bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficacy and safety of conversion therapy with Fluorouracil, Leucovorin, Oxaliplatin and Docetaxel (FLOT) in unresectable advanced gastric cancer
Authors: Zheng Lijun , Jiang Xun , Liu Zhongcheng , Lu Liesheng 
Published: December 2023

Abstract
Objectives: FLOT protocol has recently been applied in the neoadjuvant treatment for locally advanced, resectable gastric or gastroesophageal junction adenocarcinoma, while the application of FLOT regimen in conversion therapy of unresectable gastric cancer, especially in comparing the efficacy of FLOT regimen with traditional S-1 and oxaliplatin (SOX) regimen, remains to be explored. We performed a retrospective analysis to investigate the efficacy and safety of FLOT regimen in conversion therapy of unresectable advanced gastric cancer.
Methods: A total of 49 patients with unresectable advanced gastric cancer who received conversion therapy of SOX and FLOT was retrospectively analyzed from January 2019 to June 2020. The patients were divided into two groups: SOX (n=23) and FLOT (n=26). Clinical efficacy, adverse reactions, surgical safety and short-time survival of patients was compared between the two groups.
Results: The follow-up time was 24-42 months up to June 2022. No significant difference was
found between the baseline data of SOX group and FLOT group. After conversion chemotherapy, ORR in the FLOT group was significantly higher than that in SOX group (80.8% vs. 47.8%, p=0.016). There were significant differences in surgical conversion rate (52.2% vs. 80.8%, P=0.033) and TRG (P=0.041) between SOX group and FLOT group. The incidence of adverse events (AEs) was 100%. The majority of the patients had grade 1 to 2, and there was no significant difference between the two groups in the incidence of serious adverse reactions of grade 3 to 4. The operative time (213.75±26.41 min vs. 214.91±30.68 min, P=0.914), intraoperative blood loss (263.33±43.24 ml vs. 276.90±81.02 ml, P=0.535), R0 resection rate (83.3% vs. 90.5%, p=0.960) and overall postoperative complication rate (41.7% vs. 38.1%, p=1.000) was not statistically different between the two groups. There were significant differences in 2-year overall survival (OS) rate and overall median survival time between SOX and FLOT group. (2-year OS: 29.8% vs. 61.1%, overall median survival time: 16 months vs. 30 months; P=0.045)
Conclusion: FLOT regimen is safe and effective in the treatment of locally unresectable gastric cancer. Compared with SOX regimen, FLOT regimen in conversion therapy can improve the surgical conversion rate, R0 resection rate and overall survival time of patients.
Lightweight Safflower Cluster Detection Based on Yolov5
Authors: Guo Hui , Wu Tianlun , Gao Guoming , Qiu Zhaoxin , chen Haiyang 
Published: December 2023

Abstract
Safflower detection technology in the field has a crucial role in automated harvesting and the acquisition of row navigation information. Due to the small overall size of safflower clusters, their distribution is relatively dense. The environment between rows is complex, and as a result, uneven lighting severely hinders the detection of clusters. Current safflower bulb detection technology suffers from insufficient detection accuracy and a large amount of computation and complexity, which is not conducive to the deployment of automation and intelligent harvesting robots.
To address the above issues, this study presents an enhanced SF-YOLO model for target detection that substitutes Ghos_conv for the conventional convolutional block in the backbone network, for improved computational efficiency. To improve the model's characterisation ability, the backbone network is embedded with the CBAM attention mechanism. The introduction of a fusion L(CIOU+NWD) loss function enhances the accuracy of feature extraction and expedites loss convergence, thus allowing precise feature extraction and improved adaptive fusion while accelerating loss convergence. Hence, the model becomes more adaptive and faster at feature extraction. The updated K-means clustering algorithm yields anchor frames, which substitute for the original COCO dataset anchor frames. This enhances the model’s ability to adjust to multi-scale safflower information across farmlands. The model’s adaptability to multi-scale information between rows of safflowers on the dataset is enhanced through data augmentation techniques such as Gaussian blur, Gaussian noise, sharpening, and channel disruptions. This ensures better robustness against illumination, noise, and angle changes. SF-YOLO surpasses the original YOLOv5s model in tests on a self-constructed safflower dataset under complex background information, where GFlops decrease from 15.8 G to 13.2 G, and Params from 7.013 M to 5.34 M, for respective reductions of 16.6% and 23.9%, and 𝑚𝐴𝑃0.5 improves by 1.3%, to 95.3%. Safflower detection accuracy is enhanced in complex farmland environments, serving as a reference for the subsequent development of autonomous navigation and non-destructive harvesting equipment.
Application of AccuContour Software for Designing Vertebral Organ at Risk Models of Pediatric Tumors
Authors: Zhao Wenchao , Hu Miwan , Yuan Longhui , Deng Tan 
Published: December 2023

