bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetic mapping and comparative analysis of heading date in hexaploid oat
Authors: Ubert Itacir P. , Nava Itamar Cristiano 
Published: August 2024

Abstract

Heading date is a critical stage in the growth and development of oats. The objectives of this study were to identify DNA markers associated with quantitative trait loci (QTL) affecting heading date in hexaploid oat, and to locate and characterize heading date QTL by comparative analysis using an oat reference genome. Genetic linkage maps were constructed using single nucleotide polymorphism (SNP) markers in RIL lines from oat populations FL0206B-S-B-S1 × UFRGS 078030-1 and URS Taura × Leggett. Days to heading were collected in field trials, and QTLs for heading date were identified in several genomic regions of the two maps. Oat loci with the most significant additive effects were associated with linkage groups Mrg02, Mrg06, and Mrg05 in the FL0206B-S-B-S1 × UFRGS 078030-1 population and with Mrg12, Mrg24, and Mrg11 in the URS Taura × Leggett population. Major QTLs affecting heading date were mapped to locations consistent with known QTLs and candidate genes that play critical roles in regulating flowering. These genes include Hd3a and FT, which are orthologs of the Vrn3 gene and integrate the vernalization and photoperiod response pathways. The gene PRR37 is an ortholog of Ppd1, the main gene determining photoperiod sensitivity in wheat and barley. The COL13 and GI genes are involved in the regulation of flowering by photoperiod. In addition, novel QTLs were identified that are valuable for molecular selection in oat breeding programs aimed at developing new and improved oat cultivars adapted to specific growing conditions.
Transcriptomics-guided optimization of vitamins to enhance erythromycin yield in saccharopolyspora erythraea
Authors: Ke Xiang , Jiang Xing , Wang Shuohan , Tian Xiwei , Chu Ju 
Published: August 2024

Abstract

Comparative transcriptomics uncovered distinct expression patterns of genes associated with cofactor and vitamin metabolism in the high-yielding mutant strain Saccharopolyspora erythraea HL3168 E3, as compared to the wild-type NRRL 2338. An in-depth analysis was conducted on the effects of nine vitamins, and it was determined that TPP, vitamin B2, vitamin B6, vitamin B9, vitamin B12, and hemin are key enhancers in erythromycin production in E3. Then, the Plackett-Burman design and the path of steepest ascent were applied to further optimize the vitamin combination for maximum production efficiency. Otherwise, targeted metabolomics and metabolic flux analysis illuminated how vitamin supplementation modulates the central carbon metabolism with notable effects on the TCA cycle and methionine synthesis to augment the provision of energy and precursors essential for erythromycin synthesis. This work highlights the capacity for precise vitamin supplementation to refine metabolic pathways, thereby boosting erythromycin production, and provides valuable directions for application on an industrial scale.
Manifold Learning with Polynomial Projection on Cat Face Recognition
Authors: Dai Sinong , Xu Hao 
Published: August 2024

Abstract

In recent years, cat face recognition has received more and more attention. As an effective dimensional reduction method, manifold learning can help us better understand and deal with high-dimensional data. In this paper, unsupervised manifold learning based on polynomial projection is introduced for cat face recognition. Firstly, the data matrices are acquired by transforming the processed cat face picture into a matrix. Through the selection of datum points, the information coordinates are obtained which construct the polynomial kernel matrix. Next, after the polynomial projection manifold learning algorithm for cat face is proposed, it is applied to get the low-dimensional representation. Finally, carry out cat face recognition on the Graphical User Interface(GUI) and the recognition accuracy is obtained by computation simulations. Compared with the traditional dimensional reduction method, the presented method can provide a more accurate means to achieve cat face recognition which accomplishes the purpose of helping stray cats to go back home.
Exploring factors influencing the consistent adoption of a post-stroke upper extremity outcome measure using Normalisation Process Theory
Authors: Choo Silvana Xinyi , Yong Joshua , Rafi Shaikh Abdullah Bin Mohamed , Lo Chen Ju , Tong Jun Bin , Lum Elaine , Thumboo Julian 
Published: August 2024

