bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence, Predictors and Outcomes of Feedback for Ems Professionals: a Mixed-methods Diary Study
Authors: Wilson Caitlin , Budworth Luke , Janes Gillian , Lawton Rebecca , Benn Jonathan
Published: March 2024

Background
Providing feedback to healthcare professionals and organisations on performance or patient outcomes may improve care quality and professional development, particularly in Emergency Medical Services (EMS) where professionals make autonomous, complex decisions and current feedback provision is limited. This study aimed to determine the content and outcomes of feedback in EMS by measuring feedback prevalence, identifying predictors of receiving feedback, categorising feedback outcomes and determining predictors of feedback efficacy.
Methods
An observational mixed-methods study was used. EMS professionals delivering face-to-face patient care in the United Kingdom’s National Health Service completed a baseline survey and diary entries between March-August 2022. Diary entries were event-contingent and collected when a participant identified they had received feedback. Self-reported data were collected on feedback frequency, environment, characteristics and outcomes. Feedback environment was measured using the Feedback Environment Scale. Feedback outcomes were categorised using hierarchical cluster analysis. Multilevel logistic regression was used to assess which variables predicted feedback receipt and efficacy. Qualitative data were analysed using content analysis.
Results
299 participants completed baseline surveys and 105 submitted 538 diary entries. 215 (71.9%) participants had received feedback in the last 30 days, with patient outcome feedback the most frequent (n = 149, 42.8%). Feedback format was predominantly verbal (n = 157, 73.0%) and informal (n = 189, 80.4%). Significant predictors for receiving feedback were a paramedic role (aOR 3.04 [1.14, 8.00]), a workplace with a positive feedback-seeking culture (aOR 1.07 [1.04, 1.10]) and white ethnicity (aOR 5.68 [1.01, 29.73]). Diary entries reported feedback as very useful (median 6, IQR 5–7). Feedback outcomes included: personal wellbeing (closure, confidence and job satisfaction), professional development (clinical practice and knowledge) and service outcomes (patient care and patient safety). Feedback-seeking behaviour and higher scores on the Feedback Environment Scale were statistically significant predictors of feedback efficacy. Solicited feedback improved wellbeing (aOR 3.35 [1.68, 6.60]) and professional development (aOR 2.58 [1.10, 5.56]) more than unsolicited feedback.
Conclusion
Feedback for EMS professionals was perceived to improve personal wellbeing, professional development and service outcomes. EMS workplaces need to develop a culture that encourages feedback-seeking to strengthen the impact of feedback for EMS professionals on clinical decision-making and staff wellbeing.
Human-Like Named Entity Recognition with Large Language Models in Unstructured Text-based Electronic Healthcare Records: An Evaluation Study
Authors: Akbasli Izzet Turkalp , Birbilen Ahmet Ziya , Teksam Ozlem
Published: March 2024

Background
The integration of big data and artificial intelligence (AI) in healthcare, particularly through the analysis of electronic health records (EHR), presents significant opportunities for improving diagnostic accuracy and patient outcomes. However, the challenge of processing and accurately labeling vast amounts of unstructured data remains a critical bottleneck, necessitating efficient and reliable solutions. This study investigates the ability of domain specific, fine-tuned large language models (LLMs) to classify unstructured EHR texts with typographical errors through named entity recognition tasks, aiming to improve the efficiency and reliability of supervised learning AI models in healthcare.
Methods
Clinical notes from pediatric emergency room admissions at Hacettepe University İhsan Doğramacı Children's Hospital from 2018 to 2023 were analyzed. The data were preprocessed with open source Python libraries and categorized using a pretrained GPT-3 model, "text-davinci-003," before and after fine-tuning with domain-specific data on respiratory tract infections (RTI). The model's predictions were compared against ground truth labels established by pediatric specialists.
Results
Out of 24,229 patient records classified as "Others ()", 18,879 were identified without typographical errors and confirmed for RTI through filtering methods. The fine-tuned model achieved a 99.96% accuracy, significantly outperforming the pretrained model's 78.54% accuracy in identifying RTI cases among the remaining records. The fine-tuned model demonstrated superior performance metrics across all evaluated aspects compared to the pretrained model.
Conclusions
Fine-tuned LLMs can categorize unstructured EHR data with high accuracy, closely approximating the performance of domain experts. This approach significantly reduces the time and costs associated with manual data labeling, demonstrating the potential to streamline the processing of large-scale healthcare data for AI applications.
Evolution of the chemical composition of fogwater collected at four sites in the Alsace region between 2015 and 2021
Authors: Khoury Dani , Millet Maurice , Jabali Yasmine , Weissenberger Thomas , Delhomme Olivier
Published: March 2024

Four sites representing urban (Strasbourg), suburban (Geispolsheim and Cronenbourg), and rural (Erstein) in the Alsace region, north east of France are sampled to investigate the evolution of the chemical composition of fog water between 2015 and 2021. For this aim, forty-two fog samples are collected using a Caltech Active Strand Cloud Collector (CASCC). The samples are analyzed for their inorganic species (metals and ions) and their physico-chemical properties (pH, dissolved organic carbon (DOC), liquid water content (LWC), and conductivity (K)). Temporal and spatial evolutions have been also investigated between the four sampling sites. Our results are then compared to previous studies performed in 1990’s at Strasbourg. Since 1999, there is a lack of fog knowledge in Strasbourg metropolitan and complete absence of fog studies. That’s why it is interesting to resume fogwater collection in order to re-build a solid background regarding air quality in France, particularly in Alsace, and assess the effectiveness of the rules and regulations that have been implemented over time.
Research on the Dynamic Flexible Support Machining Method for Propeller Blades
Authors: Li Songmo , Wang Rui , Ge Yuhao , Guo Xiangyu , Liu Mengmeng , Zhu Xiaohu
Published: March 2024

