bluuebunny/crossref_metadata_2025 huggingface dataset:
Determinants of honeybee hive survival within cities and its use to monitor urban biodiversity: a Canadian study
Authors: Young Mischa , MacGregor Gavin , Tanguay Georges A. , Rajaonson Juste
Published: June 2023

Cities are shown to provide favourable conditions for western honeybees (Apis mellifera) by protecting them from agricultural pesticides and offering a greater diversity of flora. Nevertheless, bee populations continue to decline in many urban areas, posing threats to plant reproduction and urban biodiversity, especially as many now promote urban beekeeping as part of their conservation efforts. While current research primarily focuses on the causes of bee colony collapse, including pesticide exposure, climate change, and habitat fragmentation, little attention is dedicated to urban apiculture and factors associated with the survival of honeybees within cities. Here, we analyse data from 3,694 honeybee hives in Montreal and Toronto to assess the effect of urban and environmental factors on hive survival. We find ground-level ozone concentrations, elevation, and the number of surrounding hives to be negatively associated with hive survival, which may point towards an issue of hive saturation. Conversely, vegetation density and the COVID-19 pandemic are positively associated with the likelihood of hive survival, emphasizing the effect of urban air pollution. These findings highlight the need for urban planners to consider neighborhood-scale environmental factors to support conservation efforts and identify potential venues for enhancing bee survival within cities beyond existing urban beekeeping initiatives.
An association study of m6A methylation with major depressive disorder
Authors: Li Ying , Miao Peidong , Li Fang , Huang Jinsong , Fan Lijun , Chen Qiaoling , Zhang Yunan , Yan Feng , Gao Yan
Published: June 2023

Objective
To study the relationship between N6-methyladenosine (m6A) genes and Major Depressive Disorder (MDD).
Methods
GEO database was used to obtain the chip data and clinical information of dataset GSE98793, and the differentially expressed m6A genes was found through the analysis of the differentially expressed genes between the MDD group and the healthy control group. Random Forest method was used for screening and modeling verification. After grouping by Unsupervised Clustering Algorithm, the expression of differences between groups was calculated for further verification. The Principal Component Analysis method was used to verify again. The relationship between the differentially expressed m6A gene and immune cells、IL gene family、 NOD-like protein receptor family was calculated. Finally, the differentially expressed m6A gene was being analyzed separately.
Results
The differentially expressed m6A genes were ELAVL1 and YTHDC2. Through Random Forest screening and modeling verification, they are closely related to MDD. Unsupervised Clustering Algorithm clustering further verifies the above results. Principal Component Analysis verified the reliability of the clustering results. ELAVL1 and YTHDC2 are closely related to immune cells、 IL gene family、 NOD-like protein receptor family. Results of single gene analysis: Compared with YTHDC2, ELAVL1 was more closely related to MDD.
Conclusion
Among all m6A genes, ELAVL1 is closely related to depression, and is an important gene regulating MDD.
Effectiveness of the Biopsychosocial Model Versus the Measurable Neurophysiological Model in Patients With Temporomandibular Joint Arthropathies
Authors: Catunda Ivson Souza , Matos Marcelo Freire , Ferreira Jessica Caroline Alfonso , Learreta Jorge Alfonso , Vasconcelos Belmiro Cavalcanti do Egito
Published: June 2023

OBJECTIVE
To evaluate the efficacy patients treated based on the biopsychosocial model, with a Michigan-type myorelaxant/stabilization splint combined with alternative therapies, and Neurophysiological model with intermediate Occlusal Devices in patients with temporomandibular joint (TMJ) arthropathies based on two different treatment philosophies.
PATIENTS AND METHODS:
This was an interventional and longitudinal study of the randomized clinical trial with blinding. The survey was approved by the CEP under: CAAE 66446216.6.0000.5207. Statistical analyzes were performed based on the selection of 43 patients with diagnosis of temporomandibular arthropathies after examination of the Diagnostic Criteria for Temporomandibular Dysfunction (DC / TMD) and assistance with images such as CT scans and magnetic resonance imaging. The patients were divided into two groups: G1-Biopsychosocial group and G2-Neurophysiological group. The variables studied were pain, mandibular function, need for alternative therapies and physiological parameters of muscle recruitment and masticatory cycle, measured by electromyography and kinesiography, respectively. All patients were followed for a minimum period of 06 to 09 months.
RESULTS
The results were favorable to both treatment groups in relation to the decrease in pain symptomatology, but were more consistent and remained smaller at the end of the evaluation in the neurophysiological group. Also significant was the difference in muscle recruitment during treatment with the G2 and less use of alternative therapies for pain control compared to the Biopsychosocial group.
CONCLUSIONS
Even in the case of a preliminary and unpublished study, this research provides strong indications of the benefit of the treatment with the Neurophysiological model in patients with TMJ arthritis, as well as the improvement of the symptomatic aspects, there was a clear improvement in muscle recruitment patterns, masticatory cycle, bone marrow regeneration and joint disc recapture. Further research with anti-etiologic treatment model should be performed to confirm these results.
CLINICAL RELEVANCE:
This innovative research highlights a new model for diagnosing and treating TMJ pathologies beyond traditional palliative treatment measures, enabling a more assertive anti-etiological treatment.
Pituitary Diseases and COVID-19 Outcomes in South Korea: A Nationwide Cohort Study
Authors: Ha Jeonghoon , Kim Kyong Min , Lim Dong-Jun , Song Keeho , Seo Gi Hyeon
Published: June 2023