Abstract

Background Stroke rehabilitation guidelines recommend using outcome measures like the Fugl-Myer Assessment (FMA) and the Action Research Arm Test for post-stroke upper extremity function assessment. Despite these recommendations, challenges persist in their integration into everyday clinical practice, highlighting the crucial need to comprehend and implement outcome measurement aligned with evolving healthcare models. Objective Our study aimed to use a theory-based approach to identify the barriers and facilitators to routine use of the FMA for post-stroke upper extremity function among hospital-based occupational therapists. Methods Employing a mixed-method sequential exploratory study design rooted in the Normalisation Process Theory (NPT), we gathered quantitative data through a validated survey followed by qualitative insights analysed with directed content analysis from focus group discussions involving occupational therapists from four hospitals. Results The online survey (n = 34) revealed barriers predominantly associated with NPT constructscollective actionandcoherence. Facilitators were primarily linked to thecognitive participationconstruct. Focus group discussion revealed key barriers including inadequate coaching, competing tasks and priorities, and the perceived limited value of the FMA by therapists. Key facilitators were legitimation of therapists’ role in outcome measurement and an open learning culture. Conclusions Through a theory-based approach, we identified distinct challenges and enablers to routine outcome measurement previously not reported in the literature. Our findings provide insights on designing implementation strategies to embed the use of the FMA into routine practice.
Food Insecurity Risk and Dietary Habits of International Students in the COVID-19 Pandemic Period
Authors: Sözlü Saniye , Esin Kübra , Yassıbaş Emine , Ayyıldız Feride 
Published: August 2024

Abstract

Background
International students are at risk for food insecurity (FI), and it is believed that the COVID-19 pandemic has made this situation even worse.
Objective
This study was conducted to determine the changes in the food insecurity (FI) risk and dietary habits of international students receiving education in Türkiye during the COVID-19 pandemic.
Methods
The data were collected using an online form and included questions on demographic characteristics, socioeconomic status, anthropometric measurements, and dietary habits. The 10-item Adult Food Security Survey Module was used to assess FI.
Results
The sample of the study included 451 international university students aged 18–36 years. The mean FI score of the participants before COVID-19 was 4.8 ± 2.95, and the mean FI score during the COVID-19 period was 5.2 ± 2.86 (p < 0.01). The prevalence of FI prior to contracting COVID-19 was 74.7%, which increased to 81.2% during the pandemic (p < 0.01). The prevalence of FI in participants from Africa (87.3%) was significantly greater than that in those from Asia (77.4%) and Europe (54.6%) (p < 0.05). A greater percentage of participants whose fathers were university graduates had food security (FS) (22.7%) than did those whose fathers were primary school graduates (12.2%), and a greater percentage of participants lived with their friends had FI (86.2%) (p < 0.05). It was determined that the healthy dietary habits of the participants who experienced FI during the COVID-19 pandemic and their habits of consuming red meat, chicken, or fish; milk and dairy products; vegetables; fruits; legumes; cereals; and dried nuts decreased more than did these habits among those with FS (p < 0.01).
Conclusions
FI is highly prevalent among international students studying in Türkiye, and the COVID-19 pandemic has aggravated this situation.
Acceptance Criteria for Defects in Pe Welds, Coupling Phased Array Ultrasonic Testing and Destructive Tests
Authors: Gueugnaut Dominique , Tessier Manuel , Bechrouri Myriam , Lopitaux Aymeric , Soleau pierre 
Published: August 2024

