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Patients with diabetes who get coronavirus disease 2019 (COVID-19) are at risk of a severe disease course and mortality. Several factors especially the impaired immune response, heightened inflammatory response and hypercoagulable state contribute to the increased disease severity. However, there are many contentious issues about which the evidence is rather limited. There are some theoretical concerns about the effects of different anti-hyperglycaemic drugs. Similarly, despite the recognition of angiotensin converting enzyme 2 (ACE2) as the receptor for severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), and the role of ACE2 in lung injury; there are conflicting results with the use of angiotensin converting enzyme (ACE) inhibitors and angiotensin receptor blockers (ARB) in these patients. Management of patients with diabetes in times of restrictions on mobility poses some challenges and novel approaches like telemedicine can be useful. There is a need to further study the natural course of COVID-19 in patients with diabetes and to understand the individual, regional and ethnic variations in disease prevalence and course.

The advancement in technology especially in the field of artificial intelligence has opened up novel and robust ways to reanalyze the many aspects of human emotional behavior. One of such behavioral studies is the cultural impact on the expression and perception of human emotions. In-group advantage makes it easy for the people of the same cultural group to perceive each other’s emotions accurately. The goal of this research is to re-investigate human behavior regarding expression and perception of emotions in speech. The theoretical basis of this research is grounded on the dialect theory of emotions. For the purpose of this study, six datasets of audio speeches have been considered. The participants of these datasets belong to six different cultural areas. A fully automated, machine learning-based framework i.e. Support Vector Machine (SVM) is used to carry out this study. The overall emotion perception for all six cultural groups supports in-group advantage, whereas emotion wise analysis partially supports the In-group advantage.

The use of electric vehicles (EVs) to provide different grid services is becoming possible due to the increased penetration levels, mileage efficiencies, and useable battery sizes of EVs. One such application is providing reliability-as-a-service (RaaS) during short-term power outages. Instead of using a dedicated backup power source, EVs can be contracted to provide RaaS, which is an environmentally friendly solution with benefits for both building owners and EV owners. However, the presence of EVs at a particular location during different hours of the day and the availability of energy from EVs is uncertain. Therefore, in this study, a suitability analysis is performed concerning the use of EVs to provide RaaS for different types of buildings. First, the National Household Travel Survey (NHTS) survey data are used to estimate driver behavior, such as arrival/departure times, daily mileage, and traveling duration. Then, the usable battery size and mileage efficiency of EVs is extracted from the database of commercially available EVs. Based on these parameters, the daily energy consumption and available energy of EVs to provide RaaS are estimated. A suitability analysis is conducted for residential, commercial/industrial, and mixed buildings for both weekdays and holidays. The participation ratio of EV owners is varied between 10 and 90%, and nine cases are simulated for commercial/industrial buildings and multi-unit residential buildings. Similarly, the ratio of home-based EVs is varied between 5 and 50%, and 10 cases are tested for mixed buildings. The analysis shows that mixed buildings are the most suitable, while commercial/industrial buildings are the least suitable for using EVs to provide RaaS. To this end, an index is proposed to analyze and determine the desired ratio of EVs to be contracted from homes and workplaces for mixed buildings. Finally, the impact of EV fleet size on the available energy for RaaS is also analyzed.

Under the contemporary climate change, the Himalaya is reported to be warming at a much higher rate than the global average. However, little is known about the alpine vegetation responses to recent climate change in the rapidly warming Himalaya. Here we studied vegetation dynamics on alpine summits in Kashmir Himalaya in relation to measured microclimate. The summits, representing an elevation gradient from treeline to nival zone (3530-3740 m), were first surveyed in 2014 and then re-surveyed in 2018. The initial survey showed that the species richness, vegetation cover and soil temperature decreased with increasing elevation. Species richness and soil temperature differed significantly among slopes, with east and south slopes showing higher values than north and west slopes. The re-survey showed that species richness increased on the lower three summits but decreased on the highest summit (nival zone) and also revealed a substantial increase in the cover of dominant shrubs, graminoids, and forbs. The nestedness-resultant dissimilarity, rather than species turnover, contributed more to the magnitude of β-diversity among the summits. High temporal species turnover was found on south and east aspects, while high nestedness was recorded along north and west aspects. Thermophilization was more pronounced on the lower two summits and along the northern aspects. Our study provides crucial scientific data on climate change impacts on the alpine vegetation of Kashmir Himalaya. This information will fill global knowledge gaps from the developing world.

The increased intensity and frequency of natural disasters have attracted the attention of researchers in the power sector to enhance the resilience of power systems. Microgrids are considered as a potential solution to enhance the resilience of power systems using local resources, such as renewable energy sources, electric vehicles (EV), and energy storage systems. However, the deployment of an additional storage system for resilience can increase the investment cost. Therefore, in this study, the usage of existing EVs in microgrids is proposed as a solution to increase the resilience of microgrids with outages without the need for additional investment. In the case of contingencies, the proposed algorithm supplies energy to islanded microgrids from grid-connected microgrids by using mobile EVs. The process for the selection of EVs for supplying energy to islanded microgrids is carried out in three steps. Firstly, islanded and networked microgrids inform the central energy management system (CEMS) about the required and available energy stored in EVs, respectively. Secondly, CEMS determines the microgrids among networked microgrids to supply energy to the islanded microgrid. Finally, the selected microgrids determine the EVs for supplying energy to the islanded microgrid. Simulations have shown the effectiveness of the proposed algorithm in enhancing the resilience of microgrids even in the absence of power connection among microgrids.

