bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of CT-based non-invasive Radiographic Biomarkers for Overall Survival Stratification in Oral Cavity Squamous Cell Carcinoma
Authors: Ling Xiao , Alexander Gregory S. , Molitoris Jason , Choi Jinhyuk , Schumaker Lisa , Mehra Ranee , Gaykalova Daria A. , Ren Lei 
Published: August 2023

Abstract

This study addresses the limited non-invasive tools for Oral Cavity Squamous Cell Carcinoma OSCC survival prediction by identifying Computed Tomography (CT)-based biomarkers for improved prognosis. A retrospective analysis was conducted on data from 149 OSCC patients, including radiomics and clinical. An ensemble approach involving correlation analysis, score screening, and the Sparse-L1 algorithm was used to select functional features, which were then used to build Cox Proportional Hazards models (CPH). Our CPH achieved a 0.70 concordance index in testing. The model identified two CT-based radiomics features, Gradient-Neighboring-Gray-Tone-Difference-Matrix-Strength (GNS) and normalized-Wavelet-LLL-Gray-Level-Dependence-Matrix-Large-Dependence-High-Gray-Level-Emphasis (HLE), as well as smoking and alcohol usage, as survival biomarkers. The GNS group with values above 14 showed a hazard ratio of 0.12 and a 3-year survival rate of about 90%. Conversely, the GNS group with values less than or equal to 14 had a 49% survival rate. For normalized HLE, the high-end group (HLE > -0.415) had a hazard ratio of 2.41, resulting in a 3-year survival rate of 70%, while the low-end group (HLE <= -0.415) had a 36% survival rate. These findings contribute to our knowledge of how radiomics can be used to anticipate the outcome and tailor treatment plans from people with OSCC.
Assessing the impact of mining exploration infrastructure on ground-dwelling arthropod communities using DNA metabarcoding and habitat characteristics.
Authors: Fernandes Kristen , Clark-Ioannou Sophia , Saunders Benjamin J , Majer Jonathan , Bateman Philip W , Bunce Michael , Nevill Paul 
Published: August 2023

AbstractFor most mining projects, regular monitoring of environmental impacts is typically measured solely for the main operation footprint and not the supporting network of exploration infrastructure. Such infrastructure includes exploration tracks, roads and drill pads, where localised areas are cleared of native vegetation, and the surrounding habitat is undisturbed. Here we use DNA metabarcoding to study the impacts of mining exploration infrastructure on the ground-dwelling arthropod communities found on Banded Ironstone Formations (BIFs) in the Midwest region of Western Australia. Further, we examine whether two indicator species groups, Formicidae and Collembola, reflect the patterns in overall arthropod communities. The study was conducted at three mine sites, each with three infrastructure types: maintained tracks, unmaintained tracks, and drill pads. We collected ground-dwelling arthropods and recorded habitat characteristics (e.g. total vegetation cover, bare ground cover) along transects extending 100 m away from the disturbance into remnant vegetation. We found that all three infrastructure types impacted the habitat characteristics similarly, with physical changes in habitat extending into the remnant vegetation. However, among all three groups of arthropods (overall arthropods, Formicidae and Collembola), we observed a clear distinction between each exploration infrastructure type at the three sites, indicating a disturbance effect extending more than 100 m into remnant vegetation. We found that Formicidae communities reflected the changes in overall arthropod communities better than Collembola. Our results demonstrate the utility of DNA metabarcoding for documenting fine-scale impacts on arthropod communities and highlight the need to consider different types of disturbances associated with mining activity.
Navigating Through Complexity: Profiling the main threats to Sustainable Tropical Wetlands Management and its Implications to livelihoods welfare and ecosystem governance: A Case Study of Mityana District, Uganda
Authors: Matovu Baker , Sarfo Isaac , Bbira Yasin , Yeboah Emmanuel , Muhoozi Yosia 
Published: August 2023

