bluuebunny/crossref_metadata_2025 huggingface dataset:
Physical discomforts, feeling of the high work intensity and the related risk factors of the frontline medical staff during COVID-19 epidemic: an early-outbreak, national survey in China
Authors: Jia Liu , Ye Ming , Wang Hongliang , Wang Huaiquan
Published: October 2023

Background

Facing the unknown virus, COVID-19 medical staff kept wearing thick personal protective equipment during their work in the early stage of the outbreak. The survey was designed to investigate the physical discomforts, the feeling of the work intensity and the related risk factors of the frontline medical staff during COVID-19 epidemic in the early outbreak.

Methods

An national survey was carried out in China from March 17th 2020 to March 20th 2020 by applying a standardized WeChat questionnaire survey. The doctors or nurses working in the wards for the confirmed COVID-19 patients on front-line were eligible to participate in the survey. Descriptive analysis and multivariate logistic regression analysis were used.

Results

A total number of 515 COVID-19 medical staff, including 190 physicians and 325 nurses participated in this survey. 375 medical staff (72.8%) experienced physical discomforts at work, mostly consist of dyspnea (45.8%), pain (41.0%), chest distress (24.1%), dizziness (18.8%), and weakness (17.5%), while wearing thick isolation clothes at work. The mean onset time and peak time of these symptoms were 2.4 h and 3.5 h after working, respectively. 337 medical staff (65.4%) suffered from sleep disorders. 51 medical staff (10%) were highly worried about being infected by COVID-19 even during their work breaks. 246 medical staffs (47.8%) felt high work intensity and the independent influential factors were the effective daily sleep time and anxiety levels at break time (p = 0.04).

Conclusion

The frontline medical staff during COVID-19 epidemic felt different physical discomforts when they wear thick isolation clothes at work in the early outbreak and they felt high work intensity. These precious data will help optimize the work management strategy to ensure the physical and mental health of medical staff in the face of similar outbreaks in future.
User centric metrics for a realistic assessment of broadband services
Authors: Popoviciu Ciprian
Published: October 2023

Past broadband adoption initiatives underscored common wisdom: “We cannot manage what we cannot accurately measure”, “Trust but verify”. Self-reported Federal Communications Commission data has been notoriously unreliable or lacking granularity and that led to an overoptimistic perception of the quality and coverage of broadband services. Data collected in the past was deficient in providing a complete view of the user experience by focusing exclusively on a simple metric, bandwidth availability. Moreover, data collected in the past typically provided a point-in-time perspective on the state of broadband services in each region. In this paper, we discuss a new set of metrics and measurement techniques needed to make broadband funding decisions efficient in terms of quality of services delivered and return on investment, and to track their progress. We propose composite metrics that capture the complete value of the service to the user and emphasize the feasibility of measuring and monitoring such a metric over time.
The “Friends” That Help Dangerous Bacteria Get Into Your Salad
Authors: Dixon Megan H. , Harrod Victoria L. , Groves Russell L. , Barak Jeri D.
Published: October 2023

Salmonella enterica is a type of bacteria that can cause vomiting and diarrhea in humans. Normally, Salmonella dies when it is on the surface of healthy plant leaves. However, Salmonella has “friends” on plants that can help it survive. Plant-eating insects and phytobacteria that cause plant diseases can help Salmonella reach new places and access new food sources. Plant-eating insects can move Salmonella from one plant to another and provide Salmonella with valuable nutrients through their poop. Phytobacteria can cause sicken leaves, creating an environment that helps Salmonella enter the leaf and access protection. Both plant-eating insects and phytobacteria can cause leaves to release nutrients that can nourish dangerous bacteria like Salmonella. Together, the combination of Salmonella and insects or phytobacteria on crops may create the perfect recipe for contaminated produce that leads to disease in humans when they eat their healthy fruit or veggies.
How Intelligent is an Octopus or a Cuttlefish? Even Smarter Than You Might Think!
Authors: Schnell Alexandra , Fein-Schaffer Lynnie , Fritz Jonathan B. , Clayton Nicola
Published: October 2023

How smart is an octopus? Although we often associate intelligence with animals like dolphins, apes, elephants, parrots, and members of the crow family (jays and ravens), recent studies have revealed that octopuses and cuttlefish are also intelligent. These cephalopods have the largest brains amongst invertebrates, but their brains are completely different from our own human brains. Unlike many animals, an octopus grows up and learns on its own, without any instruction from its parents. An octopus quickly learns how to hide and camouflage itself to avoid predators. Octopuses have also been shown to use tools and sometimes they like to play. Cuttlefish, like their octopus cousins, are extremely intelligent. They are dazzling masters of camouflage, and have an excellent ability to remember past experiences, which helps guide their future behavior and decision-making. These clever cephalopods are revealing new insights that are helping scientists to understand how intelligence evolved.
Reconstructing village spatial layout to achieve rural revitalization: a case from a typical township in China
Authors: Zhu Zhiyuan , Wang Huaizhou , Yang Jihao , Feng Yongzhong
Published: October 2023

