bluuebunny/crossref_metadata_2025 huggingface dataset:
Early predictors of reading success in first grade
Authors: Sucena Ana , Garrido Cristina , Marques Cátia , Lousada Marisa
Published: August 2023

Reading acquisition is a complex process that can be predicted by several components which, in turn, can be affected by the orthography depth. This study aims to explore the early predictors of (un)success in reading acquisition within an intermediate transparent orthography. At the beginning of the school year, 119 European Portuguese-speaking first graders were assessed regarding (i) sociodemographic variables: mothers’ education and socioeconomic status (SES); (ii) cognitive variables: phonological working memory and vocabulary; (iii) reading-related variables: letter-sound knowledge, phonemic awareness, and rapid naming. Results of the three variable clusters were correlated with the final classification obtained in the Portuguese discipline. Specifically, there was a correlation between the Portuguese discipline classification with all reading and cognitive-related variables, with the highest correlations occurring with mother education and letter spelling. A regression analysis was conducted to assess the predictor impact of mother education and letter spelling (variables that correlated stronger with the Portuguese classification) on Portuguese classifications. Letter spelling was the sole significant predictor of the Portuguese classification. Based on these results, a path analysis was run to test whether letter spelling is a mediator of the relationship between the mother’s education and the Portuguese classification. The results of the model test yielded a reasonable fit, indicating a relationship between the mother’s education and letter spelling, which in turn, relates to the Portuguese classification. The identification of reading predictors in an intermediate-depth orthography such as European Portuguese contributes to more accurate identification of at-risk children.
Effects of smartphone addiction on cognitive function and physical activity in middle-school children: a cross-sectional study
Authors: Al-Amri Ahlam , Abdulaziz Sahar , Bashir Shahid , Ahsan Mohammad , Abualait Turki
Published: August 2023

Introduction

This study aimed to investigate the effects of smartphone addiction on cognitive function and physical activity in middle-school children.

Methods

A population of 196 children (boys and girls) from middle schools were recruited for this study with an average age of 12.99 ± 0.81 years, a height of 153.86 ± 6.50 meters, a weight of 48.07 ± 7.31 kilograms, and a body mass index of 20.22 ± 2.08 kg/m2. Smartphone addiction was determined using Arabic versions of the Smartphone Addiction Scale-Short Version, and physical activity levels were assessed by a physical activity questionnaire for older children. The working memory and selective attention domains of cognitive function were evaluated using a laptop screen's digital version of the memory automaticity and Flanker tasks, respectively. A one-way MANOVA was conducted to determine the differences in working memory between the smartphone-addicted and non-addicted groups. The relationship between smartphone addiction and physical activity was analyzed using Pearson's chi-squared test.

Results

The cognitive function-attention domain accuracy component showed a statistically significant difference between the groups, with a p-value of 0.05). The reaction time between smartphone-addicted and non-addicted children showed no statistically significant difference (p = 0.817). The relationship between smartphone addiction and physical activity was statistically significant (p < 0.001).

Discussion

The interaction effects between physical activity and smartphone addiction on reaction times showed statistically insignificant (p = 0.25) differences, showing that physical activity's effect on reaction times did not depend on smartphone addiction levels. The non-addicted children had significantly higher physical activity levels than the addicted children, indicating that smartphone addiction reduced physical activity.
Beyond the label: current evidence and future directions for the interrelationship between electronic cigarettes and mental health
Authors: Bautista Malia , Mogul Allison S. , Fowler Christie D.
Published: August 2023

Electronic cigarette use has dramatically increased over the last decade. With this recent technological development and wide range of constituents in various products, putative adverse effects on the brain and body have been largely unexplored. Here, we review current evidence linking electronic nicotine cigarette use with potential health consequences and provide evidence supporting an association between drug use and depression in humans. We also examine the biological effects of individual constituents in electronic cigarette aerosols, which include labeled ingredients, such as propylene glycol, vegetable glycerin, nicotine, and flavorants, as well as unlabeled ingredients found in the aerosols, such as carbonyls and heavy metals. Lastly, we examine the effects of electronic cigarette use on endogenous metabolism via changes in cytochrome P450 enzymes, which can thereby impact therapeutic outcomes. While the current evidence offers insight into the potential effects of electronic cigarette use on biological processes, further studies are necessary to determine the long-term clinical relevance of aerosol inhalation.
Exploring intelligent hospital management mode based on artificial intelligence
Authors: Mi Dezhi , Li Yong , Zhang Kangying , Huang Chaoni , Shan Wenjia , Zhang Jiangbo
Published: August 2023

Objective

To address the challenges posed by the COVID-19 pandemic, our hospital developed an intelligent hospital management mode specifically tailored to COVID-19 patients.

Methods

This study included patients with confirmed diagnosis of COVID-19 admitted to our hospital between January 2020 to December 2022. We sought to explore intelligent hospital management mode based on artificial intelligence (AI) and new technologies such as 5G, Internet of Things (IoT), wearable devices, robots, and small programs.

