bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantitative Electroencephalographic Analysis of Delirium Tremens Development Following Alcohol-withdrawal Seizure
Authors: Mo Hee-Jung , Yoon Jee-Eun , Kim Dong Wook , Im Hee-Jin
Published: December 2021

Seizures and delirium tremens (DTs) are recognized as severe alcohol-withdrawal symptoms. Prolonged admission and serious complications associated with alcohol-withdrawal are responsible for increased costs and use of medical and social resources. We compared differences in quantitative electroencephalography (EEG) in patients after alcohol-withdrawal seizures (AWS; n = 13), performed in the intensive care unit within 48 h of admission, and in age- and sex-matched healthy controls. We also investigated the prognostic value of quantitative EEG, for the development of alcohol DTs after AWS in a retrospective, case‒control study. The spectral power of each band frequency and the ratio of the theta to alpha band (TAR) in the electroencephalogram were analysed using iSyncBrain® (iMediSync, Inc., Korea). The beta frequency and the alpha frequency band power were significantly higher and lower, respectively, in patients than in age- and sex-matched healthy controls. In AWS patients with DTs, the relative beta3 power was lower, particularly in the left frontal area, and the TAR was significantly higher in the central channel than in those without DTs. Quantitative EEG showed neuronal excitability and decreased cognitive activities characteristic of AWS patients associated with alcohol withdrawal state and we demonstrated that quantitative EEG also might be a helpful tool for detecting patients at high risk of developing DTs during an alcohol-dependence period.
A Multi-Parameter Evaluation of the Neuroprotective and Cognitive-Enhancing Effects of Origanum Onites L. (Turkish Oregano) Essential Oil on Scopolamine-Induced Amnestic Rats
Authors: Aykac Asli , Teralı Kerem , Özbeyli Dilek , Ede Seren , Albayrak Ömercan , Başer Kemal Hüsnü Can , Şener Göksel
Published: December 2021

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by progressive deterioration of cognitive functions (dementia) and represents a growing public health concern since the population in the age groups at risk is increasing. The latter raises an urgent need to translate research findings in the basic brain and behavioral sciences into anti-AD drugs and disease-modifying therapies. Origanum onites (L.), also called Turkish oregano, is a perennial and herbaceous plant species grown for centuries for medicinal, cosmetic and culinary purposes. This is the first study to investigate the putative neuroprotective and pro-cognitive activities of O. onites essential oil (OOEO) against scopolamine-induced amnesia of AD-type in Wistar albino rats. The results of behavioral tests revealed that OOEO administration was able to significantly alleviate learning and memory impairments induced by scopolamine in vivo. The observed effects could be attributed to inhibition of acetylcholinesterase activity, attenuation of oxidative stress and prevention of neuronal apoptosis in the hippocampus and frontal cortex of AD rats. Modulation of pro-inflammatory enzymes, including cyclooxygenase-2, inducible nitric oxide synthase and myeloperoxidase, might further contribute to the neuroprotective properties of OEOO, as predicted by our in silico models. These findings offer novel insights into the therapeutic potential of OEOO in patients with AD.
Characterization of Temperature Fields in Laser Beam Welded Hollow-Cylindrical Cold Crack Samples from High Strength Steel 100Cr6
Authors: Wasilewski Eric , Doynov Nikolay , Ossenbrink Ralf , Michailov Vesselin
Published: December 2021

This work presents a comparative study of thermal conditions that occur during laser beam welding of high strength steel 100Cr6 that often leads to a loss of technological strength and may conditionally produce cold cracks. The results from both experiments and thermal-metallurgical FE-simulations indicate that the type of heat coupling changes significantly when welding with different process parameters, e.g., in the transition between conduction and deep penetration welding. Further, the simulations show that as a result of the high welding speeds and reduced energy per unit length, extremely high heating rates of up to 2x104 K s-1 (set A) resp. 4x105 K s-1 (set B) occur in the material. Both welds thus concern a range of values for which conventional Time-Temperature-Austenitization (TTA) diagrams are not currently defined, so that the material models can only be calibrated using general assumptions. This noted change in energy per unit length and welding speeds causes significantly steep temperature gradients with a slope of approximately 5x103 K mm-1 and strong drops in the heating and cooling rates, particularly in the heat affected zone near the weld metal. This means that even short distances along the length present a staggering difference in relation to the temperature peaks. The temperature cycles also show very different cooling rates for the respective parameter sets, although in both cases they are well below a cooling time t8/5 of one second, so that the phase transformation always leads to the formation of martensite. The results from this study are intended to be used for further detailed experimental and numerical investigation of microstructure, hydrogen distribution, and stress-strain development at different restrain conditions.
A Machine Learning-based Approach to Identify Therapists who can Perceive Client-Side Effects in Psychotherapy
Authors: Yao Lijun , Xu Zhiwei , Zhao Xudong , Chen Yang , Liu Liang , Fu Xiaoming , Chen Fazhan
Published: December 2021

