Simulation Study on Airflow Organization and Environment in Reconstructed Fangcang Shelter Hospital Based on CFD

With frequent outbreaks of COVID-19, the rapid and effective construction of large-space buildings into Fangcang shelter hospitals has gradually become one of the effective means to control the epidemic. Reasonable design of the ventilation system of the Fangcang shelter hospital can optimize the indoor airflow organization, so that the internal environment can meet the comfort of patients and at the same time can effectively discharge pollutants, which is particularly important for the establishment of the Fangcang shelter hospital. In this paper, through the reconstruction of a large-space gymnasium, CFD software is used to simulate the living environment and pollutant emission efficiency of the reconstructed Fangcang shelter hospital in summer under different air supply temperatures, air supply heights and exhaust air volume parameters. The results show that when the air supply parameters are set to an air supply height of 4.5 m, an air supply temperature of 18 °C, and an exhaust air volume of a single bed of 150 m3/h, the thermal comfort can reach level I, and the ventilation efficiency for pollutants can reach 69.6%. In addition, the ventilation efficiency is 70.1% and 70.3% when the exhaust air volume of a single bed is continuously increased to 200 and 250 m3/h, which can no longer effectively improve the pollutant emission and will cause an uncomfortable blowing feeling to patients. © 2023 by the authors.

Nanosponges: As a Dynamic Drug Delivery Approach for Targeted Delivery

Recent advancements in nanotechnology have resulted in improved medicine delivery to the target site. Nanosponges are three-dimensional drug delivery systems that are nanoscale in size and created by cross-linking polymers. The introduction of Nanosponges has been a significant step toward overcoming issues such as drug toxicity, low bioavailability, and predictable medication release. Using a new way of nanotechnology, nanosponges, which are porous with small sponges (below one microm) flowing throughout the body, have demonstrated excellent results in delivering drugs. As a result, they reach the target place, attach to the skin's surface, and slowly release the medicine. Nanosponges can be used to encapsulate a wide range of medicines, including both hydrophilic and lipophilic pharmaceuticals. The medication delivery method using nanosponges is one of the most promising fields in pharmacy. It can be used as a biocatalyst carrier for vaccines, antibodies, enzymes, and proteins to be released. The existing study enlightens on the preparation method, evaluation, and prospective application in a medication delivery system and also focuses on patents filed in the field of nanosponges.Copyright © 2023 The Authors.

Marginal Cost of Energy Volatility in the Brazilian Interconnected Power System

From 2018 to 2022, on average, 70% of the Brazilian effective electric generation was produced by hydropower, 10% by wind power, and 20% by thermal power plants. Over the last five years, Brazil suffered from a series of severe droughts. As a result, hydropower generation was reduced, but demand growth was also declined as results of the COVID-19 pandemic and economic recession. From 2012 to 2022, the Brazilian reservoir system operated with, on average, only 40% of the active storage, but storage recovered to normal levels in the first three months of 2022. Despite large capacity of storage reservoirs, high volatility of the marginal cost of energy was observed in recent years. In this paper, we used two optimization models, NEWAVE and HIDROTERM for our study. These two models were previously developed for mid-range planning of the operation of the Brazilian interconnected power system. We used these two models to optimize the operation and compared the results with observed operational records for the period of 2018-2022. NEWAVE is a stochastic dual dynamic programming model which aggregates the system into four subsystems and 12 equivalent reservoirs. HIDROTERM is a nonlinear programming model that considers each of the 167 individual hydropower plants of the system. The main purposes of the comparison are to assess cooperation opportunities with the use of both models and better understand the impacts of increasing uncertainties, seasonality of inflows and winds, demand forecasts, decisions about storage in reservoirs, and thermal production on energy prices. © World Environmental and Water Resources Congress 2023.All rights reserved

Thermal Image Processing System for the measurement of body temperature using a Drone

