There are many new land use and land cover (LULC) products emerging yet there is still a lack of in-situ data for training, validation, and change detection purposes. The LUCAS (Land Use Cover Area frame Sample) survey is one of the few authoritative in-situ field campaigns, which takes place every three years in European Union member countries. More recently, a study has considered whether citizen science and crowdsourcing could complement LUCAS survey data, e.g., through the FotoQuest Austria mobile app and crowdsourcing campaign. Although the data obtained from the campaign were promising when compared with authoritative LUCAS survey data, there were classes that were not well classified by the citizens, and the photographs submitted through the app were not always of sufficient quality. For this reason, in the latest FotoQuest Go Europe 2018 campaign, several improvements were made to the app to facilitate interaction with the citizens contributing and to improve their accuracy in LULC identification. In addition to extending the locations from Austria to Europe, a change detection component (comparing land cover in 2018 to the 2015 LUCAS photographs) was added, as well as an improved LC decision tree and a near real-time quality assurance system to provide feedback on the distance to the target location, the LULC classes chosen and the quality of the photographs. Another modification was the implementation of a monetary incentive scheme in which users received between 1 to 3 Euros for each successfully completed quest of sufficient quality. The purpose of this paper is to present these new features and to compare the results obtained by the citizens with authoritative LUCAS data from 2018 in terms of LULC and change in LC. We also compared the results between the FotoQuest campaigns in 2015 and 2018 and found a significant improvement in 2018, i.e., a much higher match of LC between FotoQuest Go Europe and LUCAS. Finally, we present the results from a user survey to discuss challenges encountered during the campaign and what further improvements could be made in the future, including better in-app navigation and offline maps, making FotoQuest a model for enabling the collection of large amounts of land cover data at a low cost.

Background: A new coronavirus (SARS-CoV-2) that emerged from Wuhan, Hubei Province, China, has spread throughout the world and is declared a pandemic by the World Health Organization (WHO). A lot remains to be understood of SARS-CoV-2 and the disease (COVID-19). SARS-CoV-2 has until recently been identified as responsible for both asymptomatic and serious life-threatening infections. The unavailability of specific therapeutic agents is a major hurdle in the treatment and management of COVID-19 patients. The present review attempts to evaluate the immunobiochemical aspects of the pathogenesis, diagnosis, and management of SARS-CoV-2 infection. Main Body: This review is a comprehensive evaluation of the data collected through various sources, including Google Scholar, PubMed, and Scopus. The articles were searched and selected using key words such as “Coronavirus disease (COVID-19)”, “Diagnosis of COVID-19”, Pathogenesis of Covid-19”, “management of COVID-19”, “Immunology of COVID-19”, and “Complications of COVID-19”. The study noted that the novel Coronavirus infection could result in an exaggerated immune response, causing a cytokine storm and damaging several organs of the body. The infected patients develop several complications, including immunological, hematological, and biochemical alterations. Consequently, COVID-19 patients may develop cardiovascular, liver, renal, and neurological complications, among others. Conclusion: An increased understanding of the immunobiochemical aspects of the disease may contribute to better management of SARS-CoV-2-infected persons, as evidenced from the available literature. A holistic approach to the management of COVID-19 patients taking into consideration the effect of COVID-19 infection on various organs of the body assumes increased significance in patient management.

Background: Understanding SARS-CoV-2 dynamics and transmission is a serious issue. Its propagation needs to be modeled and controlled. The Alsace region in the East of France has been among the first French COVID-19 clusters in 2020. Methods: We confront evidence from three independent and retrospective sources: a population-based survey through internet, an analysis of the medical records from hospital emergency care services, and a review of medical biology laboratory data. We also check the role played in virus propagation by a large religious meeting that gathered over 2,000 participants from all over France mid-February in Mulhouse. Results: Our results suggest that SARS-CoV-2 was circulating several weeks before the first officially recognized case in Alsace on February 26^th 2020 and the sanitary alert on March 3^rd. The religious gathering seems to have played a role for secondary dissemination of the epidemic in France, but not in creating the local outbreak. Conclusions: Our results illustrate how the integration of data coming from multiple sources could help trigger an early alarm in the context of an emerging disease. Good information data systems, able to produce earlier alerts, could have avoided a general lockdown in France.

This paper proposed a damping method for enhancing oscillatory stability performance of power systems with high penetration of renewable energy by a resilient wide-area multi-mode controller. The resilient wide-area multi-mode controller is used as an additional controller in a renewable energy system with a battery energy storage to enhance the damping of the critically weak modes. The weak modes are likely to be triggered in the event of line outages or any other disturbances, and the system may become unstable in the absence of proper corrective and preventive control. A firefly algorithm has been employed to design such a controller. Eigenvalue analysis and time-domain simulation are used to analyze the performance of the proposed controller in a realistic representative power system. From the simulation results, it is evident that the oscillatory stability performance of the renewable rich power system can be enhanced with the proposed control to keep the damping on critical modes to the industrial standards. Furthermore, renewable energy penetration can be increased significantly in the realistic representative system by introducing the proposed controller without disturbing the oscillatory stability margin.

Wenchuan earthquake that occurred in China in 2008 caused severe damage to a large number of electric substations. In this paper, Kriging interpolation method was used to calculate the impact area of the instrumental seismic intensity in Wenchuan earthquake, and to compare the intensities based on strong motion observation against the instrumental seismic intensities at locations where the observation data is available. The instrumental seismic intensities were calculated for the Wenchuan Earthquake at substations in the national power grid with voltage of 110kV or higher in areas of Mianyang, Deyang, Guangyuan and Chengdu. The cumulative Gaussian distribution function was then used to fit the relationship of the curves of the damage probabilities of high-voltage electrical equipment such as transformers, voltage mutual inductors, current mutual inductors, circuit breakers, isolating switches and lightning arrester with their instrumental seismic intensities. The damage probability density distribution curve of high-voltage electrical equipment based on the instrumental seismic intensities was obtained. The results showed that: (1) In the lower seismic intensity region, the mean instrumental seismic intensity was in good agreement with the traditional seismic intensity, but there was noticeable dispersion; in regions of intensity IX and above, the instrumental intensity was lower than the seismic intensity, but there was a lower degree of dispersion. (2) Among high-voltage electrical equipment, the transformers were most vulnerable to damage and they had some damage even under lower instrumental intensity. More damage would be produced when the instrumental intensity reached VIII or above; the second most vulnerable equipment was the circuit breaker, and the damage was most likely to occur when the instrument intensity was IX or above . (3) The damage rate curves of lightning arresters, current mutual inductors, voltage mutual inductors and isolating switches were relatively close to each other and the damage probability was the highest when the instrumental intensity was about X.

Uniform water soluble MoS2 quantum dots (WS-MSQDs) are synthesized via a sequential combination of sintering/etching/exfoliation method and solvothermal route. The obtained WS-MSQDs with average size of approximately 3.4 nm exhibit sufficient water solubility and remarkable fluorescence properties. The WS-MSQDs have been utilized as a probe for detection of Fe3+ ions with high selectivity and specificity. Furthermore, the WS-MSQDs exhibit high fluorescence stability under different conditions. Finally, the WS-MSQDs are successfully applied for the fluorescence imaging of Fe3+ in living cells, which exhibited practical potential for biomedical applications.

