bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synergizing Expertise and Technology: The AI Revolution in Radiotherapy for Personalized and Precise Cancer Treatment
Authors: Kouhen Fadila , El gouach Hanae , Saidi Kamal , Errafiy Nadia , Dahbi Zineb 
Published: August 2023

In recent years, the field of radiotherapy has witnessed remarkable advancements with the integration of artificial intelligence (AI) technologies into clinical practice.
Traditionally, radiotherapy treatment planning has been a labor-intensive process, requiring meticulous manual segmentation and optimization. With the advent of AI, particularly deep learning algorithms, the accuracy and efficiency of target delineation and organ-at-risk segmentation have significantly improved. AI-driven algorithms analyze voluminous medical imaging data, enabling rapid and precise contouring, thus expediting the planning phase and reducing inter-observer variability.
Furthermore, AI&#039;s role extends to treatment plan optimization, where it intelligently explores vast parameter spaces to generate optimal plans tailored to individual patients. This not only saves dosimetrists&#039; time but also enhances plan quality by accounting for complex anatomical variations and personalized clinical goals.
In the realm of treatment delivery, AI-powered real-time image guidance enhances the accuracy of patient positioning, ensuring precise radiation targeting. Adaptive radiotherapy, enabled by AI, allows on-the-fly plan modifications in response to anatomical changes, significantly improving treatment accuracy in scenarios like tumor shrinkage or weight loss.
Beyond planning and delivery, AI algorithms contribute to outcome prediction by analyzing historical patient data and treatment responses. This predictive capability aids clinicians in making informed decisions and refining treatment strategies for better prognoses.
Despite the revolutionary potential, challenges remain in seamlessly integrating AI into clinical workflows. Ethical considerations, data privacy, and algorithm interpretability necessitate cautious implementation. Additionally, fostering interdisciplinary collaboration between AI experts and radiation oncologists is imperative to harness the technology&#039;s full potential.
This paper explores the impact of AI in four key areas of radiotherapy: automated segmentation, dosimetric and machine quality assurance, adaptive radiation therapy, and clinical outcome prediction.
3D Body Center of Mass at the Workplace under Hypogravity
Authors: Maillard Tatiana 
Published: August 2023

The center of mass dynamics of human seated posture in a work environment under hypogravity (0&amp;lt;g&amp;lt;1) have rarely been investigated and it remains to be accomplished. The present study determined the difference in the body system of 32 participants working under simulated 1/6g (Moon) and 1g (Earth) for comparison reason using static and dynamic action measurements. This was based on analyzing the participant&#039;s center of mass before, during, and after the task when they started to get fatigued. According to this analysis, there is a positive relation (p&amp;lt;0.01) with a positive coefficient of correlation between CoM body shift down along the Y axis and gravity level for males and females. At the same time, the same positive relationship (p&amp;lt;0.01) between the tilt of the body back along the Z axis and the level of gravity was found only in females. This offers fresh perspectives for comprehending hypogravity. It can also improve workplace ergonomics, body stability, equipment design, and biomechanics.
AOGC: Anchor Free Oriented Object Detection Based on the Gaussian Centerness
Authors: Wang Zechen , Bao Chun , Cao Jie , Hao Qun 
Published: August 2023

Oriented object detection is a challenging task in scene text detection and remote sensing image analysis, which has attracted extensive attention in recent years with the development of deep learning. Currently, mainstream oriented object detectors are based on preset anchor boxes. This method increases the computational load of the network and cause a large amount of anchor box redundancy. To solve this problem, we propose anchor-free oriented object detection based on the Gaussian centerness(AOGC), a single-stage anchor-free detection method. Our method uses contextual attention FPN(CAFPN) to obtain the contextual information of the target. Then we design a label assignment method for oriented objects. Finally, we develop a Gaussian kernel-based centerness branch, which can effectively determine the significance of different anchors. AOGC achieves mAP of 74.30% on the DOTA-1.0 datasets and 89.80% on the HRSC2016 datasets, respectively. AOGC exhibits superior performance to other methods in oriented anchor-free object detection methods.
The The Implications of Transformational and Transactional Leadership on Organizational Commitment
Authors: Asrarudin  
Published: August 2023

