bluuebunny/crossref_metadata_2025_split huggingface dataset:
Electrotherapy, thermotherapy, chemotherapy, and cryotherapy to regenerate Prunus armeniaca L. free of ACLSV, ApMV, and TRSV
Authors: khafri Asieh Zare , zarghami reza , Naderpour Masoud , Ahmadi Behzad , Mirzaei Leila 
Published: December 2022

Abstract
In the present study, in vitro regenerated shoot tips of three apricot cultivars namely ˈQaysiˈ, ˈShamsˈ and ˈOrdubadˈ, already infected with Apple chlorotic leaf spot Trichovirus (ACLSV), Apple mosaic Ilarvirus (ApMV), and Tobacco ring spot Nepovirus (TRSV), were exposed to electrotherapy (0, 30, 40, 50, and 100 mA), thermotherapy (38°C for 7 days), chemotherapy (ribavirin at 0, 25, 50, 75, and 100 mg L− 1), or droplet-vitrification cryotherapy (40 min at 0°C prior to -20°C and − 80°C for 10 and 15 min, respectively) to achieve virus-free plants. Although electrotherapy with current intensities more than 40 mA led to drastic decrease in explants' viability, a 40–60% virus removal rate was noticed depending on the type of virus and the variety tested. Amongst various shoot tip sizes exicised, 1.0–2.0 mm explants exhibited by far more survival (60–80%) and virus eradication rate (90–100%) following thermotherapy. The explants' survival and proliferation rates also decreased with increment of ribivirin concentration in the culture medium as compared to the untreated cultures. The rate of virus elimination, however, inclined by 75–100% upon exposure to 25 mg L− 1 ribavirin. According to our results, production of virus-free regenerants would be feasible in Prunus armeniaca L. providing proper therapeutic methods are adopted as regards the type of infecting virus and the host variety.
SARS-CoV-2 Case Detection Using Community Event-Based Surveillance System – February to September 2020: Lessons Learned from Senegal
Authors: Seck Oumy , Roka Jerlie Loko , Ndiaye Mamadou , Namageyo Apophia , Sam Abdoulaye , Mangane Abdoulaye , Dieye Ndeye Licka , Ndoye Babacar , Diop Boly , Ting Jim , Pasi Omer 
Published: December 2022

Abstract

Background: Within 10 months of the first global case, the SARS-CoV-2 outbreak resulted in over 15,000 positive cases and more than 500 deaths in Senegal. We describe the design and implementation of a community EBS (CEBS) system in Senegal and how it contributed to strengthening the country's surveillance system during the COVID-19 pandemic.
Methodology: We examined data collected from COVID-19 specific phone calls within a CEBS system serving 14 regions of Senegal over the period from February to September 2020. We abstracted data on call origin, residence information, call status (validated or non-validated) and linked it to laboratory-confirmed cases from the national system. The number of calls received were mapped to positive cases of SARS-CoV-2by week. We used Excel for data analysis.
Results: A total of 10,751 out of 10,760 calls received were COVID-19 calls from all 14 regions in Senegal. The majority of the COVID-19 calls were from the Dakar (84.8%: 9,117/10,751) and Thies (7.4%: 801/10,751) regions. Of the COVID-19 calls, 50.2% (5402/10751) were validated and sent to the health district for investigation. Only 25% (1354/5402) of the validated calls were positive cases of SARS-CoV-2. The highest number of positive SARS-Cov-2 cases were reported from the Dakar (85%, 1152/1354) and Thies (8%, 104/1354) regions. The volume of COVID-19 calls increased after the first lab-confirmed case during week 10 (March 2020) through week 20 to 24 (June 2020) and eventually tapered off during week 28 (July 2020).
Conclusion: COVID-19 accelerated EBS system implementation in Senegal. Implementation of the CEBS contributed to the identification of positive cases of SARS-CoV-2; however, operational challenges such as missing data, incomplete information, and lack of system linkage persist. Consideration of these challenges can guide improvements and facilitate the successful implementation of EBS systems during a pandemic in Senegal and elsewhere.
Improving air quality assessment using physics-inspired deep graph learning
Authors: Li Lianfa , Wang Jinfeng , Franklin Meredith , Yin Qian , Wu Jiajie , Camps-Valls Gustau , Zhu Zhiping , Wang Chengyi , Ge Yong , Reichstein Markus 
Published: December 2022

