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An outbreak occurred in Wanhua District of Taipei City. It was traced to a cluster infection originating from a teahouse. To prevent further large-scaled community spread, the Taipei City Government established the first community rapid test screening station. This report describes the station's strategy and performance and key factors that contributed to its operation. The project involves collaboration among various departments of Taipei City Government, including the health, environmental, police, transportation, and fire departments. The station provides rapid screening, polymerase chain reaction (PCR) testing, and immediate isolation and follow-up medical services upon the detection of a positive case. These services are accessible to local residents and are intended to ease hospitals' burdens. In 36 days, a total of 8532 people were tested, and 419 confirmed cases were identified. Over the same period, the weekly number of positive cases in Wanhua District decreased from 356 to 40, and the PCR positive rate decreased from 21.7% to 1.2%. The policy of establishing rapid screening station, contact tracing and mask wearing policy are key strategies for interrupting chains of transmission of COVID-19. This intervention has become a model for preventing the spread of the epidemic and establishing community rapid screening stations in Taiwan.

An actual scientific and practical task related to the sustainable development of the country’s energy sector is to forecast parameters and predict the conditions of operation of solar cells and solar batteries in regular and non-regular situations. It is emphasized that this makes it possible to provide solar energy with high efficiency indicators, in particular, the indicator of profitability on invested capital in the construction of solar panels. The main specific research method is regression analysis – to build a forecast model of the total amount of generated energy of solar panels in ground installations under variable conditions of operation. An analysis of the distribution of the output data of the model by the number of solar battery modules was carried out using the example of terrestrial solar installations. To obtain empirical data, 31 objects in the Dnipropetrovsk and Zaporizhia oblasts, which have functioning solar batteries with different numbers of modules, were selected. This makes it possible to calculate the weighted average amount of generated energy during operation under variable conditions. 10 intervals of frequency values were separated with the largest range of values within the interval of 10,000–20,000 pieces of solar modules. A model of the dependence of the total amount of generated energy on the number of solar battery modules and the weighted average amount of generated energy was built based on regression analysis. It was determined that the influencing factor of the model «number of solar modules» has a positive influence on the resulting factor (productivity of solar panels), while the influencing factor «weighted average amount of generated energy» has a negative influence. However, the «number of solar modules» influence factor is more significant. The obtained results give grounds for asserting the possibility of their implementation in the energy sector, Актуальною науково-практичною проблемою сталого розвитку енергетики країни є прогнозування параметрів та передбачення умов функціонування сонячних елементів та сонячних батарей в штатних та позаштатних ситуаціях. Акцентовано, що це дозволяє забезпечити сонячної енергетики високі показники ефективності, зокрема показник прибутковості на інвестований капітал у побудову сонячних батарей. Основним специфічним методом дослідження є регресійний аналіз – для побудови моделі прогнозу загальної кількості генерованої енергії сонячних батарей у наземних установках за умови експлуатації в змінних умовах. Здійснено аналіз розподілу вихідних даних моделі за кількістю модулів сонячних батарей на прикладі наземних сонячних установок. Для отримання емпіричних даних обрано 31 об’єкт у Дніпропетровській та Запорізькій областях, що мають функціонуючі сонячні батареї з різною кількістю модулів. Це надає можливість розрахувати середньозважену кількість генерованої енергії при експлуатації в змінних умовах. Відокремлено 10 інтервалів значень частот, при цьому найбільший діапазон значень знаходиться у інтервалі 10000–20000 штук модулів сонячних батарей. Побудовано модель залежності загальної кількості генерованої енергії від кількості модулів сонячних батарей та середньозваженої кількості генерованої енергії на основі регресійного аналізу. Визначено, що фактор впливу моделі «кількість модулів сонячних батарей» має позитивний вплив на результативний фактор (продуктивність сонячних батарей), тоді як фактор впливу «середньозважена кількість генерованої енергії» має негативний вплив. Однак більш значущім є фактор впливу «кількість модулів сонячних батарей». Отримані результати дають підстави стверджувати щодо можливості втілення їх у енергетичний сектор

On the aero-engine combustor liner, a phenomenon of overheating resembling a hot spot exists, accompanied by a preferential peeling of the YSZ thermal barrier coating that will negatively affect the service life of the component. The hot spot temperatures will affect the ineffectiveness of YSZ, so in this paper, the morphological and property changes of YSZ sintering is investigated experimentally, and a coupled analysis of the YSZ crack propagation mode under the hot spot is performed using ABAQUS. The results show that the pore fractal size D of YSZ increases by 15%. Inside the hot spot region, the coating has a shear stress of 75 MPa. By inserting cohesive units globally in the FEM to simulate the random crack initiation and propagation, unlike the thinning of YSZ layered peeling caused by uniform superheating, the hot spot will cause the crack initiation at the tip of the pores inside the coating and the oblique propagation, eventually forming an oblique crack connection through the pores. When the temperature gradient reaches 30 K/mm, the crack propagation is 40% greater than in a uniform temperature field; consequently, the YSZ in the hot spot boundary region with a greater temperature gradient results in more severe bulk peeling.

Photovoltaic technology is receiving increasing attention due to its abundant nature, inexhaustible, easy to implement with low maintenance cost, whose use will reach 940 GW in 2021. The non-participation of mechanical or mobile components within it makes it still efficient and increasingly attractive. Faced with this dizzying growth, the health of photovoltaic modules must be a concern, as various failures can occur, of which nearly 50% of defects are hot spots. These faults can lead to changes in PV characteristics, and therefore maximum voltage. This can also change the maximum power available to the load and thus reduce the efficiency of photovoltaic energy production. In order to solve this problem that lies in minimizing these impacts, we review the hot spot fault, its equivalent model, and the operation and strategy of the maximum power point tracker in this specific case. Finally, it is clearly established that photovoltaic systems are extremely sensitive to the hot-spot fault, the use of a MPPT maximum power point tracker is an undeniable solution for improving the efficiency of photovoltaic systems.

Nanotelesa so proteini izvedeni iz posebne vrste imunoglobulinov, ki imajo samo težko verigo in imajo zaradi tega posebne lastnosti. Dodaten vpogled v način prepoznave antigenov z nanotelesi lahko dobimo z analizo energijsko močnejših interakcij (ang. hot-spot). Za iskanje teh interakcij in silico smo uporabili program FoldX, s katerim lahko izvedemo iskanje z mutacijo aminokislinskih ostankov v alanin in ovrednotimo nastalo spremembo proste energije pri nastanku kompleksa nanotelo-antigen. Na ta način smo našli 652 energijsko močnih interakcij v bazi 123 struktur kompleksov nanotelo-antigen. Ugotovili smo, da aminokislinski ostanek tirozin najpogosteje tvori energijsko močne interakcije, pretežno pa se te nahajajo v področju zanke CDR3. Zdi se tudi, da med številom interakcij in kontaktov ni nikakršne korelacije. Izsledki bi lahko bili eden od korakov za morebitno načrtovanje nanoteles za medicinsko uporabo. Nanobodies are proteins derived from heavy chain-only antibodies and as a result, have unique properties. To study how a nanobody binds to the appropriate antigen, we can analyse the places in the structure where energy interactions are the strongest, called hot spots. To find such interactions in silico, the FoldX program can be used to perform an alanine scanning method, because of which we can evaluate how free energy changes in the nanobody-antigen complex. With that method, we found 652 hot spots in a dataset of 123 nanobody-antigen complexes. We found that the amino acid most represented in hot spots is tyrosine and that the majority can be found in the CDR3 region of the nanobody. Furthermore, there appears to be no correlation between the number of hot spots and contacts in each nanobody. The results could be one of the steps on the way to designing nanobodies for medical use.

