bluuebunny/crossref_metadata_2025_split huggingface dataset:
Numerical modeling of the largest event recorded in the most susceptible area to debris flow in Brazil
Authors: CORREA Claudia Vanessa dos Santos SANTOS , Reis Fábio Augusto Gomes Vieira , Giordano Lucília do Carmo , Cabral Victor Carvalho , Veloso Vinícius de Queiroz , D’Affonseca Fernando Mazo 
Published: February 2024

Abstract

Debris flows are rapid downslope, gravity-driven movements of highly viscous, dense and concentrated/hyperconcentrated fluid materials. In Brazil, the most susceptible area to this type of mass movement comprises the oriented foothills of Serra do Mar. Several numerical modeling approaches have been created to measure, identify, predict and monitor debris flow. Rapid mass movement simulation (RAMMS) is a single-phase numerical model that describes the flow frictional behavior using the Voellmy relation. In this work, the RAMMS method is applied to model the debris flow event that occurred in 1967 in Caraguatatuba (State of Sao Paulo). Induced by heavy rains, this debris flow event is one of the largest recorded in Brazil, with more than 100 deaths and major socioeconomic and environmental impacts. Back-analysis studies are applied to assist the model setup and the results evaluations. The simulations suggest that debris flows in the Serra do Mar region are strictly granular, and the debris are preferentially deposited in regions with low slopes (< 5°). The model results can be used to support political and engineering actions aimed at mitigating the effects of future events.
Simulation of Wire Arc Additive Manufacturing of Dissimilar Transition Joint in Steel-Aluminum
Authors: Silva Nilo Nogueira , Coelho Fagner Guilherme Ferreira , Sade Wagner 
Published: February 2024

Abstract

Dissimilar welding of non-ferrous metals can present difficulties since it can result in the formation of very fragile intermetallic compounds. The aim of this study was therefore to perform a computer simulation of the interaction between steel and aluminum using alloy UNS N06625 or copper as the transition joint, with a view to the deposition of dissimilar materials using the wire arc additive manufacturing process. The computer simulation was carried out using Simufact Welding® software, observing the characteristics of the part before carrying out the deposition process, determining the probable properties and dilutions of the selected materials, and the distortions and residual stresses of the part produced. Through this study, it was possible to evaluate the characteristics of the deposition of dissimilar materials by applying alloy UNS N06625 or copper as a transition joint between steel and aluminum and to predict the properties of the part produced by different welding processes.
Multisensory experiences of affective touch in virtual reality enhance engagement, body ownership, perceived pleasantness, and arousal modulation
Authors: Sun Wenhan , Banakou Domna , Świdrak Justyna , Valori Irene , Slater Mel , Fairhurst Merle 
Published: February 2024

Abstract

When engaging in physical contact, our emotional response hinges not only on the nuanced sensory details and the receptive properties of the skin but also on contextual cues related to the situation and interpersonal dynamics. The consensus is that the nature of the affective interactive experience in social touch is shaped by a combination of ascending, C-tactile (CT) afferents mediated somatosensory information, and modulatory, top-down information. The question we pose here is whether, in the absence of somatosensory input, multisensory cues alone can suffice to create a genuinely pleasant, authentic, and engaging experience in virtual reality. The study aims to explore how affective touch is perceived in immersive virtual environments, considering varied social norms in neutral settings or settings like a physiotherapy room where the touch provider is a healthcare professional. We conducted an experiment with 58 male and female healthy adults, where we employed a within-group counterbalanced design featuring two factors: (a) visuo-tactile affective touch, and (b) visual-only affective touch. Findings, drawn from questionnaires and collected physiological data, shed light on how contextual factors influence implicit engagement, self-reported embodiment, co-presence, as well as the perceived realism and pleasantness of the touch experience. Our findings, in line with the literature, indicate that to experience the advantages of touch in immersive virtual worlds, it is essential to incorporate haptic feedback, as depending solely on visual input may not be adequate for fully realizing the optimal benefits of interpersonal touch. Furthermore, in contradiction with our hypothesis, a less ambiguous context (specifically, the physiotherapy room and touch from a physiotherapist) is not linked to heightened touch pleasantness.
Eccentric compressive tests and analytical study of RC columns strengthened with cementitious grout under small eccentric compression
Authors: Peng Gang , Hu Xiaopeng , Niu Ditao , Zhong Shuai 
Published: February 2024

