bluuebunny/crossref_metadata_2025 huggingface dataset:
Eccentricity Reduction of Slotless Self- Bearing Motor System Based on Adaptive Neural Network and Sliding Mode Control
Authors: Giap Van Nam , Nguyen Quang Dich , Pham Duc Hung , Lin Chih-Min
Published: August 2023

This paper presents the effectiveness of a hybrid control method for the slotless self-bearing motor (SSBM), which combined by an improved adaptive radial basic function neural network (ARBFNN) and adaptive improved reaching law (AIRL) sliding-mode control (SMC) with the aim of softening the eccentricity of the rotor of SSBM. The source of eccentricity is considered from the disturbances and uncertainties and the self-vibration of the rotor. First, the mathematical model of the bearing motor system with fully embedded sources of the perturbations is represented. Second, the proposed control algorithms for SSBM system with the proof of stability via the Lyapunov theorem are given. Third, the illustrative examples of simulation and experimental studies are given to shown the effectiveness and power of the proposed control algorithms. The outcomes of the proposed control algorithms are small overshoots, small settling-times, and stable steady-states. The tested disturbances in the simulation study were mostly rejected by an ARBFNN. The performance of proposed controller with ARBFNN in experiment is better the case of controller without ARBFNN.
Movies vs books or comic-books for consolidating knowledge in college students: Results of an empirical study
Authors: Romero-Martínez Ángel , Sarrate-Costa Carolina , Martínez Manuela , Luis Moya-Albiol
Published: August 2023

Objectives. Not only does integrating movies into the college classroom represent an opportunity for promoting knowledge, it also increases students’ interest in daily lessons. However, little is known regarding the type of academic movie tasks which might help establish relevant concepts in Psychobiology. Hence, the main objectives of this study were: 1) to analyse whether using commercial movies to answer a set of questions would have a positive impact on the acquisition of new concepts; 2) to evaluate whether watching movies presents specific advantages in student performance when compared to reading books or comic-books by answering the same questions and evaluating student perception regarding satisfaction, commitment, difficulty, and usefulness.
Method. Participants were randomly assigned to two mandatory (n= 89) or voluntary (n = 74) tasks after indicating whether they preferred watching movies or reading books or comic-books to answer specific questions. The total score of both tasks (assessed by two independent reviewers based on common correction criteria) was collected. In addition, an online survey gathered students’ hobbies and habits before starting the tasks, as well as their perceptions regarding the tasks after completing them. The final score was obtained from the final objective exam which measured their subject knowledge.
Results. Our study revealed that students preferred watching movies to complete their tasks, which had a positive impact on the consolidation of their knowledge. Nonetheless, there were no differences between the groups’ (type of stimulus or mandatory character) performance or students’ perception of both tasks.
Conclusions. Our study highlights which type of academic tasks could be employed in Psychobiology for consolidating knowledge. Moreover, it reinforces the notion that students’ preferences do not necessarily correspond with their performance.
Charitable deductions: modelling of longitudinal taxpayers’ data for time-regularity estimation and future predictions
Authors: Pittavino Marta , Huber Giedre Lideikyte
Published: August 2023

The present study is the continuation of an existing one, with a new research question and novel statistical predictions. It represents the first large-scale time-series analysis of tax incentives for charitable giving in Switzerland for regular donors, and one of the few charitable deductions’ projections globally. Using unique panel data of the entire Geneva taxpayers’ population, from 2001 to 2011, we concentrate on the frequency of donations, by analyzing the characteristics of regular donors. This period also encompassed a legal reform that raised ceilings for charitable deductions. Taxpayers who deducted only once represent 29% of the study population, while the remaining 71% indicate taxpayers deducting more than once. We also observe that regular donors are not driven by the ceilings for tax incentives, however, wealth is an important variable characterizing the donations’ frequency. Moreover, time-series forecasting models have been used to project the future amount of donations and donors. A total amount of donations in a range of (79, 114) million in 2012-2022 has been predicted from the best model. These figures help understanding the magnitude of deductions and they allow to take better decision of the ceiling of tax incentives for charitable giving, while highlighting the main relevant factors.
Characterization of cadmium biosorption by cadmium-resistant strains: Equilibrium, kinetics, and thermodynamics
Authors: Xie Weixia , Zhu Mengke , Fan Ruijuan , Yan Xingfu
Published: August 2023

In this paper, six cadmium (Cd) resistant strains were used to find the optimal conditions and understand the biosorption process of strains. Influences of pH, temperature, initial Cd2+ content, bacterial dose, and treatment time on Cd2+ biosorption were investigated. The key mechanism of Cd2+ biosorption by selected microbes was preliminarily determined by examining the biosorption process using isothermal biosorption and kinetic models. The strain showed best Cd2+ removal effect at initial Cd2+ content of 50 ~ 100 mg·L-1, pH 7 ~ 9, 30°C temperature, and adsorbent dose of 0.01 g (Cd-6, Cd-7), 0.04 g (Cd-5), and 0.08 g (Cd-1, Cd-2, and Cd-3). The removal efficiency at these conditions was found to be above 90%. The equilibrium state was observed after 120 min of culture time. In six strains, the Cd2+ biosorption obeyed the Langmuir biosorption model, intra-particle diffusion model, and quasi-second-order kinetic model. This suggested that Cd2+ was absorbed by the six strains through monolayer biosorption. Moreover, chemical biosorption was found to be the major restricting factor for the biosorption rate, along with intra-particle diffusion. The six strains Cd2+ biosorption, with spontaneous endothermic reaction below 30°C and spontaneous exothermic reaction above 30°C. This study provides valuable strain resources and data support for the remediation of soil having high concentration of Cd.
Reducing Salivary Toxicity with Adaptive Radiotherapy (ReSTART): A Randomized Controlled Trial comparing conventional IMRT to adaptive IMRT in head and neck Squamous Cell Carcinomas
Authors: Ghosh-Laskar Sarbani , Sinha Shwetabh , Kumar Anuj , Samanta Asesh , Mohanty Samarpita , Kale Srikant , Khan Faizalam , Lewis Shirley , Murthy Vedang
Published: August 2023

