bluuebunny/crossref_metadata_2025 huggingface dataset:
Basic assessment on adding platelet measurement to legal health checkup in Japan: A cross-sectional and 20-year longitudinal study
Authors: Kasuya Kayoko , Fukai Kota , Watanabe Yuuya , Furuya Yuko , Nakazawa Shoko , Honda Toru , Hayashi Takeshi , Nakagawa Toru , Tatemichi Masayuki , Korenaga Masaaki
Published: April 2023

Background

In Japan, health checkups for workers are legally compulsory. Considering legal health checkup items are important for Japanese workers' health problems. To date, the legal health checkup items for blood cell counts include only red blood cell counts and hemoglobin but not platelet counts. This study aimed to investigate the significance of measuring platelets in workers by showing the association between the FIB-4 index (FIB-4), which can be easily calculated from factors including platelet counts and viral hepatitis infection.

Method

Both cross-sectional and longitudinal analyses were conducted on the comprehensive medical examinations of male workers. In fiscal year (FY) 2019, a logistic regression model was applied to 12,918 examinees. For 13,459 examinees (mean age = 47.5 ± 9.3 SD), FY2000 was set to be followed until FY2019. A total of 149,956 records between FY2000 and FY2019 were analyzed cross-sectionally, and 8,038 men who were consecutively examined to FY2019 at the longest were analyzed longitudinally. Receiver operating characteristic (ROC) curve–area under the ROC curve (ROC–AUC) and Cox proportional methods were used to examine the association between platelet-related indices and viral hepatitis infection.

Results

Logistic regression showed that the risk of FIB-4 ≥ 2.67 was mostly associated with hepatitis C virus antibody (HCVAb) positivity [odds ratio (OR) = 2.51, 95% confidence interval (CI) = 1.08–5.86], while negatively associated with body mass index (BMI) (OR = 0.54, 95% CI = 0.30–0.97), and not associated with the presence of fatty liver. To detect HVC Ab positivity, ROC–AUC showed more effectiveness in FIB-4 than in the AST/ALT ratio (0.776, 95% CI = 0.747–0.773 vs. 0.552; 95% CI = 0.543–0.561). The Cox analysis showed that the risk of FIB-4 ≥ 2.67 was closely associated with hepatitis B virus surface antigen (HBsAg) [hazard ratio (HR) = 3.1, 95% CI = 2.0–4.6] and HCV Ab positivity (HR = 3.2, 95% CI = 2.0–5.0).

Conclusion

Our results suggest that it might be worth considering that usage of information on platelets in legal health checkups could be some help not to overlook workers with hepatitis virus carriers as a complementary countermeasure, although further investigations are needed into its practical application.
Children's internal migration and subjective wellbeing of older parents left behind: Spiritual or financial support?
Authors: Lu Ying , Lin Yi-Yang , Qu Jun-Qiao , Zeng Yi , Wu Wan-Zong
Published: April 2023

Introduction

Against the background of population aging and large-scale internal migration, this study uses an ordered logit with two-way fixed effects to examine the effect of children's internal migration on the subjective wellbeing of parents left behind. The study is based on the China Family Panel Studies database.

Methods

Data were obtained from CFPS (China Family Panel Studies), and ordered logit with two-way fixed effects was used to test the total effect of children's internal migration on subjective wellbeing of parents left behind, and KHB test was used to separate intergenerational spiritual support and intergenerational financial support to examine the intergenerational support preferences of parents left behind.

Results

The results show that children's internal migration has a significant negative effect on the subjective wellbeing of parents left behind, mainly through the reduction of intergenerational spiritual support. Furthermore, intergenerational financial support significantly mitigates this negative effect. There is heterogeneity in the direction of the total wellbeing effect across parents' preferences, as well as in the masking effect of financial support. However, the effect of financial support never fully offsets the effect of spiritual support.

Discussion

To cope with the negative effects of children's internal migration on parents, positive measures should be taken to change parental preferences.
The impact of educational interventions on COVID-19 and vaccination attitudes among patients in Michigan: A prospective study
Authors: Takagi Maya Asami , Hess Samantha , Smith Zachary , Gawronski Karissa , Kumar Ayushi , Horsley Jacob , Haddad Nicholas , Noveloso Bernard , Zyzanski Stephen , Ragina Neli
Published: April 2023

Background

Mass vaccination serves as an effective strategy to combat the COVID-19 pandemic. Vaccine hesitancy is a recognized impediment to achieving a vaccination rate necessary to protect communities. However, solutions and interventions to address this issue are limited by a lack of prior research.

Methods

Over 200 patients from 18 Michigan counties participated in this study. Each participant received an initial survey, including demographical questions and knowledge and opinion questions regarding COVID-19 and vaccines. Participants were randomly assigned an educational intervention in either video or infographic format. Patients received a post-survey to assess changes in knowledge and attitudes. Paired sample t-tests and ANOVA were used to measure the effectiveness of the educational interventions. Participants also elected to complete a 3-month follow-up survey.