At present, most of the propeller machining adopts single-sided machining, and its machining vibration and deformation seriously affect the machining accuracy. To reduce the machining vibration, a dynamic flexible support machining method is proposed, i.e., while the tool is machining, the multi-point flexible support device supports the blade and counteracts the milling force to suppress the vibration and deformation. Due to the complex shape of the blade and the special structure of the support device, the blade is divided into different areas, and a support motion trajectory combining symmetric and asymmetric motions is planned, and then a set of post-processing systems is introduced. After obtaining the tool position points, the support points are solved cyclically by the ergodic method. Subsequently, the support points are interpolated, and the vectors are smoothed to obtain smooth and continuous support trajectories. Finally, the machining parameters are calculated, and the machining data applicable to the XYZ-3RPS hybrid machine are integrated. The feasibility of the proposed support trajectory and post-processing algorithm was ultimately demonstrated through practical machining experiments.
Awareness and use of improved livestock feed technologies among agro-pastoral households in the West African Sahel
Authors: Umutoni clarisse , AYANTUNDE Augustine
Published: March 2024

Seasonal scarcity of quality feed continues to be a bottleneck for agro-pastoralists and is the most important limitation to livestock production in agro-pastoral systems in the West African Sahel. In this regard, diverse promising technologies to increase the production and availability of quality feed have been introduced. Despite the introduction of various feed technologies in the region, the adoption rate by smallholder farmers is very low. The objective of this study was to identify factors affecting the likelihood of using improved livestock feed technologies among agro-pastoral households in two regions of Niger. A logit model was employed using data collected from randomly selected 218 agro-pastoral households between February and April 2023. The study revealed low awareness and use of improved livestock feed technologies among agro-pastoral households. The findings suggested the positive impact of education level, membership of farmer groups and ownership of small ruminant on enhancing the probability of using improved livestock feed technologies. Households’ geographical area was one of the determinant factors in using improved livestock feed technologies. The use of improved livestock feed technologies was also influenced by family size.The study provides guidance to inform strategies by the decision-makers to enhance the utilization of improved livestock feed technologies among agro-pastoral households in the West African Sahel. Suggested strategies may in turn alleviate the current problem of low productivity of livestock, contribute to improving household food security and nutrition among agro-pastoral communities.
Dengue vector specie’s niche distribution modeling over India using the machine learning-based MaxEnt model
Authors: Prasad Peri Hari
Published: March 2024

NTD (Neglected Tropical diseases), such as dengue, will severely impact public health. So, proper measures and preventive steps should be taken to mitigate dengue outbreaks. This is accomplished by predicting dengue hotspots using SDM models. A well-known Maxent (Maximum Entropy) model was employed to forecast the future spread of vectors based on environmental data, including bio-climatic variables. Accuracy evaluation was performed using AUC values. Historical data on the presence of Aedes aegypti and Aedes albopictus were gathered from GBIF.org (1981–2004), along with corresponding climatic data from (https://chelsa-climate.org/). Features were selected through correlation analysis and AUC optimization, and the model was fitted accordingly. Predictions about future distribution were made under three climatic scenarios, namely SSP126, SSP370, and SSP585, derived from CMIP-6 data. There is a significant aegypti vector distribution over India. Meanwhile, albopictus distribution is less severe compared to the aegypti vector. The vector expansion is visible in all three climatic scenarios, especially in northeastern regions such as West Bengal, partial IGP regions like Madhya Pradesh, and all union territories. The model fitted with utmost accuracy in both training and testing. The aegypti accuracy for training and testing are 0.8081 and 0.7658, and similarly for albopictus, 0.8252 and 0.8056. This analysis will give public health experts a vision for planning mitigation strategies. This was only a preliminary analysis based on environmental modeling rather than mechanistic modeling, which may give more insights. However, climate change will profoundly impact VBD (Vector-Borne Diseases).
Empowering Emerging Adults with Type 1 Diabetes: Crafting a Financial and Health Insurance Toolkit through Community-Based Participatory Action Research
Authors: Blanchette Julia E. , Lewis Claudia B. , Shannon Chantel S. , Kanchibhatla Anuhya , Rieke Jorden , Roche Mary Jane , Johnson Dove-Anna , Williams Dionne , Webb Shay , Diaz Crystal N. , Lundgrin Erika L. , Allen Nancy A. , Litchman Michelle L. , Hatipoglu Betul
Published: March 2024