Objectives:
The utility of Adaptive Radiation Therapy (ART) in Head and Neck Squamous Cell Carcinoma (HNSCC) remains to be ascertained. While multiple retrospective and single-arm prospective studies have demonstrated its efficacy in decreasing parotid doses and reducing xerostomia, there is a lack of adequate randomized evidence.
Methods and Analysis:
ReSTART is an ongoing phase III randomized trial of patients with previously untreated, locally advanced HNSCC of the oropharynx, larynx, and hypopharynx. Patients are randomized in a 1:1 ratio to the standard Intensity Modulated Radiation Therapy (IMRT) arm {Planning Target Volume (PTV) margin 5 mm} vs. ART arm (standard IMRT with a PTV margin 3 mm, two planned adaptive planning at 10th and 20th fractions). The stratification factors include the primary site and nodal stage. The RT dose prescribed is 66Gy in 30 fractions for high-risk PTV and 54Gy in 30 fractions for low-risk PTV over five weeks, along with concurrent chemotherapy.
The primary endpoint is to compare salivary toxicity between arms using salivary scintigraphy 12 months’ post-radiation. To detect a 25% improvement in the primary endpoint at 12 months in the ART arm with a two-sided 5% alpha value and a power of 80% (and 10% attrition ratio), a sample size of 130 patients is required (65 patients in each arm). The secondary endpoints include acute and late toxicities, locoregional control, disease-free survival, overall survival, quality of life, and xerostomia scores between the two arms.
Discussion:
The ReSTART trial aims to answer an important question in Radiation Therapy for HNSCC, particularly in a resource-limited setting. The uniqueness of this trial, compared to other ongoing randomized trials, includes the PTV margins and the xerostomia assessment by scintigraphy at 12 months as the primary endpoint.
Ethics and dissemination:
This trial was approved by the Institutional Ethical Committee of Tata Memorial Hospital, Mumbai, on 3rd February 2017.
Trial Registration Number:
The trial is prospectively registered with the Clinical Trial Registry of India (CTRI) (Reg no: CTRI/2018/08/ 015531).
Outcomes of Robotic surgery in a single institution high volume hepatobiliary oncology unit
Authors: Fellow Kunal Nandy , Patkar Shraddha , Varty Gurudutt , Shah Tanvi , Goel Mahesh
Published: August 2023

Introduction
Hepatobiliary surgery has traditionally been performed via an open approach. With the advent of robotic surgery, minimal access approach in hepatobiliary oncology has gained impetus due to it technical superiority and favorable learning curve over laparoscopy. We present our experience of Da Vinci Xi system in hepatobiliary oncology
Materials and methods
This is a retrospective study from a prospectively maintained database. All patients who underwent surgery between June 2015 till July 2023 for suspected gallbladder cancer and primary or metastatic liver tumors were included.
Results
A total of 113 patients were included, of which 2 patients were declared inoperable in view of peritoneal metastasis. Seventy-five patients underwent surgery for gallbladder related pathologies that included 47(42.3%) radical cholecystectomies, 27(24.3%) simple cholecystectomies and 1(0.9%) revision cholecystectomy. 36 patients underwent surgeries for primary or metastatic liver tumors which included 26(23.4%) left lateral hepatectomy, 6 (5.4%) non-anatomical resection, 2(1.8%) right hepatectomy, 1(0.9%) robotic assisted right hepatectomy and 1(0.9%) left hepatectomy. Conversion to open was required in 17 (15.3%) patients. Median blood loss was 250 (10-3500) ml and median hospital stay was 4 (1-25) days. Median lymph nodal yield was 8(2-22) in patients who underwent lymph nodal dissection for gallbladder cancer. Eleven (9.9%) patients had significant morbidity (Clavien Dindo Grade III or more). There was one post operative mortality (0.9%).
Conclusion
Robotic hepatobiliary surgery is feasible and can be performed safely after adequate training. Patient selection is of utmost importance and is the key to establishing a robust robotic hepatobiliary oncosurgery program.
Racial and Socioeconomic Disparities in Survival Among Women with Advanced-stage Ovarian Cancer Who Received Systemic Therapy
Authors: Washington Caretia J. , Karanth Shama D. , Wheeler Meghann , Aduse-Poku Livingstone , Braithwaite Dejana , Akinyemiju Tomi F.
Published: August 2023