Abstract
Wetlands are crucial ecosystems that promote sustainable livelihood and biodiversity conservation, especially in tropical regions. However, recent studies have reported increasing threats to wetlands both environmental and human which threaten the provision and acquisition of several wetland benefits. Though there is recognition of the value of wetlands, in most local communities, there is limited knowledge and research on the benefits of wetlands and the level of threat thus affecting wetland governance. This research addresses this gap by conducting participatory research to create a baseline inventory that identifies the main wetlands and threats to inform policy. The study was conducted in 14 sub-counties and a sample of 105 wetlands along the wetlands of Lake Wamala and River Mayanja wetlands system in Mityana District was captured. The field data was collected from 150 respondents. Study findings found that there is an increasing human threat to wetlands especially in the River Mayanja seasonal wetlands and the level of damage/threat on Lake Wamala wetlands. Respondents further reported an increasing threat of environmental drivers such as climate change. Since the level of damage to wetlands in Mityana especially the permanent wetlands is relatively low, we recommend a focus on capacity building, development of wetlands action plans, increased support to local wetland authorities, and a system thinking approach in wetland threat identification and management.
Perceptions of dental students towards abrupt curriculum changes: a qualitative study
Authors: Nafea Ebtihaj 
Published: August 2023

Abstract
Background
Any abrupt changes in the educational system can have a negative effect on students. Dental students at X University faced two abrupt changes in the undergraduate curriculum over a two-year period, namely the COVID-19 pandemic and the national shift to the three-term system. This research aims to investigate the effect of these changes on dental students.
Methods
Semi-structured interviews were carried out with ten fifth-year students, who were asked about their perception of the curriculum changes and their thoughts and adaptation strategies.
Results
The results showed that high levels of stress and impaired academic achievements were associated with sudden changes in curriculum. The students perceived the national transition in the curriculum negatively and worse than what they experienced during the pandemic.
Conclusions
Justifying the reasons for curriculum change greatly affected the students’ perceptions. Recommendations for smooth curriculum transition were provided in this research.
Growth Hormone Impact on Psychological Health in Children with Short Stature： An Exploratory Study
Authors: zheng zhichao , Shan Xiaoou , Jin Jiahui , Lu Yili , Rong Xing , Luo Yue , Wu Huiping 
Published: August 2023

Abstract

Background
Growth hormone is widely used in children with short stature. However, the relationship between growth hormone and psychological health remains unclear. Our aim is to explore the correlation between growth hormone and psychology in children with short stature and to evaluate potential confounders.
Methods
All participants were recruited from the Pediatric Endocrine Unit at the Second Affiliated Hospital of Wenzhou Medical University. They were divided into two groups: the growth hormone deficiency group (GHD-G) and the idiopathic short stature group (ISS-G). The Symptom Checklist-90 (SCL-90) was used to assess psychological health. Other confounding variables were studied through background surveys and blood chemistry examination.
Results
Linear regression analysis revealed that a higher growth hormone stimulation peak (GHSP) was associated with a higher score on the SCL-90 (β = 0.027, 95%CI = 0.007 to 0.047, P = 0.00962). This association remained after adjusting for age, sex, and laboratory indices (β = 0.023, 95%CI = 0.003 to 0.043, P = 0.02652). Further analysis showed an interaction between GHSP and luteinizing hormone (LH) (P = 0.0018). When LH was greater than 0.2 U/L, the SCL-90 score increased as the GHSP increased (β = 0.0566, P = 0.0001); however, when LH was less than 0.2 U/L, no significant relationship was found (β = -0.0022, P = 0.8631).
Conclusions
Growth hormone deficiency does not negatively affect psychological health in children with short stature. However, elevated GH levels may have adverse effects on psychological health, especially in adolescents. Therefore, it is important to reassess GH and its potential psychological impact on children with short stature
Design and Optimization of a Transparent and Flexible MIMO Antenna for Compact IoT and 5G Applications
Authors: Abbasi Muhammad Nawaz , Aziz Abdul , AlJaloud Khaled , Chishti Abdul Rehman , Alqahtani Ali H. , Abbasi Durria , Tahir Farooq A. , Khan Zia Ullah , Hussain Rifaqat 
Published: August 2023

