Search

Passive immunotherapy with plasma derived from convalescent patients recovering from SARS-CoV-2 infection can be a promising approach in the treatment of COVID-19 patients. It is important that blood establishments are ready to satisfy requests for immune plasma by defining the requirements applicable to plasma donors and the standards for preparation, qualification, storage, distribution, and control of product use. This Position paper aims to give recommendations on the biological characteristics of a plasma preparation from convalescent donors and to support the evaluation of this therapeutic approach in more rigorous investigations.

There is a large value in making Pulp and Paper mills more energy efficient. ABB has developed an energy assessment service where opportunities to save energy in the paper machine are identified. The energy assessment is done by quantifying energy flows, benchmarking energy users, data mining and steam sensitivity analysis and by experiments and additional measurements at the paper machine. Energy quantification helped in identifying main energy consumer, benchmarking was useful to assess the gap between operating performance and best performance whereas data mining and steam sensitivity analysis helped in studying the impact of key operating variables on performance of paper machines. After the assessment an action plan was presented to the mill for energy efficiency improvement together with a return on investment.

Solid waste always produce negative impacts to the environment, thus effective solutions must be implemented. However, most people are not concerned of the importance of recycling. At the Universiti Kebangsaan Malaysia (UKM) which has already launched the sustainable campus programme in 2007, the initiative to managing the solid waste and conducting the recycling programs were advocated through the Zero Waste Campus Initiative (ZWCI), where the team are committed to do the awareness, practices and enforcement regarding solid waste management in UKM. It would be undesirable if these initiatives to educate the majority of the community of UKM were not put into practice. To solve this problem, a study has been conducted to determine an effective method of recycling management at UKM in providing quality service that encouraged UKM's community to recycle. The effectiveness of recycling programs is influenced by a number of factors such as proper service facilities and good management system. Paper recycling boxes in each office which is one of recycling component that play important role to educate UKM staff and awareness of importance recycling system in waste management campus. This paper discusses the efforts carried out at UKM to create an operational system and implement efficient recycling management by improving the current management system.

Most influenza vaccines are generally safe, but influenza vaccines can cause rare serious adverse events. Some adverse events, such as fever and febrile seizures, are more common in children than adults. There can be differences in the safety of vaccines in different populations due to underlying differences in genetic predisposition to the adverse event. Live attenuated vaccines have not been studied adequately in children under 2 years of age to determine the risks of adverse events; more studies are needed to address this and several other priority safety issues with all influenza vaccines in children. All vaccines intended for use in children require safety testing in the target age group, especially in young children. Safety of one influenza vaccine in children should not be extrapolated to assumed safety of all influenza vaccines in children. The low rates of adverse events from influenza vaccines should not be a deterrent to the use of influenza vaccines because of the overwhelming evidence of the burden of disease due to influenza in children.

We study the evolution of deformation on a quasi 2D paper sample during fatigue and creep experiments. Paper is a fibrous material, sensitive to various parameters (humidity, temperature, history effect). As for many materials, the lifetime varies a lot. Basquin's law claims that the number of cycles at break in fracture tests has a power-law dependence on the external load amplitude; Monkman-Grant relationship predicts that lifetime is proportional to the minimum strain rate during creep. The main question is therefore: is it possible to predict the time-dependent rupture? We perform creep and cyclic tests on paper samples. The main tools of investigation are acoustic emission (AE) -based analysis and digital image correlation (DIC). Via the AE, one can follow the damage evolution in samples, like microcrack formation that releases elastic energy. The DIC instead works well as a tool to measure at great accuracy both global and local deformation fields. From these, local strain rates can be derived, which then can be used to understand the microscopic dynamics that lie behind a certain rheology or sample response. The issue is to predict the break by looking at the sample-to-sample variation and by comparing experiments.

This paper reports on an on-going action research that enquires into the academic writing of a project paper by international post-graduate students enrolled at Universiti Kebangsaan Malaysia. Preliminary observations reveal that many of these students are underprepared for the task, citing cross-cultural limitations stemming from differences in teaching and learning styles vis-avis here and their home countries. They also claim that they are not prepared for the autonomy that is presented in the data collecting process and the writing of the paper. This action research aims to address the problem with a focus on the Statement of Problem. Data for the study were collected through semi-structured questionnaires, interviews and document analysis. The researchers believe that if intervention is provided at the early stages of the writing, these novice writers should be able to achieve academic socialization.

Current studies agree on the need of training university students in various competences. Among them, writing stands out as an essential competence. This study analyzes the abstract produced by Spanish PhD candidates in the context of an academic writing workshop. These abstracts were rewritten as a result of peers’ and supervisors’ reviews. The purpose is to analyze the construction of this type of text in relation to its content categories. The results attest a series of challenges faced by students and help teachers in the design of their teaching instruction.

Ethics and communication with patients are basic transversal skills for the Degrees in Medicine, Physiotherapy and Nutrition. In this model, senior students use video to create simulated clinical cases with ethics and communication components, and conduct academic mentoring using these cases. To ensure quality video recordings, the students are introduced to visual language by students of the Master's in Communication, thus completing the learning cycle.

Australia produces both black and brown coal and is the world's fourth largest producer of black coal, after China, USA and India. Australian underground coal mines operate under controlled safety codes. The establishment of the mine safety management system, including the 1994 outburst management plan, contributed to a significant improvement in mine safety leading to non-fatality in outburst related incidences since 1994. The management of outburst risk, as a part of the overall safety and health management system is described. Also discussed are the introduction of outburst threshold limit values and the desorption rate index which forms the basis for determining safe mining conditions along with the “Authority to Mine” process The measures taken and lessons learned from safe mining of Australia's outburst prone mines represent an opportunity for improved mining safety in other countries, such as China.. The role of the Australian Coal Association Research Program, which supports research in critical areas such as outburst risk control and management, is also discussed.