Purpose
The purpose of this study was to assess the association between race/ethnicity and all-cause mortality among women with advanced-stage ovarian cancer who received systemic therapy.
Methods
We analyzed data from the National Cancer Database on women diagnosed with advanced-stage ovarian cancer from 2004 to 2015 who received systemic therapy. Race/ethnicity was categorized as Non-Hispanic (NH) White, NH-Black, Hispanic, NH-Asian/Pacific Islander, and Other. Income and education were combined to form a composite measure of socioeconomic status (SES) and categorized into low-, mid-, and high-SES. Multivariable Cox proportional hazards models were used to assess whether race/ethnicity was associated with the risk of death. Models were adjusted for age, SES, comorbidity level, and receipt of surgery.
Results
The study population comprised 53,367 women (52.4% ages ≥ 65 years, 82% NH-White, 8.7% NH-Black, 5.7% Hispanic, and 2.7% NH-Asian/Pacific Islander) in the analysis. After adjusting for covariates, the NH-Black race was associated with a higher risk of death versus NH-White race (aHR: 1.12; 95% CI: 1.07,1.18), while Hispanic race was associated with a lower risk of death compared to NH-White women (aHR: 0.87; 95% CI: 0.80, 0.95). Furthermore, NH-Black women versus NH-White women had an increased risk of mortality among those with low-SES characteristics (aHR:1.12; 95% CI:1.03–1.22) and mid-SES groups (aHR: 1.13; 95% CI:1.05–1.21).
Conclusions
Among women with advanced-stage ovarian cancer who received systemic therapy, NH-Black women experienced poorer survival compared to NH-White women. Future studies should be directed to identify drivers of ovarian cancer disparities, particularly racial differences in treatment response and surveillance.
Process simulation of steam-gasification of biomass for H2 -enriched gaseous fuel production
Authors: Cao Yan , Bai Yu , Du Jiang
Published: August 2023

Gasification is recognized as an environmentally friendly process for converting low-quality biomass materials into a valuable gaseous fuel. In this work, a novel simulation model for air/steam gasification of biomass (wood pellet) is developed using ASPEN plus to study the feasibility of producing H2-rich syngas. Benzene and naphthalene were used as tar model compounds and olivine was used as a catalyst. The model developed in this research includes five main sections, which are: dehydration reactor (DRY), decomposition reactor (PYR), tar cracking reactor (TAR-C), gasification reactor (GASIF1) and catalyst reactor (GASIF2). The model was validated with the experimental data available in the published literature and a good agreement was achieved. In the gasification section, influence of air ratio, AR (0.2-0.4), steam/biomass ratio, SBR (0-1.0) and temperature (725-875 °C) was studied. It was found that the addition of olivine not only decreases the tar yield, but also somewhat improved CGE by increasing H2 content in the gas stream. CCE also increased slightly, which can be due to the conversion of the carbon content in the tar to light hydrocarbons (CH4) and other carbon-based gases. In addition, air-steam gasification of wood pellet with olivine could achieve the highest H2 content of 15.17 vol% under optimal conditions (AR=0.3, SBR=0.66 and T=825 °C), in which the CCE and CGE reached 87.35% and 45.46%, respectively.
Effects of abiotic stress associated with climate change on potato yield and tuber quality under multi-environment trial in New Zealand
Authors: Siano Allan BANASIHAN , Roskruge Nick , Kerckhoffs Huub , Sofkova-Bobcheva Svetla
Published: August 2023

In the 2018/19 growing season, a multi-environment trial in Opiki, Hastings, and Ohakune located in three different regions of the North Island of New Zealand was conducted to evaluate responses of selected potato cultivars to abiotic stress associated with climate change. Heat and drought stresses were evident with supra-optimal temperatures (> 25°C) in Opiki and Hastings, and sub-optimal rainfall (< 500mm) in Opiki, which influenced the different morpho-physiological characteristics of the potato crop, ultimately affecting yield and tuber quality. These abiotic stresses also increased the incidence of malformation, growth cracks, and second growth in tubers reducing the total and marketable yields by 43% and 45%, respectively. In addition, the genotype × environment analysis showed that Ohakune had the most favorable environmental conditions for potato production since all cultivars in this site had superior marketable yields. ‘Taurus’ was the most stable and adaptable cultivar across trial sites (wide adaptation), while Hermes’ and ‘Snowden’ were more adapted under Opiki and Hastings conditions (specific adaptation), respectively. As established in this study, heat and drought stresses have significant effects on the morpho-physiology, yield, and tuber quality of commercial potato cultivars in New Zealand.
Determining the optimal cut-off scores for the Chinese version of the Memorial Anxiety Scale for Prostate Cancer (MAX-PC)
Authors: Huang Qingmei , Jiang Ping , Ding Yuanqi , Zheng Li , Luo Jie , Dai Yun , Wu Fulei , Wang Wei
Published: August 2023