An electrical system audit is important in every building or dwelling to ensure the safety of the occupants. The audit was conducted following the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) level 2 standard. In this study where the locale is a university laboratory, results found that there is a thermal anomaly in the main distribution panels, which is an indication of a loose connection or possible overload and leads to technical system loss, loss of energy and cause a fire in the long run. There are also multiple cable splices going to the distribution panel, which is a violation of the electrical code. The lighting in the area does not meet the required illumination for laboratory safety. Moreover live bus bars were exposed on the distribution panel., {"references":["A Simple Guide to Health Risk Assessment Office Environment Series OE 5/2003.","Abdelatia, B.; Marenne, C.; Semidor, C. Daylighting strategy for sustainable schools: case study of prototype classrooms in Libya. Journal of Sustainable Development 2010, 3 (3). https://doi.org/10.5539/jsd.v3n3p60.","Booth, et. al., Rural electric research, National Rural Electric Cooperative Association, 1990","Boyden S. Biological determinants of optimal health; in Vorster DJ (ed): Proceedings of a Conference Held in Blantyre Malawi. London, International Biology Program, 1971 April 5–12.","C.P. Fernandez, Jr., Power system design for a 2000 MTPD cement finishing plant, 2005","Del Carmen, J. Effective methods / techniques in checking pilferages and reducing line losses, International Convention on Rural Electrification, July 1992","Earley, M. W.; Sargent, J. S.; Sheehan, J. V.; Caloggero, J. M. National Electrical Code Handbook; National Fire Protection Association: Quincy, USA, 2005","Fielding, R. Learning, lighting and color: Lighting design for schools and universities in the 21st Century; DesignShare, 2006.","Fink, D. G.; H. Wayne Beaty. Standard handbook for electrical engineers, Fourteenth Edition; McGraw-Hill, New York, USA, 2000.","Globe Telecom. Lean six sigma green belt training manual, 2012","Gustafson, M. W.; Baylor, J. S. Approximating the system losses equation (power systems). IEEE Transactions on Power Systems 1989, 4 (3), 850–855. https://doi.org/10.1109/59.32571.","Harriss, D. W. Line loss and its reduction, New Zealand Energy, August 1977","Hassler, S. The Institute of Electrical and Electronics Engineer (IEEE) Spectrum, July 2003","Hazan, E. System economics benefit from loss reduction measures on transmission and distribution, July 1982, Trans. and Distrib. (USA) vol. 34 No. 7 , 18, 20, 22, 37 Journal/Abstract no. B82062281","Institute of Integrated Electrical Engineers, Philippine Electrical Code Part 1, Volume 1, 2009","Juran, J. M.; A Blanton Godfrey. Juran's Quality Handbook; McGraw-Hill, New York, USA, 1999.","Juslin H. School lighting and efficient way to improve out children's educational and well being, 2005","Locke, A. M.; Book, H. W. Economic loading of transformers, electric light and power, April 1978, pp. 54-56","McCreery J.; Hill T. Illuminating the classroom environment, https://spaces4learning.com/articles/2005/02/01/illuminating-the-classroom-environment.aspx (accessed 2023 -01 -25).","McPartland, J.F. Making Electrical Calculations, Electr. Const. Maint., McGraw-Hill, New York, USA 1975","NRECA Research Project 90-7, Distribution System Loss Management Manual, 1990","Rahmatullah, B. D. Effective methods/techniques in checking pilferages and reducing line losses, international convention on rural electrification, July 1992","Robert Scott Mcgowen. The impact of school facilities on student achievement, attendance, behavior, completion rate and teacher turnover rate in selected Texas high schools - a dissertation; 2007.","Samani, S. A. The Influence of Light on Student's Learning Performance in Learning Environments: A Knowledge Internalization Perspective. World Academy of Science, Engineering and Technology 2011, 57 (2011).","Tanner, C. K. The Influence of School Architecture on Academic Achievement. Journal of Educational Administration 2000, 38 (4), 309–330. https://doi.org/10.1108/09578230010373598."]}

In this work, a defective commercial module with a rounded IV characteristic is analyzed in detail to identify the sources of its malfunction. The analysis of the module includes thermography images taken under diverse conditions, the IV response of the module obtained without any shadow, and shadowing one cell at a time, as recommended by the IEC 61215 Standard. Additionally, a direct measurement of the IV characteristic and resistance of single cells in the panel has been conducted to verify the isolation between the p and n areas. In parallel, theoretical cell and module behaviors are presented. In this frame, simulations show how cell mismatch can be the explanation to the rounded IV output of the solar panel under study. From the thermal images of the module, several localized hot spots related to failing cells have been revealed. During the present study, thermal breakdown is seen before avalanche breakdown in one of the cells, evidencing a hot spot. Not many papers have dealt with this problem, whereas we believe it is important to analyze the relationship between thermal breakdown and hot spotting in order to prevent it in the future, since hot spots are the main defects related to degradation of modern modules.

Anhijaline špilje pripadaju specifičnim speleološkim fenomenima Mediteranskog krša. Tijekom protekla četiri desetljeća istraživanja anhijalinih špilja u Hrvatskoj enormno su se proširila i intenzivirala. Međutim, ukupna zajednica vodenih beskralješnjaka ostala je nedovoljno poznata. Istraživanje zajednica je provedeno na 99 uzoraka prikupljenih u 39 anhijalinih špilja tijekom svih sezona u razdoblju od rujna 2001. do svibnja 2011. godine kako bi se analizirala struktura i raznolikost vodenih beskralješnjaka te opisale razlike između četiri Makrogeomorfološke regije Hrvatske definirane prema Bognaru i sur. (2012). Zabilježeno je ukupno 46 svojti vodenih beskralješnjaka unutar šest koljena. Najdominantniji predstavnici jadranske anhijalne špiljske faune bili su člankonošci ili točnije rakovi. Identificirali smo vruće točke bioraznolikosti, Vodenu jamu na otoku Gustac u Kornatskom arhipelagu u makrogeomorfološkoj regiji 2.3. SZ Dalmacija s arhipelagom. Makrogeomorfološka regija od posebnog interesa za zaštitu je 2.3. SZ Dalmacija s arhipelagom unutar koje je zabilježen najveći ukupni broj vodenih beskralježnjaka u istraživanim anhijalinim špiljama, te najveći broj špilja (ukupno četiri) s velikim brojem svojti vodenih beskralješnjaka (≥15). Anchialine caves belong to the specific speleological phenomenon in the Mediterranean karst. Over the last four decades, research on the anchialine caves in Croatia has expanded enormously. However, total anchialine aquatic invertebrate assemblages remain poorly understood. The assemblages were determined from 99 samples collected in 39 anchialine caves during seasonal surveys carried out from September 2001 to May 2011 to analyze the structure and diversity of aquatic invertebrate assemblages and to describe the differences between four Macrogeomorphological regions of Croatia according to Bognar et al. (2012). A total of 46 taxa of invertebrates in six phyla were identified. The most dominant representatives of the Adriatic anchialine cave fauna were arthropods or, more precisely, crustaceans. We identified a hotspot of biodiversity the pit Vodena jama on the island Gustac in Kornati Archipelago in the Macrogeomorphological region 2.3. NW Dalmatia with archipelago. Macrogeomorphological region of particular interest for protection is 2.3. NW Dalmatia with the archipelago within which the largest total number of aquatic invertebrates were recorded in the investigated anchialine caves, and the largest number of caves (four in total) with a large number of aquatic invertebrate taxa (≥15).