In December 2019, several cases of pneumonia caused by SARS-CoV-2 were identified in the city of Wuhan (China), which was declared by the WHO as a pandemic in March 2020 because it caused enormous problems to public health due to its rapid transmission of contagion. Being an uncontrolled case, precautions were taken all over the world to moderate the coronavirus that undoubtedly was very deadly for any person, presenting several symptoms, among them we have fever as a common symptom. A biosecurity measure that is frequently used is the taking of temperature with an infrared thermometer, which is not well seen by some specialists due to the error they present, therefore, it would not represent a safe measurement. In view of this problem, in this article a thermal image processing system was made for the measurement of body temperature by means of a drone to obtain the value of body temperature accurately, being able to be implemented anywhere, where it is intended to make such measurement, helping to combat the spread of the virus that currently continues to affect many people. Through the development of the system, the tests were conducted with various people, obtaining a more accurate measurement of body temperature with an efficiency of 98.46% at 1.45 m between the drone and the person, in such a way that if it presents a body temperature higher than 38° C it could be infected with COVID-19. © 2023 IEEE.

Dynamic Insulation Systems to Control Airborne Transmission of Viruses in Classrooms: A Review of 'Airhouse' Concept

The discovery of the Covid-19 virus in China at the end of 2019 has drastically altered the global landscape. The virus, which has now become a pandemic, has wrought devastation on the world, infecting over 500 million people and killing over 6 million. The virus's mutation into a few variations, however, has enabled the world's alarming situation to continue until now. Airborne particles and viruses including the new Covid-19 variant -Omricon, is not only extremely contagious but also can be transferred by airborne transmission, putting vulnerable people like children at risk, particularly in classrooms. Amongst the strategies to control airborne transmission of viruses and to improve indoor thermal and air quality is using ventilation strategies -such as dynamic insulation. Thus, this paper will review at how dynamic insulation systems in conventional farming and residential buildings, cleanrooms and other controlled environments work to reduce airborne viruses and particles in a room. An innovative "Airhouse" concept that combines with activated carbon has been researched and investigated with regard to the dynamic insulation systems.This system has a high potential to reduce the air temperature, humidity, and airborne viruses including Covid-19 whilst maintaining a steady airflow rate in a normal room. Therefore, it has a great deal of potential to decrease or eliminate concerns about the transmission of airborne viruses and adapt ventilation systems to new pandemic threats.

Thermal stability of diagnostic targets plasmodium falciparum histidine rich protein II and plasmodium lactate dehydrogenase in rapid detection.

During the COVID-19 epidemic, blood samples are usually processed at 56 to attenuate the virus before pathogen detection. 71 blood samples of malaria patients reported by Shanghai Center for Disease Control and Prevention in 2017-2019 were collected, including 38 with Plasmodium falciparum infection, 8 P. malariae, 11 P. ovale and 14 P. vivax. The effect of inactivation on the thermal stability of P. falciparum histidine rich protein II (PfHRPII) and Plasmodium lactate dehydrogenase (pLDH) in blood samples was assessed before and after incubation at 56 for 30 min using the rapid diagnostic test (RDT) kit. The results showed that among the 38 P. falciparum T1-positive (PfHRPII) blood samples before heat treatment, 35 samples remained to be T1-positive (92.11%, 35/38, chi2=3.123, P>0.05) after heat treatment;while 54 blood samples (26 P. falciparum, 6 P. vivax, 10 P. ovale and 12 P. vivax) that were T2-positive (pLDH) before heat treatment turned to be T2-negative (positive rate 0, 0/54, chi2=87.755, P<0.01) after heat treatment. It was demonstrated that PfHRPII is stable during incubation at 56 for 30 min, while pLDH is unstable and degraded or inactivated during the heating. Therefore, the detection results of P. falciparum will not be affected by RDT, but diagnosis of the parasites other than P. falciparum in blood samples may be missed.Copyright © 2021, National Institute of Parasitic Diseases. All rights reserved.

