benign paroxysmal positional vertigo by implementing validated screening tools and recognised guidance.

Objective

This study aimed to explore whether routine screening of referrals to a community falls service can identify those with benign paroxysmal positional vertigo, for fast-tracked management.

Methods

Patients referred to a community falls service were screened for possible benign paroxysmal positional vertigo using the Dizziness Handicap Inventory, and triaged to a physiotherapy-led falls and benign paroxysmal positional vertigo assessment service.

Results

Twenty-five per cent of patients were fast-tracked to a falls and benign paroxysmal positional vertigo assessment service for management. The community falls service waiting list reduced by 25 per cent.

Conclusion

The data support incorporating assessment and treatment of benign paroxysmal positional vertigo into routine practice within all falls services.
Changes in United States Summer Temperatures Revealed by Explainable Neural Networks
Authors: Labe Zachary M. , Johnson Nathaniel C. , Delworth Thomas L.
Published: January 2024

To better understand the regional changes in summertime temperatures across the conterminous United States (CONUS), we adopt a recently developed machine learning framework that can be used to reveal the timing of emergence of forced climate signals from the noise of internal climate variability. Specifically, we train an artificial neural network (ANN) on seasonally averaged temperatures across the CONUS and then task the ANN to output the year associated with an individual map. In order to correctly identify the year, the ANN must therefore learn time‐evolving patterns of climate change amidst the noise of internal climate variability. The ANNs are first trained and tested on data from large ensembles and then evaluated using observations from a station‐based data set. To understand how the ANN is making its predictions, we leverage a collection of ad hoc feature attribution methods from explainable artificial intelligence (XAI). We find that anthropogenic signals in seasonal mean minimum temperature have emerged by the early 2000s for the CONUS, which occurred earliest in the Eastern United States. While our observational timing of emergence estimates are not as sensitive to the spatial resolution of the training data, we find a notable improvement in ANN skill using a higher resolution climate model, especially for its early twentieth century predictions. Composites of XAI maps reveal that this improvement is linked to temperatures around higher topography. We find that increases in spatial resolution of the ANN training data may yield benefits for machine learning applications in climate science.
Ocean Mixing in a Shelf Sea Driven by Energetic Internal Waves
Authors: Whitwell C. A. , Jones N. L. , Ivey G. N. , Rosevear M. G. , Rayson M. D.
Published: January 2024

Internal waves drive ocean mixing and enhance the transport of heat, momentum and other tracers in shelf seas. We collected observations of mixing over a 30‐day period from three cross‐shore moorings placed on the 330, 200 and 150 m isobaths on the offshore side of a pelagic ridge on the Australian North West Shelf. The region is forced by energetic surface and internal tides, exhibits non‐linear internal waves, experiences flow‐topography interactions, and is subject to episodic intense wind events. This complex forcing drove energetic diapycnal mixing at all sites. We identified five dominant internal wave forcing categories: mode‐1 waves at low‐frequency (time scales from double the buoyancy period to 4 hr), mode‐1 waves at high‐frequency (HF) (time scales between the buoyancy period and double the buoyancy period), mode‐2 waves, internal bores, and internal hydraulic jumps. Overall, just 15% of mixing events accounted for 90% of the total observed heat flux over the record. Mixing during internal wave events accounted for as much as 50% of the total heat flux in some locations. Of the internal wave categories, HF mode‐1 waves were the most significant contributors to the total heat flux at all sites (∼20%). On the other hand, internal bores made significant contributions to mixing only at the 200 and 150 m moorings; they made no contribution to mixing at the 330 m mooring. At the shallowest mooring, the different internal wave categories all made similar contributions to the total flux, indicating an increasingly complicated relationship between the evolving internal wavefield and the mixing.
Forecasting of Global Ionosphere Maps With Multi‐Day Lead Time Using Transformer‐Based Neural Networks
Authors: Shih Chung‐Yu , Lin Cissi Ying‐tsen , Lin Shu‐Yu , Yeh Cheng‐Hung , Huang Yu‐Ming , Hwang Feng‐Nan , Chang Chia‐Hui
Published: January 2024