Abstract
Existing methods for fine-scale air quality assessment have significant gaps in their reliability. Purely data-driven methods lack any physically-based mechanisms to simulate the interactive process of air pollution, potentially leading to physically inconsistent or implausible results. Here, we report a hybrid multilevel graph neural network that encodes fluid physics to capture spatiotemporally dynamic characteristics of air pollutants. On a multi-air pollutant test in China, our method consistently improved extrapolation accuracy by an average of 11–22% compared to representative machine learning methods, and generated physically consistent spatiotemporal trends of air pollutants at regional and fine scales.
High-precision plant height measurement by drone with RTK-GNSS and single camera for real-time processing
Authors: Matsuura Yuta , Heming Zhang , Nakao Kousuke , Qiong Chang , Firmansyah Iman , Kawai Shin , Yamaguchi Yoshiki , Maruyama Tsutomu , Hayashi Hisayoshi , Nobuhara Hajime 
Published: December 2022

Abstract
Conventional crop height measurements performed using aerial drone images require the 3D reconstruction results of several aerial images obtained through structure from motion. Therefore, they require extensive computation times and their measurement accuracy is not high; if the 3D reconstruction result fails, several aerial photos must be captured again. To overcome these challenges, this study proposes a high-precision measurement method that uses a drone equipped with a monocular camera and real-time kinematic global navigation satellite system (RTK-GNSS) for real-time processing. This method performs high-precision stereo matching based on long-baseline lengths during flight by linking the RTK-GNSS and aerial image capture points. A new calibration method is proposed to further improve the accuracy and stereo matching speed. Throught the comparison between the proposed method and conventional methods in natural world environments, wherein it reduced the error rates by 62.2% and 69.4%, at flight altitudes of 10 and 20 m. Moreover, a depth resolution of 1.6 mm and reduction of 44.4% and 63.0% in the errors were achieved at an altitude of 4.1 m, and the execution time was 88 ms for images with a size of 5472 × 3468 pixels, which is sufficiently fast for real-time measurement.
Revisiting plane strain: Necessary conditions for its realization
Authors: Saeed Hasan Aftab , Awan Yasser Riaz , Sheikh Shawaiz 
Published: December 2022

Abstract
Without exception, every physical object is three-dimensional. However, in many stress analysis situations the analyst is justified in using simplified two-dimensional idealizations of plane stress and plane strain, reducing the complexity of the problem. By obviating the need to mesh in the third dimension, this advantage also extends to numerical studies, helping economize significantly on time and computational power requirements. In plane stress idealization the out-of-plane stresses are zero, whereas in plane strain the out-of-plane strains are zero. These idealizations have variously been linked with the out-of-plane dimension as well as the end conditions of the object under consideration. However, the exact correlation of the out-of-plane dimension with these idealizations remains ambiguous. One certain instance of plane stress is a situation where the out-of-plane dimension of the object is very small as compared to its in-plane dimensions; and additionally, the loading is purely in-plane. On the other hand, there is much disagreement found in literature regarding the necessary conditions for the realization of plane strain, which needs to be addressed. Employing finite element analysis and analytical solutions, this work aims to resolve this issue.
Molten Salt Shielded Synthesis of the Nanolaminated Transition Metal Boride Fe2AlB2
Authors: Benamor Hiba , Benamor Abdessabour , Chiker Nabil , Hakem Maamar , Krea Mohamed , Bouras Omar , Sahraoui Tahar , Hadji Mohamed 
Published: December 2022

