bluuebunny/crossref_metadata_2025 huggingface dataset:
“I Did My Own Research”: Overconfidence, (Dis)trust in Science, and Endorsement of Conspiracy Theories
Authors: Vranic Andrea , Hromatko Ivana , Tonković Mirjana
Published: July 2022

Epistemically suspect beliefs, such as endorsement of conspiracy theories or pseudoscientific claims, are widespread even among highly educated individuals. The phenomenon of conspiratorial thinking is not new, yet the COVID-19 pandemic, causing a global health crisis of an unprecedented scale, facilitated the emergence and rapid spread of some rather radical health-related pseudoscientific fallacies. Numerous correlates of the tendency to endorse conspiracy theories have already been addressed. However, many of them are not subject to an intervention. In this study, we have tested a model that includes predictors ranging from stable characteristics such as demographics (gender, age, education, and size of the place of residence), less stable general traits such as conservatism and overconfidence in one’s own reasoning abilities, to relatively changeable worldviews such as trust in science. A hierarchical regression analysis (N= 859 participants) showed that included predictors explained a total of 46% of the variance of believing in COVID-19 conspiracy theories, with only gender, overconfidence, and trust in science yielding significance. Trust in science was the strongest predictor, implying that campaigns aimed at enhancing public trust in both science as a process, and scientists as individuals conducting it, might contribute to the reduction in susceptibility to pseudoscientific claims. Furthermore, overconfidence in one’s own reasoning abilities was negatively correlated with an objective measure of reasoning (syllogisms test) and positively correlated with the endorsement of conspiracy theories, indicating that the so-called Dunning-Kruger effect plays a role in pseudoscientific conspiratorial thinking regarding COVID-19.
The Physiological Effects of Air Pollution: Particulate Matter, Physiology and Disease
Authors: Pryor Jack T. , Cowley Lachlan O. , Simonds Stephanie E.
Published: July 2022

Nine out of 10 people breathe air that does not meet World Health Organization pollution limits. Air pollutants include gasses and particulate matter and collectively are responsible for ~8 million annual deaths. Particulate matter is the most dangerous form of air pollution, causing inflammatory and oxidative tissue damage. A deeper understanding of the physiological effects of particulate matter is needed for effective disease prevention and treatment. This review will summarize the impact of particulate matter on physiological systems, and where possible will refer to apposite epidemiological and toxicological studies. By discussing a broad cross-section of available data, we hope this review appeals to a wide readership and provides some insight on the impacts of particulate matter on human health.
Consumers' Knowledge, Attitudes, and Practices Toward Calorie Labeling in Riyadh City, Saudi Arabia: A Cross-Sectional Assessment
Authors: AlShehri Nouf M. , AlMarzooqi Mezna A.
Published: July 2022

Background

Menu calorie labeling is a useful means to encourage consumers to be informed about healthy eating and food choices. It is projected as an innovative method that will change the food environment and increases consumers' awareness of calories.

Objective

This study aims to determine the consumer's knowledge, attitudes, and practices toward menu calorie labeling in Saudi Arabia.

Methods

This is a descriptive cross-sectional study involving 435 consumers in Saudi Arabia. The participants filled out an online electronic survey questionnaire that assesses the demographic factors, knowledge, attitudes, practices, and barriers toward menu calorie labeling. Logistic regression was performed to determine the predictor of attitudes of consumers toward menu calorie labeling.

Results

Of those 435 consumers, 50.1% were men, 33% were in the age group of 30–39, and 49.4% had a bachelor's degree. The majority of the participants reported that they can understand the calorie labels that were presented on the menus of the restaurants (N = 365, 83.9%). A high percentage of participants reported that calorie labeling encourages them to choose foods with a smaller number of calories (N = 387, 89%) and supported the posting of calorie content next to the price of the food items on the menus (N = 405, 93.1%). Barriers to using calorie labels were time-consuming and low-calorie food items are usually costly. Gender and educational attainment were found significantly associated with consumers' knowledge while marital status and BMI level were found significantly associated with attitudes and practices to using calorie labels (p < 0.05).

Conclusion

Overall, the participants had adequate knowledge and positive attitudes about menu calorie labeling in Saudi Arabia. Menu calorie labeling may be a useful policy tool for promoting healthy eating habits and appropriate caloric consumption.
The Diagnostic Value of Mitochondrial Mass of Peripheral T Lymphocytes in Early Sepsis
Authors: Pang Ling-Xiao , Cai Wen-Wei , Chen Lue , Fu Jin , Xia Chun-Xiao , Li Jia-Yan , Li Qian
Published: July 2022

Background

Studies have shown that lymphocyte dysfunction can occur during the early stages of sepsis and that cell dysfunction is associated with mitochondrial dysfunction. Therefore, quantifying the mitochondrial function of lymphocytes in patients with sepsis could be valuable for the early diagnosis of sepsis.

Methods

Seventy-nine patients hospitalized from September 2020 to September 2021 with Sepsis-3 were retrospectively analyzed and subsequently compared with those without sepsis.