Abstract
This work presents an optically transparent and flexible MIMO antenna that features two square patch elements placed in close proximity, aiming to meet the demands of compactness, flexibility, optical transparency, and visual appeal for IoT applications and future 5G wireless communication. The design includes a simple offset feed configuration to achieve the required isolation and impedance matching. It simplifies the process of creating closely spaced transparent MIMO antenna configurations. By optimizing and analyzing this structure, the antenna achieves better isolation and diversity gain performance, even when the patch elements are positioned very close to each other. To achieve optical transparency and flexibility, the antenna uses thin polyethylene terephthalate (PET) material as a substrate, which is a thermoplastic polymer resin from the polyester family. The wired metal mesh parameters for conducting parts of the MIMO antenna and offset position of the feed are carefully optimized to achieve required optical transparency, isolation, impedance matching and radiation performance without any complex decoupling or impedance matching network.
A Hybrid Method Using FABRIK and Custom ANN in Solving Inverse Kinematic for Generic Serial Robot Manipulator
Authors: Bai Ye , Hsieh Sheng-Jen 
Published: August 2023

Abstract

Solving Inverse kinematic(IK) of general robot manipulators remains significant challenge in current industrial manufacturing, particularly in human-robot collaborative scenarios. Most current approaches employ numerical, analytical or machine learning methods to solve IK. However, accurately determining the end-effector(EE) position and capable of handling multiple solutions are unresolved challenges. In this paper, we propose a hybrid method that combines Forward and Backward Reaching Inverse Kinematics(FABRIK) with a custom Artificial Neural Network(ANN) to solve IK for a broad range of serial robot manipulators. The results demonstrate that the hybrid method yields a unique solution and achieves a lower position error(up to 0.002 inches) compared to a standard ANN implementation. Furthermore, compared to the numerical method(FABRIK), the hybrid approach offers a more versatile framework for solving IK, resulting in superior overall performance in terms of solving complexity and accuracy among the three methods.
Devosia lacusdianchii sp. nov., an attached bacterium inhibited by metabolites from its symbiotic algae
Authors: Deng Qing-Lin , Xiao Yao , Jia Ru , Xie Xin , Wang Le , Wang Xin , Yang Jian-Yuan , Zhang Bing-Huo 
Published: August 2023

Abstract
A novel alphaproteobacterial strain JXJ CY 41T was isolated from a culture mass of Microcystis, collected from Lake Dianchi, south-west, China. Strain JXJ CY 41T was gram-negative, aerobic, motile, with rod-shaped cells (0.4–1.0 × 1.7–3.5 μm). It was positive for catalase and starch hydrolysis, negative for oxidase and hydrolysis of Tweens (20, 40, and 80). Growth occurred at 10–44°C, pH 5.0–10.0, and 0–5.0% (w/v) NaCl. Major fatty acids included C16:0 (28.1%), 11-methyl C18:1 ω7c (36.7%) and C18:1 ω7c (20.8%). Q10 was the sole ubiquinone. The polar lipids were diphosphatidylglycerol, phosphatidylglycerol, glycolipid, and an unidentified lipid. The DNA G + C content was 63.1%. Its 16S rRNA gene sequence showed high similarities with Devosia oryziradicis G19T (99.5%; not validly published), D. yakushimensis Yak96BT (98.3%) and D. ginsengisoli Gsoil 520T (98.1%), and less than 98.1% similarities with other members of the genus Devosia. The digital DNA-DNA hybridization (dDDH) and average nucleotide identity (ANI) values between strain JXJ CY 41T and its 5 closest similar strains were 19.9-24.1% and 75.7-80.5%, respectively. Based on these data above, strain JXJ CY 41T was identified as a novel species of the genus Devosia, for which the epithet Devosia lacusdianchii sp. nov. was proposed. The type strain is JXJ CY 41T (=KCTC 72812T=CGMCC 1.17502T). Strain JXJ CY 41T exhibited different interactions with Maf under different conditions, and Maf could control the bacterial cellular density by secreting unknown specific chemical compounds according to algal nutritional requirement.
Development and validation of a prediction model for in-hospital mortality in patients with sepsis
Authors: SHI WEN , Xie Mengqi , Mao Enqiang , Yang Zhitao , Zhang Qi , Chen Yinyin , Ni Tongtian , Chen Erzhen , Chen Ying 
Published: August 2023