Background: Emerging adults aged 18-30 years face challenges during life transitions, with an added burden of navigating the health care system and additional costs associated with diabetes. This stress is compounded by overall low levels of health insurance literacy in this population, as people may not know about available financial and health care resources to minimize suboptimal diabetes outcomes. This study aimed to tailor a financial and health insurance toolkit to emerging adults with type 1 diabetes, including racially, ethnically diverse, and Medicaid-insured individuals, through community-based participatory action research.
Methods: An academic research team and citizen scientists from a national organization held six online community advisory board (CAB) content-creation meetings to understand how to tailor a financial and health insurance toolkit. The CAB comprised six racially and insurance-diverse emerging adults with type 1 diabetes and four content experts (clinical, financial, and insurance). A deductive thematic qualitative analysis was utilized. Three researchers independently coded the data and then convened to reach group consensus. Two CAB members performed member-checking.
Results: The following key themes emerged to tailor the toolkit: ensuring that content covers empowerment and self-advocacy, including genuine stories and multimedia visuals for aesthetics, addressing clinician bias, acknowledging racial and ethnic disparities in care, incorporating cultural representation, and demystifying Medicaid stigma.
Conclusions: By successfully partnering with the CAB and a community organization through a community-based participatory action research approach, we will develop a financial and health insurance Toolkit tailored to the needs of racially and ethnically diverse and Medicaid-insured emerging adults with type 1 diabetes.
Machine learning reveals the interplay between muscle fatty acids and the gut microbiota: implications for high-quality pork
Authors: Pan Ningfeng , Shi Pengjun , Zhu Qian , Wang Chenyu , Ouyang Qing , Huang Xingguo , Hung Ifen , Liu Chunxue , Xu Kang , Li Yuying , Yang Guan , Yin Yulong , Yin Jie
Published: March 2024

Background
High-quality pork is rich in functional fatty acids such as α-linolenic (ALA), γ-linolenic acid (GLA), docosahexaenoic acid (DHA), and eicosapentaenoic acid (EPA), which are thought to prolong lifespan. Multiple studies have confirmed the role of the gut microbiota in muscle fatty acid deposition in pigs, but the inherent complexity of the microbiota remains poorly understood.
Results
Using a machine learning-based data mining approach, we analyzed a dataset containing meat quality, muscle fatty acids, and gut microbiota from 291 pigs to identify potential predictors of total fatty acid (TFA) and unsaturated fatty acids (UFA) content for high-quality pork with better meat color or marbling score. Microbial α diversity exhibited positive predictive power for muscle polyunsaturated fatty acids (PUFAs), especially for GLA, DHA, and EPA. A core set of two microbial phyla (Actinobacteria and Spirochaetes) and 11 genera extracted from the pig gut microbiome correlated with the level of muscle fatty acids. In addition to the fatty acid degradation pathway, Escherichia was negatively associated with the levels of most fatty acids, including oleic acid, ALA, GLA, and EPA. Positive correlations of GLA, DHA, and EPA depositions in the muscle were shared in two microbial genera (Bradyrhizobium and Lachnoclostridium), which also negatively correlated with the fatty acid degradation pathway.
Conclusions
Overall, we revealed an intricate network of correlations between muscle fatty acids and the gut microbiota, suggesting that there are multiple routes to produce high-quality healthy pork that is rich in functional fatty acids.
Determination of the Temporal-Spatial Distribution Patterns of Ancient Heritage Sites in China and their Influencing Factors via GIS
Authors: Li Xiaojia
Published: March 2024

Exploring the temporal and spatial distribution as well as the influencing factors of ancient archaeological sites can illuminate the developmental trajectory of human civilization, aiding in the comprehension of the geographical environment, resource distribution, climatic conditions,and other aspects of historical periods.In particular, exploring the temporal and spatial distribution is highly important for the management and protection of these sites. Using ArcGIS 10.8 software, we analysed the distribution of 1,194 historical ancient sites among the key national cultural heritage sites. The research findings are as follows: (1) The distribution of ancient sites demonstrates an agglomerative spatial pattern. The nearest neighbour index (R<1) for sites from various historical periods indicates an agglomerative spatial distribution of ancient sites across different historical periods, with the clustering degree being relatively poor for sites from the Wei-Jin, Northern and Southern Dynasties and in the Ming and Qing periods. The regions with a concentration of ancient sites are the middle and lower reaches of the Yangtze River and Yellow River basins. Furthermore, there is a higher abundance of ancient sites in the southeastern region than in the northwestern region. (2) The distribution of ancient sites in different historical periods also exhibits an imbalance, with an overall downwards trend in the number of ancient sites in China. Notably, more ancient sites were found for the prehistoric and pre-Qin periods. The temporal trend of ancient sites during historical periods follows a trajectory from northeast to northwest, northeast to southwest, etc. (3) The temporal and spatial distributions of ancient sites are influenced by multiple factors, including social development, the natural environment, geographical elements, and socioeconomic and political factors. Finally, based on an understanding of the spatiotemporal distribution pattern of ancient sites and the factors that influence this pattern, recommendations for conservation and development can be proposed and supported by modern technological methods, with the aim of offering insights for the protection and sustainable development of heritage sites.
Enhancing Qualitative Microwave Imaging Indicators by Autoencoder Based Deep Learning Algorithm
Authors: BAYAT İbrahim Halil , DOĞU Semih , AKINCI Mehmet Nuri , CROCCO Lorenzo , AKDUMAN İbrahim
Published: March 2024