Results

Univariate analysis showed statistical differences between the data of the two groups regarding age, neutrophil/lymphocyte, procalcitonin (PCT), C-reactive protein, total bilirubin, serum creatinine, type B natriuretic peptide, albumin, prothrombin time, activated partial thromboplastin time, lactic acid, single-cell mitochondrial mass (SCMM)-CD3, SCMM-CD4, SCMM-CD8, and Acute Physiology and Chronic Health Evaluation II score (P < 0.05). Multivariate logistic regression analysis performed on the indicators mentioned above demonstrated a statistical difference in PCT, lactic acid, SCMM-CD4, and SCMM-CD8 levels between the two groups (P < 0.05). The receiver operating characteristic curves of five models were subsequently compared [area under the curve: 0.740 (PCT) vs. 0.933 (SCMM-CD4) vs. 0.881 (SCMM-CD8) vs. 0.961 (PCT + SCMM-CD4) vs. 0.915 (PCT+SCMM-CD8), P < 0.001].

Conclusion

SCMM-CD4 was shown to be a better diagnostic biomarker of early sepsis when compared with the traditional biomarker, PCT. Furthermore, the value of the combination of PCT and SCMM-CD4 in the diagnosis of early sepsis was better than that of SCMM-CD4 alone.
Losartan Attenuates Radiation-Induced Damage on Testes and Accelerates Tubular Regeneration
Authors: Santos Lais L. Manção dos , Alves Marco G. , Chies Agnaldo Bruno , Spadella Maria Angélica
Published: July 2022

Male germ cells are particularly susceptible to radiation; infertility being a common consequence after radiotherapy as it impairs spermatogenesis. This study aimed to test whether treatment with losartan (LOS), a selective antagonist of angiotensin II receptor subtype 1 (AT1R), can prevent or attenuate the acute and long-term radiation-induced damage to testes. Wistar rats were randomly distributed into six groups, three of which were studied on day 2 after irradiation: control (CTRL 2), irradiated non-treated (IR 2), and irradiated and treated with LOS (IRLOS 2); and three other groups that were studied on day 60 after irradiation: control (CTRL 60), irradiated non-treated (IR 60), and irradiated and treated with LOS (IRLOS 60). Seven consecutive days before and on the day of irradiation with 2.5 Gy directly administered in the scrotum, the animals were treated with LOS (34 mg/kg/two times/day). This treatment was continued 2 or 60 days after irradiation. The sperm quality was assessed from epididymis cauda. In addition, the testes were submitted to histopathological and morphometric-stereological analysis as well as the proliferating cell nuclear antigen (PCNA) quantification. Serum FSH and LH and plasma testosterone levels were also determined. The data obtained 2 days after the irradiation showed germ cell apoptosis, formation of vacuoles in the seminiferous epithelium, sloughing of germ cells into the lumen, and retention and phagocytosis of step-19 spermatids in Sertoli basal cytoplasm. The treatment with LOS in this period did not prevent or attenuate a radio-induced damage to the testes, illustrating that this drug does not protect against apoptosis derived from direct effects of radiation. On the other hand, 60 days after exposure, the data evidenced the deleterious effects of ionizing radiation on the testes as decreasing of testicular, epididymal, and seminal vesicle masses; tubular atrophy; reduction of cellular proliferation; and loss of germ cells. LOS was able to prevent some of those deleterious effects, promoting improvements in seminal vesicle mass, sperm vitality, plasma testosterone levels, vacuole number, and cell proliferation. In conclusion, inhibition of the AngII/AT1R axis by LOS is effective in protecting the indirect/delayed radiation damage resulting from oxidative stress established in the tissue.
Dietary Patterns and Dietary Recommendations Achievement From Latin American College Students During the COVID-19 Pandemic Lockdown
Authors: Murillo Ana Gabriela , Gómez Georgina , Durán-Agüero Samuel , Parra-Soto Solange Liliana , Araneda Jacqueline , Morales Gladys , Ríos-Castillo Israel , Carpio-Arias Valeria , Cavagnari Brian M. , Nava-González Edna J. , Bejarano-Roncancio Jhon Jairo , Núñez-Martínez Beatriz , Cordón-Arrivillaga Karla , Meza-Miranda Eliana Romina , Mauricio-Alza Saby , Landaeta-Díaz Leslie
Published: July 2022

This study aimed to compare the diet quality of different dietary patterns among college students from Latin American countries, including vegetarians, vegans, and omnivores during the COVID-19 pandemic. A cross-sectional, observational, multicenter study was conducted including a non- probabilistic sample of university students from 10 countries. University students were invited to participate in the study through social network platforms. Participants were self-reported to have followed a specific dietary pattern; either the Prudent diet, Western diet, Ovo-dairy-vegetarian diet, Fish-vegetarian diet, Strict vegetarian diet (vegan) or other. The last three patterns (vegetarians and vegans) were grouped as following a plant-based diet. A self-assessment survey was used to evaluate healthy eating habits using a questionnaire with values between 1 (do not consume) and 5 (consume) for a total of 9–45 points (higher values represent better eating habits). Unhealthy habits were assessed with nine questions. A total of 4,809 students filled out the questionnaire, and the majority of them were females (73.7%). A high percentage have been in lockdown for more than 5 months and were in lockdown when the survey was released. 74.3% were self-reported to follow a prudent diet, while 11.4% reported following a western dietary pattern and 8.8% a plant-based diet. When compliance with healthy and unhealthy dietary habits was analyzed, although all groups had low compliance, the plant-based diet group (56.09 ± 6.11) performed better than the Western diet group (48.03 ± 5.99). The total diet quality score was significantly higher for plant-based diet followers, who also tended to better achieve the recommendations than omnivorous students, especially the ones following a western diet. These results present evidence that young adults such as college-aged students have unhealthy dietary habits. However, the ones who follow a plant-based diet such as vegetarians and vegans exhibit better scores and healthier dietary conducts.
Polypoid arteriovenous malformation of the rectum: A case report
Authors: Krizzuk Dimitri , Cotesta Maria , Galiffa Giampaolo , Peluso Ilaria , Falbo Francesco , Biancucci Andrea , Puscio Sara , Michelotto Chiara , Pasecinic Carolina , Montalto Gioacchino Maria , Sammartino Francesco
Published: July 2022