Abstract

This research is a literature review that examines various literatures on the implication transformational and transactional leadership. The purpose of this research is to find out the implications of transformational and transactional leadership on organizational commitment; similarities and differences behaviors of transformational and transactional leadership towards organizational commitment. The method used in this research is integrative literature review which assesses, criticizes, and synthesizes different literatures to create new theoretical framework. This research finding shows that transformational and transactional leadership have implications on the commitment of each employee to the values ​​and goals of the organization. Transformational leadership builds long-term relationship while transactional leadership builds short-term relationships with subordinates based on shared goals and rewards are given when subordinates are able to achieve goals and vice versa sanctions are given if the goals cannot be achieved. Creative and innovative behavior is not the main thing but status quo is important.
The Influence of Emotional Intelligence, Organizational Culture and Team Work On Employee Performance at The Royale Krakatau Hotel, Cilegon
Authors: Pancasasti Ranthy , Putra Aries Pratama , Nuraisah Fitri , Khalqiyah Sofwah 
Published: August 2023

The purpose of this study is to analyze a model that is expected to improve employee performance by involving emotional intelligence, organizational culture and teamwork.
Originality/value: Novelty in this research is that no previous research has been found that discusses emotional intelligence, organizational culture and teamwork on Employee Performance at The Royale Krakatau Hotel, Cilegon.
Research limitations: The limitations of this study are only to analyze the influence of emotional intelligence, organizational culture and teamwork on employee performance at The Royale Krakatau Hotel, Cilegon.
Design / methodology / approach: The research method is quantitatively by using a questionnaire with an Ordinal scale of 10 points and the sampling technique was carried out by simple random sampling. The number of samples used was 120 employees to test the four (4) predetermined hypotheses. The Structural Equation Model-Partial Least Square (SEM-PLS) model was used to test the statistical significance of the path coefficient.
Findings: The findings of the study explain that Emotional Intelligence has a not significant positive effect on Employee Performance, Organizational Culture has an insignificant positive effect on Employee Performance, Emotional intelligence has a positive and significant effect on Organizational Culture, Emotional Intelligence has a positive and significant effect on Teamwork, Organizational Culture has a positive and significant effect on Teamwork, Teamwork has a positive and insignificant effect on Employee Performance.
Institutional Conflict in Employee Output, Absenteeism and Turnover
Authors: Owusu-Acheampong Eugene , Antwi Joseph 
Published: August 2023

Abstract
This study aimed to examine the effect of conflict on employee output, absenteeism and turnover. The study was quantitative, and the design was a descriptive survey. The population for the study was stratified, and the study participants were selected randomly. The instrument was a questionnaire, and the IBM SPSS version 22 was used to generate the results for discussion. The study revealed that conflict adversely influences employee performance and also accounts for frequent employee absenteeism, low output and turnover. One implication for leadership from the study is that workplace conflicts significantly affect employee output, absenteeism and turnover. Each employee faces different conflicts that must be understood and resolved. By implication, organisational leaders must design jobs appropriately for employees to prevent duplications and foster peaceful collaboration among employees. This will help them build trust among themselves at the workplace. This will reduce interpersonal, relationship and task-related conflicts within the organisation. This will minimise conflict and its dysfunctional consequences on the employees and the organisation. Literature on the conflict in higher institutions appears to be scarce in Ghana. This study is different as it examines the relationship between conflict and employee performance using work output, absenteeism and turnover in technical universities in Ghana.
Techno-Economic Analysis to Project Hydrogen Pathways Potential Across the United States
Authors: Saafi M A. , Gordillo V. 
Published: August 2023