Sickle cell disease is characterized by stiff, “sickled” red blood cells that have difficulty moving through the bloodstream and do not efficiently carry oxygen. It is an inherited disease with severely limited treatment options, and is caused by a point mutation. Its prevalence in black and brown communities makes the already limited treatment options even less accessible. Base editing and prime editing are two relatively recent discoveries in the field of genome editing and were developed after the groundbreaking discovery of the CRISPR Cas9 system. While not fully tested, they hold a lot of promise in providing alternative treatment options for sickle cell disease. Both editing systems are able to install individual point mutations in the beta globin gene, which is where the sickle cell mutation occurs, and can thus cure sickle cell disease (in theory). In this paper we outline the mechanisms of CRISPR-Cas9 systems and base and prime editing, and provide insight into how to apply them to treat SCD. Further investigation should be done on specific editing systems and designs to use to ensure optimal treatment of SCD.

Wenchuan earthquake that occurred in China in 2008 caused severe damage to a large number of electric substations. In this paper, Kriging interpolation method was used to calculate the impact area of the instrumental seismic intensity in Wenchuan earthquake, and to compare the intensities based on strong motion observation against the instrumental seismic intensities at locations where the observation data is available. The instrumental seismic intensities were calculated for the Wenchuan Earthquake at substations in the national power grid with voltage of 110kV or higher in areas of Mianyang, Deyang, Guangyuan and Chengdu. The cumulative Gaussian distribution function was then used to fit the relationship of the curves of the damage probabilities of high-voltage electrical equipment such as transformers, voltage mutual inductors, current mutual inductors, circuit breakers, isolating switches and lightning arrester with their instrumental seismic intensities. The damage probability density distribution curve of high-voltage electrical equipment based on the instrumental seismic intensities was obtained. The results showed that: (1) In the lower seismic intensity region, the mean instrumental seismic intensity was in good agreement with the traditional seismic intensity, but there was noticeable dispersion; in regions of intensity IX and above, the instrumental intensity was lower than the seismic intensity, but there was a lower degree of dispersion. (2) Among high-voltage electrical equipment, the transformers were most vulnerable to damage and they had some damage even under lower instrumental intensity. More damage would be produced when the instrumental intensity reached VIII or above; the second most vulnerable equipment was the circuit breaker, and the damage was most likely to occur when the instrument intensity was IX or above . (3) The damage rate curves of lightning arresters, current mutual inductors, voltage mutual inductors and isolating switches were relatively close to each other and the damage probability was the highest when the instrumental intensity was about X.

Soybean maturity is a trait of critical importance for the development of new soybean cultivars, nevertheless, its characterization based on visual ratings has many challenges. Unmanned aerial vehicles (UAVs) imagery-based high-throughput phenotyping methodologies have been proposed as an alternative to the traditional visual ratings of pod senescence. However, the lack of scalable and accurate methods to extract the desired information from the images remains a significant bottleneck in breeding programs. The objective of this study was to develop an image-based high-throughput phenotyping system for evaluating soybean maturity in breeding programs. Images were acquired twice a week, starting when the earlier lines began maturation until the latest ones were mature. Two complementary convolutional neural networks (CNN) were developed to predict the maturity date. The first using a single date and the second using the five best image dates identified by the first model. The proposed CNN architecture was validated using more than 15,000 ground truth observations from five trials, including data from three growing seasons and two countries. The trained model showed good generalization capability with a root mean squared error lower than two days in four out of five trials. Four methods of estimating prediction uncertainty showed potential at identifying different sources of errors in the maturity date predictions. The architecture used solves limitations of previous research and can be used at scale in commercial breeding programs.

Background: Most drug-resistant Escherichia coli isolates in dogs come from diseased dogs. Prior to this study, the prevalence and risk factors of fecal carriage drug-resistant E. coli and epidemic clone sequence type (ST) 131 (including subtypes) isolates in dogs were unknown. Methods: Rectal swabs were used for E. coli isolation from 299 dogs in a veterinary teaching hospital in Taiwan. Antibiotic resistance and multiplex PCR analyses of E. coli for major STs were performed. Result: There were 43.1% cefazolin-resistant, 22.1% fluoroquinolone-resistant, and 9.4% extended-spectrum beta-lactamase-producing E. coli in our cohort. In the phylogenetic study, B2 was the predominant group (30.1%). The cefazolin-resistant group and ciprofloxacin-resistant group had greater antibiotic exposure in the last 14 days (P < 0.05). The age, sex, and dietary habits of the antibiotic-resistant and -susceptible groups were similar. In the seven isolates of ST131 in fecal colonization, the most predominant subtypes were FimH41 and FimH22. Conclusion: Recent antibiotic exposure was related to the fecal carriage of antibiotic-resistant E. coli isolates. Three major subtypes (FimH41, H22, and H30) of ST131 can thus be found in fecal carriage in dogs in Taiwan.

Pneumonia cases of unknown etiology in Wuhan, China, were reported to the WHO on 31st of December 2019. Later the pathogen was reported to be a novel coronavirus designated Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that causes Coronavirus Disease 2019 (COVID-19). SARS-CoV-2 is a novel pathogenic beta coronavirus that infects humans causing severe respiratory illness. However, multifarious factors can contribute to the susceptibility to COVID-19 related morbidity and mortality such as age, gender and underlying comorbidities. Importantly, SARS-CoV and SARS-CoV-2 entry into the host cells is mediated via ACE2 receptor. However, ACE2 receptor binding affinity to SARS-CoV-2 is 4 folds higher than that to SARS-CoV. Identification of different aspects such as binding affinity, differential antigenic profiles of spike glycoproteins, and ACE2 polymorphisms might influence the investigation of potential therapeutic strategies targeting SARS-CoV-2/ACE2 binding interface. Here we aim to elaborate on SARS-CoV-2 S1/ACE2 ligand that facilitates viral internalization as well as to highlight the differences between SARS-CoVs binding affinity to ACE2. We also discuss the possible immunogenic sequences of spike glycoprotein and the effect of ACE2 polymorphism on viral binding/infectivity and host susceptibility to disease. Furthermore, targeting of ACE2 will be discussed to understand its role in therapeutics.

Radiological risk affect the quality of the environment in buildings since population and workers can be potentially exposed to high level of dose. Radon gas emanated from both subsoil and building materials represents the most important source of radiation exposure for people. This study investigates the sustainability concept of a small rural village of Ischia Island, named Ciglio, in relation to the radiological risk. Radon activity concentration was measured in typical green tuff dwellings and in water samples collected from a local spring using E-Perm devices. Moreover, for green-tuff as building material, the radon emanation coefficient was calculated by gamma spectroscopy. The results highlight the importance to perform environmental radon monitoring and to investigate the radon content of building materials, especially in geographical areas characterized by traditional use of typical stones for constructions. In conclusion, the sustainability development of rural buildings is possible if the radiological risk for inhabitants and workers was assessed.

Daphne wolongensis described on the basis of a few known individuals was investigated in the wild, in Baoxing Valey, Sechuan. Its status of valid species was verified morphologically and genetically. Three newly found populations were compared to the closely related species Daphne retusa, D. tangutica, D. longilobata, D. acutiloba, D. sureil, to clones available in cultivation and selected cultivars. The high bootstrap values indicate a good level of genetic differentiation between each of the studied species. The hypothesis whether D. wolongensis is a hybridogenous species was rejected, it is a well-defined independent species. Based on morphological and genetic data, it seems likely that another species, D. limprichtii can be a mountain form of D. tangutica. Variability of populations in Wolong gives a good opportunity to select genotypes with a higher or better performance of combination of traits. From 51samples collected in Wolong it was possible to select the top ten different types as genetic resources for breeding. Daphne wolongensis, in the visited sites of Wolong area, occupies less than 1 km2. Together with isolated finds, the number of found individuals is less than 500 and the area is not larger than 10 km2, thus it falls to the IUCN category of “Critically Endangered” plants.