Rural revitalization is a strategy proposed by China to address the imbalance and insufficiency of urban and rural development. The purpose of village system reconstruction is to optimize the rural spatial structure and realize the efficient allocation of resource elements, which is of great significance to the overall revitalization of rural areas. This research adopts the analytic hierarchy process (AHP), the multi-index comprehensive evaluation method, and the GIS spatial analysis, taking Zhiyang Town as a case, reconstructing the index selection of the village-level system, putting forward a set of complete classification systems through the selecting village scale, resource conditions, social economic development level, industry, and other related data index, and building a village-level evaluation system. The 25 villages in Zhiyang Town were divided into four classes. Different development paths are proposed for different levels of villages. The evaluation of the village development level and reconstruction path of the village hierarchy system has certain practical guiding values for rural construction, which are of great significance for realizing rural revitalization.
Impact of food-related conflicts on self-reported food insecurity
Authors: Fiandrino Stefania , Dowd Caitriona , Martini Giulia , Mejova Yelena , Omodei Elisa , Paolotti Daniela , Tizzani Michele
Published: October 2023

Food security is recognized as an inherent human right, enshrined within the principles of the Agenda 2030. The Global Report of Food Crises 2022 points out 193 million people facing severe food insecurity across 53 countries, posing challenges to decision-makers and institutions. Among the many causes of food crises, violent conflict, economic shocks, and environmental pressures are the most influential. In this work, we focus primarily on the conflict-related domain. Finding a stable relationship between conflict and food insecurity is complex for several reasons: first, the relationship is mutually reinforcing; second, the full impact of conflict on food insecurity may take time to have an effect; and third, conflict itself is a multidimensional phenomenon and can include multiple types of violent events. This research set out to comparatively assess the impact of different types of violence on self-reported food insecurity in three prominent food crisis contexts: Burkina Faso, Syria, and Yemen. A measure of food-related classifying events was developed using a rules-based approach. The analysis showed that this approach can effectively code and classify food-related conflict in diverse contexts. By refining the search string, it becomes possible to capture food-related conflict in various food systems. Our findings point out that the new-build measure of food-related conflict is more strongly correlated to subsequent self-reported insufficient food consumption than other forms of violence. The results demonstrate that this relationship is robust across a range of data collection windows and across discrete time periods of analysis. In summary, the research suggests that focusing on the use of food and food systems as tactics in conflict can be highly valuable for understanding and addressing food insecurity.
Applying societal metabolism to characterize water availability, requirement, and scarcity in agriculture. A case study of Mexico
Authors: Escamilla Enrique Zunzunegui , Ordoñez Gonzalo Ángeles , Orozco-Ramírez Quetzalcóatl , Caballero Castrillo Maribel A. , Morales Mora Miguel A.
Published: October 2023

Given the environmental challenges of soil depletion, water scarcity, and resource competition, the agricultural products market demands a continuous increase in annual crop productivity. Nevertheless, it is often overlooked whether there are favorable conditions within the biophysical constraints of the natural system to meet such a requirement. This paper contemplates an integrated analysis that connects the interaction of water-land-food and production value (WLFPV) from the availability, requirement, and scarcity of water based on the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) framework. This study evaluates nine crops (agave, avocado, berries, coffee, figs, native maize, pitaya-pitahaya, critical banana, and vanilla) of high commercial value from the central-eastern region of Mexico to obtain their metabolic profiles and answer this question. For this, relative water stress index (RWSI) was used as well as intensity and metabolic density indicators for each crop. The findings were then visualized and communicated through maps. The results indicate that: (1) The annual available water satisfies the total water requirement of the crops of 1,782.6 hm3, planted in 276,965 hectares that produce 803,191 tons of food with a value of 165.2 million USD. (2) 65% of the area dedicated to the production of agave, pitaya-pitahaya, and other crops is affected by a water deficit. This area’s relative water stress index (RWSI) ranges from moderate to high. In the short term, they can constrain agricultural development areas. (3) The metabolic intensity and density indicators show that the combined efficiency of the water demand/supply relationship for native maize was very deficient in 23 of the 50 municipalities. From our analysis perspective, it was possible to understand the changes occurring in the Socio-Ecological System of the nine agricultural chains. A trend in decreased rainfall and water levels in the aquifers for food production was observed.
The effect of the surgical treatment of brachycephalic obstructive airway syndrome on the thermoregulatory response to exercise in French bulldogs: a pilot study
Authors: Žgank Žiga , Nemec Svete Alenka , Lenasi Helena , Vodičar Janez , Erjavec Vladimira
Published: October 2023

Introduction

Due to altered anatomy of the upper respiratory tract, brachycephalic dogs exhibit increased airway resistance and reduced surface area for evaporative heat loss, predisposing them to respiratory and thermoregulatory problems, a syndrome referred to as Brachycephalic Obstructive Airway Syndrome (BOAS). Compared to non-brachycephalic dogs, brachycephalic breeds are more susceptible to heat-related injuries even at low ambient temperatures and relatively low physical activity levels. Surgical treatment alleviates clinical signs, potentially improving dogs’ thermoregulatory ability with BOAS. Our study aimed to investigate the thermoregulatory response in French bulldogs before and after the surgical correction of BOAS, respectively.