Abstract
Objective
The aim of this study is to develop and validate a multivariate prediction model for mortality risks at 28, 42, and 56 days in patients with sepsis in the intensive care units (ICUs) by utilizing locally sourced datasets, eschewing reliance on open-source clinical databases in developing nations.
Methods
A retrospective cohort study was conducted on 2389 sepsis patients admitted to ICUs across two campuses of a tertiary hospital from January 1, 2020, to June 30, 2022. An independently developed clinical decision support system captured electronic data. Enrolled patients were randomly divided into a training set (n = 1673) and a validation set (n = 716) in a 7:3 ratio. Variables identified through Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis were integrated into a multivariate Cox proportional hazards regression model to construct a nomogram. Model accuracy was assessed using the area under the receiver operating characteristic curve (AUROC). Nomogram performance was evaluated for discrimination, calibration, and clinical utility in both sets.
Results
The risk score was developed based on 9 independent predictive factors from an original pool of 32 potential predictors. Notably, the prognostic nomogram revealed the minimum APACHE II score's paramount influence on prognosis, followed by days of mechanical ventilation, number of vasopressors, maximum and minimum SOFA scores, infection sources, gram-positive or gram-negative bacteria, and malignancy. A publicly accessible online calculator implementing this nomogram is available at (https://tingyutongji.shinyapps.io/Nomogram/). The nomogram demonstrated superior discriminative ability, with AUROC values of 0.882 (95%CI, 0.855–0.909) and 0.851 (95%CI, 0.804–0.899) at 4 weeks; 0.836 (95%CI, 0.798–0.874) and 0.820 (95%CI, 0.761–0.878) at 6 weeks; and finally, at week 8, it achieved AUROC values of 0.843 (95%CI, 0.800-0.887) and 0.794 (95%CI, 0.720–0.867) in both training and validation sets. Furthermore, both sets exhibited strong discrimination and calibration, supported by C-indexes of 0.872 and 0.839, respectively, confirmed through decision curve analysis, highlighting the significant net clinical benefit provided by the developed nomogram.
Conclusion
A risk assessment model and web-based calculator have been devised to predict in-hospital mortality among ICU sepsis patients. Targeting factors identified as relevant in the model could potentially enhance survival rates for critically ill patients during their hospital stay.
Clinical outcomes of sentinel node navigation surgery in patients with preoperative estimated stage IA endometrial cancer and evaluation of validity for continuing sentinel node navigation surgery based on dispersion of recurrence probability
Authors: YAMASHITA TSUYOSHI , Itoh Takahiro , Asano Takuya , Suina Asuka , Nishimori Mitsutaka , Munakata Satoru , Satoh Hideki 
Published: August 2023

Abstract
Background To evaluate the feasibility of the use and continuation of sentinel lymph node navigation surgery (SNNS) for patients with preoperative estimated stage IA endometrial cancer
Methods This retrospective study selected the electronic medical records of all patients who had received CT scans and MRI imaging prior to surgery from April 1, 2009 to March 31, 2021. Sentinel lymph nodes (SLNs) were detected by administrating 99mTc-phytate and/or indocyanine green into the cervix, and the clinical outcomes of the patients who underwent SNNS or pelvic lymph node dissection (PLND) were evaluated. Furthermore, in case of recurrence, a procedure to determine whether the facility should continue with SNNS or not was developed that compares the maximum likelihood hypothesis and an alternative one based on recurrence rates.
Results Among 137 patients, SLN biopsies with ultrastaging were performed on 91 patients. The SLN detection rate was 95.6%. During the 59-month median observation period, no statistically significant differences were shown in overall survival, disease-specific survival and disease-free survival between the SNNS and PLND groups when introducing the propensity score method (with p-values of 0.06, 0.153, and 0.625, respectively). Our procedure demonstrated that, in our department without recurrence up to the 65th attempt, it was possible to continue SNNS if a recurrence occurs at the 66th attempt.
Conclusions SNNS for patients with preoperative estimated stage IA does not seem to worsen the prognosis. We confirmed the validity of continuing SNNS by using our procedure even in the absence of evidence like randomized control trials.
Investigation of the quartz cuvette surface contamination used for permanganate quantification in tap water by photothermal lens spectroscopy
Authors: Soyeh Ilhem , Hannachi Riadh , Sammouda Habib 
Published: August 2023

