bluuebunny/crossref_metadata_2025 huggingface dataset:
Creating a model of cross-task motivation — A meta-narrative review of the literature on dynamic motivation
Authors: Feyer Frida K.
Published: June 2023

Introduction

Substantial research on job motivation over the years has identified motivation to be essential to work outcomes such as wellbeing, attitudes, and performance. Yet, research on job motivation addressing temporal influences has been sparse. Existing research has addressed job motivation as an aggregation of the motivation for tasks, ignoring the possibility of temporal effects where the motivation for one task affects motivation in a subsequent task. The current meta-narrative review analyzes existing research on task motivation and synthesizes findings into a model of cross-task motivation.

Methods

Using a predetermined search strategy, a systematic search yielded 1,635 documents of which 17 were selected. Papers were analyzed using a meta-narrative approach according to RAMSES publication standards.

Results

Four key meta-narratives were identified, contributing information from different research traditions; (1) restoration effects after need frustration, (2) intrinsic and extrinsic motivation, (3) cognitive carryover effects, and (4) meaning of work. Synthesizing findings from these meta-narratives, a meta-theoretical model for understanding cross-task motivation was proposed.

Discussion

This model provides an extension of existing motivational theories elucidating temporal motivational processes. Implications for practitioners include the possibility of arranging jobs to maximize positive motivational outcomes.
A transdiagnostic approach to negative symptoms: exploring factor structure and negative symptoms in bipolar disorders
Authors: Ihler Henrik Myhre , Lyngstad Siv Hege , Mørch-Johnsen Lynn Egeland , Lagerberg Trine Vik , Melle Ingrid , Romm Kristin Lie
Published: June 2023

Background

Negative symptoms are increasingly recognized as transdiagnostic phenomena, linked to reduced quality of life and functioning, and often caused or worsened by amendable external factors such as depression, social deprivation, side-effects of antipsychotics or substance use. The structure of negative symptoms fits into two dimensions: diminished expression and apathy. These may differ in association with external factors that influence their severity and may thus require different treatment approaches. The dimensions are comprehensively established in non-affective psychotic disorders but are understudied in bipolar disorders.

Methods

We conducted exploratory and confirmatory factor analyses in a sample of 584 individuals with bipolar disorder to assess the latent factor structure of negative symptoms as measured by the Positive and Negative Syndrome Scale (PANSS), and performed correlational analyses and multiple hierarchical regression analyses to investigate links between the two dimensions of negative symptoms and clinical and sociodemographic correlates.

Results

The latent factor structure of negative symptoms fits into two dimensions, i.e., diminished expression and apathy. A diagnosis of bipolar type I or a history of psychotic episodes predicted more severe levels of diminished expression. Depressive symptoms were associated with more severe negative symptoms across dimensions, yet 26.3% of euthymic individuals still displayed at least one mild or more severe negative symptom (PANSS score ≥ 3).

Discussion

The two-dimensional structure of negative symptoms seen in non-affective psychotic disorders reproduces in bipolar disorders indicating similarities in their phenomenology. Diminished expression was associated with a history of psychotic episodes and a diagnosis of BD-I, which may infer closer connections to psychosis liability. We found significantly less severe negative symptoms in euthymic than depressed participants. Nevertheless, more than a quarter of the euthymic individuals had at least one mild negative symptom, demonstrating some degree of persistence beyond depressed states.
Protecting, promoting and supporting breastfeeding in all policies: reframing the narrative
Authors: Tomori Cecília
Published: June 2023

Recent research highlights the importance of breastfeeding to health across the lifecourse, yet inadequate investment to facilitate breastfeeding according to World Health Organization recommendations threatens to undermine breastfeeding’s protective effects. Western media narratives often fail to convey the significance of breastfeeding, and such narratives can hinder efforts to direct sufficient resources to scaling up effective systems and generating policy change. Delayed action disproportionately harms poor and marginalized communities. The urgency of making these investments in an era of rapidly intensifying climate change and other crises is clear. Reframing the narrative is needed to better appreciate the significance of breastfeeding as well as to recognize and address extensive efforts of undermine it. Evidence-based scientific, health professional and media discussions are necessary to recognize breastfeeding as foundational to food and health security and to enact change so that protecting, promoting and supporting breastfeeding is integrated across all policies.
Saline nasal irrigation and gargling in COVID-19: a multidisciplinary review of effects on viral load, mucosal dynamics, and patient outcomes
Authors: Huijghebaert Suzy , Parviz Shehzad , Rabago David , Baxter Amy , Chatterjee Uday , Khan Farhan R. , Fabbris Cristoforo , Poulas Konstantinos , Hsu Stephen
Published: June 2023