Background: The full reopening of schools in September 2020 was associated with an increase in COVID-19 cases and outbreaks in educational settings across England. Methods: Primary and secondary schools reporting an outbreak (≥2 laboratory-confirmed cases within 14 days) to Public Health England (PHE) between 31 August and 18 October 2020 were contacted in November 2020 to complete an online questionnaire. Interpretation: There were 969 school outbreaks reported to PHE, comprising 2% (n = 450) of primary schools and 10% (n = 519) of secondary schools in England. Of the 369 geographically-representative schools contacted, 179 completed the questionnaire (100 primary schools, 79 secondary schools) and 2,314 cases were reported. Outbreaks were larger and across more year groups in secondary schools than in primary schools. Teaching staff were more likely to be the index case in primary (48/100, 48%) than secondary (25/79, 32%) school outbreaks (P = 0.027). When an outbreak occurred, attack rates were higher in staff (881/17,362; 5.07; 95%CI, 4.75–5.41) than students, especially primary school teaching staff (378/3852; 9.81%; 95%CI, 8.90–10.82%) compared to secondary school teaching staff (284/7146; 3.97%; 95%CI, 3.79–5.69%). Secondary school students (1105/91,919; 1.20%; 95%CI, 1.13–1.28%) had higher attack rates than primary school students (328/39,027; 0.84%; 95%CI, 0.75–0.94%). Conclusions: A higher proportion of secondary schools than primary schools reported a COVID-19 outbreak and experienced larger outbreaks across multiple school year groups. The higher attack rate among teaching staff during an outbreak, especially in primary schools, suggests that additional protective measures may be needed. Funding: PHE

Background: We aimed to describe changes in characteristics and treatment strategies of hospitalised patients with COVID-19 and detail the mortality trend over time. Methods: Observational cohort study of all consecutive patients admitted ≥ 48 h to Hospital Clinic of Barcelona for COVID-19 (1 March–30 September 2020). Findings: A total of 1645 consecutive patients with COVID-19 were assessed over a 7-month period. Overall mortality (≤30 days) was 9.7% (159 patients), 7.7% in patients hospitalised in regular wards and 16.7 % in patients requiring ICU admission. Overall mortality decreased from 11.6% in the first month to 1.4% in the last month, reflecting a progressive, significant downward trend (p for trend 700 ng/mL (OR 2.3, CI 1.3–4.1), ferritin>489 ng/mL (OR 1.9; CI 1.5–3.2), C-RP>7 mg/dL (OR 2.6; CI 1.5–4.6), and shorter duration from symptom onset to hospital admission (OR 1.11; CI 1.04–1.17) were factors associated with 30-day mortality at hospital admission. Conversely, hospital admission in the last months (OR 0.80; CI 0.65–0.98) was significantly associated with lower mortality. Interpretation: In-hospital mortality has decreased in patients with COVID-19 over the last, few months, even though main patient characteristics remain similar. Several changes made when managing patients may explain this decreasing trend. Our study provides current data on mortality of patients hospitalised with COVID-19 that might be useful in establishing quality of standard of care. Funding: EIT Health, European Union´s Horizon 2020 Research and Innovation Programme), EDRD. PPA [CM18/00132], NGP [FI19/00133], and CGV [FIS PI18/01061], have received grants from Ministerio de Sanidad y Consumo, ISCIII. Resumen: Contexto: Nuestro objetivo es describir los cambios en las características y las estrategias de tratamiento de los pacientes hospitalizados por COVID-19, y detallar la tendencia de la mortalidad en el tiempo. Métodos: Estudio observacional de cohortes de todos los pacientes consecutivos, ingresados por COVID-19 durante más de 48 horas, en el Hospital Clínic de Barcelona (del 1 de marzo al 30 de septiembre de 2020). Resultados: Un total de 1645 pacientes consecutivos fueron evaluados durante un período de 7 meses. La mortalidad global (≤30 días) fue del 9.7% (159 pacientes): 7.7% en pacientes hospitalizados en salas convencionales, y 16.7% en pacientes que requirieron ingreso en UCI. La mortalidad global disminuyó del 11.6% en el primer mes al 1.4% en el último mes evaluado, reflejando una progresiva y significativa tendencia a la baja (p para la tendencia 700 ng/mL (OR 2.3; CI 1.3–4.1), ferritina>489 ng/mL (OR 1.9; CI 1.5–3.2), PCR>7 mg/dL (OR 2.6; CI 1.5–4.6), y una menor duración desde el inicio de síntomas a la hospitalización (OR 1.11; CI 1.04–1.17) fueron factores asociados a la mortalidad intrahospitalaria a 30 días. Por el contrario, el ingreso hospitalario previo en los últimos meses (OR 0.80; CI 0.65–0.98) se asoció significativamente a una menor mortalidad. Discusión: La mortalidad intrahospitalaria ha disminuido en los pacientes con COVID-19 durante los últimos meses, incluso siendo similares las características de los pacientes. Algunos cambios realizados en el manejo de estos pacientes podrían explicar esta tendencia decreciente. Nuestro estudio aporta datos actualizados en la mortalidad de los pacientes hospitalizados con COVID-19, que podrían ser útiles de cara a establecer unos cuidados estándar de calidad. Financiación: EIT Health, European Union´s Horizon 2020 Research and Innovation Programme, EDRD. PPA [CM18/00132], NGP [FI19/00133] y CGV [FIS PI18/01061], han recibido becas del Ministerio de Sanidad y Consumo, ISCIII.

This paper based on the images of the primary short circuited melted mark (PSM) and secondary short-circuited melted mark(SSM), set out to demonstrate the application of image processing in fire material evidence identification. Because there are few researches about the accurate description for image of different situation, it is difficult to further study the differences between PSM and SSM. therefore, in this paper, the image processing technique, as an accurate description based on quantitative analysis method is put forward, and it is found that the images can be extracted out of contour and texture characteristics, which can be processed with the statistical means, so as to classify the PSM and SSM from the morphologically point of view accurately.