Abstract
Background: The AccuContour software was used to outline the spine and lumbar spine of children with solid tumors separately to evaluate and compare the outline effect, which provided the basis for the subsequent establishment of automatic outline models of the cervical and thoracic spine and further improved the accuracy of vertebral body outline.
Methods: Forty-three children with solid tumors were selected as group A, from which 37 children with solid tumors with intact lumbar vertebrae in the localized CT images were selected as group B, and were respectively imported into the artificial intelligence outlining system for manual outlining. In group A, all vertebrae in the image were outlined, and in group B, only the lumbar vertebrae were outlined, and the outlined images were deep-learnt in the system to establish the automatic outlined model A and model B. Thirteen children with solid tumors were selected, and the same children's vertebrae were automatically outlined based on models A and B, and manually outlined at the same time. The volume difference, position difference and shape consistency of the vertebral bodies were evaluated and compared between the automatic and manual outlining.
Results: Statistical analysis of the data from Model A and B groups showed statistically significant differences in ΔV%, HD95, and DSC （Dice Similarity Coefficient, DSC）values (P<0.05).
Conclusion: The artificial intelligence automatic outlining system has a high accuracy in outlining vertebrae, and the accuracy of outlining lumbar vertebrae alone is higher than that of outlining all vertebrae within the image, and the automatic sketching models of cervical and thoracic vertebrae can be established subsequently to further improve the accuracy of vertebrae sketching.
Sexual Desire and Erotic Fantasies questionnaire: Development and validation of the Sexual Desire scale (SDEF1)
Authors: Nimbi Filippo Maria , Galizia Roberta , ciocca giacomo , Zimic Aleša Bratina , Jannini Emmanuele , Simonelli Chiara , Tambelli Renata 
Published: December 2023

Abstract

The main aim of the present study was to test the psychometric properties of the Sexual Desire and Erotic Fantasies questionnaire - Part 1 Sexual Desire (SDEF1), developed as a sex-positive measure of different sexual desire expressions. The SDEF1 was assessed with 1,773 Italian participants (1,105 women, 645 men, and 23 other genders). The final version showed a 6-factor structure including 28 items: sexual desire, negative feelings to sexual desire, autoerotic desire, regular partner desire, attractive person desire, and responsive desire. The SDEF1 revealed good psychometric properties such as internal reliability, construct, and discriminant validity, and has shown to be able to differentiate women and men with and without sexual dysfunctions/problems. Results of the current study seem to validate the idea that the SDEF1 could be a useful measure to assess different areas of sexual desire and its use could be recommended for clinical and research purposes.
Evaluation of the diversity and uniqueness of woody plant communities in park forests transformed form forest patches on urban hills
Authors: Ning Qu , Shilei Zhang , Wang Zhikang , Li Chunlin , Liangzhen Zhang , Sun Lintng , Zhiquan Cao , Qing Qin , Fan Peixian 
Published: December 2023