Properties of composites based on recycled polypropylene and lignocellulosic agricultural waste

In the present work, composites based on recycled polypropylene (PPr) and 30% treated and untreated lignocellulosic waste were prepared. The recycled polypropylene comes from recovered surgical masks used during the COVID-19 pandemic, from which the elastic band and the metal strip have been removed. The lignocellulosic waste used as a reinforcing agent consisted of the depleted substrate from the culture of Pleurotus ostreatus fungi, being a sawdust enriched in chitin pellets of corn cobs treated with borhot from the brewing of beer. The composites with 30% of treated/untreated sawdust were obtained in dynamical conditions by melt processing. The effects of sawdust, both treated and untreated, on tensile properties (strength and modulus of elasticity), dynamic-mechanical properties (storage/loss modulus and loss factor), thermal conductivity and thermal stability were studied. The results showed improved thermal and mechanical properties of bio-composite materials based on recycled polypropylene from used face masks and sawdust, which can be used as construction materials. © 2023, Fundatia Serban Solacolu. All rights reserved.

A Study on Establishing Thermal Output Conditions of Radiant Ceiling Heating Panels for Improving Thermal Comfort of Perimeter Zone in Buildings

Amid concerns over airflow-induced transmission of the COVID-19 virus in buildings frequented by large numbers of people, such as offices, the necessity for radiant ceiling heating panels has increased. This is due to the concern that the airflows emitted from the convection heating systems installed near the ceiling or windows for winter heating may be a major cause of COVID-19 transmission. In this study, we aim to evaluate thermal comfort under various indoor and outdoor environmental conditions of a building and present the thermal output conditions of the radiant ceiling heating panel that can replace the convection heating system while ensuring comfort in the perimeter zone and handling the heating load. As a result, we were able to present, in a chart format, the thermal output conditions that can secure thermal comfort by analyzing the indoor airflow distribution depending on the surface temperature of the radiant ceiling heating panel, the interior surface temperature of the window, and the influence of internal heat generation. Moreover, through derived empirical formulas, we were able to determine the heating conditions of the panel that can secure the necessary heat dissipation while minimizing discomfort, such as downdrafts, even for indoor and outdoor conditions that were not evaluated in this study.

Lessons Learned from the COVID-19 Pandemic: A Multigroup Structural Equation Modelling of Underground Space Environment and Users' Health

Due to the inherent limitations of underground spaces, such as the lack of natural ventilation and sunlight, underground space users tend to face more health risks compared with their aboveground counterparts. However, little is known about how the underground environment, users' health, and their associations were impacted by the outbreak of the pandemic. In this study, we investigated and compared the impacts of the general underground environment on regular users' physical and psychological health before and after the pandemic. To achieve this aim, the data from 525 surveys were collected from eleven underground sites, followed by an objective field measurement study conducted at five underground sites in Hong Kong pre- and post-outbreak of the pandemic. The multigroup structural equation modelling results indicated that: (i) surprisingly, the users' satisfaction towards almost all underground environment factors, including greenery, connectivity with the aboveground environment, thermal comfort, ventilation, indoor air quality, acoustic comfort, and lighting, excluding wayfinding, were significantly higher in the post-outbreak period;(ii) the users' health, both physical and psychological, was significantly better in the post-outbreak period;(iii) the impacts of visual comfort on the users' physical and psychological health were significantly greater in the post-outbreak period (critical difference ratio (;CDR;) > 1.96);(iv) the impacts of wayfinding, greenery, and acoustic and thermal comfort on the users' physical or psychological health were significant only in the pre-outbreak period (;CDR;> 1.96);(v) the impacts of connectivity on the users' physical and psychological health were significant in both the pre- and post-outbreak periods (;CDR;< 1.96). The findings were further cross-validated using the objective measurement results. With an increasing need to develop healthy underground spaces, the study contributes to the development, design, and management of the underground environment to enhance the users' health in the post-outbreak era.

Meteorological-Data-Based Modeling for PV Performance Optimization

Developing a sustainable and reliable photovoltaic (PV) energy system requires a comprehensive analysis of solar profiles and an accurate prediction of solar energy performance at the study site. Installing the PV modules with optimal tilt and azimuth angles has a significant impact on the total irradiance delivered to the PV modules. This paper proposes a comprehensive optimization model to integrate total irradiance models with the PV temperature model to find the optimal year-round installation parameters of PV modules. A novel integration between installation parameters and the annual average solar energy is presented, to produce the maximum energy output. The results suggest an increase in energy yields of 4% compared to the conventional scheme, where tilt angle is equal to the latitude and the PV modules are facing south. This paper uses a real-time dataset for the NEOM region in Saudi Arabia to validate the superiority of the proposed model compared to the conventional scheme, but it can be implemented as a scheme wherever real-time data are available.