Ionospheric total electron content (TEC) is a key indicator of the space environment. Geophysical forcing from above and below drives its spatial and temporal variations. A full understanding of physical and chemical principles, available and well‐representable driving inputs, and capable computational power are required for physical models to reproduce simulations that agree with observations, which may be challenging at times. Recently, data‐driven approaches, such as deep learning, have therefore surged as means for TEC prediction. Owing to the fact that the geophysical world possesses a sequential nature in time and space, Transformer architectures are proposed and evaluated for sequence‐to‐sequence TEC predictions in this study. We discuss the impacts of time lengths of choice during the training process and analyze what the neural network has learned regarding the data sets. Our results suggest that 12‐layer, 128‐hidden‐unit Transformer architectures sufficiently provide multi‐step global TEC predictions for 48 hr with an overall root‐mean‐square error (RMSE) of ∼1.8 TECU. The hourly variation of RMSE increases from 0.6 TECU to about 2.0 TECU during the prediction time frame.
Incorporating longitudinal history of risk factors into atherosclerotic cardiovascular disease risk prediction using deep learning
Authors: Yu Jingzhi , Yang Xiaoyun , Deng Yu , Krefman Amy E. , Pool Lindsay R. , Zhao Lihui , Mi Xinlei , Ning Hongyan , Wilkins John , Lloyd-Jones Donald M. , Petito Lucia C. , Allen Norrina B.
Published: January 2024

It is increasingly clear that longitudinal risk factor levels and trajectories are related to risk for atherosclerotic cardiovascular disease (ASCVD) above and beyond single measures. Currently used in clinical care, the Pooled Cohort Equations (PCE) are based on regression methods that predict ASCVD risk based on cross-sectional risk factor levels. Deep learning (DL) models have been developed to incorporate longitudinal data for risk prediction but its benefit for ASCVD risk prediction relative to the traditional Pooled Cohort Equations (PCE) remain unknown. Our study included 15,565 participants from four cardiovascular disease cohorts free of baseline ASCVD who were followed for adjudicated ASCVD. Ten-year ASCVD risk was calculated in the training set using our benchmark, the PCE, and a longitudinal DL model, Dynamic-DeepHit. Predictors included those incorporated in the PCE: sex, race, age, total cholesterol, high density lipid cholesterol, systolic and diastolic blood pressure, diabetes, hypertension treatment and smoking. The discrimination and calibration performance of the two models were evaluated in an overall hold-out testing dataset. Of the 15,565 participants in our dataset, 2170 (13.9%) developed ASCVD. The performance of the longitudinal DL model that incorporated 8 years of longitudinal risk factor data improved upon that of the PCE [AUROC: 0.815 (CI 0.782–0.844) vs 0.792 (CI 0.760–0.825)] and the net reclassification index was 0.385. The brier score for the DL model was 0.0514 compared with 0.0542 in the PCE. Incorporating longitudinal risk factors in ASCVD risk prediction using DL can improve model discrimination and calibration.
Method for multi-task learning fusion network traffic classification to address small sample labels
Authors: Liu Lan , Yu Yongjie , Wu Yafeng , Hui Zhanfa , Lin Jun , Hu Junhan
Published: January 2024

In the context of the proliferated evolution of network service types and the expeditious augmentation of network resource deployment, the requisition for copious labeled datasets to facilitate superior performance in traffic classification methods, particularly those hinging on deep learning, is imperative. Nonetheless, the procurement and annotation of such extensive datasets necessitate considerable temporal and human resource investments. In response to this predicament, this work introduces a methodology, termed MTEFU, leveraging a deep learning model-based multi-task learning algorithm, strategically designed to mitigate the reliance on substantial labeled training samples. Multiple classification tasks, encompassing duration, bandwidth size, and business traffic category, are incorporated, with a shared parameter strategy implemented amongst tasks to assure the transference of information across disparate tasks. Employing CNN, SAE, GRU, and LSTM as multi-task learning classification models, training validation and experimental testing were conducted on the QUIC dataset. A comparative analysis with single-task and ensemble learning methods reveals that, in the context of predicting network traffic types, the accuracy derived from the multi-task learning strategy, even with a mere 150 labeled samples, can emulate the 94.67% accuracy achieved through single-task learning with a fully labeled dataset of 6139 samples.
Prevalence and determinants of hand hygiene behavior among Indian population: a systematic review and meta-analysis
Authors: Hareesh P. V. , Rajkumar Eslavath , Gopi Aswathy , Sri Lakshmi K N. V. , Romate John
Published: January 2024

