bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and fabrication of carbon fiber lattices using 3D weaving
Authors: McClintock Hayley , Lipson Hod , Xiong Zechen , Rergis Bruno
Published: April 2023

We present a method of designing and fabricating 3D carbon fiber lattices. The lattice design and fabrication is based on crocheting and sewing techniques, where carbon fiber tow is woven through two parallel carbon fiber grids and reinforced with vertical carbon fiber tubes. This process allows for more design flexibility than other current methods. For example, within a single lattice, different density weave patterns can be used to address specific load requirements. Though fabricated manually here, this process can also be automated for large scale production. With this design flexibility, simplified fabrication, and high strength, the lattices proposed here offer an advantage as compared to similar existing structures.
GPU based High-Efficiency PSO Algorithm with Initialization strategy and Thread Self-adaption
Authors: Liu Ye , Wu Jia , Ren Hui , Yang Shuopeng , Zhang Fuqiang
Published: April 2023

Particle Swarm Optimization (PSO) is a widely employed heuristic-based method that effectively addresses a variety of optimization problems owing to its simplicity and robustness. Despite its advantages, PSO's extensive computational demands can hinder its practical applications. As parallel computing and Graphics Processing Units (GPUs) have advanced, researchers have explored these technologies to overcome the computational efficiency limitations of PSO. This paper presents a High-Efficiency PSO (HEPSO) algorithm, which optimizes the PSO process within a GPU-based architecture. The HEPSO algorithm enhances GPU computational performance by: 1) transferring the data initialization process from CPUs to GPUs, minimizing the I/O overhead resulting from repetitive data migration during computation. 2) implementing a self-adaptive thread management strategy to improve algorithm execution efficiency. To evaluate the efficacy of HEPSO, we conducted experiments using four benchmark optimization functions. Our findings indicate that the time speedup ratio of HEPSO compared to GPU-PSO exceeds sixfold. Furthermore, when assessing the time required for function convergence, HEPSO outperforms GPU-PSO, necessitating only 1/3 of the time in most instances.
Effectiveness of Parallel Computer Data and Video English Course Based on Neural Network
Authors: She Min , Zhang Fen
Published: April 2023

With the expansion of the scale of deep learning network and the rapid increase of the number of network training parameters, the network training time is getting longer and longer. In deep learning, convolutional neural network reduces the number of some parameters through weight distribution, but the problems such as large number of parameters and long network training time still exist. This paper implements convolutional neural network in distributed environment, and proposes parallel computer data and time-based scheduling strategy to optimize distributed convolutional neural network. This paper also studies the effectiveness of video English curriculum. It is found that with the development of network technology, information technology is more and more widely used in the education industry, and students can realize distance autonomous learning. At present, the network teaching platform is diversified, with the functions of knowledge point learning, online examination and so on. Aiming at the problems existing in the video English course, the project response theory is introduced into the design and development of the platform system. Taking college users as the research object, this paper constructs a data model of College Students' learning behavior, provides all-round services for college students, and improves the effectiveness of video English teaching. At the same time, based on the project response theory, this paper analyzes the current situation of College Students' autonomous learning, so as to improve the efficiency of College Students' autonomous learning. Based on neural network, this paper makes an in-depth study on parallel computer data and video English course, hoping to bring some help to the improvement of College Students' English learning.
Application of Marxist-Based Science and Technology Theory in the Ethical Review of Artificial Intelligence Robots
Authors: Huang Huiling , Zhong Shengbiao
Published: April 2023

Marxist scholars' research on science and technology spans multiple levels of business, politics, and society. At the economic level, Marxist scholars recognize the contribution of science and technology to economic development. At the political level, Marxist scholars strictly define the relationship between science and technology and ideology. At the social level, starting from the value dimension of the moral level, Marxist scholars reflect the application of science and technology, and have great educational value and reference value for the systematic research of Marxist science and technology theory with Chinese characteristics socialist modernization. In order to obtain the best PMU configuration, this article first optimizes a single target with the number of configurations as the goal, and proposes a hybrid optimization algorithm that combines graph theory and artificial intelligence technology. Then a PMU failure analysis principle is proposed, which focuses on the configuration and error amount of the entire network, and uses an improved genetic simulated annealing algorithm to perform multi-objective optimization. It has high application value in the PMU configuration of large-scale systems, which is inseparable from the development of artificial intelligence robots and the integration of moral systems. Only by integrating moral systems into the development of AI robots can the human needs of AI robots be truly met. This is not only aimed at filling many gaps in the development of AI robots, but also aimed at maintaining the moral system of human beings. In addition, without the support of an ethical system, only technology can promote the development of artificial intelligence robots. In all the behaviors of artificial intelligence robots, we will implement the principle of "harmony" and realize the harmonious coexistence of artificial intelligence robots and humans.
Soft-Stable Interface in Grasping Multiple Objects by Wiring-tension
Authors: Nguyen Van Pho , Bohra Dhyan Sunil , Chow Wai Tuck
Published: April 2023