Enhancing microwave inverse imaging methods has garnered significant attention in the field of deep learning and microwave imaging, owing to their immense potential in tackling non-linear problems. Microwave imaging techniques commonly encounter the adverse effects of noise in measurements, leading to suboptimal results. In this research, we propose a novel deep neural network-based model that effectively mitigates the noise effects on qualitative microwave indicators, resulting in high-quality reconstructions. We consider various configurations of dielectric objects in free space to address the microwave imaging problem. The scattered field is computed using the two-dimensional method of moments, employing an antenna array comprising 36 infinitely long line sources. Subsequently, the linear sampling method is utilized to generate multi-frequency qualitative indicators, which are then employed as input to a deep learning network along with corresponding binary ground-truth images. The proposed deep learning model comprises 11 layers, including convolutional and deconvolutional layers, without any dropout or pooling layers to prevent information loss. The results of the network are compared with Jaccard index to see how similar they are. The proposed method achieves higher accuracy and Jaccard score, demonstrating the efficacy of the proposed deep learning approach. Notably, the simplicity of the model construction contributes to its appeal, as it operates in conjunction with the results obtained from the linear sampling method. The presented results underscore the remarkable capabilities of the proposed deep learning method in enhancing microwave inverse imaging.
Damage Detection of wire rope Broken wire Damage Based on deep Semi- supervised Learning
Authors: zhang Juwei , Ye Qiang , Chen Quankun
Published: March 2024

Aiming at the problems such as the existence of a large amount of background information for wire rope image, the lack of efficient and accurate damage area extraction methods. A novel wire rope image preprocessing method is proposed, which can automatically adjust the pose of wire rope, remove the background information of wire rope image, and extract the damage area of wire rope. In response to the problem that deep learning based wire rope damage detection methods require a large amount of labeled data, a convolutional neural network model WR-CNN adapted to the steel wire rope dataset is designed, And combine WR-CNN with the semi-supervised learning example provided by Temporal Ensembling to form WR-TE-CNN. Aiming at the problem that the existing detection methods of broken wire damage do not consider the difference information between different types of damage and the similar information between the same type of damage, the distance loss function is introduced into the loss function of WR-TE-CNN and the characteristic quantity of calculating distance loss function is improved ( Before the improvement it was called WR-TE-DLCNN, after the improvement it was called WR-TE-IDLCNN ). The experimental results show that When the proportion of labeled data is 0.5, the wire breakage recognition rate of WR-TE-IDLCNN exceeds WR-CNN and is 99.04%. WR-TE-IDLCNN can further utilize the information between different types of damage and between the same types on the basis of WR-TE-DLCNN.
Nursing Students' and Faculty Perspectives: Challenges and Insights into Digital Classes during the Pandemic
Authors: K Puvaneswari. , Sriniva Umavalli , Christhumary. Preetha Carolin , Sakthivel Rajathi , Kanagaraj Anbueswari , Jacob Jessy , Yesuwilson Albin Joseph
Published: March 2024

Introduction
The pedagogical transition from traditional to distance learning is a challenge for nursing education during the pandemic in India, since the faculty and students were not exposed to the virtual classes
Methods
A qualitative research examined faculty and students perspectives of the challenges and insights into digital classes in the during the pandemic. Convenient sampling was employed to gather qualitative data from the diploma, undergraduate, or postgraduate programs students who had experienced digital classes during the pandemic. Six focus group interviews were done with the total of 32 nursing students, and 14 faculty. After obtaining consent each session lasting between 1.5 to 2 hours. The data were analyzed using thematic analysis, following Braun and Clarke's (2012) six-phase analytical process.
Results
The major themes created through students' perspectives were 1)Closing the Educational Divide: Bridging the Gap with E-Technology, 2.Exposed to Different Approaches of teaching -learning, 3. Challenges & Technological Glitches in the digital Classroom, 4.Expression of Dissatisfaction, 5.Struggling with Self-Motivation and 6.Environmental influences. The major themes created through faculty perspectives were 1.Escalating Workload: Navigating Increased Demands, 2.Enhanced Technology Proficiency: Gaining Improved Access, 3.Discipline Concerns, 4.Improved methods of teaching, 5.Lack of Clinical learning and 6.Need for Special Platform. Along with the major themes sub-themes were also reported.
Conclusion
This study concluded that digital classes were very convenient and beneficial during pandemic. Both the group of respondents stressed the challenges which need to be focused to fill the gap in future. Keywords- Digital classes, Pandemic, Nursing students, Nursing faculty, Challenges, Insights
Scope of recruitment for insider immigrant community gatekeepers: A case example of recruiting Ghanaian immigrants in the United States for a research study
Authors: Kodwo-Nyameazea Yale
Published: March 2024

This study draws on the author’s fieldwork experience to explore the scope of participant recruitment for insider immigrant community gatekeepers. The scope of recruitment includes being a member of the immigrant community, soliciting for participation from community members, volunteering, and being self-motivated to recruit participants. In their role, insider immigrant community gatekeepers not only decided who received the research information and who eventually participated in the research activities but also provided support to the researchers that they had granted community access. Insider immigrant community gatekeepers use a combination of personal qualities and a range of skills to recruit participants. They drew on their credibility and trustworthiness to build and maintain rapport and relationships that elicited community members’ participation in research. They used their good communication and storytelling skills to attract and persuade potential participants to complete research activities. Insider immigrant community gatekeepers have patience and self-motivation to persist and overcome community members’ rejection of recruitment overtures, organize activities that facilitate participation in research, and provide information that helps researchers make informed decisions about recruitment.
Efficacy of the da Vinci robot versus thoracoscopic surgery for patients with mediastinal tumors of different body mass index: a multicenter propensity score-matched study
Authors: Hong Ziqiang , Liu Qing , Li Haochi , Cao Wei , Zhang Jinlong , He Xiaoyang , Jin Dacheng , Gou Yunjiu
Published: March 2024