Abstract
Since signing the legally binding Paris agreement, fighting climate change has been an increasingly important task worldwide. The United Sates (U.S.), being highly industrialized, recognizes to be one of the largest greenhouse gas global emitters and has set a long-term strategy to reach Net-Zero Emissions by 2050. One of the key emerging potential decarbonization pathways is hydrogen (H2), which could be considered as a long-duration energy storage (LDES) option for an electric grid dominated by renewable energy generation. In this work, we conduct a techno-economic analysis to determine least cost solutions for H2 production, considering different scenarios for wind and photovoltaic-sourced renewable electricity supply under a set of given operational constraints. The model used is a mixed integer linear program that minimizes the plant's net present cost (NPC) over a defined project lifetime. We quantify the impact of intermittency by comparing the operational performance of different regions in the U.S. reflected on levelized H2 production costs and required built storage. The renewable electricity production is modeled using 10 years of historical meteorological data for each region on an hourly basis. Moreover, we evaluate the complementarity of solar and wind electricity, the effect of dynamic storage sizing, and the economic dispatch of renewable energy curtailment.
PASSIVE FIT OF CAD\CAM FRAMEWORKS DESIGNED BASED ON VIRTUAL IMPLANT POSITIONS VERSUS ACTUAL IMPLANT POSITIONS: A PILOT INVITRO STUDY
Authors: Kamel Mohamed El-Sayed , ElKhashab Mohamed Amr , Radi Iman Abdelwahab 
Published: August 2023

Abstract
Aim: To evaluate the passive fit of CAD/CAM implant supported frameworks that are constructed before and after implant placement.
Methodology: A sample of 5 Kennedy class I models that loaded with 10 models bilaterally. In the first group, 3 implants were installed using full guided protocol and loaded with 3 units screw retained metal framework that constructed before implant placement based on virtual implant positions in aid of full digital work flow. While the second group was the control group, in which 3 implant were installed and loaded with 3 units screw retained metal frameworks constructed after implant installation based on their implant positions. The frameworks were screwed to multi-unit abutments seven tests were carried out to assess passive fit of the frameworks. These tests were visual, tactile test using examination probe, floss slippage, one screw test , screw resistance test and fit checker. Radiographs were done in conjunction with these tests to assess presence of gaps at abutment –framework interface.
Reconstitution kinetics of severe cerebrospinal fluid abnormalities in cryptococcal meningitis
Authors: Dambietz Christine , Heming Michael , Brix Tobias Johannes , Schulte-Mecklenbeck Andreas , Tepasse Phil-Robin , Gross Catharina C. , Trebicka Jonel , Wiendl Heinz , zu Hörste Gerd Meyer 
Published: August 2023

Abstract
Cryptococcal meningitis (CC) is a rare and severe fungal infection in immunocompromised patients, affecting the cerebrospinal fluid (CSF). Host response and immunological mechanisms after CSF invasion of Cryptococcus neoformans have rarely been investigated in detail before. We retrospectively collected standard CSF analysis and flow cytometry data of CSF and blood in patients with cryptococcal meningitis (n=7) and compared them to immunocompromised patients without meningitis (n=13) and healthy controls (n=7). Flow cytometry analysis revealed an elevation of natural killer cells in the CSF of CC patients. Follow-up CSF analysis over up to 150 days showed heterogeneous and slow normalization of CSF after induction of antifungal therapy. Flow cytometry of blood and CSF may thus aid the diagnosis and follow-up of CC patients.
Testing a mixed method learning evaluation approach for real-time assessments of the implementation process
Authors: Hudson Kristian , Shaw Philippa , Osborn David , Lamb Danielle , Rehill Nirandeep , Russell Gregor , Stevenson Fiona , Kearney Matt , Beveridge Edward , Copsey Gemma , Oliver Emily , Sharma Vishal , Balasubramanian Bijal , Khurshid Zuneera 
Published: August 2023