Methods

Thirteen dogs were exposed to dynamic exercise on a treadmill and the dynamics of their rectal temperature (RT) and heart rate (HR) was measured. The experiment was performed in two independent sessions, before and after the surgical treatment. The test consisted of two consecutive 5-min walks at a speed of 2.5 km/h, first at an inclination of 0% and the second at an inclination of 5%, and a 30-min recovery period. Rectal temperature and HR were measured before the start of the test (t0), at the end of the first (t1) and the second part (t2), and 15 min (t3) and 30 min (t4) in the recovery.

Results

A significant increase in RT and HR was observed during exercise and recovery compared to the resting values, implying that the exercise intensity was sufficient to challenge the thermoregulatory response. The increase of RT was significantly lower during both parts (t1: p  = 0.004; t2: p  <  0.001) of exercise after the surgical treatment than before the treatment. Although a trend of lower RT after recovery was observed compared to before the surgery, it did not reach statistical significance. Similarly to RT, the HR was significantly lower during exercise after the first (p  =  0.020) and the second part (p  =  0.011) of exercise after the surgery compared to before the surgery but did not reach significance in the recovery.

Conclusion

Surgical treatment of BOAS can improve thermoregulation during exercise in French bulldogs with BOAS.
Comparative pathology of experimental pulmonary tuberculosis in animal models
Authors: Hunter Laura , Ruedas-Torres Inés , Agulló-Ros Irene , Rayner Emma , Salguero Francisco J.
Published: October 2023

Research in human tuberculosis (TB) is limited by the availability of human tissues from patients, which is often altered by therapy and treatment. Thus, the use of animal models is a key tool in increasing our understanding of the pathogenesis, disease progression and preclinical evaluation of new therapies and vaccines. The granuloma is the hallmark lesion of pulmonary tuberculosis, regardless of the species or animal model used. Although animal models may not fully replicate all the histopathological characteristics observed in natural, human TB disease, each one brings its own attributes which enable researchers to answer specific questions regarding TB immunopathogenesis. This review delves into the pulmonary pathology induced by Mycobacterium tuberculosis complex (MTBC) bacteria in different animal models (non-human primates, rodents, guinea pigs, rabbits, cattle, goats, and others) and compares how they relate to the pulmonary disease described in humans. Although the described models have demonstrated some histopathological features in common with human pulmonary TB, these data should be considered carefully in the context of this disease. Further research is necessary to establish the most appropriate model for the study of TB, and to carry out a standard characterisation and score of pulmonary lesions.
Long-Term Outcomes After Epigastric Hernia Repair in Women—A Nationwide Database Study
Authors: Christoffersen M. W. , Henriksen N. A.
Published: October 2023

Aim: Women have the highest prevalence of epigastric hernia repair. Outcomes after epigastric hernia repair are rarely reported independently, although pathology and surgical techniques may be different than for other primary ventral hernias. The aim of this study was to evaluate long-term outcomes after epigastric hernia repairs in women on a nationwide basis.

Methods: Nationwide cohort study from the Danish Hernia Database. Complete data from women undergoing elective epigastric hernia repair during a 12 years period (2007–2018) was extracted. A 100% follow-up was obtained by combining data from the National Civil Register. The primary outcome was operation for recurrence, secondary outcomes were readmission and operation for complications. Outcomes for open sutured repair, open mesh repair mesh, and laparoscopic repairs were compared.

Results: In total, 3,031 women underwent elective epigastric hernia repair during the study period. Some 1,671 (55.1%) women underwent open sutured repair, 796 (26.3%) underwent open mesh repair, and 564 (18.6%) underwent laparoscopic repair. Follow-up was median 4.8 years. Operation for recurrence was higher after sutured repairs than after open mesh and laparoscopic repairs (7.7% vs. 3.3%, vs. 6.2%, p < 0.001). The risk of operation for complications was slightly higher after open mesh repair compared with sutured repair and laparoscopic repair (2.6% vs. 1.2%, vs. 2.0%, p = 0.032), with more operations for wound complications in the open mesh group (2.0%, p = 0.006).

Conclusion: More than half of the women underwent a suture-based repair, although mesh repair reduces risk of recurrence. Open mesh repair had the lowest risk of recurrence, but on the expense of slightly increased risk of wound-related complications.
SFSNet: An Inherent Feature Segmentation Method for Ground Testing of Spacecraft
Authors: Li Yingxiao , Ma Ping , Huo Ju
Published: October 2023