Despite a global call to action, many deaths occur yearly in developing nations from contagious diseases due to poor sanitation and hygiene. Although hand hygiene (HH) behavior was critical in preventing the COVID-19 pandemic, the sustainability of such practices is still questionable. Therefore, the current systematic review and meta-analysis investigated the prevalence and determinants of HH behavior among the Indian population (PROSPERO registration ID: CRD42022344961). Systematic searches on electronic databases, including ScienceDirect, Scopus, Web of Science, JSTOR, PubMed, and Google Scholar, targeted qualitative and quantitative studies that report HH behaviors in India. Pooled effect sizes were calculated with the inverse-variance method using random-effects models, acknowledging the study heterogeneity. Out of 1053 studies, 15 studies that met eligibility criteria were included in the qualitative synthesis. Among them, five studies were included in the meta-analyses. The overall prevalence of HH before food was 55% (95% CI = 31–78), and after the toilet was 84% (95% CI = 65–96). Subgroup analysis showed that before-food HH prevalence pre- and post-COVID-19 was 61% and 36%, respectively, whereas after-toilet HH prevalence was 91% and 74%, respectively. Meta-regression revealed statistically non-significant results for COVID-19 status. While it could not adequately explain the heterogeneity of the ‘before-food prevalence’ studies (Adj. R2 = − 34.80%), it did account for more than 19% in ‘after-toilet prevalence’ (Adj. R2 = 19.72%). This systematic review highlights various demographic, psychosocial, and environmental determinants of HH behavior. The results offer the potential for a deeper comprehension of the key factors influencing HH in India and could find implications for developing viable interventions. This aids in planning efficient promotional campaigns to enhance personal hygiene and control infectious diseases in the nation.
Comparing automated and manual assessments of tear break-up time using different non-invasive devices and a fluorescein procedure
Authors: Zeri Fabrizio , Rizzo Giulia Carlotta , Ponzini Erika , Tavazzi Silvia
Published: January 2024

To evaluate the agreement and repeatability of an automated topography-based method for non-invasive break-up time (NIBUT) analyses in comparison with two other NIBUT procedures, the fluorescein procedure (fBUT), and with the manual assessment with the same device. In the first experiment, a semi-randomised crossover study was performed on forty-three participants (23.1 ± 2.1 years). NIBUT measurements were collected in a randomised order, in both eyes of participants with EasyTear View + (Easytear, Rovereto), Polaris, and Sirius + (CSO, Firenze). Then a fBUT was collected. The overall measurement procedure was repeated in a further session (retest) on the same day. In a second experiment, a retrospective randomised crossover study was performed on eighty-five NIBUT videos previously recorded by the Sirius+. Two observers assessed manually the videos and the NIBUTs were compared with the automatic ones. In the first experiment, ANOVA showed a significant difference between the four measures in both eyes (p < 0.001). Significant differences were found in the paired comparisons between each NIBUT procedure and fBUT (Wicoxon; p < 0.05). Sirius+ resulted in agreement only with Polaris in the left eye. Correlations between all NIBUT procedures resulted in statistical significance in both eyes. All procedures showed very good test-rest reliability. In the second experiment, a significant correlation between automated and manual NIBUT was found, but also a significant statistical difference between the two measurements, although clinically negligible (0.3 s). The investigated NIBUT devices perform differently from each other (and from fBUT), so they cannot be considered interchangeable. The automated measure of NIBUT with Sirius+ has a negligible clinical difference compared to manual assessment on the same device.
Oral health related quality of life in head and neck cancer survivors within the first year following treatment: a cross-sectional study in Karachi, Pakistan
Authors: Qamar Sana , Rozi Shafquat , Sawani Sobia , Awan Muhammad Sohail , Akhtar Shabbir , Siddiqui Moghira Iqbaluddin , Abbas Syed Akbar , Taimoor Shazia , Raza Khan Farhan
Published: January 2024