The electrical, mechanical and thermal conductivity of ethylene butene copolymer (EBC) composites with carbon fibers were studied. EBC/carbon-fiber composites can be utilized as an electro-mechanical material which is capable of changing it electric resistance with mechanical strain. Carbon fibers were introduced to EBC with different concentrations (5-25 wt%). The results showed that the addition of carbon fibers to EBC could increase the electric resistance up to 10 times. Increasing the load to 2.9 MPa could increase the electric resistance change by 4500% compared 25% fiber sample with pure EBC. It is also noted that the electric resistance of the EBC/CF composites underwent a dramatic increase with raising the strain, for example, the resistance change was around 13 times more at 15% strain in comparison to 5% of strain; The thermal conductivity tests showed that the addition of carbon fibers could increase the thermal conductivity by 40%, from 0.19 to 0.27 (Wm-1K-1). It was also observed that the addition of carbon fibers to EBC could increase the thermal conductivity.

Reductions in water availability and increasing rainfall variability are generating a narrative of growing competition for water in the Mediterranean basin. In this article, we explore the distribution and importance of water resources in the Muga River Basin (Catalonia, Spain) based on key stakeholders’ perceptions. We performed a sociocultural evaluation of the main water ecosystem services in the region through stakeholder interviews and participatory mapping. The basin was generally perceived as a hotspot of ecosystem services, but we detected varying opinions and considerable differences in the perceptions of importance and spatial distribution of water ecosystem services. These discrepancies were linked to the varying levels of stakeholders’ dependence on water. Our findings are important for contributing to correct water planning and management in the river basin, which is a complex water social system marked by conflicts between different stakeholder groups vying for the same resource. This complex situation requires bottom-up strategies to create transparent, participatory decision-making models.

A brief technical and economic insight into producing the water-soluble yellow colorant limocitrol 3-O-6”-[3-hydroxyl-3-methylglutaryl)])-β-D-glucopyranoside from waste lemon peel via simple solid-liquid extraction in aqueous ethanol or via hydrodynamic cavitation of waste lemon peel in water, shows that the biocolorant can be obtained at affordable cost. Coupled to the simplicity and sustainability of the extraction processes suggested, the high chemical and physical stability of this polymethoxylated flavanol and the health benefits of citrus flavonoids, support industrialization of this new bioeconomy production.

Rationale: Examining trends in patient characteristics, processes of care and outcomes, across an epidemic, provides important opportunities for learning. Objectives: To report and explore changes in admission rates, patient characteristics, processes of care and outcomes for all patients with COVID-19 admitted to intensive care units (ICUs) in England, Wales and Northern Ireland. Methods: Population cohort of 10,287 patients with COVID-19 in the Case Mix Programme national clinical audit from 1 February to 2 July, 2020. Analyses were stratified by time period (pre-peak, peak, post-peak) and geographical region. Multivariable logistic regression was used to estimate differences in 28-day mortality, adjusting for patient characteristics over time. Main results: Admissions to ICU peaked simultaneously across regions on 1 April, with ongoing admissions peaking ten days later. Compared with pre- and post-peak periods, patients admitted during the peak were slightly younger but had greater respiratory and renal dysfunction. Use of invasive ventilation and renal replacement reduced over time. Twenty-eight-day mortality reduced from 43.5% (95% CI 41.6% to 45.5%) pre-peak to 34.3% (95% CI 32.3% to 36.2%) post-peak; a difference of −8.8% (95% CI: −5.2%, −12.3%) after adjusting for patient characteristics. London experienced the highest admission rate and had higher mortality during the peak period but a greater reduction in post-peak mortality. Conclusion: This study highlights changes in patient characteristics, processes of care and outcomes, during the UK COVID-19 epidemic. After adjusting for the changes in patient characteristics and first 24-hour physiology, there was substantial improvement in 28-day mortality over the course of the epidemic.

Glutathione peroxidases (GPxs) form a broad family of antioxidant proteins essential for maintaining redox homeostasis in eukaryotic cells. In this study, we used an integrative approach that combines bioinformatics, molecular biology, and biochemistry to investigate the role of GPxs in reactive oxygen species detoxification in the unicellular eukaryotic model organism Tetrahymena thermophila. Both phylogenetic and mechanistic empirical model analyses provided indications about the evolutionary relationships among the GPXs of Tetrahymena and the orthologous enzymes of phylogenetically related species. In-silico gene characterization and text mining were used to predict the functional relationships between GPxs and other physiologically-relevant processes. The GPx genes contain conserved transcriptional regulatory elements in the promoter region, which suggest that transcription is under tight control of specialized signaling pathways. The bioinformatic findings were next experimentally validated by studying the time course of copper (Cu)-dependent regulation of gene transcription and enzymatic activity. Results emphasize the role of GPxs in the detoxification pathways that, by complex regulation of Cu-dependent GPx gene expression, enables Tetrahymena to survive in high Cu concentrations and the associated redox environment.

Non-homologous end-joining (NHEJ) is a DNA repair pathway required to detect, process, and ligate DNA double-stranded breaks (DSBs) throughout the cell cycle. The NHEJ pathway is necessary for V(D)J recombination in developing B and T lymphocytes. During NHEJ, Ku70 and Ku80 form a heterodimer that recognizes DSBs and promotes recruitment and function of downstream factors PAXX, MRI, DNA-PKcs, Artemis, XLF, XRCC4, and LIG4. Mutations in several known NHEJ genes result in severe combined immunodeficiency (SCID). Inactivation of Mri, Paxx or Xlf in mice results in normal or mild phenotype, while combined inactivation of Xlf/Mri, Xlf/Paxx, or Xlf/Dna-pkcs leads to late embryonic lethality. Here, we describe three new mouse models. We demonstrate that deletion of Trp53 rescues embryonic lethality in mice with combined deficiencies of Xlf and Mri. Furthermore, Xlf^-/-Mri^-/-Trp53^+/- and Xlf^-/-Paxx^-/-Trp53^+/- mice possess reduced body weight, severely reduced mature lymphocyte counts, and accumulation of progenitor B cells. We also report that combined inactivation of Mri/Paxx results in live-born mice with modest phenotype, and combined inactivation of Mri/Dna-pkcs results in embryonic lethality. Therefore, we conclude that XLF is functionally redundant with MRI and PAXX during lymphocyte development in vivo. Moreover, Mri genetically interacts with Dna-pkcs and Paxx.