Background. The purpose of present study was to evaluate the efficacy and safety of Da Vinci robot-assisted thoracoscopic surgery (RATS) versus video-assisted thoracoscopic surgery (VATS) for the treatment of patients with mediastinal tumors of different body mass indices (BMI).
Methods. A retrospective cohort study was used to collect 260 patients with mediastinal tumors admitted to three medical centers in China from December 2020 to December 2023. These patients underwent mediastinal tumor resection by RATS (n=125) or VATS (n=135). Propensity score matching (PSM) analysis was performed for both groups, and further, the patients were divided into N-BMI group (18.5 kg/m2≤BMI<25 kg/m2) and H-BMI group (BMI≥25 kg/m2) based on their BMI to compare patients’ surgery-related information.
Results. The RATS group was more advantages in terms of intraoperative blood loss, total postoperative drainage, postoperative drainage time, and postoperative hospital stay. In terms of hospitalization costs, the VATS group was more advantageous. Subgroup analysis showed that in the H-BMI group, in addition to obtaining similar findings as before the subgroup analysis, we found a statistically significant difference in shorter operative time and lower incidence of postoperative complications in the RATS group.
Conclusion. Compared to VATS, RATS has technical and short-term efficacy advantages, although it has the drawback of high costs associated with the treatment of mediastinal tumors. In patients with mediastinal tumors of high BMI, RATS can achieve better short-term outcomes and safety, especially in terms of reducing the incidence of postoperative complications.
Comparison of Illumina MiSeq and microscopy methodologies for the analysis of diatom communities in five estuaries along the southern coast of the Korean Peninsula
Authors: Kim Young-Saeng , Yun Hyun-Sik , Lee Jae-Hak , Lee Kyung-Lak , Choi Jae-Sin , Won Doo Hee , Kim Yong Jae , Kim Han-Soon , Yoon Ho-Sung
Published: March 2024

The study of microalgal communities is critical for understanding aquatic ecosystems. These communities are primarily composed of diatoms (Bacillariophyta), and two methods are commonly used to study them: microscopy and Illumina MiSeq. These two methods are distinct, and their differences are reflected in the results they yield. Thus, their suitability for analyzing diatom communities is often debated and evaluated. In this study, these two methods were used to analyze the diatom communities in the same water samples, and the results obtained were compared. The taxonomy of the species constituting the diatom communities was confirmed, and both methods showed that the species belonging to the Bacillariales and Naviculales orders (class Bacillariophyceae) are diverse. However, at the lower taxonomic levels (family, genus, and species), microscopy tended to show a bias toward detecting diatom species belonging to the Bacillariaceae and Naviculaceae families. The results obtained from the two methods differed in terms of the identification of each diatom present in the communities and the analysis of their structural characteristics. These results are consistent with the fact that diatoms belonging to the Nitzschia and Navicula genera are abundant in the communities, furthermore, only the Illumina MiSeq showed the abundance of the Melosira, Entomonis, and Amphiprora genera. Although the results obtained from microscopy tended to be biased, they were superior to those of Illumina MiSeq regarding species-level identification. Based on the results obtained via microscopy and Illumina MiSeq, it was revealed that neither method is perfect and that each has clear strengths and weaknesses. Therefore, for the effective and accurate analysis of diatom communities, it is desirable to combine the two methods.
A distributed geometric rewiring model
Authors: Lopez-Chavira Magali , Aguirre-Guerrero Daniela , Marcelín-Jiménez Ricardo , Vásquez-Toledo Luis Alberto , Bernal-Jaquez Roberto
Published: March 2024

We propose a distributed rewiring model which starts with a planar graph embedded into the Euclidean space and then behaves as a distributed system, where each node is provided with a set of dynamic links. The proposed rewiring evolves through cycles, where nodes explore the network to identify possible shortcuts and rewire their dynamic links. The rewiring decisions are subject to Euclidean and geodesic distance constrains. The emerging networks were assessed through topological and robustness analyses. We found that the networks display a variety of characteristics observed in complex networks encompassing phenomena such as preferential attachment, the distinctive traits of small-world networks, the presence of community structures, and robustness against degradation process. We consider that our proposal can be applied in the design of those self-managed systems in which there is a limitation on communication resources that can be represented by the Euclidean distance and, however, the components themselves can deploy strategies to optimize the transport of information and develop tolerance before contingencies.
Synthese geschützter TPA-Spinlabel für die Markierung von Nukleinsäuren und Proteinen
Authors:   , Kaiser Frank
Published: March 2024