After completing treatment for head and neck cancer (HNC), patients often face oral complications like oral pain, limited mouth opening and dry mouth which significantly reduce their oral health related quality of life (OHRQoL). These issues impact their overall well-being, social activities and long-term survival. The primary objective of this study was to evaluate OHRQoL and its association with sociodemographic characteristics, oral hygiene practices and oral clinical parameters such as oral hygiene status and oral mucositis grade in patients who have completed treatment for head and neck cancer. This cross-sectional study involved 79 HNC-treated patients within first year after completion of cancer treatment attending ENT and dental clinics at outpatient department (OPD) setting in Karachi. Data was collected electronically using structured questionnaire comprising of EORTC QLQ H&N – 35 to measure OHRQoL, patients were also examined for oral hygiene status using oral hygiene index- simplified (OHI-s) and oral mucositis grade using WHO oral mucositis scale. Multiple linear regression was used to test OHRQoL associations with the sociodemographic and different clinical factors. The result showed an overall mean score for oral health related quality of life (OHRQoL) of 25.02 ± 15.86 (95% CI 21.46–28.57), with difficulty in mouth opening 53.16 ± 18.88 and dry mouth 45.14 ± 24.48 being predominant concerns for decline in the OHRQoL in the population. Male predilection was observed among participants n = 60 (75.9%), majority of the participants n = 41 (51.9%) were below 52 years of age. n = 63 (80%) participants received radiotherapy alongside surgery and chemotherapy. Most of participants n = 66 (83.5%) experienced moderate to severe oral mucositis with poor oral hygiene status n = 56 (71%). Significant associations were found between OHRQoL and BMI, OH status, marital status, monthly income, gender and fluoride toothpaste (p < 0.05). These findings suggest that Quality of Life (QoL) among HNC treated patients is negatively impacted by their poor oral health, post cancer treatment. Therefore, it is important to evaluate and modify the current treatment modalities and involve multidisciplinary teams, to improve their OHRQoL thereby enhancing overall QoL.
HBV promotes its replication by up-regulating RAD51C gene expression
Authors: Peng Ting-wei , Ma Qing-feng , Li Jie , Wang Xue , Zhang Cong-hui , Ma Junwen , Li Jun-yi , Wang Wei , Zhu Cheng-liang , Liu Xing-hui
Published: January 2024

Chronic hepatitis B virus (HBV) infection is a major cause of hepatocellular carcinoma (HCC), pegylated-interferon-α(PEG-IFNα) and long-term nucleos(t)ide analogs (NUCs) are mainly drugs used to treat HBV infection, but the effectiveness is unsatisfactory in different populations, the exploration of novel therapeutic approaches is necessary. RAD51C is associated with DNA damage repair and plays an important role in the development and progression of tumors. Early cDNA microarray results showed that RAD51C expression was significantly increased in HBV-infected HCC cells, however, the relationship between HBV infection and abnormal expression of RAD51C has not been reported. Therefore, we conducted RT-PCR, western blot, Co-immunoprecipitation(Co-IP), and immunofluorescence(IF) to detect HBV-RAD51C interaction in RAD51C overexpression or interfering HCC cells. Our results showed that RAD51C and HBV X protein(HBX) produced a direct interaction in the nucleus, the HBV infection of HCC cells promoted RAD51C expression, and the increased expression of RAD51C promoted HBV replication. This indicated that RAD51C is closely related to the occurrence and development of HCC caused by HBV infection, and may bring a breakthrough in the the prevention and treatment study of HCC.
Isotropic gap formation, localization, and waveguiding in mesoscale Yukawa-potential amorphous structures
Authors: Sarihan Murat Can , Govdeli Alperen , Lan Zhihao , Yilmaz Yildirim Batuhan , Erdil Mertcan , Wang Yupei , Aras Mehmet Sirin , Yanik Cenk , Panoiu Nicolae Coriolan , Wong Chee Wei , Kocaman Serdar
Published: January 2024

