bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of propionyl group on birefringence and wavelength dispersion of propionylated cellulose acetate optical compensation films
Authors: Min Xiaoyu , Han Xueqing , Wu Tong , An Minfang , Li Liangbin 
Published: January 2023

Abstract
Propionylated cellulose acetate (PCA) with different propionyl substitution degrees (DSPr) was synthesized, and the corresponding optical films were prepared by solution casting. The birefringence and its wavelength dispersion of PCA films stretched at 10°C above and below the glass transition temperature (Tg) with different draw ratios (DR) were studied. The introduction of propionyl group at different substitution sites present different contribution to birefringence and its wavelength dispersion. The propionyl group at C-2 and C-3 sites have a larger positive orientation birefringence with stronger inverse wavelength dispersion, while that at the C-6 site shows a higher negative orientation birefringence with weaker normal wavelength dispersion compared with the acetyl group. Compared with CA film, the introduction of the propionyl group weakens the orientation birefringence of PCA film. With the increase of DSPr from 0.023 to 0.303, the occurrence of propionyl substitution only at the C-6 site turns to C-2, C-3 and C-6 sites and the wavelength dispersion of in-plane birefringence (Δnin) decreases. When DSPr is further increased to 0.537, the Δnin and out-of-plane birefringence (Δnth) of PCA films at different DR show a very weak wavelength dispersion with the relative horizontal curves. Current results indicate that when the substitution degree of the propionyl group and acetyl group is suitable, the wavelength dispersion of PCA film can be eliminated.
New evidence in the relationship between trade openness and food security in Sub-Saharan Africa
Authors: Théodore GNEDEKA Kodjo , WONYRA Kwami Ossadzifo 
Published: January 2023

Abstract
This paper re-examines the effect of trade openness on food security in Sub-Saharan African countries. Panel data covering 37 Sub-Saharan African countries over the period from 2004 to 2018 were mobilized. We employ a system GMM approach to account for unobserved heterogeneity, correlated individual effects and potential endogeneity of the explanatory variables was adopted. As food security is a multidimensional concept, we used four indicators to capture it. To improve the robustness of the empirical results, we also used globalisation as an alternative factor to trade openness. The empirical results show that trade openness significantly improves food security in Sub-Saharan Africa. However, in the presence of political instability, a deterioration of the food security situation is observed. The results reveal also that the quality of institutions, economic growth, remittances, human capital and the importance of the agricultural sector are also factors favouring the level of food security in sub-Saharan Africa. Any policy aimed at trade openness must take into account the quality of institutions in order to achieve the expected results.
JEL: C33; F14; Q18
Intelligent system for cognitive study on student's network based on computational analysis
Authors: Maan Harkeerat Singh , Kaur Mandeep , Patil Rajkumar 
Published: January 2023

Abstract
The neurological, behavioral, and cognitive problems in teenage students are increasing day by day. It is very important to address these issues by gathering information from public opinion. The distribution of Public Opinion Information (POI) in student work is unsystematic, and it is difficult to extract the needed information intelligently. In this research, an intelligent extraction algorithm for analyzing public opinion data from student work is proposed. The algorithm is based on human-computer interaction, machine learning, and computational techniques. A fuzzy semantic autocorrelation mapping feature set of public opinion information is developed from the student work, along with a spatial structural model of data semantic distribution features. The statistical feature quantity of semantic similarity of the public opinion data is retrieved from the student work, and semantic ambiguity is decreased. Adaptive learning and machine understanding, along with human-computer interaction, are used to process the data. In the human-computer interaction machine understanding center, the processor adjusts the grid partition of public opinion information of the student work according to the differences in statistical features, constructs a feature decomposition model of student behavior, and performs context mapping. Finally, semantic analysis is carried out to analyze student behavior based on cognitive study. The simulation outcomes show that the proposed method is computationally inexpensive, has low time complexity, and has the ability to provide real-time monitoring of public opinion information on student behavior.
Application of Intelligent Models in Determining the Pore Pressure of Hydrocarbon Reservoirs
Authors: Kianoush Pooria , Mohammadi Ghodratollah , Hosseini Seyed Aliakbar , Khah Nasser Keshavarz Faraj , Afzal Peyman 
Published: January 2023