Background: Side effects in psychotherapy are sometimes unavoidable. Therapists play a significant role in the side effects of psychotherapy, but there have been few quantitative studies on the mechanisms by which therapists contribute to them. Methods: We designed the Psychotherapy Side Effects Questionnaire-Therapist Version (PSEQ-T) and released it online through an official WeChat account, where 530 therapists participated in the cross-sectional analysis. The therapists were classified into groups with and without perceptions of clients’ side effects. A number of features were selected to distinguish the therapists by category. Six machine learning–based algorithms were selected and trained by our dataset to build classification models. To make the prediction model interpretable, we leveraged the Shapley Additive exPlanations (SHAP) method to quantify the importance of each feature to the therapist categories.Results: Our study demonstrated the following: 1) Of the therapists, 316 perceived the side effects of the clients in the ongoing psychotherapy sessions, with a 59.6% incidence of side effects. Among all 7 perception types of the side effects, the most common type was “make the clients or patients feel bad” (49.8%). 2) A random forest–based machine-learning classifier offered the best predictive performance to distinguish the therapists with and without perceptions of clients’ side effects, with an F1 score of 0.722 and an AUC value of 0.717. 3) When “therapists’ psychological activity” was considered a possible cause of the side effects in psychotherapy by the therapists, it was the most relevant feature for distinguishing the therapist category.Conclusions: Our study revealed that the therapist's mastery of the limitations of psychotherapy technology and theory, especially the awareness and construction of their own psychological states, was the most important factor in predicting the therapist's perception of the side effects of psychotherapy.
Analysis of Smart Home use based on the Degree of Health-related Risk Variation: A Cross - Sectional National Survey in China
Authors: He Feiying , Wu Yibo , Yang Jiao , Chen Keer , Xie Jingyu , Tuersun Yusupujiang , Li Lehuan , Wu Fangjing , Kan Yifan , Deng Yuqian , Zhao Liping , Chen Jingxi , Sun Xinying , Liao Shengwu , Chen JiangYun
Published: December 2021

BackgroundDigital health has become a heated topic today and smart homes have received much attention as an important area of digital health. However, most of the existing studies have focused on discussing the impact of smart homes on people or the attitudes of older people towards smart homes. Only few studies have focused on relationship between health-related risks and use of smart homes.AimsTo investigate the association between health-related risks and the use of smart homes, provide new recommendations to promote the implementation of digital health strategies and achieve health for all.MethodsWe used data from 11,031 participants aged 18 and above. The population was clustered based on five health-related risk factors: perceived social support, family health, health literacy, media use, and chronic diseases self-behavioral management. A total of 23 smart homes were categorized into three sub-categories: entertainment smart home, functional smart home, and health smart home. We analyzed demographic characteristics and utilization rate of smart home across different cluster.ResultsThe participants were clustered into three groups: low risk, meddle risk, and high risk. The utilization rate of smart home was the most popular in the low risk group (total smart home: 86.97%; entertainment smart home: 61.07%, functional smart home: 77.42%, and health smart home: 75.33%; p < 0.001). For entertainment smart home, smart TV had the highest utilization rate (low risk: 45.73%; middle risk: 43.52%, high risk: 33.38%, p<0.001). For functional smart home, smart washing machine (low risk: 37.66%, middle risk: 35.11%, high risk: 26.49%; p<0.001) and smart air conditioner (low risk: 35.95%, middle risk: 29.13%, high risk: 24.61%) were higher than other of this category. For health smart home, sports bracelet has the highest utilization rate (low risk: 37.29%, middle risk: 24.49%, high risk: 22.83%).ConclusionHealth-related risks are an important factor affecting the use of smart homes. Joint efforts of government and product manufacturers are needed to broaden the smart home market and promote the implementation of digital health strategies.
A Clinical Evaluation Study of Cardiothoracic Ratio Measurement Using Artificial Intelligence
Authors: Saiviroonporn Pairash , Wonglaksanapimon Suwimon , Chaisangmongkon Warasinee , Chamveha Isarun , Yodprom Pakorn , Butnian Krittachat , Siriapisith Thanogchai , Tongdee Trongtum
Published: December 2021

Background
Artificial Intelligence, particularly the Deep Learning (DL) model, can provide reliable results for automated cardiothoracic ratio (CTR) measurement on Chest x-ray (CXR) images. In everyday clinical use, however, this technology is usually implemented in a non-automated (AI-assisted) capacity because it still requires approval from radiologists. We investigated the performance and efficiency of our recently proposed models for the AI-assisted method intended for clinical practice.
Methods
We validated four proposed DL models (AlbuNet, SegNet, VGG-11, and VGG-16) to find the best model for clinical implementation using a dataset of 7,517 CXR images from manual operations. These models were investigated in single-model and combined-model modes to find the model with the highest percentage of results where the user could accept the results without further interaction (excellent grade), and with measurement variation within ± 1.8% of the human-operating range. The best model from the validation study was then tested on an evaluation dataset of 9,386 CXR images using the AI-assisted method with two radiologists to measure the yield of excellent grade results, observer variation, and operating time. A Bland-Altman plot with coefficient of variation (CV) was employed to evaluate agreement between measurements.
Results
The VGG-16 gave the highest excellent grade result (68.9%) of any single-model mode with a CV comparable to manual operation (2.12% vs 2.13%). No DL model produced a failure-grade result. The combined-model mode of AlbuNet+VGG-11 model yielded excellent grades in 82.7% of images and a CV of 1.36%. Using the evaluation dataset, the AlbuNet+VGG-11 model produced excellent grade results in 77.8% of images, a CV of 1.55%, and reduced operating time by almost ten-fold (1.07 ± 2.62 secs vs 10.6 ± 1.5 sec) compared to manual operation.
Conclusion
Due to its exceptional accuracy and speed, the AlbuNet+VGG-11 model could be clinically implemented to assist radiologists with CTR measurement.
Insights Into Amino Acid Metabolism and Incorporation by Compound- Specific Carbon Isotope Analysis of three-Spined Sticklebacks
Authors: Jochmann Maik , Hesse Tobias , Nachev Milen , Khaliq Shaista , Franke Frederik , Scharsack Jörn , Kurtz Joachim , Sures Bernd , Schmidt Torsten
Published: December 2021