With unrelenting SARS-CoV-2 variants, additional COVID-19 mitigation strategies are needed. Oral and nasal saline irrigation (SI) is a traditional approach for respiratory infections/diseases. As a multidisciplinary network with expertise/experience with saline, we conducted a narrative review to examine mechanisms of action and clinical outcomes associated with nasal SI, gargling, spray, or nebulization in COVID-19. SI was found to reduce SARS-CoV-2 nasopharyngeal loads and hasten viral clearance. Other mechanisms may involve inhibition of viral replication, bioaerosol reduction, improved mucociliary clearance, modulation of ENaC, and neutrophil responses. Prophylaxis was documented adjunctive to personal protective equipment. COVID-19 patients experienced significant symptom relief, while overall data suggest lower hospitalization risk. We found no harm and hence recommend SI use, as safe, inexpensive, and easy-to-use hygiene measure, complementary to hand washing or mask-wearing. In view of mainly small studies, large well-controlled or surveillance studies can help to further validate the outcomes and to implement its use.
Impact of multi-source data augmentation on performance of convolutional neural networks for abnormality classification in mammography
Authors: Hwang InChan , Trivedi Hari , Brown-Mulry Beatrice , Zhang Linglin , Nalla Vineela , Gastounioti Aimilia , Gichoya Judy , Seyyed-Kalantari Laleh , Banerjee Imon , Woo MinJae
Published: June 2023

Introduction

To date, most mammography-related AI models have been trained using either film or digital mammogram datasets with little overlap. We investigated whether or not combining film and digital mammography during training will help or hinder modern models designed for use on digital mammograms.

Methods

To this end, a total of six binary classifiers were trained for comparison. The first three classifiers were trained using images only from Emory Breast Imaging Dataset (EMBED) using ResNet50, ResNet101, and ResNet152 architectures. The next three classifiers were trained using images from EMBED, Curated Breast Imaging Subset of Digital Database for Screening Mammography (CBIS-DDSM), and Digital Database for Screening Mammography (DDSM) datasets. All six models were tested only on digital mammograms from EMBED.

Results

The results showed that performance degradation to the customized ResNet models was statistically significant overall when EMBED dataset was augmented with CBIS-DDSM/DDSM. While the performance degradation was observed in all racial subgroups, some races are subject to more severe performance drop as compared to other races.

Discussion

The degradation may potentially be due to (
1) a mismatch in features between film-based and digital mammograms (
2) a mismatch in pathologic and radiological information. In conclusion, use of both film and digital mammography during training may hinder modern models designed for breast cancer screening. Caution is required when combining film-based and digital mammograms or when utilizing pathologic and radiological information simultaneously.
A robust radiomic-based machine learning approach to detect cardiac amyloidosis using cardiac computed tomography
Authors: Lo Iacono Francesca , Maragna Riccardo , Pontone Gianluca , Corino Valentina D. A.
Published: June 2023

Introduction

Cardiac amyloidosis (CA) shares similar clinical and imaging characteristics (e.g., hypertrophic phenotype) with aortic stenosis (AS), but its prognosis is generally worse than severe AS alone. Recent studies suggest that the presence of CA is frequent (1 out of 8 patients) in patients with severe AS. The coexistence of the two diseases complicates the prognosis and therapeutic management of both conditions. Thus, there is an urgent need to standardize and optimize the diagnostic process of CA and AS. The aim of this study is to develop a robust and reliable radiomics-based pipeline to differentiate the two pathologies.

Methods

Thirty patients were included in the study, equally divided between CA and AS. For each patient, a cardiac computed tomography (CCT) was analyzed by extracting 107 radiomics features from the LV wall. Feature robustness was evaluated by means of geometrical transformations to the ROIs and intra-class correlation coefficient (ICC) computation. Various correlation thresholds (0.80, 0.85, 0.90, 0.95, 1), feature selection methods [p-value, least absolute shrinkage and selection operator (LASSO), semi-supervised LASSO, principal component analysis (PCA), semi-supervised PCA, sequential forwards selection] and machine learning classifiers (k-nearest neighbors, support vector machine, decision tree, logistic regression and gradient boosting) were assessed using a leave-one-out cross-validation. Data augmentation was performed using the synthetic minority oversampling technique. Finally, explainability analysis was performed by using the SHapley Additive exPlanations (SHAP) method.

Results

Ninety-two radiomic features were selected as robust and used in the further steps. Best performances of classification were obtained using a correlation threshold of 0.95, PCA (keeping 95% of the variance, corresponding to 9 PCs) and support vector machine classifier reaching an accuracy, sensitivity and specificity of 0.93. Four PCs were found to be mainly dependent on textural features, two on first-order statistics and three on shape and size features.

Conclusion

These preliminary results show that radiomics might be used as non-invasive tool able to differentiate CA from AS using clinical routine available images.
Teledentistry from research to practice: a tale of nineteen countries
Authors: El Tantawi Maha , Lam Walter Yu Hang , Giraudeau Nicolas , Virtanen Jorma I. , Matanhire Cleopatra , Chifamba Timothy , Sabbah Wael , Gomaa Noha , Al-Maweri Sadeq Ali , Uribe Sergio E. , Mohebbi Simin Z. , Hasmun Noren , Guan Guangzhao , Polonowita Ajith , Khan Sadika Begum , Pisano Massimo , Ellakany Passent , Baraka Marwa Mohamed , Ali Abdalmawla Alhussin , Orellana Centeno José Eduardo , Pavlic Verica , Folayan Morenike Oluwatoyin
Published: June 2023

Aim

The COVID-19 pandemic has accelerated teledentistry research with great interest reflected in the increasing number of publications. In many countries, teledentistry programs were established although not much is known about the extent of incorporating teledentistry into practice and healthcare systems. This study aimed to report on policies and strategies related to teledentistry practice as well as barriers and facilitators for this implementation in 19 countries.