An overview for biomedical waste management during pandemic like COVID-19.

Amid COVID-19, world has gone under environmental reformation in terms of clean rivers and blue skies, whereas, generation of biomedical waste management has emerged as a big threat for the whole world, especially in the developing nations. Appropriate biomedical waste management has become a prime concern worldwide in the pandemic era of COVID-19 as it may affect environment and living organisms up to a great extent. The problem has been increased many folds because of unexpected generations of hazardous biomedical waste which needs extraordinary attentions. In this paper, the impacts and future challenges of solid waste management especially the biomedical waste management on environment and human beings have been discussed amid COVID-19 pandemic. The paper also recommends some guidelines to manage the bulk of medical wastes for the protection of human health and environment. The paper summarizes better management practices for the wastes including optimizing the decision process, infrastructure, upgrading treatment methods and other activities related with the biological disasters like COVID-19. As achieved in the past for viral disinfection, use of UV- rays with proper precautions can also be explored for COVID-19 disinfection. For biomedical waste management, thermal treatment of waste can be an alternative, as it can generate energy along with reducing waste volume by 80-95%. The Asian Development Bank observed that additional biomedical waste was generated ranged from 154 to 280 tons/day during the peak of COVID-19 pandemic in Asian megacities such as Manila, Jakarta, Wuhan, Bangkok, Hanoi, Kuala Lumpur.

A paced multi-stage block-wise approach for object detection in thermal images.

The growing advocacy of thermal imagery in applications, such as autonomous vehicles, surveillance, and COVID-19 detection, necessitates accurate object detection frameworks for the thermal domain. Conventional methods could fall short, especially in situations with poor lighting, for instance, detection during night-time. In this paper, we propose a paced multi-stage block-wise framework for effectively detecting objects from thermal images. Our approach utilizes the pre-existing knowledge of deep neural network-based object detectors trained on large-scale natural image data to enhance performance in the thermal domain constructively. The employed, multi-stage approach drives our model to achieve higher accuracies. And the introduction of the pace parameter during domain adaption enables efficient training. Our experimental results demonstrate that the framework outperforms previous benchmarks on the FLIR ADAS dataset on the person, bicycle, and car categories. We have also illustrated further analysis of the framework, such as the effect of its components on accuracy and training efficiency, its generalizability to other thermal datasets, and its superior performance on night-time images in contrast to state-of-the-art RGB object detectors.

A Multi-market Comparison of the Intraday Lead-Lag Relations Among Stock Index-Based Spot, Futures and Options.

Using 1-min data, we explore the dynamic variation of the intraday lead-lag relations between stock indices and their derivatives through a comprehensive study with broader coverage of research objectives and methodologies. This paper provides explicit evidence that the futures and options exhibit price leadership over the spot market, and the options is ahead of the futures on most trading days in all three markets. This paper also reports a new finding that the relation between the derivative and its underlying index reverses when the index return has a significantly larger mean value, and the reversal phenomenon is also observed in the relations between the futures and the options, which enriches the empirical results of intraday lead-lag relations. Moreover, these conclusions still hold under the impact of extreme events, e.g., the outbreak of the Covid-19. Finally, we construct a pair trading strategy based on the intraday lead-lag relationships, which can get better performance than the corresponding spot index. Our findings can potentially help regulators understand the price discovery process between the index and its derivatives, and also be of great value for timely adjustment of investors intraday trading strategies.

Self-Destructive Structural Color Liquids for Time-Temperature Indicating.

