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This study investigates the efficacy of using discarded textile (cotton and polycotton) and paper waste (newspaper and corrugated cardboard) as substrates to form sheets with optimum tensile strength. The effect of alkali treatment (sodium hydroxide (NaOH) and sodium bicarbonate (NaHCO3)), compressive loads (200 N and 500 N), and the use of binding agents (blackstrap molasses, sodium alginate, and cornstarch) were studied to optimize the tensile strength of homogeneous sheets. The alkali treatment using 5% NaOH for 5 h of soaking demonstrated the highest increase in tensile strength of 21% and 19% for cotton and newspaper, respectively. Increasing compressive load from 200 N to 500 N showed the highest increase in tensile strength of 37% and 42% for cotton and newspaper, respectively. Remarkably, among the binders, cornstarch at 20% concentration obtained an increase in tensile strength of 395%, 320%, 310%, and 185% for cotton, polycotton, corrugated cardboard, and newspaper sheets, respectively. The optimum results obtained from this study will be utilized to develop biodegradable seedling pots using discarded textile and paper waste.

The disruptive force of the COVID-19 pandemic is lessening in power and plans are being made for the postcrisis period, among which increasing the sustainability of higher education is of significant importance. The study aims at establishing students’ existing environment-related routines during their home confinement, as a basis for applying green measures to campus living once academic life is resumed with the physical presence of students. The collected data rely on self-reported information provided by 816 students from Politehnica University of Timisoara (Romania), collected via an online, anonymous survey. The novelty of the approach is that household environment-related routines are investigated during a crisis period, with the possibility to build upon the results to implement tailored measures to encourage or diminish environmentally relevant consumption by young, highly skilled individuals. The students display a moderate awareness of environmental issues and indicate consumption routines that may be steered towards an increased sustainability-conscious campus life, through the combined intervention of the university, city administration, and stakeholder involvement. The findings are used to explore the possible directions for action towards increasing or contributing to the territorial sustainability in the socio-ecological context of Timisoara, the largest university city in the western part of Romania via educational, managerial and policy interventions.

Protecting the health of farmworkers is a crucial issue. Previous studies report that safety training and educational interventions might increase farmworkers’ protective behaviors. The present study aimed to investigate the effectiveness of distributing a checklist as an interventional measure for pesticide protection in rural Asia, where pesticide poisoning is a major problem. This study was a community-based interventional study, using the distribution of a checklist with pesticide protective habits in Narail district, Bangladesh, with a total of 100 eligible males. Two questionnaire surveys were conducted before distributing the checklist and 25 days after. Change between the baseline and follow-up surveys was measured by frequency scores of protective behavior. The average pesticide-protective behavioral score increased from 4.58 in the baseline survey to 8.11 in the follow-up. Additionally, the checklist was more effective in the group with higher education, the younger group, and the group with lower pesticide-protective behavioral scores in the baseline survey. The paper checklist on protective behaviors against pesticide poisoning was effective because of the increase in the frequency of such positive behavior among farmworkers. Thus, intervention measures should be implemented to increase the knowledge and awareness regarding pesticide protection habits to protect the health of farmworkers.

Attention to the environment and its problems has undergone unprecedented growth in recent years [...]

The COVID-19 pandemic has impacted the management of non-communicable diseases in health systems around the world. This study aimed to understand the impact of COVID-19 on diabetes medicines dispensed in Australia. Publicly available data from Australia’s government subsidised medicines program (Pharmaceutical Benefits Scheme), detailing prescriptions by month dispensed to patients, drug item code and patient category, was obtained from January 2016 to November 2020. This study focused on medicines used in diabetes care (Anatomical Therapeutical Chemical code level 2 = A10). Number of prescriptions dispensed were plotted by month at a total level, by insulins and non-insulins, and by patient category (general, concessional). Total number of prescriptions dispensed between January and November of each year were compared. A peak in prescriptions dispensed in March 2020 was identified, an increase of 35% on March 2019, compared to average growth of 7.2% in previous years. Prescriptions dispensed subsequently fell in April and May 2020 to levels below the corresponding months in 2019. These trends were observed across insulins, non-insulins, general and concessional patient categories. The peak and subsequent dip in demand have resulted in a small unexpected overall increase for the period January to November 2020, compared to declining growth for the same months in prior years. The observed change in consumer behaviour prompted by COVID-19 and the resulting public health measures is important to understand in order to improve management of medicines supply during potential future waves of COVID-19 and other pandemics.

Our aim was to compere diabetes-related distress (DD) in young patients with type 1 diabetes mellitus (T1DM) and in their parents before and during the national COVID-19-related lockdown when schools operated on-line. Problems Areas in Diabetes-Child (PAID-Ch), Teen (PAID-T) and Parent (P-PAID-Ch, P-PAID-T) questionnaires in paper version were used to evaluate DD before COVID-19 pandemic (November 2019–February 2020) and during the lockdown (April 2020) the same surveys were performed by phone. We enrolled 76 patients (median age (Q1–Q3): 13.6 (11.8–15.2) years, 21 children, 55 adolescents, T1DM duration 3.7 (1.7–6.8) years). Initial PAID score was lower in teenage boys than in girls (34.0 (24.0–42.0) vs. 44.5 (40.0–50.5), p = 0.003). In teens PAID score decreased significantly during the lockdown (−3.0 (−11.0–3.0), p = 0.018), more in girls than boys (p = 0.028). In children (−3.0 (−14.0–7.0), p = 0.131) and parents PAID did not change (teens’ parents: 3.0 (−9.0–10.0), p = 0.376, children’s parents: −5.0 [−9.0–1.0], p = 0.227). In the studied group COVID-19 pandemic-related lockdown was associated with decrease in DD in teens with T1DM, particularly in girls, while no significant change in DD was observed in children or parents. DD decrease in teens during the pandemic should attract attention to the potential “rebound” of DD related to return to regular on-site school routine.

In competitive athletes, the differential diagnosis between nonpathological changes in cardiac morphology associated with training (commonly referred to as “athlete’s heart”) and certain cardiac diseases with the potential for sudden death is an important and not uncommon clinical problem. The use of noninvasive, fast, and cheap analytical techniques can help in making diagnostic differentiation and planning subsequent clinical strategies. Recent studies have demonstrated the role of gut microbiota and their metabolites in the onset and the development of cardiovascular diseases. Trimethylamine (TMA), a gut bacteria metabolite consisting of carnitine and choline, has recently emerged as a potentially toxic molecule to the circulatory system. The present work aims to develop a simple and cost-effective capillary electrophoresis-based method for the determination of TMA in biological samples. Analytical characteristics of the proposed method were evaluated through the study of its linearity (R2 > 0.9950) and the limit of detection and quantification (LOD = 1.2 µg/mL; LOQ = 3.6 µg/mL). The method shows great potential in high-throughput screening applications for TMA analysis in biological samples as a novel potential biomarker of cardiovascular diseases. The proposed electrophoretic method for the determination of TMA in biological samples from patients with cardiac disease is now in progress.