Purpose
Anxiety is a common emotion experienced by patients with prostate cancer (PCa), and can be exacerbated by testing the prostate-specific antigen (PSA) index. The Memorial Anxiety Scale for Prostate Cancer (MAX-PC) was developed to assess the cancer-specific anxiety of these patients, but lack of appropriate thresholds for this scale limits its use. This study aimed to utilize ROC curve analysis to identify the best cut-off values for the Chinese version of the MAX-PC scale.
Methods
A cross-sectional survey was conducted using the Chinese version of the MAX-PC scale and the Generalized Anxiety Disorder Scale (GAD). ROC curve analysis, Youden index, Kappa consistency test and McNemar test were used for the optimal cutoff points for screening mild, moderate, and severe cancer-specific anxiety levels in patients with PCa, on the Chinese version of the MAX-PC scale.
Results
Two eighty-seven patients with PCa completed the survey. The appropriate cut-off values for the MAX-PC scale for screening patients with PCa for cancer-specific anxiety were 20, 28, and 38 for mild, moderate, and severe anxiety, respectively with the highest Youden indices. The Kappa and McNemar’s test showed the best level of consistency with values of 0.627, 0.580, and 0.606 for screening mild, moderate, and severe anxiety, respectively.
Conclusions
The scores 20, 28, and 38 are the best cut-off values for the Chinese version of the MAX-PC scale. This scale should be used for screening cancer-specific anxiety for patients with PCa to assess and evaluate their anxiety levels and provide targeted interventions.
Multidimensional optimization for accelerating light-powered biocatalysis in Rhodopseudomonas palustris
Authors: Zhang Yang , Meng Wenchang , He Yuting , Chen Yuhui , Shao Mingyu , Yuan Jifeng
Published: August 2023

Background
Whole-cell biocatalysis has been exploited to convert a variety of substrates into high-value bulk or chiral fine chemicals. However, the traditional whole-cell biocatalysis typically utilizes the heterotrophic microbes as the biocatalyst, which requires carbohydrates to power the cofactor (ATP, NAD(P)H) regeneration.
Results
In this study, we sought to harness purple non-sulfur photosynthetic bacterium (PNSB) as the biocatalyst to achieve light-driven cofactor regeneration for cascade biocatalysis. We substantially improved the performance of Rhodopseudomonas palustris-based biocatalysis by using a highly active and conditional expression system, blocking the side-reactions, controlling the feeding strategy, and attenuating the light shading effect. We found that 50 mM ferulic acid could be completely converted to vanillyl alcohol in the recombinant strain, reaching 770.8 mg/g-cdw vanillyl alcohol. In addition, > 99.9% conversion of p-coumaric acid to p-hydroxybenzyl alcohol (620.7 mg/g-cdw) was similarly achieved under light-anaerobic conditions. Moreover, we examined the isoprenol utilization pathway (IUP) for pinene synthesis and 188 mg/g-cdw pinene with 92% conversion rate from 30 mM isoprenol was obtained.
Conclusions
Taken together, these results suggested that R. palustris could be a promising host for light-powered biotransformation, which offers an efficient approach for synthesizing value-added chemicals in a green and sustainable manner.
Probing the Biology of Zinc Alpha 2-Glycoprotein and the role it plays in cachexia
Authors: Pandit Parth
Published: August 2023

Background
Cachexia is a metabolic disease characterized by significant weight loss and muscle wasting, and it is responsible for a substantial number of cancer-related deaths. Zinc-alpha-2-glycoprotein (ZAG) plays a role in the regulation of weight and body fat through the metabolism of lipids and glucose. In healthy individuals, ZAG promotes homeostasis by inducing the breakdown of adipose tissue, leading to reduced fat storage and overall weight. However, in various carcinomas and cancer patients, upregulation of ZAG is observed, resulting in rapid weight loss. Mutations in ZAG, specifically the amino acids Tryptophan 148, Arginine 73, Phenylalanine 101, and Isoleucine 76, have been identified and replaced with Alanine. The effects of these mutants, as well as the wild-type ZAG, can be investigated through experimental studies. Additionally, ZAG is believed to have a lipid binding site that may be crucial for its function.
Methods
To assess the impact of ZAG variants on lipolysis, a lipolysis colorimetric kit was used to measure their effects on 3T3 adipose cells. This allowed for the determination of the β-adrenoreceptor signalling pathways involved in the lipolytic effect of ZAG. The lipolysis experiments were conducted over a specific time period, as the duration of treatment can be a limiting factor influencing lipolysis.
Results
Among the ZAG variants tested, the Tryptophan-Alanine mutant exhibited increased lipolysis after 1 hour of treatment compared to other variants. These findings suggest that the specific mutations in ZAG can influence its lipolytic activity.
Conclusion
Identifying the ligand(s) and understanding the interactions between them and ZAG is crucial in advancing our knowledge of the mechanisms underlying ZAG's function. Ultimately, the development of therapeutics targeting ZAG could provide cancer patients with treatment options to attenuate weight loss, leading to improved prognoses and a better quality of life.
Rheumatoid arthritis and heart failure: A bidirectional two-sample Mendelian randomization study
Authors: Yang Yan , Cui Fenfang , xu Min , He Qin , Liu Ying , Lan Ying , Zhang Xiqian , zheng yaxian , Zhang Xu
Published: August 2023