Nukleinsäuren und Proteine bilden zusammen mit den Kohlenhydraten und Lipiden die vier großen Gruppen der Biomoleküle. Dabei setzen sich Nukleinsäuren aus einer variierenden Abfolge von Nukleotiden zusammen. Gleiches trifft auf die Proteine zu, wobei deren Bausteine als Aminosäuren bezeichnet werden. Die Reihenfolge der Bausteine bestimmt zusammen mit der Interaktion, die die einzelnen Bestandteile untereinander eingehen, deren Funktion. Um deren Wirkungsweise verstehen und nachverfolgen zu können, wurden unterschiedliche Methoden entwickelt, zu welchen auch die EPR-Spektroskopie gehört. Durch den Einbau modifizierter Nukleotide oder Aminosäuren lassen sich Spinlabel in die sonst EPR-inaktiven Nukleinsäuren und Proteine einführen. Diese Marker lassen sich grundsätzlich in drei Klassen unterteilen (Metallionen, Nitroxidradikale und TAMs), weisen aber immer mindestens ein ungepaartes Elektronenpaar auf. Die Festphasensynthese ist eine Standardprozedur zur Herstellung von markierten Nukleinsäuren und Proteinen. Allerdings führen die Bedingungen dieser Methode zumindest teilweise zur Zersetzung der Nitroxidradikale, die dieser Arbeit zugrunde liegen, wenn sie direkt während der Synthese eingebaut werden. Der direkte Einbau ist aber in vielen Fällen essenziell, um bestimmte Eigenschaften zu erzielen. Um den Abbau des Nitroxidradikals während der Festphasensynthese zu verhindern, kann dieses vorübergehend mit einer Schutzgruppe versehen werden, welche sich anschließend wieder abspalten lässt. Der Schwerpunkt dieser Arbeit liegt hierbei auf der Darstellung neuer photolabil geschützter Spinlabel zur Synthese markierter Proteine und Nukleinsäuren. Basierend auf den Nukleotiden Uridin und Cytidin konnten zwei für die RNA-Synthese vorgesehene Phosphoramidite synthetisiert werden, welche jeweils an der 5-Position des Pyrimidinrings mit einem photolabil geschützten Spinlabel auf Basis von TPA versehen waren. Durch Einbau des Uridinderivats in das Neomycin-Aptamer konnte zudem der Einfluss der Spinlabel auf die lokale Struktur mit Hilfe von in-line probing gezeigt werden. Der gleiche TPA-Label konnte ebenfalls mit einem Lysin gekuppelt werden, welches später über ein orthogonales tRNA/Aminoacyl-tRNA Synthetase Paares in eine Polypeptid eingebaut werden sollte. In Kooperation mit dem AK Grininger ist auch ein nicht geschützter Spinlabel zur kupferfreien Markierung der Fettsäuresynthase entstanden. Abschließend war noch die Synthese eines auf Phenylalanin basierenden photolabil geschützten Spinlabel in Arbeit, welcher jedoch nicht beendet werden konnte. Dieser sollte mittels Festphasensynthese einbaubar sein, weswegen er am N-Terminus mit Fmoc geschützt ist.
For Us, By Us
Authors: Habtamu Sandra
Published: March 2024

This article describes how one group of African American women educators set out to change the narrative surrounding the achievement of African American girls at their high school through the creation of an elective course entitled Ourstory, which was designed using the tenets of culturally relevant, African-centered, and Black feminist pedagogy. The main goal of the Ourstory course was to use the study of African American women’s history and heritage to increase self-esteem, self-efficacy and provide a safe space for the African American girls involved. This descriptive study explores the design and implementation of the Ourstory class using a qualitative analysis of the course syllabus, lesson plans, course materials, student work, observations, and interviews with staff and students. The findings from this study demonstrate that there is value in creating a space for African American girls to express themselves and build community.
Black Girl Politics
Authors: Curtis Sabrina
Published: March 2024

Despite the informed, culturally attuned, active, and robust nature in which Black girls enter into dialectical exchange with one another, their peers, and other adults in schools and communities, Black girls’ critical and political literacies are often minimalized and undervalued. In this paper, I discuss my engagement with two Black girls who participated in Black Girl Politics, a literacy collaborative and curricular intervention designed to explore Black girls’ theorizing about social and political ideas and social change. I outline the girls’ engagement with a multimodal policy project in which they reimagine how to better resource schools in ways that expand access to time and space for implementing activities that promote Black girl joy and wellbeing. This paper highlights how educational opportunities and curricular interventions for nurturing Black girls’ political consciousness can prepare them to be informed, active members of society, and empower them to challenge social practices compromising their sense of freedom and belonging.
Beyond the Dress Code
Authors: Mbalia Jendayi , Amari Balton  , Leila Wright
Published: March 2024

Historically, Black females have been dehumanized by the policing, hyper-sexualization, and fetishizing of their bodies. This dismissal of their humanness is rooted in enslavement and is perpetuated in society at large, the media, and in schools today. As a result, the bodies of Black girls are under constant gaze and scrutiny. This directly connects to the policing of what they wear and results in them being disproportionately dress coded in their learning spaces. This paper, written in dialogue, shares the insight of two Black, female students, and fifteen other Black female students whom they interviewed at Midwest High School as it relates to the disproportionate treatment of Black girls at their school.
FACTORS CONTRIBUTING TO AND ASPECTS OF POST-TRAUMATIC GROWTH ASSOCIATED WITH BREAST CANCER
Authors:   Psycho Oncology PGDCP 11894389., Sirpaul Sanya
Published: March 2024