Efficiently manipulating objects in a group state is an emergent challenge for the soft robot hands. Overcoming this problem requires such hands to have highly stable structures to bear the heavy loads and highly compliant design to universally adapt to diverse object geometries. This study proposed a novel platform to develop the robot hands in manipulating multiple objects at each trial. In this scenario, the objects were in soft contact with an elastic wire mounted on the finger skeletons. This combination formed a harmonious hybrid finger that inherited both the soft flexible properties of the wire and the strong-stable bearing of the finger skeleton. One theoretical model was proposed to estimate the kinematics of manipulating multiple objects by the wiring-based fingers. Based on this model, we designed a hybrid gripper comprising two wiring-based fingers for conducting experimentally evaluations in manipulating four group samples: double bevel gears, double bevel gears plus pneumatic connector, double glue bottles, and double silicon bottles. The experimental results indicated that our proposed gripper reached good performance with high success rates in durability tests at different levels of the lifting velocity and high adaption with objects in soft-friendly interaction. These outcomes are potential to efficiently manipulate multiple complex objects per trial without requiring complicated controls.
Urinary 18-hydroxycortisol is superior to plasma 18-hydroxycortisol for primary aldosteronism subtyping
Authors: Rao Menghua , She Xuhui , Ma Wenjun , Bian Jin , Zhao Beibei
Published: April 2023

Urinary and plasma 18-hydroxycortisol (18-OHF) have been investigated for primary aldosteronism (PA) subtyping. However, there is no research exploring the impact of sample types on the diagnostic performance of 18-OHF in PA subtyping. In this study, 18-OHF levels in both urine and plasma were determined in patients with idiopathic adrenal hyperplasia (IHA), aldosterone-producing adenoma (APA), and essential hypertension (EH) by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Urinary18-OHF was determined using an established LC-MS/MS method, whereas plasma18-OHF was measured by a modified LC-MS/MS method. Differences in urinary and plasma 18-OHF levels between APA, IHA, and EH patients were investigated by Kruskal-Wallis test for non-parametric analysis. The LC-MS/MS method yielded a lower limit of quantitation (LLOQ) of 18-OHF in urine of 4.28 nmol/L and 0.190 nmol/L in plasma. The intra- and inter-precision for urine and plasma methods were < 6%, with accuracies between 95.9% and 110.3%. Urinary and plasma 18-OHF in 12 IHA, 18 APA, and 91 EH patients were quantified and analyzed. Non-parametric analysis by Kruskal-Wallis test revealed that urinary 18-OHF levels in IHA and APA patients were significantly different (P < 0.05) while plasma 18-OHF levels were not (P > 0.05), indicating that urinary 18-hydroxycortisol outperformed plasma 18-hydroxycortisol for primary aldosteronism subtyping.
Current observations on shifts in malaria vector biting behavior and changing vulnerability to malaria transmission in contrasting ecosystems in Western Kenya
Authors: Nzioki Irene , Machani Maxwell G. , Onyango Shirley A. , Kabui Kevin K. , Githeko Andrew K. , Ochomo Eric , Yan Guiyun , Afrane Yaw A.
Published: April 2023

Background: Designing, implementing, and upscaling effective malaria vector control strategies necessitates understanding of when and where transmission occurs. This study assessed the biting patterns of potentially infectious malaria vectors at various hours, locations, and human behavior in different ecological settings in western Kenya.
Methods: Hourly indoor and outdoor catches of human-biting mosquitoes were sampled from 1900 to 0700 hours for four consecutive nights in four houses per village using human landing collection method. The nocturnal biting activities of each Anopheles species were expressed as the mean number of mosquitoes landing per person per hour. The human behavior study was conducted via observations and questionnaire surveys. Species within Anopheles gambiae and Anopheles funestus complexes were differentiated by polymerase chain reaction (PCR) and the presence of Plasmodium falciparumcircumsporozoite proteins (CSP) determined by enzyme-linked immunosorbent assay (ELISA).
Results: Altogether, a total of 2,037 adult female Anophelines were collected comprising of An. funestus s.l. (76.7%), An.gambiae s.l.(22.8%) and Anopheles coustani (0.5%). Overall, Anopheles funestus was the predominant species collected in Ahero (96.7%) while An. gambiae s.l was dominant in Kisian (86.6%) and Kimaeti (100%) collections. PCR results revealed that An. arabiensis constituted 80.5% and 79% of the An.gambiae s.l samples analysed from Ahero and Kisian respectively. An. gambiae s.s (hereafter An.gambiae)(98.1%) was the dominant species collected in Kimaeti. All the An. funestus s.l samples analysed belonged to An. funestus s.s ( hereafter An. funestus). Indoor biting densities of Anopheles gambiae and An. funestus exceeded the outdoor biting densities in all sites. The peak biting occurred early morning between 0430-0630 hours in the lowlands for An. funestus both indoors and outdoors. In the highlands (Kimaeti), the peak biting of An.gambiae occurred between 0100-0200 hours indoors. Over 50% of the study population stayed outdoors from 1800 to 2200 hours and woke up at 0500 hours coinciding with the times highest numbers of vectors were collected. The sporozoite rate was higher in vectors collected outdoors, with An. funestus being the main malaria vector in the lowlands and An. gambiaein the highland.
Conclusion: The study shows heterogeneity of Anophelines distribution, high outdoor malaria transmission, and peak biting activity by An. funestus (early morning ) when humans are not protected by bed nets in the lowland sites. Additional vector control efforts targeting the behaviors of these vectors i.e using non-pyrethroids-based indoor residual spraying and spatial repellents outdoors are needed.
Validity of neural networks in determining lower limb kinematics in stationary cycling
Authors: Bini Rodrigo Rico , Nascimento Vitor Bertoli , Nibali Aiden
Published: April 2023