Abstract

In this paper, compressive tests of RC columns strengthened with cementitious grout under small eccentric compression were performed to explore the strengthening response. The effects of reinforcement position and thickness on the failure modes, bearing capacity, ductility, and stiffness of the columns were analyzed. Results indicated that the bearing capacity and corresponding deflection of the columns increased gradually with the increase of reinforcement thickness, and the enhancements in bearing capacity of compressive-side strengthened columns were obviously greater than that of the tensile-side strengthened columns. Simultaneously, the ductility coefficients presented a decreasing trend with the increase of reinforcement thickness while the influence of reinforcement position on the ductility coefficients of the columns did not show consistent variations. Moreover, the stiffness degradation rate of the compressive-side strengthened columns was slower than that of tensile-side strengthened columns, and the stiffness degradation rate of the columns decreased with the increase of the reinforcement thickness. Thereafter, a rational calculation method for predicting the bearing capacity of the columns strengthened with cementitious grout under small eccentric compression was proposed.
A robust optimisation genetic algorithm for HDR prostate brachytherapy including all major uncertainties I: Algorithm implementation
Authors: Kennedy Andrew C. , Douglass Michael J. J. , Santos Alexandre M. C. 
Published: February 2024

Abstract
Introduction
In high-dose-rate prostate brachytherapy, uncertainties cause a deviation from the nominal treatment plan, leading to a possible failure of clinical objectives in the delivered scenario. Robust optimisation has the potential to maximise the probability that these objectives are met during treatment.
Method
A computationally efficient probabilistic robust optimisation algorithm was developed and evaluated comprehensively on one patient by comparing it to the treatment-planning-systems (TPS) optimised plan. Three objective functions were maximised within a genetic algorithm (NSGA-ii), each an approximation for robustness against uncertainty for three clinical objectives: the minimum dose to the hottest 90% of the prostate target, , and the maximum doses to the urethra, ,and the rectum, . The approximations are derived from a probabilistic robust evaluation algorithm incorporating 14 major planning and treatment uncertainties. The robustness of a plan was quantified as a pass-rate from 500 probabilistic uncertainty scenarios for , and .Two hundred robust-optimised plans are generated that are the best trade-off between the three-competing DVH metric pass-rates.
Results
The robust-optimised plans on average (mean) increased in overall robustness by 58.5±3.0%(SD: 7.1%, min: 34.1%, max: 67.7%) compared to the TPS-optimised plan. The robustness increase for the pass-rate was 31.2±2.2%(SD: 15.6%, min: -5.1%, max: 46.7%), for the pass-rate, the increase was 48.2±2.6%(SD: 11.9%, min: 26.9%, max: 67.7%), and for the pass-rate, the change was 0.0±1.1%(SD: 0.72%, min: -2.6%, max: 0.4%).
Conclusion
The robust optimisation algorithm was demonstrated to produce more robust plans than the TPS, in an increased probability of target coverage and organs-at-risk sparing within a clinically reasonable time.
Investigating the efficacy of radiotherapy and photodynamic treatments using gold nanoclusters carrying 5-aminolevulinic acid on the K562 cell line
Authors: Khosravi Hossein , Saeedi Soheila , Goodarzi Alireza , Nikzad Safoora , Amiri Fatemeh , Farmani Abbas 
Published: February 2024

Abstract
Background
In this study, a nanosystem of gold particles functionalized with aminolevulinic acid was used in combination with radiotherapy and photodynamic therapy on the K562 cell line to increase treatment efficacy. One of the benefits of performing this project is to investigate the effects of two combined methods—radiotherapy and photodynamic therapy—on cancer cell lines, which are expected to be useful in cancer treatment.
Methods
The MTT test was used to assess cell viability. First, approximately 10,000 cells were seeded in 96-well plates. The cells were kept in an incubator for 24 hours and then treated with 1.25, 0.625 or 0.3125 mg/mL nanoparticles. In the next step, the plates were treated with a laser for 60 seconds and then 2 or 4 Gy doses of X-rays with an energy of 6 megaelectron volts or vice versa. Cell counting was performed using a slide hemocytometer. To measure MTT levels, commercial kits were used according to the manufacturer’s instructions.
Results
The results of this study showed that the most effective treatment method was laser irradiation before X-rays were applied at a dose of 4 Gy to K562 cells in the presence of gold nanoparticles (4 Gy X-ray + nano + laser before), for which the average survival rate was 27.0120%.
Conclusions
The results of this study showed that gold nanoparticles can be investigated and used as a new treatment option for all types of cancer as a complement to photodynamic therapy and radiation therapy.
A Study on the Feasibility of Optimizing Gastric Cancer Screening to Reduce Screening Costs in China Using a Gradient Boosting Machine: A prospective, large-sample, single-center study
Authors: Fu Xin-yu , Qi Rongbin , Xu Shan-jing , Huang Meng-sha , Zhu Cong-ni , Wu Hao-wen , Ma Zong-qing , Song Ya-qi , Liu Zhi-cheng , Tang Shen-Ping , Lu Yan-di , Yan Ling-ling , Li Xiao-Kang , Liang Jia-wei , Mao Xin-li , Ye Li-ping , Li Shao-wei 
Published: February 2024