Abstract
In this work, the PhotoThermal Lens (PTL) spectroscopy was used to investigate the contamination effect of the quartz cuvette on the quantification of permanganate concentration in tap water at neutral pH. Different permanganate solutions were prepared at a concentration range from 0.2 µM to 10 µM. The PTL signal measurements performed for samples having the same permanganate concentration in tap water increase continuously. Contrary to the solutions prepared in distilled water where the PTL signal remains constant for all the measurements. Thus, it results from that the main cause of this behavior is related to the decomposition reaction of permanganate in tap water giving rise to manganese dioxide, which then will be adsorbed on the optical window surfaces of the quartz cuvette. The contribution of the adsorbed amount on the PTL signal was examined and its variation was described based on Langmuir model. To remove this contamination effect caused by the adsorption process, three 0.1 M acidic solutions (HCl, H2SO4 and H3PO4) were applied separately for the cleaning of the optical window surfaces. The obtained results show that 4 min is sufficient to reach a desorption rate higher than 90% whatever the used acid.
Design and Implementation of an IoT Drowsiness Detection System for Drivers
Authors: KALLEL Fathi 
Published: August 2023

Abstract
Drowsiness stands as a significant peril to road safety, manifesting as a prominent contributor to severe injuries, fatalities, and substantial economic ramifications within the realm of road accidents. The presence of drowsiness substantially diminishes driving performance, fostering a decline in attentiveness and reaction times. This, in turn, exacerbates the potential for accidents and underscores the criticality of addressing drowsiness-related issues to mitigate the adverse consequences on road safety. The objective of this research work is to design and implement an IoT based intelligent alert system for vehicles, capable of automatically mitigating the risks associated with drowsy driving. Indeed, we propose a real time drowsy driver alert system including a hardware and a software parts. The hardware part includes a camera for face image acquisition and a Raspberry Pi 4 platform for real time face image processing to analyze eye blinks and drowsiness detection. The software part includes a web application for drivers’ management and a mobile application for drowsiness detection and notification management. In fact, once the driver's drowsiness is detected, the system instantaneously sends all details to a wireless connected real-time database and the mobile application module issues a warning message, while a Raspberry Pi monitoring system delivers an audible alert to the driver.
An efficient approach to investigate the learner performance in academia
Authors: Murugan Stalin. M , Kalyani S 
Published: August 2023

Abstract

Now a days, teaching and learning process demands a lot of supervision and analysis to provide quality and easy understanding of subject concepts. Though a lot of innovative approaches are introduced, still looks for efficient mechanism to broadcast the concepts understanding. Many students lose their interest in studies due to traditional way of teaching and memorizing the answers. In addition to that, the assortment of multiple language people and various family background, the investigation of individual student performance still lacks with existing traditional techniques. This paper introduces a novel approaches to deal the students information in higher education level and suggest the hybrid machine learning approaches to provide high quality and amicable education content. The proposed approach investigates ten different traditional machine learning algorithms and finds the optimal solutions. The investigated techniques are evaluated qualitatively and quantitatively using different datasets and yields plausible performance by addressing various challenges.
Swift Augmented Human-Robot Dynamics Modeling for Rehabilitation Planning Analyses
Authors: Akbari Vahid , Mahdizadeh Omid , Moosavian S. Ali A. , Nabipour Mahdi 
Published: August 2023

Abstract
With the widespread implementation of robotics exoskeletons in rehabilitation, modeling and dynamics analysis of such highly nonlinear coupled systems has become significantly important. In this paper, a swift numerical human-robot dynamics modeling has been developed to achieve accurate and realistic interpretation. This takes into consideration the separation and impact between multiple bodies for rehabilitation planning. To this end, first, a novel parallel algorithm combined with sequential interaction conditions is proposed based on the numerical Recursive Newton-Euler method. The approach begins by deriving separated numerical models for the complicated system: i.e. both the human and the robot. These models are then augmented, with a primary focus on reducing the error of the interaction conditions, including positions and forces. To evaluate the proposed model accuracy, the results are compared with a previously validated non-recursive analytical model. Additionally, the quality of the connection between the human and the robot is assessed to establish a suitable control objective and an effective interaction strategy for rehabilitation planning. The study employs a lower-limb walking assistive robot developed in the ARAS lab (RoboWalk) to validate the proposed method. The algorithm is empirically implemented on the RoboWalk test stand, ensuring the integrity of the proposed dynamics modeling. Finally, the effectiveness of the model-based controller is assessed by using the proposed method, providing valuable tools for the enhancement of overall performance of such a complex dynamics system.