Influences of current direction on 1 Hz motor cortex rTMS by Carolina Kanig, Mirja Osnabruegge, Florian Schwitzgebel, Wolfgang Mack, Martin Schecklmann, Stefan Schoisswohl

“…Additionally, we investigated possible confounding variables. Methods: Twenty-five healthy subjects received 2000 pulses of 1 Hz rTMS at 110 % resting motor threshold intensity over the left motor hotspot inducing anterior-posterior – posterior-anterior (AP-PA) and posterior-anterior – anterior-posterior (PA-AP) current directions in the brain. …”
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Evaluation of proton and carbon ion beam models in TReatment Planning for Particles 4D (TRiP4D) referring to a commercial treatment planning system by Yinxiangzi Sheng, Lennart Volz, Weiwei Wang, Marco Durante, Christian Graeff

“…Purpose: To investigate the accuracy of the treatment planning system (TPS) TRiP4D in reproducing doses computed by the clinically used TPS SyngoRT. Methods: Proton and carbon ion beam models in TRiP4D were converted from SyngoRT. …”
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Progression of the first stage of spontaneous labour: A prospective cohort study in two sub-Saharan African countries. by Olufemi T Oladapo, Joao Paulo Souza, Bukola Fawole, Kidza Mugerwa, Gleici Perdoná, Domingos Alves, Hayala Souza, Rodrigo Reis, Livia Oliveira-Ciabati, Alexandre Maiorano, Adesina Akintan, Francis E Alu, Lawal Oyeneyin, Amos Adebayo, Josaphat Byamugisha, Miriam Nakalembe, Hadiza A Idris, Ola Okike, Fernando Althabe, Vanora Hundley, France Donnay, Robert Pattinson, Harshadkumar C Sanghvi, Jen E Jardine, Özge Tunçalp, Joshua P Vogel, Mary Ellen Stanton, Meghan Bohren, Jun Zhang, Tina Lavender, Jerker Liljestrand, Petra Ten Hoope-Bender, Matthews Mathai, Rajiv Bahl, A Metin Gülmezoglu

“…Based on a 95th percentile threshold, nulliparous women may take up to 7 hours to progress from 4 to 5 cm and over 3 hours to progress from 5 to 6 cm. …”
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[18F]F-FMISO and [18F]F-FLT PET/CT dual-nuclide imaging for in vivo prediction of drug resistance in pancreatic cancer by SUN Chenwei, HAI Wangxi, QU Qian, XI Yun

“…The comparison of [18F]F-FMISO and [18F]F-FLT PET differences before and after chemotherapy provides the most accurate prediction of drug resistance and survival time.…”
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Waist-to-Height Ratio – Reference Values and Associations with Cardiovascular Risk Factors in a Russian Adult Population by Kholmatova K, Krettek A, Dvoryashina IV, Malyutina S, Cook S, Avdeeva E, Kudryavtsev AV

“…In women, WHtR had stronger associations with age, university education, poor financial situation, blood pressure, HDL cholesterol, and ln-transformed C-reactive protein, in men – with being married, current smoking, LDL and non-HDL cholesterol, and HbA1c.Conclusion: Three-quarters of the study population had WHtR values exceeding the conventional threshold for abdominal obesity. Men and women differed in the WHtR associations with socio-demographic and lifestyle risk factors, biomarkers of inflammation, hypertension, dyslipidemia, and diabetes. …”
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China Aerosol Raman Lidar Network (CARLNET)—Part I: Water Vapor Raman Channel Calibration and Quality Control by Nan Shao, Qin Wang, Zhichao Bu, Zhenping Yin, Yaru Dai, Yubao Chen, Xuan Wang

“…Based on the distribution of lidar in regions with different humidity conditions, the method of real-time calibration and quality control based on radiosonde data is established for the first time. …”
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Identification of biomarkers for Laryngeal squamous cell carcinoma through Mendelian randomization and integrated bioinformatics analysis by Pengjian Zhang, Weizhang Chen, Kai Chen, Yuanhang Ye, Weijun Wu

“…Abstract Background Laryngeal squamous cell carcinoma (LSCC) is a common head and neck tumor with an increasing incidence rate and limited therapeutic efficacy in advanced stages. Methods This study integrated multi-omics data from multiple databases to comprehensively analyze the role of pan-apoptosis-related genes (PANRGs) in the prognosis of LSCC. …”
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Estimation and evaluation of iron reserves in the eastern area of Eileh1 mine, Razavi Khorasan province by Hamid Esmati Daroneh, Maryam Gholamzadeh

“…Following geometric modeling and constructing a block model for the deposit, we estimated reserves for various iron-grade thresholds and compared the results of both methods. …”
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NON-INVASIVE ASSESSMENT OF CORONARY BLOOD FLOW IN PATIENTS WITH 2ND TYPE DIABETES DURING EXERCISE TEST by A. V. Zagatina, N. T. Zhuravskaya

“…Threshold value that determine relation of patients to CHD or non-CHD group, was 1,7 for CR. …”
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Climate adaptive energy efficiency modeling using a generalized additive approach to optimize building performance across Chinese climate zones by Jian Yang, Mu He, Xingzhu Zhang, Qimeng Ning, Yu Chen, Maryam Alsadat Ziaei Mazinan

“…Research suggests a new method to M&V EEM using generalized additive models (GAM) to provide a way to measure how EEMs perform across different commercial buildings (i.e., offices, mixed-use developments, and healthcare). …”
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A Physics-Guided Neural Network for Flooding Area Detection Using SAR Imagery and Local River Gauge Observations by Monika Gierszewska, Tomasz Berezowski

