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Assessment of the factors for the adoption of Internet of things (IoT) in the logistics: a PLS-SEM (partial least squares structural equation modeling) approach
PurposeThe purpose of this study is to investigate the influence that technological, environmental and organizational factors have on the rate of Internet of Things (IoT) adoption within the logistics industry. In addition, the moderating effect that the risk factor has on the technological, environmental and organizational factors regarding the implementation of IoT in logistics.Design/methodology/approachFor the purpose of testing the models and hypotheses, a survey was carried out in order to collect the responses from currently employed individuals at various companies working in the field of logistics or IoT. For the purpose of analysis, the authors made use of the partial least squares structure equation model (PLS-SEM) technique.FindingsFindings of this study concluded that technology- and environmental-related factors significantly affect the adoption of IoT in logistics, while risk acts as a moderator for the technological-related factor only in the adoption of IoT in logistics.Research limitations/implicationsThe relevance of the authors' study lies in the growing importance of IoT in logistics and the need for logistics companies to understand the factors that impact the adoption of IoT in their operations. By identifying and analyzing the factors that influence IoT adoption in logistics, the authors' study provides valuable insights that can help logistics companies make informed decisions about whether and how to adopt IoT.Practical implicationsThe research will help organizations make strategies for the successful adoption of IoT and ease the lives of all the stakeholders.Originality/valueIn this research, the authors attempted to find the factors that influence the adoption of IoT in logistics management. The influence of the technological, environmental, organizational and risk-related factors on the adoption of IoT in logistics management was studied. The moderating effect of risk over these factors on the adoption of IoT in logistics was also analyzed. This is original work and has never been done earlier.
Journal Article
Reactive Oxygen Species and Redox Signaling in Chronic Kidney Disease
Chronic kidney disease (CKD) remains a worldwide public health problem associated with serious complications and increased mortality rates. Accumulating evidence indicates that elevated intracellular levels of reactive oxygen species (ROS) play a major role in the pathogenesis of CKD. Increased intracellular levels of ROS can lead to oxidation of lipids, DNA, and proteins, contributing to cellular damage. On the other hand, ROS are also important secondary messengers in cellular signaling. Consequently, normal kidney cell function relies on the “right” amount of ROS. Mitochondria and NADPH oxidases represent major sources of ROS in the kidney, but renal antioxidant systems, such as superoxide dismutase, catalase, or glutathione peroxidase counterbalance ROS-mediated injury. This review discusses the main sources of ROS and antioxidant systems in the kidney, and redox signaling pathways leading to inflammation and fibrosis, which result in abnormal kidney function and CKD progression. We further discuss the important role of the nuclear factor erythroid 2-related factor 2 (Nrf2) in regulating antioxidant responses, and other mechanisms of redox signaling.
Journal Article
Procyanidin B2 improves endothelial progenitor cell function and promotes wound healing in diabetic mice via activating Nrf2
One of the major reasons for the delayed wound healing in diabetes is the dysfunction of endothelial progenitor cells (EPCs) induced by hyperglycaemia. Improvement of EPC function may be a potential strategy for accelerating wound healing in diabetes. Procyanidin B2 (PCB2) is one of the major components of procyanidins, which exhibits a variety of potent pharmacological activities. However, the effects of PCB2 on EPC function and diabetic wound repair remain elusive. We evaluated the protective effects of PCB2 in EPCs with high glucose (HG) treatment and in a diabetic wound healing model. EPCs derived from human umbilical cord blood were treated with HG. The results showed that PCB2 significantly preserved the angiogenic function, survival and migration abilities of EPCs with HG treatment, and attenuated HG‐induced oxidative stress of EPCs by scavenging excessive reactive oxygen species (ROS). A mechanistic study found the protective role of PCB2 is dependent on activating nuclear factor erythroid 2‐related factor 2 (Nrf2). PCB2 increased the expression of Nrf2 and its downstream antioxidant genes to attenuate the oxidative stress induced by HG in EPCs, which were abolished by knockdown of Nrf2 expression. An in vivo study showed that intraperitoneal administration of PCB2 promoted wound healing and angiogenesis in diabetic mice, which was accompanied by a significant reduction in ROS level and an increase in circulating EPC number. Taken together, our results indicate that PCB2 treatment accelerates wound healing and increases angiogenesis in diabetic mice, which may be mediated by improving the mobilization and function of EPCs.