Abstract

As a promising reference technique for non-destructive evaluation of both electrowelded and butt-fused assemblies, Phased Array Ultrasonic Testing (PAUT) is still studied extensively in several laboratories worldwide and is supported by the technical standard ISO TS 16943. During the last ten years, several joint projects have been completed aiming at evaluating the acuity of PAUT applied to both pipes and electrofused assemblies either exhumed from the field or prepared in laboratory. More recently, a focus has been made on fixing some acceptance criteria combining PAUT data and long term resistance of the laboratory joints. This paper presents the updated data obtained on electrofused assemblies − 63 mm saddles and 110 mm sockets – containing different types of defects such as: insufficient heating time, pipe under-penetration in the socket, excessive loaclized scraping, pollutants and calibrated thin strips, in both mass and cross configuration, put at the interface pipe-saddle. PAUT scanning on the different specimens, both during the welding phase and after cooling, confirms the capability of the technique to visualize and size the Heat Affected Zone (HAZ), which can be revealed and compared afterwards on sample sections. Moreover, most of the defects are detected and sized, confirming the fairly good Probability of Detection (POD) of PAUT, except for the smallest strips which are located in non accessible zones, due to the particular design of the saddle. Long term resistance of the welds is then evaluated by Hydrostatic Pressure Tests (HPT) followed by a decohesion test after rupture, according to the requirements of both the ISO 13956 and NF EN 1555 standards. Under such test conditions, every joints comply with the requirements of the standards (rupture time greater than 1,000 hours at 80°C and 5 MPa), even those violating the critical proportions of non-welded zones.
Efficacy of malic and tartaric acid in mitigation of cadmium stress in Spinacia oleracea; Modulations in Physiological and Biochemical Attributes
Authors: Shabbir Ansa , Shah Anis Ali , Usman Sheeraz , Ahmed Shakil , Kaleem Muhammad , Shafique Shiffa , Gatasheh Mansour K. 
Published: August 2024

Abstract

The increasing level of cadmium (Cd) contamination in soil due to the actions of humans is a significant problem. This problem not only harms the natural environment, but it also causes major harm to human health via the food chain. The use of chelating agent is useful strategy to improve the heavy metal. This research aimed to mitigate Cd stress by application of organic acids i.e., malic (MA) and tartaric acid (TA). We evaluated the physiological and biochemical features, growth traits of Spinacia oleracea L. under Cd stress. Soil was treated with 100 µM Cd, as well as two dosages of foliar sprays (100 and 150 µM) of MA and TA were applied. The results of this study revealed that exogenously applied 100 µM Cd significantly reduced root and shoot length as well as fresh and dry weight, leaf number, leaf area, photosynthetic pigments, gas exchange parameters, Soil plant analysis development (SPAD), and increase the antioxidants of S. oleracea. Malic and tartaric acids (100 and 150µM) both at 2 level may lower Cd concentrations while also enhancing nutrient uptake and accumulation in treated plants exposed to the Cd environment. Malic and Tartaric acid both overcome the toxicity caused by Cd stress in S. oleracea. When these organic chelates used they have significant effect on all morphological, physiological and biochemical parameters. These finding also demonstrates that TA and MA, when used together, have the ability to reduce Cd-induced phytotoxicity by reducing Cd uptake and enhancing plant development parameters.
Research on the characteristics of highly-cited papers on pandemics from the perspective of alternative metrology
Authors: Zou Zongfeng , Sun Xi-yun , Nan Lv , Shao Wei , Wu Jingwen 
Published: August 2024

Abstract

[Background] At present, an increasing number of researchers have studied pandemics and published papers to help people better cope with pandemics.
[Purpose/significance] This study explores the value of Altmetrics to facilitate academic responses to pandemics on the web and helps public health organizations design communication strategies through an analysis of the dissemination characteristics of high-cited pandemic papers on social media. To excavate the potential of pandemic papers from the perspective of alternative measurement is also beneficial to more objectively and effectively evaluate the social influence of those papers.
[Method/process] Correlation analysis was carried out between traditional bibliometric indicators and various Altmetrics indicators. We can also more clearly understand the characteristics of academic dissemination on Twitter and Mendeley platforms by using visual analysis and descriptive statistical analysis methods.
[Result/Conclusion] Our findings conclude that online media has become an important tool for disseminating scientific knowledge related to global pandemics. The Altmetric indicators are significantly different from the citation indicator, which can express the impact of the high-cited pandemic papers from a new perspective.In conclusion, Altmetrics will be a perfect supplement to the quantitative evaluation of such papers.
Revealing the biodiversity of wild bees (Hymenoptera: Apoidea: Anthophila) in flower strips in Mediterranean floodplains. Which monitoring method fits best?
Authors: Moldoveanu Oana Catalina , Maggioni Martino , Vergari Daniele , Dani Francesca Romana 
Published: August 2024