“…Additionally, we compared the results with other unsupervised methods, such as Otsu thresholding, Chan-Vese segmentation, Gaussian mixture model, and spectral clustering. …”
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Influence of tongue volume, oral cavity volume and their ratio on upper airway: A cone beam computed tomography study by S.S. Rana, O.P. Kharbanda, B. Agarwal

“…Segmentation of the upper airway, tongue and oral cavity was performed manually using Mimics 11.0 (Materialise, Leuven, Belgium) software at different thresholds for air and the tongue. The Hounsfield units (HU) for airway volume of the different facial region ranged from −1024 to −500. …”
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Analysis of multi-frequency ultrasound effect on acoustic microcavitations in N-dimensional fluid by Ali F. Abu-Bakr, Ahmed K. Abu-Nab, Zain F. AbuShaeer

“…Acoustic microcavitation and associated mechanical effects, such as stress and strain, are significant in decreasing cavitation thresholds and improving cavitation effects at multiple (i.e., single, dual, and triple) frequencies. …”
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The effectiveness of a novel artificial intelligence (AI) model in detecting oral and dental diseases by Ravi Rathod, Saffa Dean, Christopher Sproat

“…Ninety different unseen images were selected and presented to the AI model to test the accuracy of disease detection. …”
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Dynamic Challenges of Active Tuberculosis: Prevalence and Risk Factors of Co-Infection in Clinical and Microbiological Characteristics at King Abdulaziz University Hospital, Jeddah... by Mokhtar JA, Attallah DM, Jiman-Fatani AA, Al-Rabia MW, Alqarni MA, Saleh BH, Amboon MM, Altorki TA, Alkuwaity KK, Abujamel T, Kaki R, Albarakati TN, Daghistani H, Ismail MA, Alharbi O, Abu ITM, Alfadil A, Ibrahem K, Mufrrih M, Sait AM

“…Effective strategies, targeted interventions, and future research are vital for reducing mortality.This study examines the stability of tuberculosis (TB) disease presentation using dynamic models among patients treated at King Abdulaziz University Hospital (KAUH) in Jeddah, Saudi Arabia.Key findings include:This is the first study to analyze TB disease stability across different demographic groups.Males, elderly individuals, cancer patients, and those with pulmonary disease or other comorbidities were found to have a higher risk of death from TB.The results emphasize the need for healthcare practices to adopt the “equilibrium state” method for hazard assessment. …”
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The reproducibility of 31-phosphorus MRS measures of muscle energetics at 3 Tesla in trained men. by Lindsay M Edwards, Damian J Tyler, Graham J Kemp, Renee M Dwyer, Andrew Johnson, Cameron J Holloway, Alan M Nevill, Kieran Clarke

“…The CV of PCr(1/2t) was 40%, yet much of this variance was inter-subject such that differences of <20% were detectable with n = 15, given a significance threshold of p<0.05.…”
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High-Precision Qiantang River Water Body Recognition Based on Remote Sensing Image by Hongcui Wang, Yihong Zheng, Ouxiang Chen

“…River water body identification plays an important role in flood monitoring, urban planning, Thus, it attracts more interests of studying and investigating, especially based on remote sensing technology, The traditional NDWI (Normalized Difference Water Index) and MNDWI (Modified Normalized Difference Water Index) methods are widely used, However, these methods need manual intervention to select the threshold, In order to achieve automatic water body recognition, deep learning methods, such as CNN, VGG, Unet etc., are applied, Currently there are few works on the water body identification of Qiantang River, Here, one major challenge for high-precision Qiantang water body recognition is the real complex water body features and complicated geological environment, They are the dense distribution of small water bodies in the Qiantang River Basin, large differences in water body nutrition, and the high complexity of surface environments such as mountains and plains, We investigated two traditional and several deep learning methods and found that WatNet was the most effective model for Qiantang River, This model adopts the structure based on encoder-decoder convolutional network, It uses MobileNetV2 as the encoder, which makes it extract more water feature information while being lightweight and uses ASPP module to capture global multi-scale features in deep layers, Experimental results show that the MIoU and OA (Overall Accuracy) can reach 0. 97 and 0. 99 respectively.…”
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The relationship between intraosseous catheter tip placement, flow rates, and infusion pressures in a high bone density cadaveric swine (Sus scrofa) model by Joseph A. Gehrz, Victoria C. Kay, Derek W. Grady, Alec D. Emerling, Andrew McGowan, Erin R. Reilly, Vikhyat S. Bebarta, Joshua Nassiri, Jorge Viñals, Gregory J. Zarow, Jonathan D. Auten

“…Computed tomography scans were scored by radiologists and categorized as zone 1 (medullary space), zone 2 (trabecular bone), or zone 3 (cortical bone) catheter tip placements. Differences between zones in flow rates, mean pressures, and peak pressures were assessed using analysis of variance and analysis of covariance to account for participant and site differences at the p < 0.05 threshold. …”
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The changes of parameters of the systemic inflammatory answer syndrome on early stages of complicated acute pancreatitis by R. M. Agayev, A. A. Mamadov, F. S. Idrisov, E. A. Iskandarov, E. A. Aliyeva

“…Doing analysis of square under the ROC-curve the threshold meaning for immature granulocytes was determined as 0.81%. …”
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Effect of Management on Spatial and Temporal Distribution of Soil Physical Properties by Engin Özgöz, Hikmet Günal, Hüseyin Önen, Mustafa Bayram, Nurullah Acir

“…PR at subsurface (&gt;2MPa) and BD at surface and subsurface soils (1.47 g cm-3) exceeded the threshold values in some fields of the study area. …”
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