Amorphous photonic structures are mesoscopic optical structures described by electrical permittivity distributions with underlying spatial randomness. They offer a unique platform for studying a broad set of electromagnetic phenomena, including transverse Anderson localization, enhanced wave transport, and suppressed diffusion in random media. Despite this, at a more practical level, there is insufficient work on both understanding the nature of optical transport and the conditions conducive to vector-wave localization in these planar structures, as well as their potential applications to photonic nanodevices. In this study, we fill this gap by investigating experimentally and theoretically the characteristics of optical transport in a class of amorphous photonic structures and by demonstrating their use to some basic waveguiding nanostructures. We demonstrate that these 2-D structures have unique isotropic and asymmetric band gaps for in-plane propagation, controlled from first principles by varying the scattering strength and whose properties are elucidated by establishing an analogy between photon and carrier transport in amorphous semiconductors. We further observe Urbach band tails in these random structures and uncover their relation to frequency- and disorder-dependent Anderson-like localized modes through the modified Ioffe-Regel criterion and their mean free path - localization length character. Finally, we illustrate that our amorphous structures can serve as a versatile platform in which photonic devices such as disorder-localized waveguides can be readily implemented.
Metal–organic framework-based atmospheric water harvesting for enhanced photovoltaic efficiency and sustainability
Authors: Alezi Dalal , Li Renyuan , Alsadun Norah , Malik Arijit , Shekhah Osama , Wang Peng , Eddaoudi Mohamed
Published: January 2024

The global demand for photovoltaic (PV) cooling is projected to increase over the coming years, driven by the growing adoption of solar energy and the need to improve the efficiency and performance of PV systems.
In situ investigation of controlled polymorphism in mechanochemistry at elevated temperature
Authors: Linberg Kevin , Sander Philipp C. , Emmerling Franziska , Michalchuk Adam A. L.
Published: January 2024

Through thermo-mechanochemical conditions it is possible to generate metastable crystal forms below equilibrium thermodynamic transition temperatures, making thermo-mechanical conditions an exciting new direction for solid form control.
Recent advances in all-solid-state batteries for commercialization
Authors: Sung Junghwan , Heo Junyoung , Kim Dong-Hee , Jo Seongho , Ha Yoon-Cheol , Kim Doohun , Ahn Seongki , Park Jun-Woo
Published: January 2024

Challenges in the commercialization of all solid-state and next-generation batteries including strategies, key points, and application of solid-state batteries.
Investigation of the nanostructure and reactivity of soot particulates from diesel/methanol dual-fuel combustion with and without EGR
Authors: Chen Hao , Ji Zhenhua , Wang Xiaochen , Pan Mingzhang , Yi Chengshan , Zhang Peng
Published: January 2024

Independently of the methanol substitutions, introducing EGR for diesel/methanol dual-fuel combustion lowers soot oxidation reactivity and this trend is highly linked with the more ordered nanostructure.
Indigenous Bacteria Diversity of Fermetodege Based on Molecular Analysis The Next Generation Sequencing (NGS)
Authors: Isnawati  , Muhaimin Fitriari Izzatunnisa
Published: January 2024