Abstract
Fe2AlB2 is one of many ternary transition metal borides called MAB phases, which attracted interest owing to its magnetocaloric effect and magnetic properties. Herein, the molten salt shielded synthesis (MS3) of Fe2AlB2 powder is studied using potassium bromide “KBr” in an open-air atmosphere. The synthesis process of the MAB phase, from Fe, Al, and B elemental powders, was studied with and without Sn additive in the temperature range of 900–1200°C. The obtained powders were analyzed using XRD, TDA, GTA and SEM analysis. The corresponding results revealed a successful synthesis of nearly-pure Fe2AlB2 phase at 1000°C for only one hour of holding time, beyond which FeB impurities form. These results show the efficiency of KBr (with Sn as a synthesis aid ‘additive’) in increasing the reactivity of this MAB phase in terms of the lowest synthesis temperature and time reported to date.
Application of artificial neural networks for predicting imidazole derivatives antimicrobial activity against Enterococcus faecalis
Authors: Badura Anna , Krysiński Jerzy , Nowaczyk Alicja , Poćwiardowska-Głąb Marta , Buciński Adam 
Published: December 2022

Abstract

The paper discusses artificial neural networks (ANNs) as a useful deep learning (DL) method to assist researchers in the search for new therapeutic and disinfectant substances. Two ANN models have been designed to predict the biological activity of the compounds based on their physicochemical properties and their structure. The said activity was tested againstEnterococcus faecalisbacteria on a series of 140 imidazole derivatives. The regression model designed, predicted the minimum growth inhibitory concentration ofE. faecalis(regression model: training data R = 0.91; test data R = 0.91; validation data R = 0.97). The classification model, on the other hand, divided the tested compounds into active or inactive against the tested microorganism predictive (classification accuracy: 92.86%). The exponential demand for new compounds in the pharmaceutical industry, requires alternative experimental methods to reduce the time and cost of development. Therefore, this paper proposes ANN as an alternative to standard techniques for predicting complex biological phenomena.
Account for MEGA-STN thermal fusion device in use of positron wave thermal energy
Authors: Lee  
Published: December 2022

Abstract
This paper is aimed at investigating the practical realization of the positron wave thermal energy. We made a MEGA-STN thermal fusion device in order to demonstrate our idea. The MEGA-STN is the device which amplifies heat when it is supplied with thermal energy. It is the result of the aggregation of each micro nano particle. If we were to express the part of it in a structural formula, it is as follows.
The fusion reaction of thermal energy in the MEGA-STN is generated on account of each micro nano particle’s chemical change, and high temperature heat occurs by the interchangeability between micro nano particles. We minimized heat loss by fusing the insulted ceramic nano particles on the outer surface of our MEGA-STN. The MEGA-STN is basically able to create thermal energy of 500~1800 degrees centigrade. Here a prerequisite is the input of minimal thermal energy. If the minimal thermal energy is supplied from the outside or generates heat internally, it is amplified to 300~500 percentage of the supplied heat.
Each of positronic nano particles in MEGA-STN, MEGA-Structural fusion Technology of Nano materials react to thermal energy and release great thermal energy, and the released great thermal energy collides into each other and generates greater thermal energy. At this time, wave is created and disturbs the properties of water and disintegrates them, and as a result they are changed. The more vibrations, the more transformations of water particle. This principle is the same as even dead water can revive.
Thermal particles that are produced when micro nano particle and thermal energy collide generate multiple waves, and they resonate and transport in micro nano particle. Within this resonant orbit they continuously collide and spin like tonado, and thermal energy is amplified and fast rotational force is created. Commonly if we are going to make this rotational force, we must spin only magnetic particle. This structure of micro nano particle is not magnetic, but yet it does maximize the rotational force.
The MEGA-STN using the positron wave thermal energy is available for the industry related to electricity and thermal energy by substituting gas, oil, coal, wood, nuclear power, and can be viable alternative to the exsisting source of energy by using as a substitute for the engine of car, train, air, vessel and etc.
Theoretical Analysis of The New Organic Materials as Effective Sensitizer in Dye-Sensitized Solar Cells
Authors: AL-Temimei Faeq A. , Abbas Hawraa H. , Mohsen Suhad H. 
Published: December 2022