Vaccines are undoubtedly a powerful weapon in our fight against global pandemics, as demonstrated in the recent COVID-19 case, yet they often face significant challenges in reliable cold chain transport. Despite extensive efforts to monitor their time-temperature history, current time-temperature indicators (TTIs) suffer from limited reliability and stability, such as difficulty in avoiding human intervention, inapplicable to subzero temperatures, narrow tracking temperature ranges, or susceptibility to photobleaching. Herein, we develop a class of structural color materials that harnesses dual merits of fluidic nature and structural color, enabling thermal-triggered visible color destruction based on triggering agent-diffusion-induced irreversible disassembly of liquid colloidal photonic crystals for indicating the time-temperature history of the cold chain transport. These self-destructive structural color liquids (SCLs) exhibit inherent irreversibility, superior sensitivity, tunable self-destructive time (minutes to days), and a wide tracking temperature range (-70 to +37 °C). Such self-destructive SCLs can be conveniently packaged into flexible TTIs for monitoring the storage and exposure status of diverse vaccines via naked-eye inspection or mobile phone scanning. By overcoming the shortcomings inherent in conventional TTIs and responsive photonic crystals, these self-destructive SCLs can increase their compatibility with cold chain transport and hold promise for the development and application of the next-generation intelligent TTIs and photonic crystals.

Uniform Gold Nanostructure Formation via Weakly Adsorbed Gold Films and Thermal Annealing for Reliable Localized Surface Plasmon Resonance-Based Detection of DNase-I.

Deoxyribonuclease-I (DNase-I), a representative endonuclease, is an important biomarker for the diagnosis of infectious diseases and cancer progression. However, enzymatic activity decreases rapidly ex vivo, which highlights the need for precise on-site detection of DNase-I. Here, a localized surface plasmon resonance (LSPR) biosensor that enables the simple and rapid detection of DNase-I is reported. Moreover, a novel technique named electrochemical deposition and mild thermal annealing (EDMIT) is applied to overcome signal variations. By taking advantage of the low adhesion of gold clusters on indium tin oxide substrates, both the uniformity and sphericity of gold nanoparticles are increased under mild thermal annealing conditions via coalescence and Ostwald ripening. This ultimately results in an approximately 15-fold decrease in LSPR signal variations. The linear range of the fabricated sensor is 20-1000 ng mL-1 with a limit of detection (LOD) of 127.25 pg mL-1 , as demonstrated by spectral absorbance analyses. The fabricated LSPR sensor stably measured DNase-I concentrations from samples collected from both an inflammatory bowel disease (IBD) mouse model, as well as human patients with severe COVID-19 symptoms. Therefore, the proposed LSPR sensor fabricated via the EDMIT method can be used for early diagnosis of other infectious diseases.

Contribution of the catalytic dyad of SARS-CoV-2 main protease to binding covalent and noncovalent inhibitors.

The effect of mutations of the catalytic dyad residues of SARS-CoV-2 main protease (MProWT) on the thermodynamics of binding of covalent inhibitors comprising nitrile [nirmatrelvir (NMV), NBH2], aldehyde (GC373), and ketone (BBH1) warheads to MPro is examined together with room temperature X-ray crystallography. When lacking the nucleophilic C145, NMV binding is ∼400-fold weaker corresponding to 3.5 kcal/mol and 13.3 °C decrease in free energy (ΔG) and thermal stability (Tm), respectively, relative to MProWT. The H41A mutation results in a 20-fold increase in the dissociation constant (Kd), and 1.7 kcal/mol and 1.4 °C decreases in ΔG and Tm, respectively. Increasing the pH from 7.2 to 8.2 enhances NMV binding to MProH41A, whereas no significant change is observed in binding to MProWT. Structures of the four inhibitor complexes with MPro1-304/C145A show that the active site geometries of the complexes are nearly identical to that of MProWT with the nucleophilic sulfur of C145 positioned to react with the nitrile or the carbonyl carbon. These results support a two-step mechanism for the formation of the covalent complex involving an initial non-covalent binding followed by a nucleophilic attack by the thiolate anion of C145 on the warhead carbon. Noncovalent inhibitor ensitrelvir (ESV) exhibits a binding affinity to MProWT that is similar to NMV but differs in its thermodynamic signature from NMV. The binding of ESV to MProC145A also results in a significant, but smaller, increase in Kd and decrease in ΔG and Tm, relative to NMV.