Background

Intestinal arteriovenous malformation is an abnormal connection between arteries and veins that bypasses the capillary system and may be a cause of significant lower gastrointestinal bleeding. On endoscopy, arteriovenous malformations are usually flat or elevated, bright red lesions. Overall, rectal localization of arteriovenous malformations is rare. The same may be said about polypoid shape arteriovenous malformations. Herein, we present a case of a large rectal polypoid arteriovenous malformations.

Methods

Clinical, diagnostic, and treatment modalities of the patient were reviewed. Pre- and post-operative parameters were collected and analyzed. The clinical English literature is also reviewed and discussed

Results

A 60-year-old female patient was admitted to our emergency department for rectorrhagia and anemia. Rectoscopy revealed a polypoid lesion in the rectum and the biopsy showed fibrosis, necrosis areas, and hyperplastic glands. A total body contrast-enhanced computed tomography (CT) was performed revealing a parietal pseudonodular thickening with concentric growth and contrast enhancement, extending for about 53 mm. The mass wasn't removed endoscopically due to concentric growth, sessile implant, and submucosal nature. The patient underwent an uneventful laparoscopic anterior rectal resection. The postoperative hospitalization was free of complications. Histology showed the presence of a polypoid AVM composed of dilated arteries, veins, capillaries, and lymphatics, engaging the submucosa, muscularis, and subserosa layer.

Conclusion

After a review of the current English literature, we found only one case of rectal polypoid AVM. The scarcity of documented cases encumbers optimal diagnostic and treatment approaches.
Changes in Gallbladder Contractile Function and its Influencing Factors After Minimally Invasive Gallbladder-Preserving Surgery for Cholecystitis With Incarcerated Gallstones
Authors: Ai Xiang-Nan , Wang Teng-Fei , Zhang Qiang , Ouyang Cai-Guo , Wu Zhen-Yu
Published: July 2022

Background

Cholecystitis with incarcerated gallstones (CIG) is a type of acute abdomen in the field of hepatobiliary surgery. Whether gallbladder-preserving surgery (GPS) can be performed to treat it, however, depends on the improvement of gallbladder contractile function. The present study aimed to investigate the changes in gallbladder contractile function and its influencing factors after minimally invasive GPS for CIG.

Methods

A total of 95 patients with CIG treated in the Aerospace Center Hospital between May 2017 and May 2019 were enrolled as the study subjects. All patients received minimally invasive GPS. The patients' operation-related conditions (including stone removal success rate, duration of surgery, intraoperative blood loss, etc.), changes in gallbladder contractile function, and influencing factors of GPS were analyzed.

Results

Among the 95 patients included in the study, the success rate of stone removal was 100%, the duration of surgery was 76.0 ± 26.5 min, and the intraoperative blood loss was 10.17 ± 4.43 ml. The rate of good gallbladder contractile function at one and two years after surgery was significantly higher than before surgery (P < 0.05). Age, duration of surgery, stone recurrence, and diabetes were the independent risk factors for postoperative gallbladder contractile function (P < 0.05).

Conclusion

Minimally invasive GPS for patients with CIG has a good curative effect. The changes in gallbladder contractile function after the surgery are influenced by many factors.
Exploring the scope of 4sb and 12a lymph node dissection for cT2-4 lower third gastric cancer: Study protocol for a prospective cohort trial
Authors: Zhang Haiqiao , Zheng Zhi , Liu Xiaoye , Cai Jun , Yin Jie , Zhang Jun
Published: July 2022

Background

Currently, the extent of 4sb and 12a lymph node dissection is not clear and is based on the personal understanding of the surgeon. It may result in damage to the splenic artery and portal vein, leading to surgical complications. Therefore, this study aims to explore the scope of 4sb and 12a lymph node dissection in cT2-4 lower third gastric cancer.

Methods

This is an ongoing prospective cohort trial. The total sample size required for the trial (March 2022 to February 2025) is approximately 524 patients. The participants are divided into the experimental (4sb first branch and 12a anterior lymphadenectomy) or control groups (traditional 4sb and 12a lymphadenectomy). Electronic data capture systems will be used to collect demographic, laboratory test, auxiliary examination, operation, postoperative condition, postoperative pathology, and follow-up data. The primary outcome is the 12a lymph node metastatic rate. Secondary outcomes include the pathology (consisting of the 4sb lymph node metastatic rate, the number of 4sb lymph nodes dissected, the number of 12a lymph nodes dissected and tumor pathological staging), a safety evaluation index (consisting of complications and mortality ≤30 days after surgery), an efficacy evaluation (consisting of operation data and postoperative recovery status), and follow-up data (consisting of 3-year or 5-year disease-free survival and overall survival).