Due to the rapid increase in price of resources, the role of energy management and utilisation has become significant in processing industry. Industries can be more competitive by increasing the energy efficiency and eliminating waste. In this research, an old-style paper plant situated in China has been selected for the case study. The purpose of the study is to test whether the energy usage is reasonable and to exploit the potential of waste as a resource for its production process. To do so, a huge data of the paper plant are obtained, and then based on these figures, a model has been established to find out the potential wastes and thermal energy loss of the process. The simulation results revealed that the mill's energy use is quite reasonable, however, findings found that there are still further possibility for organic waste to be reused.

The paper based on the exemplary affordable housing projects in Tonglu County explores a set of cost-effective external wall thermal insulating system to meet the characteristic requirements of small-size affordable housing with strict cost control, enhance the quality of the well-being project, i.e. the affordable housing as a whole, allow lowincome and poorly-housed groups to enjoy livability deriving from the energy saving technology, and provide certain references for external wall thermal insulating design of affordable housing in the future.

The dissolved CO 2 accumulation has become an important factor restricting production in the high-density recirculating aquaculture system in which pure oxygen injection is used. In this paper, a novel CO 2 removal device is designed for the recirculating aquaculture water environment based on the principle of gas exchange. In terms of experiments, the DOE (design of experiment) method is applied to design three factor two level orthogonal experiment, Further, significance effect of gas to liquid ratios (G / L), inlet CO 2 concentration, the water flow rate (Q W ) on CO 2 removal efficiency is analyzed. Results show that G/L has the most significant influence on the CO 2 removal efficiency. Influences of the latter two on CO 2 removal efficiency are not apparent. Tests results of G/L effect on CO 2 removal efficiency show that, when G/L=1∼5, CO 2 removal efficiency increases rapidly with the increase of G/L; when G/L=5, CO 2 removal efficiency=80%∼88%; when G/L=8, CO 2 removal efficiency=86%∼92%, when G/L>8, CO 2 removal efficiency increases gently with the increase of G/L. Considering both system energy saving and effective removal of carbon dioxide, G/L=5∼8 is considered to be the best for the aquaculture water CO2 removal device running, CO 2 removal efficiency=80%∼92%.

This paper based on rough set, the original data, attribute reduction, value reduction, the rule extraction, the final diagnosis model building apple’s disease, disease diagnosis for apple to provide practical diagnostic tool.

This paper presents a description of the CO2 removal process of 500MW coal and gas fired power plants. The parameters and other operating conditions for Aspen Plus rate based model were selected to achieve 85% of CO2 removal. The effects of absorber pressure and packing height on re-boiler duty are studied. Re-boiler duty is decreasing with the increase of packing height and absorber pressure. The effect of solvent properties on CO2 removal efficiency is also analyzed. The removal efficiency increases as the increase of MEA concentration and temperature. When the lean loading of MEA solvent is increased, efficiency of the removal process is decreasing. The liquid and vapour phase temperature profiles and CO2 loading in the absorber are analyzed to understand the model behaviour.

Northern white ash had been the wood of choice for Major League Baseball (MLB) bats until the introduction of hard maple in the late 1990 s. Since the introduction of maple to the game, there has been a perceived increase in the rate of bats to exhibit multi-piece failures (MPF)–both ash and maple. Lab and field data indicate that while a maple bat is as equally likely to crack as an ash bat, maple is three times more likely than ash to exhibit an MPF. In 2009 MLB implemented a number of additional regulations and inspection processes for the wood billets in an effort to reduce the MPF rate. In 2010, another regulation was added requiring that before any new wood species can be introduced to the game, it must it must obtain approval from MLB Baseball Operations. This paper will describe a proposed wood species certification protocol to quantify its durability relative to ash, where ash is being taken as the acceptable baseline for durability. A demonstration of the protocol is conducted using yellow birch with white ash as the baseline. Finite element models of bats made of these two wood species are used to explore the relationship between wood density and bat durability.

Cyanide, one of the known most toxic chemicals, is widely used in mining and jewellery industries for gold extraction and recovery from crushed ores or electroplating residues. Cyanide toxicity occurs because this compound strongly binds to metals, inactivating metalloenzymes such as cytochrome c oxidase. Despite the toxicity of cyanide, cyanotrophic microorganisms such as the alkaliphilic bacterium Pseudomonas pseudoalcaligenes CECT5344 may use cyanide and its derivatives as a nitrogen source for growth, making biodegradation of cyanurated industrial waste possible. Genomic, transcriptomic and proteomic techniques applied to cyanide biodegradation ('cyan-omics') provide a holistic view that increases the global insights into the genetic background of cyanotrophic microorganisms that could be used for biodegradation of industrial cyanurated wastes and other biotechnological applications.

The chemical industry is a major source of pollution, because it contains a number of processes related to water use. The effluent may contain relatively large amounts of organic and inorganic substances such that the aquatic environment is constantly threatened. To find new methods of treating industrial waste water, we tried to implement the de-pollution properties of fibers of Luffa cylindrica, taking as a model of pollution of synthetic phenol solutions. In the first step, we studied the kinetics of adsorption for the system phenol/Luffa cylindrica fiber that is made in advance with different fiber (raw, processed) to find the one that has the greatest affinity for the adsorbent, and as a method of analyzing the UV spectrophotometry. In the second stage, the focus on the different flow patterns in porous media and the constraints fluid/porous media. This work shows that historically, the design of processing units depends only on hydrodynamic considerations. Currently, she needs to assess the physical and chemical aspects inherent in the process of adsorption dynamics.

Arginase-induced L-arginine deprivation is emerging as a key mechanism for the downregulation of immune responses. We hypothesised that arginase activity increases with disease severity in HIV-seropositive patients. Our results show that peripheral blood mononuclear cells (PBMCs) from 23 HIV-seropositive patients with low CD4+ T cell counts (≤350 cells/μl) expressed significantly more arginase compared with 21 patients with high CD4+ T cell counts. Furthermore, we found a significant association between the two principal prognostic markers used to monitor HIV disease (CD4+ T cell count and plasma viral load) and PBMC arginase activity in antiretroviral therapy naïve patients but not in patients undergoing therapy.