Methods

Data were presented per country about information and communication technology (ICT) infrastructure, income level, policies for health information system (HIS), eHealth and telemedicine. Researchers were selected based on their previous publications in teledentistry and were invited to report on the situation in their respective countries including Bosnia and Herzegovina, Canada, Chile, China, Egypt, Finland, France, Hong Kong SAR, Iran, Italy, Libya, Mexico, New Zealand, Nigeria, Qatar, Saudi Arabia, South Africa, United Kingdom, Zimbabwe.

Results

Ten (52.6%) countries were high income, 11 (57.9%) had eHealth policies, 7 (36.8%) had HIS policies and 5 (26.3%) had telehealth policies. Six (31.6%) countries had policies or strategies for teledentistry and no teledentistry programs were reported in two countries. Teledentistry programs were incorporated into the healthcare systems at national (n = 5), intermediate (provincial) (n = 4) and local (n = 8) levels. These programs were established in three countries, piloted in 5 countries and informal in 9 countries.

Conclusion

Despite the growth in teledentistry research during the COVID-19 pandemic, the use of teledentistry in daily clinical practice is still limited in most countries. Few countries have instituted teledentistry programs at national level. Laws, funding schemes and training are needed to support the incorporation of teledentistry into healthcare systems to institutionalize the practice of teledentistry. Mapping teledentistry practices in other countries and extending services to under-covered populations increases the benefit of teledentistry.
Neutrophil to lymphocyte ratio and principal component analysis offer prognostic advantage for dogs with mammary tumors
Authors: Uribe-Querol Eileen , Romero-Romero Laura , Govezensky Tzipe , Rosales Carlos
Published: June 2023

Introduction

In veterinary medicine, cancer is the leading cause of death in companion animals, and mammary gland tumors represent the most common neoplasm in female dogs. Several epidemiological risk factors, such as age, breed, hormones, diet, and obesity have been reported to be relevant for canine mammary tumors. Nowadays, the gold standard for diagnosis of canine mammary tumors is the pathological examination of the suspected tissue. However, tumor grade can only be assessed after surgical removal or biopsy of the altered tissue. Therefore, in cases of tumors that could be surgically removed, it would be very helpful to be able to predict the biological behavior of the tumor, before performing any surgery. Since, inflammation constitutes part of the tumor microenvironment and it influences each step of tumorigenesis, cellular and biochemical blood markers of systemic inflammation, such as the neutrophil to lymphocyte ratio (NLR) and the albumin to globulin ratio (AGR) have been proposed as prognostic factors for human cancer development. The NLR and the AGR have not been explored enough as prognostic factors for cancer development in veterinary medicine.

Methods

To determine the prognostic value of NLR in canine mammary tumors, clinical records including biochemistry and hematological studies of female dogs with mammary tumors and of control healthy dogs, were used to determine the pre-treatment NLR and AGR. Other clinical data included age, breed, tumor size, histological tumor grade, and survival time after surgery.

Results and discussion

It was found that a higher pre-treatment NLR value (NLR > 5) associates with less survival rate. In contrast, the AGR did not show any predictive value on the malignancy of the tumor. However, by combining the NLR with AGR, age of the dog, and tumor size in a principal component analysis (PCA), the grade of the tumor and survival after surgery could be appropriately predicted. These data strongly suggest that pre-treatment NLR values have a prognostic value for the survival rate after surgery of dogs with mammary tumors.
Laparoscopic vs. Open Approach in Emergent Inguinal Hernia: Our Experience and Review of Literature
Authors: Moreno-Suero Francisco , Tallon-Aguilar Luis , Tinoco-González José , Sánchez-Arteaga Alejandro , Suárez-Grau Juan Manuel , Alvarez-Aguilera Miriam , Morales-Conde Salvador , Padillo-Ruiz Javier
Published: June 2023

There is currently no consensus or homogeneous recommendation about the role of the laparoscopic approach in emergent inguinal hernia surgery. The aim of this manuscript is showing our experience and results of laparoscopic approach for emergent groin hernia repair comparing with open approach. A retrospective review of a prospectively maintained database between January 2011 and December 2021 of acute incarcerated groin hernia that were operated at Virgen del Rocio University Hospital. In this period, they were identified 463 patients with groin hernia that required an emergency repair. 454 patients underwent open surgery (group 1) and 36 patients underwent laparoscopic approach (TAPP procedure) (group 2). Median length stay was 1 day in lap group and 2 days in open approach. Reintervention was necessary in 20 cases (4.40%) from group 1 and one (2.27%) from group 2. In laparoscopic approach, no mortality was described but in open approach, 10 patients (2.20%) died. Globally, 58 cases (12.77%) from group 1 and six patients (16.66%) from group 2 presented any complication. Wound infection was higher in group of open repairs (5.94% vs. 2.77%). Non-surgical complications were higher in open approach (19 vs. 0). There is no statistical significance in any of these items. Laparoscopic approach is a safe, feasible and effective therapeutic option for the treatment of incarcerated groin hernia that require emergency surgery, but prospective and randomized comparative studies are needed to establish the best approach.
Classification of CO Environmental Parameter for Air Pollution Monitoring with Grammatical Evolution
Authors: Spyrou Evangelos D. , Stylios Chrysostomos , Tsoulos Ioannis
Published: June 2023