Discussion

By exploring the scope of 4sb and 12a lymph node dissection on the premise of ensuring radical cure of the tumor, the operation is simplified, the operation time is shortened, the damage of important blood vessels is reduced, the intraoperative and postoperative complications are reduced, and the patient recovers as soon as possible. Our study is a prospective exploration of the pathology, safety, efficacy, and prognosis of the new and traditional methods of 4sb and 12a lymph node dissection.

Trial registration

Chinese Clinical Trial Registry, ChiCTR2200057698 (registration date: March 15, 2022).
Analysis of the Solidification Process of Metal Alloys Under Microgravity Conditions
Authors: Fredriksson Hasse
Published: July 2022

The solidification of metal alloys under low gravity conditions mainly deviates in four physical properties compared with samples solidified on earth. The coarseness of the structure and the solidification temperature increase. The latent heat and the solubility of alloying elements in solids are changed. Experimental results are presented and analyzed in order to find a unified theoretical understanding. The differences in the measured quantities between experiments performed in space and on earth were calculated and are presented in this article. Kinetic, thermodynamic, and thermophysical relations were used to analyze those values. The change in the melting point was found to be a result of an increase in the vibrational amplitude of the atoms in the solid. The increase in the latent heat results from an increase in the vibration of atoms in the liquid. The changes in the solubility are a result of an increase in heat of fusion of the alloying element. Furthermore, the increase in the coarseness of the structure is explained as an increase in the atom’s vibration. The analysis highlights that the atom’s vibration increases with decreasing gravity; especially, the amplitude will increase. The explanation for this is given by a decrease in the binding energy between the atoms with decreasing gravity. The decrease in binding energy for liquids is larger than for solids.
Genetic Characterization of a Novel Bovine Rotavirus A G37P[52] Closely Related to Human Strains
Authors: Singh Vikash K. , Neira Victor , Brito Barbara , Ariyama Naomi , Sturos Matt , Mor Sunil K.
Published: July 2022

Bovine rotavirus A (boRVA) strains are common causative agents of diarrhea in calves, resulting in economic losses to the beef and dairy industry. Importantly, this virus has a zoonotic relevance due to its ability to reassort with human rotaviruses. In this study, fecal samples were collected from three calves with diarrhea during an outbreak on a dairy farm. The genetic material of boRVA was detected by real-time reverse transcription PCR (rtPCR) in two samples. Then the virus in one of these positive samples was identified as a novel boRVA genotype closely related with human rotavirus strains mainly from the USA based on whole-genome characterization. However, we consider the novel boRVA as the etiological agent of the outbreak due to the lesions associated with a rotavirus infection. Further studies are necessary to clarify the evolutionary advantages that novel rotavirus genotypes may have.
Decision Making in the Context of Paediatric Solid Organ Transplantation Medicine
Authors: Prüfe Jenny
Published: July 2022

This manuscript aims to outline ethical, legal, and psychosocial key situations in the context of transplantation under special consideration of children. Besides being particularly vulnerable, children as minors by law are not meant to consent to whatever medical procedure is applied to them. Rather their next-of-kin and medical staff are to decide. In the context of transplantation thus it needs to be reflected under which circumstances a child can become an organ donor or receive an organ. This essay will not provide answers to current questions in transplantation medicine but provide an overview of present European practices and juxtapose divergent courses of action which are based on an assumed similar social-cultural background. Data are drawn from a systematic comparison of the various national organ transplantation laws and tissue acts. Ethical reflections are based on a thematically targeted literature search using PubMed Central and PhilPapers databases.
Characterisation of Pineapple Cultivars under Different Storage Conditions Using Infrared Thermal Imaging Coupled with Machine Learning Algorithms
Authors: Mohd Ali Maimunah , Hashim Norhashila , Abd Aziz Samsuzana , Lasekan Ola
Published: July 2022

The non-invasive ability of infrared thermal imaging has gained interest in various food classification and recognition tasks. In this work, infrared thermal imaging was used to distinguish different pineapple cultivars, i.e., MD2, Morris, and Josapine, which were subjected to different storage temperatures, i.e., 5, 10, and 25 °C and a relative humidity of 85% to 90%. A total of 14 features from the thermal images were obtained to determine the variation in terms of image parameters among the different pineapple cultivars. Principal component analysis was applied for feature reduction in order to prevent any effect of significant difference between the selected features. Several types of machine learning algorithms were compared, including linear discriminant analysis, quadratic discriminant analysis, support vector machine, k-nearest neighbour, decision tree, and naïve Bayes, to obtain the best performance for the classification of pineapple cultivars. The results showed that support vector machine achieved the best performance from the combination of optimal image parameters with the highest classification rate of 100%. The ability of infrared thermal imaging coupled with machine learning approaches can be potentially used to distinguish pineapple cultivars, which could enhance the grading and sorting processes of the fruit.
CARVER+Shock and Business Process Management in Improving Food Safety of Primary Production
Authors: Wysokińska-Senkus Aneta , Górna Justyna , Kaźmierczak Magdalena , Mielcarek Paweł , Senkus Piotr
Published: July 2022