Interpretation of isotope data is of upmost importance in ecology to build sound models for the study of animal diets, migration patterns and physiology. However, our understanding of isotope fractionation and incorporation into different consumer tissues is still limited. We therefore measured the δ13C values of individual amino acids from muscle and liver tissue of three-spined sticklebacks (Gasterosteus aculeatus) over time in a controlled feeding experiment. The isotope signatures of amino acids in the liver quickly responded to even small shifts in dietary isotope compositions, whereas muscle tissue remained isotopically constant over time. No significant fractionation between diet and fish tissues was observed for half of the amino acids in both liver and muscle tissue, supporting the idea of direct nutrient routing on a protein rich diet. Small isotopic differences were observed for alanine, glycine and serine between diet and liver, indicating that metabolic processes such as glycolysis or gluconeogenesis can be tracked by the isotope signatures of their main substitutes. We demonstrate that compound-specific isotope analysis has great potential to investigate the main metabolic pathways of organisms and suggest further investigations using isotopically enriched materials to facilitate the correct interpretation of ecological field data.
Perphenazine and Prochlorperazine Decrease Glioblastoma U87-MG Cells Migration and Invasion: Analysis of the ABCB1 and ABCG2 Transporters, E-Cadherin, α-Tubulin, and Integrins (α3, α5, and β1) Levels.
Authors: Otręba Michał , Stojko Jerzy , Kabała-Dzik Agata , Rzepecka-Stojko Anna
Published: December 2021

Purpose: Glioblastoma multiforme is the most frequent malignant brain tumor as well as one of the most lethal and untreatable human tumors with a very poor survival rate. Thus, novel and effective strategies of treatment are required. Integrins play a crucial role in the regulation of cellular adhesion and invasion. Moreover, integrins and alpha-tubulin are very important in cell migration, while E-cadherin plays the main role in tumor metastasis. Their ability to penetrate the BBB and signs of intracerebral activity are very important in glioblastoma therapy. ABC transporters ABCB1 and ABCG2, which are localized in the brain endothelial capillaries of BBB, play a crucial role in the development of multidrug resistance, and are modulated by phenothiazine derivatives. Methods: The impact on the motility of human glioblastoma U87-MG was evaluated with a wound healing assay; cellular migration, and invasion by the transwell assay, while ABCB1, ABCG2, E-cadherin, α-tubulin, and integrins content was determined with the Western blot.Results: This study explores the effect of perphenazine and prochlorperazine on ABCB1, ABCG2, E-cadherin, α-tubulin, and integrins (α3, α5, and β1) amount as well as on migration and invasion ability of human glioblastoma (U87-MG) cells. The results suggest that perphenazine and prochlorperazine modulate multidrug resistance proteins (they decrease ABCB1 and increase ABCG2), E-cadherin, α-tubulin, and integrins amount as well as impair migration and invasion of the U87-MG cell line. Conclusions: The decrease of migration and invasion ability after phenothiazine derivatives treatment due to the increase of ABCG2 and E-cadherin as well as the decrease of α-tubulin, and integrins amounts can support the hypothesis that perphenazine and prochlorperazine have the anticancer effect on human glioblastoma U87-MG cells.
Enhanced Energy Storage Density and Excellent Thermal Stability Under Low Electric Fields of KF-added BNT–ST-AN Relaxor Ferroelectric Ceramics Prepared by the Solid-state Combustion Technique
Authors: Kornphom Chittakorn , Saenkam Kamonporn , Bongkarn Theerachai
Published: December 2021

Homogeneous 0.722(Bi0.5Na0.5TiO3)-0.228(SrTiO3)-0.05(AgNbO3) (BNT-ST-AN) ceramics with various amounts of potassium fluoride (KF) added were prepared by the solid-state combustion technique. The ceramics presented a single perovskite phase with coexisting rhombohedral (R), cubic (C) and orthorhombic (O) phases. The amount of the R phase decreased while the percentage of the C+O phase increased when KF addition increased from 0.0 to 3.0 mol%. The smallest grain size, the highest density and maximum dielectric constant (em) were achieved with a KF addition of 1.5 mol%. Following this design composition of the ceramics, the highest recoverable energy-storage density (Wrec ~1.60 J/cm3) and η above 85.8% at a low electric field (100 kV/cm) were obtained from BNT-ST-AN with KF addition at 1.5 mol% because this composition contained a morphotropic phase boundary (MPB) region and had the smallest grain size, which gave the lowest remnant polarization (Pr) and a large maximum polarization (Pm). Additionally, BNT-ST-AN with KF addition at 0.15 mol% exhibits stability over a wide range of temperatures (25–150°C) at a low electric field (100 kV/cm), which shows great potential in pulse-power system applications.
Influence of Vibrotactile Random Noise on the Smoothness of the Grasp Movement in Patients in Chemotherapy-Induced Peripheral Neuropathy
Authors: Osumi Michihiro , Sumitani Masahiko , Otake Yuko , Nishi Yuki , Nobusako Satoshi , Morioka Shu
Published: December 2021