The pandemics of major infectious diseases often cause public health, economic, and social problems. Virtual reality (VR) and augmented reality (AR), as two novel technologies, have been used in many fields for emergency management of disasters. The objective of this paper was to review VR and AR applications in the emergency management of infectious outbreaks with an emphasis on the COVID-19 outbreak. A search was conducted in MEDLINE (PubMed), Embase, IEEE, Cochrane Library, Google engine, Google scholar, and related websites for papers published up to May 2, 2020. The VR technology has been used for preventing or responding to infections by simulating human behaviors, infection transmission, and pathogen structure as a means for improving skills management and safety protection. Telehealth, telecommunication, and drug discovery have been among the other applications of VR during this pandemic. Moreover, AR has also been used in various industries, including healthcare, marketing, universities, and schools. Providing high-resolution audio and video communication, facilitating remote collaboration, and allowing the visualization of invisible concepts are some of the advantages of using this technology. However, VR has been used more frequently than AR in the emergency management of previous infectious diseases with a greater focus on education and training. The potential applications of these technologies for COVID-19 can be categorized into four groups, i.e., 1) entertainment, 2) clinical context, 3) business and industry, and 4) education and training. The results of this study indicate that VR and AR have the potential to be used for emergency management of infectious diseases. Further research into employing these technologies will have a substantial impact on mitigating the destructive effects of infectious diseases. Making use of all the potential applications of these technologies should be considered for the emergency management of the current pandemic and mitigating its negative impacts.

Covid-19 seriously impacts and endangers lives of millions worldwide. To fight the spread of the virus, governments have taken various restricting measures including stay at home orders. Ultimately, the home delivery volume increased significantly, which still bears the risk of human–human infection during the final delivery. From a logisticians perspective, autonomous delivery vehicles (ADVs), which are a contactless delivery solution, have the potential to radically change the way groceries are delivered to customer homes and help to stop the spread of the virus. However, to date, research on user acceptance of ADVs is rare. This paper theoretically extends the Unified Theory of Acceptance and Use of Technology (UTAUT2) including gender as a moderator. The study is based on quantitative data collected in Germany through an online questionnaire (n = 501). Data were analysed using structural equation modelling. The results indicate that trust in technology, price sensitivity, innovativeness, performance expectancy, hedonic motivation, social influence, and perceived risk determine behavioural intention. However, some constructs are only significant for women. The findings of this paper have theoretical, managerial and policy contributions and implications within the areas of last-mile delivery and technology acceptance.

The purpose of this paper is to take stock of the knowledge gained over the last few years on Feline Infectious Peritonitis in a synthetic way. Apart from the bibliographical study regarding the works of numerous authors, we state our results concerning the study of the experimental reproduction of the disease. From all the cat infectious diseases, Feline Infectious Peritonitis is the clinical entity the most recently evidenced. In this paper we shall state the elements now clearly established on this disease but numerous points are still to be made clear. Contagious disease of viral origin, it affects domestic and wild Felidae. Clinically, in its most typical form, it is characterised by the progressive development of an exudative sero-fibrinous peritonitis and a febrile and gradual weakness of the general condition. It slowly and regularly develops into death.

Biomedical images contain a large volume of sensor measurements, which can reveal the descriptors of the disease under investigation. Computer-based analysis of such measurements helps detect the disease, and thereby swiftly aid medical professionals to choose adequate therapy. In this paper, we propose a robust deep learning ensemble framework known as COVID Fuzzy Ensemble Network, or COFE-Net. This strategy is proposed for the task of COVID-19 screening from chest X-rays (CXR) and CT Scans, as a part of Computer-Aided Detection (CADe) for medical practitioners. We leverage the strategy of Transfer Learning for Convolutional Neural Networks (CNNs) widely adopted in recent literature, and further propose an efficient ensemble network for their combination. The principles of fuzzy logic have been leveraged to combine the measured decision scores generated by three state-of-the-art CNNs – Inception V3, Inception ResNet V2 and DenseNet 201 – through the Choquet fuzzy integral. Experimental results support the efficacy of our approach over empirical ensembling, as the fuzzy ensembling strategy for biomedical measurement consists of dynamic refactoring of the classifier ensemble weights on the fly, based upon the confidence scores for coalitions of inputs. This is the chief advantage of our biomedical measurement strategy over others as other methods do not adjust to the multiple generated measurements dynamically unlike ours.Impressive results on multiple datasets demonstrate the effectiveness of the proposed method. The source code of our proposed method is made available at: https://github.com/theavicaster/covid-cade-ensemble .

This work proposes an agent-based model to analyze the spread processes of the COVID-19 epidemics in open regions and based on hypothetical social scenarios of viral transmissibility. Differently from other previous models, we consider the environment to be a multi-region space in which the epidemic spreads according to the dynamics and the concentration of agents in such regions. This paper suggests that software agents can provide a more suitable model for individuals, and their features, thus showing the influence of civil society in the context of pandemic management. This is achieved by modeling an individual as an agent with a wide range of features (health condition, purchasing power, awareness, mobility, professional activity, age, and gender). The model supports the design of populations and interactions akin to real-life scenarios. Simulation results show that the proposed model can be applied in several ways to support decision-makers to better understand the epidemic spread and the actions that can be taken against the pandemic.

Psoriasis is a chronic inflammatory skin disease that is characterized by well-demarcated erythematous plaques with a silver scale. Although many new and emerging therapeutic agents are often sufficient to control the disease, there is still a need for alternative treatment options in challenging cases. Extracorporeal photopheresis (ECP) has been applied to many T-cell-mediated diseases to restore immune homeostasis and treat psoriasis effectively. In this paper, we present a psoriasis patient who did not respond to methotrexate, narrowband ultraviolet B, or acitretin. Because of a diagnosis of non-Hodgkin lymphoma, the patient had contraindications for cyclosporine, fumaric acid esters, and biologics but achieved remission with a total of 12 sessions of ECP in two and a half months. Although exacerbation was recorded after polymerase chain reaction (PCR) confirmed coronavirus 2019 (COVID-19) disease infection at the end of the first month, scores from the psoriasis area severity index (PASI) and dermatological life quality index (DLQI) were regressed significantly within two and a half months. ECP seems to provide an effective and rapid response for psoriasis and should be considered for psoriasis patients who fail to respond or have contraindications to existing treatments.