Context: Food safety is essential for every human. It determines public health, nutrition, elimination of hunger, and the promotion of sustainable agriculture. It is crucial for sustainable production, consumption, and international food trade. Ensuring food safety is the fundamental challenge of the 21st century. Food safety is often related to food defense and includes protection against intentional contamination with various chemical, biological, or other harmful substances. By introducing food protection tools and methods, any company reduces risk and creates an opportunity to generate more significant and reliable profits and improved production for society. One such method could be the CARVER+Shock. The method is an offensive targeting prioritization tool that has been adapted for use in the food sector. Objective: The article aims to present the experience of the first implementation of CARVER+Shock in a Polish primary production company, to improve the approach to food safety and food defense. Methods: The article is a case study. Descriptive analysis was performed to analyze legal acts and safety management standards in food defense. The authors used the CARVER+Shock expert method to estimate companies’ vulnerability. CARVER is an acronym for Criticality, Accessibility, Recoverability, Vulnerability, Effect, Recognizability. The visualization and risk analysis were made using business process management and business process modeling (VACD diagram) Results and conclusions: Primary production enterprise dealing with the cultivation and confectioning of the pre-treatment and sale of peeled onions for further processing purposes was examined. Five essential stages of the production process were assessed, and risks were assigned. Recognizability and criticality turned out to be the most crucial attribute of CARVER+Shock. Overall, the study showed that the company was not fully prepared for the threat posed by food terrorism. The organization did not have any procedures describing how to proceed during deliberate attacks. In addition, workers had low awareness of food defense throughout the food chain. Based on these conclusions, several detailed improvement actions were formulated. The results obtained from the pioneering application of the CARVER+Shock method for a Polish primary production company may constitute a benchmark for other sectors of the food industry, both domestically and abroad. Significance: The article describes the results of the first Polish attempts to use CARVER+Shock and business process management to improve the approach to food safety in a primary production enterprise.
Stimbiotic Supplementation Alleviates Poor Performance and Gut Integrity in Weaned Piglets Induced by Challenge with E. coli
Authors: Song DongCheol , Lee JiHwan , Kwak WooGi , Song MinHo , Oh HanJin , Kim YongJu , An JaeWoo , Chang SeYeon , Go YoungBin , Cho HyunAh , Kim HyeunBum , Cho JinHo
Published: July 2022

The aim of this study was to investigate the effects of stimbiotic (STB), a xylanase and xylo-oligosaccharide complex. A total of 36 male weaned pigs with initial body weights of 8.49 ± 0.10 kg were used in a 3-week experiment. The experiment was conducted in a 2 × 3 factorial arrangement (six replicates/treatment) of treatments consisting of two levels of challenge (challenge and non-challenge) and three levels of STB (0, 0.5, and 1 g/kg diet). Supplementations STB 0.5 g/kg (STB5) and STB 1 g/kg (STB10) improved the G:F (p = 0.04) in piglets challenged with STEC. STB supplementation, which also decreased (p < 0.05) the white blood cells, neutrophils, lymphocytes, and expression levels of tumor necrosis factor-alpha and interleukin-6. Supplementations STB5 and STB10 improved (p < 0.01) the lymphocytes and neutrophils in piglets challenged with STEC on 14 dpi. Additionally, supplementations STB5 and STB10 improved (p < 0.01) the tumor necrosis factor-alpha in piglets challenged with STEC on 3 dpi. Supplementations STB5 and STB10 also improved the villus height-to-crypt depth ratio (p < 0.01) in piglets challenged with STEC. Supplementation with STB reduced (p < 0.05) the expression levels of calprotectin. In conclusion, STB could alleviate a decrease of the performance, immune response, and inflammatory response induced by the STEC challenge.
Emerging Computational Approaches for Antimicrobial Peptide Discovery
Authors: Agüero-Chapin Guillermin , Galpert-Cañizares Deborah , Domínguez-Pérez Dany , Marrero-Ponce Yovani , Pérez-Machado Gisselle , Teijeira Marta , Antunes Agostinho
Published: July 2022

In the last two decades many reports have addressed the application of artificial intelligence (AI) in the search and design of antimicrobial peptides (AMPs). AI has been represented by machine learning (ML) algorithms that use sequence-based features for the discovery of new peptidic scaffolds with promising biological activity. From AI perspective, evolutionary algorithms have been also applied to the rational generation of peptide libraries aimed at the optimization/design of AMPs. However, the literature has scarcely dedicated to other emerging non-conventional in silico approaches for the search/design of such bioactive peptides. Thus, the first motivation here is to bring up some non-standard peptide features that have been used to build classical ML predictive models. Secondly, it is valuable to highlight emerging ML algorithms and alternative computational tools to predict/design AMPs as well as to explore their chemical space. Another point worthy of mention is the recent application of evolutionary algorithms that actually simulate sequence evolution to both the generation of diversity-oriented peptide libraries and the optimization of hit peptides. Last but not least, included here some new considerations in proteogenomic analyses currently incorporated into the computational workflow for unravelling AMPs in natural sources.
Structural Design and Lubrication Properties under Different Eccentricity of Magnetic Fluid Bearings
Authors: Wang Ao , Pan Jiabao , Wu Huaibiao , Ye Jin
Published: July 2022