Results

Intelligent hospital management mode can help improve the quality of life of patients, while also improving the management ability of the hospital, as it can automatically deliver timely patient reminders, maintain environmental cleanliness, and help in the transportation of medical equipment without any manual labor. This can help in conserving time and reducing the workload of medical staff. Moreover, itcan help intellectualize patient admission, patient discharge, and hospital management, thereby helping in providing efficient medical and patient humanistic care.

Conclusions

The development of intelligent management mode can reduce the burden of medical personnel and the probability of developing infection and bring about timely and better patient care. Intelligent management can play a pivotal role in control of the epidemic, treating patients, allocation of resources, tracing the root cause of the virus, and monitoring.
The occurrence of acute primary angle closure triggered, aggravated, and accelerated by COVID-19 infection: retrospective observational study
Authors: Ying Yue , Zhai Ruyi , Sun Yanan , Sheng Qilian , Fan Xintong , Kong Xiangmei
Published: August 2023

Introduction

The aim of this study is to demonstrate the relevance of primary acute angle closure (APAC) and COVID-19 infection, compare the demographic features and manifestations between COVID-19 positive and negative patients with APAC, and infer the underlying mechanism.

Methods

This study is based on all patients diagnosed with APAC at the glaucoma center of Eye, Ear, Nose and Throat Hospital of Fudan University (Fenyang road center) from 15th December 2022 to 11th January 2023. Totally 171 APAC cases were categorized into COVID-19 positive and negative group. Demographic features and final treatment level of the patients were compared between the two groups. Clinical manifestations, intraocular pressure, and anterior chamber configuration were also compared between the two groups.

Results

In the COVID-19 positive group, the number of cases with APAC onset spiked in 22nd December 2022, which coincided with the spike of COVID-19 antigen positive people. Compared to the COVID-19 negative group, COVID-19 positive APAC patients were younger with a lower percentage of APAC history. Additionally, more eyes of COVID-19 positive APAC patients showed keratic precipitates. COVID-19 positive eyes had significantly larger anterior chamber depth with a more dilated pupil. Therefore, COVID-19 infection could probably act as a triggering factor of APAC

Discussion

The onset of APAC might be accelerated by COVID-19 infection for patients with younger age and milder anatomical configuration. Additionally, COVID-19 related APAC cases might have a more abrupt and fierce onset. Ophthalmic emergent services should not be neglected during the epidemic period.
Cognitive orientation to daily occupational performance (CO-OP) approach as telehealth for a child with developmental coordination disorder: a case report
Authors: Shiozu Hiroyasu , Kurasawa Shigeki
Published: August 2023

Aim

This study aimed to propose a possible interventional form of occupational therapy through a case study report of the applied Cognitive Orientation to daily Occupational Performance (CO-OP) approach as telehealth for a child with developmental coordination disorder (DCD).

Methods

The intervention method was CO-OP-based tele-occupational therapy for a boy with DCD and his mother; 10 sessions were conducted using a video-conferencing system. This study used the Canadian Occupational Performance Measure (COPM) and the Performance Quality Rating Scale (PQRS) as assessment tools. The PQRS evaluated each occupational performance based on videos recorded during the online sessions and videos taken by the mother of the child.

Results

The CO-OP approach improved COPM performance and satisfaction as well as PQRS scores in the following five goals: (1) handwriting, (2) column addition, (3) jumping rope, (4) playing on the bar, and (5) riding a bicycle.

Conclusions

An online approach based on the CO-OP was realistic and effective, to some extent. Continuing to develop telehealth interventions in the future is recommended.
The potential impact of banana Xanthomonas wilt on food systems in Africa: modeling scenarios of policy response and disease control measures
Authors: Petsakos Athanasios , Kozicka Marta , Blomme Guy , Nakakawa Juliet N. , Ocimati Walter , Gotor Elisabetta
Published: August 2023

Banana Xanthomonas wilt (BXW) is one of the most important diseases threatening banana production in Africa south of the Sahara (SSA). In this study, we examine the potential impacts of BXW on banana production, demand, and food security in SSA, if the disease spread across all banana-producing countries in the region. The analysis is based on a multidisciplinary approach that combines a mathematical model of field-level BXW spread over time with a dynamic global partial equilibrium economic model. Since BXW control relies exclusively on management, we analyze three scenarios of BXW spread that are constructed around assumptions about the level of policy response to the disease, and about how this response may affect the adoption of appropriate management practices by farmers to control BXW. Modeling results suggest that if the disease is left uncontrolled, banana production in SSA within 10 years can decrease by as much as 55%, compared to a BXW-free baseline scenario, resulting in economic losses of around 25 billion USD. At the same time, the population at risk of hunger in countries that highly depend on bananas as a staple food is projected to increase by more than 4.6%. Even a limited policy response to BXW can reduce infections and mitigate some of the production, economic, and food security consequences. BXW impacts are almost completely negated when farmers have good knowledge of the disease and fully adopt the appropriate management practices. This result highlights the need for policy frameworks which rely on sustained and coordinated efforts by public and private stakeholders, within and across SSA countries and at different geographical scales. It also aims to raise awareness and promote the adoption of such practices, while also considering local peculiarities and socioeconomic conditions.
Case report: Long-term survival in puppies assessed with echocardiography, electrocardiography and cardiac troponin I after acute death in littermates due to parvoviral myocarditis
Authors: Dines Brenda , Kellihan Heidi , Allen Carolyn , Loynachan Alan , Bochsler Philip , Newbury Sandra
Published: August 2023