Abstract

Background and aim:
The current cancer screening model in our country involves preliminary screening and identification of individuals who require gastroscopy, in order to control screening costs. The purpose of this study is to optimize the screening process using Gradient Boosting Machines (GBM), a machine learning technique, based on a large-scale prospective gastric cancer screening dataset. The ultimate goal is to further reduce the cost of initial cancer screening.
Methods
The study constructs a GBM machine learning model based on prospective, large-sample Taizhou City gastric cancer screening data and validates it with data from the Minimum Security Cohort Group (MLGC) in Taizhou City. Both data analysis and machine learning model construction were performed using the R programming language.
Results
A total of 195,640 cases were used as the training set, and 32,994 cases were used as an external validation set. A GBM was built based on the training set, yielding area under the curve (AUC) and area under the precision-recall curve (AUCPR) values of 0.99938 and 0.99823, respectively. External validation of the model yielded AUC and AUCPR values of 0.99742 and 0.99454, respectively. Through a visual analysis of the model, it was determined that the variable for Helicobacter pylori IgG could be eliminated. The GBM model was then reconstructed without the H. pylori IgG variable. In the training set, the new model achieved an AUC of 0.99817 and an AUCPR of 0.99462, whereas in the external validation set, it achieved an AUC of 0.99742 and an AUCPR of 0.99454.
Conclusion
This study utilized a dataset of 230,000 samples to train and validate a GBM model, optimizing the initial screening process by excluding the detection of H. pylori IgG antibodies while maintaining satisfactory discriminative performance. This conclusion will contribute to a reduction in the current cost of gastric cancer screening, demonstrating its economic value. Furthermore, the conclusion is derived from a large sample size, giving it clinical significance and generalizability.
Efficacy of Intrathecal Mesenchymal Stem Cell-Neural Progenitor Therapy in Progressive MS: Results from a Phase II, Randomized, Placebo-Controlled Clinical Trial
Authors: Harris Violaine K , Stark James , Williams Armistead , Roche Morgan , Malin Michaela , Kumar Anjali , Carlson Alyssa L , Kizilbash Cara , Wollowitz Jaina , Andy Caroline , Gerber Linda M , Sadiq Saud A 
Published: February 2024

Abstract

Background
Mesenchymal stem cell-neural progenitors (MSC-NPs) are a bone marrow mesenchymal stem cell (MSC)-derived ex vivo manipulated cell product with therapeutic potential in multiple sclerosis (MS). The objective of this study was to determine efficacy of intrathecal (IT) MSC-NP treatment in patients with progressive MS.
Methods
The study is a phase II randomized, double-blind, placebo-controlled clinical trial with a compassionate crossover design conducted at a single site. Subjects were stratified according to baseline Expanded Disability Status Scale (EDSS) (3.0-6.5) and disease subtype (secondary or primary progressive MS) and randomized into either treatment or placebo group to receive six IT injections of autologous MSC-NPs or saline every two months. The primary outcome was EDSS Plus, defined by improvement in EDSS, timed 25-foot walk (T25FW) or nine-hole peg test. Secondary outcomes included the individual components of EDSS Plus, the six-minute walk test (6MWT), urodynamics testing, and brain atrophy measurement.
Results
Subjects were randomized into MSC-NP (n = 27) or saline (n = 27) groups. There was no difference in EDSS Plus improvement between the MSC-NP (33%) and saline (37%) groups. Exploratory subgroup analysis demonstrated that in subjects who require assistance for ambulation (EDSS 6.0-6.5) there was a significantly higher percentage of improvement in T25FW and 6MWT in the MSC-NP group (3.7% ± 23.1% and − 9.2% ± 18.2%) compared to the saline group (-54.4% ± 70.5% and − 32.1% ± 30.0%), (p = 0.030 and p = 0.036, respectively). IT-MSC-NP treatment was also associated with improved bladder function and reduced rate of grey matter atrophy on brain MRI. Biomarker analysis demonstrated increased MMP9 and decreased CCL2 levels in the cerebrospinal fluid following treatment.
Conclusion
Results from exploratory outcomes suggest that IT-MSC-NP treatment may be associated with a therapeutic response in a subgroup of MS patients.
Trial Registration
: ClinicalTrials.gov NCT03355365, registered November 14, 2017, https://clinicaltrials.gov/study/NCT03355365?term=NCT03355365&rank=1.
Association between preconception and early pregnancy exposure to fine particulate matter and neural tube defects: A nested case-control study
Authors: Chuang Bao-Ru , Lee Chung-Chin , Lin Yu-Ting , Jung Chau-Ren , Chen Mei-Ling , Hwang Bing-Fang 
Published: February 2024