Abstract

Background: Stakeholders involved in implementation efforts progress through multiple cycles of learning and problem solving, to which traditional evaluation approaches for implementation of healthcare innovations often fail to pay attention. Learning evaluation principles provide an alternative evaluation approach to capture and feedback ongoing learning in an iterative and informative way. This paper outlines a novel evaluation approach aligned with learning evaluation principles which will be tested in an implementation study examining an intervention designed to improve mental and physical health in people with severe mental illness (UCLPartners-Primrose).
Methods: This evaluation outlines five key steps: (1) Conduct baseline data collection to understand the implementation context; (2) Identify process and outcome measures of interest to each implementation site; (3) Collect and analyse qualitative and quantitative data on contextual factors in real-time via regular contact interviews; (4) Feedback synthesised data and learning to sites on an ongoing basis via lightning reports; (5) Generate learning from process, action, and outcome data, lightning reports, and post intervention interviews. This protocol draws from learning evaluation principles and the steps will be achieved using the Stanford lightning reports and the Consolidated Framework for Implementation Research. The application of this approach will be tested over 18 months through the implementation evaluation of an intervention, UCLPartners-Primrose.
Discussion: This protocol describes a flexible, iterative, and contextualised learning evaluation approach, which is expected to capture within-system learning through rapid analysis and feedback loops, amenable to the needs of implementation sites. This approach will enable the triangulation of the implementation experiences of the end users with the knowledge of implementation researchers, to build a more holistic picture of implementation barriers and enablers to bridge the gap between real-time data collection and its transformation into actions.
Conclusion: This is an innovative implementation evaluation approach developed to be more rapid, relevant, and responsive than traditional methods and encourages greater researcher-implementer collaboration. It therefore holds benefits for implementers and research teams involved in implementation efforts.
Elicitors in the production of tomato crop infected with Tomato brown rugose fruit virus and Pepino mosaic virus
Authors: Ortiz-Martínez Luis Enrique , Ochoa-Martínez Daniel Leobardo , Gutiérrez Jorge 
Published: August 2023

Abstract

Elicitors are considered sustainable alternatives for the management of plant viruses. The aim of the present study was to evaluate the effectiveness of nine elicitors on morphology, yield, and fruit quality of tomato plants inoculated with Tomato brown rugose fruit virus (ToBRFV), Pepino mosaic virus (PepMV), and both (ToBRFV + PepMV). The experiment was set up under a completely randomized design with six replicates. Ten days after transplanting, virus inoculation was done mechanically in all the treatments, except the negative controls. Three morphological, four yield, and seven fruit quality variables were evaluated. Virablock® 3G50 increased yield by more than 44% compared with the positive control in plants inoculated with ToBRFV, PepMV, and the mixed infection, while Supermagro cell extract and enhanced Supermagro increased yield in plants inoculated with ToBRFV and the mixed infection by more than 82% and 34%, respectively. Virablock® 3G50 and an ethanolic extract of Arracacia bracteata showed the highest values in fruit quality variables.
Identification of a novel mutation and a rare case of CLN6 and computation protein structure
Authors: Saboori Fozhan , Nejad Nazanin Ghaderi 
Published: August 2023