Background Patients with chemotherapy-induced peripheral neuropathy (CIPN) often suffer from sensorimotor dysfunction of the distal portion of the extremities (e.g., loss of somatosensory sensation, numbness/tingling, difficulty typing on a keyboard, or difficulty undoing or doing up a button). The present study aimed to reveal the effects of subthreshold vibrotactile random noise stimulation on sensorimotor dysfunction in CIPN patients without exacerbating symptoms. Methods Twenty-five patients with CIPN and 28 age-matched healthy adults participated in this study. To reveal the effects of subthreshold vibrotactile random noise stimulation on sensorimotor function, participants were asked to perform grasp movement tasks during random noise stimulation delivered to the volar and dorsal wrist. We set three intensity conditions of the vibrotactile random noise: 0%, 60%, and 120% of the sensory threshold (Noise 0%, Noise 60%, and Noise 120% conditions). In the grasp movement task, the distance between the thumb and index finger was recorded while the participant attempted to grasp a target object, and the smoothness of the grasp movement was quantified by calculating normalized jerk in each experimental condition. The experimental data were compared using two-way repeated-measures analyses of variance with two binary factors: experimental condition (Noise 0%, 60%, 120%) × group (Healthy controls, CIPN patients).Results The smoothness of the grasp movement was only improved in the Noise 60% condition without exacerbating numbness/tingling in CIPN patients and healthy controls. Conclusions The current study suggested that the development of treatment devices using stochastic resonance can improve sensorimotor function for CIPN patients.Trial registration UMIN Clinical Trials Registry（UMIN-CTR）No. UMIN000024776https://rctportal.niph.go.jp/s/detail/um?trial_id=UMIN000024776#
Human Activity Recognition of Exoskeleton Robot with Supervised Learning Techniques
Authors: Mai Jiacheng , chen zhiyuan , Yi Chunzhi , Ding Zhen
Published: December 2021

Lower limbs exoskeleton robots improve the motor ability of humans and can facilitate superior rehabilitative training. By training large datasets, many of the currently available mobile and signal devices that may be worn on the body can employ machine learning approaches to forecast and classify people's movement characteristics. This approach could help exoskeleton robots improve their ability to predict human activities. Two popular data sets are PAMAP2, which was obtained by measuring people's movement through inertial sensors, and WISDM, which was collected people's activity information through mobile phones. With the focus on human activity recognition, this paper applied the traditional machine learning method and deep learning method to train and test these datasets, whereby it was found that the prediction performance of a decision tree model was highest on these two data sets, which is 99% and 72% separately, and the time consumption of decision tree is the least. In addition, a comparison of the signals collected from different parts of the human body showed that the signals deriving from the hands presented the best performance in terms of recognizing human movement types.
1,25-dihydroxyvitamin D3 Ameliorates Lupus Nephritis Through Inhibiting NF-κB and MAPKs Signaling Pathways in MRL/lpr Mice
Authors: Li Xuewei , Zhao Yingzhe , Xu Ning , Lv E , Ci Cunzeng , Li Xiangling
Published: December 2021

Background: Lupus nephritis (LN) is a common and serious complication of systemic lupus erythematosus (SLE). However, the etiology and pathogenesis of LN remain unknown. 1,25-dihydroxyvitamin D3（1,25-(OH)2-VitD3）is the active form of vitamin D, which has been known to have important functions in inflammation and immune diseases. In this study, we investigated Its protective effects and underlying mechanism in MRL/lpr mice, a well-studied animal model for lupus.Methods: At the age of 11 weeks, forty-eight MRL/lpr mice were randomly divided into two groups with 24 mice per group: the VitD3-treated group and control group. Mice in the VitD3-treated group received 4μg/kg 1,25-dihydroxyvitamin D3 in 1％ dimethyl sulfoxide (DMSO) intraperitoneal injection twice a week for 3 weeks (mice were executed at 0,2,4,6 weeks after treatment); mice in the control group treated with intraperitoneal injection of 1% DMSO for 3 weeks (mice were executed at 0,2,4,6 weeks after injections). The mice were sacrificed and the serum and kidney samples were collected respectively at planned intervals. Then the skin lesions, histological changes, inflammatory factors (TNF-α, IL-17) and immunological markers (A-ds DNA, C3, IgG, IgM) with time were analyzed between the groups. Furthermore, the NF-κB and MAPKs signaling pathways were also detected to explicate the underlying mechanism. Results: Compared to the control group, mice in the VitD3-treated group showed less skin lesions, less kidney injury, lower serum anti-ds DNA antibody, lower inflammatory cytokines TNF-α, IL-17 and higher serum complement C3; they also had less deposition of IgG, IgM and C3 within glomeruli. Moreover, the expressions of NF-κB and MAPKs signaling pathways were decreased, while those levels were increased with time.Conclusion: This study shows that 1,25-dihydroxyvitamin D3 exerts a protective effect against lupus nephritis via regulating the NF-κB and MAPKs signaling pathways, which will be developed as a potential agent for the treatment of Lupus nephritis. And the relationship between lupus activity and NF-kB and MAPKs signaling pathways with time was revealed.
Demographic and Clinical Parameters Are Comparable Across Different Types of Pediatric Feeding Disorders
Authors: Galai Tut , Friedman Gal , MA Michal Moses , Shemer Kim , Gal Dana L , Yerushalmy-Feler Anat , Lubetzky Ronit , Cohen Shlomi , Moran-Lev Hadar
Published: December 2021