Abstract

Background
Although several environmental factors may increase the risk of neural tube defects (NTDs), the association between exposure to particulate matter with an aerodynamic diameter of ≤ 2.5 µm (PM2.5) and NTDs is not completely understood.
Objectives
This study aimed to exam the association between expoure to PM2.5 and NTDs during preconception and early pregancy and determine the crucial time windows.
Method
We conducted a nested case-control study from the Taiwan Maternal and Child Health Database between 2004 and 2017. We applied satellite-based models with a 1 km resolution to estimate the weekly average PM2.5 from 3 months before conception to the first trimester of pregnancy. We used conditional logistic regression with distributed lag nonlinear models (DLNMs) to assess the effects of weekly average PM2.5 on the risk of NTDs and exposure-response relationships.
Results
We identified 13,676 incident NTD cases in 2,640,709 participants. There were significant associations between exposure to PM2.5 from 3 months before conception to the first trimester of gestation and the risk of NTDs (odds ratio [OR]: 1.16; 95% confidence incidence [CI]: 1.13, 1.18 per 10 µg/m3 changes), anencephaly (OR: 1.38; 95% CI: 1.08, 1.75 per 10 µg/m3 changes), encephalocele (OR: 1.72; 95% CI: 1.57, 1.87 per 10 µg/m3 changes), and hydrocephalus (OR: 1.12; 95% CI: 1.06, 1.19 per 10 µg/m3 changes). In DLNMs, the risk of NTDs increased from 10 weeks before conception to 19 weeks of gestation. The effects of preconception and early pregnancy exposure to PM2.5 on the risk of NTDs were considerably stronger in pregnant women with diabetes and preeclampsia and infants with low birth weight (< 2,500 g) than those without these conditions.
Conclusion
Our findings suggest that exposure to PM2.5 during preconception and early pregnancy may increase the risk of NTDs in offspring. Moreover, low birth weight, gestational diabetes, and preeclampsia increase the risk of NTDs associated with maternal exposure to PM2.5.
Characteristics, Outcomes and Prevalence of Pregnant Women with Placenta Accreta Spectrum in Black Lion Hospital - Five years retrospective study , Addis Ababa, Ethiopia, 2023
Authors: Mohammed Fuad Ahmed , Wube Yared Tesfaye , Gondere Fikremelekot Temesigen , Tesfaye Kiflom 
Published: February 2024