Fluctuating crude oil price and global environmental problems such as global warming and climate change lead to growing demand for the production of renewable chemicals as petrochemical substitutes. Butanol is a nonpolar alcohol that is used in a large variety of consumer products and as an important industrial intermediate. Thus, the production of butanol from renewable resources (e.g., biomass and organic waste) has gained a great deal of attention from researchers. Although typical renewable butanol is produced via a fermentative route (i.e., acetone-butanol-ethanol (ABE) fermentation of biomass-derived sugars), the fermentative butanol production has disadvantages such as a low yield of butanol and the formation of byproducts, such as acetone and ethanol. To avoid the drawbacks, the production of renewable butanol via non-fermentative catalytic routes has been recently proposed. This review is aimed at providing an overview on three different emerging and promising catalytic routes from biomass/organic waste-derived chemicals to butanol. The first route involves the conversion of ethanol into butanol over metal and oxide catalysts. Volatile fatty acid can be a raw chemical for the production of butanol using porous materials and metal catalysts. In addition, biomass-derived syngas can be transformed to butanol on non-noble metal catalysts promoted by alkali metals. The prospect of catalytic renewable butanol production is also discussed.

Health services quality and sustainability rely mainly on a qualified workforce. Adequately trained public health personnel protect and promote health, avert health disparities, and allow rapid response to health emergencies. Evaluations of the healthcare workforce typically focus on physicians and nurses in curative medical venues. Few have evaluated public health workforce capacity building or sought to identify gaps between the academic training of public health employees and the needs of the healthcare organizations in which they are employed. This project report describes the conceptual framework of “Sharing European Educational Experience in Public Health for Israel (SEEEPHI): harmonization, employability, leadership, and outreach”—a multinational Erasmus+ Capacity Building in Higher Education funded project. By sharing European educational experience and knowledge, the project aims to enhance professionalism and strengthen leadership aspects of the public health workforce in Israel to meet the needs of employers and the country. The project’s work packages, each jointly led by an Israeli and European institution, include field qualification analysis, mapping public health academic training programs, workforce adaptation, and building leadership capacity. In the era of global health changes, it is crucial to assess the capacity building of a well-qualified and competent workforce that enables providing good health services, reaching out to minorities, preventing health inequalities, and confronting emerging health challenges. We anticipate that the methods developed and the lessons learned within the Israeli context will be adaptable and adoptable by other countries through local and cultural adjustments.

A pilot-scale airlift bioreactor (ALBR) system was built and operated continuously for refinery excess sludge (RES) reduction. Combined ALBR and function-enhanced microbes (composed of photosynthetic bacteria and yeast) were integrated into the system. The pilot-scale ALBR was operated for 62 days, and the start-up time was 7 d. Continuous operation showed that the sludge reduction efficiency was more than 56.22%, and the water quality of the effluent was satisfactory. This study focused on investigating the effects of hydraulic retention time (HRT) on the stability of the system and the effect of sludge reduction. Under different HRT conditions of 40, 26.7, 20, and 16 h, the sludge reduction rates reached 56.22%, 73.24%, 74.09%, and 69.64%, respectively. The removal rates of chemical oxygen demand (COD) and total nitrogen (TN) decreased with decreasing HRT, whereas the removal rate of NH4+-N increased. The removal rate of total phosphorus (TP) was approximately 30%. Results indicate that the ALBR and function-enhanced microbe system can reduce sludge and treat sewage simultaneously, and the effluent is up to the national emission standard. Addition of function-enhanced microbes can promote the degradation of petroleum hydrocarbon substances in the sludge, especially alkanes with low carbon numbers. This study suggests that the optimal HRT for the system is 16 h. The total operation cost of the ALBR combined with the function-enhanced microbe system can be reduced by 50% compared with the cost of direct treatment of the RES system.

The coronavirus pandemic (COVID-19) has had multilevel effects on non-COVID-19 health and health care, including deferral of routine cancer prevention and screening and delays in surgical and other procedures. Health and health care use has also been affected by pandemic-related loss of employer-based health insurance, food and housing disruptions, and heightened stress, sleep disruptions and social isolation. These disruptions are projected to contribute to excess non-COVID-19 deaths over the coming decades. At the same time municipalities, health systems and individuals are making changes in response to the pandemic, including modifications in the environmental to promote health, implementation of telehealth platforms, and shifts towards greater self-care and using remote platforms to maintain social connections. We used a multi-level biopsychosocial model to examine the available literature on the relationship between COVID-19-related changes and breast cancer prevention to identify current gaps in knowledge and identify potential opportunities for future research. We found that COVID-19 has impacted several aspects of social and economic life, through a variety of mechanisms, including unemployment, changes in health care delivery, changes in eating and activity, and changes in mental health. Some of these changes should be reduced, while others should be explored and enhanced.

Theoretical models of suicide are based on risk factors associated with suicide, such as psychiatric pathology, genetics, epigenetics, functional brain disorders, and impaired decision making. In current clinical practice, the predominant risk model is the medical model, which posits that treating suicide risk is primarily a matter of treating psychiatric disorders. However, even comprehensive risk factor models cannot overcome the basic problem that, by their nature, they cannot accommodate the suicidal person’s psychological experience of suicidality. Risk factor models do not translate into effective treatment models. Suicide risk is highly personal and fluid, and is related to individual vulnerabilities and to person-specific events triggering suicidal thoughts and actions. Clinicians need treatment models that are meaningful to suicidal patients. Understanding the single person’s suicidality requires a patient-centered approach. Therapeutic interventions that effectively reduce the risk of suicidal behavior have been developed from general principles of psychotherapy. Therapy process factors associated with effective therapies are working alliance, validation of the individual patient’s thoughts and feelings, active treatment engagement. Psychological therapies need patients who are active participants in a collaborative working relationship between therapist and patient. The goal must be to jointly develop a meaningful understanding of the suicidal crisis. In view of the limited personal resources in health care systems it is important that effective therapies are brief and effective. Future research must aim to improve our understanding of the factors involved in effective therapies in order to optimize treatments for individuals at risk. This may also include the integration of biological risk factors in psychological treatment models.

Today, a person’s health literacy (HL) is perceived as a critical determinant for their health. It is well known that limited health literacy is associated with harmful health behaviours, the lower use of preventive services, problems in making use of healthcare resources and poor skills for the self-management of chronic disorders. This study analysed the level and factors associated with HL in high school students in southern Poland. The study is based on the data from a paper-and-pencil survey of high schools students in the Malopolska Voivodshop. The students were selected using a two-stage cluster random sampling procedure. The level of HL was assessed with the European Health Literacy Survey Questionnaire, consisting of 47 items. Univariate logistic and linear regression models were applied to analyse the association between general HL score and the main domain-specific indices. The respondents whose parents had attended University and came from more affluent families were less likely to demonstrate limited HL. There was a significant positive relationship between the self-assessment of the economic situation, size of accommodation, the level of expenditure on a mobile phone and receiving external support, the size of the book collection at home, and domain-specific HL sub-indices. In conclusion, among socio-demographic factors, the parents’ education is the only consistent predictor of the level of HL in high school students. Furthermore, most variables reflecting the economic status of the respondent’s family are significantly associated with the general HL score and its sub-indices.