Positive clinical outcomes of a group of surviving puppies from a litter affected by parvoviral myocarditis are detailed in this case report. Past reports focus on the negative outcomes of littermates of puppies who have died of parvoviral myocarditis. In this case, two puppies in a shelter setting, from a litter exposed to parvovirus, died suddenly with parvoviral myocarditis diagnosed at necropsy. The other seven puppies were screened for cardiac health with echocardiogram, electrocardiogram, and cardiac troponin I prior to adoption. All seven puppies had normal echocardiograms, electrocardiograms, and normal initial and recheck cardiac troponin I results. At recheck 2 years after the initial round of testing, two of the puppies were screened and continue to have normal cardiac diagnostics. All seven dogs are alive and thriving at 5 years old in homes with adopters who were given a complete medical history on the dogs prior to adoption. In summary, the outcomes for puppies in litters affected by parvoviral myocarditis are variable but they do not have to be grave. The use of cardiac diagnostics including echocardiogram, electrocardiogram and cardiac troponin I may serve as a prognostic basis for assessing the potential outcomes for the surviving puppies in affected litters.
Case report: Surgical treatment and long-term successful outcome of a spinal intramedullary vascular malformation in a dog
Authors: Santifort Koen M. , Plonek Marta , Grinwis Guy C. M. , Carrera Ines , Platt Simon
Published: August 2023

A 3.5-year-old male intact Staffordshire terrier crossbreed dog was presented with a one-week history of progressive paraparesis with fecal and urinary incontinence. Neurological examination was consistent with a T3-L3 myelopathy. A magnetic resonance imaging study revealed the presence of a well-circumscribed hemorrhagic space-occupying lesion at the level of T12, suspected to be a vascular malformation, such as cavernoma or arteriovenous fistula, primary hematoma or hamartoma; less likely considerations included hemorrhagic inflammation or hemorrhagic primary or secondary neoplasia. A dorsal laminectomy, durotomy, and midline dorsal myelotomy were performed with a surgical microscope, and the vascular lesion was identified and removed. Histological examination of surgical samples yielded fibrin, hemorrhage, hematoidin pigment, and some neural tissue. Although a lining wall was visualized during surgery consistent with a vascular malformation, there was no histological confirmation of such a structure, hampering definitive classification of the lesion. There was no gross or histopathological evidence that would support a diagnosis of a hamartoma or benign neoplasia. The dog was paraplegic with intact nociception the day following surgery. Ambulation was recovered within 2 weeks. Progressive and complete recovery of neurological function was seen over the next 12 weeks. No recurrence of neurological dysfunction was seen over a 12-month follow-up period. Surgical treatment should be considered in dogs with spinal intramedullary vascular lesions which can have a successful long-term outcome.
Gender Differences in Migrant Workers Health in China
Authors: Tian Yihao , Zhan Yong , Wu Min
Published: August 2023

Objectives: This study aimed to explore the distribution and differences in the health status of migrant workers in China by gender and age. In addition, it investigated the causes of health inequalities among them.

Methods: This paper analyzes the differences in health status across age groups for migrant workers of different genders based on the data from the China Migrant Dynamic Survey in 2018. It also empirically assesses how education level and health insurance impact gender-related health inequalities.

Results: The results suggest that female migrant workers in China have significantly lower health levels than males. Furthermore, these differences in health are exacerbated with age. This disparity may be attributed to lower participation in social insurance participation and less educational attainment among female migrant workers than their male counterparts.

Conclusion: The government should take effective practical measures to increase the social insurance participation rate of female migrant workers. Moreover, investing in female education to reduce health inequality among migrant workers is essential.
Environmental Burden of Disease due to Emissions of Hard Coal- and Lignite-Fired Power Plants in Germany
Authors: Liebig-Gonglach Michaela , Neunhäuserer Lina , Kuenen Jeroen , Hoffmann Barbara , Soppa Vanessa , Diegmann Volker , Hornberg Claudia
Published: August 2023

Objectives: The study estimated the environmental burden of disease (EBD) attributable to a long-term exposure of the population to nitrogen dioxide (NO2) and fine particulate matter (PM2.5) emissions from hard coal- and lignite-fired power plants in Germany for the year 2015.

Methods: The contribution of coal-fired power plants to the total air pollutant concentration was modelled using a chemical transport model and then combined with population data to assess the corresponding population exposure. We calculated years of life lost (YLL), years of life with disability, or disability-adjusted life years for different health outcomes with a strong evidence for an association with the exposure.