In the final approach stage of rendezvous and docking of a spacecraft, the pose parameters of the target spacecraft need to meet docking or berthing capture conditions. Visible light visual measurement systems are increasingly employed in spacecraft ground tests to extract the geometric features of spacecraft to calculate and verify the accuracy of pose parameters. Most current feature-segmentation algorithms are unable to break through the scale transformation problem of spacecraft movement and the noise interference of multi-layer insulation materials in imaging. To overcome these challenges, we propose a novel feature segmentation algorithm based on the framework of deep convolutional neural networks. Firstly, a full convolution model of the encoding-decoding structure is constructed based on data for the ground test. A feature concatenation module is applied and combined with a network backbone to improve the segmentation performance. Then, a comprehensive loss function is presented and optimized by the pose characteristics of the spacecraft in the approach phase. Furthermore, a specific spacecraft simulation dataset to train and test our segmentation model is built through data augmentation. The experimental results verify that the proposed method achieves accurate segmentation of spacecraft of different scales, suppresses the interference caused by multilayer insulation material, and has strong robustness against motion ambiguity. The pixel accuracy of our proposed method reaches 96.5%, and the mean intersection over union is 93.0%.
Investigating and Analyzing Self-Reporting of Long COVID on Twitter: Findings from Sentiment Analysis
Authors: Thakur Nirmalya
Published: October 2023

This paper presents multiple novel findings from a comprehensive analysis of a dataset comprising 1,244,051 Tweets about Long COVID, posted on Twitter between 25 May 2020 and 31 January 2023. First, the analysis shows that the average number of Tweets per month wherein individuals self-reported Long COVID on Twitter was considerably high in 2022 as compared to the average number of Tweets per month in 2021. Second, findings from sentiment analysis using VADER show that the percentages of Tweets with positive, negative, and neutral sentiments were 43.1%, 42.7%, and 14.2%, respectively. To add to this, most of the Tweets with a positive sentiment, as well as most of the Tweets with a negative sentiment, were not highly polarized. Third, the result of tokenization indicates that the tweeting patterns (in terms of the number of tokens used) were similar for the positive and negative Tweets. Analysis of these results also shows that there was no direct relationship between the number of tokens used and the intensity of the sentiment expressed in these Tweets. Finally, a granular analysis of the sentiments showed that the emotion of sadness was expressed in most of these Tweets. It was followed by the emotions of fear, neutral, surprise, anger, joy, and disgust, respectively.
Face Image Segmentation Using Boosted Grey Wolf Optimizer
Authors: Zhang Hongliang , Cai Zhennao , Xiao Lei , Heidari Ali Asghar , Chen Huiling , Zhao Dong , Wang Shuihua , Zhang Yudong
Published: October 2023

Image segmentation methods have received widespread attention in face image recognition, which can divide each pixel in the image into different regions and effectively distinguish the face region from the background for further recognition. Threshold segmentation, a common image segmentation method, suffers from the problem that the computational complexity shows exponential growth with the increase in the segmentation threshold level. Therefore, in order to improve the segmentation quality and obtain the segmentation thresholds more efficiently, a multi-threshold image segmentation framework based on a meta-heuristic optimization technique combined with Kapur’s entropy is proposed in this study. A meta-heuristic optimization method based on an improved grey wolf optimizer variant is proposed to optimize the 2D Kapur’s entropy of the greyscale and nonlocal mean 2D histograms generated by image computation. In order to verify the advancement of the method, experiments compared with the state-of-the-art method on IEEE CEC2020 and face image segmentation public dataset were conducted in this paper. The proposed method has achieved better results than other methods in various tests at 18 thresholds with an average feature similarity of 0.8792, an average structural similarity of 0.8532, and an average peak signal-to-noise ratio of 24.9 dB. It can be used as an effective tool for face segmentation.
Barriers and Facilitators to the Implementation of the Early-Onset Sepsis Calculator: A Multicenter Survey Study
Authors: van Veen Liesanne E. J. , van der Weijden Bo M. , van Bodegom-Vos Leti , Hol Jeroen , Visser Douwe H. , Achten Niek B. , Plötz Frans B.
Published: October 2023

Prior studies demonstrated the neonatal early-onset sepsis (EOS) calculator’s potential in drastically reducing antibiotic prescriptions, and its international adoption is increasing rapidly. To optimize the EOS calculator’s impact, successful implementation is crucial. This study aimed to identify key barriers and facilitators to inform an implementation strategy. A multicenter cross-sectional survey was carried out among physicians, residents, nurses and clinical obstetricians of thirteen Dutch hospitals. Survey development was prepared through a literature search and stakeholder interviews. Data collection and analysis were based on the Consolidated Framework for Implementation Research (CFIR). A total of 465 stakeholders completed the survey. The main barriers concerned the expectance of the department’s capacity problems and the issues with maternal information transfer between departments. Facilitators concerned multiple relative advantages of the EOS calculator, including stakeholder education, EOS calculator integration in the electronic health record and existing positive expectations about the safety and effectivity of the calculator. Based on these findings, tailored implementation interventions can be developed, such as identifying early adopters and champions, conducting educational meetings tailored to the target group, creating ready-to-use educational materials, integrating the EOS calculator into electronic health records, creating a culture of collective responsibility among departments and collecting data to evaluate implementation success and innovation results.
Changes in Lifestyle Habits in Individuals with Diabetes during the COVID-19 Pandemic: The ELSA-Brasil Cohort Study
Authors: Dartora William Jones , Schmidt Maria Inês , Griep Rosane Harter , Duncan Bruce B.
Published: October 2023