Results

Patients showed increased knowledge after the educational intervention in six out of seven COVID-19 topics (p < 0.005). There was increased vaccine acceptance after the intervention but no difference in the effectiveness between the two intervention modalities. Post-intervention, more patients believed in CDC recommendations (p = 0.005), trusted the vaccine (p = 0.001), believed the vaccines had adequate testing (p = 0.019), recognized prior mistreatment in the medical care system (p = 0.005), agreed that a source they trust told them to receive a vaccine (p = 0.015), and were worried about taking time off of work to get a vaccine (p = 0.023). Additionally, post-intervention, patients were less concerned about mild reactions of the virus (p = 0.005), the rapid development of the vaccines (p < 0.001), and vaccine side effects (p = 0.031). Data demonstrated that attitude and knowledge improved when comparing pre-educational intervention to follow-up but decreased from post-intervention to follow-up.

Conclusion

The findings illustrate that educational interventions improved COVID-19 and vaccine knowledge among patients and that the knowledge was retained. Educational interventions serve as powerful tools to increase knowledge within communities and address negative views on vaccination. Interventions should be continually utilized to reinforce information within communities to improve vaccination rates.
Learning from real world data about combinatorial treatment selection for COVID-19
Authors: Zhai Song , Zhang Zhiwei , Liao Jiayu , Cui Xinping
Published: April 2023

COVID-19 is an unprecedented global pandemic with a serious negative impact on virtually every part of the world. Although much progress has been made in preventing and treating the disease, much remains to be learned about how best to treat the disease while considering patient and disease characteristics. This paper reports a case study of combinatorial treatment selection for COVID-19 based on real-world data from a large hospital in Southern China. In this observational study, 417 confirmed COVID-19 patients were treated with various combinations of drugs and followed for four weeks after discharge (or until death). Treatment failure is defined as death during hospitalization or recurrence of COVID-19 within four weeks of discharge. Using a virtual multiple matching method to adjust for confounding, we estimate and compare the failure rates of different combinatorial treatments, both in the whole study population and in subpopulations defined by baseline characteristics. Our analysis reveals that treatment effects are substantial and heterogeneous, and that the optimal combinatorial treatment may depend on baseline age, systolic blood pressure, and c-reactive protein level. Using these three variables to stratify the study population leads to a stratified treatment strategy that involves several different combinations of drugs (for patients in different strata). Our findings are exploratory and require further validation.
Macrophages and small extracellular vesicle mediated-intracellular communication in the peritoneal microenvironment: Impact on endometriosis development
Authors: Wang Yifan , Dragovic Rebecca A. , Greaves Erin , Becker Christian M. , Southcombe Jennifer H.
Published: April 2023

Endometriosis is an inflammatory disease that is defined as the growth of endometrium-like tissue outside the uterus, commonly on the lining of the pelvic cavity, visceral organs and in the ovaries. It affects around 190 million women of reproductive age worldwide and is associated with chronic pelvic pain and infertility, which greatly impairs health-related life quality. The symptoms of the disease are variable, this combined with a lack of diagnostic biomarkers and necessity of surgical visualisation to confirm disease, the prognosis can take an average timespan of 6–8 years. Accurate non-invasive diagnostic tests and the identification of effective therapeutic targets are essential for disease management. To achieve this, one of the priorities is to define the underlying pathophysiological mechanisms that contribute to endometriosis. Recently, immune dysregulation in the peritoneal cavity has been linked to endometriosis progression. Macrophages account for over 50% of immune cells in the peritoneal fluid and are critical for lesion growth, angiogenesis, innervation and immune regulation. Apart from the secretion of soluble factors like cytokines and chemokines, macrophages can communicate with other cells and prime disease microenvironments, such as the tumour microenvironment, via the secretion of small extracellular vesicles (sEVs). The sEV-mediated intracellular communication pathways between macrophages and other cells within the peritoneal microenvironment in endometriosis remain unclear. Here, we give an overview of peritoneal macrophage (pMΦ) phenotypes in endometriosis and discuss the role of sEVs in the intracellular communication within disease microenvironments and the impact they may have on endometriosis progression.
ICA’s bug: How ghost ICs emerge from effective rank deficiency caused by EEG electrode interpolation and incorrect re-referencing
Authors: Kim Hyeonseok , Luo Justin , Chu Shannon , Cannard Cedric , Hoffmann Sven , Miyakoshi Makoto
Published: April 2023

Independent component analysis (ICA) has been widely used for electroencephalography (EEG) analyses. However, ICA performance relies on several crucial assumptions about the data. Here, we focus on the granularity of data rank, i.e., the number of linearly independent EEG channels. When the data are rank-full (i.e., all channels are independent), ICA produces as many independent components (ICs) as the number of input channels (rank-full decomposition). However, when the input data are rank-deficient, as is the case with bridged or interpolated electrodes, ICA produces the same number of ICs as the data rank (forced rank deficiency decomposition), introducing undesired ghost ICs and indicating a bug in ICA. We demonstrated that the ghost ICs have white noise properties, in both time and frequency domains, while maintaining surprisingly typical scalp topographies, and can therefore be easily missed by EEG researchers and affect findings in unknown ways. This problem occurs when the minimum eigenvalue λmin of the input data is smaller than a certain threshold, leading to matrix inversion failure as if the rank-deficient inversion was forced, even if the data rank is cleanly deficient by one. We defined this problem as the effective rank deficiency. Using sound file mixing simulations, we first demonstrated the effective rank deficiency problem and determined that the critical threshold for λmin is 10−7 in the given situation. Second, we used empirical EEG data to show how two preprocessing stages, re-referencing to average without including the initial reference and non-linear electrode interpolation, caused this forced rank deficiency problem. Finally, we showed that the effective rank deficiency problem can be solved by using the identified threshold (λmin = 10−7) and the correct re-referencing procedure described herein. The former ensures the achievement of effective rank-full decomposition by properly reducing the input data rank, and the latter allows avoidance of a widely practiced incorrect re-referencing approach. Based on the current literature, we discuss the ambiguous status of the initial reference electrode when re-referencing. We have made our data and code available to facilitate the implementation of our recommendations by the EEG community.
Regulation of dendritic spines in the amygdala following sleep deprivation
Authors: Rexrode Lindsay , Tennin Matthew , Babu Jobin , Young Caleb , Bollavarapu Ratna , Lawson Lamiorkor Ameley , Valeri Jake , Pantazopoulos Harry , Gisabella Barbara
Published: April 2023