This study was conducted to investigate the prevalence of Coxiella burnetii infection according to cattle breeds and growth types. A total of 491 cattle [cattle breed: 216 dairy cattle and 275 beef cattle; according to growth type: indoor housing (n = 294) and grazing (n = 197)] were tested for the presence of C. burnetii DNA and antibodies against C. burnetii using a commercial enzyme-linked immunosorbent assay (ELISA). Overall, 10.8% and 8.8% of the cattle were positive by PCR and for C. burnetii antibodies, respectively. The prevalence of C. burnetii was significantly higher in beef cattle than in dairy cattle using PCR (13.6% vs 7.4%; P = 0.032) and ELISA (14.6% vs 1.4%; P = 0.000), respectively. The overall infection rate of C. burnetii was significantly high in grazing cattle (PCR: 24.9%, ELSIA: 21.3%; P = 0.000) compared with housing cattle (PCR: 1.4%, ELISA: 0.3%). The results indicate that beef cattle have a significantly higher risk of contracting C. burnetii infection compared with dairy cattle (21.5% vs. 7.9%, χ2 = 5.82, P = 0.000, odds ratio = 3.197, 95% CI: 1.80-5.67). In addition, the infection of C. burnetii was significantly associated with grazing (P = 0.000). Moreover, a risk of contracting C. burnetii infection in grazing cattle was increased by 32.57-fold (95% CI: 12.84-82.60, P = 0.000) compared with indoor housed cattle. The phylogenetic analysis based on the IS111 gene revealed that our isolates were grouped together with humans, ticks, goats, and cattle isolates found in several countries. C. burnetii isolates circulating in the Republic of Korea exhibit genetic variations. Consequently, our results suggest that cattle are potential reservoirs for C. burnetii infection and most importantly, grazing acts as a high risk factor for the occurrence and transmission of this infection.

Andean blueberries are wild berries grown and consumed in Ecuador which contain high values of bioactive compounds, mainly anthocyanins, with powerful antioxidant activity. The aim of this study was to evaluate the profile and contents of (poly)phenols and carotenoids in Andean blueberry by HPLC-DAD-MSn and determine a wide range of its biological activities. The antioxidant capacity of this fruit was evaluated in vitro by three different methods and in vivo using the zebrafish animal model, also the toxicity effect was determined by the zebrafish embryogenesis test. Besides, the antimicrobial activity and the capacity of Andean blueberry to produce hemagglutination in blood cells were evaluated. Finally, the bioaccessibility of (poly)phenols and related antioxidant capacity were determined in the different phases of an in vitro digestion. The global results indicated no toxicity of Andean blueberry, weakly bacteriostatic activity, and high contents of anthocyanins and antioxidant capacity, which were partially bioaccesible in vitro (~ 50 % at the final intestinal step), contributing to the knowledge of its health benefits for consumers and its potential use in the food and pharmaceutical industry as functional ingredient.

MicroRNAs are used as biomarkers for classification of cancer subtypes since certain miRNAs are differentially expressed in normal and patient samples. Moreover, miRNAs target mRNAs and can heavily influence Gene Expressions. Thus, deregulation of miRNAs is linked to various disorders. Thus, miRNAs can be used for prognosis and developing personalized health solutions for patients. Given the importance of miRNAs, there has been substantial work done in the field. In this paper, recent works in the field of using miRNAs expressions of patients were considered. A total of 20 papers were surveyed which utilized feature selection ensembles, fuzzy logic as well as deep learning. 10 papers have been reported which offer insight into how miRNAs can be utilized for subtype-specific or generalized cancer diagnosis.

The experimental results of forces and efforts derived from the opening of incisions in the orbital cavity in a pig’s head are presented in this article. The different areas of the incision openings are related to the needs at the incision procedure for a dacryocystorhinostomy. In terms of the experimental procedure, an origin and a plane are defined so as to allow the location of the opening of the incision. The incisions are retracted along an axis of said origin. This procedure has been based on the mathematical model developed for this work, which consists of a procedure for determining the behavior of an incision when a force is applied to retract the skin. The experimental data obtained, suggests the existence of an almost linear relationship between the increment of resistance in relation to the time obtained for each opening, the same of which is deemed to be consistent with the behavior of an elastic material.

Due to legal regulations, the rise of globalised (online) commerce and the need for public health protection, the analysis of spirits (alcoholic beverages > 15 % vol) is a task with growing importance for governmental and commercial laboratories. In this article a newly developed method using nuclear magnetic resonance (NMR) spectroscopy for the simultaneous determination of 15 substances relevant for the quality and authenticity assessment of spirits is described. The new method starts with a simple and rapid sample preparation and does not need an internal standard. For each sample a group of 1H-NMR spectra is recorded, among them a 2D spectrum for analyte identification and 1D spectra with suppression of solvent signals for quantification. Using the Pulse Length Based Concentration Determination (PULCON) method, concentrations are calculated from curve fits of the characteristic signals for each analyte. The optimisation of the spectra, their evaluation and the transfer of the results are done fully automatically. Glucose, fructose, sucrose, acetic acid, citric acid, formic acid, ethyl acetate, ethyl lactate, acetaldehyde, ethanol, methanol, n-propanol, isobutanol, isopentanol, 2-phenylethanol and 5-(hydroxymethyl)furfural (HMF) can be quantified with an overall accuracy better than 8 %. This new NMR-based targeted quantification method enables the simultaneous and efficient quantification of relevant spirits ingredients in their typical concentration ranges in one process with good accuracy. It has proven to be a reliable method for all kinds of spirits in routine food control.

Foot-and-mouth disease virus (FMDV) causes the highly contagious foot-and-mouth disease, which is characterized by the appearance of vesicles in and around the mouth and feet of cloven-hoofed animals. BHK21 cells are the cell line of choice for the propagation of FMDV for vaccine production world-wide but vary in their susceptibility for different FMDV strains. Previous studies showed that the FMDV resistance of a certain BHK cell line can be overcome by using a closely related but permissive cell line for the pre-adaptation of the virus, but the adapted strains were found to harbor several capsid mutations. In this study, these adaptive mutations were introduced into the original Asia-1 Shamir isolate individually or in combination to create a panel of 17 Asia-1 mutants by reverse genetics and examine the effects of the mutations on receptor usage, viral growth, immunogenicity and stability. A single amino acid exchange from glutamic acid to lysine at position 202 in VP1 turned out to be of major importance for productive infection of the suspension cell line BHK-2P. In consequence, two traditionally passage-derived strains and two recombinant viruses with a minimum set of mutations were tested in vivo. While the passaged-derived viruses showed a reduced particle stability, the genetically modified viruses were more stable but did not confer a protective immune response against the original virus isolate.

Mitigation of Anthropogenic CO2 emissions possess a major global challenge for modern societies. Herein catalytic solutions are meant to play a key role. Among the different catalysts for CO2 conversion Cu supported on molybdenum carbide is receiving increasing attention. Hence, in the present communication we show the activity, selectivity and stability of fresh-prepared -Mo2C catalysts and compare the results with those of Cu/Mo2C, Cs/Mo2C and Cu/Cs/Mo2C in CO2 hydrogenation reactions. The results showed that all the catalysts were active and the main reaction product was methanol. The results showed that copper-cesium and molybdenum effectively interact and that cesium promoted the formation of metallic Mo. While, the incorporation of copper is positive to improve the activity and selectivity to methanol, the presence of Mo0 phase was detrimental for the conversion and selectivity. Moreover, the catalysts promoted by cesium underwent redox surface transformations during the reaction that diminished their catalytic performance. The molybdenum phase in Cu/Mo2C changes during reaction leading to metallic molybdenum and tuning the catalytic activity.

This work presents the results of a computational study of the chemical reactivity and bioactivity properties of the members of the Theopapuamides A-D family of marine peptides by making use of our own proposed methodology named Computational Peptidology (CP) that has been successfully considered in previous studies of this kind of molecular systems. CP allowed for the determination of the global and local descriptors that come from Conceptual Density Functional Theory (CDFT) that can give an idea of the chemical reactivity properties of the marine natural products under study which are already known to be related to their bioactivity. At the same time, the validity of the procedure based on the adoption of the KID (Koopmans in DFT) technique as well as the MN12SX/Def2TZVP/H2O model chemistry has been successfully verified. Together with several Chemoinformatic tools that can be used for the improvement of process of Virtual Screening, some additional properties of these marine peptides were identified related to their ability to behave as useful drugs. With the further object of analyzing their bioactivity some parameters of usefulness for future QSAR studies, their predicted biological targets and the the ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) parameters related to the Theopapuamides A-D pharmacokinetics are also reported.