Background
The pituitary gland is either directly or indirectly impacted by SARS-CoV-2 infection. As a consequence of SARS-CoV-2 infection, hypothalamic-pituitary dysfunction or pituitary apoplexy can occur. This study aimed to investigate severe COVID-19 outcomes and COVID-19-related mortality in patients with underlying pituitary disease in Korea using a nationwide cohort database.
Methods
Data required for this study were obtained from the Health Insurance Review and Assessment Service of Korea. Patients with SARS-CoV-2 infection between January 2020 and December 2021 were divided into the following three groups and analyzed: Group A, those who were hospitalized for SARS-CoV-2 infection without underlying pituitary disease (n = 725,170); Group B, those who were hospitalized for SARS-CoV-2 infection with underlying pituitary disease without exposure to systemic steroids (n = 1,509); Group C, patients with underlying pituitary disease and exposure to systemic steroids (n = 365). Differences in severe COVID-19, requirement for oxygen therapy, intensive care unit admission, application of invasive ventilation or use of extracorporeal membrane oxygenation, and COVID-19-related death between groups were then analyzed.
Results
Group C had the highest rates of hospitalization after COVID-19 infection (82.2%) and mortality within 30 days of infection (6.8%). Group B had 1.3-fold increase in severe COVID-19 outcome compared to Group A. Group C had 1.8-fold and 1.3-fold increase in severe COVID-19 outcome compared to Group A and Group B, respectively. Group C also had 2.34 and 3.24 times higher mortality rate within 30 days of COVID-19 infection than in Group A and Group B, respectively.
Conclusion
In conclusion, patients with pituitary disease who are receiving systemic steroids have poorer outcomes and higher mortality associated with COVID-19. Therefore, thorough COVID-19 infection control is required in these patients.
Perioperative, functional, and oncologic outcomes after ablation or partial nephrectomy for solitary renal tumors: a systematic review and meta-analysis of comparative trials
Authors: Wen Zhi , Wang Li , Huang Jing , Liu Yang , Chen Cai-xia , Wang Chong-jian , Chen Lin-lin , Yang Xue-song
Published: June 2023

Objectives
The perioperative, functional, and oncological outcomes of patients with solitary small renal tumors(SRMs) treated with ablation(AT) or partial nephrectomy(PN) remain controversial. The aim of this study was to compare the outcomes of these two surgical techniques.
Methods
In April 2023, we conducted a literature search in several widely used databases worldwide, including PubMed, Embase, and Google Scholar. Review Manager was used to compare various parameters. The study was registered with PROSPERO (CRD42022377157).
Results
Our final meta-analysis included 13 cohort studies with a total of 2,107 patients. Compared to partial nephrectomy (PN), ablation (AT) had shorter hospital stays (WMD − 2.37 days, 95% CI -3.05 to -1.69; p < 0.00001), shorter operating times (WMD − 57.06 min, 95% CI -88.92 to -25.19; p = 0.0004), less postoperative creatinine increases (WMD − 0.17 mg/dL, 95% CI -0.29 to -0.05; p = 0.006), less postoperative glomerular filtration rate decreases (WMD − 9.84 mL/min/1.73 m2, 95% CI -14.25 to -5.44; p < 0.0001), less postoperative new-onset chronic kidney disease (OR 0.33, 95% CI 0.16 to 0.71; p = 0.005), and less intraoperative blood loss (WMD − 285.92 ml, 95% CI -428.44 to -143.40; p < 0.0001). The transfusion rate was lower in the ablation group (OR 0.17, 95% CI 0.06 to 0.51; p = 0.001). The risk of local recurrence was higher in the ablation group (OR 2.96, 95% CI 1.27 to 6.89; p = 0.01), while the risk of distant metastasis was higher in the partial nephrectomy group (OR 2.81, 95% CI 1.28 to 6.18; p = 0.01). The intraoperative and postoperative complication rates were lower in the ablation group (OR 0.23, 95% CI 0.08 to 0.62; p = 0.004 and OR 0.21, 95% CI 0.11 to 0.38; p < 0.00001, respectively). However, overall survival, postoperative dialysis rate, and tumor-specific survival were not different between the two groups.
Conclusions
Our data suggest that ablation and partial nephrectomy are equally safe and effective in the treatment of small solitary kidney tumors and are better options for patients with poor preoperative physical condition or poor renal function.
Catalytic potential of silicon nanocages for CO2 reduction reaction to CO, CH4, HCOOH, HCHO and CH3OH production
Authors: Li XiLan , Wang Jing , Wei XiaoLi
Published: June 2023