Full list of authors: Emami, Razieh; Tiede, Paul; Doeleman, Sheperd S.; Roelofs, Freek; Wielgus, Maciek; Blackburn, Lindy; Liska, Matthew; Chatterjee, Koushik; Ripperda, Bart; Fuentes, Antonio; Broderick, Avery E.; Hernquist, Lars; Alcock, Charles; Narayan, Ramesh; Smith, Randall; Tremblay, Grant; Ricarte, Angelo; Sun, He; Anantua, Richard; Kovalev, Yuri Y.; Natarajan, Priyamvada; Vogelsberger, Mark.--This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)., We propose the tracing of the motion of a shearing hot spot near the Sgr A* source through a dynamical image reconstruction algorithm, StarWarps. Such a hot spot may form as the exhaust of magnetic reconnection in a current sheet near the black hole horizon. A hot spot that is ejected from the current sheet into an orbit in the accretion disk may shear and diffuse due to instabilities at its boundary during its orbit, resulting in a distinct signature. We subdivide the motion into two different phases: the first phase refers to the appearance of the hot spot modeled as a bright blob, followed by a subsequent shearing phase. We employ different observational array configurations, including EHT (2017, 2022) and the next-generation Event Horizon Telescope (ngEHTp1, ngEHT) arrays, with several new sites added, and make dynamical image reconstructions for each of them. Subsequently, we infer the hot spot angular image location in the first phase, followed by the axes ratio and the ellipse area in the second phase. We focus on the direct observability of the orbiting hot spot in the sub-mm wavelength. Our analysis demonstrates that for this particular simulation, the newly added dishes are better able to trace the first phase as well as part of the second phase before the flux is reduced substantially, compared to the EHT arrays. The algorithm used in this work can be easily extended to other types of dynamics, as well as different shearing timescales. More simulations are required to prove whether the current set of newly proposed sites are sufficient to resolve any motions near variable sources, such as Sgr A*. © 2023 by the authors. Licensee MDPI, Basel, Switzerland., Razieh Emami acknowledges the support by the Institute for Theory and Computation at the Center for Astrophysics, as well as grant numbers 21-atp21-0077, NSF AST-1816420, and HST-GO-16173.001-A for the very generous supports. We thank the supercomputer facility at Harvard where most of the simulation work was carried out. P.T. and F.R. was supported by NSF grants AST-1935980 and AST-203430. A.R. and K.C. acknowledge support by the National Science Foundation under Grant No. OISE 1743747. P.T., A.R., and K.C. acknowledge the support of grants from the Gordon and Betty Moore Foundation and the John Templeton Foundation. P.N. gratefully acknowledges support at the Black Hole Initiative (BHI) at Harvard as an external PI with grants from the Gordon and Betty Moore Foundation and the John Templeton Foundation. Support for this work was provided by NASA through the NASA Hubble Fellowship grant HST-HF2-51518.001-A awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-26555., With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S).

This paper describes an innovative Decentralized Technical Sustainable Drainage System (SuDS) concept, which is based on technical devices, such as sieves, sedimentation barriers, floating barriers and a magnetic module, which addresses, mainly, the fine matter. The SuDS is designed as a retrofit system so that no costly and time-consuming conversion measures are necessary. Due to the possibility of free configurability of individual modules in the three levels, road, gully and drain, a novel solution approach is presented, which is not available on the market, for a reduction in solids in general and microplastics in particular. The retention performance of selected modules and their combinations is demonstrated by means of bench tests according to the test procedure of the German Institute for Construction Engineering (DIBt) for the evaluation of decentralized treatment systems. Four different rain intensities, from light to medium up to heavy rain, are charged to the filter modules. Collected and fractionated road-deposited sediment (RDS) was selected as the test substance (10 kg). Additional tests with tyre powder, PE pellets, cigarette butts and candy wrappers helped to make clear the filter process of the particulate matter. The retention performance was determined by the mass balance between the defined dosage and at the outlet. For this purpose, the total volume flow of the effluent was passed over a stainless-steel sieve with a diameter of 600 mm and a mesh size of 20 µm. For the test substance, RDS retention rates up to 97% were measured. Very fine matter, particularly, was technically challenging to obtain

Background In the process of designing drugs and proteins, it is crucial to recognize hot regions in protein–protein interactions. Each hot region of protein–protein interaction is composed of at least three hot spots, which play an important role in binding. However, it takes time and labor force to identify hot spots through biological experiments. If predictive models based on machine learning methods can be trained, the drug design process can be effectively accelerated. Results The results show that different machine learning algorithms perform similarly, as evaluating using the F-measure. The main differences between these methods are recall and precision. Since the key attribute of hot regions is that they are packed tightly, we used the cluster algorithm to predict hot regions. By combining Gaussian Naïve Bayes and DBSCAN, the F-measure of hot region prediction can reach 0.809. Conclusions In this paper, different machine learning models such as Gaussian Naïve Bayes, SVM, Xgboost, Random Forest, and Artificial Neural Network are used to predict hot spots. The experiment results show that the combination of hot spot classification algorithm with higher recall rate and clustering algorithm with higher precision can effectively improve the accuracy of hot region prediction.

Integrin-linked kinase (ILK) has emerged as a controversial pseudokinase protein that plays a crucial role in the signaling process initiated by integrin-mediated signaling. However, ILK also exhibits a scaffolding protein function inside cells, controlling cytoskeletal dynamics, and has been related to non-neoplastic diseases such as chronic kidney disease (CKD). Although this protein always acts as a heterotrimeric complex bound to PINCH and parvin adaptor proteins, the role of parvin proteins is currently not well understood. Using in silico approaches for the design, we have generated and prepared a set of new tripeptides mimicking an alpha-parvin segment. These derivatives exhibit activity in phenotypic assays in an ILK-dependent manner without altering kinase activity, thus allowing the generation of new chemical probes and drug candidates with interesting ILK-modulating activities.

Globally, dementia is one of the highest priority public health policy issues. This study was conducted to analyze the spatial distribution pattern of dementia prevalence using geographic weighted regression analysis and to identify preventable risk factors at the regional level of dementia prevalence. For the data to be analyzed, this work used the 2020 regional dementia prevalence index of the Korea Central Dementia Center and the regional health statistics of the Korea Centers for Disease Control and Prevention Agency (KDCA). Spatial autocorrelation analysis, hot spot analysis, and geographic weighted regression analysis were performed to identify regional associations of dementia prevalence, cluster regions with high dementia prevalence, and risk factors for regional dementia prevalence. As a result of the hot spot analysis, the regions corresponding to the hot spots with the high prevalence of dementia were found to be adjacent to each other, such as in Jeonnam, Jeonbuk, and Gyeongbuk, and the regions corresponding to the cold spots with the low prevalence of dementia were adjacent to each other, such as Seoul, Gyeonggi, Incheon, Busan, and Ulsan. The results of geographic weighted regression analysis showed that educational level, walking practice rate, hypertension prevalence, and a low-sodium diet preference were found to be risk factors for the prevalence of dementia. These results suggest that there is a need for a dementia prevalence management strategy to increase the walking practice rate and low-sodium diet preference rate, and decrease the hypertension prevalence, centering on the hot spot area, which is a cluster area with high dementia prevalence. This study is expected to be useful as basic data that can help in prioritizing health policies considering spatial characteristics for community health promotion.

The hot spot effect is an important factor that affects the power generation performance and service life in the power generation process. To solve the problems of low detection efficiency, low accuracy, and difficulty of distributed hot spot detection, a hot spot detection method using a photovoltaic module based on the distributed fiber Bragg grating (FBG) sensor is proposed. The FBG sensor array was pasted on the surface of the photovoltaic panel, and the drift of the FBG reflected wavelength was demodulated by the tunable laser method, wavelength division multiplexing technology, and peak seeking algorithm. The experimental results show that the proposed method can detect the temperature of the photovoltaic panel in real time and can identify and locate the hot spot effect of the photovoltaic cell. Under the condition of no wind or light wind, the wave number and variation rule of photovoltaic module temperature value, environmental temperature value, and solar radiation power value were basically consistent. When the solar radiation power fluctuated, the fluctuation of hot spot cell temperature was greater than that of the normal photovoltaic cell. As the solar radiation power decreased to a certain value, the temperatures of all photovoltaic cells tended to be similar.