As a lubricant, the viscosity of the magnetic fluid changes with the external magnetic field, which improves the bearing capacity of the oil film and hence the lubrication effect, and has a promising application in bearings. Based on the Roelands viscosity theory, the Shliomis model is used to derive the viscous temperature, viscous pressure, and magnetic viscosity characteristics of magnetic fluids under the influence of an applied magnetic field, and further proposes a structural model of magnetic fluid lubricated bearings to investigate the pressure, temperature and magnetic intensity distribution of magnetic fluids under different eccentricity conditions. The results show that the viscosity of the magnetic fluid decreases exponentially with increasing temperature, rises linearly with increasing pressure, and increases and stabilizes with increasing magnetic induction strength. Because the minimum film thickness point is the dividing point between the convergent wedge and the dispersed wedge, the pressure distribution of the lubricant film separates high pressure from low pressure at the minimum film thickness, and the differential pressure increases with the increase in eccentricity. The temperature distribution of the high-temperature zone is mainly distributed in the middle of the film, and the minimum film thickness zone and the maximum temperature increases with the increase in eccentricity. The magnetic intensity distribution of the strong magnetic field is mainly concentrated in the minimum film thickness zone, and the magnetic induction intensity increases with the increase in eccentricity. The results of this study have certain research significance for solving the problem of the poor lubrication effect of bearing lubricant due to high temperature.
Would Forest Regrowth Compensate for Climate Change in the Amazon Basin?
Authors: Haghtalab Nafiseh , Moore Nathan , Nejadhashemi Pouyan
Published: July 2022

Following potential reforestation in the Amazon Basin, changes in the biophysical characteristics of the land surface may affect the fluxes of heat and moisture behavior. This research examines the impacts of potential tropical reforestation on surface energy and moisture budgets, including precipitation and temperature. The study is novel in that while most studies look at the opposite driver (deforestation), this one examines the impact of potential forest rehabilitation on atmospheric behavior using WRF.V3.9 (weather research and forecast model). We found that forest rehabilitation across the Amazon Basin can make the atmosphere cooler with more moisture and latent heat (LH), especially during May-November. For instance, the mean seasonal temperature decreased significantly by about 1.2 °C, indicating the cooling effects of reforestation. Also, the seasonal precipitation increased by 5 mm/day in reforested areas. By reforestation, the mean monthly LH also increased as much as 50 W m−2 in August in certain areas, while available moisture to the atmosphere increased by 27%, indicating possible causal mechanisms between increased LH and precipitation and emphasizing the mechanisms that were identified between the onset of the wet season and forest cover. Therefore, it is likely that forest regrowth across the basin leads to, if not reverses regional climate change, at least slowing down the rate of changes in the climate.
Mineral Identification Based on Deep Learning Using Image Luminance Equalization
Authors: Zhang Junyu , Gao Qi , Luo Hailin , Long Teng
Published: July 2022

Mineral identification is an important part of geological research. Traditional mineral identification methods heavily rely on the identification ability of the identifier and external instruments, and therefore require expensive labor expenditures and equipment capabilities. Deep learning-based mineral identification brings a new solution to the problem, which not only saves labor costs, but also reduces identification errors. However, the accuracy of existing recognition efforts is often affected by various factors such as Mohs hardness, color, picture scale, and especially light intensity. To reduce the impact of light intensity on recognition accuracy, we propose an efficient deep learning-based mineral recognition method using the luminance equalization algorithm. In this paper, we first propose a new algorithm combining histogram equalization (HE) and the Laplace algorithm, and use this algorithm to process the luminance of the identified samples, and finally use the YOLOv5 model to identify the samples. The experimental results show that our method achieves 95.6% accuracy for the identification of 50 common minerals, achieving a luminance equalization-based deep learning mineral identification method.
Deep-Learning Model Selection and Parameter Estimation from a Wind Power Farm in Taiwan
Authors: Lin Wen-Hui , Wang Ping , Chao Kuo-Ming , Lin Hsiao-Chung , Yang Zong-Yu , Lai Yu-Huang
Published: July 2022

Deep learning networks (DLNs) use multilayer neural networks for multiclass classification that exhibit better results in wind-power forecasting applications. However, improving the training process using proper parameter hyperisations and techniques, such as regularisation and Adam-based optimisation, remains a challenge in the design of DLNs for processing time-series data. Moreover, the most appropriate parameter for the DLN model is to solve the wind-power forecasting problem by considering the excess training algorithms, such as the optimiser, activation function, batch size, and dropout. Reinforcement learning (RN) schemes constitute a smart approach to explore the proper initial parameters for the developed DLN model, considering a balance between exploration and exploitation processes. Therefore, the present study focuses on determining the proper hyperparameters for DLN models using a Q-learning scheme for four developed models. To verify the effectiveness of the developed temporal convolution network (TCN) models, experiments with five different sets of initial parameters for the TCN model were determined by the output results of Q-learning computation. The experimental results showed that the TCN accuracy for 168 h wind power prediction reached a mean absolute percentage error of 1.41%. In evaluating the effectiveness of selection of hyperparameters for the proposed model, the performance of four DLN-based prediction models for power forecasting—TCN, long short-term memory (LSTM), recurrent neural network (RNN), and gated recurrence unit (GRU) models—were compared. The overall detection accuracy of the TCN model exhibited higher prediction accuracy compared to canonical recurrent networks (i.e., the GRU, LSTM, and RNN models).
AAQAL: A Machine Learning-Based Tool for Performance Optimization of Parallel SPMV Computations Using Block CSR
Authors: Ahmed Muhammad , Usman Sardar , Shah Nehad Ali , Ashraf M. Usman , Alghamdi Ahmed Mohammed , Bahadded Adel A. , Almarhabi Khalid Ali
Published: July 2022