Results: The burden of disease from PM2.5 emissions from lignite is 1.2 times higher than that from hard coal emissions (7,866 YLL compared to 6,412 YLL). NO2 emissions from lignite, cause a burden of disease 2.3 times higher than hard coal NO2-emission (13,537 YLL compared to 5,906 YLL). The EBD for both pollutants is dominated by diseases of the cardiovascular system.

Conclusion: Abandoning energy generation by coal-fired power plants would lower the burden of disease in Germany.
Decision Making under Conditions of Uncertainty and Risk in the Formation of Warehouse Stock of an Automotive Service Enterprise
Authors: Makarova Irina , Buyvol Polina , Gabsalikhova Larisa , Belyaev Eduard , Mukhametdinov Eduard
Published: August 2023

This article is devoted to the problem of determining the rational amount of spare parts in the warehouse of a service center of an automobile manufacturer’s branded network used for maintenance and current repairs. This problem was solved on the basis of the accumulated statistical data of failures that occurred during the warranty period of vehicle operation. In the calculation, game methods were used. This took into account the stochastic need for spare parts and the consequences of their presence or absence in stock, which are expressed in the form of a profit and an additional possible payment of a fine in case of a discrepancy between the current level of demand for spare parts and the available spare parts. Two cases of decision making are considered: under conditions of risk and uncertainty, the occurrence of which depends on the amount of information about the input flow of enters to the service center. If such statistics are accumulated, then the decision is made taking into account the possible risk associated with the uncertainty of a specific need for spare parts. Otherwise, the probability of a particular need is calculated on the basis of special criteria. To optimize the collection of information about the state of warehouse stocks, the transfer of information, and the assessment and forecasting of stocks, well-organized feedback is needed, which is shown in the form of an algorithm.
Systematic Analysis and Design of Control Systems Based on Lyapunov’s Direct Method
Authors: Voßwinkel Rick , Röbenack Klaus
Published: August 2023

This paper deals with systematic approaches for the analysis of stability properties and controller design for nonlinear dynamical systems. Numerical methods based on sum-of-squares decomposition or algebraic methods based on quantifier elimination are used. Starting from Lyapunov’s direct method, these methods can be used to derive conditions for the automatic verification of Lyapunov functions as well as for the structural determination of control laws. This contribution describes methods for the automatic verification of (control) Lyapunov functions as well as for the constructive determination of control laws.
Error Analysis of a New Five-Degree-of-Freedom Hybrid Robot
Authors: San Hongjun , Ding Lin , Zhang Haobin , Wu Xingmei
Published: August 2023

The error analysis of the robot has a very practical significance for improving its accuracy. Therefore, this paper conducts an error analysis for a new five-degree-of-freedom hybrid robot designed to conduct responsible surface machining. Initially, the error sources of the hybrid robot were sorted out to determine the number of error sources. Then, the error mapping model of the hybrid robot is established by the closed-loop vector method and the first-order perturbation method. Based on the mapping property of the 6th-order velocity Jacobi matrix, the compensable and non-compensable error sources affecting the posture error at the end of the hybrid robot are separated. Finally, the error analysis of the separated error sources is carried out to study the effect of single error sources and multiple error sources coupled with the posture error at the end of the robot. The results show that among the individual error sources, the dynamic and fixed platform hinge position error has the most significant effect on the end of the robot; among the integrated posture errors after coupling multiple error sources, the position of the dynamic and fixed platform hinge position error and the translational joint initial position dominate; the analysis of the different trajectories also yields that the error introduced by each error source increases gradually with the increase of the end trajectory. When designing this hybrid robot, attention should be paid to the manufacturing and installation accuracy of the dynamic and fixed platform hinge point positions and the translational joint initial position.
Long-Distance GNSS-Denied Visual Inertial Navigation for Autonomous Fixed-Wing Unmanned Air Vehicles: SO(3) Manifold Filter Based on Virtual Vision Sensor
Authors: Gallo Eduardo , Barrientos Antonio
Published: August 2023

This article proposes a visual inertial navigation algorithm intended to diminish the horizontal position drift experienced by autonomous fixed-wing UAVs (unmanned air vehicles) in the absence of GNSS (Global Navigation Satellite System) signals. In addition to accelerometers, gyroscopes, and magnetometers, the proposed navigation filter relies on the accurate incremental displacement outputs generated by a VO (visual odometry) system, denoted here as a virtual vision sensor, or VVS, which relies on images of the Earth surface taken by an onboard camera and is itself assisted by filter inertial estimations. Although not a full replacement for a GNSS receiver since its position observations are relative instead of absolute, the proposed system enables major reductions in the GNSS-denied attitude and position estimation errors. The filter is implemented in the manifold of rigid body rotations or SO(3) in order to minimize the accumulation of errors in the absence of absolute observations. Stochastic high-fidelity simulations of two representative scenarios involving the loss of GNSS signals are employed to evaluate the results. The authors release the C++ implementation of both the visual inertial navigation filter and the high-fidelity simulation as open-source software.
Relationship between Beef Quality and Bull Breed
Authors: Kostusiak Piotr , Slósarz Jan , Gołębiewski Marcin , Sakowski Tomasz , Puppel Kamila
Published: August 2023