In this study, the catalytic abilities of on Ni-C50 and Ni-Si50 nanocages for CO2 reduction reaction to CO, CH4, HCOOH, HCHO and CH3OH creation are examined by theoretical methods. The possible mechanisms for CO2 reduction reaction are examined and ΔGreaction of reaction steps to produce the CO, CH4, HCOOH, HCHO and CH3OH on Ni-C50 and Ni-Si50 nanocages are calculated. Results indicated that, the rate limiting step for CH4 and CH3OH production is the nanocage-*CO → nanocage-*CHO on Ni-C50 and Ni-Si50 nanocages. Results shown that the overpotential of CO2 reduction reaction on Ni-C50 and Ni-Si50 nanocages are lower than various metal catalysts. It can be concluded that the Ni-Si50 nanocage has more negative ΔGreaction values and lower free barrier energy than Ni-C50 nanocage to process the reaction steps of CO2 reduction. Results demonstrated that the overpotential for CH4 and CH3OH production are lower than HCOOH and HCHO creation on Ni-C50 and Ni-Si50 nanocages. Finally, the Ni-C50 and Ni-Si50 nanocages are proposed as novel catalysts for CO2 reduction reaction to produce the CO, CH4, HCOOH, HCHO and CH3OH species.
Identification and sensitivity analysis of vehicle body compound vibration
Authors: Wang Yuanshao , Su Xiaoping , Zang Liguo
Published: June 2023

The identification and sensitivity analysis of compound vibration is the basis of vibration control of vehicle body. In the paper, the mechanism and key influencing factors of compound vibration are analyzed by establishing the dynamic mathematical model with 11 degrees of freedom, and the experiment method for identifying compound vibration is put forward. The sensitivity of influencing factors of compound vibration of the body is analyzed by establishing a rigid-flexible coupling dynamic simulation model. The results show that vertical vibration, roll vibration and pitch vibration are the main forms of the vehicle body vibration, the key influencing factor of vertical vibration is rear suspension stiffness, the key influencing factors of roll vibration are lower control arm length and rear suspension damping, front suspension stiffness and rear suspension stiffness are the key influencing factors of pitch vibration. The research results provide a theoretical basis and reference for mastering the composition and formation mechanism of compound vibration of vehicle body.
Apical transportation induced by reciprocating files in removal of GuttaCore and single- cone from curved root canals: A micro-CT analysis
Authors: Hassan Regir , Ibrahim Abdulkareem Ramadhan
Published: June 2023

Objectives: Endodontic instruments tend to diverge from the long axis of root canal during preparation. This tendency increases with increasing canal curvature and retreatment cases. The purpose of this study was to assess and compare the apical transportation induced by different reciprocating single file systems in curved canals obturated with GuttaCore and single-cone obturation techniques using microcomputed tomography.
Materials and methods: Sixty-four mandibular molar teeth with root canal systems that have two independent severely curved canals in the mesial root have been chosen for the current study. The root canals have been instrumented with WaveOne Gold primary file and obturated by Single-cone and GuttaCore obturation techniques. First micro-CT scan has been taken and the samples have been subdivided into 4 groups for each obturation technique (n=16 canals each group) according to the retreatment system: Group R: Reciproc (R25 file), group RB: Reciproc Blue (R25 file), group WO: WaveOne (Primary file 25) and group WOG: WaveOne Gold (Primary file 25). After the retreatment procedures, the second micro-CT scan has been taken and then the apical transportation at 2, 3 and 4 mm from the apex were calculated.
Results: Apical transportation caused by Reciproc and WaveOne groups was significantly higher than the Reciproc Blue and WaveOne Gold groups.
Conclusion: Under the circumstances of the current study, Reciproc and WaveOne files caused higher apical transportation than the Reciporc Blue and WaveOne Gold files. The lowest apical transportation occurred at 2 mm from the apex.
Clinically relevant: The use of Reciproc blue and WaveOne Gold files can be considered safer in the removal of GuttaCore and single-cone obturation materials
Establishment of a metabolite prediction model for the risk of diabetic nephropathy in Chinese type 2 diabetic population
Authors: Su Jing-Yang , Chen Yong-Jie , Zhang Wei , Zhang Rui , Liu Tong-Feng , Yang Xi-Lin , Fang Zhong-Ze
Published: June 2023

Objective
This study aimed to examine the relationship between different plasma metabolites and the risk of diabetic nephropathy (DN), and to build a risk prediction model for DN in Chinese type 2 diabetes patients.
Methods
A hospital-based cross-sectional study was conducted in this study. According to medical records, 743 patients from a tertiary hospital were retrieved and divided into diabetic nephropathy group (DN group) and non-diabetic nephropathy group (non-DN group). The levels of metabolites such as amino acids and acylcarnitine in plasma were assayed by Laser Counter Measures System (LC-MS). Then partial least squares regression was used to rank the importance of these metabolites. Receiver operating characteristic (ROC) curves were made for the variables at the top of the importance list. Area under curve (AUC) was used to evaluate the performance of the prediction model.
Results
Of 743 hospitalized patients with type 2 diabetes, 145 of whom had DN. Compare to non-DN group, DN group had higher systolic blood pressure (SBP) (P = 0.001), high-density lipoprotein cholesterol (HDL-C) (P = 0.01) and low-density lipoprotein cholesterol (LDL-C) (P = 0.042), and more stroke patients (P < 0.001) and diabetic retinopathy (DR) patients(P < 0.001). Finally, a risk prediction model including citrulline, leucine, tyrosine, valine, propionyl carnitin (C3), palmitoylcarnitine (C16) was obtained with an AUC of 0.709(95% CI:0.626–0.793).
Conclusions
A DN risk prediction model composed of 6 plasma metabolites is a simple and effective tool to detect the risk of DN in Chinese diabetic patients.
Hangeshashinto for prevention of oral mucositis in patients undergoing hematopoietic stem cell transplantation: a randomized phase II study
Authors: Yoshimatsu Masako , Kawashita Yumiko , Soutome Sakiko , Murata Maho , Sawayama Yasushi , Kurogi Tadafumi , Nakao Noriko , Miyazaki Yasushi , Umeda Masahiro , Ukai Takashi
Published: June 2023