Background:
Extensive observational studies suggested an association between rheumatoid arthritis (RA) and heart failure (HF). Nevertheless, whether there was a solid causal association was still unclear because of confounding factors. Therefore, a bidirectional two-sample Mendelian randomization (MR) study was performed to investigate whether genetically predicted RA is related to the risk of HF and vice versa.
Methods:
RA data were obtained from large-scale genome-wide association studies (GWASs), including 5,539 cases and 20,169 controls. Data on HF were obtained from the FINNGEN biobank, including 13,087 cases and 195,091 controls of European ancestry. The inverse-variance weighted method, weighted median and MR-Egger were used for estimating and verifying the possible causal effect of RA and HF. The Funnel plots, leaveone-out analyses and MR-Egger regression were used in the sensitivity analysis.
Results:
Genetic susceptibilities of RA increased the risk of HF (OR=1.02; 95% CI 1.00-1.04, p =0.03), while HF did not increase the risk of RA.
Conclusion:
Genetic liability to RA is associated with a higher risk of HF. On the other direction, HF is not related to RA. Our research supports the clinical need for screening HF in patients with RA, which has milestone significance in exploring whether to provide appropriate HF treatment for RA patients.
Explainable predictions of a machine learning model to forecast the postoperative length of stay for severe patients: Machine Learning Model Development and Evaluation
Authors: Cho Ha Na , Ahn Imjin , Gwon Hansle , Kang Hee Jun , Kim Yunha , Seo Hyeram , Choi Heejung , Kim Minkyoung , Han Jiye , Kee Gaeun , Park Seohyun , Jun Tae Joon , Kim Young-Hak
Published: August 2023

Background
Predicting the length of stay in advance will not only benefit the hospitals both clinically and financially but enable healthcare providers to better decision-making for improved quality of care. More importantly, understanding the length of stay of severe patients who require general anesthesia is key to enhancing health outcomes.
Objective
Here, we aim to discover how machine learning can support resource allocation management and decision-making resulting from the length of stay prediction.
Methods
A retrospective cohort study was conducted from January 2018 to October 2020. A total cohort of 240,000 patients’ medical records was collected. The data were collected exclusively for preoperative variables to accurately analyze the predictive factors impacting the postoperative length of stay. The main outcome of this study is an analysis of the length of stay (in days) after surgery until discharge. The prediction was performed with ridge regression, random forest, XGBoost, and multi-layer perceptron neural network models.
Results
The XGBoost resulted in the best performance with an average error within 3 days. Moreover, we explain each feature’s contribution over the XGBoost model and further display distinct predictors affecting the overall prediction outcome at the patient level. The risk factors that most importantly contributed to the stay after surgery were as follows: a direct bilirubin laboratory test, department change, calcium chloride medication, gender, and diagnosis with the removal of other organs. Our results suggest that healthcare providers take into account the risk factors such as the laboratory blood test, distributing patients, and the medication prescribed prior to the surgery.
Conclusion
We successfully predicted the length of stay after surgery and provide explainable models with supporting analyses. In summary, we demonstrate the interpretation with the XGBoost model presenting insights on preoperative features and defining higher risk predictors to the length of stay outcome. Our development in explainable models supports the current in-depth knowledge for the future length of stay prediction on electronic medical records that aids the decision-making and facilitation of the operation department.
Experimental assessment and prediction of design parameter influences on vacuum-based granular grippers
Authors: Wacker Christian , Dierks Niklas , Kwade Arno , Dröder Klaus
Published: August 2023

Innovative soft robotic grippers, such as granular grippers, enable the automated handling of a wide spectrum of different geometries, increasing the flexibility and robustness of industrial production systems. Granular grippers vary in their design as well as the configuration, which affects the specific characteristics and capabilities regarding grippable objects. Relevant aspects are the selection of granulates and membranes, as they affect the deformability. This results in influences on the achievable gripping forces, which vary with the gripped objects geometry. The present research investigates the influences of different configurations on the achievable gripping forces for an innovative vacuum-based granular gripper concept. Specifically, the focus lies on design as well as configuration parameters, which could influence the achievable gripping force. Influencing parameters are determined based on a literature review of similar gripping concepts. Various adjustment possibilities are identified, such as materials of granulates or membranes. The possible configuration options are experimentally analyzed with a one-factor-at-a-time approach. The possibility of modelling their interrelations is examined with approaches for linear models and compared to interpolations based on Machine Learning. Especially the granulate filling level and the membrane configuration exhibit the largest influences, which were best predicted with the approach based on artificial neural networks. A selection of an optimized gripper configuration for a specified object set as well as possible further developments such as a continuous expandability of the approaches and integrations with simulations are discussed. As a result of these analyses, this research provides methodologies for an optimized selection of a gripper configuration for an improved object-specific achievable gripping force and allows for more efficient handling processes with the examined type of vacuum-based granular gripper.
Impact of Diverse Agroforestry Systems on Soil Carbon Inventories and Microbial Activities in Indo-Gangetic Plains of Samastipur, Bihar
Authors: Singh Nongmaithem Raju , Raizada A. , Singh Ashish , Devi N. Peetambari , Singh Soibam Lanabir , Saurabh Kirti , Lamare D. M. , Singh L. Netajit , Pebam Rocky
Published: August 2023