Background: In the present study, cisplatin, artemisinin and oleanolic acid were evaluated alone and in combination, on human ovarian A2780, A2780ZD0473R and A2780cisR cancer cell lines with aim of overcoming cisplatin resistance and side effects. Methods: Cytotoxicity was assessed by MTT reduction assay. CI values were used as a measure of combined drug effect. MALDI TOF/TOF MS/MS and 2-DE gel electrophoresis were used to identify protein biomarkers in ovarian cancer and to evaluate combination effects. Results: Synergism from combinations was dependent on concentration and sequence of administration. Generally, bolus was most synergistic. 49 proteins differently expressed by 2 ≥ fold were: CYPA, EIF5A1, Op18, p18, LDHB, P4HB, HSP7C, GRP94, ERp57, mortalin, IMMT, CLIC1, NM23, PSA3,1433Z, and HSP90B were down-regulated, whereas hnRNPA1, hnRNPA2/B1, EF2, GOT1, EF1A1, VIME, BIP, ATP5H, APG2, VINC, KPYM, RAN, PSA7, TPI, PGK1, ACTG and VDAC1 were up-regulated, while TCPA, TCPH, TCPB, PRDX6, EF1G, ATPA, ENOA, PRDX1, MCM7, GBLP, PSAT, Hop, EFTU, PGAM1, SERA and CAH2 were not-expressed in A2780cisR cells. The proteins were found to play critical roles in cell cycle regulation, metabolism and biosynthetic processes and drug resistance and detoxification. Conclusion: Results indicate that appropriately sequenced combinations of cisplatin with ART and OA may provide a means to reduce side effects and circumvent platinum resistance.

Plants are affected by soil environments to the same extent they affect soil functioning through interactions between environmental and genetic factors. Here, five plant species (broad bean, pea, cabbage, fennel, and olive) grown under controlled pot conditions were tested for their ability to differently stimulate the degradation of standard litter. Litter, soil C and N contents and soil microbial abundance were measured. The architecture and morphological traits of roots systems were also evaluated by using specific open-source software (SmartRoot). Soil chemical and microbiological characteristics were significantly influenced by the plant species. Variations in soil C/N dynamics were correlated with the diversity of root traits among species. Early-stage decomposition of the standard litter changed on the basis of the plant species. The results indicated that key soil processes are governed by interactions between plant roots, soil C and N, and the microbial metabolism that stimulate decomposition reactions. This, in turn, can have marked effects on soil chemical and microbiological fertility, both fundamental for sustaining crops, and can promote the development of new approaches for optimizing soil C and N cycling, managing nutrient transport, and sustaining and improving net primary production.

Signaling through GPR109a, the putative receptor for the endogenous ligand β-OH butyrate, inhibits adipose tissue lipolysis. Niacin, an anti-atherosclerotic drug that can induce insulin resistance, activates GPR109a at nM concentrations. GPR109a is not essential for niacin to improve serum lipid profiles. To better understand the involvement of GPR109a signaling in regulating glucose and lipid metabolism, we treated GPR109a wildtype (+/+) and knockout (-/-) mice with repeated overnight injections of saline or niacin in physiological states characterized by low (ad libitum fed) or high (16h fasted) concentrations of the endogenous ligand, β-OH butyrate. In the fed state, niacin increased expression of PEPCK mRNA independent of genotype, while increasing CPT1 mRNA only in GPR109a -/- mice. Niacin decreased fasting serum non-esterified fatty acid concentrations in both GPR109a +/+ and -/- mice. Independent of GPR109a expression, niacin blunted fast-induced hepatic triglyceride accumulation and peroxisome proliferator activated receptor α (PPARα) mRNA expression. Surprisingly, GPR109a knockout did not affect glucose or lipid homeostasis or hepatic gene expression in either fed or fasted mice. In turn, GPR109a does not appear to be essential for the metabolic response to the ketogenic state or the pharmacological benefits associated with niacin.

Purpose: Recently introduced molecules namely long non-coding RNAs (lncRNAs) are associated with various diseases, including breast cancer, and they may have the potential to act as biomarkers. Invasive ductal carcinoma (IDC) is a frequently observed type of breast cancer that diagnosis through immunohistochemical methods. However, no reliable non-invasive markers such as circulating markers have been introduced for it, so far. Materials and methods: The relative quantitation (RQ) of two lncRNAs, RP11-445H22.4 and TINCR, was measured in tumoral tissues and paired adjacent non-tumoral tissues (PANTs) as well as in plasma samples using real-time polymerase chain reaction (RT-PCR). Furthermore, promoter methylation of the two lncRNAs genes was assessed using methylation-specific PCR (MSP). In order to compare the diagnostic values, plasma levels of CA 15-3 were measured as a conventional circulating biomarker using ELISA. The receiver operating characteristic (ROC) curve was used to illustrate the sensitivity and specificity of the potential biomarkers. Results: The RP11-445H22.4 and TINCR genes were upregulated in tumor tissues compared to PANTs (RQ_{RP11-445H22.4} = 2.7, RQ_TINCR = 4.4). Furthermore, the presence of RP11-445H22.4 and TINCR in the plasma of patients was significantly more than healthy controls (RQ_{c.RP11-445H22.4} = 4.12, RQ_c.TINCR = 4.16, P<0.001). The promoters of RP11-445H22.4 and TINCR genes were hypomethylated in the tumoral tissues with a negative correlation with their gene expression. Conclusion: Based on the findings, it can be speculated that the expression levels of these two lncRNAs as well as their promoter methylation can be considered as a therapeutic target and potential biomarker for breast carcinoma.

Metal 3D printing technology is a promising manufacturing method, especially in the case of complex shapes. The quality of the printed product is still a challenging issue for mechanical applications. The anisotropy of the microstructure, imperfections, and residual stress are some of the issues that diminish the mechanical properties of the printed sample. The simulation could be used to investigate some technical details, and this research has tried to computationally study the metal 3D printing of austenitic stainless steel to address austenite microstructure and local yield strength. Two computational codes were developed in Visual basics 2015 to simulate the local heating/cooling curve and subsequent austenite microstructure. A stochastic computational code was developed to simulate austenite grain morphology based on calculated thermal history. Then Hall-Pitch equation was used to estimate the yield strength of the printed sample. These codes were used to simulate the effect of temperature of the printer’s chamber on microstructure and subsequent yield strength. The austenite grain topology is more columnar at a lower temperature. The percentage of the equiaxed zone will be increased at a higher chamber’s temperature. Almost a fully equiaxed austenite microstructure will be achieved at 800 C chamber’s temperature, but the last printed layer, which is columnar and can be removed by cutting then. The estimated local austenite grain size and the local yield strength in the equiaxed regions are in the range of 15 to 30 μm and 270 to 330 MPa at 800 C temperature of printer’s chamber, respectively.