Abstract
In this work, a computational investigation was used to design and study new materials based on carminic acid isomers as organic dyes for DSSCs. Density functional theory (DFT) was applied to report the ground state and the excited state characteristic was reported by utilizing time-dependent DFT (TD-DFT) methods. Some electronic, optical, photolytic and electron transfer properties are evaluated to achieve our study. The results indicate that modifying the chemical structure of a dye by doping improves light harvesting efficiency while reducing the driving force for electron injection and the potential of dye renewal while boosting dye aggregation on the electrode surface. The new structures dyes displays strong charge transfer absorption bands in the visible, excellent electronic, sufficient driving force and photoelectric conversion efficiency in comparison with carminic acid. Also, All suggested dyes have sufficient properties to achieve high PCE of the DSSCs. These results are adequate for a potential effective electron injection process. Accordingly, the theoretical methods are significant to provide experimental methods for designing new, highly efficient materials for optoelectronic applications.
The confrontation of robots and the challenges facing artificial intelligence
Authors: Fard Mahdy Ebrahimi , Gordji Madjid Eshaghi 
Published: December 2022

Abstract
Artificial intelligence is the knowledge of knowing and designing intelligent agents, although the topic of artificial intelligence is very attractive, its challenges are equally important. The dangers of a robot's wrong decisions in confronting humans or two robots and other problems of wrong decisions by robots have been the concern of many scientists in this field. In this article, we have presented a solution to the mentioned problems using the Hyper Move Theory (HMT) method and in the form of an example.
Carboxylated Graphene Quantum Dots-Mediated Photothermal Therapy Enhances Drug-Membrane Permeability, ROS Production, and the Immune System Recruitment on 3D Glioblastoma Models.
Authors: Perini Giordano , Palmieri Valentina , Friggeri Ginevra , Augello Alberto , De Spirito Marco , Papi Massimiliano 
Published: December 2022

Abstract
Graphene quantum dots (GQDs) are biocompatible nanoparticles employed in biomedical field, thanks to their size and photophysical properties. GQDs have shown the capability to cross biological barriers, including the blood-brain barrier, which makes them promising agents for brain diseases therapy. It has been shown that surface-functionalized GQDs enhance membrane fluidity and intracellular uptake, exerting a synergistic effect with antitumor drugs at subtherapeutic doses. Here we tested GQDs effects in combination with chemotherapeutic agents doxorubicin and temozolomide, on a complex 3D spheroid model of glioblastoma. We observed that the capability of GQDs to absorb and convert near-infrared light into heat is a key factor in membrane permeability enhancement on 3D model. This non-invasive therapeutic strategy named photothermal therapy (PTT), combined to chemotherapy at subtherapeutic doses, significantly increased the effect of antitumor drugs, by reducing tumor growth and viability. Furthermore, the increase in membrane permeability due to GQDs-mediated PTT enhanced the release of reactive oxygen species with strong migration of the immune system towards irradiated cancer spheroids. Our data indicate that the increase in membrane permeability can enhance the efficacy of antitumor drugs at subtherapeutic doses against glioblastoma, reducing side effects and directing immune response, ultimately improving quality of life for patients.
Parental drinking, mental health and educational level, and offspring’s subsequent prescription drugs treatment for sleep problems. A Longitudinal HUNT Survey and Registry Study
Authors: Lund Ingunn Olea , Andersen Njål , Ask Helga , Andreas Jasmina Burdzovic 
Published: December 2022