Land use significantly influenced in soil organic carbon (SOC) and its intricate dynamics, subsequently influencing various soil biochemical processes, as well as soil microbial and metabolic indices. This investigation aimed effect of different agroforestry systems (AFS) with diverse intercrops on soil carbon and pools and microbial properties up to 30 cm soil depth. The total organic carbon (TOC) content across the AFS in surface soils (0-15cm) ranged 8.75 to 11.45 g kg− 1. Poplar based AFS had 10.8 to 23.6% higher (p < 0.05) TOC while lowest in Semal (8.75g kg− 1). TOC decreased − 19 to -30.3% in subsurface (15-30cm) compared to surface soils. Very labile carbon (F1), labile carbon (F2), less labile carbon (F3) and non-labile carbon (F4) constituted 38.5, 15.3, 20.3 and 25.9% of TOC in surface soils and 34.1, 14.3, 22.1 and 29.4% in subsurface soils. Poplar based AFS had higher Basal Respiration (25.2%) while lowest (0.475 µg CO2-C g− 1 h− 1) in Mango. Poplar recorded higher Carbon Management Index in surface (209.73%) and subsurface (178.5%). Principal component analysis has shown the first two PCs represented 82.69% of the total variation wherein TOC was the most influential factor in PC1 and microbial metabolic quotient (qCO2) in PC2. Overall, Poplar based AFS outperformed among AFSs. So, therefore, we suggest, promotion of poplar-based systems to restore soil carbon and microbial properties as well as overall soil health while ensuring nutritional security of the Indo-Gangetic plains of Samastipur.
A new intuitionistic fuzzy time series method based on the bagging of decision trees and principal component analysis
Authors: Yücesoy Erdinc , Egrioglu Erol , Bas Eren
Published: August 2023

Intuitionistic fuzzy time series methods provide a good alternative to the forecasting problem. It is possible to use the historical values of the time series as well as the membership and non-membership values obtained for the historical values as effective factors in improving the forecasting performance. In this study, a high order single variable intuitionistic fuzzy time series reduced forecasting model is first introduced. A new forecasting method is proposed for the solution of the forecasting problem in which the functional structure between the historical information of the intuitionistic time series and the forecast is obtained by bagging of decision trees based on the high order single variable intuitionistic fuzzy time series reduced forecasting model. In the proposed method, the intuitionistic fuzzy c-means clustering method is used to create intuitionistic fuzzy time series. To create a simpler functional structure with Bagging of decision trees, the input data from lagged variables, memberships, and non-membership values are subjected to dimension reduction by principal component analysis. The performance of the proposed method is compared with popular forecasting methods in the literature for ten different time series randomly obtained from the S&P500 stock market. According to the results of the analyses, the forecasting performance of the proposed method is better than both classical forecasting methods and some popular shallow and deep neural networks.
Evaluation of the Binding Properties of A New Phenylurea Appended Carbazole Compound to Pepsin/Trypsin by Computational and Multi-Spectral Analysis
Authors: Gökoğlu Elmas , Doyuran Bensu , Özen Gülşah , Duyar Halil , Taskin-Tok Tugba , Seferoğlu Zeynel
Published: August 2023

A novel carbazole compound, named 1-(9-ethyl-9H-carbazol-3-yl)-3-phenylurea (Cpu) was synthesized and its binding properties with protease enzymes (pepsin and trypsin) has been examined by steady-state fluorescence measurements, UV/vis absorption, infrared (FT-IR) and circular dicroism (CD) spectroscopies and also computational methods. The fluorescence experimental results indicated that the quenching mechanism of enzyme by Cpu is static process. The thermodynamic parameters (both negative ΔH/ΔS) and molecular docking results suggested that the binding of Cpu to pepsin/trypsin were driven by hydrogen bonds and van der Waals forces. Based on Förster’s theory, the binding distance (r) between pepsin/trypsin and Cpu was calculated to be 3.072/2.784 nm, which implies that non-radiative energy transfer occurs from enzyme to Cpu. Furthermore, absorption, CD, and FT-IR spectral analysis provided an evidence that the presence of Cpu induced notable changes in the secondary structures and microenvironmental of both pepsin and trypsin, supporting its significant influence on these enzymes.
Identification and in vitro characterization of a novel porcine parvovirus 6 in Russia
Authors: Komina Alina , Anoyatbekova Afshona , Krasnikov Nikita , Yuzhakov Anton
Published: August 2023

Porcine parvovirus 6 (PPV6) was first identified in aborted swine fetuses in China in 2014. Since its identification, an increased number of PPV6 cases have been reported in many countries with developed pig breeding. In this study, the first identification of porcine parvovirus 6 in Russia, its phylogenetic analysis, and its characterization in vitro are reported. During the investigation, 521 serum samples collected from pigs of different ages from seven regions of the Russian Federation were tested. In four regions, the DNA of the virus was detected. The overall prevalence of porcine parvovirus 6 in Russia was 9.4%. Fattening pigs were the group with the most frequent detection of the virus genome. Phylogenetic analysis of the Russian isolate detected in a domestic boar indicated high homology with strains from Spain. In vitro studies revealed that PPV6 mostly replicates in SPEV and SK cell cultures and, to a lesser extent, in ST. Our results demonstrated that PPV6 induced typical apoptotic features in cells, including DNA fragmentation, chromatin margination, nuclear condensation, pyknosis of nuclei, symplast formation, and various pathological mitoses.
Estimation of TBM Penetration rate using Gradient Boosting-based Algorithms
Authors: Ghorbani Ebrahim , Adoko Amoussou Coffi , Yagiz Saffet
Published: August 2023