The beef industry in Poland heavily relies on the Polish Holstein-Friesian (PHF) breed, known for its primary use in dairy production, but which also contributes significantly to the beef supply. In contrast, the Limousine (LM), Hereford (HH), and Charolaise (CH) breeds have gained popularity due to their ideal specialized characteristics for beef production. As PHF continues to dominate the beef market, a thorough comparison of its beef quality and nutritional attributes with the three most popular beef breeds in Poland is essential. This study aims to address this knowledge gap by conducting a rigorous comparison. The experiment was carried out on the beef from 67 bulls kept in a free-stall system with standardized feeding. The highest total antioxidant status (TAS) was found in CH and was 147.5% higher than that in PHF. Also, compared with PHF, a large difference of 70% was observed in LM, while in HH it was only 6.25%. For degree of antioxidant potential (DAP), the highest concentration was found in LM, while CH had a slightly lower score than LM. PHF had the lowest scores for each of the analyzed parameters of protein fraction. For anserine, taurine, creatinine, and creatine content, the highest results were found for LM. For carnosine and coenzyme Q10, the highest values were found for CH. Overall, these results highlight the impact of maturity and breed on carcass composition and quality. Late-maturing breeds, such as LM and CH, tend to exhibit leaner carcasses with superior fatty acid profiles and antioxidant properties. This knowledge is valuable for producers, enabling them to make informed decisions regarding breed selection and production strategies to meet specific market demands for beef with the desired composition and quality.
Effects of SLC45A2 and GPNMB on Melanin Deposition Based on Transcriptome Sequencing in Chicken Feather Follicles
Authors: Li Ruiting , Wang Yanxing , Liu Yihan , Li Donghua , Tian Yadong , Liu Xiaojun , Kang Xiangtao , Li Zhuanjian
Published: August 2023

As an essential genetic and economic trait, chicken feather color has long been an important research topic. To further understand the mechanism of melanin deposition associated with coloration in chicken feathers, we selected feather follicle tissues from the neck and wings of chickens with differently colored feathers (yellow, sub-Columbian, and silver) for transcriptome analysis. We focused on genes that were expressed in both the wings and neck and were expressed with the same trends in breeds with two different plumage colors, specifically, SLC45A2, GPNMB, MLPH, TYR, KIT, WNT11, and FZD1. GO and KEGG enrichment analyses showed the DEGs were enriched in melanin-related pathways, such as tyrosine metabolic pathway and melanogenesis, and PPI analysis highlighted the genes SLC45A2 and GPNMB as associated with melanin deposition. Verification experiments in chicken melanocytes demonstrated that these two genes promote melanocyte melanin deposition. These data enrich our knowledge of the mechanisms that regulate chicken feather color.
Study on the Adaptive Regulation of Light on the Stress Response of Mandarin Fish (Siniperca chuatsi) with Re-Feeding after Starvation
Authors: Zhou Jian , Li Qiang , Huang Zhipeng , Zhang Lu , Mou Chengyan , Zhao Zhongmeng , Zhao Han , Du Jun , Yang Xiaojun , Liang Xufang , Duan Yuanliang
Published: August 2023

Light influences the stress response to environmental stimuli and feeding behaviors of Siniperca chuatsi and, thus, is an important regulator of normal growth and development. In this study, we first explored the important role of light on the digestive and stress capacity of S. chuatsi by studying the changes in physiological and biochemical indicators of S. chuatsi, taking the re-feeding after starvation as the constant environmental stimulus and the light intensity as the adjustable environmental stimulus. The activity of protease and lipase was generally higher in the stomach tissues than in the intestinal tissues, especially lipase, which was higher in stomach tissues under all light conditions, and the protease and lipase activity peaked in the stomach tissues of S. chuatsi at a light intensity of 18.44 ± 3.00 lx and in intestinal tissues at 11.15 ± 2.01 lx, respectively, indicating that greater light intensity increased the digestive capacity of stomach tissues, whereas lower light intensity facilitated the digestive capacity of intestinal tissues. The tissues of the gill, stomach, and intestine had relatively high activity of stress-related enzymes, whereas the tissues of the brain, kidney, liver, and plasma samples had relatively low activity of enzymes. Collectively, the results show that light intensity at 11.15 ± 2.01 lx promoted digestive capacity in the intestine and enhanced the anti-stress ability of S. chuatsi in response to stress induced by re-feeding after starvation. These findings should prove useful for artificial breeding of S. chuatsi.
Genetic Structure and Genetic Diversity of the Endemic Korean Aucha Perch, Coreoperca herzi (Centropomidae), in Korea
Authors: Kim Kang-Rae , Kim Sang Ki , Sung Mu-Sung , Yu Jeong-Nam
Published: August 2023