Fermetodege was fermented feed that was developed by researchers which is proven to increase the biomass and semen quality of ruminant livestock. The raw material for making this fermented feed were cellulose-rich materials, so this fermented feed contains many kinds of cellulolytic bacteria.The objective of this study was to reveal the diversity of indigenous bacteria in a fermented feed is called Fermetodege. Fermetodege is made from fermented water hyacinth (Eichhornia crassipes), corn (Zea mays) cobs and rice (Oryza sativa) bran. This mixture is rich in cellulose and a good source of cellulolitic bacterial isolates. The cellulolitic bacteria is source of cellulase enzyme. Revealing of bacterial diversity is carried out through a series of procedures which include making a fermetodege, fermenting it and taking samples in the mesophilic I, thermophilic, mesophilic II and maturing phase. The bacterial community in the feed was dominated by groups (from the most to the least), namely Bacilli, Clostridia, Gammaproteobacteria, Bacteroidia, Negativicutes, Actinobacteria and Desulvovibrionia, Alfaproteobacteria and Coriobacteria. Based on the NGS results, it was found that there were 9 groups of bacterial communities in the fermented feed.
Phylogenetic Relationship of Indigenous Bacteria Fermetodege based on Next-Generation Sequencing (NGS) Molecular Analysis
Authors: Izzatunnisa Muhaimin Fitriari , Isnawati
Published: January 2024

The objective of this study was to reveal the phylogenetic relationship of indigenous bacteria in a fermented feed called Fermetodege made from fermented water hyacinth (Eichhornia crassipes), corn (Zea mays) cobs and rice (Oryza sativa) bran using a phylogenetic tree. This mixture is rich in cellulose and a good source of cellulolytic bacterial isolates. Phylogenetic trees can provide important information, including the evolutionary processes, the similarity of characters, and their bio prospects. To establish the phylogenetic relationship of indigenous bacteria, fermetodege was made through a series of procedures. Afterwards, molecular analysis was carried out using NGS. Based on UPGMA analysis, there were ten definphylaylum and oindefiniteite groups. The phylum includes Firmicutes, Bacteroidota, Proteobacteria, Actinobacteriota, Desulfobacteriota, Cyanobacteria, Chloroflexi, Campilobacteriota, Acidobacteriota, and Synergistota. It was found that Proteobacteria are closely related to Actinobacteriota, which are more closely related to Firmicutes than Bacteroidota. The main characteristic of bacteria in each phase of the fermentation process is their optimum growth temperature. The optimum growth temperature in the mesophilic phase I, II and ripening phase is around 30-50 oC. Meanwhile, bacteria in the thermophilic phase grow well at temperatures around 70 oC. In addition, another characteristic of these bacterial species is its ability to degrade cellulose.
Biological Aspects of Yellowfin Tuna in Bone Gulf Waters, Indonesia
Authors: Jalil  , Mallawa Achmar , Amir Faisal , Safruddin  , Pangabean Donwill
Published: January 2024

The aim of this study was to examine the composition, growth patterns and condition factors of yellowfin tuna caught in Bone Gulf waters. Sample collection was carried out in July – November 2018 at two stations, i.e., station 1 in Cimpu Luwu Regency and station 2 at the Lonrae Fish Landing Site, Bone Regency. At station 1, 10,366 individuals were caught, with an average size of 81.19 cm in length and of 14.43 kg in weight. Station 2 had a larger average size, i.e., 97.14 cm in length and 27.79 kg in weight. The results of the analysis of tuna growth patterns at station 1 and station 2 showed a value of b < 3, indicating negative allometric growth. This means that the weight gain of the species was slower than its length gain. The average value of the condition factor was 1.03±0.25 for station 1 and 1.07±43 for station 2. These values varied according to temporal variation and fish size.
Shelf oceanography and small pelagic fishes in the Java Sea
Authors: Apriansyah  , Atmadipoera Agus S. , Nugroho Dwiyoga , Noviyanti Rinda
Published: January 2024