Background: In Indonesia, coronary heart disease (CHD) and stroke are estimated to cause more than 470 000 deaths annually. In order to inform primary prevention policies, we estimated the sex- and age-specific burden of CHD and stroke attributable to five major and modifiable vascular risk factors: cigarette smoking, hypertension, diabetes, elevated total cholesterol, and excess body weight. Methods: Population attributable risks for CHD and stroke attributable to these risk factors individually were calculated using summary statistics obtained for prevalence of each risk factor specific to sex and to two age categories (<55 and ≥55 years) from a national survey in Indonesia. Age- and sex-specific relative risks for CHD and stroke associated with each of the five risk factors were derived from prospective data from the Asia-Pacific region. Results: Hypertension was the leading vascular risk factor, explaining 20%-25% of all CHD and 36%-42% of all strokes in both sexes and approximately one-third of all CHD and half of all strokes across younger and older age groups alike. Smoking in men explained a substantial proportion of vascular events (25% of CHD and 17% of strokes). However, given that these risk factors are likely to be strongly correlated, these population attributable risk proportions are likely to be overestimates and require verification from future studies that are able to take into account correlation between risk factors. Conclusions: Implementation of effective population-based prevention strategies aimed at reducing levels of major cardiovascular risk factors, especially blood pressure, total cholesterol, and smoking prevalence among men, could reduce the growing burden of CVD in the Indonesian population.

The COVID-19 pandemic has revealed the importance of good quality data for demonstrating the extent, nature and impact of ethnic and racial disparities within society.1 2 Where it has been available, data on race and ethnicity has long been used to highlight persistent inequalities in healthcare globally.3 Recent events of historical and political significance have also brought a renewed attention and momentum to these issues, for example, Black Lives Matter and Empire Windrush in the UK. In particular, people from minoritised ethnic groups may be concerned due to historical and recent abuses of power, and personal experiences of discrimination or insensitivity within healthcare.5 A Canadian study found that some patients were concerned ethnicity data collection could lead to negative stereotyping, and could affect their treatment.10 One participant who identified as Indigenous was apprehensive about revealing his ethnicity: I would feel insulted, offended, marginalized, targeted. Trust for public institutions varies by ethnic group, these variations are the result of persistent structural racism, cultural racism and experiences of discrimination.16 Lack of trust can manifest itself in real world health outcomes, including greater levels of vaccine hesitancy.16 The trust deficit is particularly noteworthy for ethnicity data collection; ethnicity is self-defined and so relies on an individual answering on their own behalf. The European Commission recommends the monitoring of ethnic equality data across all EU member states; however, only three countries (Ireland, Finland, UK) have placed a legal duty of data collection on public bodies.11 The historical and political context of mainland Europe means that in many countries, data on ethnic origin is regarded as highly politically sensitive and potentially dangerous.

The Lie group method is a powerful technique for obtaining analytical solutions for various nonlinear differential equations. This study aimed to explore the behavior of nonlinear elastic wave equations and their underlying physical properties using Lie group invariants. We derived eight-dimensional symmetry algebra for the (3+1)-dimensional nonlinear elastic wave equation, which was used to obtain the optimal system. Group-invariant solutions were obtained using this optimal system. The same analysis was conducted for the damped version of this equation. For the conservation laws, we applied Noether’s theorem to the nonlinear elastic wave equations owing to the availability of a classical Lagrangian. However, for the damped version, we cannot obtain a classical Lagrangian, which makes Noether’s theorem inapplicable. Instead, we used an extended approach based on the concept of a partial Lagrangian to uncover conservation laws. Both techniques account for the conservation laws of linear momentum and energy within the model. These novel approaches add an application of variational calculus to the existing literature. This offers valuable insights and potential avenues for further exploration of the elastic wave equations.

Despite the historical position of the F-expansion method as a method for acquiring exact solutions to nonlinear partial differential equations (PDEs), this study highlights its superiority over alternative auxiliary equation methods. The efficacy of this method is demonstrated through its application to solve the convective–diffusive Cahn–Hilliard (cdCH) equation, describing the dynamic of the separation phase for ternary iron alloys (Fe–Cr–Mo) and (Fe–X–Cu). Significantly, this research introduces an extensive collection of exact solutions by the auxiliary equation, comprising fifty-two distinct types. Six of these are associated with Weierstrass-elliptic function solutions, while the remaining solutions are expressed in Jacobi-elliptic functions. I think it is important to emphasize that, exercising caution regarding the statement of the term ’new,’ the solutions presented in this context are not entirely unprecedented. The paper examines numerous examples to substantiate this perspective. Furthermore, the study broadens its scope to include soliton-like and trigonometric-function solutions as special cases. This underscores that the antecedently obtained outcomes through the recently specific cases encompassed within the more comprehensive scope of the present findings.

The utilization of the Lie group method serves to encapsulate a diverse array of wave structures. This method, established as a robust and reliable mathematical technique, is instrumental in deriving precise solutions for nonlinear partial differential equations (NPDEs) across a spectrum of domains. Its applications span various scientific disciplines, including mathematical physics, nonlinear dynamics, oceanography, engineering sciences, and several others. This research focuses specifically on the crucial molecule DNA and its interaction with an external microwave field. The Lie group method is employed to establish a five-dimensional symmetry algebra as the foundational element. Subsequently, similarity reductions are led by a system of one-dimensional subalgebras. Several invariant solutions as well as a spectrum of wave solutions is obtained by solving the resulting reduced ordinary differential equations (ODEs). These solutions govern the longitudinal displacement in DNA, shedding light on the characteristics of DNA as a significant real-world challenge. The interactions of DNA with an external microwave field manifest in various forms, including rational, exponential, trigonometric, hyperbolic, polynomial, and other functions. Mathematica simulations of these solutions confirm that longitudinal displacements in DNA can be expressed as periodic waves, optical dark solitons, singular solutions, exponential forms, and rational forms. This study is novel as it marks the first application of the Lie group method to explore the interaction of DNA molecules.