Background: Knowledge and understanding of risk mechanisms associated with pediatric feeding disorders (PFD) remain limited. We aimed to investigate causative factors associated with PFD and their relation to specific PFD types according to the recent consensus WHO-based definition. Methods: We retrospectively reviewed the medical records of children with PFD and retrieved their demographic and clinical characteristics. Healthy age- and sex-matched children served as controls. Results: Included were 254 children with PFD [median (interquartile range) age 16.4 (9.5-33) months at diagnosis] and 108 children in the control group [median age 24.85 (14.5-28.5) months]. According to the WHO-based definition, disturbances in oral intake were predominantly related to nutritional dysfunction in 118 (46.6%), feeding skill dysfunction in 83 (32.3%), medical conditions in 42 (16.7%) and psychosocial dysfunction in 11 (4.4%). In multivariate analysis, children with PFD had a higher risk for lower socioeconomic background (P<0.01) and low birth weight (26.8% compared to 7.4% ,P<0.001). Moreover, significantly fewer children in the PFD group were breastfed (75% versus 89%, P=0.003). There were no significant differences in any of those variables between PFD types. Conclusions: Low socioeconomic status, lack of breastfeeding, and low birth weight were significantly more frequent in children with PFD. PDF manifest as multiple dysfunctions, thus highlighting the need to offer these children and their families multidisciplinary care.
The Utility of Serum Anti-thyroglobulin Antibody and Thyroglobulin in the Preoperative Differential Diagnosis of Thyroid Follicular Neoplasm
Authors: Chen Zhijiang , Lin Yinghe , Lai Shuiqing , Wang Peiqing , Li Jinlian , Wang Long , Guan Haixia , Kuang Jian
Published: December 2021

PurposeIt is challenging to distinguish follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA) before surgery due to the lack of malignant ultrasound features, the underdiagnosis by fine-needle biopsy, and the absence of definitive markers. We investigated whether thyroglobulin (Tg), anti-thyroglobulin antibody (TgAb), thyroid peroxidase antibodies (TPOAb), and thyroid stimulating hormone (TSH) could help differentiate FTC from FTA.MethodsA total of 319 patients with follicular neoplasms were included. We analyzed the serum markers as continuous and categorical variables between FTC and FTA. Also, we analyzed the prevalence of FTC in different serum markers groups.ResultsThe TgAb was a risk factor of FTC. Versus the TgAb group (≤11.68 IU/mL), OR of the group (11.69-30.50 IU/mL) and the group (＞30.50 IU/mL) were 2.206 (1.114-4.369, P=0.023) and 3.247 (1.684-6.260, P＜0.001), respectively. Versus the TgAb group (≤11.68 IU/mL), the malignant prevalence of the group (＞30.50 IU/mL) was higher (13.1% vs. 32.9%, P=0.001). In TgAb (-) patients, the Tg was another risk factor of FTC. Versus the Tg group (≤38.51 ng/mL), OR of the group (＞434.60 ng/mL) was 3.836 (1.625-9.058, P=0.002); the malignant prevalence of the group (＞434.60 ng/mL) was 47.2% and higher than other groups.ConclusionsThe TgAb and Tg may have utility in the preoperative differential diagnosis of follicular neoplasm. The higher TgAb and Tg were associated with higher malignant risk. Thus, we should be cautious of preoperative TgAb and Tg in follicular neoplasm.
Wheat Leaf Area Index Prediction Using Data Fusion Based on High-Resolution Unmanned Aerial Vehicle Imagery
Authors: Wu Shuang , Deng Lei , Guo Lijie , Wu Yanjie
Published: December 2021

Background: Leaf Area Index (LAI) is half of the amount of leaf area per unit horizontal ground surface area. Consequently, accurate vegetation extraction in remote sensing imagery is critical for LAI estimation. However, most studies do not fully exploit the advantages of Unmanned Aerial Vehicle (UAV) imagery with high spatial resolution, such as not removing the background (soil and shadow, etc.). Furthermore, the advancement of multi-sensor synchronous observation and integration technology allows for the simultaneous collection of canopy spectral, structural, and thermal data, making it possible for data fusion.Methods: To investigate the potential of high-resolution UAV imagery combined with multi-sensor data fusion in LAI estimation. High-resolution UAV imagery was obtained with a multi-sensor integrated MicaSense Altum camera to extract the wheat canopy's spectral, structural, and thermal features. After removing the soil background, all features were fused, and LAI was estimated using Random Forest and Support Vector Machine Regression.Result: The results show that: (1) the soil background reduced the accuracy of the LAI prediction, and soil background could be effectively removed by taking advantage of high-resolution UAV imagery. After removing the soil background, the LAI prediction accuracy improved significantly, R2 raised by about 0.27, and RMSE fell by about 0.476. (2) The fusion of multi-sensor synchronous observation data improved LAI prediction accuracy and achieved the best accuracy (R2 = 0.815 and RMSE = 1.023). (3) When compared to other variables, 23 CHM, NRCT, NDRE, and BLUE are crucial for LAI estimation. Even the simple Multiple Linear Regression model could achieve high prediction accuracy (R2 = 0.679 and RMSE = 1.231), providing inspiration for rapid and efficient LAI prediction.Conclusions: The method of this study can be transferred to other sites with more extensive areas or similar agriculture structures, which will facilitate agricultural production and management.
An Investigation Into the Effect of Pre-bending on the Tube Hydro-forging Technology
Authors: Lin Caiyuan , Chu Guan-Nan , Sun Lei
Published: December 2021