Photovoltaic panels exposed to harsh environments such as mountains and deserts (e.g., the Gobi desert) for a long time are prone to hot-spot failures, which can affect power generation efficiency and even cause fires. The existing hot-spot fault detection methods of photovoltaic panels cannot adequately complete the real-time detection task; hence, a detection model considering both detection accuracy and speed is proposed. In this paper, the feature extraction part of YOLOv5 is replaced by the more lightweight Focus structure and the basic unit of ShuffleNetv2, and then the original feature fusion method is simplified. Considering that there is no publicly available infrared photovoltaic panel image dataset, this paper generates an infrared photovoltaic image dataset through frame extraction processing and manual annotation of a publicly available video. Consequently, the number of parameters of the model was 3.71 M, mAP was 98.1%, and detection speed was 49 f/s. A comprehensive comparison of the accuracy, detection speed, and model parameters of each model showed that the indicators of the new model are superior to other detection models; thus, the new model is more suitable to be deployed on the UAV platform for real-time photovoltaic panel hot-spot fault detection.

Several empirical studies of reductions in air pollutants as social distancing and working from home (WFH) policies have sparked recommendations that the COVID-19 pandemic might have been responsible for better air quality particularly in urban area. These findings offer a compelling provocation for the scientific community to detect and investigate variations to air quality as a consequence of government enforced quarantine. In spite of countless research studies focusing on the connection between WFH policy and air pollutant levels, the majority of discussion has unfortunately ignored the central role of other potential sources (e.g. agricultural waste burnings, cooking emissions, and industrial releases) in governing air quality, or has neglected the psychological and social impacts of COVID-19. In this study, a t test was used to compare the average concentrations of PM2.5 and COVID-19-infected numbers (n) in three different periods which were n

This study analyzed the spatial distribution patterns of depression among vulnerable elderly across Republic of Korea. The average level of depression in the basic administrative districts was derived using the individual depression scores from the Health Interview Survey data. Results of the spatial autocorrelation analysis revealed that the Moran’s I value was 0.3138, indicating the existence of a neighborhood effect in the depression of the vulnerable older adults at the regional level. Subsequently, cluster analysis and one-way ANOVA were conducted for the hot spots where vulnerable older adult depression was concentrated. Based on the cluster analysis results, hot spots were the areas where the facilities that are necessary for the daily lives of older adults were insufficient and were categorized into three types. The findings indicate that environmental characteristics at the regional level should be considered in addition to the environmental characteristics of the house and neighborhood, which have been primarily addressed in previous studies.

Gallium-doped p-type passivated emitter and rear contact (PERC) solar cells, which eliminate light-induced degradation (LID) and reduce the impact of light- and elevated-temperature-induced degradation (LeTID), have completely replaced boron-doped p-type PERC cells. However, in previous experiments, we found hot spots in the center of gallium-doped PERC solar cells. In this study, it was found that gallium-doped PERC cells had uneven resistivity, which caused hot spots brought about by the avalanche breakdown of PN junctions. There were significant hot spots in the center of the tested cells, with an average resistivity of 0.4–0.5 Ωcm and nonuniformity greater than 30%, or at an average resistivity of 0.5–0.6 Ωcm with nonuniformity greater than 40%. In this paper we describe and study in detail hot spots triggered by the uneven resistivity of gallium-doped cells and analyze the causes and related influencing factors, thereby providing guidance and a reference for the improvement of the performance and reliability of gallium-doped PERC solar cells.

Though the combustion chemistry of dimethyl ether (DME) has been widely investigated over the past decades, there remains a dearth of ignition data that examines the low-temperature, low-pressure chemistry of DME. In this study, DME/`air¿ mixtures at various equivalence ratios from lean (0.5) to extremely rich (5.0) were ignited behind reflected shock waves at a fixed pressure (3.0 atm) over the temperature range 625¿1200¿K. The ignition behavior is different from that at high-pressures, with a repeatable ignition delay time fall-off feature observed experimentally in the temperature transition zone from the negative temperature coefficient (NTC) regime to the high-temperature regime. This could not be reproduced using available kinetic mechanisms as conventionally homogeneous ignition simulations. The fall-off behavior shows strong equivalence ratio dependence and disappears completely at an equivalence ratio of 5.0. A local ignition kernel postulate was implemented numerically to quantifiably examine the inhomogeneous premature ignition. At low temperature, no pre-ignition occurs in the mixture. A conspicuous discrepancy was observed between the measurements and constrained UV simulations at temperatures beyond the NTC regime. A third O2 addition reaction sub-set was incorporated into AramcoMech 3.0, together with related species thermochemistry calculated using the G3/G4/CBS-APNO compound method, to explore the low-temperature deviation. The new reaction class does not influence the model predictions in IDTs, but the updated thermochemistry does. Sensitivity analyses indicate that the decomposition of hydroperoxy-methylformate plays a critical role in improving the low-temperature oxidation mechanism of DME but unfortunately, the thermal rate coefficient has never been previously investigated. Further experimental and theoretical endeavors are required to attain holistic quantitative chemical kinetics based on our understanding of the low-temperature chemistry of DME. Financial support from the National Natural Science Foundation of China (No. 91741115 and 51888103) and Shanxi National Science Foundation (2018JC-002) is acknowledged. peer-reviewed 2022-09-14

Power transformers are the most common equipment in an electric power system, which has been manufactured in the last decade. However, overheating can damage them, considerably reducing their operation lives, which may cause economic losses to the power utilities. The motivation of this paper is to investigate the time and power overload limits that a power transformer can be subjected to and how it will impact its temperature. Investments in the grid can be delayed if a transformer can support some overload during some momentary load demand increase. In this context, this paper presents a study of a 30/40MVA power transformer by 3D finite element method (FEM) for coupled thermal-electromagnetic simulations to investigate its thermal behaviour when it is submitted to its nominal load at a steady-state operation and a variable load during a period of one day. The simulations were performed with the commercial software packages Flux 3D and AcuSolve, for electromagnetic and thermal modelling, respectively. The modelled equipment was based on a power transformer installed in the Light Serviços de Eletricidade S.A, the utility that supplies electrical energy to the city of Rio de Janeiro, in Brazil. Since the literature doesn’t present many works simulating coupled thermal-electromagnetic power transformers in 3D-FEM, this paper has the goal to bring new contributions to this field. Three study cases were modelled, and some simplifications in transformer’s geometry were made in some of them to reduce the computation time usually required for such a simulation. The obtained results are presented and compared with the measured values for the temperature in the hot spot of the transformer and in the top of the oil, to investigate the impact of these simplifications in the calculated results.

Coherent control is an ingenious tactic to steer a system to a desired optimal state by tailoring the phase of an incident ultrashort laser pulse. A relevant process is the two-photon–induced photoluminescence (TPPL) of nanoantennas, as it constitutes a convenient route to map plasmonic fields, and has important applications in biological imaging and sensing. Unfortunately, coherent control of metallic nanoantennas is impeded by their ultrafast femtosecond dephasing times so far limiting control to polarization and spectral optimization. Here, we report that phase control of the TPPL in resonant gold nanoantennas is possible. We show that, by compressing pulses shorter than the localized surface plasmon dephasing time (

Urban environment imposes challenges due to its dynamics and thermodynamic characteristics of the built environment. The present study aims to study the effect of lockdown during COVID-19 on the spatio-temporal land surface temperature (LST) patterns in Dehradun city. The TIRS sensor data of 14 April 2020 (post-lockdown), 28 April 2019, 25 April 2018 and 08 May 2017 were downloaded, and LST was retrieved using radiative transfer equation. The wardwise change in LST, urban hot spots and thermal comfort was studied as a function of built-up density. It was observed that there was an overall decrease in LST values in Dehradun city in post-COVID lockdown period. Wards with high built-up density had minimum decrease in LST; on the contrary, wards with large proportion of open spaces and having low, medium built-up density had the maximum decrease in LST. Hot spot analysis was carried out using Getis Ord GI* statistic, and the level of thermal comfort was found using the urban thermal field variance index. It was observed that there was an increase in number of hot spots accompanied by a decrease in thermal comfort level post-lockdown. The methodology proposed in the present study can be applied to other Indian cities which exhibit similar growth patterns and will provide a tool for rational decision making.