The sudden outbreak of coronavirus disease 2019 (COVID-19) revealed the need for fast and reliable automatic tools to help health teams. This paper aims to present understandable solutions based on Machine Learning (ML) techniques to deal with COVID-19 screening in routine blood tests. We tested different ML classifiers in a public dataset from the Hospital Albert Einstein, Sao Paulo, Brazil. After cleaning and pre-processing the data has 608 patients, of which 84 are positive for COVID-19 confirmed by RT-PCR. To understand the model decisions, we introduce (i) a local Decision Tree Explainer (DTX) for local explanation and (ii) a Criteria Graph to aggregate these explanations and portrait a global picture of the results. Random Forest (RF) classifier achieved the best results (accuracy 0.88, F1-score 0.76, sensitivity 0.66, specificity 0.91, and AUROC 0.86). By using DTX and Criteria Graph for cases confirmed by the RF, it was possible to find some patterns among the individuals able to aid the clinicians to understand the interconnection among the blood parameters either globally or on a case-by-case basis. The results are in accordance with the literature and the proposed methodology may be embedded in an electronic health record system.

New coronavirus (COVID-19) is a newly emerging and highly infectious form of typical pneumonia with a high rate of transmission. The COVID-19 pneumonia has spread to 147 countries and areas as of Mar.16th 2020, which has tremendous impact on the global public health. It is well known that, in China, the pandemic has been contained effectively with a series of emergency measures. It is necessary to share the existing experience of China in the fight against the pandemic to the world. Especially, during the process of prevention and containment of the pandemic, ambulances play an important role in transporting infectious patients. In this paper, focusing on the safety and quantity of negative pressure ambulances, the influence of ambulance on newly confirmed cases is given. Analysis of negative pressure ambulance on the containment of COVID-19 is shown. The potential development of ambulance is discussed. While the pandemic still continues spreading across the world, we hope to share our experience in the implementation of these strategies by China to save more life.

Highlights • Automatically enhance, divide, and validate the COVID-19 CT images into regions with similar properties such as contrast and structure. • Efficient Kapur entropy-based multilevel thresholding unsupervised procedure. • Measure, visualize, and study comparisons of the infected by COVID-19 volume. • The experiment results indicate that the proposed method can reach the desired heat-mapping of COVID-19 lesion and has the potential to be used for clinical application including developing country., History shows that the infectious disease (COVID-19) can stun the world quickly, causing massive losses to health, resulting in a profound impact on the lives of billions of people, from both a safety and an economic perspective, for controlling the COVID-19 pandemic. The best strategy is to provide early intervention to stop the spread of the disease. In general, Computer Tomography (CT) is used to detect tumors in pneumonia, lungs, tuberculosis, emphysema, or other pleura (the membrane covering the lungs) diseases. Disadvantages of CT imaging system are: inferior soft tissue contrast compared to MRI as it is X-ray-based Radiation exposure. Lung CT image segmentation is a necessary initial step for lung image analysis. The main challenges of segmentation algorithms exaggerated due to intensity in-homogeneity, presence of artifacts, and closeness in the gray level of different soft tissue. The goal of this paper is to design and evaluate an automatic tool for automatic COVID-19 Lung Infection segmentation and measurement using chest CT images. The extensive computer simulations show better efficiency and flexibility of this end-to-end learning approach on CT image segmentation with image enhancement comparing to the state of the art segmentation approaches, namely GraphCut, Medical Image Segmentation (MIS), and Watershed. Experiments performed on COVID-CT-Dataset containing (275) CT scans that are positive for COVID-19 and new data acquired from the EL-BAYANE center for Radiology and Medical Imaging. The means of statistical measures obtained using the accuracy, sensitivity, F-measure, precision, MCC, Dice, Jacquard, and specificity are 0.98,0.73,0.71,0.73,0.71,0.71,0.57,0.99respectively; which is better than methods mentioned above. The achieved results prove that the proposed approach is more robust, accurate, and straightforward.

We aimed to investigate how evacuation measures could be effectively implemented in the event of multiple disasters caused by natural hazards under conditions of the novel coronavirus infection (COVID-19) pandemic, which is rapidly spreading worldwide. We conducted a review of literature focusing on complex disasters, entailing natural disasters in combination of outbreaks or endemics of infectious diseases. Using the Google Scholar search engine, we identified and reviewed 24 papers sourced from academia, governments, and concerned organizations, and associated data on such disasters, commencing with the Great Hanshin-Awaji Earthquake, which occurred in 1995. In light of our review, we developed a summary of correspondences and problems linked to compound disasters involving conjunctions of outbreaks/endemics and natural disasters that could offer insights for developing measures to deal with natural disasters that occur in the context of the COVID-19 pandemic. We subsequently attempted to differentiate the characteristics of evacuation measures relating to COVID-19 from those relating to other infectious diseases using three sets of extracted keywords: (1) surveillance and information sharing, (2) evacuation center environment and stockpiled supplies, and (3) community disaster risk reduction and community leadership. We identified issues relating to evacuation measures that would need to be explored further to improve disaster management and preparedness in the future., Highlights • Rapid diagnosis of COVID-19 infected persons is essential at evacuation centers • The issue of securing space for isolation is critical for preventing the spread of the infection • Strong “leadership of the people” is reported to have contributed significantly to the maintenance of sanitary environments in evacuation centers in the past