Tube hydro-forging (THFG) combining with the pre-bending is an advanced method to manufacture the complex cross-sectional tubular component with curved axis. However, the effect of pre-bending on the subsequent THFG, especially on the critical internal pressure required to inhibit wrinkling, has not been clarified yet. Therefore, this paper makes a detailed study on it. At first, based on the energy method, the change rule between the critical internal pressure and the hoop strain was established when pre-bending was considered. Subsequently, the mechanics condition difference between single and double curvature differential segment during THFG was analyzed. Via the plastic theory, the distribution of hoop strain could be obtained. Mainly due to the uneven distribution of thickness and cold work-hardening caused by pre-bending, the maximum hoop strain at the outer straight-wall was greater than that at the inner straight-wall during THFG. Substituting the maximum hoop strain at the outer/inner straight-wall into the change rule, then their mathematical model of the critical internal pressure to restrain the wrinkling could be solved respectively. Finally, the critical internal pressure considering pre-bending was determined by that of outer straight-wall, and its value was always greater than the critical internal pressure without considering pre-bending under the same punch stroke. With the increase of bending radius, the critical internal pressure difference between considering and not considering pre-bending also increases. When the bending radius was 250 mm, the critical internal pressure difference was 33%, while it increased to 74% as the bending radius reduced to 100 mm, all of which were verified by experiment. The effect of friction coefficient on the critical internal pressure was also studied. In conclusion, this work provided a new and more accurate prediction model of critical internal pressure to guide practical production for when existing the pre-bending.
Self-efficacy in Breastfeeding Predicts How Mothers Perceive Their Preterm Infant’s State-Regulation
Authors: Rosenblad Andreas Karlsson , Funkquist Eva-Lotta
Published: December 2021

Background: Mothers of preterm infants often perceive the infant as having problems with crying, sleeping and feeding, sometimes summarised as ‘state-regulation’. Breastfeeding rates are lower among preterm infants, and the mother’s self-efficacy in breastfeeding is central to understanding which mothers are going to breastfeed their infants. The aim of this study was to investigate whether the late preterm infant’s mother’s self-efficacy in breastfeeding was associated with how the mother experienced her infant’s state-regulation at three months of corrected age.Methods: The study had a prospective and longitudinal design with a consecutive data collection through questionnaires. Results: The analyses showed that being an older mother, perceiving breastfeeding support, and having a higher breastfeeding self-efficacy were all significantly associated with identifying the infant as having better state-regulation. Conclusion: There was an association between mothers’ self-efficacy in breastfeeding and her perceptions of how good state-regulation the infant had. This is an important finding, as self-efficacy is a manageable factor that could positively affect how the mother perceives taking care of her infant.Clinical implication: Health care professionals should target mother’s self-efficacy in breastfeeding to improve mother-infant relationship.
Resonance Y-shape Solitons and Mixed Solutions for a (2+1)-dimensional Generalized Caudrey-Dodd-Gibbon-Kotera-Sawada Equation in Fluid Mechanics
Authors: ma hongcai , Yue Shupan , Deng Aiping
Published: December 2021

Under the well-known bilinear method of Hirota, the specific expression for N-soliton solutions of (2+1)-dimensional generalized Caudrey-Dodd-Gibbon-Kotera-Sawada(gCDGKS) equation in fluid mechanics is given. By defining a noval restrictive condition on N-soliton solutions, resonant Y-type and X-type soliton solutions are generated. Under the previous new constraints, combined with the velocity resonance method and module resonant method, the mixed solutions of resonant Y-type solitons and line waves, breather solutions are found. Finally, with the support of long wave limit method, the interaction between resonant Ytype solitons and higher-order lumps is shown, and the motion trajectory equation before and after the interaction between lumps and resonant Y-type solitons is derived.
Pan-cancer survey and evaluation of the oncogenic role of NF-κB1
Authors: Huang Lihong , zheng ruoling , Gong Huasong , Qiao Yongchao
Published: December 2021

Although emerging cells or animals based evidence supports an association between nuclear factor kappa-B1 (NF-κB1) cells and cancers, there has no pan-cancer analysis. Therefore, based on TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus) data sets, we first studied the potential carcinogenic effect of NF-κB1 in 33 tumors. As we not only found high expression of NF-κB1 in most tumors, but also found that NF-κB1 expression is closely related to the prognosis of tumor patients. Enhanced phosphorylation of S893 was observed in several tumors, such as breast cancer, uterine corpus endometrial carcinoma or lung adenocarcinoma. In thymoma, NF-κB1 expression was relevant to CD8+ T-cell infiltration levels, and tumor-associated fibroblast infiltration has also seen in other tumors, such as uterine corpus endometrial carcinoma or glioblastoma multiforme. In addition, the functional mechanism of NF-κB1 also involves the related functions of protein processing and RNA metabolism. In this study, NF-κB1 was pan-cancer study in order to have a systematic and comprehensive understanding of the carcinogenic effect of NF-κB1 in different tumors.
Effect of Prior Antibiotic or Chemotherapy Treatment on Immunotherapy Response in Non-small Cell Lung Cancer
Authors: Nyein Andrew F. , Bari Shahla , Hogue Stephanie , Zhao Yayi , Maller Bradley , Sha Sybil , Gomez Maria F. , Rollison Dana E. , Robinson Lary A.
Published: December 2021