Abstract

In the process of urbanization, forest patches on hills are transformed into urban park forests, their functions changing from production to ecological and landscape. The diversity and uniqueness of plant communities support the ecological and landscape functions of parks, but there is a lack of indicators and methods to assess their uniqueness. We propose two evaluation indicators for woody plant community uniqueness in urban parks based on importance value (IV, the average of relative abundance, relative frequency, and relative dominance): the mean non-overlapping IV (MNIV) and the local contribution to beta diversity based on IV (LCBD1). Subsequently, we investigated and evaluated the diversity and uniqueness of woody plant communities in eight hill parks (Parks 1–8) in Qingdao. A total of 101 species were found, with an average of 23.88 ± 5.96 species per park. The Shannon-Wiener and Pielou indices were in the ranges of 1.42–3.13 and 0.48–0.91, respectively. Results from principal coordinate analysis and cluster analysis and the orders of MNIV and LCBD1 suggest that Parks 4 and 8 have the most unique woody plant communities. MNIV was significantly (P < 0.05) positively correlated with Shannon-Wiener and Pielou indexes, while LCBD1 was significantly (P < 0.05) positively correlated with local beta diversity based on species abundance. MNIV and LCBD1 were significantly (P < 0.05) negatively correlated with IV of Pinaceae and significantly (P < 0.05) positively correlated with IVs of Anacardiaceae, Cannabiaceae, and Ginkgoaceae plants. Therefore, diversities of woody plant communities from residual forest patches show great variations. The diversity and IVs of characteristic plants are key factors affecting uniqueness.
Continuously increasing e-scooter accidents and their possible prevention in a large European city
Authors: Frank Stefan , Sator Thomas , Kinsky Rudolf M. , Frank Julia K. , Frank Roland , Fialka Christian , Mittermayr Rainer , Boesmueller Sandra 
Published: December 2023

Abstract

Purpose
During the last few years, the number of electric scooter (e-scooter) users has risen to an all-time high. This study aimed to analyze e-scooter related accidents and trauma prevention measures in a large European city (Vienna, Austria).
Methods
This retrospective study comprises a thorough data assessment and analysis of all e-scooter related accidents between 2018 and 2021 at a large level 1 trauma center in Vienna. Based on the data analysis, risk factors were identified, and possible prevention strategies were proposed.
Results
During the observed period, 1337 patients sustained an injury from an e-scooter. Of these, 1230 were injured directly while driving (92%). The remaining 107 patients (8%) were classified as non-driving injuries. 927 injuries involved males (69.3%). The mean age was 32.1 years (range 4–86 years). Of all injured patients, 429 (32.1%) sustained at least one serious injury. The most common injuries included radial head fractures and concussions. Among the accidents treated, the use of protective equipment was sporadic. For example, helmets were worn in only 13.7% of cases. Wearing a helmet reduced the number of head injuries (24% versus 46.8%). In just three years, the number of patients increased 19-fold with a focus in the summer months.
Conclusion
This study shows a substantial and sustained increase in e-scooter accidents with potentially serious injuries. Helmet use was found to be an effective form of head injury prevention. Further options for using protective equipment should be evaluated to improve the safety aspects of riding e-scooters.
Construction and Validation of Sprinkler Pattern Radius Computational Model
Authors: Tuo Yunfei , Lu Qiwei , Liang Jiaping , Xiang Ping , Yang Qiliang , Li Jianqiang , He Xiahong 
Published: December 2023

Abstract
In ascertaining the sprinkler and micro-sprinkler computational approach. computing models of sprinkler pattern radius were generated in accordance with hydraulic parameters such as, nozzle diameter(E), working pressure(P), installation heights(D), jet angle of sprinkler flow(A), discharging coefficient(µ), wind direction(WD) and wind Speed (WS), water flow state, and motion of water droplets in the air, as well as accounted for Newton's second law of motion, aerodynamics, and fluid mechanics principles. Furthermore, it was confirmed that the empirical formula for the typical sprinkler pattern radius, which related E, P, A, D, WD, and WS. The results demonstrated a substantial correlation between the sprinkler pattern radius and E, P, D, A, μ, WD, WS, water flow regime, and droplet motion in the air, the sprinkler pattern radius increased in the downwind by 5.2342%-10.6278%, and decreased in the headwind by 4.6897%-9.8623% than the absence of wind, additionally, the direction of sprinkler pattern radius changed with the WD altered, meanwhile, sprinkler pattern radius dropped with WS increased. Between the calculated and measured values of the computational model, the r2(coefficients of determination), c(coefficient of concordance), RMSE(mean root square error), MBE(mean bias error), MAE(mean absolute error), and MRE(mean relative error) were 0.9146, 0.9205, 8.7748%, 10.4980%, 8.2524%, and 8.1421%, respectively, the computed values and measured values of computational model in wind had fewer r2 and c, as well as bigger RMSE, MBE, MAE, and MRE compared to no wind. This study's computational model features a straightforward concept, a wide range of influencing factors, full physical significance, high computational accuracy, a negligibly small error, and broad applicability, the sprinkler pattern radius as it changes can be accurately reflected by the computer model, this study offers theoretical support for estimating sprinkler hydraulic performance as well as technical backing for sprinkler irrigation system strategy and design, it has significance for promoting the sprinkler irrigation quality.
Empowering Dysarthric Communication: Hybrid Transformer-CTC based Speech Recognition System
Authors: R Vinotha , D Hepsiba , Anand Vijay 
Published: December 2023