With the vigorous development of the 5G industry, the characteristic hazardous waste, spent coppery etchant, was also produced in large quantities. In recent years, there are many companies that have begun to collect spent coppery etchant for the purpose of producing recycled products, such as copper sulfate, copper oxide, basic copper chloride, and copper powder, which often contain large amounts of heavy metals. However, due to the lack of relevant standards and applicable regulatory measures, some of the recycled products flow to the feed processing industry and even to the food processing industry. This study investigated the pollution status of heavy metals in recycled products of spent coppery etchant and evaluated the impact of recycled products exposure on human health. The results showed that the content of Zn was the highest, which was 21 times higher than the corresponding standard limit. Human health risk assessment indicated that the hazard quotients of As account for 87.5% of the entire HI value, while the average carcinogenic risk values of As for copper sulfate, copper oxide, basic copper chloride, and copper powder are 1.09 × 10−5, 3.19 × 10−5, 1.29 × 10−5, 7.94 × 10−6, respectively. Meanwhile, suggestions on the supervision of recycled products and the concentration limits of heavy metals in recycled products were put forward.

The article examines Israel’s experience in managing the COVID-19 vaccination program beginning in December 2020. Utilizing principles of mass casualty event management, such as triaging, flow of casualty care, and flexibility (among others), we analyze Israel’s vaccination program. The successful Israeli experience was found to be based on timely coordinated and adaptive health system logistics and operations, as well as cooperative population behaviors.

The increasing average life expectancy worldwide results in an elderly population with significant health care needs. However, dental care is often not a focus of care. It is well known that oral and overall health are directly related. Therefore, the Mini Dental Assessment (MDA) was developed to provide a simple analysis of oral health status, although it is currently only available in paper form, with all associated drawbacks, from illegible writing to the inability to quickly search the collected forms. This study aimed to develop a digital application (app) for mobile devices that can overcome the problems associated with paper forms. After the digital MDA was developed, its usability was evaluated by nurses, a questionnaire was answered, and it was compared to the analog MDA with patients in a pilot study. The usability of the app (System Usability Scale) was 95.18 ± 4.26, representing a very high usability. Furthermore, this app showed good clinical applicability. The results also showed that the digital MDA was accepted by nurses in their daily routine and was preferred to the analog MDA. A follow-up study with a higher number of subjects is highly recommended.

Background: Outside activities have decreased due to the spread of the COVID-19 since 2019, therefore, the need for education using information and communication technology (ICT) for older adults with mild cognitive impairment (MCI) has increased. This study systematically evaluated the effects of cognitive enhancement interventions using ICT on older adults with MCI. Methods: Six electronic databases (CINAHL, Cochrane CENTRAL, EMBASE, PubMed, RISS, and KISS) were searched for relevant articles published from 25 January to 10 February, 2021. Results: As a result of the systematic literature review, 12 research papers were finally selected as the literature for quality evaluation, and 11 final papers were selected, excluding one in the quality evaluation. From the synthesis in this study, it was found that cognitive intervention using ICT showed a statistically significant positive effect on cognitive function when compared with various control groups (SMD = 0.4547, p &lt, 0.001, 95% CI: 0.1980–0.7113). Conclusions: Through this study, cognitive intervention using ICT showed a small effect size for older adults with mild cognitive impairment, and statistically significant results were found.

Wolfram Syndrome (WS) is a rare neurodegenerative disease with autosomal recessive inheritance and characterized by juvenile onset, non-autoimmune diabetes mellitus and later followed by optic atrophy leading to blindness, diabetes insipidus, hearing loss, and other neurological and endocrine dysfunctions. A wide spectrum of neurodegenerative abnormalities affecting the central nervous system has been described. Among these complications, neurogenic bladder and urodynamic abnormalities also deserve attention. Urinary tract dysfunctions (UTD) up to end stage renal disease are a life-threatening complication of WS patients. Notably, end stage renal disease is reported as one of the most common causes of death among WS patients. UTD have been also reported in affected adolescents. Involvement of the urinary tract occurs in about 90% of affected patients, at a median age of 20 years and with peaks at 13, 21 and 33 years. The aim of our narrative review was to provide an overview of the most important papers regarding urological impairment in Wolfram Syndrome. A comprehensive search on PubMed including Wolfram Syndrome and one or more of the following terms: chronic renal failure, bladder dysfunction, urological aspects, and urinary tract dysfunction, was done. The exclusion criteria were studies not written in English and not including urinary tract dysfunction deep evaluation and description. Studies mentioning general urologic abnormalities without deep description and/or follow-up were not considered. Due to the rarity of the condition, we considered not only papers including pediatric patients, but also papers with pediatric and adult case reports

The United Nations Universal Declaration of Human Rights is widely acknowledged as a landmark document in the history of human rights. Drafted by representatives from all over the world, the declaration was proclaimed by the United Nations General Assembly in Paris on 10 December 1948 (General Assembly resolution 217 A) as a common standard for all peoples and all nations. The declaration sets out a series of articles that articulate a number of fundamental human rights to be universally protected. Article 23 of the declaration relates to the right to work and states that people have a human right to work, or engage in productive employment, and may not be prevented from doing so. The right to work is enshrined in international human rights law through its inclusion in the International Covenant on Economic, Social and Cultural Rights, where the right to work emphasizes economic, social and cultural development. This paper presents ongoing research that highlights how a disruptive co-design approach contributes to upholding UN Article 23 through the creation of a series of innovative working practices developed with people living with dementia. The research, undertaken in collaboration with several voluntary and third sector organizations in the UK, looks to break the cycle of prevailing opinions, traditional mindsets, and ways-of-doing that tend to remain uncontested in the health and social care of people living with dementia. As a result, this research has produced a series of innovative work opportunities for people living with dementia and their formal and informal carers that change the perception of dementia by showing that people living with dementia are capable of designing and making desirable products and offering much to UK society after diagnosis. In this ongoing research, the right to continue to work for people living with dementia post-diagnosis in creative and innovative ways has clearly helped to reconnect them to other people, helped build their self-esteem, identity and dignity and helped keep the person with dementia connected to their community, thus delaying the need for crisis interventions. This paper reports on a series of future work initiatives for people living with dementia where we have used design as a disruptive force for good to ensure that anyone diagnosed with dementia can exercise their right to work and engage in productive and rewarding employment.

Increasing land utilization, population aggregation and strong land–sea interaction make coastal areas an ecologically fragile environment. The construction of an ecological security pattern is important for maintaining the function of the coastal ecosystem. This paper takes Jiaodong Peninsula in China, a hilly coastal area, as an example for evaluating landscape ecological risk within a comprehensive framework of “nature–neighborhood–landscape”, based on spatial principal component analysis, and it constructs the ecological security pattern based on the minimum cumulative resistance model (MCR). The results showed that the overall level of ecological risk in the study area was medium. The connectivity between the areas of low landscape ecological risk was relatively low, and the high risk areas were concentrated in the north of the Peninsula. A total of 11 key ecological corridors of three types (water, green space and road corridors) and 105 potential corridors were constructed. According to the ecological network pattern, landscape ecological optimization suggestions were proposed: key corridors in the north and south of Jiaodong Peninsula should be connected; urban development should consider current ecological sources and corridors to prevent landscape fragmentation; and the ecological roles of potential corridors should be strengthened. This paper can provide a theoretical and practical basis for ecological planning and urban master planning in coastal areas in the future.