One in eight people receive a diagnosis of breast cancer, making it one of the most frequent malignancies. Post-traumatic growth (PTG), which is defined by positive changes in functioning in a variety of life dimensions, is often brought on by this traumatic event. The research that has previously been done on PTG and breast cancer is critically examined in this work. After a thorough search using reliable resources, 25â€“30 articles were found six of them were chosen based on predetermined standards.The results showcase that post-traumatic growth in the areas of greater appreciation for life and better relationships is common among breast cancer survivors. There are multiple factors involved in this occurrence. Though extreme sequelae may have the opposite effect on PTG, perceived emotional intensityand mild sequelae all positively influence PTG. Coping mechanisms, especially those that are adaptive, are proven essential to PTG.The PTG process is aided by social resources like contact with PTG models (cancer survivors), support from ones spouse and co-workers, and quality of marital support.In PTG, demographic considerations also come into play.There is a positive correlation between higher PTG and younger age, lower education level, and lack of college degree. However, the analysis resulted in mixed results over the association between time since diagnosis and PTG, which calls for additional qualitative study in the area. Given the limitations of self-report measures, the subjectivity of researcher interpretations, and the emphasis on a Western population, care must be taken when interpreting these results. However, our analysis provides significant insights for clinicians and researchers and underscores the potential for promoting posttraumatic growth in breast cancer patients and survivors.
ASSESSING COMMUNICATIVE COMPETENCE AMONG SCHOOL TEACHERS: A CRITICAL ANALYSIS
Authors:   Professor & Head, Department of English, KBP Mahavidyalaya, Pandharpur (Autonomous) MS, India., S. Mane Samadhan
Published: March 2024

Effective communication is paramount in the field of education, particularly among school teachers who serve as conduits of knowledge and facilitators of learning. This research article examines the communicative competence of school teachers, exploring its multifaceted dimensions and implications for pedagogical practice. Drawing upon theoretical frameworks and empirical evidence, this study investigates the components of communicative competence, its role in classroom interactions, and the factors influencing its development and enhancement. Additionally, it offers insights into the assessment methods and strategies for fostering communicative competence among school teachers.
Enzymatic Kinetic Resolution of Tertiary Benzyl Bicyclic Alcohols: Studies of the Reaction Conditions for a More Efficient Protocol
Authors: de Almeida Laiza , Ganéo Neto Laerte , Milagre Cintia , Milagre Humberto
Published: March 2024

The reactivity and steric hindrance of optically active tertiary alcohols limit the development of more direct enantioselective methodologies for their synthesis, such as kinetic resolution (KR). In this work, we optimized the reaction conditions of an enzymatic KR of two tertiary benzyl bicyclic alcohols using readily available reagents and biocatalyst. Studies were conducted with 1-methyl-1,2,3,4-tetrahydronaphthalen-1-ol and 1-methyl-2,3-dihydro-1H-inden-1-ol as substrates and commercial lipase A from Candida antarctica (CAL-A) as biocatalyst for the enantioselective transesterification of these racemic tertiary alcohols. After varying the reaction parameters, such as acyl donor, solvent, and enzyme/substrate ratio, the (R)-esters were obtained with high conversions (44-45%) and excellent enantiomeric excess (96-99%) in only 4-5 h, to our knowledge being the best result for KR of the evaluated tertiary alcohols in terms of reaction rate, conversion, and enantioselectivity reported so far.
Assessment of household's willingness to pay for improved water supply services in emerging nations: a case study of Adama City, Ethiopia
Authors: Aminu Beshir Abelkassim , Reddythota Daniel , Alemayehu Essays
Published: March 2024

Adama City grew rapidly due to its proximity to Addis Ababa, resulting in increased industrial, urban activities, and population growth. However, this expansion has resulted in drinking water shortages, which is a critical community's concern. The aim of this study was to determine households’ willingness to pay (WTP) for improved water supply services in Adama, with factors influencing WTP. To quantify households’ WTP, a contingent valuation (CV) technique was used and data from 435 respondents was gathered through field surveys, KII, and HHs interviews. A binary logistic model was utilized to examine variables that have a significant impact on households’ WTP. The analysis revealed several independent variables, such as gender, age, marital status, education level, and monthly income, additionally, water quantity, quality, availability, and affordability. The study found that 39.77 and 26.21% of residents of the city were dissatisfied with the quality and quantity of available water supply, respectively. The study discovered that 92% of households were willing to pay an additional $7.26 USD above their average monthly water cost of $3.58 USD to improve water delivery services. Factors that influence households’ WTP for improved water supply services should be considered. The study's findings can help legislators and water supply companies to design sustainable projects that meet community needs.
From shower to table: fate of organic micropollutants in hydroponic systems for greywater treatment and lettuce cultivation
Authors: Mendoza Esther , Vosse Josephine , Azzellino Arianna , Santos Lúcia H. M. L. M. , Semitsoglou-Tsiapou Sofia , Comas Joaquim , Buttiglieri Gianluigi
Published: March 2024