Good Architecture Matters: The Architect's Perspective on Design for Ageing and Energy Efficiency

Custom-built solutions for ageing, urban regeneration, energy efficiency, thermal performance, and well-being are contemporary challenges that have prompted considerable research over the past decades. In the construction field, subjects such as energy efficiency and thermal performance are often addressed within the scope of mandatory regulations, the suitability of construction solutions and the incorporation of technical equipment. Considering four residential structures for older adults under construction in Portugal, this paper aims to highlight the importance of a comprehensive approach to these issues, including architectural quality as the main target. In pursuit of this, a cohesive set of intervention principles guided the analysis: the adaptive reuse of raw materials;taking advantage of the site's conditions;vegetation (type and location);construction options and durability;solar exposure and shading;the pedagogy of building use;and the comfort and thermal perception. Several reflections emerge from the analysis: good architectural design must consider dynamic models incorporating each context and the site's conditions;the culture of use and maintenance and the notion of "adaptive comfort" are primary factors to enhance thermal performance and energy efficiency;and each building is a unique result of a complex negotiation process. Bridging research through practice, and multidisciplinary scientific integration enable engagement with reality and raise awareness of the constraints and challenges to innovation in LTC design.

Mask Detection and Classification in Thermal Face Images

Face masks are recommended to reduce the transmission of many viruses, especially SARS-CoV-2. Therefore, the automatic detection of whether there is a mask on the face, what type of mask is worn, and how it is worn is an important research topic. In this work, the use of thermal imaging was considered to analyze the possibility of detecting (localizing) a mask on the face, as well as to check whether it is possible to classify the type of mask on the face. The previously proposed dataset of thermal images was extended and annotated with the description of a type of mask and a location of a mask within a face. Different deep learning models were adapted. The best model for face mask detection turned out to be the Yolov5 model in the "nano" version, reaching mAP higher than 97% and precision of about 95%. High accuracy was also obtained for mask type classification. The best results were obtained for the convolutional neural network model built on an autoencoder initially trained in the thermal image reconstruction problem. The pretrained encoder was used to train a classifier which achieved an accuracy of 91%.

Under Pandemic: Assessment of Ventilation in Secondary Schools in The Netherlands

To investigate the sufficiency of ventilation during the COVID-19 pandemic for school children, a field study was conducted in 37 classrooms of 11 Dutch secondary schools between October 2020 and June 2021. All the classrooms were visited twice, before and after a three-month national lockdown, when different measures against COVID-19 were taken by the schools. For each visit, both CO2 concentrations and air temperature were measured during school hours, and detailed information on building/classroom characteristics, occupancy, and COVID-19 measures was collected. Results show that before the lockdown, CO2 concentrations in most classrooms exceeded the threshold levels of the Dutch Fresh Schools guidelines. The significantly lower CO2 concentrations measured after the lockdown, however, were mainly due to the decreased occupancy. Moreover, with windows and doors always being opened on purpose, the performance of different ventilation regimes could not be compared, while such behaviour may also lead to thermal discomfort for school children. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Towards improved thermal comfort predictions and higher energy savings: building energy model of an open-plan office based on indoor CO2 and temperature controls

In recent work, a Hierarchical Bayesian model was developed to predict occupants' thermal comfort as a function of thermal indoor environmental conditions and indoor CO2 concentrations. The model was trained on two large IEQ field datasets consisting of physical and subjective measurements of IEQ collected from over 900 workstations in 14 buildings across Canada and the US. Posterior results revealed that including measurements of CO2 in thermal comfort modelling credibly increases the prediction accuracy of thermal comfort and in a manner that can support future thermal comfort prediction. In this paper, the predictive model of thermal comfort is integrated into a building energy model (BEM) that simulates an open-concept mechanically-ventilated office space located in Vancouver. The model predicts occupants' thermal satisfaction and heating energy consumption as a function of setpoint thermal conditions and indoor CO2 concentrations such that, for the same thermal comfort level, higher air changes per hour can be achieved by pumping a higher amount of less-conditioned fresh air. The results show that it is possible to reduce the energy demand of increasing fresh air ventilation rates in winter by decreasing indoor air temperature setpoints in a way that does not affect perceived thermal satisfaction. This paper presents a solution for building managers that have been under pressure to increase current ventilation rates during the COVID-19 pandemic. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.