The COVID-19 pandemic and society’s response to it may have constrained the ability of those with diabetes to achieve a healthy lifestyle. We conducted a longitudinal study to assess the frequency and magnitude of sedentary habits, physical activity, sleep, alcohol consumption, weight, and smoking from July 2020 to February 2021 and compared these levels to those before the pandemic (2017–2019) in 1082 participants of the ELSA-Brasil study with known diabetes. Our results showed that inappropriate sleep duration was common (649, 68.9%) before the pandemic. Many (447, 31.1%) with this problem achieved an adequate sleep duration during the pandemic. Significant increases occurred in time in front of screens (1.3; 95%CI 0.66–2.11 h/day) and time sitting or reclining (1.4, 95%CI 0.8–2.3 h/day). Physical activity decreased (270, 95%CI 243–298 MET-min/wk). Alcohol consumption decreased without statistical significance (−19.6, 95%CI −51.1–11.9 g/w). In general, changes were similar between diabetics and non-diabetics, except that screen time in-creased less (−0.18, −0.35–−0.01 h/day) for those with diabetes. Sleep duration improved, but the frequency of sedentary habits increased, and physical activity decreased during the pandemic. Understanding changes brought on by the pandemic is essential to facilitate the implementation of quality health care for those with diabetes in moments of social stress.
Evaluating Formic Acid as a Behavioral Modifier in African Savanna Elephants
Authors: Wright Mark G. , Gatti Irene , Au Michelle G. , Salehi Juliana , Spencer Craig R. , Allin Paul , Mafra-Neto Agenor
Published: October 2023

Formic acid was investigated as a potential repellant for African savanna elephants (Loxodonta africana) as a semiochemical option for managing elephant movements and interactions with human infrastructure. Formic acid is a naturally occurring compound, used as an alarm pheromone and as a defensive chemical in Formicine ants, and thus a potentially desirable option compared to introducing exogenous deterrents that are foreign to the elephants’ natural habitats. Although most elephants observed (85%) did not interact with treatments containing formic acid, of the cohort of individuals (n = 38) that did respond, the majority showed a mild to moderate avoidance response, while a small proportion of elephants were distinctly repelled when experiencing formic acid cues, in some cases causing whole herds to evacuate an area. The potential for using formic acid as an elephant repellant to modulate elephant behavior in field situations is discussed.
Dataset of Contamination (2009–2022) Legacy Contaminants (PCB and DDT) in Zooplankton of Lake Maggiore (CIPAIS, International Commission for the Protection of Italian-Swiss Waters)
Authors: Bettinetti Roberta , Piscia Roberta , Manca Marina , Galassi Silvana , Quadroni Silvia , Dossi Carlo , Perna Rossella , Boggio Emanuela , Boldrocchi Ginevra , Mazzoni Michela , Villa Benedetta
Published: October 2023

In this paper, we describe a 13-year (2009–2022) dataset of legacy POP concentrations (DDTtot and sumPCB14 from 2016 isomers and congeners concentrations are also reported) in the planktonic crustaceans of Lake Maggiore (≥450 µm size fraction). The data were collected in the framework of a monitoring program finalized to assess the presence of pollutants in the lake biota, including zooplankton organisms directly preyed by fish. The data report both concentration of DDTtot and sumPCB14 in the zooplankton and the standing stock density and biomass of the population in each season. The dataset allows for detecting changes in the concentration over the long term and within a year, thus providing evidence for the seasonal and the plurennial variations in the presence of these pollutants in the lake. They also provide a basis for further studies aimed at modeling paths and the fate of persistent organic pollutants, for which the amount of toxicants stocked in the zooplankton compartment linked to fish is a crucial estimate.
Closed-Loop Uncertainty: The Evaluation and Calibration of Uncertainty for Human–Machine Teams under Data Drift
Authors: Bishof Zachary , Scheuerman Jaelle , Michael Chris J.
Published: October 2023

Though an accurate measurement of entropy, or more generally uncertainty, is critical to the success of human–machine teams, the evaluation of the accuracy of such metrics as a probability of machine correctness is often aggregated and not assessed as an iterative control process. The entropy of the decisions made by human–machine teams may not be accurately measured under cold start or at times of data drift unless disagreements between the human and machine are immediately fed back to the classifier iteratively. In this study, we present a stochastic framework by which an uncertainty model may be evaluated iteratively as a probability of machine correctness. We target a novel problem, referred to as the threshold selection problem, which involves a user subjectively selecting the point at which a signal transitions to a low state. This problem is designed to be simple and replicable for human–machine experimentation while exhibiting properties of more complex applications. Finally, we explore the potential of incorporating feedback of machine correctness into a baseline naïve Bayes uncertainty model with a novel reinforcement learning approach. The approach refines a baseline uncertainty model by incorporating machine correctness at every iteration. Experiments are conducted over a large number of realizations to properly evaluate uncertainty at each iteration of the human–machine team. Results show that our novel approach, called closed-loop uncertainty, outperforms the baseline in every case, yielding about 45% improvement on average.
DAT-MT Accelerated Graph Fusion Dependency Parsing Model for Small Samples in Professional Fields
Authors: Li Rui , Shu Shili , Wang Shunli , Liu Yang , Li Yanhao , Peng Mingjun
Published: October 2023