Abstract
Background
Placenta accreta spectrum is known to be associated with significant maternal morbidity and mortality usually because of catastrophic hemorrhage during delivery. The Prevalence rates ranged from 0.01 to 1.1% with an overall pooled prevalence of 0.17% (95% confidence interval, 0.14–0.19). The aim of this study was to determine the prevalence, characteristics and outcome of pregnant mothers with placenta accreta spectrum in black lion hospital.
Methodology: An institution based
cross-sectional study from January 1, 2018 to December 31, 2022. FIGO classification system for the clinical diagnosis of placenta accreta spectrum disorder were used to define cases and enroll the participants. Data was cleaned, entered and analyzed using SPSS version 26.0 statistical software and MS excel. Descriptive statistics were used to describe baseline characteristics.
Result
From the 24,844 deliveries, prevalence of cesarean delivery- 37.3%; prevalence of placenta accreta spectrum to be 0.1% (1 out of 994) and of which, 16 (64%)- abnormally adherent type (grade 1) and 9 (36%)-abnormally invasive type [grade 2 (24%) and grade 3 (12%)]. Placenta accreta spectrum was suspected prenatally in 28% of the mothers. Risk factors identified in 92% (23 out of 25) of the mothers were either placenta previa or cesarean delivery; in 60% (15 out of 25) of the mothers both placenta previa and prior cesarean delivery. Average estimated blood loss of 1568 (± 849) ml and 17 out of 25 (68%) were transfused. There was no maternal death and intensive care unit admission.
Conclusion and Recommendations:
The prevalence of cesarean delivery is very high as compared to the national figure. Antenatal suspicion or prenatal diagnosis of placenta accreta spectrum is very low thus all pregnant mothers with risk factors especially mothers with cesarean delivery and placenta previa should be screened for placenta accreta spectrum. Mothers with suspected placenta accreta spectrum should be managed with optimal preparation as possible.
Assessing Water Quality in Rivers Flowing into the Caspian Sea in term of pollution using Water Quality Indices and Remote Sensing indices
Authors: Mokarram Marzieh , Behrooz Reza Dahmardeh , Pourghasemi Hamid Reza 
Published: February 2024

Abstract

Ensuring the water quality of the rivers flowing into the Caspian Sea is crucial for preserving the delicate ecosystem and safeguarding the environmental health of the region. In this study, objectives encompassed determining water quality using various indices, creating zoning maps through ordinary kriging to identify contamination locations, employing Principal Component Analysis (PCA) to identify crucial parameters, and establishing the relationship between water quality indices and spectral reflections. The results revealed significant variations in pollution levels across the studied rivers. The Haraz River exhibited the highest chemical pollution (chemical Water quality index (WQI: 0.87), while the Talar River demonstrated the highest physical WQI (6.36) and overall water pollution (6.53). Additionally, the Babolroud River registered the highest pollution in the Dissolved Oxygen Deficit Index (DODI) (84.12) and Dissolved Oxygen Saturation (Dosat) (7.45), while the Talar River topped Domeasured (18), and both the Talar and Haraz rivers were identified as the most polluted based on the Pollution Load Index (PLI) (26.21) and Eutrophication Index (EI) (120.68), respectively. Utilizing the PCA method highlighted the pivotal role of the chemical WQI (-0.932 and − 0.896) in assessing water quality in the Babolroud and Talar Rivers, while the Dosat index (0.943) emerged as crucial for accurate evaluation of the Haraz River. Further analysis of the relationship between water quality and remote sensing indices revealed the pronounced association of unveiled the Modified Normalized Difference Water Index (MNDWI) index pronounced association with chemical WQI in the Talar River (coefficient: -0.705) and the robust correlation between Dosat and the MNDWI in the Haraz River (correlation rate: -0.824). Conversely, the Talar River exhibited a direct correlation between the chemical WQI and BSI (correlation level: 0.827), indicative of increased turbidity.
Artificial Honeybee Colony Algorithm: An Adaptive Optimization Method for Generating Migrating Search SpacesOptimization Method for Generating Migrating Search Spaces
Authors: Nichols Alec Chandler , Mulani Sameer B , Phillips Sean 
Published: February 2024

Abstract

Leveraging the adaptive characteristics of biological superorganisms, the Artificial Honeybee Colony (AHC) algorithm is an agent-based algorithm that integrates pollination models, particle swarm dynamics, and mutualistic plant-pollinator relations to generate new solution spaces and search for and generate resilient (or optimal) solutions to complex or nonlinear problems. The search space or environment adapts as solutions propagate using a density clustering algorithm, where only the higher quality solutions survive to cultivate into increasingly denser clusters via a pollination model. For verification, the AHC's capabilities were tested against particle swarm optimization and gradient descent with golden sections search for five benchmark functions given three different initial guesses ranging in proximities to the optimal solution. The AHC outperformed the other two methods in all five tests, locating optimal solutions in every case regardless of the initial guess' proximity to the optimum. Additionally, a global sensitivity analysis determined the most sensitive tunable parameter to be the pollination cluster radius, which determines the area new solutions appear within at each iteration via pollination. The results of these tests and applications demonstrate how the AHC's adaptive characteristics are beneficial in optimizing the resilience of highly interconnected, nonlinear, or complex problems where the user may have little to no former knowledge or intuition.