Environmental factors in time and space play a critical role in advancing the sustainable development of the fresh agricultural product supply chain. This paper, availing the panel data of 31 Chinese provinces from 2008 to 2019, constructs a system of indicators assessing the development of the fresh agricultural product supply chain, and obtains the comprehensive development level in the Entropy Weight Method (EWM). Furthermore, it establishes a comparison between optimal solutions generated by the Instrumental Variables Method (IVM) and the Generalized Method of Moments (GMM) over the endogeneity issue of variables, creates the comparison between the weighted regression methods of Geographically Weighted Regression (GWR) and Multi-scale Geographic Weighted Regression (MGWR), and obtains the relationship among the 14 environmental factors in their spatio-temporal impacts on the development of the fresh agricultural product supply chain. The results indicate that: (1) the environmental influencing factors in this paper have significant endogenous problems and various environmental factors impact on the fresh agricultural product supply chain in different trends and to different degrees. (2) With different bandwidths, the environmental factors could impact the fresh agricultural product supply chain to greatly varied degrees, demonstrating a strong attribute of regional correlation.

The epidemic of psychosocial risks continues to increase and the COVID-19 pandemic has even worsened this threat on workers’ health. This inexorable and evidence-based rise seems to be impervious to the preventive strategies proposed for more than 40 years. Hypotheses are proposed to explain this serious problem that drastically impacts public health and the economy. The objectives of this paper are to present, in this broad context of societal and cultural changes, how the present shift in management paradigms may represent opportunities to reduce work-related diseases. In the first part of this paper, we will summarize the situation on three main issues and their relation with psychosocial risks: (1) evolution of the occupational safety and health field, (2) change in the nature of work, and (3) emerging models of governance. In the second part, we will describe, through a few examples (among many others), how emerging models of corporate governance may reduce and prevent stress and burnout. Work is changing fundamentally, and this impacts workers’ (and managers’) health and well-being, that is why approaches in line with these changes are necessary. The COVID-19 pandemic has produced major changes in work organization. This may offer promising opportunities to reanalyze working conditions for a better control of occupational diseases and stress with all the benefits these improvements will bring for society and for individuals.

The increasing amount of waste in cities poses a great challenge for sustainable development. Promoting waste sorting is one of the priorities for various levels of public authorities in the context of the rapid growth of waste generation all around China. To achieve this goal, waste-sorting policies should be precisely designed to ensure successful waste reduction at all stages. Previous studies have neglected the spillover effects of different regulatory policies, which may affect the overall goal of reducing waste by influencing different waste production stages. This paper fills this gap by comparing the spillover effects of two typical waste-sorting policies on sustainable consumption behaviours through a survey conducted in Shanghai and Beijing (control group). By combining quasi-natural experiment and questionnaire methods, this paper analyses data through a mediation test to explore the spillover effects between different regulatory policy groups and the effects of the mediation psychological factors. Results show that a penalty policy significantly decreases people’s sustainable consumption behaviours through a negative spillover effect, while a voluntary participation policy significantly increases sustainable consumption behaviours through a positive spillover effect. Results can provide implications for policymaking in waste management and other pro-environmental fields to help cities become more sustainable by shifting multiple behaviours.

Since the beginning of the COVID-19 pandemic in March 2020, national and international authorities started to develop and update datasets to provide data to researchers, journalists and health care providers as well as public opinion. These data became one of the most important sources of information, which are updated daily and analysed by scientists in order to investigate and predict the spread of this epidemic. Despite this positive reaction from both national and international authorities in providing aggregated information on the diffusion of COVID-19, different challenges have been underlined in previously published studies. Different papers have discussed strengths and weaknesses of these types of datasets by focusing on different quality perspectives, which include the statistical methods adopted to analyse them, the lack of standards and models in the adoption of data for their management and distribution, and the analysis of different data quality characteristics. These studies have analysed datasets at the general level or by focusing the attention on specific indicators such as the number of cases or deaths. This paper further investigates issues and opportunities in the diffusion of these datasets under two main perspectives. At the general level, it analyses how data are organized and distributed to scientific and non-scientific communities. Moreover, it further explores the indicators adopted to describe the spread of the COVID-19 epidemic while also highlighting the level of detail used to describe them in terms of gender, age ranges and territorial units. The paper focuses on six European countries: Belgium, France, Germany, Italy, Spain and UK.

By considering the recently proposed definitions and metrics, oral healthcare quality management (OHQM) emerges as a distinct field in the wider healthcare area. The goal of this paper is to systematically review quality management initiatives (QMIs) implementation by dental clinics. The research methodology approach is a review of 72 sources that have been analyzed using the Context–Intervention–Mechanism–Outcome Framework (CIMO). The analysis identifies five mechanisms that explain how quality management initiatives are implemented by dental clinics. The simplest QMIs implementations are related to (1) overall quality. The next ones, in terms of complexity, are related to (2) patient satisfaction, (3) service quality, (4) internal processes improvement, and (5) business outcomes. This paper is the first attempt to provide a critical review of this topic and represents an important advancement by providing a theoretical framework that explains how quality management is implemented by practitioners in this field. The results can be used by scholars for advancing their studies related to this emerging research area and by healthcare managers in order to better implement their quality management initiatives.

The basic premise of regional ecological construction would be to scientifically and effectively grasp the characteristics of land use change and its impact on landscape ecological risk. The research objects of this paper are the typical areas of the Yellow River Basin in China and “process-change-drive” as the logical main line. Moreover, this paper is based on multi-period land use remote sensing data from 2000 to 2020, the regional land use change process and influencing factors are identified, the temporal and spatial evolution and response process of landscape ecological risk are discussed, and the land use zoning control strategy to reduce ecological risk is put forward. The results indicated: (1) The scale and structure of land use show the characteristics of “many-to-one” and “one-to-many”, (2) the process of land use change is affected by the alternation of multiple factors. The natural environment and socio-economic factors dominate in the early stage and the location and policy factors have a significant impact in the later stage, (3) the overall landscape ecological risk level and conversion rate show a trend of “high in the southeast, low in the northwest”, shift from low to high and landscape ecological risks gradually increase, and (4) in order to improve the regional ecological safety and according to the characteristics of landscape ecological risk and spatial heterogeneity, we should adopt the management and control zoning method and set different levels of control intensity (from key intensity to strict intensity to general intensity), and develop differentiated land use control strategies.