The sparse matrix–vector product (SpMV), considered one of the seven dwarfs (numerical methods of significance), is essential in high-performance real-world scientific and analytical applications requiring solution of large sparse linear equation systems, where SpMV is a key computing operation. As the sparsity patterns of sparse matrices are unknown before runtime, we used machine learning-based performance optimization of the SpMV kernel by exploiting the structure of the sparse matrices using the Block Compressed Sparse Row (BCSR) storage format. As the structure of sparse matrices varies across application domains, optimizing the block size is important for reducing the overall execution time. Manual allocation of block sizes is error prone and time consuming. Thus, we propose AAQAL, a data-driven, machine learning-based tool that automates the process of data distribution and selection of near-optimal block sizes based on the structure of the matrix. We trained and tested the tool using different machine learning methods—decision tree, random forest, gradient boosting, ridge regressor, and AdaBoost—and nearly 700 real-world matrices from 43 application domains, including computer vision, robotics, and computational fluid dynamics. AAQAL achieved 93.47% of the maximum attainable performance with a substantial difference compared to in practice manual or random selection of block sizes. This is the first attempt at exploiting matrix structure using BCSR, to select optimal block sizes for the SpMV computations using machine learning techniques.
Nonlinear Impact Force Reduction of Layered Polymers with the Damage-Trap Interface
Authors: Islam Md Shariful , Xu Luoyu Roy
Published: July 2022

In this paper, a damage-trap material interface design of polymeric materials was proposed. Towards that, baseline and layered Polymethyl methacrylate (PMMA) and Polycarbonate specimens were fabricated with a Loctite 5083 adhesive layer between the interfaces. Out-of-plane impact experiments were conducted and found that the maximum impact force was reduced in layered polymers with so-called “damage-trap material interfaces”. At the impact energy of 20 J, the maximum impact force of the layered PMMA specimens with the 5083 adhesive was reduced by 60% compared to the identical specimens without any adhesive bonding. For the layered Polycarbonate specimens with the 5083 adhesive bonding, the maximum impact force was reduced by 20% and energy absorption was increased by 130%. Simplified contact mechanics analysis showed that the low Young’s modulus of the 5083 adhesive layers was a key parameter in reducing impact force and damage. Therefore, a simple and effective way to design layered materials with improved impact resistance was proposed.
Data Naming Mechanism of LEO Satellite Mega-Constellations for the Internet of Things
Authors: Xia Mingfei , Hu Shengbo , Luo Hongqiu , Yan Tingting , Shi Yanfeng
Published: July 2022

The low earth orbit (LEO) mega constellation for the internet of thing (IoT) has become one of the hot spots for B5G and 6G concerns. Information-centric networking (ICN) provides a new approach to the interconnection of everything in the LEO mega constellation. In ICN, data objects are independent of location, application, storage and transport methods. Therefore, data naming is one of the fundamental issues of ICN, and research on the data naming mechanism of the LEO mega constellation for the IoT is thus the focus of this study. Adopting a fusion of hierarchical, multicomponent, and hash flat as one structure, a data naming mechanism is proposed, which can meet the needs of the IoT multiservice attributes and high-performance transmission. Additionally, prefix tokens are used to describe hierarchical names with various embedded semantic functions to support multisource content retrieval for in-network functions. To verify the performance of the proposed data naming mechanism, an NS-3-based simulation platform for LEO mega constellations for the IoT is designed and developed. The test simulation results show that, compared with the IP address, the ICN-HMcH naming mechanism can increase throughput by as much as 54% and reduce the transmission delay of the LEO mega satellites for the IoT by 53.97%. The proposed data naming mechanism can provide high quality of service (QoS) transmission performance for the LEO mega constellation for IoT and performs better than IP-based transmission.
Real Coded Mixed Integer Genetic Algorithm for Geometry Optimization of Flight Simulator Mechanism Based on Rotary Stewart Platform
Authors: Petrašinović Miloš D. , Grbović Aleksandar M. , Petrašinović Danilo M. , Petrović Mihailo G. , Raičević Nikola G.
Published: July 2022

Designing the motion platform for the flight simulator is closely coupled with the particular aircraft’s flight envelope. While in training, the pilot on the motion platform has to experience the same feeling as in the aircraft. That means that flight simulators need to simulate all flight cases and forces acting upon the pilot during flight. Among many existing mechanisms, parallel mechanisms based on the Stewart platform are suitable because they have six degrees of freedom. In this paper, a real coded mixed integer genetic algorithm (RCMIGA) is applied for geometry optimization of the Stewart platform with rotary actuators (6-RUS) to design a mechanism with appropriate physical limitations of workspace and motion performances. The chosen algorithm proved that it can find the best global solution with all imposed constraints. At the same time, the obtained geometry can be manufactured because integer solutions can be mapped to available discrete values. Geometry is defined with a minimum number of parameters that fully define the mechanism with all constraints. These geometric parameters are then optimized to obtain custom-tailored geometry for aircraft flight simulation.
Formation of Stable Cruciform Assembly of Gold Nanoparticles from Cannabis indica Leaves
Authors: Khadria Anjul , Paul Subhankar
Published: July 2022