Purpose: Increasing access to marker-less technology has enabled practitioners to obtain kinematic data more quickly. However, the validation of many of these methods is lacking. Therefore, the validity of pre-trained neural networks was explored in this study compared to reflective marker tracking from sagittal plane cycling motion.
Methods: Twenty-six cyclists were assessed during stationary cycling at self-selected cadence and moderate intensity exercise. Standard video from their sagittal plane was obtained to extract joint kinematics. Hip, knee, and ankle angles were calculated from marker digitisation and from two deep learning-based approaches (TransPose and MediaPipe).
Results: Typical errors ranged between 1-10°for TransPose and 3-9°for MediaPipe. Correlations between joint angles calculated from TransPose and marker digitalization were stronger (0.47-0.98) than those from MediaPipe (0.25-0.96).
Conclusion: TransPose seemed to perform better than MediaPipe but both methods presented poor performance when tracking the foot and ankle. This seems to be associated with the low frame rate and image resolution when using standard video mode.
Ileoileal knotting a rare cause of double loop small bowel obstruction,diagnostic and intraoperative challenge at Ethiopian Leku district hospital,sidama region,April 2023 ,case report
Authors: Kibret Asfaw
Published: April 2023

Baground

Intestinal obstruction is common cause for abdominal surgeries. Among the causes for intestinal obstruction ileal knotting is the unusual and rare cause with very few case reports in the globe and in Ethiopia.Almost all cases were intraoperative surprises.We report a case of strangulated closed loop obstruction caused by ileoileal knotting at distal ileum near ileocecal junction,its diagnostic and management challenges and the roll of the “Integrated Emergency surgical officers’’ early emergency surgica interventions role in district primary hospitals in Ethiopia where there is scarce general specialist surgeon.

Case presentation

Here we discuss a 78yrs old male Ethiopian patient presented to our district hospital with sign symptoms of strangulated small bowel obstruction and exploratory laparatomy was done with intraoperative surprise of ileoileal knot with gangreneous closed loop obstruction at ileocecal junction.The gangreneous segment was resected and ileo ascending colon anastomosis was done.The post operative stay was uneventful and patient discharged on his 7th post operation date.

Conclusion

Here we present this case to highlight difficulty of preoperative diagnosis and the need of high index of suspicion as well as the management challenges of resection anastomosis when the knot is near to ileocecal junction and the undeniable role of emergency surgical officers for early intervension such emergency cases who need early intervensios.
Patch seriation to visualize data and model parameters
Authors: Lasfar Rita , Tóth Gergely
Published: April 2023

We developed a new seriation merit function for enhancing the visual information of data matrices. A local similarity matrix is calculated, where the average similarity of a neighbouring objects is calculated in a limited variable space and a global function is constructed to maximize the local similarities and cluster them into patches by simple row and column ordering. The method identifies data clusters in a powerful way, if the similarity of objects is caused by some variables and these variables differ for the distinct clusters. The method can be used in the presence of missing data and also on more than two-dimensional data arrays. We show the feasibility of the method on different data sets: on QSAR, chemical, material science, food science, cheminformatics and environmental data in two- and three-dimensional cases. The method can be used during the development and the interpretation of artificial neural network models by seriating different features of the models. It helps to identify interpretable models by elucidating clusters of objects, variables and hidden layer neurons.
Role of Point of Care Ultrasound in the Absence of Radial pulse and unrecordable Blood pressure during the Assessment of Shock: Case report
Authors: Getachew Melaku , Alemayehu Amanuel , Weldesilase Dereje , Degefu Natanim , Jufara Tilahun Jiru , Yewedalsew Selome Fantahun , Jauhal Sonja , Kalantari Hossein , Hassen Getaw Worku
Published: April 2023

Point-of-care ultrasound (POCUS) has been an integral part of patient evaluation in the Emergency Department. It has been used increasingly for the evaluation of critically ill and trauma patients. We report a case of 60-year-old male patient who presented to the Emergency department with flank pain and urinary symptoms suggesting pyelonephritis with unrecordable blood pressure indicating potential septic shock, but the absence of bilateral radial pulses triggered the use of POCUS which reveal bilateral radial artery occlusion.
Development and Validation of a Model including Arterial Enhancement Fraction to Predict the Progression in HCC Patients Undergoing Chemoembolization
Authors: Chai Bin , Xiang Dongqiao , Wang Wei , Ren Yanqiao , Wang Fuquan , Wang Jihua , Li Yi , Zhou Guofeng , Zheng Chuansheng
Published: April 2023