Enhancing urban vitality is a key goal for both the government and ordinary urban residents, and creating this vitality is emphasized in China’s urban development strategy. Enhancing urban vitality through the rational design of urban forms is a leading topic of Western urban research. An urban growth pattern (UGP) reflects the dual characteristics of a static pattern and the dynamic evolution of the external urban form. It affects urban vitality by influencing the spatial allocation of internal structural elements and patterns in the adjacent location. The cellular automata (CA) mode can effectively simulate the aggregation process of urban growth (infilling expansion or edge expansion). However, it does not simulate the diffusion of urban growth, specifically the evolution of outlying expansion. In addition, CA focuses on learning, simulating, and building knowledge about geographic processes, but does not spatially optimize collaborative land use against multiple objectives or model multi-scale land use. As such, this paper applies a coupling model called the “promoting urban vitality model,” based on cellular automata (CA) and genetic algorithm (GA) (abbreviated as UV-CAGA). UV-CAGA optimally allocates cells with different UGPs, creating a city form that promotes urban vitality. Wuhan, the largest city in Central China, was selected as a case study to simulate and optimize its urban morphology for 2025. The main findings were as follows. (1) The urban vitality of the optimized urban form scheme was 4.8% higher than the simulated natural expansion scheme. (2) Compared to 2015, after optimization, the simulated sizes of the newly increased outlying, edge, and infilling areas in 2025 were 6.51 km2, 102.69 km2, and 23.48 km2, respectively, these increases accounted for 4.90%, 77.32%, and 17.68%, respectively, of the newly increased construction land area. This indicated that Wuhan is expected to have a very compact urban form. (3) The infilling expansion type resulted in the highest average urban vitality level (0.215), the edge expansion type had the second highest level (0.206), outlying growth achieved the lowest vitality level (0.199). The UV-CAGA model proposed in this paper improves on existing geographical process simulation and spatial optimization models. The study successfully couples the “bottom-up” CA model and “top-down” genetic algorithm to generate dynamic urban form optimization simulations. This significantly improves upon traditional CA models, which do not simulate the “diffusion” process. At the same time, the spatial optimization framework of the genetic algorithm in the model also provides insights related to other effects related to urban form optimization, such as urban environmental security, commuting, and air pollution. The integration of related research is expected to enrich and improve urban planning tools and improve the topic’s scientific foundation.

(1) Background: The appearance of physician rating websites (PRWs) has raised researchers’ interest in the online healthcare field, particularly how users consume information available on PRWs in terms of online physician reviews and providers’ information in their decision-making process. The aim of this study is to consistently review the early scientific literature related to digital healthcare platforms, summarize key findings and study features, identify literature deficiencies, and suggest digital solutions for future research. (2) Methods: A systematic literature review using key databases was conducted to search published articles between 2010 and 2020 and identified 52 papers that focused on PRWs, different signals in the form of PRWs’ features, the findings of these studies, and peer-reviewed articles. The research features and main findings are reported in tables and figures. (3) Results: The review of 52 papers identified 22 articles for online reputation, 15 for service popularity, 16 for linguistic features, 15 for doctor–patient concordance, 7 for offline reputation, and 11 for trustworthiness signals. Out of 52 studies, 75% used quantitative techniques, 12% employed qualitative techniques, and 13% were mixed-methods investigations. The majority of studies retrieved larger datasets using machine learning techniques (44/52). These studies were mostly conducted in China (38), the United States (9), and Europe (3). The majority of signals were positively related to the clinical outcomes. Few studies used conventional surveys of patient treatment experience (5, 9.61%), and few used panel data (9, 17%). These studies found a high degree of correlation between these signals with clinical outcomes. (4) Conclusions: PRWs contain valuable signals that provide insights into the service quality and patient treatment choice, yet it has not been extensively used for evaluating the quality of care. This study offers implications for researchers to consider digital solutions such as advanced machine learning and data mining techniques to test hypotheses regarding a variety of signals on PRWs for clinical decision-making.

Discrete-event simulation (DES) is a stochastic modeling approach widely used to address dynamic and complex systems, such as healthcare. In this review, academic databases were systematically searched to identify 231 papers focused on DES modeling in healthcare. These studies were sorted by year, approach, healthcare setting, outcome, provenance, and software use. Among the surveys, conceptual/theoretical studies, reviews, and case studies, it was found that almost two-thirds of the theoretical articles discuss models that include DES along with other analytical techniques, such as optimization and lean/six sigma, and one-third of the applications were carried out in more than one healthcare setting, with emergency departments being the most popular. Moreover, half of the applications seek to improve time- and efficiency-related metrics, and one-third of all papers use hybrid models. Finally, the most popular DES software is Arena and Simul8. Overall, there is an increasing trend towards using DES in healthcare to address issues at an operational level, yet less than 10% of DES applications present actual implementations following the modeling stage. Thus, future research should focus on the implementation of the models to assess their impact on healthcare processes, patients, and, possibly, their clinical value. Other areas are DES studies that emphasize their methodological formulation, as well as the development of frameworks for hybrid models.

Active transportation (AT) is widely viewed as an important target for increasing participation in aerobic physical activity and improving health, while simultaneously addressing pollution and climate change through reductions in motor vehicular emissions. In recent years, progress in increasing AT has stalled in some countries and, furthermore, the coronavirus (COVID-19) pandemic has created new AT opportunities while also exposing the barriers and health inequities related to AT for some populations. This paper describes the results of the December 2019 Conference on Health and Active Transportation (CHAT) which brought together leaders from the transportation and health disciplines. Attendees charted a course for the future around three themes: Reflecting on Innovative Practices, Building Strategic Institutional Relationships, and Identifying Research Needs and Opportunities. This paper focuses on conclusions of the Research Needs and Opportunities theme. We present a conceptual model derived from the conference sessions that considers how economic and systems analysis, evaluation of emerging technologies and policies, efforts to address inclusivity, disparities and equity along with renewed attention to messaging and communication could contribute to overcoming barriers to development and use of AT infrastructure. Specific research gaps concerning these themes are presented. We further discuss the relevance of these themes considering the pandemic. Renewed efforts at research, dissemination and implementation are needed to achieve the potential health and environmental benefits of AT and to preserve positive changes associated with the pandemic while mitigating negative ones.

Human bodies are continuously generating information about our health. This information can be assessed by physiological tools that gauge bio-signals such as blood pressure, heart rate, and blood glucose. Computer scientists are obtaining knowledge on new technologies to manage these bio-signals using a range of equations and approaches. Currently, real-time monitoring, cloud computing, edge computing, and the Internet of Things are key technologies that can be applied in the environmental research and public health field. In light of these and many other challenges, a Special Issue entitled Computing Techniques for Environmental Research and Public Health has been dedicated to address the current status, challenges, and future research priorities for environmental research and public health. Starting from the above considerations, this Special Issue aims to investigate the impact of adopting advanced and innovative information computing-based algorithms in environmental research and public health field applications, including ones that take advantage of recent big data, compression, multichannel, sensor, and prediction techniques. This edition of the Special Issue is focused primarily on computing techniques for environmental research and public health applications with a particular emphasis on artificial intelligence and signal processing platforms. This issue is intended to provide a highly recognized international forum to present recent advances in the International Journal of Environmental Research and Public Health. We welcome both theoretical contributions as well as papers describing interesting applications. Papers were invited for this Special Issue considering aspects of this problem, including: • public health; • bio-signal processing; • the Internet of Things; • real-time monitoring; • cloud computing. After review, a total of seven papers have been accepted for publication in this issue.