Journal Article
Multifactorial Contributors to the Longevity of Dental Restorations: An Integrated Review of Related Factors
Purpose: This integrated review aims to identify and analyze the multifactorial contributors to the longevity of direct restorations, focusing on tooth-, patient-, and dentist-related factors. Materials and Methods: A search of the literature was performed using an electronic database, PubMed/Medline, Web of Science, and Scopus, on papers published between 1980 and 2024. The titles and abstracts of papers that evaluated aspects categorized into tooth-related, patient-related, and dentist-related factors influencing restoration failure were selected and screened. Full-text assessments were conducted, and the extracted data were compiled, summarized, and synthesized. The reference lists of the collected papers were also screened, and relevant citations were included in this review. Data were gathered from clinical and laboratorial studies, systematic reviews, and meta-analyses to provide a comprehensive understanding of restoration longevity. Results: Among the tooth-related factors, multiple-surface restorations, deep margins, tooth location, and tooth vitality significantly impact restoration survival. Patient-related factors such as medical conditions, risk predictors of caries, age, sex, parafunctional habits, smoking, periodontal health, number of restorations, and socioeconomic status all play crucial roles. Regarding dentist-related factors, the decision-making process, age, experience, and dentist manual dexterity are vital aspects. Furthermore, the technique used, including isolation methods for moisture control, as well as the type of dental practice (large group vs. small practice), notably influenced the restoration survival. Conclusions: The longevity of dental restorations is influenced by a complex interplay of tooth-related, patient-related, and dentist-related factors. Strategies to improve restoration outcomes should consider all these multifactorial contributors. Continuing professional education, diligent patient guidance on the factors that influence restoration survival, careful material selection and restorative technique, and tailored individual treatment are crucial factors to reduce failure rates and improve the lifespan of restorations.
Journal Article
Exploring the Use of Complementary and Alternative Medicine in Cancer Patients
In Australia, it is estimated that around 17% to 87% of cancer patients have used one form of complementary therapy during their cancer treatment. There are numerous reasons and contributing factors for cancer patients to consider using complementary and alternative medicine (CAM). CAM information and products are readily available. However, the level of evidence to support the benefits of use in the cancer setting is limited, and the associated adverse effects and interactions with conventional medicine may not be fully studied. Besides, not all health professionals favor the concept of integrative health approaches, or have the confidence in dealing with CAM due to a lack of knowledge and standardization of practices. A thematic review of the literature was performed on the main contributing factors to cancer patients’ use of CAM, as well as the current issues that may be encountered by the patients and health professionals.
Journal Article
Nrf2 attenuates inflammatory response in COPD/emphysema: Crosstalk with Wnt3a/β‐catenin and AMPK pathways
Chronic obstructive pulmonary disease (COPD) is characterized by persistent airflow limitation and abnormal inflammatory response. Wnt/β‐catenin and AMP‐activated protein kinase (AMPK) have been shown to modulate lung inflammatory responses and injury. However, it remains elusive whether Wnt/β‐catenin and AMPK modulate nuclear factor erythroid‐2 related factor‐2 (Nrf2)‐mediated protective responses during the development of emphysema. Here we showed that treatment with a Wnt pathway activator (LiCl) reduced elastase‐induced airspace enlargement and cigarette smoke extract (CSE)‐induced lung inflammatory responses in WT mice, which was associated with increased activation of Nrf2 pathway. Interestingly, these effects of LiCl were not observed in Nrf2−/− mice exposed to elastase. In normal human bronchial epithelial (NHBE) cells, Wnt3a overexpression up‐regulated, whereas Wnt3a knockdown further down‐regulated the levels of Nrf2 and its target proteins heme oxygenase‐1 (HO‐1) and NAD(P)H: quinone oxidoreductase 1 (NQO1) by CSE treatment. In contrast, Nrf2 deficiency did not have any effects on Wnt/β‐catenin pathway in mouse lungs and NHBE cells. Both elastase and CSE exposures reduced AMPK phosphorylation. A specific AMPK activator metformin increased Wnt3a, β‐catenin, Nrf2 phosphorylation and activation but reduced the levels of IL‐6 and IL‐8 in NHBE cells and mouse lungs exposed to CSE. Furthermore, Nrf2 deficiency abolished the protection of metformin against CSE‐induced increase in IL‐6 and IL‐8 in NHBE cells. In conclusion, Nrf2 mediates the protective effects of both Wnt3a/β‐catenin and AMPK on lung inflammatory responses during the development of COPD/emphysema. These findings provide potential therapeutic targets for the intervention of COPD/emphysema.