Background
Arterial enhancement fraction of residual tumor (AEF-RT) has been recently reported as a potential prognostic predictor for hepatocellular carcinoma (HCC) treated with drug-eluting beads transarterial chemoembolization (DEB-TACE). We aim to establish a prognostic model including AEF-RT for predicting progression-free survival (PFS) in HCC patients after DEB-TACE.
Methods
The Cox model for PFS was derived in a training cohort (n = 56) and tested in a temporal validation cohort (n = 55). Model performance was assessed using the concordance index (C-index) and integrated Brier score (IBS) and was compared with existing prognostic models.
Results
The final model, termed ADMN, incorporated AEF-RT, Diameter, Margin appearance, and Neutrophil-to-lymphocyte ratio. High-risk patients defined by ADMN had 3.92 times greater progression risk than low-risk ones in the training cohort (p < 0.001) and 2.52 times greater in the validation cohort (p = 0.005). The C-index of ADMN was significantly higher than that of other models in the training cohort (0.76) and remained numerically higher in the validation cohort (0.71). The ADMN model manifested the lowest IBS at 6 and 12 months in the training cohort. Although the IBS at 6 and 12 months remained at a satisfactorily low level in the validation cohort, there was no superiority of ADMN IBS over other prognostic models at 12 months.
Conclusion
The ADMN model enabled progression risk stratification and individualized estimation of PFS in HCC patients undergoing DEB-TACE and yielded better performance than existing models. Further external validation with a larger sample size is required.
On the utility of Ensemble Rainfall Forecasts over River Basins in India
Authors: Dube Anumeha , Ashrit Raghavendra
Published: April 2023

Rivers form a lifeline for the agriculture based economy in India, but recent heavy rainfall events have caused major floods in the rivers resulting in loss of life and property. In order to accurately forecast the stream flow from the rivers firstly, an accurate forecast of rainfall over the river basins (RB) is required. Until recently, for operational flood forecasting in India, rainfall forecasts from deterministic models were used. Deterministic models often result in incorrect forecasts as they do not contain the uncertainty information. Ensemble prediction systems (EPS) sample this uncertainty and can add value to the deterministic forecasts. This study seeks to address the question ‘whether the ensemble rainfall forecasts over RBs in India are ready for hydrological applications?’ In order to answer this and generate more confidence in using probabilistic rainfall forecasts from an EPS for hydrological purposes the accuracy of the forecasts has to be established. For this purpose, we have carried out an in-depth verification of the probabilistic rainfall forecasts obtained from the NCMRWF EPS (NEPS) over 8 major RBs of India during the southwest monsoon (SWM) seasons of 2018 to 2021. The basin averaged rainfall forecasts from NEPS and observations from the Integrated Multi-satellitE Retrievals for GPM (IMERG) are used in this study. It was seen from the study that the model possesses good skill in predicting low to moderate rainfall over Himalayan rivers like Ganga and peninsular rivers like Tapi, Narmada, Cauvery, and Krishna. This is seen in terms of a low Brier Score (BS), high Brier Skill Score (BSS) and low Continuous Ranked Probability Score (CRPS), as well as lower RMSE in the ensemble mean. The skill of the model is further confirmed by comparing the RMSE in the mean with the spread in the members. The best match between the RMSE in ensemble mean and spread is seen for Ganga RB. The Relative Economic Value (REV) determines the economic value of forecasts and it shows that over Ganga, Mahanadi, and Narmada the rainfall forecasts show the maximum economic value. However, the model shows relatively poorer skill in predicting rainfall over the Brahmaputra RB located in northeastern India. From this study it can be concluded that NEPS model has reasonably good skill in predicting rainfall over RBs in northern and peninsular parts of India and it would be beneficial to use these forecasts for forecasting floods.
About the possibility to liberate fixed cations from smectites by hydrothermal treatment
Authors: Kaufhold Stephan , Dohrmann Reiner , Gröger-Trampe Jens
Published: April 2023

The chemical analysis of pure smectites exchanged by one of the typical CEC-index cations (e.g. Cu-trien) often still shows significant Na-, Ca-, and K-contents which in contrast to Mg are not expected to occur in the octahedral sheet. These so called non-structural cations were obviously not exchanged for the index cation although they are supposed to act as “gegenions” (outside the TOT layer). Such cations are termed “fixed cations”. The study proved that at least part of the fixed cations of smectites can be rendered exchangeable (liberated) by extensive water treatment before an index cation is added. The increased amount of exchangeable cations was accompanied by a decrease of the CEC which can be probably explained by partial smectite dissolution. Increasing the solid/liquid ratio in order to suppress smectite dissolution resulted in a lower amount of liberated cations but also less CEC decrease. The fixed cations, therefore, are thought to be strongly bound and can only be liberated if the smectite structure is affected. On average, low charged smectites showed less liberated cations than high charged smectites but the correlation was poor and hence does not allow to unambigously conclude an effect of the layer charge density (LCD).
Analysis of influenza epidemics in northern China during 2018-2021 and exploration of early diagnosis on influenza B
Authors: Wang Bo , Zhang Longyan , Cui Yingchun , Li Li , Guan Jianying , Chen Zhenyu , Liu Tao
Published: April 2023