Air pollution is a pressing concern in urban areas, necessitating the critical monitoring of air quality to understand its implications for public health. Internet of Things (IoT) devices are widely utilized in air pollution monitoring due to their sensor capabilities and seamless data transmission over the Internet. Artificial intelligence (AI) and machine learning techniques play a crucial role in classifying patterns derived from sensor data. Environmental stations offer a multitude of parameters that can be obtained to uncover hidden patterns showcasing the impact of pollution on the surrounding environment. This paper focuses on utilizing the CO parameter as an indicator of pollution in two datasets collected from wireless environmental monitoring devices in the greater Port area and the Town Hall of Igoumenitsa City in Greece. The datasets are normalized to facilitate their utilization in classification algorithms. The k-means algorithm is applied, and the elbow method is used to determine the optimal number of clusters. Subsequently, the datasets are introduced to the grammatical evolution algorithm to calculate the percentage fault. This method constructs classification programs in a human-readable format, making it suitable for analysis. Finally, the proposed method is compared against four state-of-the-art models: the Adam optimizer for optimizing artificial neural network parameters, a genetic algorithm for training an artificial neural network, the Bayes model, and the limited-memory BFGS method applied to a neural network. The comparison reveals that the GenClass method outperforms the other approaches in terms of classification error.
Identification of Highlighted Cells in Low-Variance Raster Data Application to Digital Elevation Models
Authors: Ureña-Cámara Manuel Antonio , Mozas-Calvache Antonio Tomás
Published: June 2023

This study describes a new algorithm developed to detect local cells of minimum or maximum heights in grid Digital Elevation Models (DEMs). DEMs have a low variance in digital levels due to the spatial continuity of the data. Traditional algorithms, such as SIFT, are based on statistical variance, which present issues to determine these highlighted cells. However, one of the main purposes of this identification is the use of these points (cells) to assess the positional accuracy of these products by comparing those extracted from the DEM with those obtained from a more accurate source. In this sense, we developed an algorithm based on a moveable window composed of variable sizes, which is displaced along the image to characterize each set of cells. The determination of highlighted cells is based on the absolute differences of digital levels in the same DEM and compared to those obtained from other DEMs. The application has been carried out using a great number of data, considering four zones, two spatial resolutions, and different definitions of height surfaces. The results have demonstrated the feasibility of the algorithm for the identification of these cells. Thus, this approach expects an improvement in traditional procedures. The algorithm can be used to contrast DEMs obtained from different sources or DEMs from the same source that have been affected by generalization procedures.
Brain Iron Metabolism, Redox Balance and Neurological Diseases
Authors: Gao Guofen , You Linhao , Zhang Jianhua , Chang Yan-Zhong , Yu Peng
Published: June 2023

The incidence of neurological diseases, such as Parkinson’s disease, Alzheimer’s disease and stroke, is increasing. An increasing number of studies have correlated these diseases with brain iron overload and the resulting oxidative damage. Brain iron deficiency has also been closely linked to neurodevelopment. These neurological disorders seriously affect the physical and mental health of patients and bring heavy economic burdens to families and society. Therefore, it is important to maintain brain iron homeostasis and to understand the mechanism of brain iron disorders affecting reactive oxygen species (ROS) balance, resulting in neural damage, cell death and, ultimately, leading to the development of disease. Evidence has shown that many therapies targeting brain iron and ROS imbalances have good preventive and therapeutic effects on neurological diseases. This review highlights the molecular mechanisms, pathogenesis and treatment strategies of brain iron metabolism disorders in neurological diseases.
Insights into the Role of Plasmatic and Exosomal microRNAs in Oxidative Stress-Related Metabolic Diseases
Authors: Duisenbek Ayauly , Lopez-Armas Gabriela C. , Pérez Miguel , Avilés Pérez María D. , Aguilar Benitez José Miguel , Pereira Pérez Víctor Roger , Gorts Ortega Juan , Yessenbekova Arailym , Ablaikhanova Nurzhanyat , Escames Germaine , Acuña-Castroviejo Darío , Rusanova Iryna
Published: June 2023