Abstract
Neuronal ceroid lipofuscinoses (NCLs) also known as Batten disease jointly account the highest incidences of hereditary neurodegenerative disease in childhood. This disease is mostly presented by vision loss, ataxia, premature mortality in later stages of disease and epileptic seizures. NCLs are categorized in different type that is relied on deficiencies in several genes. CLN6 is one of the identified NCLs and mutated gene affects a transmembrane protein embedded in the Endoplasmic Reticulum (RM). Here we report four cases presenting clinical feature of CLN6. Two novel mutations NM_017882.2: Exon 7: c.268A > G (p.Asn90Asp) as well as two homozygous mutations in NM_017882.2: Exon 3: c.679G < A. Additionally, following the finding of novel mutation, sanger sequencing method was employed to confirmed the outcome. Also, we performed a 3D structure prediction for CLN6 protein. InterPro was taken advantage to assess the domains and function in mutated sites. Both mutations are located in extracellular domain of CLN6 protein. In silico analysis demonstrated the pathogenic impact of these mutations, suggesting that the identified mutations are likely responsible for the observed phenotypic features in the patients.
Sequential colonization events with restricted gene flow in a widespread European carnation species
Authors: Cornille Amandine , Kaczmarek Thomas , Chen Xilong , Fior Simone , Venon Anthony , Roman Anamaria , Ursu Tudor-Mihai , Giraud Tatiana , Mezhenskyj Volodymyr , Koupilova Klara , Hood Michael , Widmer Alex 
Published: August 2023

Abstract
The key questions relating to the evolutionary processes underlying plant colonization success pertain to the geographic origin of the source population(s), the location of the migration routes, the extent to which genetic diversity is reduced via founder effects, and the extent of gene flow among populations during expansion. However, these questions must still be addressed for perennial herbaceous plants with large geographic distributions. We investigated the colonization history of Dianthus carthusianorum (the Carthusian Pink), one of the most widespread European carnation species. We called genome-wide 236,964 SNPs from a large sample across the D. carthusianorum distribution range, and used up-to-date population genomics approaches (approximate Bayesian computation Random-Forest method, ABC-RF) to infer population demographic history. Spatial genetic structure and diversity analyses and demographic inferences indicated successive East-West colonization events by the Carthusian Pink. ABC-RF also revealed gene flow during colonization, but only among geographically close populations. This study provides important insights into the colonization processes of herbaceous perennial species belonging to one of Europe's most diverse plant genera.
Earthquake detection capacity of Dense Oceanfloor Network system for Earthquakes and Tsunamis (DONET)
Authors: Nanjo K. Z. , Yamamoto Y. , Ariyoshi K. , Horikawa H. , Yada S. , Takahashi N. 
Published: August 2023

Abstract

For many seismicity-related studies, a reliable estimate of the magnitude of completeness is critical, because they evaluate the statistical properties of seismicity that strongly depend on correct completeness estimates. Here we adopted the Probability-based Magnitude of Completeness (PMC) method and performed a case analysis of the Nankai Trough, a target region monitored for future megathrust earthquakes. JAMSTEC (Japan Agency for Marine-Earth Science and Technology) has created a seismicity catalog that includes events in this region observed by DONET (Dense Oceanfloor Network system for Earthquakes and Tsunamis). Using seismicity data for 2015–2019, we found spatiotemporal variability of completeness magnitude Mp. Mp was lower than 1 in one of the areas where stations are densely deployed, whereas Mp was larger than 2 at the periphery and outside of the DONET area. We then evaluated the temporal evolution of Mp, highlighting how the failure of sets of observing stations influenced Mp if not repaired. Stations are aggregated around the 12 science nodes (hubs that connect the stations) and connected through the two oceanfloor backbone cables to JAMSTEC. We explored the possible use of PMC as a tool with simulation computation of node malfunction. A simulation showed that completeness estimates in the area near failure nodes were about 1 magnitude larger. If such failure occurred for nodes near the region which straddles the rupture zones of the previous Tonankai and Nankai earthquakes in 1940’s, it would most pronouncedly affect earthquake monitoring among nodes’ failures. It is desirable to repair these nodes or replace with new ones when their malfunction occurs. We then demonstrated an example of how to use Mp information as prior knowledge to seismicity-related studies. We used the b value of the Gutenberg-Richter distribution, and computed it taking Mp into consideration. We found that the spatial and temporal changes in b were strongly correlated to the magnitude-6 class slow slip that grew over two years on the Nankai Trough plate boundary, indicating the b value as a proxy that can help to image stress heterogeneity when there is a slow slip event.