The amygdala is a hub of emotional circuits involved in the regulation of cognitive and emotional behaviors and its critically involved in emotional reactivity, stress regulation, and fear memory. Growing evidence suggests that the amygdala plays a key role in the consolidation of emotional memories during sleep. Neuroimaging studies demonstrated that the amygdala is selectively and highly activated during rapid eye movement sleep (REM) and sleep deprivation induces emotional instability and dysregulation of the emotional learning process. Regulation of dendritic spines during sleep represents a morphological correlate of memory consolidation. Several studies indicate that dendritic spines are remodeled during sleep, with evidence for broad synaptic downscaling and selective synaptic upscaling in several cortical areas and the hippocampus. Currently, there is a lack of information regarding the regulation of dendritic spines in the amygdala during sleep. In the present work, we investigated the effect of 5 h of sleep deprivation on dendritic spines in the mouse amygdala. Our data demonstrate that sleep deprivation results in differential dendritic spine changes depending on both the amygdala subregions and the morphological subtypes of dendritic spines. We observed decreased density of mushroom spines in the basolateral amygdala of sleep deprived mice, together with increased neck length and decreased surface area and volume. In contrast, we observed greater densities of stubby spines in sleep deprived mice in the central amygdala, indicating that downscaling selectively occurs in this spine type. Greater neck diameters for thin spines in the lateral and basolateral nuclei of sleep deprived mice, and decreases in surface area and volume for mushroom spines in the basolateral amygdala compared to increases in the cental amygdala provide further support for spine type-selective synaptic downscaling in these areas during sleep. Our findings suggest that sleep promotes synaptic upscaling of mushroom spines in the basolateral amygdala, and downscaling of selective spine types in the lateral and central amygdala. In addition, we observed decreased density of phosphorylated cofilin immunoreactive and growth hormone immunoreactive cells in the amygdala of sleep deprived mice, providing further support for upscaling of dendritic spines during sleep. Overall, our findings point to region- and spine type-specific changes in dendritic spines during sleep in the amygdala, which may contribute to consolidation of emotional memories during sleep.
Circularity in the construction and demolition industry: Comparing weighting methods for multi-criteria decision analysis
Authors: Dytianquin Norman , Kalogeras Nikos , van Oorschot John , Abujidi Nurhan
Published: April 2023

In studying circularity in the construction and demolition industry (CDI) in the EU, five projects in selected EU countries were compared to assess how the application of circularity achieved balance in the environment, social and economic dimensions of sustainability. The selected projects using secondary data based on a web search of these projects involved different stages of the circularity ladder, used diverse design principles, and focused on different stages of the construction life cycle, making them interesting comparators for applying circularity in CDI. For strong sustainability to exist, there should be a balance between the sustainability triptych covering environment, social and economic dimensions which is often overlooked in many circular and sustainability projects with an overemphasis on one dimension and disregard for another. Selected indicators for the three dimensions included those found in environmental impact and life cycle assessments for environmental criteria, social impact assessments for social criteria and economic feasibility, and project appraisal and evaluation reports for economic criteria. In weighting criteria, several methods exist comprising subjective, objective, and integrated techniques. The robustness of objective vs. subjective weights is rather debatable. The objective of the research is to test different weighting techniques using subjective and objective methods to determine if differences in project rankings exist in terms of sustainability balance. The ranking of projects and conclusions about best practices in the CDI circular economy could be influenced by the weighting techniques used. As the weighting of criteria could influence project outcomes, objectivity in weighting is often advised. However, in this study, computational comparisons indicated that subjective methods do not significantly differ from objective ones that use mathematical and statistical rigor. As such, subjective weighting methods still conveniently capture credible and consistent results. Nonetheless, this should not detract from efforts to objectify weighting methods that lend more credence and justification to scoring and ranking results.
Protecting the Brain From Epileptic Seizures by Listening to the Heart
Authors: Hadjinicolaou Aristides , Hadjinicolaou Alexandros , Go Cristina Yip
Published: April 2023