The rapid development of information technology has made the amount of information in massive texts far exceed human intuitive cognition, and dependency parsing can effectively deal with information overload. In the background of domain specialization, the migration and application of syntactic treebanks and the speed improvement in syntactic analysis models become the key to the efficiency of syntactic analysis. To realize domain migration of syntactic tree library and improve the speed of text parsing, this paper proposes a novel approach—the Double-Array Trie and Multi-threading (DAT-MT) accelerated graph fusion dependency parsing model. It effectively combines the specialized syntactic features from small-scale professional field corpus with the generalized syntactic features from large-scale news corpus, which improves the accuracy of syntactic relation recognition. Aiming at the problem of high space and time complexity brought by the graph fusion model, the DAT-MT method is proposed. It realizes the rapid mapping of massive Chinese character features to the model’s prior parameters and the parallel processing of calculation, thereby improving the parsing speed. The experimental results show that the unlabeled attachment score (UAS) and the labeled attachment score (LAS) of the model are improved by 13.34% and 14.82% compared with the model with only the professional field corpus and improved by 3.14% and 3.40% compared with the model only with news corpus; both indicators are better than DDParser and LTP 4 methods based on deep learning. Additionally, the method in this paper achieves a speedup of about 3.7 times compared to the method with a red-black tree index and a single thread. Efficient and accurate syntactic analysis methods will benefit the real-time processing of massive texts in professional fields, such as multi-dimensional semantic correlation, professional feature extraction, and domain knowledge graph construction.
Development of the Kinetic Equation of the Groove Corrosion Process for Predicting the Residual Life of Oil-Field Pipelines
Authors: Popov Grigory , Bolobov Victor , Zhuikov Ilia , Zlotin Vladimir
Published: October 2023

One of the main reasons for oil-field pipeline failure is groove corrosion. The residual life of such pipelines is estimated based on defectoscopy corrosion rate—a ratio of the formed «groove» depth to the pipeline operation start time. In this case, it is supposed that, in the future, the «groove» will deepen at the same rate for the remaining period of the pipe’s operation. However, sometimes, oil-field pipeline operation experience shows that the remaining time of safe operation is much less than the calculated one. In this article, such a discrepancy is explained via the acceleration of the groove corrosion rate in the process of «groove» deepening due to the increasing level of mechanical stresses in the surrounding metal, which intensifies the corrosion process as a result of the mechanochemical effect. Based on a literature analysis and calculated data, the kinetic equation of the groove corrosion rate for an oil-field pipeline is proposed, which accounts for the acceleration of the process rate as the pipeline is operated and allows the more accurate estimation of its remaining service life.
Techno-Economic Analysis of State-of-the-Art Carbon Capture Technologies and Their Applications: Scient Metric Review
Authors: Adam Raghad , Ozarisoy Bertug
Published: October 2023

Carbon dioxide (CO2) emissions are a serious hazard to human life and the ecosystem. This is the reason that many measures have been put in place by the International Energy Agency (IEA) to reduce the anthropogenic-derived CO2 concentration in the atmosphere. Today, the potential of renewable energy sources has led to an increased interest in investment in carbon capture and storage technologies worldwide. The aim of this paper is to investigate state-of-the-art carbon capture and storage (CCS) technologies and their derivations for the identification of effective methods during the implementation of evidence-based energy policies. To this extent, this study reviews the current methods in three concepts: post-combustion; pre-combustion; and oxy-fuel combustion processes. The objective of this study is to explore the knowledge gap in recent carbon capture methods and provide a comparison between the most influential methods with high potential to aid in carbon capture. The study presents the importance of using all available technologies during the post-combustion process. To accomplish this, an ontological approach was adopted to analyze the feasibility of the CCS technologies available on the market. The study findings demonstrate that priority should be given to the applicability of certain methods for both industrial and domestic applications. On the contrary, the study also suggests that using the post-combustion method has the greatest potential, whereas other studies recommend the efficiency of the oxy-fuel process. Furthermore, the study findings also highlight the importance of using life cycle assessment (LCA) methods for the implementation of carbon capture technologies in buildings. This study contributes to the energy policy design related to carbon capture technologies in buildings.
Pipe Flow of Suspensions of Cellulose Nanocrystals
Authors: Kinra Saumay , Pal Rajinder
Published: October 2023

The pipeline flow behavior of suspensions of cellulose nanocrystals (CNCs) was investigated over the CNC concentration range of 0.24 to 3.65 wt% in different diameter pipelines. The CNC suspensions were Newtonian below the CNC concentration of 1 wt%. At higher concentrations, the CNC suspensions were non-Newtonian power-law fluids. For Newtonian CNC suspensions, the experimental friction factor–Reynolds number data were obtained only in the turbulent regime, and the data followed the Blasius equation closely. For power-law CNC suspensions, the experimental data of friction factor–Reynolds number covered both laminar and turbulent regimes. The experimental data followed the friction factor–Reynolds number relationships for power-law fluids reasonably well.
Approximation of Caputo Fractional Derivative and Numerical Solutions of Fractional Differential Equations
Authors: Dimitrov Yuri , Georgiev Slavi , Todorov Venelin
Published: October 2023