Purpose
Oral mucositis (OM) is a side effect associated with cancer treatment. Hangeshashinto (HST), a Kampo medicine, was originally prescribed to treat diarrhea, gastritis, and stomatitis. Several reports have described the effects of HST for OM induced by chemotherapy in patients with gastric or colorectal cancer. In this study, the effects of HST for prevention of OM were investigated in patients undergoing hematopoietic stem cell transplantation (HSCT).
Methods
Thirty patients scheduled to receive allogeneic grafts were enrolled from July 2020 to December 2021. They were randomly assigned to two groups and instructed to wash their mouth with or without HST three times a day. The observation period was from the initiation date of conditioning regimen to the date of engraftment, and the end point was the incidence of OM.
Results
Eighteen patients developed OM, the most severe of which was Grade (G)3. There was no significantly difference in the incidence of OM between the HST group and the control group. However, a negative correlation tended to be observed between the duration using HST use and the duration of OM (G2–3: P = 0.027, G3: P = 0.047).
Conclusions
The present study demonstrated that HST use did not clearly inhibit onset of OM but showed a tendency to inhibit OM exacerbation. However, further studies are necessary to fully understand the effects of HST on OM in patients undergoing HSCT.
Trial registration
This study was registered in the Japan Registry of Clinical Trials on 7 May 2020 (jRCTs071200012).
Ring artifacts suppression for X-ray CT images by fusion of dual-domain images based on improved UNet
Authors: Tan Dalong , Wu Yapeng , He Penghui , Hai Chao , Sun Liang , Yang Min
Published: June 2023

The ring artifact is one of the typical artifacts in X-ray Computed Tomography (CT) images. The existence of ring artifacts will reduce the image quality, change the structure and details of the image, and affect the interpretation of image information. How to effectively suppress ring artifacts has always been an important research direction in the industrial and medical CT fields. In this research, three experiments of CT scanning were designed by using the microfocus cone-beam CT system, we take the real CT image sequences as datasets, and design customized loss functions according to the characteristics of the ring artifacts based on the structure of UNet, in addition, a model for suppressing ring artifacts is designed both in the slice domain and sinogram domain. Then, the outputs of the dual domain are fused using the Nonsubsampled Contourlet Transform algorithm. The network model is trained and tested using the real datasets, then Peak Signal-to-Noise Ratio (PSNR), Structural Similarity (SSIM), and mean squared error (MSE) are used as the evaluation indicators of image quality. Finally, the proposed method is compared with the typical algorithms of artifact suppression, and the experimental results show that the method proposed in this research can protect the structure information in CT images while suppressing the ring artifacts to the greatest extent, and the PSNR, SSIM, and MSE of the processed images can respectively reach 39.3 dB, 98.9 and 5.2×e− 4.
Zero-touch Networks for Intelligent Manufacturing: An End-to-end Serverless-based Learning Approach
Authors: Lin Chia-Hung , Tello-Oquendo Luis , Lee Myungjin , Lien Shao-Yu , Subramaniam Suresh , Matsuura Motoharu , Hasegawa Hiroshi , Lin Shih-Chun
Published: June 2023

Industry 4.0-enabled smart factories are expected to realize the next revolution for manufacturers. Although artificial intelligence (AI) technologies have improved productivity, current use cases belong mainly to small-scale and single-task operations.A zero-touch network platform is developed for intelligent manufacturing, which unbound the potential of a smart factory by facilitating distributed AI applications in both training and inferring stages in a large-scale manner.The open radio access network (O-RAN) architecture is first introduced for the zero-touch network platform to enable globally controlling communications and computation infrastructure capability in the field.Then, a devised serverless-based framework allows intelligent and efficient learning assignments and resource allocations.Hence, requested learning tasks can be assigned to appropriate robots, and the underlying infrastructure can be used to support the learning tasks without expert knowledge.Due to the proposed network system's flexibility, powerful AI-enabled networking algorithms can ensure service-level agreements and superior performance for factory workloads.Finally, three open research directions related to backward compatibility, end-to-end enhancements, and cybersecurity are discussed for a zero-touch smart factory.
Women Empowerment, Parental Education and Future Human Capital Formation (Evidences from Urban Slum Area in India)
Authors: Das Simontini , Chakraborty Bidisha
Published: June 2023