Objectives To review leadership for dentists in patient facing, primary care dental practice. Methods A three stage systematic review with narrative synthesis included stage 1: a scoping overview of management and leadership policy context; stage 2: systematic review of review of leadership in healthcare; and stage 3: systematic focused review of leadership in patient-facing dental practice. Results The healthcare literature mirrors the generic literature in relation to the temporal evolution of leadership theories. Policy papers influence healthcare literature, though these are generally written by independent bodies, link solely to medical publications, and are often commissioned from the grand strategic level thereby grounding them in a politicised system. The healthcare leadership literature offers few studies at the operational (patient care) level of leadership, with none of these focused explicitly on dentistry and dental practice. Numerous aims, definitions, models, conceptualisations, and links to theories of leadership are reported. The stage 1 literature demonstrates more contemporaneous ideas of leadership, while the dental practice literature is too often grounded in outdated concepts and theories. Conclusions The overarching trend is from leaders to leadership; with no unified definition, model, theory, concept nor aim recognised. The fundamental importance of specific context and the reaction of others to leadership is reinforced. Leadership theories aligned to healthcare include Engaging, Authentic, Collective and the Transformational-Transactional continuum. Leadership is a dynamic, socially constructed process, only occurring in a group setting. Consisting of multiple moderating variables that demonstrate reciprocal influence on one another, these influences are neither equal nor stable. (246 words) Clinical significance Leadership is embedded in regulatory guidance and standards relating to general dental practice. It is therefore crucial to have an evidenced based understanding of what leadership means in this context, and what further work is necessary to support clinicians in the leadership domain.

Highlights • Organizations in the hospitality industry need to ensure safe operation by facilitating employee compliance with COVID-19 safety measures. • A deep approach towards compliance with COVID-19 is a four-stage psychological process including 1) heightened risk and health awareness, 2) perceived utility value, 3) behavioral adaptation, and 4) integration. • This deep compliance is driven by both management COVID-19 safety practices as well as organizational crisis response strategies that prioritize safety and maximize job security., The COVID-19 health crisis has engendered a set of additional health and safety regulations and procedures (e.g. social distancing) to the hospitality industry. The purpose of this paper is to explore in-depth how organizations can facilitate employees’ deep compliance with these procedures. Employing an instrumental case-study approach, we collected multi-level interview data and archival data in a small-medium sized restaurant in China. The findings reveal that employees’ deep compliance with safety procedures includes a four-stage psychological process, and this process is underpinned by both management safety practices and organizational crisis strategies. As the hospitality industry starts to exit lockdown and ramp up operations, this study offers theoretical and practical insights on how organizations in hospitality can protect the health and safety of their employees and the broader community.

The COVID-19 disease has once again reiterated the impact of pandemics beyond a biomedical event with potential rapid, dramatic, sweeping disruptions to the management, and conduct of everyday life. Not only the rate and pattern of contagion that threaten our sense of healthy living but also the safety measures put in place for containing the spread of the virus may require social distancing. Three different measures to counteract this pandemic situation have emerged, namely: (i) vaccination, (ii) herd immunity development, and (iii) lockdown. As the first measure is not ready at this stage and the second measure is largely considered unreasonable on the account of the gigantic number of fatalities, a vast majority of countries have practiced the third option despite having a potentially immense adverse economic impact. To mitigate such an impact, this paper proposes a data-driven dynamic clustering framework for moderating the adverse economic impact of COVID-19 flare-up. Through an intelligent fusion of healthcare and simulated mobility data, we model lockdown as a clustering problem and design a dynamic clustering algorithm for localized lockdown by taking into account the pandemic, economic and mobility aspects. We then validate the proposed algorithms by conducting extensive simulations using the Malaysian context as a case study. The findings signify the promises of dynamic clustering for lockdown coverage reduction, reduced economic loss, and military unit deployment reduction, as well as assess potential impact of uncooperative civilians on the contamination rate. The outcome of this work is anticipated to pave a way for significantly reducing the severe economic impact of the COVID-19 spreading. Moreover, the idea can be exploited for potentially the next waves of corona virus-related diseases and other upcoming viral life-threatening calamities.

The world is witnessing tumultuous times as major economic powers including the US, UK, Russia, India, and most of Europe continue to be in a state of lockdown. The worst-hit sectors due to this lockdown are sales, production (manufacturing), transport (aerospace and automotive) and tourism. Lockdowns became necessary as a preventive measure to avoid the spread of the contagious and infectious “Coronavirus Disease 2019” (COVID-19). This newly identified disease is caused by a new strain of the virus being referred to as Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS CoV-2; formerly called 2019-nCoV). We review the current medical and manufacturing response to COVID-19, including advances in instrumentation, sensing, use of lasers, fumigation chambers and development of novel tools such as lab-on-the-chip using combinatorial additive and subtractive manufacturing techniques and use of molecular modelling and molecular docking in drug and vaccine discovery. We also offer perspectives on future considerations on climate change, outsourced versus indigenous manufacturing, automation, and antimicrobial resistance. Overall, this paper attempts to identify key areas where manufacturing can be employed to address societal challenges such as COVID-19., Graphical abstract Image 1, Highlights • We review the coronavirus pandemic and discuss salient aspects of the virus, the disease, its impact, propagation and treatment options. • We examine the current testing processes and the need for developing new tools such as lab-on-the-chip. • We examine how nanotechnology and ultra-precision engineering hold the promise in developing resilient measures to tackle the pandemic. • We also examine how digital manufacturing and automation can help productivity and how modelling and simulation can aid drug and vaccine discovery. • We explore design for manufacturing approaches required for developing new face masks and PPE's. • We discuss the short- and long-term impact of COVID-19 on supply chains, climate change and lifestyles.

Global efforts around the world are focused on to discuss several health care strategies for minimizing the impact of the new coronavirus (COVID-19) on the community. As it is clear that this virus becomes a public health threat and spreading easily among individuals. Mathematical models with computational simulations are effective tools that help global efforts to estimate key transmission parameters and further improvements for controlling this disease. This is an infectious disease and can be modeled as a system of non-linear differential equations with reaction rates. This work reviews and develops some suggested models for the COVID-19 that can address important questions about global health care and suggest important notes. Then, we suggest an updated model that includes a system of differential equations with transmission parameters. Some key computational simulations and sensitivity analysis are investigated. Also, the local sensitivities for each model state concerning the model parameters are computed using three different techniques: non-normalizations, half normalizations, and full normalizations. Results based on the computational simulations show that the model dynamics are significantly changed for different key model parameters. Interestingly, we identify that transition rates between asymptomatic infected with both reported and unreported symptomatic infected individuals are very sensitive parameters concerning model variables in spreading this disease. This helps international efforts to reduce the number of infected individuals from the disease and to prevent the propagation of new coronavirus more widely on the community. Another novelty of this paper is the identification of the critical model parameters, which makes it easy to be used by biologists with less knowledge of mathematical modeling and also facilitates the improvement of the model for future development theoretically and practically.