In this paper, we consider an approximation of the Caputo fractional derivative and its asymptotic expansion formula, whose generating function is the polylogarithm function. We prove the convergence of the approximation and derive an estimate for the error and order. The approximation is applied for the construction of finite difference schemes for the two-term ordinary fractional differential equation and the time fractional Black–Scholes equation for option pricing. The properties of the approximation are used to prove the convergence and order of the finite difference schemes and to obtain bounds for the error of the numerical methods. The theoretical results for the order and error of the methods are illustrated by the results of the numerical experiments.
Stochastic Modeling of Three-Species Prey–Predator Model Driven by Lévy Jump with Mixed Holling-II and Beddington–DeAngelis Functional Responses
Authors: Danane Jaouad , Yavuz Mehmet , Yıldız Mustafa
Published: October 2023

This study examines the dynamics of a stochastic prey–predator model using a functional response function driven by Lévy noise and a mixed Holling-II and Beddington–DeAngelis functional response. The proposed model presents a computational analysis between two prey and one predator population dynamics. First, we show that the suggested model admits a unique positive solution. Second, we prove the extinction of all the studied populations, the extinction of only the predator, and the persistence of all the considered populations under several sufficient conditions. Finally, a special Runge–Kutta method for the stochastic model is illustrated and implemented in order to show the behavior of the two prey and one predator subpopulations.
To the Theory of Decaying Turbulence
Authors: Migdal Alexander
Published: October 2023

We have found an infinite dimensional manifold of exact solutions of the Navier-Stokes loop equation for the Wilson loop in decaying Turbulence in arbitrary dimension d>2. This solution family is equivalent to a fractal curve in complex space Cd with random steps parametrized by N Ising variables σi=±1, in addition to a rational number pq and an integer winding number r, related by ∑σi=qr. This equivalence provides a dual theory describing a strong turbulent phase of the Navier-Stokes flow in Rd space as a random geometry in a different space, like ADS/CFT correspondence in gauge theory. From a mathematical point of view, this theory implements a stochastic solution of the unforced Navier-Stokes equations. For a theoretical physicist, this is a quantum statistical system with integer-valued parameters, satisfying some number theory constraints. Its long-range interaction leads to critical phenomena when its size N→∞ or its chemical potential μ→0. The system with fixed N has different asymptotics at odd and even N→∞, but the limit μ→0 is well defined. The energy dissipation rate is analytically calculated as a function of μ using methods of number theory. It grows as ν/μ2 in the continuum limit μ→0, leading to anomalous dissipation at μ∝ν→0. The same method is used to compute all the local vorticity distribution, which has no continuum limit but is renormalizable in the sense that infinities can be absorbed into the redefinition of the parameters. The small perturbation of the fixed manifold satisfies the linear equation we solved in a general form. This perturbation decays as t−λ, with a continuous spectrum of indexes λ in the local limit μ→0. The spectrum is determined by a resolvent, which is represented as an infinite product of 3⊗3 matrices depending of the element of the Euler ensemble.
Drug and Protein Interaction Network Construction for Drug Repurposing in Alzheimer’s Disease
Authors: Dimitrakopoulos Georgios N. , Vrahatis Aristidis G. , Exarchos Themis P. , Krokidis Marios G. , Vlamos Panagiotis
Published: October 2023

Alzheimer’s disease is one of the leading causes of death globally, significantly impacting countless families and communities. In parallel, recent advancements in molecular biology and network approaches, guided by the Network Medicine perspective, offer promising outcomes for Alzheimer’s disease research and treatment. In this study, we aim to discover candidate therapies for AD through drug repurposing. We combined a protein-protein interaction (PPI) network with drug-target interactions. Experimentally validated PPI data were collected from the PICKLE meta-database, while drugs and their protein targets were sourced from the DrugBank database. Then, based on RNA-Seq data, we first assigned weights to edges to indicate co-expression, and secondly, estimated differential gene expression to select a subset of genes potentially related to the disease. Finally, small subgraphs (modules) were extracted from the graph, centered on the genes of interest. The analysis revealed that even if there is no drug targeting several genes of interest directly, an existing drug might target a neighboring node, thus indirectly affecting the aforementioned genes. Our approach offers a promising method for treating various diseases by repurposing existing drugs, thereby reducing the cost and time of experimental procedures and paving the way for more precise Network Medicine strategies.
Injectable In Situ Crosslinking Hydrogel for Autologous Fat Grafting
Authors: Oskarsdotter Kristin , Nordgård Catherine T. , Apelgren Peter , Säljö Karin , Solbu Anita A. , Eliasson Edwin , Sämfors Sanna , Sætrang Henriette E. M. , Asdahl Lise Cathrine , Thompson Eric M. , Troedsson Christofer , Simonsson Stina , Strand Berit L. , Gatenholm Paul , Kölby Lars
Published: October 2023