Epilepsy is a disorder in which abnormal electrical signals between brain cells lead to seizures. Seizures can cause people to shake, blank out, or even lose consciousness. When medications cannot prevent seizures and there is no brain area that can be removed to solve the problem, a procedure implanting a vagus nerve stimulator (VNS) can be an option. VNS machines send electrical pulses up to the brain through a major nerve connecting the brain to the rest of the body—the vagus nerve. These signals calm the brain down, making intense seizures less likely. Since a racing heartbeat often comes before intense seizures, new cardiac VNS machines that listen to a patient’s heart can send a burst of electricity to calm the brain down during a seizure. This article reviews how this revolutionary technology works, compares it to previous types of VNS and describes how it could help people who suffer from epilepsy.
The Fidget Factor and the obesity paradox. How small movements have big impact
Authors: Levine James A.
Published: April 2023

The hypothesis is that the Fidget Factor is the innate neurological pulse that propels humans and other species to move to support their health. Fidgets, previously thought to be spontaneous, are neurologically regulated and highly ordered (non-random). Modern societies being chair-based overwhelm Fidget Factor pulses and consequently inflict chair-based living for transportation, labor, and leisure. Despite impulses firing through the nervous system, people sit because environmental design overwhelms the biology. Urbanization and chair-based societies were designed after the industrial revolution to promote productivity; however, the consequence has been opposite. Crushing the natural urge to move—the Fidget Factor—is a public health calamity. Excess sitting is associated with a myriad of detrimental health consequences and impairs productivity. Fidgeting may reduce all-cause mortality associated with excessive sitting. The Fidget Factor offers hope; data demonstrate that workplaces and schools can be designed to promote activity and free people's Fidget Factors. Evidence shows that people are happier, healthier, wealthier, and more successful if their Fidget Factors are freed.
Impact of adoption of heat-stress tolerant maize hybrid on yield and profitability: Evidence from Terai region of Nepal
Authors: Kulkarni Atul P. , Tripathi Mahendra P. , Gautam Damodar , Koirala Keshab B. , Kandel Manoj , Regmi Dhruba , Sapkota Sudha , Zaidi Pervez Haider
Published: April 2023

Abiotic stresses (drought, heat) are one of the major impediments to enhancing the maize productivity of marginal farmers in the facet of climate change. The present study attempts to investigate the impact of heat-tolerant maize hybrid on yield and income in the Terai region of Nepal. This study uses cross-sectional farm household-level data collected in August 2021 from a randomly selected sample of 404 rural households. We used a doubly robust inverse probability weighted regression adjustment method to obtain reliable impact estimates. Adoption of heat-tolerant hybrid increases yields by 16% and income by 44% in the spring season (a stress condition). Overall, yield increases by 12%, net income by 31%, saving of 40% in seed costs, and per capita food expenditure increases by 8.50%. Hence a conducive environment must be created for scaling up heat-tolerant maize varieties to increase productivity, minimize risk, and transform of the maize sector.
Long-term renal outcomes comparison between patients with chronic kidney disease and hepatorenal syndrome after living donor liver transplantation
Authors: Tseng Hsiang-Yu , Lin Yu-Hung , Lin Chih-Che , Chen Chao-Long , Yong Chee-Chien , Lin Li-Man , Wang Chih-Chi , Chan Yi-Chia
Published: April 2023

Background and aims

Hepatorenal syndrome (HRS) is a disastrous renal complication of advanced liver disease with a poor prognosis. Restoring normal liver function through liver transplantation (LT) is a standardized treatment with favorable short-term survival. However, the long-term renal outcomes in patients with HRS receiving living donor LT (LDLT) are controversial. This study aimed to investigate the prognostic impact of LDLT in patients with HRS.

Methods

We reviewed adult patients who underwent LDLT between July 2008 and September 2017. Recipients were classified into 1) HRS type 1 (HRS1, N = 11), 2) HRS type 2 (HRS2, N = 19), 3) non-HRS recipients with pre-existing chronic kidney disease (CKD, N = 43), and 4) matched normal renal function (N = 67).

Results

Postoperative complications and 30-day surgical mortality were comparable among the HRS1, HRS2, CKD, and normal renal function groups. The 5-year survival rate was >90% and estimated glomerular filtration rate (eGFR) transiently improved and peaked at 4 weeks post-transplantation in patients with HRS. However, renal function deteriorated and resulted in CKD stage ≥ III in 72.7% of HRS1 and 78.9% of HRS2 patients (eGFR <60 ml/min/1.73 m2). The incidence of developing CKD and end-stage renal disease (ESRD) was similar between the HRS1, HRS2, and CKD groups, but significantly higher than that in the normal renal function group (both P < 0.001). In multivariate logistic regression, pre-LDLT eGFR <46.4 ml/min/1.73 m2 predicted the development of post-LDLT CKD stage ≥ III in patients with HRS (AUC = 0.807, 95% CI = 0.617–0.997, P = 0.011).