The Korean endemic aucha perch, Coreoperca herzi, belongs to the family Centropomidae. Thus far, studies on C. herzi have focused on mitochondrial genomes, egg development, and early life history, while studies on their genetic diversity or genetic structure are lacking. We investigated these aspects in this study using mitochondrial DNA data. Haplotypes were divided into the Hangang River, Nakdonggang River, Geumgang River, and southwest region water system populations. A translocated population, the Yangyang Namdaechun Stream, was confirmed to have originated from the Hangang River water system population based on haplotype distribution and genetic structure results. The FST of the mitochondrial DNA indicated distinct genetic differentiation in the Hangang, Nakdonggang, Geumgang, and southwest regions. According to COI and analyses, the analysis of molecular variance revealed a higher variance in the four water system groups (98.41%) than in the southwest region water system versus the Hangang River water system (80.27%) groups. This study presents basic data for conservation by providing extensive information on the genetic diversity, genetic structure, and translocation population of C. herzi.
Hematological and Hematopoietic Analysis in Fish Toxicology—A Review
Authors: Witeska Małgorzata , Kondera Elżbieta , Bojarski Bartosz
Published: August 2023

Hematological analysis is commonly used to assess the physiological state of fish. It includes red blood cell parameters, white blood cell parameters, and the number of thrombocytes per blood volume unit. Hematological analysis is one of the basic tools (often accompanied by biochemical and histopathological analyses) to assess the influence of organic and inorganic substances on fish. It is, therefore, applicable in both ecotoxicology and pharmacotoxicology. The advantages of this research method are the lack of need for specialized laboratory equipment and low costs, and the limitations are the need for extensive experience among the personnel performing the tests. One of the recommended methods of supplementing routinely determined hematological parameters is assessing the cellular composition and activity of hematopoietic tissue. As there is very little scientific data available on the issue of the effects of xenobiotics on the cellular structure of fish head kidney hematopoietic tissue, filling this gap should be considered an urgent need. Therefore, we recommend conducting research with the simultaneous use of hematological and hematopoietic analysis as reliable and complementary methods of assessing the impact of toxic substances on fish.
Refining Stereotaxic Neurosurgery Techniques and Welfare Assessment for Long-Term Intracerebroventricular Device Implantation in Rodents
Authors: Pérez-Martín Ester , Coto-Vilcapoma Almudena , Castilla-Silgado Juan , Rodríguez-Cañón María , Prado Catuxa , Álvarez Gabriel , Álvarez-Vega Marco Antonio , Fernández-García Benjamín , Menéndez-González Manuel , Tomás-Zapico Cristina
Published: August 2023

Stereotaxic surgeries enable precise access to specific brain regions, being of particular interest for chronic intracerebroventricular drug delivery. However, the challenge of long-term studies at this level is to allow the implantation of drug storage devices and their correct intrathecal connection while guaranteeing animal welfare during the entire study period. In this study, we propose an optimized method for safe intrathecal device implantation, focusing on preoperative, intraoperative, and postoperative procedures, following the 3Rs principle and animal welfare regulations. Our optimized protocol introduces three main refinements. Firstly, we modify the dimensions of the implantable devices, notably diminishing the device-to-mouse weight ratio. Secondly, we use a combination of cyanoacrylate tissue adhesive and UV light-curing resin, which decreases surgery time, improves healing, and notably minimizes cannula detachment or adverse effects. Thirdly, we develop a customized welfare assessment scoresheet to accurately monitor animal well-being during long-term implantations. Taken together, these refinements positively impacted animal welfare by minimizing the negative effects on body weight, surgery-related complications, and anxiety-like behaviors. Overall, the proposed refinements have the potential to reduce animal use, enhance experimental data quality, and improve reproducibility. Additionally, these improvements can be extended to other neurosurgical techniques, thereby advancing neuroscience research, and benefiting the scientific community.
Plant Design for the Conversion of Plastic Waste into Valuable Chemicals (Alkyl Aromatics)
Authors: Alali Sabah A. S. , Aldaihani Meshal K. M. B. J. , Alanezi Khaled M.
Published: August 2023

The exponential increase in production and consumption of plastic has led to accumulation of plastic waste in the environment, resulting in detrimental impacts on human health and the natural environment. Plastic pollution not only stems from discarded plastics but also from the chemicals released during plastic production and decomposition. Various waste management strategies exist for plastic waste, including landfilling, recycling, conversion to liquid fuel, and upcycling. Landfilling, which is a prevalent method, contributes to long-term environmental degradation. Recycling is practiced worldwide, but its percentage remains low, particularly in regions like South Asia. Conversion to liquid fuel through pyrolysis has been explored as a viable solution, although commercialization faces challenges. Upcycling, which involves depolymerization and repolymerization, offers an avenue to recycle plastic waste into valuable chemicals, specifically focusing on high-density polyethylene (HDPE) and low-density polyethylene (LDPE). Currently, HDPE and LDPE make up 36% of all plastic trash by mass, but they have the potential to account for far more. When plastic waste is incinerated or buried in the earth, it generates carbon dioxide and heat, which pollute our environment. Depolymerization is a way to chemically recycle plastic waste into monomers, but this process requires a large amount of energy. Controlled partial depolymerization can transform PE into new, high-quality products at a temperature of more than 400 °C with or without a catalyst. In this study, we provide a novel approach for the conversion of plastic waste, particularly HDPE and LDPE, into valuable alkyl aromatics. By implementing controlled partial depolymerization, we propose a plant design capable of transforming plastic waste into high-quality chemicals. The design aims to optimize energy consumption, process efficiency, and product quality. The research findings contribute to sustainable plastic waste management and the reduction in environmental pollution caused by plastic waste.
Research on the Intelligent Auxiliary Design of Subway Station Building Space Based on Deep Learning
Authors: An Jiang , Zhang Jiuhong , Ma Mingxiao
Published: August 2023