In this article, we analyse the computer aid screening method of COVID19 using Xray and CT scan images. The main objective is to set an analytical closure about the computer aid screening of COVID19 among the X-ray image and CT scan image. The computer aid screening method includes deep feature extraction, transfer learning and traditional machine learning image classification approach. The deep feature extraction and transfer learning method considered 13 pre-trained CNN model. The machine learning approach includes three sets of features and three classifiers. The pre-trained CNN models are alexnet, googlenet, vgg16, vgg19, densenet201, resnet18, resnet50, resnet101, inceptionv3, inceptionresnetv2, xception, mobilenetv2 and shufflenet. The features and classifiers in machine learning approaches are GLCM, LBP, HOG and KNN, SVM, Naive bay’s respectively. In addition, we also analyse the different paradigms of classifiers. In total, the comparative analysis is carried out in 65 classification models, i.e. 13 in deep feature extraction, 13 in transfer learning and 39 in machine learning approaches. Finally, all the classification models perform better in X-ray image set compare to CT scan image set.

A super-porous hybrid platform can offer significantly increased number of reaction sites for the analytes and thus can offer advantages in the biosensor applications. In this work, a significantly improved sensitivity and selectivity of hydrogen peroxide (H2O2) cancer sensor is demonstrated by a super-porous hybrid CuO/Pt NP platform. The super-porous hybrid platform is fabricated by a physiochemical approach combining the physical vapor deposition of Pt NPs and electrochemical deposition of super-porous CuO structures by adopting a dynamic hydrogen bubble technique. Under an optimized condition, the hybrid CuO/Pt biosensor demonstrates a very high sensitivity of 2,205 µA/mM∙cm2 and a low limit of detection (LOD) of 140 nM with a wide range of H2O2 detection. This is meaningfully improved performance as compared to the CuO-based H2O2 sensors as well as to the previously reported metal oxide based H2O2 sensors. The hybrid CuO/Pt platform exhibits excellent selectivity against other interfering molecules such as glucose, fructose, dopamine, and ascorbic acid. Due to the synergetic effect of highly porous CuO structures and underlying Pt NPs, the CuO/Pt architecture offers extremely abundant active sites for the H2O2 reduction and electron transfer pathways.

Age-related sarcopenia meaningfully increases the risks of functional limitations and mortality in the elderly. Although circulating microRNAs (c-miRNAs) are associated with aging-related cellular senescence and inflammation, the relationships between c-miRNAs and sarcopenia in the elderly remain unclear. This study investigates whether circulating myo-miRNAs and inflammation-related miRNAs are associated with sarcopenia in the elderly. This study recruited 77 eligible subjects (41 males and 36 females) from 597 community-dwelling older adults, and then divided into normal (n=24), dynapenic (loss of muscular function without mass, n=35), and sarcopenic groups (loss of muscular function with mass, n=18). Moreover, myo-miRNAs (c-miRNA-133a and c-miRNA-486), inflammation-related miRNAs (c-miRNA-21 and c-miRNA-146a), and inflammatory-related cytokine levels in plasma were determined using quantitative polymerase chain reaction and ELISA, respectively. The results demonstrated that sarcopenic group exhibited lesser skeletal muscle mass index (SMI), handgrip strength, and gait speed, as well as, lower c-miR-486 and c-miR-146a levels, compared to those of normal and dynapenic groups. Moreover, c-miR-486 level was positively related to SMI (r=0.334, P=0.003), whereas c-miR-146a level was positively associated with SMI (r=0.240, P=0.035) and handgrip strength (r=0.253, P=0.027). In the receiver operating characteristic analysis for predicting sarcopenia, the area under the curve in c-miR-486 was 0.708 (95% confidence interval: 0.561-0.855, P=0.008) and c-miR-146a was 0.676 (95% CI: 0.551-0.801, P=0.024). However, no significant relationships were observed between SMI/ handgrip strength/gait speed and plasma myeloperoxidase/interleukin-1?/interleukin-6 levels. In conclusion, myo-miRNA (c-miR-486) and inflammation-related miRNA (c-miR-146a) are superior to inflammatory peroxide/cytokines in plasma for serving as critical biomarkers of age-related sarcopenia.

Nickel based superalloys finds extensive usage in manufacturing of intricate part shapes in gas turbine, aircraft, submarine, and chemical industries owing their excellent mechanical property and heat resistant abilities. However, machining of such difficult-to-machine alloys up to the desired accuracy and preciseness is a complex task owing to a rapid tool wear and failure. In view of this, present work proposes an experimental investigation and optimization of process parameters of the cryogenic assisted turning process during machining of Nimonic C-263 super alloy with a multilayer CVD insert. Taguchi’s L-27 orthogonal array is used plan the experiments. Effect of input parameters viz. cutting speed (N), cutting feed (f), depth of cut (d) are studied on responses viz. surface roughness (SR), nose wear (NW) and cutting forces (F) under hybrid cryogenic (direct+indirect) machining environment. A scanning electron microscope (SEM) analysis is carried out to explore the post-machining outcomes on the performance measures. The multiple responses are converted in to single response and ranked according to Taguchi based gray relational grade (TGRG). Feed rate (f) is found to be the most influential parameter from the analysis of variance of GRG. The means of GRG for each level of process parameters are used to improve the optimal process parameters further. Finally, the confirmative experiment is performed with these optimal set of process parameters which showed an improvement of 9.34% in the value of GRG. The proposed work can be beneficial to choose ideal process conditions to enhance the performance of turning operation.

COVID-19 pandemic event requires a rapid response from various organizations at the international and national levels. One important response is the provision of information sharing facilities and monitoring of the spread of cases around the world, JHU CSSE developed the Dashboard in January 2020 and followed by WHO the same month for the WHO COVID-19 dashboard. Both dashboards have distributed information as expected by the user with their respective pros and cons. JHU CSSE Dashboard provides faster information with good access to mobile device users even though the display and color selection are less attractive. Information on the WHO COVID-19 Dashboard is often late but more data appearances and variations and comparisons between countries can be made. In the Indonesian context, ESSC for COVID-19 Geoportal as Esri Indonesia initiative has been developed with the support of data and information from various parties and developed with the principles of big data management which are fully supported by adequate spatial portal developer software from Esri. Particularly in Indonesia, there is not yet an adequate system to support spatial based decision making at the local level, therefore the development of a GIS dashboard to support provincial and district governments is highly recommended.

The consequences of Sickle Cell Disease (SCD), including ongoing hematopoietic stress and hemolysis, vascular damage and chronic therapies , such as blood transfusions and Hydroxyurea on hematopoietic stem and progenitor cell (HSPC) have not been characterized. We have quantified the frequencies of nine HSPC populations by flow cytometry in the peripheral blood of pediatric and adult patients stratified by treatment and controls. We observed broad differences between SCD patients and healthy controls. SCD is associated with 10 to 20-fold increase in CD34dim cells, and two to five-fold more CD34bright cells, a depletion in Megakaryocyte-Erythroid Progenitors and an increase in hematopoietic stem cells, when compared to controls. SCD is also associated with abnormal expression of CD235a and by very high levels of expression of the CD49f antigen. These findings were present to varying degrees in all patients, whether or not they were naïve or on chronic therapy. HU treatment tended to normalizes many of these parameters. Chronic stress erythropoiesis, inflammation caused by SCD and hydroxyurea therapy have long been suspected of causing premature aging of the hematopoietic system, and potentially increasing the risk of hematological malignancies. An important finding of this study was that the observed concentration of CD34bright cells and of all the HSPCs decreased logarithmically with time of treatment with HU. This correlation was independent of age and specific to HU treatment. Although the number of circulating HSPCs is influenced by many parameters, our findings suggest that HU treatment may decrease premature aging and hematologic malignancy risk compared to the other therapeutic modalities in SCD.