Conclusions

LDLT provides a significant survival benefit for patients with HRS. However, the risk of CKD stage ≥ III and ESRD among patients with HRS was similar to that in pre-transplant CKD recipients. An early preventative renal-sparing strategy in patients with HRS is recommended.
Antibacterial plant combinations prevent postweaning diarrhea in organically raised piglets challenged with enterotoxigenic Escherichia coli F18
Authors: Jerez-Bogota Kevin , Jensen Martin , Højberg Ole , Cormican Paul , Lawlor Peadar G. , Gardiner Gillian E. , Canibe Nuria
Published: April 2023

Antibiotics and zinc oxide restrictions encourage the search for alternatives to combat intestinal pathogens, including enterotoxigenic Escherichia coli (ETEC), a major cause of postweaning diarrhea (PWD) in pigs. PWD causes important economic losses for conventional and organic farming. This study investigated the effect of dietary supplementation with garlic and apple pomace or blackcurrant on infection indicators and the fecal microbiota of organic-raised piglets challenged with ETEC-F18. For 21 days, 32 piglets (7-weeks-old) were randomly assigned to one of four groups: non-challenge (NC); ETEC-challenged (PC); ETEC-challenged receiving garlic and apple pomace (3 + 3%; GA); ETEC-challenged receiving garlic and blackcurrant (3 + 3%; GB). ETEC-F18 was administered (8 mL; 109 CFU/ml) on days 1 and 2 postweaning. The 1st week, PC had lower average daily gain than those in the NC, GA, and GB groups (P < 0.05). NC pigs showed neither ETEC-F18 shedding nor signs of diarrhea. The PC group had higher diarrhea incidence and lower fecal dry matter than NC (≈5–10 days; 95% sEBCI). The GA and GB groups showed reduced ETEC-F18 and fedA gene shedding, higher fecal dry matter, and lower diarrhea incidence than the PC (≈5–9 days; 95% sEBCI). The NC, GA, and GB had normal hematology values during most of the study, whereas the PC had increased (P < 0.05) red blood cells, hemoglobin, and hematocrit on day 7. Haptoglobin and pig-MAP increased in all groups, peaking on day 7, but PC showed the greatest increase (P < 0.05). The fecal microbiota of PC pigs had reduced α-diversity (day 7; P < 0.05) and higher volatility (days 3–14; P < 0.05). Escherichia, Campylobacter, and Erysipelothrix were more abundant in the PC than in the NC, GB, and GA groups (log2FC > 2; P < 0.05), whereas Catenibacterium, Dialister, and Mitsoukella were more abundant in the NC, GB, and GA than in the PC group (log2FC > 2; P < 0.05). Prevotella and Lactobacillus were more abundant in the GB group (log2FC > 2, P < 0.05). In conclusion, dietary supplementation of GA and GB limited ETEC proliferation, reduced PWD, and beneficially impacted the fecal microbiota's diversity, composition, and stability.
Early Postnatal Home Visit Coverage by Health Extension Workers and Associated Factors Among Postpartum Women in Gidan District, Northeast Ethiopia
Authors: Asmamaw Desale Bihonegn , Belachew Tadele Biresaw , Endawkie Abel , Debebe Negash Wubshet
Published: April 2023

Objectives: To determine the coverage and associated factors of early postnatal home visits (PNHVs) by health extension workers (HEWs) among postpartum women in Gidan district, Northeast Ethiopia.

Methods: A community-based, cross-sectional study was conducted between 30 March and 29 April 2021 in the Gidan district, Northeast Ethiopia. A multistage sampling technique was employed to select 767 postpartum women participants. Interviewer-administered questionnaires were used to collect the data. A binary logistic regression model was fitted to identify factors associated with early PNHVs by HEWs.

Results: The coverage of early postnatal home visits was 15.13% [95% confidence interval (CI): 12.75, 17.87]. Women’s education, institutional delivery, time to reach health posts, and participation in pregnant women forums were significantly associated with early PNHVs by HEWs.

Conclusion: In the current study, the coverage of early postnatal home visits by HEWs remains low in the study area. The concerned bodies should consider interventions that promote women’s education and institutional delivery, and more efforts should be made to improve community-based participation and links with HEWs.
Intelligent Fault Diagnosis Method through ACCC-Based Improved Convolutional Neural Network
Authors: Zhang Chao , Huang Qixuan , Yang Ke , Zhang Chaoyi
Published: April 2023

Fault diagnosis plays an important role in improving the safety and reliability of complex equipment. Convolutional neural networks (CNN) have been widely used to diagnose faults due to their powerful feature extraction and learning capabilities. In practical industrial applications, the obtained signals always are disturbed by strong and highly non-stationary noise, so the timing relationships of the signals should be highlighted more. However, most CNN-based fault diagnosis methods directly use a pooling layer, which may corrupt the timing relationship of the signals easily. More importantly, due to a lack of an attention mechanism, it is difficult to extract deep informative features from noisy signals. To solve the shortcomings, an intelligent fault diagnosis method is proposed in this paper by using an improved convolutional neural network (ICNN) model. Three innovations are developed. Firstly, the receptive field is used as a guideline to design diagnosis network structures, and the receptive field of the last layer is close to the length of the original signal, which can enable the network to fully learn each sample. Secondly, the dilated convolution is adopted instead of standard convolution to obtain larger-scale information and preserves the internal structure and temporal relation of the signal when performing down-sampling. Thirdly, an attention mechanism block named advanced convolution and channel calibration (ACCC) is presented to calibrate the feature channels, thus the deep informative features are distributed in larger weights while noise-related features are effectively suppressed. Finally, two experiments show the ICNN-based fault diagnosis method can not only process strong noise signals but also diagnose early and minor faults. Compared with other methods, it achieves the highest average accuracy at 94.78% and 90.26%, which are 6.53% and 7.70% higher than the CNN methods, respectively. In complex machine bearing failure conditions, this method can be used to better diagnose the type of failure; in voice calls, this method can be used to better distinguish between voice and noisy background sounds to improve call quality.
Study of Delay Prediction in the US Airport Network
Authors: Kiliç Kerim , Sallan Jose M.
Published: April 2023