The COVID-19 pandemic has caused a "zero tourism" situation throughout the world with unpredictable consequences. Several authors analyzed the economic impacts of the COVID-19 pandemic during the second trimester of 2020, but none of them have specifically examined European Union countries and the joint actions taken to fight the pandemic. Using a case study methodology, this paper presents a literature review of the most up-to-date studies on the impacts of the COVID-19 global pandemic. Secondly, we specify the different public intervention measures implemented by the European Union in accordance with supranational governance theory and stakeholder theory. Finally, we set out the different COVID-19-related public rescue strategies for the tourism and hospitality sector at the individual level (for tourists), at the business level (for touristic companies) and at the destination level (for the European Union countries), from the perspective of stakeholders. The main contribution of our research is therefore to explore the public strategies to rescue the tourism and hospitality sector in the context of the European Union.

The COVID-19 pandemic has become one of the biggest threats to the global healthcare system, creating an unprecedented condition worldwide. The necessity of rapid diagnosis calls for alternative methods to predict the condition of the patient, for which disease severity estimation on the basis of Lung Ultrasound (LUS) can be a safe, radiation-free, flexible, and favorable option. In this paper, a frame-based 4-score disease severity prediction architecture is proposed with the integration of deep convolutional and recurrent neural networks to consider both spatial and temporal features of the LUS frames. The proposed convolutional neural network (CNN) architecture implements an autoencoder network and separable convolutional branches fused with a modified DenseNet-201 network to build a vigorous, noise-free classification model. A five-fold cross-validation scheme is performed to affirm the efficacy of the proposed network. In-depth result analysis shows a promising improvement in the classification performance by introducing the Long Short-Term Memory (LSTM) layers after the proposed CNN architecture by an average of 7-12%, which is approximately 17% more than the traditional DenseNet architecture alone. From an extensive analysis, it is found that the proposed end-to-end scheme is very effective in detecting COVID-19 severity scores from LUS images.

The severe acute respiratory syndrome coronavirus 2, called a SARS-CoV-2 virus, emerged from China at the end of 2019, has caused a disease named COVID-19, which has now evolved as a pandemic. Amongst the detected Covid-19 cases, several cases are also found asymptomatic. The presently available Reverse Transcription - Polymerase Chain Reaction (RT-PCR) system for detecting COVID-19 lacks due to limited availability of test kits and relatively low positive symptoms in the early stages of the disease, urging the need for alternative solutions. The tool based on Artificial Intelligence might help the world to develop an additional COVID-19 disease mitigation policy. In this paper, an automated Covid-19 detection system has been proposed, which uses indications from Computer Tomography (CT) images to train the new powered deep learning model- U-Net architecture. The performance of the proposed system has been evaluated using 1000 Chest CT images. The images were obtained from three different sources - Two different GitHub repository sources and the Italian Society of Medical and Interventional Radiology's excellent collection. Out of 1000 images, 552 images were of normal persons, and 448 images were obtained from COVID-19 affected people. The proposed algorithm has achieved a sensitivity and specificity of 94.86% and 93.47% respectively, with an overall accuracy of 94.10%. The U-Net architecture used for Chest CT image analysis has been found effective. The proposed method can be used for primary screening of COVID-19 affected persons as an additional tool available to clinicians.

The COVID-19 pandemic struck the tourism industry severely. Based on the review of 35 papers that studied the tourism industry in the wake of the pandemic, we propose a resilience-based framework for reviving the global tourism industry post-COVID-19. Our framework outlines four prominent factors for building resilience in the industry: government response, technology innovation, local belongingness, and consumer and employee confidence. We argue that using such inclusive resilience; the tourism industry may transform into a new global economic order characterized by sustainable tourism, society's well-being, climate action, and the involvement of local communities. We also offer directions for future research in the area., Highlights • We propose a resilience-based framework for reviving the global tourism industry. • The tourism industry may transform into a new global economic order. • Sustainable tourism, well-being of society, and climate action mark the new order.

The context of the SDGs resembles the properties of a complex adaptive system (CAS). CAS requires a specific form of leadership and leaders capable of creating social movements and via that way inducing large-scale system transformation towards the attainment of SDGs. Leaders capable of creating social movements tend to be those who occupy the highest levels of adult development (also referred as orders of consciousness). In this paper, we study the leadership approach towards the attainment of SDGs of leader, humanist and mystic from India Jaggi Vasudev Sadhguru. We have chosen him because he has initiated several social movements that have already created effects specified by SDGs. We study his approach to leadership by applying Kegan's (1994) framework of meaning-making and subject-object theory for the 5th order of consciousness. After analyzing Sadhguru's approach from that perspective, we discuss how leadership development programs should be re-designed to produce more leaders of Sadhguru's type. We contribute to the gap between adult development and leadership development if the aim is to facilitate the vertical development of participants towards the highest order of consciousness which in effect will be more capable of attaining SDGs., Highlights • Discusses the Sustainable Development Goals from the perspective of cognitive demands placed on a leader. • Unpacks the cognitive capacities from the lenses of Kegan’s orders of consciousness and subject-object theory. • Reviews the research on orders of consciousness and leadership effectiveness. • Provides in-depth study of leadership practises of Sadhguru from the perspective of subject-object theory. • Discusses principles around which leadership development programs should be structured for production of leaders capable of meeting SDGs.