Background: Research on the impacts of COVID-19 towards influenza and the early diagnosis of influenza B is limited. This study aimed to analyze the impacts of COVID-19 pandemic on influenza epidemics in northern China and explore the early-diagnosis indicators of influenza B.
Methods: 1. Data of influenza-like illness (ILI) and influenza virological surveillance in northern China during 2018-2021 winter influenza season were collected to analyze the impacts of COVID-19 pandemic on influenza epidemics. 2. Clinical characteristics of 38 influenza B positive patients and 38 influenza B negative patients confirmed during 2021 winter influenza season were retrospectively observed. Clinical symptoms and blood routine indicators of both groups were compared and analyzed.
Results: 1. During 2020 and 2021 winter influenza season, ILI% and influenza virus positive rate in northern China were both lower than those in 2018 and 2019, with the influenza B (Victoria) dominating. 2. Compared with influenza B negative group, the systemic symptoms in influenza B positive group were significantly increased. The value of white blood cell, neutrophils%, C-reactive protein and serum amyloid A in influenza B positive group were significantly lower than those in negative group, while the lymphocytes% and monocytes% were higher than those in negative group and both could be regarded as the diagnostic indicators of influenza B.
Conclusions: Influenza epidemics were greatly reduced during COVID-19 pandemic, with influenza B rebounding from 2021, and continuous surveillance is still needed. Both clinical features and blood routine indicators can be helpful towards the early diagnosis on influenza B.
Extra-musculoskeletal manifestations driving the therapeutic decision-making in patients with Spondyloarthritis: a 12-month follow-up cohort
Authors: Annunciato Danielle R , Oliveira Thauana L , Magalhães Vanessa O , Pinheiro Marcelo de Medeiros
Published: April 2023

Background: The extra-musculoskeletal manifestations (EMMs) such as recurrent acute anterior uveitis (rAAU), psoriasis (Ps), and inflammatory bowel disease (IBD), are related to the spondyloarthritis (SpA), as well as they are associated with disease activity and poor prognosis. However, there are no data addressing its relevance regarding therapeutic decision-making in clinical practice.
Objective: To evaluate the impact of EMMs to drive the treatment decision-making in patients with SpA in a 12-month follow-up.
Patients and methods: SpA patients, according to the axial and peripheral ASAS classification criteria, as well as CASPAR criteria, with any active EMM, defined as main entry criteria, were included in this longitudinal cohort study. Individuals with a history of any disease or condition that could be associated with some of the studied endpoints, including neoplasms and infectious diseases, were excluded. Specific tools related to each EMM, including Psoriasis Area Severity Index (PASI), ophthalmologic evaluation, according to the Standardization of Uveitis Nomenclature (SUN) criteria, and gut complaints were used at baseline and during the 3-, 6- and 12-month of follow-up as outcomes measures over time. Descriptive and inferential analyses were used appropriately, including Pearson’s correlation test, chi-squared test, and ANOVA. P-value less than 0.05 was considered as significant.
Results: A total of 560 patients were enrolled, of whom 472 meet the eligibility criteria. The majority (N=274; 59.6%) had one or more EMM related to SpA umbrella concept. Regarding their value in decision-making (N=141/274, 51.5%), Ps was the most prevalent (N=78/139; 28.5%), followed by rAAU (N=48/111; 17.5%) and IBD (N=15/24; 5.5%). Clinical improvement of EMMs outcomes was observed in most patients over 12-month follow-up, especially in those with rAAU and IBD (p<0.001).
Conclusion: Our results showed that EMMs guided the therapeutic decision-making in half of SpA patients, regardless of musculoskeletal condition, suggesting the inter-disciplinarity among the rheumatologist, ophthalmologist, dermatologist, and gastroenterologist plays a crucial role to manage them.
Effect of multidimensional physiotherapy on non-specific chronic low back pain: a randomized controlled trial
Authors: Bemani Sanaz , Sarrafzadeh Javad , Dehkordi Shohreh Noorizadeh , Talebian Saeed , Salehi Reza , Zarei Jamileh
Published: April 2023

Background: Many people with non-specific chronic low back pain (NSCLBP) do not recover with current conventional management. Systematic reviews show multidimensional treatment improves pain better than usual active interventions. It is unclear whether multidimensional physiotherapy improves pain better than usual physiotherapy. This study determines the effectiveness of this treatment to reduce pain and disability and improve quality of life, pain cognitions, and brain function in individuals with NSCLBP.
Methods: 70 eligible participants aged 18 to 50 years with NSCLBP were randomized into either the experimental group (multidimensional physiotherapy) or the active control group (usual physiotherapy). Pain intensity was measured as the primary outcome. Disability, quality of life, pain Catastrophizing, kinesiophobia, fear Avoidance Beliefs, active lumbar range of motion, and brain function were measured as secondary outcomes.
The outcomes were measured at pre-treatment, post-treatment, 10, and 22 weeks. Data were analyzed using intention-to-treat approaches.
Results: There were 17 men and 18 women in the experimental group (mean [SD] age, 34.57 [6.98] years) and 18 men and 17 women in the active control group (mean [SD] age, 35.94 [7.51] years). Multidimensional physiotherapy was not more effective than usual physiotherapy at reducing pain intensity at the end of treatment. At the 10 weeks and 22 weeks follow-up, there were statistically significant differences between multidimensional physiotherapy and usual physiotherapy (mean difference at 10 weeks, -1.54; 95% CI, -2.59 to -0.49 and mean difference at 22 weeks, -2.20; 95% CI, –3.25 to –1.15). The standardized mean difference and their 95% confidence intervals (Cohen's d) revealed a large effect of pain at 22 weeks: (Cohen’s d, -0.89; 95% CI (-1.38 to-0.39)). There were no statistically significant differences in secondary outcomes.
Conclusions: In this randomized controlled trial, multidimensional physiotherapy resulted in statistically and clinically significant improvements in pain compared to usual physiotherapy in individuals with NSCLBP at 10 and 22 weeks.
Trial Registration: ClinicalTrials.gov NCT04270422; IRCT IRCT20140810018754N11.
Prediction of settlement velocity of sludge area based on image analysis
Authors: GUO Shuo , CHAI Xiaohui , TANG Shixian , Lijie ZHAO , HONG Yue
Published: April 2023