In modern business, Artificial Intelligence (AI) and Machine Learning (ML) have affected strategy and decision-making positively in the form of predictive modeling. This study aims to use ML and AI to predict arrival flight delays in the United States airport network. Flight delays carry severe social, environmental, and economic impacts. Deploying ML models during the process of operational decision-making can help to reduce the impact of these delays. A literature review and critical appraisal were carried out on previous studies and research relating to flight delay prediction. In the literature review, the datasets used, selected features, selected algorithms, and evaluation tools used in previous studies were analyzed and influenced the decisions made in the methodology for this study. Data for this study comes from two public sets of domestic flight and weather data from 2017. Data are processed and split into training, validation, and testing data. Subsequently, these ML models are evaluated and compared based on performance metrics obtained using the testing data. The predictive model with the best performance (in choosing between logistic regression, random forest, the gradient boosting machine, and feed-forward neural networks) is the gradient boosting machine.
A Study on Hyperspectral Apple Bruise Area Prediction Based on Spectral Imaging
Authors: Zhang Yue , Li Yang , Han Xiang , Gao Ang , Jing Shuaijie , Song Yuepeng
Published: April 2023

Achieving fast and accurate prediction of the fruit mechanical damage area is important to improve the accuracy and efficiency of apple quality grading. In this paper, the spectral data of all samples in the wavelength range from 376 to 1011 nm were collected, the sample set was divided by the physicochemical coeval distance method, and the spectral preprocessing methods were evaluated by establishing a full-wavelength artificial neural network model. The wavelength selection of spectral data was performed by competitive adaptive reweighted sampling, L1 parameter method, and the Pearson correlation coefficient method, and the partial least squares, artificial neural network, and support vector machine (Gaussian kernel) prediction models were established to predict the fruit bruise area size. The surface fitting was performed using the actual apple bruise area, and the regression surface equation of the damage time and damage height of the fruit was established. The results showed that (1) the preprocessing method of first-order difference + SG smoothing can make the prediction model more accurate; (2) the CARS-ANN prediction model has better prediction performance and higher operation efficiency, with the prediction set root mean square error of prediction and R-value of 0.1150 and 0.8675, respectively; (3) the sparrow search algorithm was used to optimize the model, which improved the accuracy of the prediction model. The root mean square error of prediction reached 0.0743 and The R-value reached 0.9739. (4) The relationship between spectral information, bruise area, damage time, and damage degree was obtained by combining the establishment of the fitted surface of the apple bruise area with the prediction model. This study is of application and extension value for the rapid nondestructive prediction of fruit bruise area.
Genome-Wide Identification and Characterization of Olfactory Receptor Genes in Silver Sillago (Sillago sihama)
Authors: Ye Minghui , Lin Xinghua , Zhang Yulei , Huang Yang , Li Guangli , Tian Changxu
Published: April 2023

Olfactory receptor (OR) genes are essential in the specific recognition of diverse stimuli in fish. In this study, a total of 141 OR genes were identified in silver sillago (Sillago sihama), a marine fish sensitive to environmental stimuli, including 112 intact genes, 26 truncated genes, and three pseudogenes. A phylogenetic tree analysis elucidated that the OR genes of S. sihama were classified into six groups, of which β, γ, δ, ε, and ζ groups belonged to type I, and the η group belonged to type II. The type I OR genes contained almost all conserved motifs (n = 62), while type II OR genes mainly retained conserved motifs 7(3), 1, 10, 4, and 2 (n = 39). OR genes were mainly distributed on LG1, LG9, LG11, and LG12. Of all OR genes, 36.23% (50 genes) showed significant expansion in S. sihama. Ka/Ks analysis demonstrated that 227 sites were under purifying selection, while 12 sites were under positive selection, including eight genes in the OR2A12 gene subfamily. Sixty-one genes (44.20%) displayed differential expression under hypoxic stress. The identified OR genes explored the mechanism of environmental stress and ecological adaptation of S. sihama, and provided valuable genomic resources for further research on the olfaction of teleosts.
Effects of Different Dietary Protein Levels on the Growth Performance, Physicochemical Indexes, Quality, and Molecular Expression of Yellow River Carp (Cyprinus carpio haematopterus)
Authors: Wang Shihui , Tian Jingwen , Jiang Xiaona , Li Chitao , Ge Yanlong , Hu Xuesong , Cheng Lei , Shi Xiaodan , Shi Lianyu , Jia Zhiying
Published: April 2023