Abstract
In seismic methods, pore pressure is estimated by converting seismic velocity into pore pressure and calibrating it with pressure results during the well-testing program. This study has been carried out using post-stack seismic data and sonic and density log data of 6 wells in one of the fields in SW Iran. While an optimum number of attributes is selected, the General regression (GRNN) provides higher accuracy than Back Propagation (BPNN) at the initial prediction stages. Suitable attributes for estimating compressional velocity (Vp) and density from seismic data are extracted by the Emerge module of HRS.8 software. Acoustic impedance (AI) is the most applicable seismic attribute used as root and reverses AI for estimating P-wave and density. Using a set of attributes can train the system to estimate the property. The correlation coefficient of actual and predicted P-wave using an AI seismic attribute has been calculated as 0.74 and the multi-attribute technique as 0.79. Also, density and three attributes reach from 0.57 to 0.60, which shows a better relationship between seismic attributes and density. After determining optimum layers with the principal components analysis (PCA), formation pressure was modeled with the feed forward-backpropagation (FFBP-ANN) method. Correlation between 0.2 and 0.3 is suitable for generating a neural network layer, and values below 0.2 have a low correlation. Five information layers, including gamma, Vp, AI, density, and overburden pressure, have the most linear convergence with the initial pressure model and are used to modify the ANN model of effective pressure with Petrel 2016 software.
Application of Pressure-Volume (P-V) Fractal Models in Modeling Formation Pressure and Drilling Fluid Determination in an Oilfield of SW Iran
Authors: Kianoush Pooria , Mohammadi Ghodratollah , Hosseini Seyed Aliakbar , Khah Nasser Keshavarz Faraj , Afzal Peyman 
Published: January 2023

Abstract
Accurate knowledge of pore and fracture pressures is essential for drilling wells safely with the desired mud weight. By definition, overpressure occurs when the pore pressure is higher than the normal hydrostatic pressure and is associated with specific environmental conditions in a particular part of the earth. This study focuses on the formation pressure studies' domain for an oilfield in SW Iran. It generally consists of carbonate rocks with no shale interbeds except for the Kazhdumi Formation. This study is based on information from 23 wells and the interpretation of seismic data. The effective, pore, and fracture pressure models are determined from combined geostatistical models and compared with fractal models. The highest correlation between the final effective pressure cube and the velocity cube is related to the lower Fahliyan Formation with 86% and Ilam with 71%, which indicates the accuracy of the modeled data with the original data. Based on the final formation pressure cubes, the maximum pore pressure is 10,000 psi in the Gadvan Formation up to the upper Fahliyan Formation, and the maximum fracture pressure is 13,000 psi in the lower Fahliyan up to the Gotnia Formation. Based on the Logratio matrix obtained from the pressure-volume (P-V) fractal model, the maximum overall accuracy (OA) in the dominant limestone intervals is 0.74 at depths of 2000–3000 meters, which is related to the Asmari to Sarvak Formations. Furthermore, it indicates a high correlation of the pore pressure cube model obtained from the combination of sequential Gaussian simulation (SGS) and co-kriging models with acoustic impedance inversion (AI) for minimizing the time and cost of drilling in new wells of the studied field.
Sentiment Analysis Model of Imbalanced Comment Texts Based on BiLSTM
Authors: Wen Han , Zhao Junfang 
Published: January 2023