This study evaluated the dual functionality of hydroponic systems to grow edible crops while treating greywater (GW) containing 20 organic micropollutants (OMPs). Various conditions with differing nutrient contents were tested: raw GW, GW with struvite, and GW with commercial nutrient solution. System performance was assessed with plant growth and standard parameters and OMP removal. After 4-week exposure, all conditions produced healthy-looking plants, proving GW as a viable hydroponic growth medium. However, only the condition with commercial solution yielded plants comparable to the biotic control, indicating the necessity of nutrient supplementation. Effluent from conditions with well-developed plants met the requirements of the European water reuse legislation (EU 2020/741) for scenarios B–D (food crops not in direct contact with the reclaimed water and industrial crops), and had the highest OMP removal, showcasing the effectiveness of the system for OMP treatment. Estimated calculations of OMP detected in leaves (10/20 OMP detected, predominantly positive and small) resulted in calculated potential human health risks through lettuce intake for two compounds: atenolol and epoxycarbamazepine. These findings support a continued evaluation of the behavior of other OMPs and their transformation products in water–plant systems, and their consideration in legislation on water reuse and food safety.
Depuración de semillas de arroces regionales
Authors: Morales Angulo José Gregorio , Pérez Cantero Shirley Patricia , Romero Ferrer Jorge Luis
Published: March 2024

El presente folleto explica la depuración varietal en semillas de arroz, con el fin de mantener la pureza del material. Da a concoer la razón por la cual se debe realizar en los lotes destinados a producción de semilla de excelente calidad, con el fin de eliminar las plantas que, por sus características morfológicas, no correspondan al material del cual se está produciendo semilla y demás aspectos de la depuración
Desempeño agronómico del nuevo híbrido de Brachiaria cultivar mulato II en las sabanas de Córdoba, Sucre y el Bajo Cauca
Authors: Cuadrado Hugo , Torregloza Lino , Argel Pedro , Santana Martha
Published: March 2024

El Brachiaria híbrido cultivar mulato II es el resultado de tres generación de cruzamientos y selecciones, realizado por el proyecto de forrajes tropicales del CIAT en Cali Colombia.
Compatibilidad entre polímeros y la cepa c16 Azospirillum brasilense mediante el modelo termodinámico de ARRHENIUS
Authors: Cortés Patiño Sandra Lucía , Bonilla Ruth Rebeca
Published: March 2024

La aplicación en campo de un biofertilizante depende en gran parte de una correcta formulación que garantice la estabilidad y efectividad del microorganismo durante su periodo de almacenamiento. El modelo termodinámico de Arrhenius –dentro de sus diversas aplicaciones- permite predecir tiempo de vida útil de un inoculante biológico teniendo en cuenta el efecto de la temperatura de almacenamiento sobre la viabilidad celular del microorganismo. El objetivo de esta investigación fue hacer uso de esta herramienta de predicción con el fin de seleccionar el mejor polímero, una concentración y una temperatura ideal para mantener la estabilidad de un prototipo líquido con base en la cepa C16 de Azospirillum brasilense.
Validation of 3 Computer-Aided Facial Phenotyping Tools (DeepGestalt, GestaltMatcher, and D-Score): Comparative Diagnostic Accuracy Study (Preprint)
Authors: Reiter Alisa Maria Vittoria , Pantel Jean Tori , Danyel Magdalena , Horn Denise , Ott Claus-Eric , Mensah Martin Atta
Published: March 2024

BACKGROUND

While characteristic facial features provide important clues for finding the correct diagnosis in genetic syndromes, valid assessment can be challenging. The next-generation phenotyping algorithm DeepGestalt analyzes patient images and provides syndrome suggestions. GestaltMatcher matches patient images with similar facial features. The new D-Score provides a score for the degree of facial dysmorphism.

OBJECTIVE

We aimed to test state-of-the-art facial phenotyping tools by benchmarking GestaltMatcher and D-Score and comparing them to DeepGestalt.

METHODS

Using a retrospective sample of 4796 images of patients with 486 different genetic syndromes (London Medical Database, GestaltMatcher Database, and literature images) and 323 inconspicuous control images, we determined the clinical use of D-Score, GestaltMatcher, and DeepGestalt, evaluating sensitivity; specificity; accuracy; the number of supported diagnoses; and potential biases such as age, sex, and ethnicity.

RESULTS

DeepGestalt suggested 340 distinct syndromes and GestaltMatcher suggested 1128 syndromes. The top-30 sensitivity was higher for DeepGestalt (88%, SD 18%) than for GestaltMatcher (76%, SD 26%). DeepGestalt generally assigned lower scores but provided higher scores for patient images than for inconspicuous control images, thus allowing the 2 cohorts to be separated with an area under the receiver operating characteristic curve (AUROC) of 0.73. GestaltMatcher could not separate the 2 classes (AUROC 0.55). Trained for this purpose, D-Score achieved the highest discriminatory power (AUROC 0.86). D-Score’s levels increased with the age of the depicted individuals. Male individuals yielded higher D-scores than female individuals. Ethnicity did not appear to influence D-scores.

CONCLUSIONS

If used with caution, algorithms such as D-score could help clinicians with constrained resources or limited experience in syndromology to decide whether a patient needs further genetic evaluation. Algorithms such as DeepGestalt could support diagnosing rather common genetic syndromes with facial abnormalities, whereas algorithms such as GestaltMatcher could suggest rare diagnoses that are unknown to the clinician in patients with a characteristic, dysmorphic face.