A 12-week rearing trial was carried out to estimate effects on the growth performance, physicochemical indexes, quality, and the molecular expression of Yellow River Carp (Cyprinus carpio haematopterus) using five practical diets, including dietary protein levels of 220, 250, 280, 310, and 340 g/kg. The results illustrated that the fish’s weight gain (WG) and specific growth rate (SGR) were significantly influenced, with an ascending dietary protein level of up to 250 g/kg (p < 0.05). The carp muscle contents of total saturated fatty acids (∑SFA), monounsaturated fatty acids (∑MUFA), polyunsaturated fatty acids (∑PUFA), and fatty acids (∑FA) decreased significantly with the ascending dietary protein levels, except for the 250 g/kg protein diet (p < 0.05). Only the glutamic acid and total essential amino acid (∑EAA) contents were significantly influenced by the ascending dietary protein levels (p < 0.05). The relative GH expression of the carp muscle significantly decreased with the increase in the dietary protein level up to 310 g/kg, and then it significantly increased (p < 0.05). In the intestines, the peak relative TOR expression was observed on the 220 g/kg protein diet, while the relative 4EBP1 expression was significantly influenced by the dietary protein level up to 250 g/kg (p < 0.05). In the muscle, the peak relative TOR and 4EBP1 expression levels were observed on the 250 g/kg protein diet. In gills, the lowest relative Rhag, Rhbg, and Rhcg1 expression levels were observed on the 250 g/kg protein diet. Based on all of the aforementioned results, the optimal dietary protein level for Cyprinus carpio haematopterus (160.24 ± 15.56 g) is 250–280 g/kg.
SXRF for Studying the Distribution of Trace Metals in the Pancreas and Liver
Authors: Vatamaniuk Marko Z. , Huang Rong , Zhao Zeping , Lei Xin Gen
Published: April 2023

Transition metals such as iron, copper and zinc are required for the normal functioning of biological tissues, whereas others, such as cadmium, are potentially highly toxic. Any disturbances in homeostasis caused by lack of micronutrients in the diet, pollution or genetic heredity result in malfunction and/or diseases. Here, we used synchrotron X-ray fluorescence, SXRF, microscopy and mice with altered functions of major antioxidant enzymes to show that SXRF may become a powerful tool to study biologically relevant metal balance in the pancreas and liver of mice models with disturbed glucose homeostasis.
Aging Injury Impairs Structural Properties and Cell Signaling in Human Red Blood Cells; Açaì Berry Is a Keystone
Authors: Spinelli Sara , Straface Elisabetta , Gambardella Lucrezia , Caruso Daniele , Falliti Giuseppe , Remigante Alessia , Marino Angela , Morabito Rossana
Published: April 2023

Red blood cell (RBC) deformability is the ability of cells to modulate their shape to ensure transit through narrow capillaries of the microcirculation. A loss of deformability can occur in several pathological conditions, during natural RBC aging through an increase in membrane protein phosphorylation, and/or through the structural rearrangements of cytoskeletal proteins due to oxidative conditions, with a key role played by band 3. Due to the close relationship between aging and oxidative stress, flavonoid-rich foods are good candidates to counteract age-related alterations. This study aims to verify the beneficial role of Açaì extract in a d-Galactose (d-Gal)-induced model of aging in human RBCs. To this end, band 3 phosphorylation and structural rearrangements in membrane cytoskeleton-associated proteins, namely spectrin, ankyrin, and/or protein 4.1, are analyzed in RBCs treated with 100 mM d-Gal for 24 h, with or without pre-incubation with 10 μg/mL Açaì extract for 1 h. Furthermore, RBC deformability is also measured. Tyrosine phosphorylation of band 3, membrane cytoskeleton-associated proteins, and RBC deformability (elongation index) are analyzed using western blotting analysis, FACScan flow cytometry, and ektacytometry, respectively. The present data show that: (i) Açaì berry extract restores the increase in band 3 tyrosine phosphorylation and Syk kinase levels after exposure to 100 mM d-Gal treatment; and (ii) Açaì berry extract partially restores alterations in the distribution of spectrin, ankyrin, and protein 4.1. Interestingly, the significant decrease in membrane RBC deformability associated with d-Gal treatment is alleviated by pre-treatment with Açaì extract. These findings further contribute to clarify mechanisms of natural aging in human RBCs, and propose flavonoid substances as potential natural antioxidants for the treatment and/or prevention of oxidative-stress-related disease risk.
Bioactivity of Wild and Cultivated Legumes: Phytochemical Content and Antioxidant Properties
Authors: Myrtsi Eleni D. , Evergetis Epameinondas , Koulocheri Sofia D. , Haroutounian Serkos A.
Published: April 2023

The global demand for increased meat production has brought to the surface several obstacles concerning environmental impacts, animals’ welfare, and quality features, revealing the need to produce safe foodstuffs with an environmentally acceptable procedure. In this regard, the incorporation of legumes into animal diets constitutes a sustainable way out that prevents these apprehensions. Legumes are plant crops belonging to the Fabaceae family and are known for their rich content of secondary metabolites., displaying significant antioxidant properties and a series of health and environmental benefits. The study herein aims to investigate the chemical composition and antioxidant activities of indigenous and cultivated legume plants used for food and feed. The respective results indicate that the methanolic extract of Lathyrus laxiflorus (Desf.) Kuntze displayed the highest phenolic (64.8 mg gallic acid equivalents/g extract) and tannin (419.6 mg catechin equivalents/g extract) content, while the dichloromethane extract of Astragalus glycyphyllos L., Trifolium physodes Steven ex M.Bieb. and Bituminaria bituminosa (L.) C.H.Stirt. plant samples exhibited the richest content in carotenoids lutein (0.0431 mg/g A. glycyphyllos extract and 0.0546 mg/g B. bituminosa extract), α-carotene (0.0431 mg/g T. physodes extract) and β-carotene (0.090 mg/g T. physodes extract and 0.3705 mg/g B. bituminosa extract) establishing their potential role as vitamin A precursor sources. Results presented herein verify the great potential of Fabaceae family plants for utilization as pasture plants and/or dietary ingredients, since their cultivation has a positive impact on the environment, and they were found to contain essential nutrients capable to improve health, welfare, and safety.
Antioxidants in Oak (Quercus sp.): Potential Application to Reduce Oxidative Rancidity in Foods
Authors: Othón-Díaz Elsa Daniela , Fimbres-García Jorge O. , Flores-Sauceda Marcela , Silva-Espinoza Brenda A. , López-Martínez Leticia X. , Bernal-Mercado Ariadna T. , Ayala-Zavala Jesus F.
Published: April 2023