The present paper intends to investigate the impact of women empowerment on future human capital formation in urban slum area of Kolkata, India. Education and health are two important dimensions of human capital formation. We construct women empowerment index comprising of legal and political dimension, interpersonal dimension sociocultural and economic dimension. To estimate the impact of women empowerment on education of the child, Heckman selection model is used while Logit model is used to study the impact of women empowerment on nutrition status of children. The empirical results indicate though women taking decision regarding child schooling has positive significant impact on school enrolment and continuing child’s education, financial independence plays a significant positive role only in continuing education of the child but not enrolling the children to education. We find that women empowerment has positive and significant impact on enrolling their children to school as well as continuing their school education. The positive effect of women empowerment index on the enrollment and school going behavior are stronger for female child than male child. Regarding health issues, we find that the probability of having a well-nourished child increases with the rise in the status of mothers’ empowerment, irrespective of the gender of the child. Other control variables, like monthly per capita income of the household, parental educational level especially mothers’ education level and co-habiting parents have expected significant positive impact on the education status of the children.
JEL Classification: J16, J13, J24, J71
Nutrient distribution in silver birch (Betula pendula Roth) biomass grown in nutrient-poor soil
Authors: Rustowska Beata
Published: June 2023

This study was aimed at evaluating the distribution of nutrients in the organs of silver birch growing on extremely nutrient-poor stands associated with inland dunes in central Poland. The study covered three stands, aged 12, 20, and 34 years. Ten average trees were sampled from each stand, including their fine roots, coarse roots, stemwood, bark, coarse branches, fine branches, and leaves. Under each tree, the soils were sampled at depths of 0–10, 10–20, 20–40, and 40–80 cm. The contents of nitrogen (N), phosphorous (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), iron (Fe), manganese (Mn), copper (Cu), and zinc (Zn) were analyzed in the biomass and soil samples. The studied soils were classified as Arenosols; they were strongly acidic and very poor in the studied elements. The nutrient distribution in the birch biomass was highly variable. Most had their highest concentrations in the leaves, followed by the bark (N, S, Cu), roots (P, K, Mg), and branches (Ca). The highest amounts of Fe were in fine roots, whereas Mn and Zn were most abundant in the bark. Wide variability was also apparent in the bioaccumulation factors. These were usually the highest in the leaves or bark and the lowest in the stemwood. Nitrogen showed the highest bioaccumulation intensity among the studied elements, followed by S, Zn, Cu, Mn, and P. The bioaccumulation intensity of the nutrients varied among the stands, in many cases showing significant correlations (both positive and negative) with stand age.
The Impact of Parents' Entrepreneurial Attitudes on Children's Educational Choices in Brazil: A Propensity Score Matching Analysis
Authors: Benevit Bruno , Uhr Daniel , Uhr Júlia Ziero
Published: June 2023

This study employs propensity score matching with survey weight adjustment to identify the effects of parental entrepreneurial attitudes on their children's years of schooling, the likelihood of attending private schools, and the probability of enrolling in university education (public, private, or general). The microdata is from the 2015 National Household Sample Survey. The study incorporates a series of robustness tests and examines heterogeneous treatment effects. The findings indicate that parents with entrepreneurial backgrounds exhibit a greater preference for enrolling their children in private schools. This effect is amplified when both parents are entrepreneurs. The study further reveals that children of entrepreneurial parents are more likely to attend universities, with a stronger preference for private institutions. The analysis of the heterogeneous treatment effect also emphasizes how the gender of the children and the parent's entrepreneurial background significantly influence the magnitude of the treatment.
JEL: J12, J24, L26.
RETRACTED: Robust and Secure Video Authentication: A Hash-Based Watermarking Approach
Authors: Saini Preeti , Ahuja Rakesh
Published: June 2023

The authors have requested that this preprint be removed from Research Square.
Tokenization of rental real estate assets using blockchain technology
Authors: Rath Ashish , Pateriya R. K. , Tomar Deepak , Singh Surendra
Published: June 2023

The tokenization of rental real estate assets using blockchain technology has recentlygained attention as a novel way to enhance the liquidity and transparency of the real estate market. Inthis paper, we propose a smart contract-based system for the tokenization of rental estate assets usingthe Solidity programming language along with the framework. The system aims to provide a secureand transparent way to buy and sell a fraction of ownership of rental estate assets by leveraging thedecentralized and immutable nature of blockchain technology. Our study showcases the outcomes ofthe regression analysis conducted on synthetic historical data of rental estate returns and risk factors.The findings revealed a significant positive correlation between rental estate returns or rental yieldand risk-return factors. Additionally, we describe the Analysis of Variance(ANOVA) analysis, whichconfirms the statistical significance of our proposed model. Our findings suggest that tokenizationof rental estate assets using blockchain technology can bring substantial benefits to estate investors,such as increased liquidity and reduced transaction costs. This study contributes to the developmentof the estate industry by proposing a novel model of blockchain technology in the context of rentalestate asset tokenization.
Review and proposition of energy communities: The case study of Vitoria-Gasteiz
Authors: Mikel Garro-Aguilar , Ana Picallo-Perez
Published: June 2023