Abstract

Context
The ongoing pollinator decline may threaten and compromise the resilience of terrestrial ecosystems. Implementing conservation action requires monitoring pollinator populations' actual status, but this is particularly difficult for pronubes insects such as wild bees. Their monitoring is difficult and time-consuming but crucial for assessing their health status.
Objectives
Here we compared and evaluated the efficiency of three different monitoring methods to evaluate wild bee biodiversity in lowland areas sown with entomophilous flowers to support pollinating insects in a Mediterranean environment.
Methods
We sampled wild bees for two years by using hand netting, pan traps and artificial nests. We compared species richness and abundance among these methods with a particular focus on how flowering coverage affects the efficiency of walking transects and pan traps and discussed the attractiveness of the different colours of pan traps.
Results
Hand netting captured a higher abundance of wild bees than the other two methods but a similar number of species to pan traps. Artificial nests captured fewer specimens and species. Bee assemblages were significantly different between pan traps and hand netting, and pan traps had greater potential in capturing the whole bee biodiversity, but their attractiveness is negatively influenced by the flowering coverage contrary to hand netting sampling.
Conclusions
Like other studies, the three sampling methods are complementary regarding species assemblages. The juxtaposition of several monitoring methods is essential to assess the biodiversity status of species with such particularly different ecological traits.
IoT and Machine Learning Based Techniques for Monitoring and Predicting Water Hyacinth Expansion Rate in Lake Tana Ecosystem
Authors: Amssaya Haileyesus , Mekuria Fisseha , Tegegne Tesfa 
Published: August 2024

Abstract

This paper presents smart IoT networks and machine learning algorithm to monitor the aquatic environment. The growth and expansion of invasive plants in freshwater lakes requires an accurate monitoring and long-term data collection tool, which the system proposed in this paper is addressing. The expansion of invasive weed water hyacinth highly affects the biodiversity and environment of freshwater lakes and rivers. Dynamic and continuous environmental monitoring system increases the prediction accuracy of machine learning algorithms by delivering real time data. Predicting the seasonal and daily water hyacinth weed expansion rate intensity of lake Tana improves the biodiversity of the lake and living standards of the community. Laboratory based experimental data is used to predict the relationship between the intensity of water hyacinth expansion rate and influencing environmental features such as depth, temperature, pH, total nitrogen, total phosphorous and chlorophyl-a contents of lake Tana. Four machine learning techniques namely multivariate linear regression, random forest, support vector machine and extreme gradient boosting algorithms are applied for data analysis. The random forest machine learning algorithm predicts water hyacinth annual expansion rate intensity better than others.
Long-term commitment critical to reach forest restoration’s climate mitigation potential in East Africa
Authors: Liang Mengyu , Minor David , Silva Julie , Fatoyinbo Lola , Thomas Nathan , Goor Wouter van , Riemer Kars , Kigenyi Richard , Cohen Rachel , Negussie Aklilu , Jin Chen , Healey Sean , Cook-Patton Susan , Costedoat Sébastien , Heilmayr Robert , Chazdon Robin , Hansen Matthew , Dubayah Ralph , Urbazaev Mikhail , Durrant Eleanor , de Haas Sander , Duncanson Laura 
Published: August 2024

Abstract

Forest restoration is gaining momentum as a natural climate solution to provide carbon dioxide removal while also addressing the biodiversity crisis. Globally, three primary restoration strategies—natural regeneration, assisted natural regeneration, and active restoration—have been adopted. However, inconsistent monitoring of forest dynamics mean large uncertainties remain over their long-term potential to enhance carbon (C) removal. We examined over 30 years of forest aboveground carbon (AGC) estimates from high-resolution lidar, Landsat imagery, and field data across East Africa. Our study shows that assisted natural regeneration and active restoration outperform natural regeneration in enhancing forest C removal capacity, with long-term implementation (over 9 years) needed to overcome the initial lags in AGC accumulation. Restoring 14.24 million hectares of suitable areas available in East Africa, representing 2.1% of suitable restoration areas globally, could enhance forest C removal by 2.85 ± 0.82 gigatons of C (Gt C) by 2050. However, less than one quarter of this potential would be achieved by 2030. This research advances our understanding of forest restoration’s potential for enhancing C removal and the time scale for meeting climate targets. We demonstrate that long-term commitments in implementation and investment are critical for restoring forests effectively for climate mitigation.
The Role of Weather Forecasts in Climate Adaptation and Reducing Medical Costs in China
Authors: Cong Zhenglong , Liu Qingfeng , Ni Chenxu 
Published: August 2024