TBM performance prediction from the rate of penetration (ROP) point of view has yet to draw a lot of attention since it is one of the main challenges for mechanized excavation with tunnel boring machines (TBMs). In this study, five algorithms, Gradient Boosting (GB), eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), AdaBoost (AB), and CatBoost (CB) have been conducted to predict the ROP based on the Gradient Boosting theory. Six tunnel cases from different projects were examined to obtain the aim of the research. Dataset developed using those tunnel datasets includes Uniaxial compressive strength (UCS), Rock Type, Distance between Plane of Weakness (DPW), and TBM-related parameter of thrust force (TF). Mentioned Gradient Boosting algorithms were performed to obtain the most accurate results for the study. The developed models showed that XGBoost outperformed the other models, followed by the CatBoost model according to seven different evaluation metrics used to rank the models. After parameter tuning, the GB model outperformed others while those were not improved very much. By using the overall ranking according to the metrics and considering the parameter tuning time, XGBoost and CatBoost presented the first two best performances. Through SHAP values and dependency plots, the features and importance of the inputs showed the TF has the highest impact on the ROP, followed by UCS, Rock Type, and DPW. It is concluded that the XGBoost and CatBoost algorithms could be used for modeling to obtain the TBM penetration for similar rock types.
Radiographic texture analysis of the hard tissue changes following socket preservation with allograft and xenograft materials for dental implantation: A randomized clinical trial
Authors: Bayat Narges , Ghavimi Mohammad Ali , Rahimipour Kasra , Razi Sedigheh , Esmaeili Farzad
Published: August 2023

Objectives: This study aimed to assess the hard tissue changes following socket preservation with allograft and xenograft materials for dental implantation by texture analysis (TA) using cone-beam computed tomography (CBCT).
Materials and Methods: This prospective clinical trial was conducted on 25 patients who required the extraction of carious mandibular posterior teeth and their subsequent replacement with dental implants. The patients were categorized into three groups: (I) no socket preservation, (II) socket preservation with xenograft material, and (III) socket preservation with allograft material. Four months after tooth extraction, the patients were recalled for preoperative assessment before dental implantation, and CBCT scans were obtained. MaZda software was used to compare homogeneity, contrast, and texture complexity on axial CBCT sections among the three groups.
Results: Significant differences existed among the three groups in all parameters (P<0.05) except for the mean correlation parameter (P>0.05). The results showed no significant difference between the no graft and xenograft groups regarding contrast and differential (dif.) entropy (P>0.05). Also, no significant difference was found between the xenograft and allograft groups regarding the dif. variance, and also between the no graft and allograft groups regarding the inverse difference moment(InvDfMom) and dif. variance parameters (P>0.05). All other pairwise comparisons revealed significant differences (P<0.05).
Conclusion: TA can be used for quantification of radiographic changes of bone following socket preservation, and potentially accelerate the process of decision-making for dental implant treatment.
Noninferiority Clinical Trial of Adapted START NOW Psychotherapy for Outpatient Opioid Treatment
Authors: Truong Albert , Kablinger Anita , Hartman Cheri , Hartman David , West Jennifer , Hanlon Alexandra , Lozano Alicia , McNamara Robert , Seidel Richard , Trestman Robert
Published: August 2023

Background
Medications for opioid use disorder (MOUD) such as buprenorphine is effective for treating opioid use disorder (OUD). START NOW (SN) is a manualized, skills-based group psychotherapy originally developed and validated for the correctional population and has been shown to result in reduced risk of disciplinary infractions and future psychiatric inpatient days with a dose response effect. We investigate whether adapted START NOW is effective for treating OUD in a MOUD office-based opioid treatment (OBOT) setting in this non-inferiority clinical trial.
Methods
Patients enrolled in once weekly buprenorphine/suboxone MOUD OBOT were eligible for enrollment in this study. Participants were cluster-randomized, individually-randomized, or not randomized into either START NOW psychotherapy or treatment-as-usual (TAU) for 32 weeks of therapy. Treatment effectiveness was measured as the number of groups attended, treatment duration, intensity of attendance, and overall drug use as determined by drug screens.
Results
137 participants were quasi-randomized to participate in SN (n = 79) or TAU (n = 58). Participants receiving START NOW psychotherapy, when compared to TAU, had comparable number of groups attended (16.5 vs. 16.7, p = 0.80), treatment duration in weeks (24.1 vs. 23.8, p = 0.62), and intensity defined by number of groups attended divided by the number of weeks to last group (0.71 vs. 0.71, p = 0.90). SN compared to TAU also had similar rates of any positive drug screen result (81.0% vs. 91.4%, p = 0.16). This suggests that adapted START NOW is noninferior to TAU, or the standard of care at our institution, for treating opioid use disorder.
Conclusion
Adapted START NOW is an effective psychotherapy for treating OUD when paired with buprenorphine/naloxone in the outpatient group therapy setting. Always free and publicly available, START NOW psychotherapy, along with its clinician manual and training materials, are easily accessible and distributable and may be especially useful for low-resource settings in need of evidence-based psychotherapy.
Toward MR protocol-agnostic, bias-corrected brain age predicted from clinical-grade MRIs
Authors: Valdes-Hernandez Pedro , Nodarse Chavier Laffitte , Peraza Julio , Cole James , Cruz-Almeida Yenisel
Published: August 2023