In recent years, the European Union has promoted the concept of collective self-consumption and the so-called energy communities, with the aim of involving citizens in energy management and offering measures to improve energy efficiency. Spain, following the EU directives, promotes a shared use of energy, especially in urban environments. Therefore, and in accordance with this objective, this work presents the case study of incorporating energy communities including public residential buildings in Vitoria-Gasteiz (north of Spain) belonging to the public institution of the Basque Government. The aim of the study is to identify the possibilities of creating energy communities based on PV energy systems, and to analyze their feasibility considering the self-production and consumption. In addition, the possibility of including a private building rooftop of the Mercedes-Benz factory is also studied in order to produce a greater amount of energy and to be able to supply the completely electric demand of the public residential buildings. In the latter case, an economic analysis is carried out, considering the initial investment of a nearly 5 MWp photovoltaic installation, with a 2 years payback, and an environmental analysis, which shows that this photovoltaic installation would mean a saving of almost 1,600 tons of CO2 per year.
Peach Leaf Diseases Identification Using Convolutional Neural Network and Fastai Framework
Authors: Zhang Daping , Yang Hongyu , Cao Jiayu , Gong Qingtao , Kumaran Shamini Raja
Published: June 2023

Peach fruit is an ephemeral tree native to the locality of Northwest China between Tarim Basin and Kunlun Mountains' north, where it was first cultivated. Peaches have quite several health benefits such as improvement in digestion, smoother skin, and relief from allergies. However, the growing quality of peaches is a challenging task due to the common peach diseases such as brown rot, bacterial canker, peach scab, and many more. Traditionally, farmers identify peach diseases by naked eyes from the peach leaves, which is often inaccurate and unstable due to the lack of professional knowledge. Therefore, this research developed an integrated algorithm using a convolutional neural network (CNN) and Fastai Framework, known as CNN-F for peach diseases identification. To experiment with the developed algorithm, 2,657 images of diseased and non-diseased (healthy) peaches leaves are collected from the PlantVillage dataset. Using the integrated CNN-F with different models like ResNet-34, AlexNet, VGG16, and ResNet-50, the result accuracy rate has reached 94.12%, 91.12%, 92.14%, 93.23% respectively. Therefore, the application of CNN-F with ResNet-34 provides the best performance to identify the diseased leaves of peaches. This indicates that the developed algorithm can improvise the efficiency of peaches production by incorporating this algorithm to assist the farmers to cultivate healthy peaches.
Chinese Medical Named Entity Recognition Based on Pre-trained Language Models
Authors: Ruan Peiguang , Lv Wei , Li Mingxuan , Tang Weiyu
Published: June 2023

With the progressive development of academic research and the increasing standard of living, the need for medical entity identification is gradually increasing. Medical entity recognition has been rapidly developed to help build medical knowledge graphs and disease prediction, improve diagnostic accuracy, enable disease prevention, simplify clinical decision-making and reduce healthcare costs. In Chinese named entity recognition, the input is a word-level vector representation, but in Chinese text, words are the smallest units that express meaning. Although the BERT model has the advantage of excellent training results and can avoid the noise generated by the different word-level vector when the input word-level vector is used, it is wasteful for Chinese words that possess more information. Therefore, we propose a pre-training model based on Tag Embedding and Simple Lexicon word strengthening with word information fusion, which incorporates the word boundary information of the text into the more expressive text after encoding, increasing the amount of information it contains. The purpose of this study is to build a named entity recognition model using deep neural networks to improve the accuracy of medical-related entity recognition from the perspective of improving the information exploiting of medical data sets in the current era of big data informatics, and to contribute to related research.
Sputter-deposited α-MoO3 interlayers for van der Waals epitaxy and film transfer
Authors: Han Sangho , Lee Sangho , Ko Dohyun , Zhang Xinyuan , Kim Jeehwan , Ross Caroline , Kim Dong Hun
Published: June 2023

Integration of functional thin films onto flexible substrates is driven by the need to improve the performance and durability of flexible electronic devices. We present a van der Waals epitaxy technology that accomplishes the transfer of oxide or metal thin films via exfoliation or dissolution of sacrificial α-MoO3 layers produced by sputtering. The α-MoO3 thin films, consisting of weakly bonded two-dimensional layers, grew epitaxially on SrTiO3 (001) substrates, exhibiting mosaic domains rotated by 90°. Metallic Au films grown on the α-MoO3 were transferred by mechanical exfoliation or by dissolving the α-MoO3 in water at 45°C. Spinel-structured CoFe2O4 thin films grown on α-MoO3 layers were easily transferred to flexible substrates via mechanical exfoliation, and the magnetic anisotropy of the transferred CoFe2O4 films was modulated by bending.
Helping the voices of people with pancreatic cancer to be heard: a mixed media methodology to optimise recruitment for an international survey of pancreatic enzyme replacement
Authors: Landers Amanda , Cahill Charlotte , Poppy  , Kaw Anu , Brown Helen , McKenzie Clare , Agar Meera , Yenson Vanessa , Clarke Kate , Windsor John
Published: June 2023

