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Under extremely cold weather, traditional winter clothing may not be adequate to keep warm in the harsh environment. The paper aims to discuss this issue.

Wearable heat-generating (electric heating) clothing which covers the thermal sensitive zone of the human body can protect the human body from hypothermia. Existing heatable jacket in the market using carbon fiber is relatively expensive, complicated and require a lengthy manufacturing time.

Through experimental evaluation, the textile treated by plasma-assisted metal coating (PAC) has demonstrated excellent stability in temperature during the heating process.

This paper introduces an innovative, low-cost PAC technology using optimized plasma-assisted metallic deposition that is able to preserve the physical properties of the textile.

The purpose for writing this article is derived from the misery and chaos prevalent in the world due to the coronavirus pandemic – since late 2019 and still continuing as of December 2020.

A blockchain-based solution to verify the country visit trail and disease and treatment history of the passengers who arrive at the immigration counters located at various national borders and entry points is proposed. A fuzzy inference based suspect identifier system is also presented in this article that could be utilized to make further decisions based on the degree of suspicion observed on a particular passenger.

This paper attempted to put forth a blockchain-based system which consumes the healthcare and visit trail summary of a passenger (appearing for an interview before an immigration officer) and forwards it to a fuzzy inference system to reach to a conclusion that the passenger should be advised to self-quarantine, detained, or should be allowed to enter. Such a system would help to make correct decisions at the immigration counters to check pandemic diseases, like COVID-19, right at the entry points.

The implications of this work are manifold. First, the proposed framework works independent of the type of pandemic and is a readymade tool to check the spread of disease through infected human carriers. Second, the proposed framework will keep the mortality rates under check, which would give ample time for the authorities to save the lives of the people with co-morbidities and age vulnerabilities (Vichitvanichphong et al., 2018). Third, it is a general phenomenon to restrict the flights from the country where the first few cases of infection are discovered; however, the infected person, at the same time, might travel through alternative routes. The blockchain-enabled proposed framework ensures the detection of such cases at no other cost. Finally, the solution may appear costly in the first place, but it has the potential to hold back the revenue of the countries that would otherwise be spent on reactive measures.

As of now no other study or research article provides the solution to the biggest problem persists in the world in this way. The contribution is original and worth applying.

Michale Sadler PhD reports form the conference, Biotechnology in the Food Industry – New Applications and Noval Approaches

This study assessed the effectiveness of malaria classroom corner (MCC), school-based intervention in the promotion of basic malaria awareness and common control practices among children of primary school age.

A quasi-experimental design was employed, involving 206 children of primary 5 and 6 classes from two randomly selected public primary schools in Owerri, South Eastern Nigeria. The MCC was designed and set up in the intervention school (with 103 children) while the control school (with 103 children) was offered malaria health talk. Structured pre-tested questionnaire was used to collect data pre- and post-intervention in both schools. Data was analysed using Statistical Package – Stata version 14.1 (Stata Corp, College Station, TX, USA).

Results show that there was a significant enhancement of basic malaria awareness (p = 0.0003) and common preventive and management practices (p = 0.0202) among children in the intervention primary school compared to those in the control primary school.

The study did not account for actual behaviour change, as its scope was within basic malaria awareness and common control practices.

This approach could enhance awareness and proactiveness of school children towards malaria prevention and overall health consciousness.

This could help in achieving a healthy population of school children with a positive effect on their school performance.

The MCC could provide a simple, participatory and effective approach for the promotion of basic malaria awareness and common control practices among primary school-age children in malaria endemic areas. Such children could, in turn, become malaria conversation drivers and behaviour change agents in their homes and communities, thereby contributing to the malaria elimination efforts.

This review provides an overview of recent advances in electrochemical sensors for analyte detection in saliva, highlighting their potential applications in diagnostics and health care. The purpose of this paper is to summarize the current state of the field, identify challenges and limitations and discuss future prospects for the development of saliva-based electrochemical sensors.

The paper reviews relevant literature and research articles to examine the latest developments in electrochemical sensing technologies for saliva analysis. It explores the use of various electrode materials, including carbon nanomaterial, metal nanoparticles and conducting polymers, as well as the integration of microfluidics, lab-on-a-chip (LOC) devices and wearable/implantable technologies. The design and fabrication methodologies used in these sensors are discussed, along with sample preparation techniques and biorecognition elements for enhancing sensor performance.

Electrochemical sensors for salivary analyte detection have demonstrated excellent potential for noninvasive, rapid and cost-effective diagnostics. Recent advancements have resulted in improved sensor selectivity, stability, sensitivity and compatibility with complex saliva samples. Integration with microfluidics and LOC technologies has shown promise in enhancing sensor efficiency and accuracy. In addition, wearable and implantable sensors enable continuous, real-time monitoring of salivary analytes, opening new avenues for personalized health care and disease management.

This review presents an up-to-date overview of electrochemical sensors for analyte detection in saliva, offering insights into their design, fabrication and performance. It highlights the originality and value of integrating electrochemical sensing with microfluidics, wearable/implantable technologies and point-of-care testing platforms. The review also identifies challenges and limitations, such as interference from other saliva components and the need for improved stability and reproducibility. Future prospects include the development of novel microfluidic devices, advanced materials and user-friendly diagnostic devices to unlock the full potential of saliva-based electrochemical sensing in clinical practice.