Abstract
Background
Parental drinking, mental health and family socioeconomic status are all associated with offspring sleep problems, but there is a paucity of research that considers the effect of several risk factors together, as they co-occur within and across families. Also, sleep problems are closely linked with mental health problems and disentangling the effects on one or the other are important. We examined whether parental risk constellations are differently associated with offspring’s subsequent prescription drug use for sleep problems during nine years with or without prescription drug use for anxiety and/or depression.
Methods
The sample included 8773 adolescent offspring of 6696 two-parent families who participated in the Nord-Trøndelag Health Study in Norway. The exposures were five parental risk constellations characterized by drinking frequencies and quantities, mental health, and years of education. The outcomes were dispensed prescription drugs in offspring for a) only sleep problems b) sleep problems and anxiety/depression or c) only anxiety/depression during 2008–2016. We used multinomial logistic regression to model the odds of the outcomes.
Results
Compared to the overall low-risk parental constellation, none of the four risky constellations were significantly associated with increased risk of being dispensed prescription drugs only for sleep problems. Offspring from two different risk profiles were at increased risk for being dispensed both sleep and anxiety/depression prescription drugs. These were parental profiles marked by 1) low education, symptoms of mental health problems and weekly binge drinking in both parents (OR 1.90, CI = 1.06;3.42); and 2) elevated drinking in both parents and elevated symptoms of mental health problems in fathers (OR 3.32, CI = 1.49;7.39). Offspring from the risk profile with lowest parental education were at increased risk of being dispensed only anxiety/depression prescription drugs (OR 1.25, CI = 1.05;1.49).
Conclusion
Our findings suggest that parental risk constellations are not associated with increased risk of offspring receiving sleep medications without also receiving anxiety/depression medications, as two risk constellations were associated with increased risk of dispensation of both sleep and anxiety/depression prescription drugs during nine years. Receiving both may be an indication of severity. The findings underscore the importance of including measures of mental health problems when investigating sleep problems to avoid misattribution of effects.
Twenty-one-year follow-up revealed guideline-concordant and non-concordant trends in intensive care of bronchiolitis
Authors: Selin Sofia , Mecklin Minna , Korppi Matti , Heikkilä Paula 
Published: December 2022

Abstract
Purpose
To evaluate the management of bronchiolitis in the paediatric intensive care unit (PICU) before and after publication of the national bronchiolitis guidelines in 2014.
Methods
All infants treated between 2016–2020 for bronchiolitis in the PICU of Tampere University Hospital at < 12 months of age were included. The data were retrospectively collected from electronic patient records. The current results reflecting the post-guideline era were compared with previously published results for the pre-guideline 2000–2015 period. These two studies used identical protocols.
Results
Forty-six infants treated in the PICU were included. During the post-guideline era, inhaled adrenaline was given to 26 (57%), salbutamol to 7 (15%), and hypertonic saline inhalations to 35 (75%) patients. Forty-three patients (94%) received high-flow oxygen therapy (HFOT). Seventeen patients (37%) were treated with nasal continuous positive airway pressure (CPAP) and 4 (9%) with mechanical ventilation.
Conclusion
When post-guideline years were compared with pre-guideline years, the use of bronchodilators decreased in agreement, but the use of inhaled saline increased in disagreement with the guidelines. The use of respiratory support increased, evidently because of an introduction of the non-invasive HFOT treatment modality.
Existence and stability results for nonlinear fractional integro-differential coupled system
Authors: ZHOU Jue-liang , HE Yu-bo , ZHANG Shu-qin , DENG Hai-yun , LIN Xiao-yan 
Published: December 2022

Abstract
In this paper, a class of nonlinear ψ−Hilfer fractional integro-differential coupled system on bounded domain is investigated. The existence and uniqueness result for the coupled system is proved based on the contraction mapping principle. Moreover, the Ulam-Hyers-Rassias, Ulam-Hyers and Semi-Ulam-Hyers-Rassias stabilities to the initial value problem are obtained.
2020 Mathematics Subject Classification: 26A33; 34A08; 34K20; 45D05.
Conditional Saddle-point Approximations for Bivariate Compound Distributions
Authors: Alhejaili Amal D. , Alghamedi Ateq A. 
Published: December 2022

Abstract
The majority of existing research aims to explain phenomena in various fields of application that rely on bivariate random variables [1]; [2]. Although these distributions have attracted some attention in the literature, little research exists on the bivariate compound distribution. Because of the computational difficulties in implementing such a distribution, research on it is limited. This study aims to use the saddle-point approximation method, which is more powerful than other methods. This article introduces conditional saddle-point approximations to the bivariate compound distribution in continuous and discrete settings. We discuss conditional approximations for cumulative distribution functions of bivariate compound distributions. Examples of continuous and discrete distributions from the bivariate compound truncated Poisson compound class are presented. Comparisons between saddle-point approximations and the exact calculations show the great accuracy of the saddle-point methods.