Background: Pancreatic cancer is relatively rare and aggressive, with digestion and malabsorption issues often leading to significant weight loss. Recruitment of people with this malignancy into studies can be challenging and innovative methods need to be explored to improve recruitment rates.
Objective: To describe a mixed media methodology and the outcomes utilised to recruit patients to participate in a survey in a binational survey.
Setting: people with pancreatic cancer residing in Aotearoa New Zealand and Australia
Methods: The details of the mixed media method utilised to identify and recruit people with pancreatic cancer are described. This method was used to investigate pancreatic enzyme replacement therapy use in people with pancreatic cancer across Australia and Aotearoa New Zealand.
Results: The mixed media approach was successful in reaching 334 participants from a range of ethnicities and regions, representative of people with pancreatic cancer. Results showed that social media platforms were notably more efficient and cost-effective than radio and newspaper, but required additional expertise, including graphic design and media strategy knowledge.
Conclusions: Social media is an effective and efficient method of recruiting people with pancreatic cancer to a national survey. Studies utilising media to recruit patients may need to include team members with a range of skills.
Learning complex systems dynamics from vector fields over discrete measure spaces
Authors: Solis Ingrid Membrillo , Rossem Maria Van , Madeleine Tristan , Podoliak Nina , Orlova Tetiana , D'Alessandro Giampaolo , Brodzki Jacek , Kaczmarek Malgosia
Published: June 2023

A complex system is formed by entities that, through their interactions and dependencies, give rise to a unified whole with properties and behaviour distinct from those of its constituent parts. Examples of complex systems include the human brain, living cells, organisms, soft matter materials, the Earth's global climate, ecosystems and the economy. A large number of entities and dependencies produce high dimensional non-linear dynamics, which make the modelling, classification and prediction of complex systems dynamics a major challenge. Advances in modern information technology have made possible a successful use of data-driven approaches to the study of dynamical systems. However, in the particular case of complex systems there are still important open questions to address such as large and complex data sets analysis, dimensionality reduction, phase space reconstruction and global attractor classification. In this paper we introduce the theory of vector fields over discrete measure spaces to analyse data structurally complex, such as images, image gradients, and real and vector valued functions over simplicial complexes. We apply our framework to the analysis of data obtained from numerical solutions of equations commonly used in biology and physics to model a variety of complex systems. We show that our geometric framework, together with multidimensional scaling, an unsupervised learning method, can be successfully used in the analysis of large data sets for dimensionality reduction, mode decomposition and global attractor characterisation of complex systems dynamics. These results pave the way towards the characterisation and understanding of a number of complex dynamical systems.
Nutrient Management Impacts on HLB-affected ‘Valencia’ Citrus Tree Growth, Fruit Yield, and Postharvest Fruit Quality
Authors: Atta Alisheikh A. , Morgan Kelly T. , Ritenour Mark A. , Kadyampakeni Davie M.
Published: June 2023

Since the first occurrence of Huanglongbing (HLB) in the Florida commercial citrus industry in 2004, fruit yield and yield components of HLB-affected citrus have declined in endemically affected citrus tree groves. Optimal fertilization is thus critical for improving tree performance because nutrients are vital for tree growth and development, and play a significant role in tree disease resistance against various biotic and abiotic stresses. The objective of the current study was to determine whether leaf nutrient concentration, tree growth, yield, and postharvest quality of HLB-affected citrus trees were improved by the split application of nutrients. The four micronutrient application rates were used as fixed factors and the three nitrogen (N) rates were used as random factors for leaf nutrient analyses, tree growth, fruit yield, and postharvest analyses. Significant leaf manganese (Mn) and zinc (Zn) concentrations were detected when trees received foliar and soil-applied micronutrients regardless of the N rates. There was a strong regression analysis of leaf Mn and Zn nutrient concentration and nutrient rates with R2: 0.61 and 0.59, respectively. As a result, a significant leaf area index associated with foliar and soil-applied micronutrient rates had a positive correlation with leaf area index and soil pH with R2: 0.58 and 0.63 during the spring and summer seasons, respectively. Trees that received a moderate (224 kg·ha−1) N rate showed the least fruit decay percentage and total soluble solids (TSS) of 8% more than the lowest (168 kg·ha−1) and highest (280 kg·ha−1) N rates, even though fruit yield variations were barely detected as these micronutrients promoted vegetative growth. Moreover, the TSS to titratable acidity (TA) ratio of foliar and soil-applied micronutrient-treated trees showed 2% and 7% greater values than the foliar-only treated and control trees, respectively. Although micronutrients exacerbated stem-end rind breakdown (SERB), these nutrients significantly improved fruit storage when the fruits were stored for extended periods (8–11 weeks). Thus, moderate N rate, foliar (1×), and soil-applied (1×) micronutrient treatments improved tree growth, fruit postharvest, and fruit storage characteristics.
Knots and entanglement
Authors: Huang Jin-Long , McGreevy John , Shi Bowen
Published: June 2023

We extend the entanglement bootstrap program to (3+1)-dimensions. We study knotted excitations of (3+1)-dimensional liquid topological orders and exotic fusion processes of loops. As in previous work in (2+1)-dimensions [Ann. Phys. 418, 168164
(2020), Phys. Rev. B 103, 115150 (2021)], we define a variety of superselection sectors and fusion spaces from two axioms on the ground state entanglement entropy. In particular, we identify fusion spaces associated with knots. We generalize the information convex set to a new class of regions called immersed regions, promoting various theorems to this new context. Examples from solvable models are provided; for instance, a concrete calculation of knot multiplicity shows that the knot complement of a trefoil knot can store quantum information. We define spiral maps that allow us to understand consistency relations for torus knots as well as spiral fusions of fluxes.
Exploring the impact of internal marketing practices on the commitment to “green” intellectual capital
Authors: Arfara Christina , Samanta Irene
Published: June 2023