Abstract

People suffering from speech disorders face various challenges in their ability to communicate effectively, and one of the conditions they may experience is dysarthria. Dysarthria is a motor speech disorder that impacts an individual's ability to speak due to difficulties in controlling the muscles responsible for speech production. People with dysarthria may experience difficulties with articulation, pronunciation, intonation, rhythm, and pace, resulting in a slow or slurred speech pattern that can be difficult to understand. Augmentative and Alternative Communication (AAC) aids that utilize speech recognition technology have emerged as an appealing solution to support communication for individuals with dysarthria. Automatic Speech Recognition (ASR) systems trained solely on normal speech data may not accurately recognize dysarthric speech due to variations in their speech patterns and accent differences. However, a significant challenge in training ASR systems for dysarthric speech is the limited availability of data. To overcome these challenges, a hybrid architecture using the Transformer and Connectionist Temporal Classification (CTC) approach is proposed in this work. The transformer architecture is effective in learning speech patterns using limited data due to its self-attention mechanism, while the CTC approach allows for direct mapping between input speech features and output character sequences without requiring explicit alignment information. This approach is especially beneficial for speech recognition in situations involving variations in speech patterns. A hybrid architecture is trained using UA speech corpus that allows it to focus on important features of the speech and capture the relationships between them, leading to more accurate speech recognition. The performance of the proposed ASR system shows a remarkable decrease in Word Error Rate (WER) up to 2.78% and 15.67% for individuals with dysarthria who have low and very low intelligibility, respectively.
Nanofibrilation of alkali-pretreated cellulose fiber using grinding treatment
Authors: Hwang Kyojung , Park Jisoo , Lee Danbee , Gwon Jaegyoung , Chun Sang-Jin , Lee Tai-Ju , Seo Jin-Ho 
Published: December 2023

Abstract

The aim of this study is to explore the effect of strong alkali-pretreatment on manufacturing cellulose nanofibril s(CNFs) with mechanical (grinder) treatment. The structural change (from cellulose I to cellulose II) and sharply reduction in the yield of hemicellulose component (xylose) of cellulose fibers (bleached kraft pulp) were observed after strong NaOH (20 wt.%) pretreatment. However, the differences depending on treatment time (1 h or 2 h) were not significant. The subsequent mechanical (grinder) treatment did not lead to any significant changes in the chemical composition, specifically the sugar contents, of the cellulose fiber. Morphological analyses showed that generated micro- and nano-fibers in the suspension were gradually decreased with increasing mechanical pass number. Also, the mean width of the nanofibers produced from alkali-pretreated pulp was relatively thicker than those from untreated pulp. UV-transmittance and turbidity results showed that alkali pretreatment and subsequent mechanical treatment led to an increase in the nanofibril content. Therefore, alkali pretreatment and subsequent mechanical grinding provide a promising method for the efficient and cost-effective production of CNFs.
Investigating the social factors shaping the relationship between child marriage and mental health: Lessons learned from a pilot survey in Zimbabwe
Authors: Shibani Farah , Gumbonzvanda Farirai , Gumbonzvanda Nyaradzayi , Marufu Kensington , Linjesa Latih , Mugaragumbo Hildah , Musara Loveness , Musara Ethel , Mandewo Jean , Mombeshora Solomon , Mushunje Mildred , Ismail Miriam , Magama Nokutenda , Burgess Rochelle A. 
Published: December 2023