In recent years, deep learning methods have been used with increasing frequency to solve architectural design problems. This paper aims to study the spatial functional layout of deep learning-assisted generation subway stations. Using the PointNet++ model, the subway station point cloud data are trained and then collected and processed by the author. After training and verification, the following conclusions are obtained: (1) the feasibility of spatial deep learning for construction based on PointNet++ in the form of point cloud data is verified; (2) the effectiveness of PointNet++ for the semantic segmentation and prediction of metro station point cloud information is verified; and (3) the results show that the overall 9:1 training prediction data have 60% + MIOU and 75% + accuracy for 9:1 training prediction data in the space of 20 × 20 × 20 and a block_size of 10.0. This paper combines the deep learning of 3D point cloud data with architectural design, breaking through the original status quo of two-dimensional images as research objects. From the dataset level, the limitation that research objects such as 2D images cannot accurately describe 3D space is avoided, and more intuitive and diverse design aids are provided for architects.
Parameterization of Entrainment Rate for Cumulus Clouds with WRF Simulation
Authors: Guo Xiaohao , Lin Huijuan , Zhu Jinyao , Wei Fenfen
Published: August 2023

By using Weather Research and Forecasting Model (WRF) to simulate a southwest vortex precipitation process, this work studies the correlations between entrainment rate (λ) and dynamical parameters in the cloud and further fit λ. We relate the probability density distribution (PDF) to the parameterization of λ and find that the greater the probability, the larger the slope of the logarithmic liner function. The slope of the log-linear fitting function in fitting decreases for developing and enhancing cumulus clouds, which is related to the increase in updraft motion and the decrease in λ. Then, we group clouds according to cloud top heights and calculate average λ and dynamic parameters, and the results indicate that when only one dynamic parameter is used, vertical wind velocity (w) is more suitable than buoyancy (B) to be used to fit λ. The fitting functions combing one single parameter and more parameters by principal components regression are compared with two traditional schemes, and we found that λ obtained by our fitting schemes are between the two traditional schemes. Because the principal component regression method takes into account the interaction between more dynamic factors and entrainment, the fitting function, including w and B, is suitable to be applied to fit λ in the parameterization scheme for cumulus clouds.
RGSB-UNet: Hybrid Deep Learning Framework for Tumour Segmentation in Digital Pathology Images
Authors: Zhao Tengfei , Fu Chong , Tie Ming , Sham Chiu-Wing , Ma Hongfeng
Published: August 2023

Colorectal cancer (CRC) is a prevalent gastrointestinal tumour with high incidence and mortality rates. Early screening for CRC can improve cure rates and reduce mortality. Recently, deep convolution neural network (CNN)-based pathological image diagnosis has been intensively studied to meet the challenge of time-consuming and labour-intense manual analysis of high-resolution whole slide images (WSIs). Despite the achievements made, deep CNN-based methods still suffer from some limitations, and the fundamental problem is that they cannot capture global features. To address this issue, we propose a hybrid deep learning framework (RGSB-UNet) for automatic tumour segmentation in WSIs. The framework adopts a UNet architecture that consists of the newly-designed residual ghost block with switchable normalization (RGS) and the bottleneck transformer (BoT) for downsampling to extract refined features, and the transposed convolution and 1 × 1 convolution with ReLU for upsampling to restore the feature map resolution to that of the original image. The proposed framework combines the advantages of the spatial-local correlation of CNNs and the long-distance feature dependencies of BoT, ensuring its capacity of extracting more refined features and robustness to varying batch sizes. Additionally, we consider a class-wise dice loss (CDL) function to train the segmentation network. The proposed network achieves state-of-the-art segmentation performance under small batch sizes. Experimental results on DigestPath2019 and GlaS datasets demonstrate that our proposed model produces superior evaluation scores and state-of-the-art segmentation results.
Multimodal Classification Framework Based on Hypergraph Latent Relation for End-Stage Renal Disease Associated with Mild Cognitive Impairment
Authors: Fu Xidong , Song Chaofan , Zhang Rupu , Shi Haifeng , Jiao Zhuqing
Published: August 2023