A common denominator of metabolic diseases, including type 2 diabetes Mellitus, dyslipidemia, and atherosclerosis, are elevated oxidative stress and chronic inflammation. These complex, multi-factorial diseases are caused by the detrimental interaction between the individual genetic background and multiple environmental stimuli. The cells, including the endothelial ones, acquire a preactivated phenotype and metabolic memory, exhibiting increased oxidative stress, inflammatory gene expression, endothelial vascular activation, and prothrombotic events, leading to vascular complications. There are different pathways involved in the pathogenesis of metabolic diseases, and increased knowledge suggests a role of the activation of the NF-kB pathway and NLRP3 inflammasome as key mediators of metabolic inflammation. Epigenetic-wide associated studies provide new insight into the role of microRNAs in the phenomenon of metabolic memory and the development consequences of vessel damage. In this review, we will focus on the microRNAs related to the control of anti-oxidative enzymes, as well as microRNAs related to the control of mitochondrial functions and inflammation. The objective is the search for new therapeutic targets to improve the functioning of mitochondria and reduce oxidative stress and inflammation, despite the acquired metabolic memory.
Near-Infrared Blood Vessel Image Segmentation Using Background Subtraction and Improved Mathematical Morphology
Authors: Li Ling , Liu Haoting , Li Qing , Tian Zhen , Li Yajie , Geng Wenjia , Wang Song
Published: June 2023

The precise display of blood vessel information for doctors is crucial. This is not only true for facilitating intravenous injections, but also for the diagnosis and analysis of diseases. Currently, infrared cameras can be used to capture images of superficial blood vessels. However, their imaging quality always has the problems of noises, breaks, and uneven vascular information. In order to overcome these problems, this paper proposes an image segmentation algorithm based on the background subtraction and improved mathematical morphology. The algorithm regards the image as a superposition of blood vessels into the background, removes the noise by calculating the size of connected domains, achieves uniform blood vessel width, and smooths edges that reflect the actual blood vessel state. The algorithm is evaluated subjectively and objectively in this paper to provide a basis for vascular image quality assessment. Extensive experimental results demonstrate that the proposed method can effectively extract accurate and clear vascular information.
A Comparative Analysis of Optimization Algorithms for Gastrointestinal Abnormalities Recognition and Classification Based on Ensemble XcepNet23 and ResNet18 Features
Authors: Naz Javeria , Sharif Muhammad Imran , Sharif Muhammad Irfan , Kadry Seifedine , Rauf Hafiz Tayyab , Ragab Adham E.
Published: June 2023

Esophagitis, cancerous growths, bleeding, and ulcers are typical symptoms of gastrointestinal disorders, which account for a significant portion of human mortality. For both patients and doctors, traditional diagnostic methods can be exhausting. The major aim of this research is to propose a hybrid method that can accurately diagnose the gastrointestinal tract abnormalities and promote early treatment that will be helpful in reducing the death cases. The major phases of the proposed method are: Dataset Augmentation, Preprocessing, Features Engineering (Features Extraction, Fusion, Optimization), and Classification. Image enhancement is performed using hybrid contrast stretching algorithms. Deep Learning features are extracted through transfer learning from the ResNet18 model and the proposed XcepNet23 model. The obtained deep features are ensembled with the texture features. The ensemble feature vector is optimized using the Binary Dragonfly algorithm (BDA), Moth–Flame Optimization (MFO) algorithm, and Particle Swarm Optimization (PSO) algorithm. In this research, two datasets (Hybrid dataset and Kvasir-V1 dataset) consisting of five and eight classes, respectively, are utilized. Compared to the most recent methods, the accuracy achieved by the proposed method on both datasets was superior. The Q_SVM’s accuracies on the Hybrid dataset, which was 100%, and the Kvasir-V1 dataset, which was 99.24%, were both promising.
Dysfunctions of Neutrophils in the Peripheral Blood of Children with Cystic Fibrosis
Authors: Bakalović Ganimeta , Bokonjić Dejan , Mihajlović Dušan , Čolić Miodrag , Mališ Vanja , Drakul Marija , Tomić Sergej , Jojić Ivan , Rakočević Sara , Popović Darinka , Kozić Ljiljana , Vasiljević Miloš , Bekić Marina , Mašić Srđan , Ljuboja Olivera
Published: June 2023

Dysfunction of neutrophils in patients with cystic fibrosis (CF) is best characterized in bronchoalveolar lavage (BAL), whereas peripheral blood neutrophils are less examined, and the results are contradictory, especially in younger populations. Therefore, this work aimed to study functional and phenotypic changes in circulating neutrophils in children with CF. The study included 19 CF children (5–17 years) and 14 corresponding age-matched healthy children. Isolated neutrophils were cultured either alone or with different stimuli. Several functions were studied: apoptosis, NET-osis, phagocytosis, and production of reactive oxygen species (ROS), neutrophil elastase (NE), and 11 cytokines. In addition, the expression of 20 molecules involved in different functions of neutrophils was evaluated by using flow cytometry. CF neutrophils showed reduced apoptosis and lower production of NE and IL-18 compared to the healthy controls, whereas IL-8 was augmented. All of these functions were further potentiated after neutrophil stimulation, which included higher ROS production and the up-regulation of CD11b and IL-10 expression. NET-osis was higher only when neutrophils from moderate–severe CF were treated with Pseudomonas aeruginosa, and the process correlated with forced expiratory volume in the first second (FEV1). Phagocytosis was not significantly changed. In conclusion, circulating neutrophils from children with CF showed fewer impaired changes in phenotype than in function. Functional abnormalities, which were already present at the baseline levels in neutrophils, depended on the type of stimuli that mimicked different activation states of these cells at the site of infection.
Harnessing Biofabrication Strategies to Re-Surface Osteochondral Defects: Repair, Enhance, and Regenerate
Authors: Bini Fabiano , D’Alessandro Salvatore , Pica Andrada , Marinozzi Franco , Cidonio Gianluca
Published: June 2023