Background: Iran detected its first COVID-19 case in February 2020 in Qom province, which rapidly spread to other cities in the country. Iran, as one of those countries with the highest number of infected people, has officially reported 1812 deaths from a total number of 23049 confirmed infected cases that we used in the analysis. Materials and Methods: Geographic distribution by the map of calculated incidence rates for COVID -19 in Iran within the period was prepared by GIS 10.6 Spatial autocorrelation (Global Moran's I) and hot spot analysis were used to assess COVID -19 spatial patterns. The ordinary least square method was used to estimate the relationship between COVID -19 and the risk factors. The next step was to explore Geographically Weighted Regression (GWR) models that might better explain the variation in COVID -19 cases based on the environmental and socio-demographic factors. Results: The spatial autocorrelation (Global Moran's I) result showed that COVID-19 cases in the studied area were in clustered patterns. For statistically significant positive z-scores, the larger the z-score is, the more intense the clustering of high values (hot spot), such as Semnan, Qom, Isfahan, Mazandaran, Alborz, and Tehran. Hot spot analysis detected clustering of a hot spot with confidence level 99% for Semnan, Qom, Isfahan, Mazandaran, Alborz, and Tehran, as well. The risk factors were removed from the model step by step. Finally, just the distance from the epicenter was adopted in the model. GWR efforts increased the explanatory value of risk factor with better special precision (adjusted R-squared = 0.44) Conclusion: The highest CIR was concentrated around Qom. Also, the greater the distance from the center of prevalence (Qom), the fewer the patients. Hot spot analysis also implies that the neighboring provinces of prevalence centers exhibited hot spots with a 99% confidence level. Furthermore, the results of OLS analysis showed the significant correlation of CIR is with the distance from epicenter (Qom). The GWR can result in the spatial granularity providing an opportunity to well understand the relationship between environmental spatial heterogeneity and COVID-19 risk as entailed by the infection of CIR with COVID-19, which would make it possible to better plan managerial policies for public health. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

زمین لغزش­ها ازجمله مخاطرات طبیعی هستند که همه‌ساله موجب خسارات جانی و مالی زیاد، به­ویژه در نواحی کوهستانی می­شوند. شهرستان خلخال با داشتن چهرۀ کوهستانی و با توجه به وضعیت زمین­شناسی، فیزیوگرافی، اقلیمی و انسانی، عمده شرایط لازم جهت شکل­گیری حرکات لغزشی را داراست؛ لذا هدف تحقیق حاضر، پهنه­بندی خطر زمین­لغزش در این شهرستان می­باشد. در این مطالعه ابتدا، عوامل مؤثر جهت ایجاد لغزش در منطقه شناسایی شدند و سپس نسبت به تهیۀ لایه­های اطلاعاتی در سامانه اطلاعات جغرافیایی اقدام گردید. در مرحله بعد وزن­دهی عوامل مورد بررسی، با استفاده از روش ANP و در محیط نرم­افزار Super Decisionانجام گردید و تحلیل و مدل­سازی نهایی با استفاده از روش تحلیل لکه­های داغ به عنوان روش آمار فضایی و نیز روش WLC به عنوان یکی از روش­های تصمیم­گیری چند معیاره، انجام شد. نتایج مطالعه نشان داد، عوامل شیب، کاربری اراضی، بارش و لیتولوژی به ترتیب با ضریب وزنی 663/0، 646/0، 639/0 و 379/0 بیش‌ترین تأثیر را بر ایجاد زمین­لغزش در شهرستان خلخال دارند. همچنین، با توجه به نتایج به دست آمده به ترتیب 33/249، 08/385 و 14/427 کیلومتر­مربع از مساحت محدوده، در طبقات لکه داغ، با ضریب اطمینان 99، 95 و 90 درصد، قرار دارند.

Background: Alcohol use is common among male tuberculosis (TB) patients of Puducherry, particularly from lower socioeconomic strata who consume liquor from local arrack shops. These shops could be hot spots for the transmission of infection. Hence, this study aimed to explore whether arrack shops could be probable hot spots for the transmission of infection. Materials and Methods: An exploratory, descriptive study was conducted at three primary health-care centers in Puducherry, among male pulmonary TB patients using a pretested semistructured questionnaire. Home visits and visit to the arrack shop were made to assess for factors conducive to the transmission of TB. Results: Most of the patients belonged to lower socioeconomic status and consumed alcohol, mostly from arrack shops. The arrack shops had poor sanitation, were overcrowded, and multiple persons with TB visited the shop. Many had the behavior of spending more than an hour at the arrack shops. Conclusion: There is a possibility of TB transmission of at the arrack shops. Active case finding in the arrack shop may be beneficial.

Background Human echinococcosis is affected by natural environmental factors, and its prevalence shows a distinct geographical distribution. Western China has the highest endemicity of human echinococcosis worldwide, but the spatial pattern and environmental determinants of echinococcosis are still unclear. Methods Hot/cold spot analysis was used to investigate the spatial distribution of human echinococcosis prevalence. Geodetector was used to identify key natural factors, and a structured additive regression model was used to analyse the relationship between natural factors and human echinococcosis prevalence and spatially predict echinococcosis epidemics. Results Hot spots for human echinococcosis prevalence include western and southeastern parts of Tibet Autonomous Region (henceforth Tibet) and the border areas between Tibet and the provinces of Qinghai and Sichuan. Spatial effects are crucial when modelling epidemics, and relative humidity, altitude and grassland area ratio were found to have the most evident effects on echinococcosis epidemics. The relationship between these three factors and echinococcosis prevalence was non-linear, and echinococcosis risk was higher in areas with high relative humidity, high altitude, and a high ratio of grassland to other land use types. The prevalence that was predicted from the investigated environmental factors was generally higher than the actual prevalence, and more epidemic hot spots were predicted for the Qinghai-Tibet Plateau, Inner Mongolia Autonomous Region, and the provinces of Yunnan and Sichuan than the rest of western China. These results indicate that prevention and control measures may effectively reduce echinococcosis prevalence. Conclusions We suggest that the prevention and control of human echinococcosis should be prioritized in the hot spots identified here, through the rational allocation of limited medical resources to where they are most needed. Furthermore, the spatial epidemiological modelling methods used in this study can be employed in future studies on echinococcosis and similar diseases. Graphical abstract

Der Trend der Miniaturisierung führt dazu, dass elektronische Geräte auf kleinstem Raum verbaut werden und gleichzeitig einen erhöhten Funktionsumfang erfüllen müssen. Um die geforderten Leistungsdichten zu realisieren, werden zunehmend moderne Leistungshalbleiter mit sehr kleinen Abmessungen verwendet. Durch die Miniaturisierung der Leistungselektronik ist vor allem die Wärmespreizung von kleinen Heizquellen von Interesse, d.h. die Heizquelle befindet sich in der Mitte und die Wärme wird über eine größere Fläche verteilt. Mit sogenannten plattenförmigen pulsierenden Heatpipes (PHPs) kann die Wärme effizient verteilt werden. Innerhalb der PHP stellt sich eine selbstoszillierende Zweiphasenströmung ein, sodass sowohl der konvektive Wärmetransport als auch der Phasenwechsel genutzt wird. Die vorliegende Arbeit hat das Ziel, optimierte PHP-Designs zur Wärmespreizung von kleinen Heizquellen zu entwickeln., The trend towards miniaturization of electronic components leads to a higher power density. Modern power semiconductors are used to realize the required power densities. This changes the requirements for thermal management. Due to miniaturization of power electronics, heat spreading is of particular interest for small heat sources, i.e., in case that the heat source is located in the center and the heat is spread over a larger area. Flat plate pulsating heat pipes (PHPs) are a passive two-phase system for heat transport. The oscillating two-phase flow inside the PHP uses both convective heat transfer and phase change. The present work aims to develop optimized PHP designs for heat spreading of small heat sources.