Background Treatment outcomes of advanced non-small cell lung cancer (NSCLC) have substantially improved with immune checkpoint inhibitors (ICI), although only approximately 19% of patients respond to immunotherapy alone, increasing to 58% with the addition of chemotherapy. The gut microbiome has been recognized as a modulator of ICI response via its priming effect on the host immune response. Antibiotics as well as chemotherapy reduce gut microbial diversity, hence altering composition and function of the gut microbiome. Since the gut microbiome may modify ICI efficacy, we conducted a retrospective study evaluating the effects of prior antibiotic or chemotherapy use on NSCLC patient response to ICI.Methods We retrospectively evaluated 256 NSCLC patients treated between 2011-2017 at Moffitt Cancer Center with ICI ± chemotherapy, examining the associations between prior antibiotic or chemotherapy use, overall response rate and survival. Relative risk regression using a log-link with combinatorial expectation maximization algorithm was performed to analyze differences in response between patients treated with antibiotics or chemotherapy versus patients who didn’t receive antibiotics or chemotherapy. Cox proportional hazards models were constructed to evaluate associations between risk factors and overall survival. Results Only 46 (18% of 256) patients used antibiotics prior to and/or during ICI treatment, and 146 (57%) had prior chemotherapy. Antibiotic users were 8% more likely to have worse overall response rate (RR:1.08; CI:0.93-1.26; p=0.321), as well as a 35% worse overall survival (HR:1.35; CI:0.91-2.02; p=0.145), although results were not statistically significant. However, prior use of chemotherapy was significantly associated with poor ICI response (RR:1.24; CI:1.05-1.47; p=0.013) and worse overall survival (HR:1.47; CI:1.07-2.03; p=0.018). Conclusions Patients receiving antibiotics prior to and/or during ICI therapy might experience worse treatment outcomes and survival than unexposed patients, although these associations were not statistically significant and hence warrant further prospective study. Prior chemotherapy significantly reduced ICI response and overall survival. Antibiotic or chemotherapy exposure may negatively impact ICI response, perhaps through disruption of the eubiotic gut microbiome.
Thorough Statistical Analyses of Breast Cancer Co-Methylation Patterns
Authors: Sun Shuying , Dammann Jael , Lai Pierce , Tian Christine
Published: December 2021

Background: Breast cancer is one of the most commonly diagnosed cancers. It is associated with DNA methylation, an epigenetic event with a methyl group added to a cytosine paired with a guanine, i.e., a CG site. The methylation levels of different genes in a genome are correlated in certain ways that affect gene functions. This correlation pattern is known as co-methylation. It is still not clear how different genes co-methylate in the whole genome of breast cancer samples. Previous studies are conducted using relatively small datasets (Illumina 27K data). In this study, we analyze much larger datasets (Illumina 450K data). Results: Our key findings are summarized below. First, normal samples have more highly correlated, or co-methylated, CG pairs than tumor samples. Both tumor and normal have more than 93% of positive co-methylation, but normal samples have significantly more negatively correlated CG sites than tumor samples (6.6% vs. 2.8%). Second, both tumor and normal samples have about 94% of co-methylated CG pairs on different chromosomes, but normal samples have 470 million more CG pairs. Highly co-methylated pairs on the same chromosome tend to be close to each other. Third, a small proportion of CG sites’ co-methylation patterns change dramatically from normal to tumor. The percentage of differentially methylated (DM) sites among them is larger than the overall DM rate. Fourth, certain CG sites are highly correlated with many CG sites; the top 100 of such super-connector CG sites in tumor and normal samples have no overlaps. Fifth, both highly changing sites and super-connector sites’ locations are significantly different from the genome-wide CG sites’ locations. Sixth, chromosome X co-methylation patterns are very different from other chromosomes. Finally, the network analyses of genes associated with several sets of co-methylated CG sites identified above show that tumor and normal samples have different patterns. Conclusions: Our findings will provide researchers with a new understanding of co-methylation patterns in breast cancer. Our ability to thoroughly analyze co-methylation of large datasets will allow researchers to study relationships and associations between different genes in breast cancer.
Pupillary Response to Chromatic Light Stimuli as a Biomarker at the Early Stage of Glaucoma
Authors: López Carla Arévalo , Román Samuel Madariaga , Plaza Ivan
Published: December 2021