Osteochondral tissue (OC) is a complex and multiphasic system comprising cartilage and subchondral bone. The discrete OC architecture is layered with specific zones characterized by different compositions, morphology, collagen orientation, and chondrocyte phenotypes. To date, the treatment of osteochondral defects (OCD) remains a major clinical challenge due to the low self-regenerative capacity of damaged skeletal tissue, as well as the critical lack of functional tissue substitutes. Current clinical approaches fail to fully regenerate damaged OC recapitulating the zonal structure while granting long-term stability. Thus, the development of new biomimetic treatment strategies for the functional repair of OCDs is urgently needed. Here, we review recent developments in the preclinical investigation of novel functional approaches for the resurfacing of skeletal defects. The most recent studies on preclinical augmentation of OCDs and highlights on novel studies for the in vivo replacement of diseased cartilage are presented.
Computational Study of Stiffness-Tuning Strategies in Anguilliform Fish
Authors: Cui Zuo , Zhang Xuyao
Published: June 2023

Biological evidence demonstrates that fish can tune their body stiffness to improve thrust and efficiency during swimming locomotion. However, the stiffness-tuning strategies that maximize swimming speed or efficiency are still unclear. In the present study, a musculo-skeletal model of anguilliform fish is developed to study the properties of variable stiffness, in which the planar serial-parallel mechanism is used to model the body structure. The calcium ion model is adopted to simulate muscular activities and generate muscle force. Further, the relations among the forward speed, the swimming efficiency, and Young’s modulus of the fish body are investigated. The results show that for certain body stiffness, the swimming speed and efficiency are increased with the tail-beat frequency until reaching the maximum value and then decreased. The peak speed and efficiency are also increased with the amplitude of muscle actuation. Anguilliform fish tend to vary their body stiffness to improve the swimming speed and efficiency at a high tail-beat frequency or small amplitude of muscle actuation. Furthermore, the midline motions of anguilliform fish are analyzed by the complex orthogonal decomposition (COD) method, and the discussions of fish motions associated with the variable body stiffness and the tail-beat frequency are also presented. Overall, the optimal swimming performance of anguilliform fish benefits from the matching relationships among the muscle actuation, the body stiffness, and the tail-beat frequency.
Self-Reported Mental Health and Psychosocial Correlates during the COVID-19 Pandemic: Data from the General Population in Italy
Authors: Marchetti Daniela , Maiella Roberta , Palumbo Rocco , D’Ettorre Melissa , Ceccato Irene , Colasanti Marco , Di Crosta Adolfo , La Malva Pasquale , Bartolini Emanuela , Biasone Daniela , Mammarella Nicola , Porcelli Piero , Di Domenico Alberto , Verrocchio Maria Cristina
Published: June 2023

The COVID-19 pandemic tremendously impacted people’s day-to-day activities and mental health. This article describes the dataset used to investigate the psychological impact of the first national lockdown on the general Italian population. For this purpose, an online survey was disseminated via Qualtrics between 1 April and 20 April 2020, to record various socio-demographic and psychological variables. The measures included both validated (namely, the Impact of the Event Scale-Revised, the Perceived Stress Scale, the nine-item Patient Health Questionnaire, the seven-item Generalized Anxiety Disorder scale, the Big Five Inventory 10-Item, and the Whiteley Index-7) and ad hoc questionnaires (nine items to investigate in-group and out-group trust). The final sample comprised 4081 participants (18–85 years old). The dataset could be helpful to other researchers in understanding the psychological impact of the COVID-19 pandemic and its related preventive and protective measures. Furthermore, the present data might help shed some light on the role of individual differences in response to traumatic events. Finally, this dataset can increase the knowledge in investigating psychological distress, health anxiety, and personality traits.
Design and Analysis of a Typical Vertical Pressure Vessel Using ASME Code and FEA Technique
Authors: Hazizi Kristaq , Ghaleeh Mohammad
Published: June 2023