Cluster-based hot spot detection is applied in many disciplines to analyze the locations, concentrations, and evolution over time for a phenomenon occurring in an area of study. The hot spots consist of areas within which the phenomenon is most present; by detecting and monitoring the presence of hot spots in different time steps, it is possible to study their evolution over time. One of the most prominent problems in hot spot analysis occurs when measuring the intensity of a phenomenon in terms of the presence and impact on an area of study and evaluating its evolution over time. In this research, we propose a hot spot analysis method based on a fuzzy cluster hot spot detection algorithm, which allows us to measure the incidence of hot spots in the area of study. We analyze its variation over time, and in order to evaluate its reliability we use a well-known fuzzy entropy measure that was recently applied to measure the reliability of hot spots by executing fuzzy clustering algorithms. We apply this method in crime analysis of the urban area of the City of London, using a dataset of criminal events that have occurred since 2011, published by the City of London Police. The obtained results show a decrease in the frequency of all types of criminal events over the entire area of study in recent years.

Near-field properties due to surface plasmon excitation is a key element for different applications of metal nanoparticles, such as surface-enhanced Raman scattering (SERS). Therefore, a characterization of such properties is fundamental for the correct interpretation of experimental results, such as the strong fluctuation of intensities observed at low analyte concentrations, especially at single-molecule detection level. In this paper, we investigate, by classical electrodynamics simulations, the link between the near-field properties of metal nanoclusters and the intensity distribution that is expected in a given single-molecule SERS experiment. The results presented here points to the possibility of correlating the intensity histograms shapes to properties such as degree of field amplification localization and aggregation state of metal nanoparticles.

Planar fractal microstructure is observed on the silver film treated by positive corona discharge for the first time. Due to the abundant positive ions driven by the electrical field of positive polarity, surface modification is mainly induced by the plasma oxidation effect, resulting in a large scale of dendritic pattern with self-similarity and hierarchy. In contrast, negative ions dominate the plasma-film interaction under negative corona discharge condition, leading to a different surface morphology without fractal characteristics. A growth model based on the modified diffusion-limited aggregation (DLA) theory is proposed to describe the formation of the dendritic fractal structure, whilst the physics behind is attributed to the electric field directed diffusion of the positive ions around the surface roughness. Numerical simulation verifies the high density of the hot spot in the dendritic pattern, which may enable potential applications in fractal photonic metamaterials.

The morphostructural characteristics of the main taxa of southern Indian Ocean, such as the Del Cano-Crozet, Conrad, and Kerguelen plateaus, are given based on structural-tectonic analysis. A depth map of the acoustic basement of the eastern part of the Afro-Antarctic megadepression is first built using the digitized NGDS database on the thickness of the sedimentary cover of the Indian Ocean, which is available on the Internet. A critical analysis of deep seismic sounding (DSS) data on the Kerguelen plateu hs been performed. A geochemical analysis of more than 100 samples of basalts, acidic rocks, and rocks of sedimentary origin, collected on the islands of the Kerguelen archipelago and raised by dredging and deep-sea drilling from the Kerguelen and Conrad plateaus, is carried out. The study has shown that the plateaus resemble the Madagascar Ridge in terms of morphostructure and a number of other features. It is concluded that these flat-topped horst massifs were the part of the “structural bridge” that connected Madagascar and the eastern part of mainland Antarctica no later than the Paleogene. A proposed alternative version of the geological interpretation of the deep seismic data states that the plateau has a relatively homogeneous structure along the strike, including a thick (at least 15-km) layer of continental crust. An analysis of the depth map of the acoustic basement made it possible to identify the depocenters of the relatively isolated Enderby, Shackleton and Labuan basins framing the Kerguelen Plateau on the southern side. The paragenetic connections of the Kerguelen Plateau with the basins indicate that the isolation of the Kerguelen Plateau from East Antarctica and the formation of the modern structure of the region began in the Late Cretaceous and ended with the last phase of tectonic activation in the Late Miocene–Pliocene. The results of geochemical analysis show that the geochemical and petrological anomalies of the plateau and islands are associated with the crust, and not with the mantle contamination, as well as with the continental nature of the Kerguelen Plateau.

We report on the effects associated with photonic nanojet (PNJ) formation under illumination of a metallic spherical particle with a focused light beam with polarization singularity. Owing to radial polarization, the strongly focused beam generates the on-axis localized structure of intensity in the shadow area of the metal scatterer of different sizes, from the Rayleigh particle to microbeads. Significant amplification factor, small transverse size, and zero magnetic component on the axis and longitudinal polarization of the electric field are the distinctive features of such structures.

The contactless heating capacity of magnetic nanoparticles (MNPs) has been exploited in fields such as hyperthermia cancer therapy, catalysis, and enzymatic thermal regulation. Herein, we propose an advanced technology to generate multiple local temperatures in a single-pot reactor by exploiting the unique nanoheating features of iron oxide MNPs exposed to alternating magnetic fields (AMFs). The heating power of the MNPs depends on their magnetic features but also on the intensity and frequency conditions of the AMF. Using a mixture of diluted colloids of MNPs we were able to generate a multi-hot-spot reactor in which each population of MNPs can be selectively activated by adjusting the AMF conditions. The maximum temperature reached at the surface of each MNP was registered using independent fluorescent thermometers that mimic the molecular link between enzymes and MNPs. This technology paves the path for the implementation of a selective regulation of multienzymatic reactions., This work was funded by the European Commission through the HOTZYMES Project (H2020-FETOPEN-RIA 829162), the Spanish Ministry of Economy and Competitiveness under Grant No. MAT2017-88148-R (AEI/FEDER, UE) and the PIE-201960E062 project, AEI (BIO2017-84246-C2-1-R project to V.G. and J.M.F., and PID2019-109514RJ-100 to D.S.), Nanotechnology in translational hyperthermia (HIPERNANO) - RED2018-102626-T, and Fondo Social de la DGA (grupos DGA).

Graphical abstract, Cluster of differentiation 47 (CD47)/signal regulatory protein alpha (SIRPα) is a negative innate immune checkpoint signaling pathway that restrains immunosurveillance and immune clearance, and thus has aroused wide interest in cancer immunotherapy. Blockade of the CD47/SIRPα signaling pathway shows remarkable antitumor effects in clinical trials. Currently, all inhibitors targeting CD47/SIRPα in clinical trials are biomacromolecules. The poor permeability and undesirable oral bioavailability of biomacromolecules have caused researchers to develop small-molecule CD47/SIRPα pathway inhibitors. This review will summarize the recent advances in CD47/SIRPα interactions, including crystal structures, peptides and small molecule inhibitors. In particular, we have employed computer-aided drug discovery (CADD) approaches to analyze all the published crystal structures and docking results of small molecule inhibitors of CD47/SIRPα, providing insight into the key interaction information to facilitate future development of small molecule CD47/SIRPα inhibitors.