The sedimentation performance of sludge affects the operation of the entire treatment process. It is important to measure the zone settling velocity accuracy and high efficiency which can reflect the sedimentation performance of sludge. Traditional methods often rely entirely on manual implementation. Long hours of manual measurement work brings physical strain to the operator, low efficiency of the entire measurement work and a large error in the measurement results. Therefore, the method combining image processing and neural network to realize automatic recognition of the scale value of sludge water interface in sludge sedimentation video is proposed. Based on the recognized scale value, overall sedimentation change curve is drew, and the sludge sedimentation rate is calculated. Then, the activated sludge was examined by phase contrast microscope to obtain sludge image. The flocs, filamentous bacteria and other targets in the image are segmented with Labelme, the characteristics of flocs and sedimentation rate of the previous day are taken as input of deep stochastic configuration network, and the calculated sludge sedimentation rate is output for predicting layered sedimentation rate. Through experimental analysis, the prediction error is within a reasonable range. The intelligent prediction of sludge regional sedimentation velocity is realized.
Bibliometric analysis of the Global Myelodysplastic Syndrome Study 1998-2022
Authors: Ma Junlan , Zhang Wei , Li Jiaojiao , Zhai Yan , Shen Li
Published: April 2023

Myelodysplastic syndromes (MDS) is a common myeloid malignancy with a high risk of transformation into acute leukaemia. In recent decades, the treatment of MDS has made great progress, and thousands of papers on MDS treatment-related research have been published. We conducted a bibliometric analysis of the literature on MDS and discussed collaboration between authors, countries and institutions, identifying research hotspots in the field of MDS. We searched the Web of Science (core collection) on the subject of "Myelodysplastic syndromes" or "Myelodysplastic syndromes" from January 1998 to September 2022, and analyzed the year of publication, research direction, country, institution, journal, distribution of authors, In addition, visual analysis was performed with CiteSpace, VOSviewer, Gephi, Charticulator, Scimago Graphica, and network graphs were generated to evaluate collaborations between different authors, countries, and institutions and the year of outbreak in keyword concentration, as well as the time zone map display of keywords. We searched 5218 articles from WOSCC as of September 29, 2022, and we found that the number of publications fluctuated from 1998 to 2008, remained relatively stable, and showed a slow upward trend in the following years. The most published countries are the United States, Germany and Italy, and the most cited country is Sweden, where the close collaborative research of the National House is crucial to progress in the field of MDS. Since 1998, hematopoietic stem cell transplantation and post-transplantation prognosis risk research has been a research hotspot, until 2009, the discovery of azacitidine and other demethylation drugs provided new treatment strategies in the field of MDS, more and more clinical trials are committed to finding new targeted drugs and exploring new prognostic risk factors for MDS, MDS treatment and prognosis have also received continuous attention. Bibliometric analysis of MDS-related research can help researchers and clinicians quickly understand the research hotspots and development trends in this field, provide researchers with new research angles, and provide ideas for the development of new treatment strategies.
Diagnostic Accuracy of Deep Learning in Medical Image Analysis - A Case Study Using Deep Burns
Authors: Abubakar Aliyu , Ajuji Mohammed , Turaki Abdulkadir Maigari
Published: April 2023

Purpose
Precise evaluation of burn depth is essential for determining the appropriate patient care and surgical requirements. This study aimed to examine a supervised machine learning approach that incorporates dynamic feature selection for differentiating between partial-thickness and full-thickness burns, utilizing deep learning patterns in digital images.
Method
Four deep learning models (VGG-16, ResNet-50, Xception, and EfficientNetV2L), along with two classifiers (Support Vector Machine and Fully Connected layer), were used to extract features from digital images of burn wounds, implementing dynamic feature selection during the training process. The models were trained using 3-fold cross-validation and tested on an unseen data split.
Results
The proposed method achieved high prediction accuracy, with the best performance achieved using EfficientNetV2L and SVM, yielding a specificity of 99.38%, sensitivity of 100.00%, precision of 99.35%, and an AUC value of 0.9969.
Conclusion
The results indicate that the proposed approach, which employs dynamic feature selection, holds potential for clinical effectiveness in objectively assessing burn depths. This technique can aid in informed decision-making regarding patient care and surgical intervention. However, further research is required to investigate its robustness in discriminating various skin wound depths.
Identification of a novel microRNA signature for prediction of clinical prognosis and drug sensitivity/resistance analysis in Hepatocellular Carcinoma
Authors: Lu Guoan , Li Xianbin
Published: April 2023