This study aims to address the hazards associated with the design and manufacture of pressure vessels used for storing dangerous liquids, specifically focusing on the increased demand for liquefied petroleum gas (LPG) worldwide. The construction of more LPG facilities necessitates the implementation of safer pressure vessels to mitigate risks such as explosions and leakage. The primary objective of this project is to design a vertical pressure vessel, in accordance with the American Society of Mechanical Engineers (ASME) code, capable of safely storing 10 m3 of pressurised LPG. To ensure the safety of the pressure vessel, the researchers employed Autodesk Inventor Professional 2023 for geometric modelling and utilised Inventor Nastran for finite element analysis (FEA) to investigate displacements, deflections, and von Mises stresses. The vessel is cylindrical in shape and features two elliptical heads, two nozzles, a manway, and four leg supports. The FEA analysis conducted using Autodesk Inventor Nastran enabled the researchers to identify areas where structural modifications were necessary to reduce stress within the vessel. The results revealed an inverse relationship between the displacement and the tank section shell thickness. Additionally, the factor of safety exhibited a linear increase as the shell thickness increased. The researchers carefully considered permissible pressures and determined the required wall thickness to maintain acceptable maximum stresses. The findings indicate that the design of the pressure vessel is safe from failure. Among the components, the manway experiences the highest stresses, followed by the shell, while the heads, nozzles, and leg supports experience lower stresses. The researchers also conducted theoretical calculations for the entire model and ensured that the results fell within acceptable limits, further validating their design approach. The research emphasised the importance of designing pressure vessels in compliance with ASME codes to ensure safety and prevent hazards associated with improper design and manufacturing. The combination of Autodesk Inventor Professional and Inventor Nastran proved to be an effective approach for simulating and evaluating the performance of the pressure vessel. Through the analysis, the researchers found that changes to the pressure vessel structure were necessary to reduce stress. They observed an inverse relationship between displacement and tank section shell thickness, while the factor of safety increased linearly with shell thickness. Stress distribution analysis revealed that the manway and shell experienced the highest stresses, while the heads, nozzles, and leg support exhibited lower stresses. Employing the finite element method, potential stress points within the pressure vessel were identified, enabling necessary modifications to enhance its safety.
A Novel Evidence Combination Method Based on Improved Pignistic Probability
Authors: Shi Xin , Liang Fei , Qin Pengjie , Yu Liang , He Gaojie
Published: June 2023

Evidence theory is widely used to deal with the fusion of uncertain information, but the fusion of conflicting evidence remains an open question. To solve the problem of conflicting evidence fusion in single target recognition, we proposed a novel evidence combination method based on an improved pignistic probability function. Firstly, the improved pignistic probability function could redistribute the probability of multi-subset proposition according to the weight of single subset propositions in a basic probability assignment (BPA), which reduces the computational complexity and information loss in the conversion process. The combination of the Manhattan distance and evidence angle measurements is proposed to extract evidence certainty and obtain mutual support information between each piece of evidence; then, entropy is used to calculate the uncertainty of the evidence and the weighted average method is used to correct and update the original evidence. Finally, the Dempster combination rule is used to fuse the updated evidence. Verified by the analysis results of single-subset proposition and multi-subset proposition highly conflicting evidence examples, compared to the Jousselme distance method, the Lance distance and reliability entropy combination method, and the Jousselme distance and uncertainty measure combination method, our approach achieved better convergence and the average accuracy was improved by 0.51% and 2.43%.
Cross-Sectional ARDL Analysis to Access the Impact of Stressful Living Environment and Extreme Weather Events on Youth’s Education
Authors: Mata Pedro Neves , Ali Shahzad , Lucas João Luis , Martins Jéssica Nunes , Zafar Mahwish
Published: June 2023

This study’s primary objective is to investigate the impact of stressful living environments and extreme weather conditions on youth’s education. For the fulfillment of this objective, the unique and latest methodology, such as second-generation unit root, cross-sectional ARDL, and the Westerlund approach are used on panel data taken from India and Pakistan. The cross-sectional dependency test is also employed to determine the internal correlations between cross-sections. The results indicate that there are long- as well as short-run relationships between variables. This study helps to develop policies to manage natural disasters, as well as provide the theoretical background to reduce the stressful living environment.
Implementing Green Roofs in the Private Realm for City-Wide Stormwater Management in Vancouver: Lessons Learned from Toronto and Portland
Authors: Wang Junlin , Mukhopadhyaya Phalguni , Valeo Caterina
Published: June 2023

Green roofs are an innovative stormwater management technology that has numerous environmental benefits. Citywide implementation is critical to maximizing the benefits of green roofs, especially in terms of jurisdictional encouragement and advancing management programs. The City of Vancouver is interested in developing a rainwater management strategy that supports the widespread implementation of green roofs on private property. Performance control for a green roof on private property requires standards on local natural factors that affect performance; development considerations; supporting legal tools; maintenance and operation responsibilities; equity through the different types of private properties; and finally, cost. Research into the rainwater management strategies for the cities of Toronto and Portland for green roof implementation was conducted to provide insight into the best approaches for such an implementation in Vancouver. Portland and Toronto both have independent green roof standards in addition to separate rainwater management strategies. Portland focuses on a post-occupancy inspection program to monitor a green roof’s ongoing performance, while Toronto established the Green Roof Bylaw to encourage the implementation of green roofs. Incentive programs that educate and encourage private owners to take the initiative to construct and effectively operate green roofs are essential to the success of a private green roof program.
Oxidative Stability of Avocado Snacks Formulated with Olive Extract as an Active Ingredient for Novel Food Production
Authors: Martínez Carmen , Jiménez Alfonso , Garrigós Maria Carmen , Valdés Arantzazu
Published: June 2023