At present, a smart city from the perspective of the United Nations Sustainable Development Goals (SDGs) emphasizes the importance of providing citizens with promising health and well-being. However, with the continuous impact of coronavirus disease 2019 (COVID-19) and the increase of city population, the health of citizens is facing new challenges. Therefore, this paper aims to assess the relationship between building, environment, landscape design, art therapy (AT), and therapeutic design (TD) in promoting health within the context of sustainable development. It also summarizes the existing applied research areas and potential value of TD that informs future research. This paper adopts the macro-quantitative and micro-qualitative research methods of bibliometric analysis. The results show that: the built environment and AT are related to sustainable development, and closely associated with health and well-being, the application of TD in the environment, architecture, space, and landscape fields promotes the realization of SDGs and lays the foundation for integrating digital technologies such as Building Information Modeling (BIM) into the design process to potentially solve the challenges of TD, and the principle of TD can consider design elements and characteristics from based on people’s health needs to better promote human health and well-being.

Total Worker Health® (TWH) interventions that utilize integrated approaches to advance worker safety, health, and well-being can be challenging to design and implement in practice. This may be especially true for the food service industry, characterized by high levels of injury and turnover. This paper illustrates how we used TWH Implementation Guidelines to develop and implement an organizational intervention to improve pain, injury, and well-being among low-wage food service workers. We used the Guidelines to develop the intervention in two main ways: first, we used the six key characteristics of an integrated approach (leadership commitment, participation, positive working conditions, collaborative strategies, adherence, data-driven change) to create the foundation of the intervention, second, we used the four stages to guide integrated intervention planning. For each stage (engaging collaborators, planning, implementing, evaluating for improvement), the Guidelines provided a flexible and iterative process to plan the intervention to improve safety and ergonomics, work intensity, and job enrichment. This paper provides a real-world example of how the Guidelines can be used to develop a complex TWH intervention for food service workers that is responsive to organizational context and addresses targeted working conditions. Application of the Guidelines is likely transferable to other industries.

The global coronavirus (COVID-19) pandemic has tremendously reshaped the tourism industry and destinations worldwide. Tourism destinations and the travel market require empirical research to support their post-pandemic strategies, especially in relation to the influences of changing perceptions of tourism risks, experience, and behavioural intention. This paper aims to propose a conceptual model and its hypotheses of the perceived tourism risks of natural and man-made disasters to explain the associations between the expected travel experience and ultimate travel behaviour. This paper provides a foundation for further empirical study based on a literature review and discussion. Several areas of theoretical development are identified for immediate research: (1) comparison of self-interpretation and understanding of multi-dimensional tourism risks of natural and man-made complexity in epidemics across a great variety of geographical and geo-political territories, (2) a complex web of influence to changing safety concerns and risk perception by information dissemination, (3) the effect of destination selection or hesitation in travel intention caused by changing destination image, and (4) local perception of the epidemic and health crisis. Destination authorities are recommended to (1) strengthen the preparedness and emergency responses of an effective disaster management process, (2) maintain the emotional solidarity of both tourists and local residents, and (3) mitigate multiple dimensions of the perceived risks, mainly associated with the health and psychological risks of those affected.

This paper examines how economic growth and renewable energy consumption are associated with air pollution using a dynamic panel approach. Focusing on several major air pollutants, namely, particulate matter, sulfur dioxide, nitrogen oxide, and carbon monoxide, this paper tests the environmental Kuznets hypothesis and determines whether the use of renewable energy sources contributes to a reduction in air pollution. Data from a balanced panel of 145 countries for the period between 2000 and 2014 was used for the estimation of the dynamic panel model. The results of the dynamic panel model showed inverted U-shaped curves for the relationship between economic development and particulate matter and sulfur dioxide emissions. The results also revealed that increasing renewable energy consumption contributes to an improvement in air quality. Moreover, it was found that urbanization tends to decrease sulfur dioxide and nitrogen oxide emissions, while trade openness reduces particulate matter and carbon monoxide emissions but increases sulfur dioxide emissions.

As the continuous changes in environmental regulations have a non-negligible impact on the innovation activities of micro subjects, and economic policy uncertainty has become one of the important influencing factors to be considered in the development of enterprises. Therefore, based on the panel data of Chinese high-tech enterprises from 2012–2017, this paper explores the impact of heterogeneous environmental regulations on firms’ green innovation from the perspective of economic policy uncertainty as a moderating variable. The empirical results show that, first, market-incentivized environmental regulation instruments have an inverted U-shaped relationship with innovation output, while voluntary environmental regulation produces a significant positive impact. Second, the U-shaped relationship between market-based environmental regulation and innovation output becomes more pronounced when economic policy uncertainty is high. However, it plays a negative moderating role in regulating the relationship between voluntary-based environmental regulation and innovation output. This paper not only illustrates the process of technological innovation by revealing the intrinsic mechanism of environmental regulation on firm innovation, but also provides insights for government in environmental governance from the perspective of economic policy uncertainty as well.

Recently, the integration of state-of-the-art technologies, such as modern sensors, networks, and cloud computing, has revolutionized the conventional healthcare system. However, security concerns have increasingly been emerging due to the integration of technologies. Therefore, the security and privacy issues associated with e-health data must be properly explored. In this paper, to investigate the security and privacy of e-health systems, we identified major components of the modern e-health systems (i.e., e-health data, medical devices, medical networks and edge/fog/cloud). Then, we reviewed recent security and privacy studies that focus on each component of the e-health systems. Based on the review, we obtained research taxonomy, security concerns, requirements, solutions, research trends, and open challenges for the components with strengths and weaknesses of the analyzed studies. In particular, edge and fog computing studies for e-health security and privacy were reviewed since the studies had mostly not been analyzed in other survey papers.

The artificial light at night (ALAN) present in many cities and towns has a negative impact on numerous organisms that live alongside humans, including bats. Therefore, we investigated if the artificial illumination of the historic Wisłoujście Fortress in Gdańsk, Poland (part of the Natura 2000 network), during nighttime events, which included an outdoor electronic dance music (EDM) festival, might be responsible for increased light pollution and the decline in recent years of the pond bat (Myotis dasycneme). An assessment of light pollution levels was made using the methods of geographical information system (GIS) and free-of-charge satellite remote sensing (SRS) technology. Moreover, this paper reviewed the most important approaches for environmental protection of bats in the context of ecological light pollution, including International, European, and Polish regulatory frameworks. The analysis of this interdisciplinary study confirmed the complexity of the problem and highlighted, too, the need for better control of artificial illumination in such sensitive areas. It also revealed that SRS was not the best light pollution assessment method for this particular case study due to several reasons listed in this paper. As a result, the authors’ proposal for improvements also involved practical recommendations for devising suitable strategies for lighting research and practice in the Natura 2000 Wisłoujście Fortress site located adjacent to urban areas to reduce the potential negative impact of ALAN on bats and their natural habitats.