International audience; In order to introduce high-temperature superconducting fault current limiters (SFCL) into electrical networks, a model is needed to predict the various phenomena that appear within the limiter. This paper presents a model of a resistive type superconducting fault current limiter developed in OpenModelica software. The finite difference method is used to solve the heat equation. The model considers the electrical and thermal phenomena in the thickness and the length of the HTS tape, which allows to study the presence of hot spots phenomenon. An interfacial resistance is included in the proposed model

Hot spot is a serious challenge limiting long pulse operation with LHCD (lower hybrid current drive) in tokamak. In order to mitigate the hot spot in guard limiter and improve LHCD capability, effect of edge plasma density on inducing hot spot and current drive has been studied in EAST. The temperature in the guard limiter of the LH antenna, inducing hot spot directly, increases with edge density and LH power. Studies show that the hot spot is mainly ascribed to the heat flux in front of LH antenna. Further simulation indicates that such spot corresponds to the peak position of edge density due to local LH electric field. In addition, due to the stronger parametric instability (PI) behavior in the case of higher edge density, the current drive capability decreases with edge density. Strike-point splitting behaviors appear with density increase, in agreement with current profiles in the edge region and the reduction of total driven current, suggesting that more power is deposited in edge region, which does more contribution to hot spot. Above studies offer one possible idea to optimize the edge density so as to satisfy the coupling, mitigate the heat flux in the guard limiter, and improve current drive capability for fusion device.

Fire behaviour of R/C structures can be strongly affected by spalling phenomenon, which may offset the positive inherent features of concrete exposed to high temperature. This makes the screening of concretes by testing a key point in the design phase of spalling-sensitive structures. To this aim, three different testing procedures have been adopted within a multi-scale approach for investigating two concrete mixes containing different amounts of fibre. The three typologies of test are discussed by comparing experimental and numerical results, so to cast some light on their main differences. Although the experimental results may appear different, a common key of interpretation is recognized.

An accurate model describing the electro-thermal behavior of solar modules, subject to varying irradiance conditions, is presented. The model relies on an enhanced version of the popular one-diode model, implementing the temperature dependence of the parameters by means of a thermal feedback network. The feedback network is built by exploiting a very effective analytical approach which reduces computational efforts and allows an automated solution. The cell-level discretization allows the description of the temperature distribution over solar cell surfaces in panels subject to mismatch events (e.g., partial shading, localized soiling, etc.), along with its time evolution. Experiments performed on a partially shaded solar string evidence good agreement with the model. In uniform condition the temperature error is less than 3 °C, while, under mismatch, the error on the maximum temperature of a cell subject to hot spot is limited to 5 °C.

BackgroundDNA-binding hot spots are dominant and fundamental residues that contribute most of the binding free energy yet accounting for a small portion of protein–DNA interfaces. As experimental methods for identifying hot spots are time-consuming and costly, high-efficiency computational approaches are emerging as alternative pathways to experimental methods.ResultsHerein, we present a new computational method, termed inpPDH, for hot spot prediction. To improve the prediction performance, we extract hybrid features which incorporate traditional features and new interfacial neighbor properties. To remove redundant and irrelevant features, feature selection is employed using a two-step feature selection strategy. Finally, a subset of 7 optimal features are chosen to construct the predictor using support vector machine. The results on the benchmark dataset show that this proposed method yields significantly better prediction accuracy than those previously published methods in the literature. Moreover, a user-friendly web server for inpPDH is well established and is freely available athttp://bioinfo.ahu.edu.cn/inpPDH.ConclusionsWe have developed an accurate improved prediction model, inpPDH, for hot spot residues in protein–DNA binding interfaces by given the structure of a protein–DNA complex. Moreover, we identify a comprehensive and useful feature subset including the proposed interfacial neighbor features that has an important strength for identifying hot spot residues. Our results indicate that these features are more effective than the conventional features considered previously, and that the combination of interfacial neighbor features and traditional features may support the creation of a discriminative feature set for efficient prediction of hot spot residues in protein–DNA complexes.

The Republic of Burundi first reported cholera cases in 1978 and outbreaks have been occurring nearly every year since then. From 2008–2020, 6949 cases and 43 deaths were officially reported. To evaluate Burundi’s potential to eliminate cholera, we identified hotspots using cholera incidence and disease persistence as suggested by the Global Task Force for Cholera Control. The mean annual incidence for each district that reported cholera ranged from 0.29 to 563.14 cases per 100,000 population per year from 2014–2020. Ten of 12 Health Districts which recorded cholera cases reported a mean annual incidence ≥5 per 100,000 for this time period. Cholera cases occur during the second half of the year in the areas near Lake Tanganyika and along the Ruzizi River, with the highest risk district being Bujumbura Centre. Additional research is needed to understand the role of Lake Tanganyika; risks associated with fishing; migration patterns; and other factors that may explain cholera’s seasonality. Due to the consistent epidemiological pattern and the relatively small area affected by cholera, control and elimination are feasible with an integrated program of campaigns using oral cholera vaccine over the short term and community-based interventions including WASH activities for sustained control.

SARS-CoV-2 is an intensively investigated virus from the order Nidovirales (Coronaviridae family) that causes COVID-19 disease in humans. Through enormous scientific effort, thousands of viral strains have been sequenced to date, thereby creating a strong background for deep bioinformatics studies of the SARS-CoV-2 genome. In this study, we inspected high-frequency mutations of SARS-CoV-2 and carried out systematic analyses of their overlay with inverted repeat (IR) loci and CpG islands. The main conclusion of our study is that SARS-CoV-2 hot-spot mutations are significantly enriched within both IRs and CpG island loci. This points to their role in genomic instability and may predict further mutational drive of the SARS-CoV-2 genome. Moreover, CpG islands are strongly enriched upstream from viral ORFs and thus could play important roles in transcription and the viral life cycle. We hypothesize that hypermethylation of these loci will decrease the transcription of viral ORFs and could therefore limit the progression of the disease.

The Tirimbina Biological Reserve is located in the lowlands on the Atlantic versant of Costa Rica. This study provides an updated comprehensive herpetofauna species list and summarizes the results of all the herpetofauna research conducted at Tirimbina over the last ten years (2009–2019) across various microhabitats, both daytime and nighttime. We also added historical records from occasional sightings and reports from researchers, staff, visitors, interns, fellows, and volunteers since the 1990’s. We found 52 amphibian and 78 reptile species on the reserve, including a few species considered at–risk according to the IUCN Red List. We conclude that Tirimbina is a herpetofauna biodiversity hot spot in Costa Rica because it provides unique habitat characteristics for a variety of species, including habitat for both forest and forest–edge specialists. Tirimbina Biological Reserve for the Tirimbina–UCR research grant. UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Biodiversidad y Ecología Tropical (CIBET) UCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela de Biología