The process model is very essential for the model based control design. The model of the process can be identified using system identification algorithm. The system identification is done through the open loop and closed loop approaches. In this work, the lab scale conical tank setup configured as a non square MIMO system. The conical tank system is identified through the both appraoches, the effectiveness and need of the both approaces are discussed. Based on the open loop identified model the controller designed and the controller implemented in the real time the to record the process data. From this data the closed loop identification are conducted uisng N4SID algorithm. The controller seetings are obtained using the smith predcitor based IMC based PI controller for the obtained model. The proposed identification algorithm and controller tuning show the better reults over the conventional method. Moreover, this method is applicable for all the non square MIMO system.

The aim of this study was to assess the effects of organic fertilisers (cow manure + dung water; cattle slurry) applied in different annual doses of nitrogen (54 kg ha-1; 84 kg ha-1; 120 kg ha-1) according to 3 different intensities of grassland utilisation (extensive – 2 cuts per year, medium intensive – 3 cuts per year, intensive – 4 cuts per year) on percentage of plant functional groups (grasses, legumes, forbs), dry matter yield, and forage quality. The study was performed as a small-plot trial over 7 years on moderately moist grassland in the Czech Republic. The proportion of legumes was significantly higher in the fertilisation treatments with cow manure + dung-water combined with medium intensive utilisation and intensive utilisation (10.2% and 10.3%, respectively). Fertilisation significantly increased dry matter yields by 51.9 % (cow manure + dung water) and 56% (cattle slurry) compared to unfertilised controls (4.81 t ha-1). Grasslands fertilised with cattle slurry showed significantly higher concentration of crude protein (142.9 g kg-1) than unfertilised (126.4 g kg-1). Extensive grassland utilisation significantly increased crude fibre concentration (up to 282.1 g kg-1), and decreased the energy value (up to 4.68 MJ kg-1 of NEL). Organic matter digestibility was negatively influenced by extensive grassland utilisation (61.0%, 65.42 % and 67.44% for the extensive, medium intensive and intensive utilisation, respectively). Our findings suggest that medium intensive and intensive grassland utilisation using organic fertilisation which correspond to annual doses of nitrogen of 84 kg ha-1 and 120 kg ha-1, are the most suitable for animal nutrition.

The European heatwave of 2018 led to record-breaking temperatures and extremely dry conditions in many parts of the continent resulting in widespread decrease in agricultural yield, early tree-leaf senescence, and increase in forest fires in Northern Europe. Our study aims to capture the impact of the 2018 European heatwave on terrestrial ecosystem through the lens of a high-resolution solar-induced fluorescence (SIF) data acquired from the Orbiting Carbon Observatory (OCO-2) satellite. SIF is proposed to be a direct proxy for gross primary productivity (GPP) and thus can be used to draw inferences about changes in photosynthetic activity in vegetation due to extreme events. We explore spatial and temporal SIF variation and anomaly during spring and summer months across different vegetation types (agriculture, broadleaved forest, coniferous forest, and mixed forest) during the European heatwave of 2018 and compare it to non-drought conditions (most of Southern Europe). About one-third of Europe’s land area experienced a consecutive spring and summer drought in 2018. Comparing 2018 to mean (2015-2017) conditions, we found a change in intra-spring season SIF dynamics for all vegetation types, with lower SIF during the start of spring followed by an increase in fluorescence from mid-April. Summer, however, showed a significant decrease in SIF. Our results show that particularly agricultural areas were severely affected by the hotter drought of 2018. Furthermore, the intense heat wave in Central Europe showed about 31% decrease in SIF values during July and August as compared to the mean over three previous years. Furthermore, our MODIS and OCO-2 comparative results indicate that especially for forests, OCO-2 SIF has a quicker response and possible higher sensitivity to drought in comparison to MODIS’s fPAR and NDVI when considering shorter reference periods, which highlights the added value of remotely sensed solar-induced fluorescence for studying the impact of drought on vegetation.

The changing dynamics in climate is the primary and important determinant of agriculture productivity. The effects of this changing climate on overall productivity in agriculture can be understood when we study the effects of individual components contributing to the changing climate on plants and crops. Elevated CO₂ (eCO₂) and drought due to high variability in rainfall is one of the important manifestations of the changing climate. There is a considerable amount of literature that addresses climate effects on plant systems from molecules to ecosystems. Of particular interest is the effect of increased CO₂ on plants in relation to drought and water stress. As it is known that one of the consistent effects of increased CO₂ in the atmosphere is increased photosynthesis, especially in C₃ plants, it will be interesting to know the effect of drought in relation to elevated CO₂. The potential of elevated CO₂ ameliorating the effects of water deficit stress is evident from literature suggesting that these two are agents are brothers in arms protecting the plant from stress rather than partnering in crime, specifically water deficit when in isolation. The possible mechanisms by which this occurs will be discussed in this minireview. Interpreting the effects of short-term and long-term exposure of plants to elevated CO₂ in the context of ameliorating the negative impacts of drought will show us the possible ways by which there can be effective adaption to crops in the changing climate scenario.

Imbalance of homeostasis between the microbial communities and the host system leads to dysbiosis in oral micro flora. DMTU (1,3-di-m-tolyl-urea), is a biocompatible compound that was shown to inhibit Streptococcus mutansbiofilms by inhibiting its communication system (quorum sensing). Here, we hypothesized that DMTU is able to inhibit multispecies biofilms. We developed a multispecies oral biofilm model comprising an early colonizer Streptococcus gordonii, a bridge colonizer Fusobacterium nucleatum, and late colonizers Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans. We performed comprehensive investigations to demonstrate the effect of DMTU on planktonic cells and biofilms. Our findings showed that DMTU inhibits and disrupts multispecies biofilms without bactericidal effects. Mechanistic studies revealed significant down regulation of biofilm and virulence related genes in P. gingivalis. Taken together, our study highlights the potential of DMTU to inhibit polymicrobial biofilm communities and their virulence.

The research is based on the inspection performed in June 2002 for carrying out a research program for the eradication of a termite infestation due a desertic species in the area of the Saint Catherine Holy Monastery at Mount Sinai - Egypt. The paper describes the application of the registered European bait system SentritechTM and the trend of eradication during the first year. The application of bait system blocked the termite infestation inside the Katholikon (Main church) and in the surrounding after 6 months. Nevertheless, the infestation restarted and even increased again in the surrounding of the main church. An explanation of this surprising event is attempted in this paper.

The fundamental mechanism underlying negative-ion catalysis involves bond-strength breaking in the transition state (TS). Doubly-charged atomic/molecular anions are proposed as novel dynamic tunable catalysts and demonstrated in water oxidation to peroxide. Density Functional Theory TS calculations have found tunable energy activation barrier reduction ranging from 0.030 eV to 2.070eV, with Si²ˉ, Pu²ˉ, Pa²ˉ and Sn²ˉ the best catalysts; the radioactive elements usher in new application opportunities. C₆₀²ˉ reduces significantly the standard C₆₀ˉ TS energy barrier while graphene increases it, behaving like cationic systems. Rank-ordered catalysts according to their reaction barrier reduction efficiency, variation across charge states and systems reveal their tunable and wide applications, ranging from water purification to biocompatible anti-viral and anti-bacterial sanitation systems.