Six Sigma has been widely used in the health field for process or quality improvement, constituting a quite profusely investigated topic. This paper aims at exploring why some studies have more academic and societal impact, attracting more attention from academics and health professionals. Academic and societal impact was addressed using traditional academic metrics and alternative metrics, often known as altmetrics. We conducted a systematic search following the PRISMA statement through three well-known databases, and identified 212 papers published during 1998–2019. We conducted zero-inflated negative binomial regressions to explore the influence of bibliometric and content determinants on traditional academic and alternative metrics. We observe that the factors influencing alternative metrics are more varied and difficult to apprehend than those explaining traditional impact metrics. We also conclude that, independently of how the impact is measured, the paper’s content, rather than bibliometric characteristics, better explains its impact. In the specific case of research on Six Sigma applied to health, the papers with more impact address process improvement focusing on time and waste reduction. This study sheds light on the aspects that better explain publications’ impact in the field of Six Sigma application in health, either from an academic or a societal point of view.

The COVID-19 pandemic has strongly affected the dynamics of Emergency Departments (EDs) worldwide and has accentuated the need for tackling different operational inefficiencies that decrease the quality of care provided to infected patients. The EDs continue to struggle against this outbreak by implementing strategies maximizing their performance within an uncertain healthcare environment. The efforts, however, have remained insufficient in view of the growing number of admissions and increased severity of the coronavirus disease. Therefore, the primary aim of this paper is to review the literature on process improvement interventions focused on increasing the ED response to the current COVID-19 outbreak to delineate future research lines based on the gaps detected in the practical scenario. Therefore, we applied the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to perform a review containing the research papers published between December 2019 and April 2021 using ISI Web of Science, Scopus, PubMed, IEEE, Google Scholar, and Science Direct databases. The articles were further classified taking into account the research domain, primary aim, journal, and publication year. A total of 65 papers disseminated in 51 journals were concluded to satisfy the inclusion criteria. Our review found that most applications have been directed towards predicting the health outcomes in COVID-19 patients through machine learning and data analytics techniques. In the overarching pandemic, healthcare decision makers are strongly recommended to integrate artificial intelligence techniques with approaches from the operations research (OR) and quality management domains to upgrade the ED performance under social-economic restrictions.

With the rapid growth of foreign direct investment (FDI), PM2.5 pollution in Chinese cities is increasing. Based on panel data for 271 Chinese cities from 2003 to 2016, this paper uses the dynamic spatial fixed-effects Durbin model to analyze the correlation between FDI and PM2.5 pollution and the effect of FDI on urban PM2.5 concentrations, as mediated by industrial structure transformation, which is clarified using Stata/SE 16.0. The results showed that PM2.5 pollution in China has significant spatial spillover effects, and the pollution haven hypothesis is applicable to Chinese cities. The industrial structure partially mediates the relationship between FDI and PM2.5. This paper proposes that local governments should promote the market-oriented reform of FDI to create a more convenient, legalized, and international environment for FDI and innovate the governance philosophy of only reducing the existing emissions. A top-level design and sound market supervision system of PM2.5 control are also needed.

In the context of public health emergency management, it is worth studying ways to mobilize the enthusiasm of government, community, and residents. This paper adopts the method of combining evolutionary game and system dynamics to conduct a theoretical modeling and simulation analysis on the interactions of the behavioral strategies of the three participants. In response to opportunistic behavior and inadequate supervision in the static reward and punishment mechanism, we introduced a dynamic reward and punishment mechanism that considers changes in the social environment and the situation of epidemic prevention and control. This paper proves that the dynamic reward and punishment mechanism can effectively suppress the fluctuation problem in the evolutionary game process under static scenarios and achieve better supervision results through scenario analysis and simulation experiments.

In the United States, American Indian and Alaska Native (AI/AN) people are frequently under- or misrepresented in research and health statistics. A principal reason for this disparity is the lack of collaborative partnerships between researchers and tribes. There are hesitations from both academic Western scientists and tribal communities to establish new partnerships due to differences in cultural and scientific understanding, from data ownership and privacy to dissemination and project expansion. An infamous example is the mishandling of samples collected from the Havasupai Tribe by Arizona State University (ASU) scientists, leading to a legal battle between the tribe and ASU and ending in a moratorium of research with the Havasupai people. This paper will explore three successful and positive collaborations with a large and small tribe, including how the partnerships were established and the outcomes of the collaboration. In addition, the paper will provide perspective of what needs to be addressed by Western scientists if productive collaborations with tribal groups are to be established.

This paper applied landscape indexes to evaluate the size, form, and structure of green spaces in the mountainous city of Chongqing and found that green spaces benefit from certain advantages in size, but the network suffered from low heterogeneity and limited interconnectivity. To ensure the integrity and continuity of ecological processes and improve the efficiency of ecosystem services (ES), the authors used Geographic Information System (GIS) software to conduct adaptability evaluation and adjacent buffer analysis for the existing green spaces, wetlands, rivers, and other landscapes with relatively high capacity for ES. We designed a comprehensive map of potential areas for UGS expansion by superimposing the maps obtained from adaptability evaluation and buffer analysis. We also proposed some strategies that respect, consider, and evaluate aspects and special features of urban environment to optimize green space planning and improve ES efficiency, such as protection of important areas, development of green corridors, and careful consideration of ecological processes and complex functions in urban areas. Based on these strategies, the paper put forth suggestions for green space planning to improve ES efficiency that can function as foundation for subsequent green space planning.

In the past 30 years, China’s industrialization level has developed rapidly, and agricultural green development (AGD) is facing severe challenges. The research on the temporal and spatial features of the coupling and coordination of industrialization and agricultural green development is a key issue to promote the sustainable development of agriculture. This paper takes China’s industrialization and AGD level as the research object, and uses panel data from 31 provinces in China from 1990 to 2019 to construct an evaluation index system for industrialization and AGD. This paper uses the coupling coordination degree model and spatial autocorrelation analysis method to calculate, test and analyze the temporal and spatial features of the coupling coordination level of industrialization and AGD. The results show that: this paper compares the industrialization and AGD levels during the study period and finds that China’s industrialization development level is on the rise as a whole, and the AGD level shows a downward trend first and then rises later. Through the horizontal comparison of different regions, this paper finds that there is a large regional imbalance in the level of industrialization and AGD. The coupling and coordination level of industrialization and AGD has always been primary. From the time point of view, coupling coordination degree shows a trend of first decline and then rise. From a spatial point of view, coupling coordination degree varies greatly among provinces, with the eastern, central and western regions decreasing successively. The level of coupling coordination has obvious positive autocorrelation in spatial distribution, and presents significant spatial agglomeration characteristics in space. The research results can provide a theoretical basis for regionally differentiated governance of the coordinated development of industrialization and AGD, and promote coordinated development.