Gold nanoparticles have been increasingly used in several electronic, material fabrication, and biomedical applications. Several methods have been reported to prepare gold nanoparticles of various shapes and sizes with different photophysical properties. Although useful to prepare gold nanoparticles, most of the methods are not stable enough, which leads to the degradation of the nanoparticles, if they are stored at room temperatures (up to 30 °C) for a few days. In this paper, we report a novel and environmentally friendly method to synthesize self-assembled gold nanoparticles in cruciform shapes by using leaf extract of Cannabis indica as a reducing agent without the aid of any polymers or additional chemicals. The nanoparticles are found to be stable for more than a month (45 days) when stored at room temperature (up to 30 °C). They were able to form stable conjugates with bovine α-lactalbumin protein that may possess anti-cancerous properties.
Speed Control Based on State Vector Applied for Electrical Drive with Elastic Connection
Authors: Malarczyk Mateusz , Zychlewicz Mateusz , Stanislawski Radoslaw , Kaminski Marcin
Published: July 2022

The paper is focused on issues related to the control of electrical drives with oscillations of state variables. The main problem deals with the construction of the mechanical part, which contains elastic elements used as a coupling between the motor machine and the load. In such cases, strict tracking of the reference trajectory is difficult, so damping of the disturbances is necessary. For this purpose, the full state vector of the object is applied as the feedback signal for the speed controller. This method is efficient and relatively easy to implement (including the hardware part). However, the control accuracy is dependent on the quality of the parameters identification and the invariance of the object. Thus, two adaptive structures are proposed for the two-mass system. Moreover, selected coefficients were optimized using metaheuristic algorithms (symbiotic organism search and flower pollination algorithm). After presentation of the preliminaries and mathematical background, tests were conducted, and the numerical simulations are shown. Finally, the experimental verification for the 0.5 kW DC machines was performed. The results confirm the theoretical concept and the initial assumptions: the state controller leads to the precise control of the drive with a long shaft; recalculation of the parameters can improve the work of the drive under changes of time constants; modern design tools are appropriate for this application.
Bag of Tricks for Improving Deep Learning Performance on Multimodal Image Classification
Authors: Adeshina Steve A. , Adedigba Adeyinka P.
Published: July 2022

A comprehensive medical image-based diagnosis is usually performed across various image modalities before passing a final decision; hence, designing a deep learning model that can use any medical image modality to diagnose a particular disease is of great interest. The available methods are multi-staged, with many computational bottlenecks in between. This paper presents an improved end-to-end method of multimodal image classification using deep learning models. We present top research methods developed over the years to improve models trained from scratch and transfer learning approaches. We show that when fully trained, a model can first implicitly discriminate the imaging modality and then diagnose the relevant disease. Our developed models were applied to COVID-19 classification from chest X-ray, CT scan, and lung ultrasound image modalities. The model that achieved the highest accuracy correctly maps all input images to their respective modality, then classifies the disease achieving overall 91.07% accuracy.
Cyclograms Reveal Alteration of Inter-Joint Coordination during Gait in People with Multiple Sclerosis Minimally Disabled
Authors: Pau Massimiliano , Leban Bruno , Porta Micaela , Frau Jessica , Coghe Giancarlo , Cocco Eleonora
Published: July 2022

Subtle alterations of gait patterns in people with Multiple Sclerosis (pwMS) with minimal or no disability often coexist with normal spatio-temporal parameters. Here, we retrospectively investigate the existence of possible anomalies in lower limb inter-joint coordination (i.e., the functional relationship between joint pairs) in pwMS with apparently physiologic gait features. Twenty-seven pwMS with Expanded Disability Status Scale scores ≤ 2, and 27 unaffected age-and-sex-matched individuals, were tested using 3D computerized gait analysis. Raw data were processed to extract the main spatio-temporal parameters and the kinematics in the sagittal plane at the hip, knee, and ankle joints. Angle-angle diagrams (cyclograms) were obtained by coupling the flexion-extension values for the hip-knee and knee-ankle joint pairs at each point of the gait cycle. Cyclogram area, perimeter, and dimensionless ratio were employed to quantify inter-joint coordination. The results demonstrate that cyclograms of pwMS are characterized by significantly reduced perimeters for both investigated joint pairs and reduced area at the hip–knee joint pair. In the latter pair, the differences between groups involved the entire swing phase. For the knee-ankle pair, the average cyclogram of pwMS departed from normality from the late stance until the mid-swing phase. Such findings suggest that inter-joint coordination is impaired even in minimally disabled pwMS who exhibit a normal gait pattern in terms of spatio-temporal parameters. The quantitative and qualitative study of cyclogram features may provide information that is useful for better understanding the underlying mechanisms of walking dysfunctions in MS.