Abstract
This paper tries to improve the performance of imbalanced comment texts sentiment analysis by combining deep learning and class imbalanced learning methods. A sentiment analysis method for imbalanced comment texts based on BiLSTM framework is proposed. For the case of more negative samples than positive samples, when the degree of imbalance is low, the minority class samples are Adaptive Synthetic Sampling, and the CNN-BiLSTM model is proposed to realize sentiment classification by constructing Sigmoid. When the degree of imbalance is high, the samples of majority class are sampled multiple times until the original dataset is divided into multiple low imbalance datasets. Then, multiple groups of equalization Adaptive Synthetic Sampling is carried out for the samples of minority class, and BiLSTM model is learned for each group of training data respectively. Finally, Ensemble learning is adopted to obtain the final sentiment classification results. Experimental results show that this paper method is superior to the traditional imbalanced comment texts sentiment analysis method.
EEG topography preserving convolutional neural network approach to assess skill levels during laparoscopic surgical training
Authors: Manabe Takahiro , Rahul FNU , Fu Yaoyu , Intes Xavier , Schwaitzberg Steven D. , De Suvranu , Cavuoto Lora , Dutta Anirban 
Published: January 2023

Abstract
The study objective was classification of skill level based on the topographical features of the electroencephalogram(EEG) during the most complex Fundamentals of Laparoscopic Surgery(FLS) task.
We developed a novel microstate-based Common Spatial Pattern (CSP) analysis with linear discriminant analysis(LDA) classification that was compared with topography-preserving convolutional neural network(CNN) based approach to distinguish experts versus novices based on EEG. Ten expert surgeons and thirteen novice medical residents were recruited at the University at Buffalo. After informed consent, the subjects performed three trials of laparoscopic suturing and knot tying with rest periods in-between. 32-channel EEG during task performance was used to analyze spatial patterns of brain activity in 8 expert surgeons (2 dropouts due to data quality) and 13 novice medical residents. Besides conventional CSP analysis, microstate analysis was applied for preprocessing before CSP analysis for improved classification using LDA with 10-fold cross-validation. Also, a topography-preserving 3D CNN model (ESNet) was applied that considered both spatial and temporal information for the classification. Here, 5-fold cross-validation was repeated 10 times, and the results of each iteration of the testing data set were evaluated using indices, Accuracy, F1 score, Mathews Correlation Coefficient (MCC), sensitivity, and Specificity.
Microstate-based CSP analysis found that while novices had primarily the frontal cortex involved for a maximum of spatial pattern vectors, experts had the hotspot of the spatial pattern vectors over the frontal and parietal cortices where the discriminating parietal brain region was supported by the Gradient-weighted Class Activation Mapping (Grad-CAM) of our 3D CNN-based model. Here, LDA with 10-fold cross-validation achieved more than 90% classification accuracy with microstate-based CSP, while conventional regularized CSP could reach around 80% classification accuracy. Then, 3D CNN provided the highest sensitivity of 99.30%, the highest specificity of 99.70%, the highest F1 score of 98.51%, and the highest MCC of 97.56%.
Microstate-based CSP analysis improved the LDA classification (~90%) of experts versus novices based on EEG topography during a complex FLS task; however, combining the spatial and temporal information in the EEG topography preserving 3D CNN model significantly improved the classifier accuracy (>98%) in addition to providing mechanistic insights based on Grad-CAM analysis.
Aquatic bugs (Hemiptera: Heteroptera) diversity of two Tiger Reserves state Telangana, India
Authors: Banerjee Someah , Jaiswal Deepa 
Published: January 2023

Abstract
The diversity and distribution of aquatic Hemipterans were studied from Amrabad and Kawal Tiger Reserve of state Telangana. This reportdocuments 38 species of aquatic hemipterans belonging to 22 genera and 10 families from Amrabad and Kawal Tiger Reserve. Interestingly, 20 species were noted as additions to the state of Telangana with two species Ranatra libera Zettel, 1999 and Rhagovelia sumatrensis Lundblad, 1933 were observed, where the first one is the new distributional record to Deccan peninsula and latter one from southern India. Global distribution map also presented here in this article. Kawal Tiger Reserve has high species diversity than the Amrabad tiger Reserve. The present report is the first documentation from both tiger reserves on aquatic hemipterans from the state of Telangana.
The Prevalence of Obesity among Syrian Private University Students and Its Relationship with Lifestyle
Authors: Albokaay Ayman , Rumman Aisha , Hammoud Taghrid 
Published: January 2023