(1) Background: Although the number of people infected with COVID-19 has increased over time, its effects on workplace accidents are still poorly understood. On the one hand, COVID-19 can reduce workplace accidents through contracted economic activities or changes in work methods. On the other hand, it can increase workplace accidents by spreading in the workplace. The main purpose of this paper is to examine how COVID-19 affected workplace accidents in Korea during the early part of the pandemic. (2) Methods: This paper utilizes the administrative data on workplace accidents in Korea collected by Korea Occupational Safety and Health Agency. In particular, we use monthly data from February 2016 to August 2020. This period was chosen to rule out the effect from the Middle East Respiratory Syndrome outbreak in 2015 and to include COVID-19 effects in 2020, given the available data. To examine the impact of COVID-19 on workplace injury and illness, we estimate fixed effects regression models, allowing us to control for group and time effects. (3) Results: COVID-19 was generally found to reduce workplace accidents in Korea, particularly through a reduction in occupational diseases. However, we also found that COVID-19 increased occupational injuries for males and workers in the transportation industry. We provide some evidence that these workers experienced an increase in workload and were unable to change work methods including working from home during the COVID-19 pandemic. (4) Conclusions: Our results indicate that to reduce workplace accidents, government interventions should be directed at workers who are unable to change work methods and who are likely to suffer an increase in work burden due to COVID-19.

Medical education refers to education and training delivered to medical students in order to become a practitioner. In recent decades, medicine has been radically transformed by scientific and computational/digital advances—including the introduction of new information and communication technologies, the discovery of DNA, and the birth of genomics and post-genomics super-specialties (transcriptomics, proteomics, interactomics, and metabolomics/metabonomics, among others)—which contribute to the generation of an unprecedented amount of data, so-called ‘big data’. While these are well-studied in fields such as medical research and methodology, translational medicine, and clinical practice, they remain overlooked and understudied in the field of medical education. For this purpose, we carried out an integrative review of the literature. Twenty-nine studies were retrieved and synthesized in the present review. Included studies were published between 2012 and 2021. Eleven studies were performed in North America: specifically, nine were conducted in the USA and two studies in Canada. Six studies were carried out in Europe: two in France, two in Germany, one in Italy, and one in several European countries. One additional study was conducted in China. Eight papers were commentaries/theoretical or perspective articles, while five were designed as a case study. Five investigations exploited large databases and datasets, while five additional studies were surveys. Two papers employed visual data analytical/data mining techniques. Finally, other two papers were technical papers, describing the development of software, computational tools and/or learning environments/platforms, while two additional studies were literature reviews (one of which being systematic and bibliometric).The following nine sub-topics could be identified: (I) knowledge and awareness of big data among medical students; (II) difficulties and challenges in integrating and implementing big data teaching into the medical syllabus; (III) exploiting big data to review, improve and enhance medical school curriculum; (IV) exploiting big data to monitor the effectiveness of web-based learning environments among medical students; (V) exploiting big data to capture the determinants and signatures of successful academic performance and counteract/prevent drop-out; (VI) exploiting big data to promote equity, inclusion, and diversity; (VII) exploiting big data to enhance integrity and ethics, avoiding plagiarism and duplication rate; (VIII) empowering medical students, improving and enhancing medical practice; and, (IX) exploiting big data in continuous medical education and learning. These sub-themes were subsequently grouped in the following four major themes/topics: namely, (I) big data and medical curricula; (II) big data and medical academic performance; (III) big data and societal/bioethical issues in biomedical education; and (IV) big data and medical career. Despite the increasing importance of big data in biomedicine, current medical curricula and syllabuses appear inadequate to prepare future medical professionals and practitioners that can leverage on big data in their daily clinical practice. Challenges in integrating, incorporating, and implementing big data teaching into medical school need to be overcome to facilitate the training of the next generation of medical professionals. Finally, in the present integrative review, state-of-art and future potential uses of big data in the field of biomedical discussion are envisaged, with a focus on the still ongoing “Coronavirus Disease 2019” (COVID-19) pandemic, which has been acting as a catalyst for innovation and digitalization.

It is the scientific way to promote the transformation and optimization of an industrial structure to promote the improvement of its green total factor productivity (GTFP) by formulating environmental regulation policies. Based on the GTFP panel data of 30 provinces in China from 2004 to 2017, this paper takes the “Air Pollution Control and Prevention Action Plan” (APCP Action Plan) as the proxy dummy variable of environmental regulation, and uses the difference-in-differences (DID) model to explore the impact of the implementation of the APCP Action Plan on GTFP. In addition, by constructing the industrial structure optimization index, this paper analyzes how the APCP Action Plan policy affects GTFP through the transformation and optimization of industrial structure. The following basic conclusions are obtained: First, environmental regulation policies like the APCP Action Plan can improve GTFP. Second, the APCP Action Plan has regional heterogeneity in promoting GTFP in different regions. The policy only significantly affects the GTFP in the Pearl River Delta region in southern China. Third, the “quantity” and “quality” of the optimization of industrial structure will weaken the promoting effect of the APCP Action Plan on GTFP. In contrast, the rationalization of industrial structure will aggravate this promoting effect.

In this paper, we employ a directional distance function to estimate the opportunity cost arising from environmental regulations in China’s industrial sector. The change of opportunity cost is decomposed mathematically into two components including technical change and input change. Our results show that the opportunity cost attributed to environmental regulation is nil in some regions. The change of opportunity cost is marginal at the national level, as the positive effect of technical change is canceled out by the negative impact of input change on opportunity cost. Built on our mathematical decomposition, we further estimate the effects of environmental regulations on opportunity cost using a mediation model. It shows that environmental regulation has a significantly positive direct effect and a significantly negative indirect effect through foreign direct investment on opportunity cost. Our findings suggest, firstly, that inward FDI in China’s industrial sector represents relatively dirty production technology, and, secondly, industrial production has transited towards a less carbon-intensive input mix. This paper, therefore, provides new insights for the recent dynamics of carbon abatement performance of China’s industrial sector with policy implications.

Background: Cardiovascular disease is a key health condition associated with tobacco use, however, clinical measures are not typically possible in population-based studies. In this paper, we assess the reliability and validity of self-reported cardiovascular risk factors and diseases in a large nationally representative study of tobacco use and health outcomes. Methods: This paper analyzes self-reported cardiovascular risk factors and disease among adults age 40 years and older based on U.S. nationally representative data from the Population Assessment of Tobacco and Health (PATH) Study. Prevalence of cardiovascular risk factors (self-reported high blood pressure, high cholesterol, diabetes and family history of premature heart disease, BMI ≥ 35, and tobacco use) and cardiovascular disease (self-reported heart attack, stroke and/or congestive heart failure (CHF)) were considered along with ratings of physical functioning, fatigue, and general health. Results: Self-reported cardiovascular disease was found to be associated with functional health measures (walking up a flight of stairs) and general ratings of health. Prospective analyses found strong correlations between sequential data collection waves for history of hypertension, elevated cholesterol and CHF, while more modest correlations were noted for stroke and heart attack. The overall prevalence of cardiovascular disease and hypertension was comparable to those from the National Health and Nutrition Examination Survey (NHANES). Conclusions: These analyses suggest reliability and concurrent validity regarding self-reported cardiovascular risk factors and disease assessed in the PATH Study.