Abstract

Exploring cost-effective climate adaptation strategies is crucial for human well-being, yet little is known about whether and how information interventions promote climate adaptation. This paper provides the first analysis of the role of weather forecasts in reducing the health impacts of climate change, utilizing large-scale, fine-grained medical expenditure data from China’s largest medical insurance program. Our analysis reveals accurate forecasts significantly reduce weather-related medical cost: a one-degree Celsius deviation from the accurate forecast increases medical expenses over the next seven days by 13.7% when underestimating and 4.6% when overestimating the realized temperature.Moreover, the potential value of improving forecast accuracy will escalate with ongoing global warming, as the negative impacts of inaccurate forecasts are especially severe under extreme weather conditions. Out findings highlight the substantial potential of information interventions for climate adaptation and enhance understanding of health-related impacts of climate change.
Video-to-Text Pedestrian Monitoring (VTPM): Leveraging Computer Vision and Large Language Models for Privacy-Preserve Pedestrian Activity Monitoring at Intersections
Authors: Abdelrahman Ahmed S. , Abdel-Aty Mohamed , Wang Dongdong 
Published: August 2024

Abstract

Computer vision has advanced research methodologies, enhancing system services across various fields. It is a core component in traffic monitoring systems for improving road safety; however, these monitoring systems don’t preserve the privacy of pedestrians who appear in the videos, potentially revealing their identities. Addressing this issue, our paper introduces Video-to-Text Pedestrian Monitoring (VTPM), which monitors pedestrian movements at intersections and generates real-time textual reports, including traffic signal and weather information. VTPM uses computer vision models for pedestrian detection and tracking, achieving a latency of 0.05 seconds per video frame. Additionally, it detects crossing violations with 90.2% accuracy by incorporating traffic signal data. The proposed framework is equipped with Phi-3 mini-4k to generate real-time textual reports of pedestrian activity while stating safety concerns like crossing violations, conflicts, and the impact of weather on their behavior with latency of 0.33 seconds. To enhance comprehensive analysis of the generated textual reports, Phi-3 medium is fine-tuned for historical analysis of these generated textual reports. This fine-tuning enables more reliable analysis about the pedestrian safety at intersections, effectively detecting patterns and safety critical events. The proposed VTPM offers a more efficient alternative to video footage by using textual reports reducing memory usage, saving up to 253 million percent, eliminating privacy issues, and enabling comprehensive interactive historical analysis.
WITHDRAWN: Macroeconomic Factors Underlying External Currency Instability in Developing Countries: Analysis of the Democratic Republic of Congo (DRC) from 1990 to 2022.
Authors: FATAKI ALEXANDRE DONATIEN 
Published: August 2024

Abstract

This Article aims to investigate the intricate web of macroeconomic factors contributing to external currency instability in developing countries, with a particular focus on the Democratic Republic of Congo (DRC) from 1990 to 2022. Employing the Econometric modeling framework, this research offers a unique perspective by analyzing traditional macroeconomic variables and additional dimensions can be taken into account in order to set up a comprehensive analytical framework. The study seeks to unveil the complex interplay of these factors and their collective impact on the external stability of the currency in the selected timeframe.
A Positive Feedback-Based Body-Driven Transconductance Amplifier
Authors: Akbari Meysam 
Published: August 2024

Abstract

In this paper, an ultralow-power ultralow-voltage CMOS operational transconductance amplifier (OTA) with a rail-to-rail input/output swing is presented. The proposed two-stage OTA is designed based on a body-driven current mirror (CM) amplifier with a Gm-C frequency compensation technique. In addition, a transconductance boosting technique is used to enhance the performance of the input stage structure without adversely affecting the noise performance. Simulation results for 0.18 µm CMOS technology show that the proposed OTA achieves an 86 dB DC gain and a gain bandwidth of 21.9 kHz while driving a 15 pF load. The amplifier consumes 292 nW @ 0.5 V, which makes it suitable for ultralow-power applications.