Highlights • Efficient laboratories are key to the success of any disease programme. • PEI resources have contributed efforts in strengthening laboratory capacity in the region. • These contributions have not been systematically documented as lesson learnt. • With PEI programme on the ramp down, this paper documents it contributions for posterity., Background The laboratory has always played a very critical role in diagnosis of the diseases. The success of any disease programme is based on a functional laboratory network. Health laboratory services are an integral component of the health system. Efficiency and effectiveness of both clinical and public health functions including surveillance, diagnosis, prevention, treatment, research and health promotion are influenced by reliable laboratory services. The establishment of the African Regional polio laboratory for the Polio Eradication Initiative (PEI) has contributed in supporting countries in their efforts to strengthen laboratory capacity. On the eve of the closing of the program, we have shown through this article, examples of this contribution in two countries of the African region: Côte d’Ivoire and the Democratic Republic of Congo. Methods Descriptive studies were carried out in Côte d’Ivoire (RCI) and Democratic Republic of Congo (DRC) from October to December 2014. Questionnaires and self-administered and in-depth interviews and group discussions as well as records and observation were used to collect information during laboratory visits and assessments. Results The PEI financial support allows to maintain the majority of the 14 (DRC) and 12 (RCI) staff involved in the polio laboratory as full or in part time members. Through laboratory technical staff training supported by the PEI, skills and knowledge were gained to reinforce laboratories capacity and performance in quality laboratory functioning, processes and techniques such as cell culture. In the same way, infrastructure was improved and equipment provided. General laboratory quality standards, including the entire laboratory key elements was improved through the PEI accreditation process. Conclusion The Polio Eradication Initiative (PEI) is a good example of contribution in strengthening public health laboratories systems in the African region. It has established strong Polio Laboratory network that contributed to the strengthening of capacities and its expansion to surveillance of other viral priority diseases such as measles, yellow fever, Influenza, MERS-CoV and Ebola. This could serve as lesson and good example of laboratory based surveillance to improving diseases prevention, detection and control in our middle and low income countries as WHO and partners are heading to polio eradication in the world.

Two important changes are happening in health care in the US. As hospitals close in high numbers, the geographies of health care services are changing. Also, the ageing of the population brings about new and complex care needs. These are not discrete trends, as ageing impacts the who, what, and where of care needs, and hospital closures remakes the geographies of where people overall access care. Developed out of research on the impacts of hospital restructuring on workers, patients, and communities, this paper aims to understand how health care financing, care needs for the ageing, and new geographies of health services are intertwined. To do so, I look back to 1980s policy changes to Medicare, the federal health insurance program for the elderly and disabled. In 1982, Congress made two important changes to Medicare. The program began covering hospice services, constituting an expansion of care, and the government drastically changed the way it reimburses providers, effectively a contraction of the program. I trace the impacts of these changes over the next decades through analysis of media coverage and secondary research on hospital budgets. Drawing on the concept of palliative space-time, I identify a contradictory logic of death at the center of this expansion and contraction of the health care system. This death logic works to destabilize an already uneven geography of health service. Yet, this crisis has the potential for more just geographies of health and care., Highlights • US population ageing poses new challenges for caring for people as they age. • Hospital closures across the US alter how and where people receive care. • Palliative Space-time shows systems that struggle to exist but have radical potential. • Palliative Space-time helps analyse health systems, death, and care.

This article examines the economics of Africa's emerging air cargo supply chains, taking floriculture as a case study. Floriculture is an important employer, and earner of foreign exchange for several regions of central/southern and eastern Africa including more recently Ethiopia. Air transportation often plays a critical role when the supply-chain involves high-value, non-durable, relatively light-weight, and compact consignments such as flowers, and geographically when regions are difficult to access by other trunk modes. The success of air cargo chains, however, depend as much on the quality of surface modes serving various “last mile” access and egress functions, as well as efficient nodal interchange points and the availability of suitable airport and airline capacity. The last, because of the important role of belly-hold space, includes consideration of passenger as well as cargo specific services. To meet the needs of Africa's floriculture sector, a variety of supply-chain models have emerged that embrace air and surface links, as well as storage at various points in the chain. The paper considers the nature of these chains, the reason d'être for their structures, and their limitations., Highlights • Provides details of Africa's air transportation-based, floricultural cold-supply chains. • Examines the economic forces influencing the nature of the chains. • Explores the challenges of surface access to trunk air-cargo services. • Compares the features of largely market driven and more centrally controlled chains.

This paper which introduces strategic planning for foreign vassals during recession period is the result of a research project. This project has been done for Yazd Government, therefore due to security issues; statement whole of this project is not possible and therefore only some of permitted information could be mentioned. As a basic model Bryson's model was selected and the research group did its stages after each other. During this process, the group used observations, questionnaires, interviews and official national and international documents, analyzed internal and external different stakeholders, defined strategic issues and finally proposed possible strategies for the Yazd government. The procedure of strategy planning is illustrated briefly in this paper. In the end of project, the research group presents its findings and results to the client with a one year operating plan. In the next sections a short report of this project will be depicted.

The research presented in this paper is set in a Spanish University, and describes why and how group ‘learning to learn’ tutorials were introduced within an Action Research project designed to help students take greater control of their own learning. The paper shows how discoveries made during the project impacted on the implementation of the tutorials while discussing some of the perceived benefits of this approach.

Implementation of renewable energy projects (RES) involves very complex processes which are based on the latest creative techniques to give adequate solutions teaching practitioners of this multidisciplinary field. The need for a complex transfer of knowledge at the administrative level, technical level and technological level of RES projects, constitute prerequisites for success in projects implementation of this type. The present paper proposes using creative educational methods for implementing investment projects in renewable energy using a combination of methods of Goldratt. To exemplify bottleneck situations in the management of certain flows within the supply chain of the RES implementation projects, the paper proposes Drum-Buffer-Rope philosophy. In order to underline the effectiveness in fast obtaining and implementing the right solutions along the lifecycle of RES projects, the paper illustrates the steps of Theory of Constraints Thinking Process (TOCTP) integration by problem diagnosing, designing the solutions plan and integrating the solutions plan through the conceptualization of adequate diagrams communication within these types of projects.