Abstract
Introduction: Obesity is the excessive or abnormal accumulation of fat or adipose tissue in the body that is detrimental to health through its association with the risk of diabetes, cardiovascular disease, hypertension and hyperlipidemia. A major public health epidemic has only gotten worse over the past 50 years. Obesity is a complex disease with multifactorial causes. We aim in two studies to study the most important factors that cause obesity among students of the Syrian Private University, and to link the most important risk factors and lifestyle of students with obesity.
Methods: A pivotal cross-sectional study targeting 432 students of the Syrian Private University according to specific admission and exclusion criteria, data were taken from them using an electronic form that was published on the students' social media sites.
Results: By interpreting the results of the descriptive statistics of the sample and applying the Chi-Square, ANOVA and Unpaired-T-test, we extracted many interesting results regarding the assessment of obesity among the studied students. The pattern of foods rich in carbohydrates, as well as those with a positive family history of obesity.
Conclusion: The absence of a relationship between several risk factors that passed in our study Such as (the number of hours of study, prolonged sitting, the number of hours of sports practiced per week, the number of meals consumed daily or weekly, and the type of medications usually used) and the development of this incidence of obesity prompts us to search more in two main areas in the future in broader and more comprehensive studies, namely, to ascertain the reasons for the absence of this relationship in young age groups and the presence of more additional factors. In depth related to heredity and general metabolism in the body, and the search for other unconventional risk factors that may be useful in determining the causality behind the increasing frequency of obesity cases in unusually young age groups. It is currently followed.
Development of an Animal-Derived Component-Free Medium for Spodoptera frugiperda (Sf9) Cells Using Response Surface Methodology
Authors: Saisud Sureewan , Posung Manoch , Tuntigumthon Suthida , Areesirisuk Atsadawut , Dhepakson Panadda , Teeka Jantima 
Published: January 2023

Abstract
Spodoptera frugiperda (Sf9) insect cells have been widely used for recombinant protein production. Currently, serum-free media for Sf9 cells are commercially available, but they mostly still contain animal-derived components. This work aimed to develop an animal-derived component free medium for Sf9 cells. Chemically defined lipid concentrate (CDLC), yeast extract (YE), and soytone (ST) were studied for serum substitutes using a central composite design (CCD). OSF9-ADCFM contained optimum concentrations of CDLC, YE and ST at 0.5% (v/v), 11.0 g/L, and 3.0 g/L, respectively. The mean viable cell concentration of 1.71 ± 0.14 x 105 cells/mL was obtained from 5 passages (P1-P5) in 25 cm2 tissue culture flask. The use of both peptones after 10-kDa ultrafiltration had a significant effect on Sf9 cells growth. Maximum cell concentrations and the specific growth rates of cell adaptation in suspension culture were 1.79–2.17 x 106 cells/mL and 0.025–0.027 h− 1, respectively. The results indicated that OSF9-ADCFM could be used for Sf9 culture in both static and suspension culture. Further study would be needed to verify the effect on protein production of this in-house animal-derived component-free medium.
Efficient production of isobutanol from glycerol in Klebsiella pneumoniae: Regulation of acetohydroxyacid synthase, a rate-limiting enzyme in isobutanol biosynthesis at gene expression level
Authors: Jo Min-Ho , Heo Sun-Yeon , Ju Jung-Hyun , Jeong Ki Jun , Kim Min-Soo , Kim Chul-Ho , Oh Baekrock 
Published: January 2023