Journal Article
Sex, Gender, and Alcohol Use: Implications for Women and Low-Risk Drinking Guidelines
Alcohol use is coming under increasing scrutiny with respect to its health impacts on the body. In this vein, several high-income countries have issued low-risk drinking guidelines in the past decade, aiming to educate the public on safer levels of alcohol use. Research on the sex-specific health effects of alcohol has indicated higher damage with lower amounts of alcohol for females as well as overall sex differences in the pharmacokinetics of alcohol in male and female bodies. Research on gender-related factors, while culturally dependent, indicates increased susceptibility to sexual assault and intimate partner violence as well as more negative gender norms and stereotypes about alcohol use for women. Sex- and gender-specific guidelines have been issued in some countries, suggesting lower amounts of alcohol consumption for women than men; however, in other countries, sex- and gender-blind advice has been issued. This article reports on a synthesis of the evidence on both sex- and gender-related factors affecting safer levels of drinking alcohol with an emphasis on women’s use. We conclude that supporting and expanding the development of sex- and gender-specific low-risk drinking guidelines offers more nuanced and educative information to clinicians and consumers and will particularly benefit women and girls.
Journal Article
What Drives Hospitality Employees’ Trust in Service Robots?
As service robots become more prevalent in hospitality settings, understanding what shapes employees’ trust in these technologies is essential for fostering effective human–robot collaboration. Despite extensive research on customer trust and robot-related attributes, employee perspectives have received limited and fragmented attention. The aim of this study is to examine how human, robot, and organizational factors collectively influence employees’ trust in service robots, thereby offering a more comprehensive understanding of trust formation in hospitality contexts. To address this aim, this study adopts a three-dimensional trust framework (human, robot, and organizational factors) and provides the first comprehensive empirical test in the hospitality sector. Drawing on survey data from 301 frontline hospitality workers in the United States, we investigated how various human-, robot-, and organization-related factors influence employees’ trust in service robots using bootstrap multiple regression analysis. The results reveal that human factors, particularly employees’ attitudes toward and comfort with robots, emerged as dominant trust predictors. Surprisingly, organizational factors showed minimal direct impact, suggesting complex trust dynamics unique to hospitality contexts. These findings significantly expand existing human–robot interaction (HRI) theory and offer critical practical insights for hospitality managers integrating robots into frontline service.
Journal Article
Predicting anxiety and depression in elderly patients using machine learning technology
Anxiety and depression are two important mental health problems among the geriatric population. They are often undiagnosed and directly or indirectly responsible for various morbidities. Early and timely diagnosis has immense effect on appropriate management of anxiety and depression along with its co-morbidities. Owing to time constraint and enormous patient load, especially in developing county such as India it is hardly possible for a physician or surgeon to identify a geriatric patient suffering from anxiety and depression using any psychometric analysis tool. So, it is of utmost importance to develop a predictive model for automated diagnosis of anxiety and depression among them. This Letter aims to develop an appropriate predictive model, to diagnose anxiety and depression among older patient from socio-demographic and health-related factors, using machine learning technology. Ten classifiers were evaluated with a data set of 510 geriatric patients and tested with ten-fold cross-validation method. Highest prediction accuracy of 89% was obtained with random forest (RF) classifier. This RF model was tested with another data set from separate 110 older patients for its external validity. Its predictive accuracy was found to be 91% and false positive (FP) rate was 10%, compared with gold standard tool.
Journal Article