The optimization of small pelagic fisheries in the Java Sea could be enhanced by providing oceanographic information for analysis and determining potential fishing grounds. This study aims to investigate shelf oceanographic factors influencing small pelagic fisheries using multidatasets of sea surface temperature and surface salinity CROCO ocean model output (2010 – 2020), distribution of light-fishing vessel position of VIIRS satellite, and small pelagic fish catches landing data (round scads Decapterus spp. and the spotted sardinella Amblygaster sirm) at Pekalongan Fishing Port, Central Java. The results showed that the peak of fishing season for the spotted sardinella occurs during northwest monsoon, in which the eastward monsoon current and Sunda shelf throughflow brings fresher (±32.4 psu) and warmer (±28.5 oC) water into the Java Sea. In contrast, the peak of fishing season for round scads. is associated with saltier (>33.0 psu) and cooler (<28.5 °C) water supplied by the westward monsoon current and Makassar ITF during the southeast monsoon. Alternating intensification of monsoonal current along the northern Java and the southern Kalimantan coast during different monsoon periods is associated with a higher abundance of neritic and oceanic small pelagic fishes, respectively.
The Spatio-Temporal of NO2Density Weighting in The Region of Malang, East Java Province, Indonesia
Authors: Pamungkas Guntur Bagus , Kurniawati Aynunnisaa , Iskandar Cut Marcella
Published: January 2024

The paper aimed to present the spatio-temporal of NO2Density Weighting during the period April 2022 – March 2023 (1 year) with weighting model in The Region of Malang, East Java Province, Indonesia. It is based on the remote sensing data of Sentinel-5p provided by ESA Copernicus Product. The data have been processed into the following indicators: low, small, and intermediate of NO2density weighting. During the analysed period, low weight has continuously no constant, so that in the month of November 2022 there are mostly 3470.11 ha in Malang Region Area of which in this region part are raised about 95.83 %. Intermediate weight has significant reduction from 2926.96 ha in the month of July 2022 to 929.39 ha in the month of March 2023, therefore health plant increased considering the reduced area of NO2. As a conclusion, The Region of Malang is very closely developed commercial household, industrial processed, and energy production. Therefore, the Malang Region Government needs to be firm regarding the cultivation of protected areas such as green open space with various types of plant in it. In addition, the local government is also expected to always control industrial activities both on a factory and home scale.
Traditional Mangrove Management in Langensari Village, Subang, West Java: A Study on the Practice of Integrating Mangroves into Polyculture Ponds
Authors: Tri Hewindati Yuni , Novi Kusumaningrum Elizabeth
Published: January 2024

This study aimed to explore the integration of mangroves into a polyculture system involving various fish species, including milkfish (Chanos chanos), tilapia (Oreochromis mossambicus), and tiger shrimp (Penaeus monodon) in Langensari, Subang, West Java and assess water quality and analyze heavy metal content in mangrove root sediments. Observations were conducted at two observation stations, namely: Station1, in a residential pond (ST-1) and Station-2 in the estuary area (ST-2). Water quality and heavy metal content taken from root sediments were measured using AA-7000, Shimadzu® atomic absorption spectrophotometer (AAS). At Station-1 (ST-1), three dominant mangrove species were found, namely R. stylosa, A. marina, and B. gymnorhiza. While in ST-2, A. marina and S. caseolaris were found. Water quality parameters, Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), pH, and heavy metals Cu, Cd, and Pb were conducted to assess the effectiveness of the roots’ ability to precipitate pollutants. Water quality test results showed that A. marina roots were more effective at precipitating heavy metals than R. stylosa roots in both locations. A. marina showed higher levels of Cu, Cd, and Pb than R. stylosa.
Formulation of Cookies with Substitution of Fish Cork (Channa Striata) and Moringa (Moringa Oleifera) Flour as Foods Functional Protein Wealthy
Authors: Sopandi Roby Muhamad , Hakiki Dini Nur
Published: January 2024