Prognostic stratification of hepatocellular carcinoma (HCC) remains challenging. It is found that microRNAs play a crucial role in pathogenesis of HCC. Our aims to construct a useful prognostic model based on miRNA signature to determine patient at high risk of HCC progression. Detailed information of miRNA were collected from The Cancer Genome Atlas (TCGA). We categorized HCC patients into two groups (training group and testing group) and identified the prognostic miRNA signature by univariate Cox regression analysis. A novel model based on miRNA was developed for HCC prognostic prediction. Then we apply ROC curve, KM curve and multivariate Cox regression analysis to assess the prognostic performance of the novel model. The results showed that AUC values based on ROC analysis of one, three and five-year overall survival (OS) for patients were 0.742, 0.723, 0.841, and 0.706, 0.653, 0.581, and 0.721, 0.702, 0.716 for training group, testing group and whole group, respectively. It indicated that the predictive performance of prognostic model was good. The nine-miRNA signature (miR-139, miR-125b-2, miR-125b-1, miR-4746, miR-1180, miR-592, miR-9-2, miR-9-1 and miR-9-3) could independently predict OS by using cox regression analysis method. The survival rate of patients in the high-risk group was lower than that in the low-risk group (all p < 0.001). In order to predict the potential biological functions of nine-miRNA signature, a total of 356 overlapping miRNA-target genes were analyzed by pathway enrichment analysis. In addition, the results showed that the DEGs mainly enriched in cancer-related pathways, including microRNAs in cancer, Longevity regulating pathway, AMPK signaling pathway, FoxO signaling pathway, Yersinia infection and T cell receptor signaling pathway. Function analysis of miRNAs showed that the nine miRNAs are related to various critical biological function modules and interact closely based on their functional similarity. Besides, most of miRNAs can promote sensitivity or induce resistance to some anti-cancer drugs.Taken together, these findings suggested that the nine-miRNA signature model could be conductive to the prognostic diagnosis and treatment of HCC.
Gestational diabetes mellitus and risk of dementia in late life: a prospective cohort study of United Kingdom Biobank
Authors: Wu Liting , Lai Fenghua , Chen Nan , Liu Yihao , Zeng Rui , Xu Changliu , Yang Xinlei , Li Yanbing , Xiao Haipeng , Cao Xiaopei
Published: April 2023

Although it has been demonstrated that gestational preeclampsia increased the risk of dementia, there is limited information regarding the relation between history of gestational diabetes mellitus (GDM) and the risk of late life dementia. In the present study, we analyzed the correlation using United Kingdom (UK) Biobank data. Propensity score-based fine stratification weighting and a Cox proportional hazards regression model were used and the risk of dementia was presented by weighted hazard ratio (HR) with 95% confidence intervals (CIs). A multi-state model was then used to analyze the impact of GDM on the progression of dementia from diseases, including type 2 diabetes (T2DM), hypertension, stroke, and myocardial infarction (MI). The study cohort consisted of 1,177 women who were previously exposed to GDM and 217,728 women who were not previously exposed to GDM. Overall, the adjusted dementia risk was approximately 1.67- to 2.02-fold higher for women exposed to previous GDM than those not exposed. In particular, GDM exposure increased the risk for dementia among women who experienced postpartum T2DM (HR = 1.92, 95% CI = 1.05–3.53), hypertension (HR = 2.00, 95% CI = 1.13–3.55), and MI (HR = 3.16, 95% CI = 1.28–7.75). However, for women without the above postpartum complications, the risk of late life dementia did not increase. Therefore, GDM is associated with an increased risk of all-cause dementia, which may be attenuated by preventive measures against postpartum T2DM, hypertension, and MI. Barriers and strategies for preventing postpartum dementia-risk complications should be further evaluated in future studies.
Formulation & Evaluation of Polyherbal Antidiabetic Powder
Authors: Gawade Mahesh , Adlinge Akshay , Lipabe Vishal
Published: April 2023

Diabetes is a silent killer that causes significant economic damage in underdeveloped nations like India. To reduce the strain on a person's health and economy as well as the burden on society as a whole, better therapies must be developed with fewer side effects. The study's primary objective was to create a Evaluation of the polyherbal powder for diabetic mellitus based on organoleptic, rheological, physical, and phytochemical traits. The herbs used to make the polyherbal powder were annona squamosal, Trigonella foenum-graecum, Murraya koenigii, Aegle marmelos Correa, Mentha spicata Standardized methods were used to conduct the evaluations. The polyherbal powder's organoleptic characteristics were determined to be a dull brown colour, distinctive odour, astringent taste, and a reasonably fine texture. An examination of the phytochemicals revealed the presence of flavonoids, alkaloids, terpenoids, tannins, and carbs, glycosides, and steroids. The polyherbal powder had prolonged stability and good flow characteristics, according to physicochemical examination. Consequently, the polyherbal powder that may be used to treat diabetes mellitus was assessed.
Characterization of rumen microbiome and immune genes expression of crossbred beef steers with divergent residual feed intake phenotypes
Authors: Taiwo Godstime , Morenikeji Olanrewaju B. , Idowu Modoluwamu , Sidney Taylor , Adekunle Ajiboye , Cervantes Andres Pech , Peters Sunday O. , Ogunade Ibukun M.
Published: April 2023