Combined arterial spin labeling (ASL) and functional magnetic resonance imaging (fMRI) can reveal more comprehensive properties of the spatiotemporal and quantitative properties of brain networks. Imaging markers of end-stage renal disease associated with mild cognitive impairment (ESRDaMCI) will be sought from these properties. The current multimodal classification methods often neglect to collect high-order relationships of brain regions and remove noise from the feature matrix. A multimodal classification framework is proposed to address this issue using hypergraph latent relation (HLR). A brain functional network with hypergraph structural information is constructed by fMRI data. The feature matrix is obtained through graph theory (GT). The cerebral blood flow (CBF) from ASL is selected as the second modal feature matrix. Then, the adaptive similarity matrix is constructed by learning the latent relation between feature matrices. Latent relation adaptive similarity learning (LRAS) is introduced to multi-task feature learning to construct a multimodal feature selection method based on latent relation (LRMFS). The experimental results show that the best classification accuracy (ACC) reaches 88.67%, at least 2.84% better than the state-of-the-art methods. The proposed framework preserves more valuable information between brain regions and reduces noise among feature matrixes. It provides an essential reference value for ESRDaMCI recognition.
Deep Drug Discovery of Mac Domain of SARS-CoV-2 (WT) Spike Inhibitors: Using Experimental ACE2 Inhibition TR-FRET Assay, Screening, Molecular Dynamic Simulations and Free Energy Calculations
Authors: Iqbal Saleem , Lin Sheng-Xiang
Published: August 2023

SARS-CoV-2 exploits the homotrimer transmembrane Spike glycoproteins (S protein) during host cell invasion. The Omicron XBB subvariant, delta, and prototype SARS-CoV-2 receptor-binding domain show similar binding strength to hACE2 (human Angiotensin-Converting Enzyme 2). Here we utilized multiligand virtual screening to identify small molecule inhibitors for their efficacy against SARS-CoV-2 virus using QPLD, pseudovirus ACE2 Inhibition -Time Resolved Forster/Fluorescence energy transfer (TR-FRET) Assay Screening, and Molecular Dynamics simulations (MDS). Three hundred and fifty thousand compounds were screened against the macrodomain of the nonstructural protein 3 of SARS-CoV-2. Using TR-FRET Assay, we filtered out two of 10 compounds that had no reported activity in in vitro screen against Spike S1: ACE2 binding assay. The percentage inhibition at 30 µM was found to be 79% for “Compound F1877-0839” and 69% for “Compound F0470-0003”. This first of its kind study identified “FILLY” pocket in macrodomains. Our 200 ns MDS revealed stable binding poses of both leads. They can be used for further development of preclinical candidates.
Post-COVID-19 Symptoms in Adults with Asthma—Systematic Review
Authors: Kaszuba Marek , Madej Natalia , Pilinski Rafal , Sliwka Agnieszka
Published: August 2023

Background: Research on the longer-term sequelae of COVID-19 in patients with asthma is limited. Objective: To assess the frequency and severity of long-term symptoms of COVID-19 in the population of asthma patients. Methods: A systematic review of the published literature was conducted in accordance with the recommendations of the PRISMA statement. EMBASE, MEDLINE/PubMed, Web of Science, CINAHL, and Scopus Scholar were searched for terms related to asthma and post or long COVID-19, and for systematic reviews related to specific questions within our review, up to June 2022. Results: Data from 9 references publications included in the review were extracted. A total of 1466 adult asthmatic patients with COVID-19 infection were described in all the publications mentioned above. Of the long-term symptoms reported after COVID-19, patients indicated: lower respiratory symptoms, fatigue, cognitive symptoms, psychological problems, and other such as skin rashes, gastrointestinal disorders, tachycardia, palpitations, ocular disorders, ageusia/hypogeusia, anosmia/hyposmia, and poor sleep quality. These symptoms in similar intensity were observed in the comparison groups without a diagnosis of asthma. Conclusions: The published data neither confirm nor deny that long-term COVID-19 symptoms in patients with asthma diagnosis are different in strength and frequency from patients without asthma diagnosis. To indicate associations between asthma and COVID-19 infection and severity, as well as the frequency of long-term symptoms of COVID-19, more longitudinal research is needed in chronic asthma patients with different phenotypes, intensity of treatment, and degree of asthma control.
Fault Diagnosis of Planetary Gearbox Based on Dynamic Simulation and Partial Transfer Learning
Authors: Song Mengmeng , Xiong Zicheng , Zhong Jianhua , Xiao Shungen , Ren Jihua
Published: August 2023

To address the problem of insufficient real-world data on planetary gearboxes, which makes it difficult to diagnose faults using deep learning methods, it is possible to obtain sufficient simulation fault data through dynamic simulation models and then reduce the difference between simulation data and real data using transfer learning methods, thereby applying diagnostic knowledge from simulation data to real planetary gearboxes. However, the label space of real data may be a subset of the label space of simulation data. In this case, existing transfer learning methods are susceptible to interference from outlier label spaces in simulation data, resulting in mismatching. To address this issue, this paper introduces multiple domain classifiers and a weighted learning scheme on the basis of existing domain adversarial transfer learning methods to evaluate the transferability of simulation data and adaptively measure their contribution to label predictor and domain classifiers, filter the interference of unrelated categories of simulation data, and achieve accurate matching of real data. Finally, partial transfer experiments are conducted to verify the effectiveness of the proposed method, and the experimental results show that the diagnostic accuracy of this method is higher than existing transfer learning methods.