Abstract
Background: Glycerol is inexpensive and abundant, and can be used for the industrial production of value-added products. Isobutanol is an important industrial chemical that has many applications, and its biosynthesis from different carbon sources has been studied using various microorganisms. So far, isobutanol production by Klebsiella pneumoniae has been mainly studied using glucose. In this study, we produced isobutanol from glycerol based on the K. pneumoniae ΔldhAΔadcmutant harboring pBR-iBO used in previous study using K. pneumoniae, which has an excellent ability to assimilate glycerol even under limited conditions.
Results: We investigated the effect of different acetohydroxyacid synthase (AHAS) isoenzymes (rate-limiting enzymes in isobutanol biosynthesis), plasmid copy number, and different promoters as a method to increase isobutanol production by K. pneumoniae. The K. pneumoniae Cu ΔldhAΔbudA, pUC-tac-BN-ISO strain produced 2.56-fold more isobutanol than previously reported for glycerol-derived isobutanol production. Also, the in vitro enzyme activity of AHAS I (ilvBN) was greater than that of the other two isoenzymes (ilvIHand ilvGM). Evaluation of process factors indicated that an agitation speed of 200 rpm with the culture maintained at pH 6 were favorable conditions for isobutanol production (1.02 g/L).
Conclusion: We obtained enhanced isobutanol production from glycerol by metabolic engineering of K. pneumoniae. Our results demonstrated enhanced production of isobutanol from glycerol, and suggest future avenues for research in this area.
Thulium laser versus cold steel tonsillectomy with bipolar electrocautery: a prospective pilot study in adult patients
Authors: Baghdasaryan Manana , Mkhitaryan Gurgen , Martin Misakyan , Vermishyan Vahe , Tadevosyan Artashes , Poghosyan Anna 
Published: January 2023

Abstract
Objectives

Multiple surgical techniques and instruments with their advantages and disadvantages have been described to minimize intraoperative hemorrhage and reduce the operation time, postoperative pain, and incidence of comorbidities in patients undergoing tonsillectomy. The aim of this pilot study was to compare the operation time, intraoperative and postoperative bleeding, postoperative pain and wound healing of the Thulium Revolix laser tonsillectomy method over the more commonly practiced cold steel tonsillectomy.

Methods

A prospective, single-blinded randomized pilot trial was conducted from February 2020 to March 2021. The inclusion criteria were adult persons with chronic recurrent tonsillitis. Twelve adult persons (7 males and 5 females) with chronic recurrent tonsillitis were observed and underwent tonsillectomy. All persons were Armenians with a mean age of 28.7 years. The persons were randomly assigned to have one tonsil removed with a Thulium RevoLix laser 200, and the conventional cold steel tonsillectomy method was used for the other side. The operation time for each side and intraoperational bleeding were evaluated. On the second, fifth, seventh and twelfth days, pain intensity was recorded using the numeric rating pain scale, and wound healing was assessed clinically.

Results

The tonsillectomy time from incision to hemostasis was 12.08 ± 0.77 min with the laser method and 12.08 ± 0.77 min with the cold dissection method, with no statistically significant difference (P < 0.121). Intraoperative blood loss in the cold dissection method was 10.92 ± 1.31 ml, and absolutely no blood loss was observed during laser treatment (p < 0.000, t = 8.363). The highest NRS pain scores were revealed on the second postoperative day, which slightly decreased over the next 12 postoperative days in both groups. In the cold steel tonsillectomy group, the pain score was significantly higher than that in the laser tonsillectomy group on the 7th and 12th postoperative days: 1.67 ± 0.33 via 4.00 ± 0.69 (P = 0.006) on the 7th postoperative day and 0.17 ± 0.11 via 2.67 ± 0.73 (P = 0.003) on the 12th postoperative day.

Conclusion

The use of the RevoLix 200 laser for tonsillectomy in the present pilot study of 12 patients showed significantly better outcomes than those in conventional cold dissection methods in terms of intraoperative bleeding, postoperative pain and wound healing; however, there was no statistically significant difference in other parameters, such as operational time and late postoperative bleeding. A large full-scale prospective study is needed to increase the generalizability and reliability of the results.
Clinical trial registration: ISRCTN16280803 https://www.isrctn.com/ISRCTN16280803