This review explores the antioxidant properties of oak (Quercus sp.) extracts and their potential application in preventing oxidative rancidity in food products. Oxidative rancidity negatively impacts food quality, causing changes in color, odor, and flavor and reducing the shelf life of products. The use of natural antioxidants from plant sources, such as oak extracts, has gained increasing interest due to potential health concerns associated with synthetic antioxidants. Oak extracts contain various antioxidant compounds, including phenolic acids, flavonoids, and tannins, which contribute to their antioxidative capacity. This review discusses the chemical composition of oak extracts, their antioxidative activity in different food systems, and the safety and potential challenges related to their application in food preservation. The potential benefits and limitations of using oak extracts as an alternative to synthetic antioxidants are highlighted, and future research directions to optimize their application and determine their safety for human consumption are suggested.
Digital Information Credibility: Towards a Set of Guidelines for Quality Assessment of Grey Literature in Multivocal Literature Review
Authors: Abrar Muhammad Faisal , Khan Muhammad Sohail , Khan Inayat , Ali Gauhar , Shah Sajid
Published: April 2023

Credibility, in general, can be interpreted as a sense of trust in someone. The credibility of information remarkably influences the public’s willingness to do or not to do some things. In this research study, the credibility of digital news stories can be interpreted as the sense of confidence a person has in a source of available information that affects their behavior. Humans spread less credible information instead of more credible information very quickly because humans take an interest in fear, disgust, and surprise. Less credible news may affect individuals as well as economies. Therefore, there is a dire need in the current digital era to find out what affects the credibility of digital news stories. This study aims to review the published literature and the grey literature to determine the factors affecting digital news credibility and the factors that build credibility in digital news stories. In this paper, we have developed a multivocal literature review protocol to assess the credibility of digital news stories. The multivocal literature review is an advanced version of the systematic literature review that searches for grey literature in addition to the published literature. The expected outcomes after implementing our protocol will be a list of credibility factors and their practices that can play a vital role in ensuring the credibility of digital news stories. Based on this protocol, we formulated guidelines for the quality assessment of grey literature. The future direction of this research is to analyze the factors through multi-criteria decision-making (MCDM), i.e., analytical hierarchical process.
Spatial Autocorrelation Incorporated Machine Learning Model for Geotechnical Subsurface Modeling
Authors: Kim Hyeong-Joo , Mawuntu Kevin Bagas Arifki , Park Tae-Woong , Kim Hyeong-Soo , Park Jun-Young , Jeong Yeong-Seong
Published: April 2023

Machine learning models for spatial prediction have been applied in various types of research. However, spatial relation has not been fully considered in modeling, since the Cartesian coordinates of the observed points are directly employed as the location information for machine learning features. This study presents a machine learning modeling process which incorporates spatial autocorrelation for geotechnical subsurface modeling. A new set of features called the Euclidean distance field (EDF) was generated based on the distance between the query points and the observed boreholes in order to incorporate spatial autocorrelation into the machine learning model. Principal component analysis (PCA) was performed to reduce the increasing dimensionality of the dataset caused by the EDF features. Optimized machine learning models based on several popular algorithms (Support Vector Machine, Gaussian Process Regression, Artificial Neural Network, and k-Nearest Neighbor) were employed for predicting several geotechnical information as the targets. The results showed that the optimized machine learning models constructed with the EDF modeling approach generate a slightly lower Root Mean Square Error (RMSE) score compared to the model with the direct XY coordinate approach by 0.041, 0.046, 1.302, and 1.561 for ground surface elevation, groundwater level, SPT-N value, and percent finer than 0.075 mm sieve, respectively. Both modeling approaches performed well for USCS-based soil classification with the EDF model having slightly improved classification accuracy by 0.72%. Furthermore, the model can perform balance multiclass classification as indicated by the >95% precision, recall, f1-score, and balanced accuracy score. These results indicate that spatial autocorrelation has a noticeable effect. Hence, it needs to be considered to improve the overall performance of spatial machine learning modeling. Comparison of geotechnical subsurface predictions generated based on different machine learning algorithms showed that the selection of the best-performing model based only on the lowest prediction error is not appropriate for spatial prediction modeling. Therefore, thorough analysis of the predicted data by visualization is necessary in the selection process for spatial prediction modeling.