The predicted brain age minus the chronological age (‘brain-PAD’) could become a clinical biomarker. However, most brain age methods were developed to use research-grade high-resolution T1-weighted MRIs, limiting their applicability to clinical-grade MRIs from multiple protocols. To overcome this, we adopted a double transfer learning approach to develop a brain age model agnostic to modality, resolution, or slice orientation. Using 6,224 clinical MRIs among 7 modalities, scanned from 1,540 patients using 8 scanners among 15 + facilities of the University of Florida’s Health System, we retrained a convolutional neural network (CNN) to predict brain age from synthetic research-grade magnetization-prepared rapid gradient-echo MRIs (MPRAGEs) generated by a deep learning-trained ‘super-resolution’ method. We also modeled the “regression dilution bias”, a typical overestimation of younger ages and underestimation of older ages, which correction is paramount for personalized brain age-based biomarkers. This bias was independent of modality or scanner and generalizable to new samples, allowing us to add a bias-correction layer to the CNN. The mean absolute error in test samples was 4.67–6.47 years across modalities, with similar accuracy between original MPRAGEs and their synthetic counterparts. Brain-PAD was also reliable across modalities. We demonstrate the feasibility of clinical-grade brain age predictions, contributing to personalized medicine.
Revisiting the Nexus of Taxes vis-à-vis Inequality: New Insights from Wavelet Coherence Approach Using Top Decile’s Income Share in Australia
Authors: Gangopadhyay Partha , Das Narasingha
Published: August 2023

We examine the nexus between taxes and income inequality in Australia – using per capita GDP as a control variable over the period 1972-2019. We apply the bi, partial and vector wavelet coherence methodologies to investigate the nature and the direction of coherences between chosen variables to marshal evidence of a complex relationship between taxes and inequality. Our findings are three-fold: first, from 2000 to 2019, per capita GDP significantly leads inequality in higher frequencies (long-run), while in the middle frequency, only after 2015, significant coherence is observed between these two variables. In lower frequencies, or short-run, from 1972 to 1985 and from 2017 onward, significant coherence is observed with the same lead-lag relationship between per capita GDP and inequality. Both partial wavelet and vector wavelet models confirm the time-varying effect of GDP on inequality, which also fluctuated across frequencies. For checking the robustness of our findings, we then extended the analysis to incorporate the effect of resource booms on Australian inequality. Even with resource booms, the central messages of our findings on the nexus between taxes and inequality in Australia remain unaltered, which indicates that Australia enjoys a strong taxation base to fund quality public services and targeted transfers for controlling inequality.
JEL Classification: H20; H25; A14; B23; C32
Establishment and characterization of a recurrent MPNST primary cell line:RsNF
Authors: Zhang Xingnan , Hu Chenhao , Li Dezhi , Liu Song
Published: August 2023

Malignant peripheral schwannoma (MPNST) is a highly aggressive and recurrent soft tissue sarcoma. It most commonly occurs secondary to neurofibromatosis type I, and it has a 5-year survival rate of only 8%-13%. In order to better study the tumor heterogeneity of MPNST and to develop diverse treatment options, more tumor-derived cell lines are needed to obtain richer biological information. Here, we established a patient-derived primary cell line of relapsed MPNST-RsNF cells with a genetic background of NF1 mutation. Through tumor molecular marker targeted sequencing and single-cell transcriptome sequencing, it was found that chromosome 7 copy number variation (CNV) was amplified in this cell line, and ZNF804B, EGFR, etc., were overexpressed on chromosome 7. Therefore, RsNF cells can be used as a useful tool in NF1 associated-MPNST genomic amplification studies and to develop new therapeutic strategies.
Breathing in Virtual Reality for Promoting Mental Health: A Scoping Review
Authors: Pancini Elisa , Natale Anna Flavia Di , Villani Daniela
Published: August 2023

Breathing techniques have long been recognized as effective strategies for promoting mental health-related outcomes such as relaxation and emotional regulation. Virtual reality (VR), with its immersion and interactivity, offers the possibility to amplify the effectiveness of breathing techniques in promoting mental health. Recently, there has been an increasing use of VR to support breathing, although a formal summary of this integration is lacking. Following the PRISMA-ScR reporting guidelines, this scoping review aims to investigate the integration of breathing techniques and VR experiences and examine their potential effects on mental health-related outcomes. The synthesis of the reviewed studies (n = 14) reveals that different VR experiences can be used to strengthen breathing techniques. VR can, for example, reduce distractions and enhance focus during breathing exercises, provide direct, real-time feedback on the practice, and be used to create personalized environments, allowing users to train their breathing techniques in various contexts, from calming virtual nature settings to safe environments for practicing breathing skills that can be applied to real-life situations. Furthermore, this scoping review reveals the positive effects of VR-based breathing interventions on reducing clinical symptoms and increasing well-being and physical health outcomes. Overall, while acknowledging some methodological heterogeneity in the existing studies, the findings demonstrate the unique and promising potential of integrating breathing techniques with VR experiences. Future research is recommended to understand long-term effects, user experience, and the potential customization of interventions for diverse clinical and well-being contexts.