Analysis of the oxidative stability of novel avocado chips with added natural extracts was carried out with the aim of reducing the chemical additive content in their formulation. Two different natural extracts were initially evaluated and characterized: one obtained from olive pomace (OE) and other from pomegranate seed waste. OE was selected due to its better antioxidant potential according to FRAP, ABTS, and DPPH assays as well as its higher total phenolic content. The formulations used were 0, 1.5 wt.%, and 3 wt.% of OE. A gradual disappearance of the band found around 3009 cm−1 and related to unsaturated fatty acids was observed in the control sample in contrast to formulations with added OE. The band observed near 3299 cm−1 widened and intensified with time due to the oxidation degree of samples, with this effect being higher in the control chips. The observed changes in fatty acid and hexanal content with storage time underlined the higher extent of oxidation in the control samples. This fact could suggest an antioxidant protectant action of OE in avocado chips during thermal treatment, which was attributed to the presence of phenolic compounds. The obtained chips incorporating OE represent a viable option for the development of a natural, healthy, and clean-label avocado snack at competitive cost and with low environmental impacts.
Combination of Milk and Plant Proteins to Develop Novel Food Systems: What Are the Limits?
Authors: Lima Nascimento Luis Gustavo , Odelli Davide , Fernandes de Carvalho Antônio , Martins Evandro , Delaplace Guillaume , Peres de sá Peixoto Júnior Paulo , Nogueira Silva Naaman Francisco , Casanova Federico
Published: June 2023

In the context of a diet transition from animal protein to plant protein, both for sustainable and healthy scopes, innovative plant-based foods are being developing. A combination with milk proteins has been proposed as a strategy to overcome the scarce functional and sensorial properties of plant proteins. Based on this mixture were designed several colloidal systems such as suspensions, gels, emulsions, and foams which can be found in many food products. This review aims to give profound scientific insights on the challenges and opportunities of developing such binary systems which could soon open a new market category in the food industry. The recent trends in the formulation of each colloidal system, as well as their limits and advantages are here considered. Lastly, new approaches to improve the coexistence of both milk and plant proteins and how they affect the sensorial profile of food products are discussed.
Recent Advances in Halal Bioactive Materials for Intelligent Food Packaging Indicator
Authors: Mohd Hatta Farah Ayuni , Mat Ali Qurratu Aini , Mohd Kashim Mohd Izhar Ariff , Othman Rashidi , Abd Mutalib Sahilah , Mohd Nor Nurul Hafizah
Published: June 2023

Food safety and security are top priorities for consumers and the food industry alike. Despite strict standards and criteria for food production processes, the potential for food-borne diseases due to improper handling and processing is always present. This has led to an urgent need for solutions that can ensure the safety of packaged foods. Therefore, this paper reviews intelligent packaging, which employs non-toxic and environmentally friendly packaging with superior bioactive materials that has emerged as a promising solution. This review was prepared based on several online libraries and databases from 2008 to 2022. By incorporating halal bioactive materials into the packaging system, it becomes possible to interact with the contents and surrounding environment of halal food products, helping preserve them for longer periods. One particularly promising avenue of research is the use of natural colourants as halal bioactive materials. These colourants possess excellent chemical, thermal, and physical stabilities, along with antioxidant and antimicrobial properties, making them ideal candidates for use in intelligent indicators that can detect food blemishes and prevent pathogenic spoilage. However, despite the potential of this technology, further research and development are needed to promote commercial applications and market development. With continued efforts to explore the full potential of natural colourants as halal bioactive materials, we can meet the increasing demand for food safety and security, helping to ensure that consumers have access to high-quality, safe, and nutritious foods.
Prodigiosin-Producing Serratia marcescens as the Causal Agent of a Red Colour Defect in a Blue Cheese
Authors: Rodríguez Javier , Lobato Cristina , Vázquez Lucía , Mayo Baltasar , Flórez Ana Belén
Published: June 2023

Technological defects in the organoleptic characteristics of cheese (odour, colour, texture, and flavour) reduce quality and consumer acceptance. A red colour defect in Cabrales cheese (a traditional, blue-veined, Spanish cheese made from raw milk) occurs infrequently but can have a notable economic impact on family-owned, artisanal cheesemaking businesses. This work reports the culture-based determination of Serratia marcescens as the microbe involved in the appearance of red spots on the surface and nearby inner areas of such cheese. Sequencing and analysis of the genome of one S. marcescens isolate, RO1, revealed a cluster of 16 genes involved in the production of prodigiosin, a tripyrrole red pigment. HPLC analysis confirmed the presence of prodigiosin in methanol extracts of S. marcescens RO1 cultures. The same was also observed in extracts from red areas of affected cheeses. The strain showed low survival rates under acidic conditions but was not affected by concentrations of up to 5% NaCl (the usual value for blue cheese). The optimal conditions for prodigiosin production by S. marscescens RO1 on agar plates were 32 °C and aerobic conditions. Prodigiosin has been reported to possess antimicrobial activity, which agrees with the here-observed inhibitory effect of RO1 supernatants on different bacteria, the inhibition of Enterobacteriaceae, and the delayed development of Penicillium roqueforti during cheesemaking. The association between S. marcescens and the red colour defect was strengthened by recreating the fault in experimental cheeses inoculated with RO1. The data gathered in this study point towards the starting milk as the origin of this bacterium in cheese. These findings should help in the development of strategies that minimize the incidence of pigmenting S. marcescens in milk, the red defect the bacterium causes in cheese, and its associated economic losses.