Glaucoma is a multifactorial neurodegenerative disease of the optic nerve currently considered a severe health problem because of its high prevalence, being the primary cause of irreversible blindness worldwide. The most common type corresponds to Primary Open-Angle Glaucoma (POAG). Glaucoma produces, among other alterations, a progressive loss of Retinal Ganglion Cells (RGC) and its axons, key to generate the action potential that reaches the visual cortex to create the visual image. It indicates a Visual Field (VF) loss whose main feature is to be painless, and this makes early detection difficult, causing a late diagnosis and delaying a timely treatment indication that slows down its progression. Intrinsically photosensitive Retinal Ganglion Cells (ipRGCs), which represent a subgroup of RGCs being sensitive to damage, are characterized by reacting to short-wave light stimulation close to 480 nm and among their non-visual function, the role in the generation of the pupillary reflex stands out. Currently, the sensitivity of clinical trials correlates to RGC damage, however the need for an early damage biomarker is still relevant. It is an urgent task to create new diagnostic approaches to detect an early stage of glaucoma in a prompt, quick, and economical manner. We suggest evaluating the pupillary response to chromatic light as a potential biomarker of disease, its diagnostic benefit, and its cost-effectiveness in clinical practice to reduce irreversible damage caused by glaucoma.
Prevalence And Risk Factors of Electrocardiogram Abnormalities In Patients With Rheumatoid Arthritis: A Machine Learning Study With Follow-Up Data
Authors: Hu Zuoyu , Hu Zhuoran , Guo Xinghua , Weng Weizhen , Chen Ye , Pan Yunfeng
Published: December 2021

OBJECTIVES: Electrocardiogram (ECG) abnormalities could predict some subsequent cardiovascular events. Cardiac involvement is a major extra-articular manifestation in rheumatoid arthritis (RA). We aimed to determine the prevalence of three major ECG abnormalities in RA patients, discover the associated ECG abnormalities associated with machine learning (ML) approaches, and then examine these preselected factors in the follow-up patients with traditional Cox regression. METHODS: Consecutive RA patients’ records were retrieved from the hospital database; about one-third of patients had follow-up data. Abnormal ECGs with clinical significance were grouped into non-specific ST-segment/T-wave changes, QT interval prolongation, and QRS-T angle increase. Machine learning approaches assessed the associated factors of these abnormalities. The top-important factors selected by the most optimal ML would be used to construct Cox regression models. RESULTS: Two hundred twenty-six patients were enrolled for the first step cross-sectional study. Non-specific ST-T changes (27%) were the most prevalent abnormalities among patients with abnormal ECGs. Random forest models had the best performance in the discovery of associated factors for three outcomes. Cox regression validated that rheumatoid factor and low-density lipoprotein were common risk factors within those three abnormalities. Hypertension, ESR, and serum immunoglobulin G were influential factors for non-specific ST-T changes, prolonged QT interval, and increased QRS-T angle specifically. CONCLUSION: Non-specific ST-T changes were the most common abnormalities seen in ECGs of RA patients. Our finding suggests that rheumatoid factor, LDL, hypertension, and inflammatory indicators are important risk factors for these ECG abnormalities.
Clarification and repair in emergency remote EFL classes
Authors: Giacosa Antonella
Published: December 2021

During the sudden shift in education onto digital platforms due to the Covid-19 emergency, teachers became streamers and experimented with new tools to involve their students in video-mediated, multi-floor, multiparticipant, and multimodal interactions. In turn, students experienced new ways to participate in lessons and interact with instructors. This study focuses on clarification and repair in videoconferencing as a strategy to address trouble in video-mediated communication and to re-establish mutual understanding. Through participant observation of online classes, the researcher collected data on classroom interactions, which are analyzed through conversation analysis. The findings show how the digital affordances of video-mediated conversation help teachers and students manage intersubjectivity and compensate for the lack of non-verbal cues typical in face-to-face interaction, such as facial expressions or tone of voice. Consequently, this article argues that the wisdom gained during the pandemic can help teachers and lecturers better deal with clarification and repair in digital conversations. Ultimately, it can increase their digital interactional competence, thus giving way to more interaction and learning in EFL classes, both online and in-person.
Recensione: Russel, Victoria & Murphy-Judy, Kathryn (2020). Teaching language online. Routledge.
Authors: Casentini Marco
Published: December 2021

La presente recensione mira ad offrire una valutazione critica del volume Teaching Language Online di Victoria Russel e Kathryn Murphy-Judy. Nella prima parte della recensione viene introdotto l’argomento generale trattato dal libro, descrivendone brevemente i contenuti di ogni capitolo. Nella seconda parte si fornisce una descrizione dei contenuti in prospettiva critica, evidenziandone i punti di forza e le eventuali criticità.
Ripensare l’insegnamento delle lingue straniere a partire dall’esperienza della didattica a distanza: introduzione al numero speciale
Authors: Borro Ilaria , Conti Sergio , Fiorenza Elisa
Published: December 2021

La didattica a distanza emergenziale determinata dalla pandemia da Covid-19 ha posto insegnanti e studenti di fronte a sfide inedite, forzando un cambiamento senza precedenti in termini di entità e rapidità. Questo numero speciale raccoglie contributi sulla didattica delle lingue, accomunati dalla volontà di trarre vantaggio dalle problematicità legate all’insegnamento a distanza per innescare riflessioni e cambiamenti necessari e duraturi, capaci di prescindere dalla situazione emergenziale che li ha generati. Questa introduzione descrive il contesto in cui insegnanti e studenti si sono trovati a operare, sottolineandone le implicazioni glottodidattiche in termini di gestione dell’input, dell’output, dell’interazione e della valutazione delle competenze. Offriamo una sintesi dei contributi inclusi nel numero speciale, seguita da una riflessione sulle possibili conclusioni trasversali all’intero volume.