This paper proposes a progressive, multi-level framework for diagnosing maintenance performance: rapid performance health checks of key performance for different equipment groups and end-to-end process diagnostics to further locate potential performance issues. A question-based performance evaluation approach is introduced to support the selection and derivation of case-specific indicators based on diagnostic aspects.

The case research method is used to develop the proposed framework. The generic parts of the framework are built on existing maintenance performance measurement theories through a literature review. In the case study, empirical maintenance data of 196 emergency shutdown valves (ESDVs) are collected over a two-year period to support the development and validation of the proposed approach.

To improve processes, companies need a separate performance measurement structure. This paper suggests a hierarchical model in four layers (objective, domain, aspect and performance measurement) to facilitate the selection and derivation of indicators, which could potentially reduce management complexity and help prioritize continuous performance improvement. Examples of new indicators are derived from a case study that includes 196 ESDVs at an offshore oil and gas production plant.

Methodological approaches to deriving various performance indicators have rarely been addressed in the maintenance field. The proposed diagnostic framework provides a structured way to identify and locate process performance issues by creating indicators that can bridge generic evaluation aspects and maintenance data. The framework is highly adaptive as data availability functions are used as inputs to generate indicators instead of passively filtering out non-applicable existing indicators.

The purpose of this chapter was to develop a framework for comprehensive business diagnostics, which can be integrated into the management of small and medium-sized businesses.

The chapter proposes a multiloop model of comprehensive business diagnostics, which provides the company with timely and objective information about the dynamics of its key performance indicators. The model allows enterprises of the real sector to optimize the information acquiring process with the help of the express diagnostics indicators and ensure the high quality and efficiency of the obtained information. Testing of the multiloop model at the Pavlovo Posad Shawl Manufactory JSC involved three stages: express diagnostics (ED), general diagnostics (GD), and comprehensive diagnostics (CD).

The results determined the need to move to the comprehensive diagnostics (CD) loop of the model. The approbation of the suggested model at the shawl manufacture, particularly the CD loop, allowed the authors to identify the key factors influencing the company's main economic and financial indicators.

The proposed multiloop model can be used at enterprises with different forms of ownership, including small and medium-sized businesses, both in Russia and abroad.

A multiloop model of comprehensive business diagnostics provides managerial staff with qualitative real-time information that helps them make informed and effective management decisions.

The proposed multiloop model allows businesses to acquire data about the dynamics of key indicators, determine the factors' impacts on key financial and economic indicators, and ensure high efficiency of management decisions with minimal cost.

The purpose of this study is to develop a testing method for tin pest in tin – copper (SnCu) alloys. Tin pest is the allotropic transformation of white β-tin (body-centered tetragonal structure) into gray α-tin (diamond cubic structure) at temperatures < 13.2°C.

Bulk samples of Sn99Cu1 weight per cent (purity, 99.9 weight per cent) were cast in the form of roller-shaped ingots with a diameter of 1.0 cm and a height of 0.7 cm. The samples were then divided into four groups. The first group included samples artificially inoculated with α-tin powder. The second group was inoculated in the same way as the samples from the first group but additionally subjected to mechanical pressing. The third group of ingots was only subjected to mechanical pressing. The fourth group of samples consisted of as-received roller-shaped ingots.All samples were divided into two groups and kept either at −18°C or at −30°C for the low-temperature storage test. For tin pest identification, a visual inspection was made, using a Hirox digital microscope over 156 days at intervals not longer than 14 days. The plot of the transformation rate, presented as the average increase in the area of α-tin warts in time, was also determined. To demonstrate the differences between regions of β- and α-tin, scanning ion microscopy observations using the focused ion beam technique was performed.

The first symptoms of tin pest were observed for the inoculated, mechanically pressed samples stored at −18°C, as well as those at −30°C, after less than 14 days. In the first stage of transformation, the rate was higher at −30°C for some time but, after about 75 days of storage at sub-zero temperatures, the rate at −30°C became lower compared to the rate at −18°C. Inoculation via the application of substances which are structurally similar to α-tin was efficient for the proposed new approach of rapid testing only when applied with simultaneous mechanical pressing. Infection from pressed-in seeds, leading to conventional seeded growth, was more rapid than infection in contact with seeds (without mechanical pressing), where the transition mechanism was induced by the epitaxial growth of metastable ice.

The new rapid method for the diagnostic testing of the susceptibility of different SnCu alloys to tin pest in a period much shorter than 14 days (within single days for storage at −30°C) is proposed and described. The test procedure described in this paper produced results several times quicker than conventional procedures, which may take years. In effect, the behavior of tin alloys in the face of tin pest may be predicted much more easily and much earlier. The same procedure can be applied to other SnCu alloys used in electronics (and in other areas), if the test samples are prepared in a similar manner.

Healthcare innovations for bottom-of-pyramid populations face considerable risks and few economic incentives. Can entrepreneurial innovators provide new solutions for global health? This chapter examines how a technology enterprise built a collaborative network and supportive ecosystem making it possible to steer an innovation for TB patients through discovery, development, and delivery. Ecosystem resources were mobilized and upstream and downstream co-innovation risks were mitigated to commercialize a new diagnostic test. Detailed evidence on this innovation for TB care uses ecosystem analysis to clarify core issues in the context of joint value creation. The case study shows how resources from private and public partners can be leveraged and combined by the focal firm to build joint value and to lower execution, co-innovation, and adoption risks in healthcare ecosystems combating diseases of poverty.