The purpose of this study is to explore how internal marketing practices affect the commitment of organizations’ “green” intellectual capital. It examines the relationship between internal marketing practices and the commitment to its “green” intellectual capital’s components: human, relational, and structural. Moreover, it investigates to what extent internal marketing practices are applied to strategic, operational, and implementation levels, affecting “green” intellectual capital commitment. A 27-item questionnaire was used to collect quantitative data. Six hundred nine employees from large companies operating in various business sectors in Greece participated in a survey from July to November 2020. The findings documented a strong impact of internal marketing practices (90.5%) on the commitment to “green” intellectual capital. Internal marketing practices applied at operational levels have the most substantial effect on the commitment of “green” intellectual capital (t = 17.387), while practices at implementation levels are not significant (t = 3.668). The results also indicated that internal marketing practices applied at strategic levels significantly influence the commitment to “green” intellectual capital (t = 15.747). Finally, the study discusses the theoretical and managerial contributions.
Acknowledgment This study has been funded by the University of West Attica / Special Account for Research Grants.
Functional Aspect of Hashtagging in Virtual Communication: Kemerovo State University Online
Authors: Kalashnikova Anna , Poselenova Evgeniya
Published: June 2023

Hashtags affect the conceptual sphere of Internet users and may promote certain ideologies because they are a synthetic tool of virtual communication. The research objective was to classify hashtags in virtual communication using the methods of conversational, contextual, discursive, content, and intent analyses. The study covered the online representations of the Kemerovo State University and its hashtags (2020–2023), namely, those of its official accounts, institutes, departments, trade unions, and student communities. The author revealed the following functions. The predictive function guided the first impression and was followed by compression, structuring, differentiating, and navigation functions, which systematized the content. The stereotyping function manifested itself in the image formation, while the axiological function asserted a set of ideologies behind it. The actualizing function was responsible for correlating the content with the media agenda. The manipulative and attractive functions demonstrated the suggestive aspect of the communicative potential of hashtags that represented the basic concepts of the university's conceptual sphere: kinship and family, community, a sense of belonging, stability, etc. In general, they developed an ideological model that formed a positive image of the university for the target audience.
University Media Discourse as a Means of Patriotic Education for Young People
Authors: Oliz'ko Natal'ya
Published: June 2023

Most institutions of higher education have official websites that are represented in social networks and messengers, thus providing students with relevant information. Patriotic education being a state priority, university media can also help to raise patriotism in students and develop an objective view of this state value. This research featured the Telegram channel of the Chelyabinsk State University in 2020–2022. The medialinguistic method made it possible to reveal the peculiarities of interaction between verbal and non-verbal sequences while the pragmalinguistic analysis helped to establish the communicative intention of the media text. The messages were multimodal and combined different types of information. The greatest pragmatic impact belonged to the publications that combined visual, textual, and auditory information. Patriotic narrative resonated with the target audience through a compilation of verbal and non-verbal components, such as facial expressions, gestures, intonation, body movement, and postures, that aimed at one and the same pragmatic effect.
Sentiment Analysis: Linguistic Potential of Preprocessing Regimentation
Authors: Barkovich Aleksandr
Published: June 2023

The article deals with the sentiment analysis regimentation as a relevant direction in automated natural language processing and its linguistic potential. Despite its impressive practical significance, the sentiment analysis still lacks reliable theoretical foundation. Although information technologies develop very fast, their fundamental foundations correlate with the linguistic system of knowledge. In fact, the methodological priority of the applied linguistics has no alternative with regard to the interdisciplinary specificity of the modern communication. The complex nature of this research made the authors appeal to the computer linguistics in order to provide a meta-description on the algorithmization and modeling of sentiment evaluation. The effectiveness of the relevant practice was conditioned by the optimal configuration of the procedure and an appropriate material evaluation. The preprocessing included identifying the meta-structure, defining its referentiality and level orientation, and choosing the analysis model. The authors described these main steps of the preprocessing algorithm, as well as the relevant practice. The study contributes to productive theoretical optimization of text sentiment analysis. In a broad context, the expedient disclosure of linguistic potential is relevant to the whole sphere of automated natural language processing.
The Internet as a Source and Method of Assessing Texts for Unambiguous Understanding: Speech by the President of Russia
Authors: Napreenko Galina , Ertel' Kristina
Published: June 2023

Reverse machine translation can be used to identify the degree of readability of the source text because intelligibility correlates with translatability. The authors employed the methods of reverse machine translation, a program for comparing texts, and Internet search queries to test a speech given by President Vladimir Putin for unambiguity and prove the initial hypothesis about the correlation between the categories of intelligibility and translatability. If the translated fragment demonstrated no distortion of meaning, it was more lexically similar to the source text, which means it was more comprehensible for the program. The results were confirmed using a text comparison tool. The prospect of further research lies in the comparison of reverse machine translation and reverse manual translation in terms of comprehensibility, accessibility, and translatability.