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES This master's thesis presents a study carried out on the identification of the electrical parameters of the photovoltaic module (PV) through characteristic curves measured in real climatic conditions, under various conditions of irradiance and temperature. For this, it is proposed to evaluate meta-heuristic and analytical techniques, seeking to qualify the expressions that best physically represent the electrical parameters of a diode model. In this way, this study presents a new proposal for a solution, bringing together analytical techniques and meta heuristics. The solution is based on a meta heuristic algorithm based on a JAYA optimization strategy, solving implicitly and integrated the various irradiance and temperature correction equations. The proposed method makes the union between the best of the two techniques analyzed and compared, in addition to allowing to compare and analyze the different models presented in the literature. In addition, at the end a case study is carried out and the influence of hot spots on the I-V curve and electrical parameters of the model of a diode of photovoltaic modules is evaluated. Thus, the main contributions of this dissertation are: the possibility of evaluating the models that have greater relevance in the problem of estimating the electrical parameters of a diode model; Obtaining electrical parameters and identifying the influence of temperature and irradiance under I-V curves and under the behavior of parameters; reduction of RMSE with the reached value 1.2119E-1 from the measured and estimated current through the application of the proposed method for the entire set of IV curves, presenting a reduction of the RMSE, in relation to the works presented and discussed in the state of the art for the same data set; evaluation of the impacts of hot spot on the photovoltaic modules and demonstration that the weighted average temperature (Tpond), better represented the operating temperature of the module. With the average RMSE of 4.12E-3 obtained, which represented an improvement of 48% when compared and we assigned the operating temperature to the value obtained by a sensor in the center of the module. Esta dissertação de mestrado apresenta um estudo realizado sobre a identificação dos parâmetros elétricos de módulo fotovoltaico (FV) através de curvas características medidas em condições climáticas reais, sob diversas condições de irradiância e temperatura. Para isso, propõem-se avaliar técnicas meta-heurísticas e analíticas, buscando qualificar as expressões que melhor representem fisicamente os parâmetros elétricos do modelo de um diodo. Desta forma, esse estudo apresenta uma nova proposta de solução realizando a união de técnicas analíticas e meta heurísticas. A solução é fundamentada em um algoritmo meta heurístico baseado em estratégia de otimização JAYA, resolvendo de forma implícita e integrada as diversas equações de correção da irradiância e temperatura. O método proposto faz a união entre o melhor das duas técnicas analisadas e confrontadas, além de permitir comparar e analisar os diferentes modelos apresentados na literatura. Além disso, ao final é realizado um estudo de caso e avaliado a influência de pontos quentes na curva I-V e parâmetros elétricos do modelo de um diodo de módulos fotovoltaicos. Assim, as principais contribuições desta dissertação são: a possibilidade de avaliar os modelos que possuem maior relevância no problema de estimação dos parâmetros elétricos do modelo de um diodo; Obtenção dos parâmetros elétricos e identificação da influência da temperatura e irradiância sob as curvas I-V e sob o comportamento dos parâmetros; redução do RMSE com o valor alcançado 1,2119E-1 de entre a corrente medida e estimada através da aplicação do método proposto para todo o conjunto de curvas I-V, apresentando uma redução do RMSE, com relação aos trabalhos apresentados e discutido no estado da arte para o mesmo conjunto de dados; avaliação dos impactos de ponto quente sobre os módulos fotovoltaico e demonstração que a temperatura média ponderada (Tpond), melhor representou a temperatura de operação do módulo. Com o RMSE médio de 4,12E-3 obtido, que representou uma melhoria de 48% quando comparado e atribuímos a temperatura de operação o valor obtido por um sensor no centro do módulo. São Cristóvão

Infectious diseases, such as COVID-19, SARS, MERS, etc., have seriously endangered human safety, economy, and education. During the spread of epidemics, restricting the range of activities of personnel is one of the options for the prevention and treatment of infectious diseases. A global navigation satellite system (GNSS), it can provide accurate coordinates of latitude and longitude to targets with GNSS receivers. However, it is not common to use GNSS coordinates to represent positions in social life. For epidemic management, it is important to know the locations (and addresses) of targets, especially in social life. When there are many targets, it is not easy to efficiently map these coordinates to locations. Therefore, we propose a GNSS-based crowd-sensing strategy for specific geographical areas that can be used to calculate how many targets are in specific geographical areas or whether a target is in a specific area. This strategy is based on the coordinates of latitude and longitude provided by GNSS to find the locations of these coordinates. As simulated data, the data records containing latitude and longitude in a well-known social networking service platform are used. The strategy is also available for mining hot spots or hot areas.

Several factors cause the output degradation of the photovoltaic (PV) module. The main affecting elements are the higher PV module temperature, the shaded cell, the shortened or conducting bypass diodes, and the soiled and degraded PV array. In this paper, we introduce an image processing technique that automatically identifies the module generating the hot spots in the solar module. In order to extract feature points, we used the maximally stable extremal regions (MSER) method, which derives the area of interest by using the inrange function, using the blue color of the PV module. We propose an effective matching method for feature points and a homography translation technique. The temperature data derivation method and the normal/ abnormal decision method are described in order to enhance the performance. The effectiveness of the proposed system was evaluated through experiments. Finally, a thermal image analysis of approximately 240 modules was confirmed to be 97% consistent with the visual evaluation in the experimental results.

There have been numerous reports that the impact of the ongoing COVID-19 epidemic has disproportionately impacted traditionally vulnerable communities associated with neighborhood attributes, such as the proportion of racial and ethnic minorities, migrants, and the lower income households. The goal of this ecological cross-sectional study is to examine the demographic and economic nature of spatial hot and cold spots of SARS-CoV-2 rates in New York City and Chicago as of April 13, 2020 using data from the New York City Department of Health and Mental Hygiene, Illinois Department of Public Health, and the American Community Survey. In both cities, cold spots (clusters of low SARS-CoV-2 rate ZIP code tabulation areas as identified by the Getis-Ord (GI*) statistic) demonstrated social determinants of health characteristics typically associated with better health outcomes and the ability to maintain physical distance (“social distancing”). These neighborhoods tended to be wealthier, have higher educational attainment, higher proportions of non-Hispanic white residents, and more workers in managerial occupations (all p values

Recently, photochemical synthesis has attracted wide interest on in situ preparing the surface-enhanced Raman scattering (SERS) substrate with excellent performance, especially in a compact space and microfluidic channel. Herein, a facile, green and cost-effective approach to in situ photochemically synthesize silver nanoaggregates is demonstrated for SERS applications. By adjusting the photo-irradiation conditions, the morphologies and sizes of the silver nanoaggregates can be deliberately tailored. The synthesized silver nanoaggregates-based substrates exhibit a highly sensitive and reproducible SERS activity with a low detection limit of 10&minus, 8 M for 4-Aminothiophenol detection and relative standard deviation of 12.3%, paving an efficient and promising route for in situ SERS-based rapid detection in the environmental monitoring and food quality control.

Президент России Владимир Путин подписал закон о дополнительных социальных гарантиях для журналистов, работающих в горячих точках. Закон представляет собой поправки к действующему закону СМИ. Поправки обязывают работодателя заключать с работником договоры страхования, обеспечивать журналистов, работающих в горячих точках, средствами индивидуальной защиты, опознавательным знаком Пресса ( Press ) и международным удостоверением журналиста, а также проводить обучение сотрудников мерам безопасности. С 1 сентября 2019 г. закон на стороне журналистов., Russian President Vladimir Putin signed a law on additional social guarantees for journalists working in trouble spot. The law is an amendment to the current media law. The amendments oblige the employer to enter into insurance contracts with the employee, to provide journalists working in trouble spots with personal protective equipment, the press identification mark and the international journalists certificate, as well as to train employees in security measures., №8 (2020)

Non-native species have been introduced at escalating rates during the last decades, mainly due to the dispersion generated by the increasing trade and transport worldwide. Mollusks, the second largest metazoan phylum in terms of species richness, are no exception to this pattern, but, to date, a comprehensive synthesis of non-native mollusk species (NNMS) in South America was not available. For this purpose, an e-discussion group was formed with malacologists and taxonomists from South America, where we exchanged and analyzed bibliography, databases and information about NNMS, providing expert opinion to this assessment. The first list of non-native mollusk species for South America, considering terrestrial, freshwater and marine environments, includes 86 NNMS distributed in 152 ecoregions (terrestrial, freshwater and marine) of the 189 recognized for the South American continent. Information on their native region, vectors, first record for South America and distribution, are also provided. In the analysis of the distribution of the NNMS and the entry points of each species (e.g., ports, cargo and passenger airports, cities) and status of conservation of the ecoregions, four hot spots were recognized: Subtropical-AtlanticNorthern Andes, Central Andes and Southern Andes. This work, thus, sets the baseline on NNMS for South America, a key piece of information regarding the development of policies targeting the management of biological invasions and their socio-ecological impacts., Facultad de Ciencias Naturales y Museo, Consejo Nacional de Investigaciones Científicas y Técnicas