This research aims to develop cookies with fish meal supplementation cork and moringa flour for protein-wealthy functional food. The formulations of cookies with percentage variations, namely in F1 (70% wheat flour: 30% cork fish flour), F2 (60% wheat flour: 40% cork fish meal), F3 (50% wheat flour: 50% cork fish meal). All the treatment using the addition of 2.5% moringa flour. The analysis is protein, fat, moisture content, ash, and crude fibre. The data was analysed using One-Way ANOVA and a differential test using Duncan’s Post Hoc. The result showed cork fish substitution significantly affect protein, water content, and carbohydrate. The organoleptic test combination 70% what flour and 30% cork fish meal high acceptance in texture and taste. The best combination was cookies F3 with 50% wheat flour and 50% cork fish meal that have 17.40±0.06% protein content; 15.47±0.02 fat; 2.28±0.23 water content; 1.54±0.04 ash; 63.31 carbohydrate, and 1,96±0,03% crude fibre.
Development Model of Cloud Computing Adoption for Industrial 4.0 Implementation Strategy for Improve MSMEs Performance
Authors: Syairudin Bambang , Nabila Aditia Ayu Rahma
Published: January 2024

Presently, the adoption of digital technology among Indonesian MSMEs is rather minimal, standing at around 12.5%. A cloud computing service provides SMEs with an inexpensive option by offering self-service, broad network access, flexibility, resource sharing, and pay-as-you-go, all of which can enhance corporate performance. The realization of the cloud computing adoption strategy requires a comprehensive model to achieve its values. This study aims to explore the beliefs and intents of MSMEs regarding the factors that influence the adoption of cloud computing. Additionally, it seeks to examine the correlation between cloud computing usage and business performance. This study used a random sampling technique of 60 MSMEs data from questionnaires analysed using the PLSSEM method. The results of the hypothesis test indicate that factors such as knowledge acquisition and sharing, perceived usefulness, ease of use, risk, and cost do not have a significant impact on behavioural intention. Meanwhile, behavioural intention significantly affects cloud computing adoption, affecting performance by improving productivity and flexibility. The implication of the results can be a recommendation for increasing the implementation of cloud computing adoption in MSMEs.
Review of Nielsen versus SMART in Heuristic Evaluation of Online Transportation Application
Authors: Firmansyah Frans , Riskinanto Anggar
Published: January 2024

The increase in the number of users of online transportation applications is accompanied by a high number of complaints regarding usability issues. Meanwhile, there is the SMART method beside Nielsen’s method for heuristic evaluation that provides more emphasis on mobile application. The purpose of the research is to determine the fittest method in the heuristic evaluation of one of the online transportation applications in Indonesia. The research used a comparative study approach by comparing the number of obtained usability issues from Nielsen’s method and the SMART method. The evaluation process involved three usability experts who identify the usability issues in two types of frameworks, which are Nielsen’s and SMART. The findings of this study indicate that the SMART method discovers a higher number of issues around 7.7% (not significant) compared to the Nielsen method. The SMART method is also able to identify more issues across severity levels 2, 3, and 4. Based on these results, the SMART method is considered may be fitter than Nielsen’s method in evaluating online transportation applications in Indonesia. The research is expected to serve as a reference for conducting evaluations on mobile devices in Indonesia.
Unveiling the Potential of Artificial Intelligence in Digital Marketing for Universitas Terbuka
Authors: Kharis Selly Anastassia Amellia , Zili Arman Haqqi Anna , Putri Agustiani , Robiansyah Anton
Published: January 2024

The rapid advancement of digital technology and artificial intelligence (AI) moving at an incredibly fast pace. AI have revolutionized various industries and the field of marketing is no exception. This study aims to explore the potential advantages of utilizing AI in the digital marketing strategies of Universitas Terbuka. The study explores the personalization, predictive analytics, sentiment analysis, segmentation and targeting using AI in digital marketing of Universitas Terbuka. Universitas Terbuka can gain valuable insights into student preferences, behaviours, trends to create digital marketing strategies efficiently. Based on the trends in Google search engine over a year, the peak of searched the most for Universitas Terbuka on Google were North Kalimantan, Bengkulu, Bangka Belitung, Papua, and East Kalimantan. The cities that searched the most for Universitas Terbuka on Google were Bontang, Tarakan, Pangkal Pinang, Cibinong, and Balikpapan. Embracing AI-driven approaches can enhance student engagement, improve marketing effectiveness, and ultimately fulfill the university’s mission of providing accessible and high-quality education to learners from all walks of life.