We investigated whole blood and hepatic mRNA expressions of immune genes and rumen microbiome of crossbred beef steers with divergent residual feed intake phenotype to identify relevant biological processes underpinning feed efficiency in beef cattle. Low-RFI beef steers (n = 20; RFI = − 1.83 kg/d) and high-RFI beef steers (n = 20; RFI = + 2.12kg/d) were selected from a group of 108 growing crossbred beef steers (average BW = 282 ± 30.4 kg) fed a high-forage total mixed ration after a 70-d performance testing period. At the end of the 70-d testing period, liver biopsies and blood samples were collected for total RNA extraction and cDNA synthesis. Rumen fluid samples were also collected for analysis of the rumen microbial community. The mRNA expression of 84 genes related to innate and adaptive immunity was analyzed using pathway-focused PCR-based arrays. Differentially expressed genes were determined using P-value ≤ 0.05 and fold change (FC) ≥ 1.5 (in whole blood) or ≥ 2.0 (in liver). Gene ontology analysis of the differentially expressed genes revealed that pathways related to pattern recognition receptor activity, positive regulation of phagocytosis, positive regulation of vitamin metabolic process, vascular endothelial growth factor production, positive regulation of epithelial tube formation and T-helper cell differentiation were significantly enriched (FDR < 0.05) in low-RFI steers. In the rumen, the relative abundance of PeH15, Arthrobacter, Moryella, Weissella and Muribaculaceae was enriched in low-RFI steers, while Methanobrevibacter, Bacteroidales_BS11_gut_group, Bacteroides and Clostridium_sensu_stricto_1 were reduced. In conclusion, our study found that low-RFI beef steers exhibit increased mRNA expression of genes related to immune cell functions in whole blood and liver tissues, specifically those involved in pathogen recognition and phagocytosis regulation. Additionally, these low-RFI steers showed differences in relative abundance of some microbial taxa which may partially account for their improved feed efficiency compared to high-RFI steers.
Genotype by environment interaction of bread wheat genotypes under timely and late sown planting conditions in central zone of India
Authors: Khare Vikrant , Shukla R. S. , Pandey Suneeta , Singh S. K.
Published: April 2023

The purpose of this study was to ascertain the genotype by environment interaction (GEI) of heat tolerance wheat genotypes. The objective was to inspect the stable wheat genotype for timely and late sown planting condition in central zone of India. For that total of 20 wheat genotypes, including two parents and three commercial checks, were tested across 6 (timely sown) + 4 (late sown) environments at Jabalpur, Narmadapuram, and Sagar district of Madhya Pradesh state of India in 2019-20 and 2021-21. The per plant yield and grain filling rate data were considered to perform univariate and multivariate stability analysis. Our result revealed that environment, genotype, and GEI effects were significant (P < 0.001) across all the environments and individual environmental conditions. The greater performing along with high stability for grain yield JW3288, L8 and L13 while for grain filling rate L11, L13 and L11 genotypes were identified in timely sown, late sown and across all the environments, respectively. In order to find stable and high-performing genotypes, the GEI accompanied by several models but AMMI and GGE models were further effective and accurate than the linear regression model. In conclusion according to univariate and multivariate stability analysis L13 was the utmost genotype across all the environments therefore, it might be used in future breeding programs although, Jabalpur was recognized as the most discriminating and representative environments across all the environments.
What Is Wrong with Winter Chill Models in Warm Climates?
Authors: Louw Esmé , Allderman Laura , Cook Nigel
Published: April 2023

Bud dormancy is an evolutionary strategy that protects temperate fruit trees from low temperatures during winter. With adequate winter chilling, it is a process consisting of a rapid entrance phase where growth inhibition increases to a maximum and is then released via an exit phase. This progression is, however, different in areas with insufficient winter chill. In such areas, the dormancy entrance phase is protracted, and the exit phase is often incomplete. Several chill models have been designed to describe the plants’ response to chill accumulation to match cultivar and site. Although it is known that these models are less accurate in warm winter areas, their accuracy during the two dormancy phases has always been assumed equal. The aim of this study was to investigate the accuracy of four chill models during the entrance and exit phases of bud dormancy of ‘Royal Gala’ buds from two contrasting climatic areas. One-year-old shoots were collected from commercial orchards and forced to determine their bud dormancy level. Before forcing, the shoots received varied amounts of chill additional to the field chill. The bud dormancy progression was represented as joint two- or three-line models to determine the entrance and exit phases. For each phase, the dormancy level of every sample was plotted against its chill accumulation based on four chill models (Chilling Hours, Utah, Positive Utah, and Dynamic Model). Results were compared to determine the ability of each model to predict the linearity of the dormancy progression. The results indicated that although all the models were able to describe the exit phase of bud dormancy successfully, none could describe a linear entrance phase. This suggests that during the onset of dormancy, buds respond to temperature differently to what is measured by the chill models making the models unreliable when winter chill is inadequate.