Autologous fat grafting is hampered by unpredictable outcomes due to high tissue resorption. Hydrogels based on enzymatically pretreated tunicate nanocellulose (ETC) and alginate (ALG) are biocompatible, safe, and present physiochemical properties capable of promoting cell survival. Here, we compared in situ and ex situ crosslinking of ETC/ALG hydrogels combined with lipoaspirate human adipose tissue (LAT) to generate an injectable formulation capable of retaining dimensional stability in vivo. We performed in situ crosslinking using two different approaches; inducing Ca2+ release from CaCO3 microparticles (CMPs) and physiologically available Ca2+ in vivo. Additionally, we generated ex situ-crosslinked, 3D-bioprinted hydrogel-fat grafts. We found that in vitro optimization generated a CMP-crosslinking system with comparable stiffness to ex situ-crosslinked gels. Comparison of outcomes following in vivo injection of each respective crosslinked hydrogel revealed that after 30 days, in situ crosslinking generated fat grafts with less shape retention than 3D-bioprinted constructs that had undergone ex situ crosslinking. However, CMP addition improved fat-cell distribution and cell survival relative to grafts dependent on physiological Ca2+ alone. These findings suggested that in situ crosslinking using CMP might promote the dimensional stability of injectable fat-hydrogel grafts, although 3D bioprinting with ex situ crosslinking more effectively ensured proper shape stability in vivo.
Preserving and Celebrating Syrian Intangible Cultural Heritage in the UK: Strategies, Insights, and Untold Narratives
Authors: Alsalloum Ataa
Published: October 2023

In recent times, the significance of living heritage during crises has gained prominence. While the aftermath of such crises often leads to lessons being forgotten, those in conflict zones persistently endure hardships. This study examines the pivotal role of intangible cultural heritage (ICH) in bolstering resilience, particularly among diaspora communities, using Syrians in the UK as a case study. We delve into the primary ICH practices that they adopt, their assimilation techniques within the UK, the impact of wartime experiences on their reactions to the COVID-19 pandemic lockdown, and the consequent effects on host communities. Employing a diverse methodological framework that includes online public lectures, interviews, and direct observations, our results underscore the Syrian diaspora’s earnest commitment to preserving its rich heritage. Beyond the poignant losses of invaluable art and treasures to conflict, a dominant narrative of hope and enduring human spirit emerges. As illuminated by our findings, Syrians’ resilience extends beyond mere survival, reflecting a deep-seated pride in identity and an unyielding cultural spirit. This resilience not only marks the continuation of Syrian culture but also highlights its capacity to evolve, adapt, and enrich new environments.
Only 11 Simple Sequence Repeats Needed to Identify Chinese Cabbage (Brassica rapa L.) Cultivars
Authors: Kim Jiwon , Lim Jihyeon , Jeong Yunjeong , Yu Hyewon , Park Yong , Lim Chaewan , Chae Wonbyoung
Published: October 2023

Chinese cabbage is a popular leaf vegetable, and many cultivars have been developed for different regions and growing seasons. For the identification of the cultivars, many marker systems have been applied, but they usually require a large number of markers and expensive equipment. Therefore, it is necessary to develop an efficient and economical method for identifying Chinese cabbage cultivars. In this study, we aimed to develop a marker system with the minimum number of markers using simple PCR and gel electrophoresis. A total of 48 simple sequence repeats (SSRs) in a previous study were screened based on their chromosomal location and applied to 105 Chinese cabbage cultivars. The minimum number of markers was selected based on their genomic location, polymorphic information content, and allele frequency. To validate the cultivar identification capability of selected SSRs, they were applied to genetically similar cultivar pairs from a previous study. Eleven SSRs were finally selected, and they successfully identified cultivars with high genetic similarity, as well as all 105 Chinese cabbage cultivars tested. The proposed SSRs require only 11 primer sets, simple PCR, and gel electrophoresis, which need less time and resources compared to previous ones. These SSRs can be used not only in small seed companies and laboratories but also in large-scale seed companies.
Garden Waste Compost Tea: A Horticultural Alternative to Promote Plant Growth and Root Traits in Tomato (Solanum lycopersicum L.) Plants
Authors: González-Hernández Ana Isabel , Gómez-Sánchez María Ángeles , Pérez-Sánchez Rodrigo , Morales-Corts María Remedios
Published: October 2023

The application of garden waste compost teas (CTs) in sustainable agriculture constitutes a biostimulant and environmentally friendly alternative. The purpose of this work was to study the physicochemical properties of three CTs prepared with different brewing processes (CT1, CT2, and CT3) immediately after extraction and six months later to determine whether those properties changed over time and evaluate the effect of CT application on tomato (Solanum lycopersicum L.) plant growth. The brewing process had a significant effect on the extracts’ chemical composition, while long-term storage did not lead to significant differences. The most energy-efficient CT was evaluated in a pot and in vitro assays by measuring plant growth parameters and root traits. CT1 directly supplied to the substrate increased the leaf number, plant height, and dry weight of tomato plants compared to the control and foliar treatments, whereas no significant differences were found among foliar treatments. In terms of the effects of CT application on root development, the results of the in vitro assays showed that CT supply enhanced the primary root length, lateral root number, and root fresh weight while decreasing shoot height and weight in 10-day-old tomato seedlings. From an agronomic standpoint, this study contributes new insights regarding the storage stability of CT and its impact on tomato plant growth.