Abstract
Purpose: In Zimbabwe, 1 in 3 girls are married before 18, yet no studies focus explicitly on the relationship between child marriage and mental health. We conducted a pilot survey (n=100) to investigate the associations between common social factors linked to early and child marriage including: age, number of children, education level, unwanted pregnancies, and main source of income, with mental health
Methods: Survivors aged 15-50 years completed researcher-facilitated surveys, which included the Shona Symptom Questionnaire (SSQ) and Patient Health Questionnaire (PHQ-9) and demographic questions adapted from the Zimbabwean DHS.
Results: 68% of participants met the cut off for diagnosis of common mental disorders (CMD) based on the SSQ. Our logistic regressions showed with an increase in age, survivors were 1.06 times more likely (p = 0.05, CI = 1.00, 1.13) to meet criteria for a CMD. We also found that those with unwanted pregnancies were 5 times more likely to meet criteria for CMDs (AOR= 5.33, p < 0.01, CI= 1.94, 14.63), in comparison with those with wanted pregnancies. Finally, we found family/partner income reduced the odds of depression by 84% (AOR= 0.16, p < 0.04, CI= 0.03, 0.90), in comparison with those with no income or had selected ‘own business/self’ as their main income source.
Conclusions: Findings suggest the value of longitudinal cohort studies in this population to identify the strategic point of intervention for survivors who face high risk for mental health disorders.
Evaluation of Oxidative Stress Parameters and Histopathological Changes Due to Simultaneous Exposure to Toluene and High Noise Level in Lung Tissue of Adult Male Rats
Authors: Beyrami Sona , Gharari Noradin , niri Hasan Hadadzadeh , Farhang Somayeh , Abbaszadeh Hojjat Allah , Mahmoudi Saeed , Fazlzadeh Mehdi 
Published: December 2023

Abstract
Background
Concurrent exposure to noise and toluene is a common occurrence in industrial environments. This study is conducted to evaluate oxidative stress parameters and histopathological changes when simultaneously exposed to loud noise and toluene.
Methods
For this purpose, 32 male Wistar rats in four experimental groups (n = 8 in each group) were used. 1- control group, 2- the group exposed to an 8 kHz octave band noise (100 dB) (8h/day), 3- the group exposed to toluene (500 ppm) (8h/day), 4- the group simultaneously exposed to noise (100 dB) and toluene (500 ppm) (8 h/day). In this study, DNA damage is evaluated by 8-hydroxy-2-deoxyguanosine (OHdG-8) concentration measurement using the ELISA kit, and lipid peroxidation (MDA) and glutathione (GSH) levels are determined throughout lung tissue.
Results
The results partially showed that concurrent exposure to loud noise and toluene could lead to pathological damage to rat lung tissue. Besides, the elevation of OhdG-8 levels and MDA production in the lung was observed, and on the other hand, the GSH level dropped during the simultaneous exposure.
Conclusions
The results of this study confirmed that the interaction of noise and toluene increases the accumulation of DNA oxidation products, and progressive morphological damage, and also weakens the antioxidant defense system in the rat lung tissues.
Emerging Technologies and Sustainability in Brazilian Ports and Terminals: An Analysis of the Current Situation
Authors: Resende Renilson José Silva , Cunha Darliane , Porte Marcelo de Santana , Oliveira Clóvis Bôsco Mendonça , Cutrim Sérgio Sampaio 
Published: December 2023

Abstract
In the face of the growing demand for maritime transportation in the global economic context, ports are under increasing pressure from stakeholders to enhance their operational effectiveness and address environmental issues such as air and water pollution and inherent energy and security challenges. The transition to smarter and environmentally responsible ports is perceived not only as a choice but a strategic necessity, considering the multifaceted demands of the current global landscape. The Sustainable Development Goals offer a comprehensive framework to guide this evolution. In the Brazilian context, this paper aims to explore the impact of emerging technologies on the sustainability of Brazilian port industry. The research explores how such technological advancements influence the sustainability of the Brazilian port sector, considering their potential to drive sustainable practices and enhance operational efficiency. The study focused on Brazilian ports and terminals with the highest cargo volumes, including a sample of 23 port entities. The methodology adopted consisted of content analysis of sustainability reports published by the study's companies. An analysis of the sustainability reports of Brazilian ports and terminals reveals a diversity of technologies in continuous application. Technologies such as cameras, radar systems, artificial intelligence, and vessel traffic services, among others, are assuming multifaceted roles encompassing environmental monitoring, maritime traffic management, operational optimization, and security assistance. These technological advancements bolster the efficiency and safety of port operations and contribute significantly to sustainability efforts by facilitating early issue detection and mitigating environmental impacts. Furthermore, they create a pathway for the integration of emerging technologies like the Internet of Things and machine learning, offering the promise of additional efficiency gains and innovative solutions within the port sector.