Standard evolutionary theory, supported by mathematical modelling of outbred, dispersed populations predicts that ageing is not an adaptation. We recently argued that in clonal, viscous populations, programmed organismal death could promote fitness through social benefits and has, in some organisms (e.g. Caenorhabditis elegans), evolved to shorten lifespan. Here we review previous adaptive death theory, including consumer sacrifice, biomass sacrifice, and defensive sacrifice types of altruistic adaptive death. In addition we discuss possible adaptive death in semelparous fish, coevolution of reproductive and adaptive death, and adaptive reproductive senescence in C. elegans. We also describe findings from recent tests for the existence of adaptive death in C. elegans using computer modelling. Such models have provided new insights into how trade-offs between fitness at the individual and colony levels mean that senescent changes can be selected traits. Exploring further the relationship between adaptive death and social interactions, we consider examples where adaptive death results more from action of kin than from self-destructive mechanisms and, to describe this, introduce the term adaptive killing of kin.

Accurate and timely testing has become an essential measure in combatting the COVID-19 global pandemic. Currently, polymerase chain reaction (PCR) based assays are the most relied on methods for SARS-CoV-2 detection. This traditional workflow involves a viral RNA extraction from the viral transport media storing nasopharyngeal swabs collected from patients, followed by PCR based detection. While accurate, this methodology is time consuming and resource heavy, causing for delays in receiving results or limited access to testing. Herein, we demonstrate a validated method for SARS-CoV-2 detection from viral transport media using a two-step, direct-to-PCR workflow revolving around shaker-mill homogenization. This method completely bypasses the extraction steps of the traditional workflow, replacing it with 30 seconds of mechanical disruption sufficient to allow for COVID-19 detection with a 96.43% sensitivity and 100% specificity when compared to traditional extraction to PCR based methods.

EGFR mutations are heterogenous but all carry the same weighting in the Lung-molGPA. The aim of this study was to elucidate the different prognostic implications of molecular subtypes and frontline TKIs in EGFR-mutated lung adenocarcinoma with synchronous brain metastases (BM) using the Lung-molGPA. Medical records were searched in hospital databases from 2011 to 2015. Patients with EGFR-mutated adenocarcinoma and brain metastases who received TKIs were included. The Kaplan-Meier method was used to estimate survival, and multivariate Cox proportional hazard models were used to estimate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). A total of 256 patients were included with a median overall survival (OS) of 17.2 months. In multivariate analysis of OS, only age (70 versus &lt;70 years, HR:1.71, 95% CI:1.25-2.35, p&lt;0.001), KPS (&lt;70 versus 70, HR:1.71, 95% CI:1.26-2.31, p&lt;0.001), and rare mutations (other versus exon 19 deletions, HR:1.78, 95% CI:1.04-3.05, p=0.037) remained statistically significant. In patients with a Lung-molGPA score 2.5, EGFR molecular subtypes had different median OS (exon 19 deletions versus Leu858Arg versus other, 18.8 vs 12.4 vs 12.1 months, p=0.021). In conclusion, different molecular subtypes treated with frontline TKIs have different prognostic implications in the Lung-molGPA. Further prospective studies are warranted to validate these findings.

In this paper, a metal cutting machine position control have been designed and simulated using Matlab/Simulink Toolbox successfully. The open loop response of the system analysis shows that the system needs performance improvement. Static output feedback and full state feedback H₂ controllers have been used to increase the performance of the system. Comparison of the metal cutting machine position using static output feedback and full state feedback H₂ controllers have been done to track a set point position using step and sine wave input signals and a promising results have been analyzed.

Room-temperature phosphorescent (RTP) materials have been attracted tremendous interest owing to their unique material characteristics and potential applications for state-of-the-art optoelectronic devices. Recently, we have reported a synthesis and fundamental photophysical properties of new RTP materials based on benzil, i.e., fluorinated monobenzil derivative and fluorinated and non-fluorinated bisbenzil derivative analogues [Yamada, S. et al, Beilstein J. Org. Chem. 2020, 16, 1154–1162.]. To further understand their RTP properties, here we investigated the excited-state dynamics and photostability of the derivatives by means of time-resolved and steady-state photoluminescence spectroscopies. For these derivatives, clear RTP emissions with lifetimes on the microsecond timescale were identified. Among them, the monobenzil derivative was found to be the most efficient RTP material, showing both the longest lifetime and highest amplitude RTP emission. Time-resolved photoluminescence spectra measured at 77 K and density functional theory calculations revealed the existence of a second excited triplet state in the vicinity of the first excited singlet state for the monobenzil derivative, indicative of the presence of a fast intersystem crossing pathway. A discussion of the correlation between the excited state dynamics, emission properties, and conformational flexibility of the three derivatives is presented.

This article shows the numerical results and the analysis of households' degree of knowledge in an intermediary city such as Huelva (Andalusia, Spain) about the sustainable use of urban water. It analyzes the needs and values regarding water and the attitudes that households maintain regarding the acceptance of reclaimed water and the use of new technologies to achieve more efficient and sustainable consumption. These results are part of the stages of needfinding and synthesis of Design Thinking methodology, adopted as a framework to improve the efficiency and sustainability of urban water among households in this city. Different statistical analysis techniques of surveys sent to households and the use of clustering are the mathematical tools used to draw conclusions and recommendations that allow the design of a web-based prototype grounded on Product Service Systems methodology, as a tool to improve the engagement of households concerning water and align citizens with the sustainability of their city. Strategies of customization and technological facilitators will be the means to improve the hydrosocial contract among households in Huelva in future later stages of the project.

Workloads may be classified as either internal or external. Internal workloads (heart rate, blood lactate, session rate of perceived exertion (sRPE) are categorised as the individual’s response to an external workload (volume, intensity). sRPE is an easily monitored variable which has been shown to have possible associations with other internal (1) and injury rates (2, 3) in contact sports. This case study describes the internal workload monitoring of a schoolboy rugby player during the entirety of his season (September to March) with the subsequent relationships between workload and time loss injuries being explored. Time loss injuries are defined as injuries which caused the individual to miss training or match play time (4). Acute to chronic workload ratio (ACWR) and exponentially weighted moving average (EWMA) were monitored, a novel ACWR:EWMA ratio was also calculated. High ACWR and low EWMA values were associated with injury occurrence, the ACWR:EWMA ratio may account for this. EWMA may be a better predictor of “time loss” injuries than ACWR. The ACWR:EWMA ratio may merit further scientific exploration in the future.

The most extensive urban growths in the next 30 years are expected to occur in developing countries. Lagos, Nigeria - Africa’s second most populous megacity- is a prime example. To achieve more sustainable and resilient cities, there is a need for modeling the urban growth patterns of major cities and analyzing their implications. In this study, the urban growth of Lagos state was modeled using the Multi-Layer Perceptron (MLP) neural network for the transition modeling and the Markov Chain analysis for the change prediction, achieving a model accuracy of 81.8%. An innovative visual validation of the model results using the ArcGIS was combined with kappa correlation statistics. The results show that by 2031, built-up areas will be the most spatially extensive LULC class in the study area with percentage coverage of 34.1% as opposed to 9% in 1986. The coverage of bare areas is also expected to increase by 53% between 2016 and 2031. Conversely, 24.9% and 68.3% loss of forestlands and wetlands respectively, are expected between 2016 and 2031. In view of the 11^th goal of SDGs which focuses on achieving sustainable cities and communities, the objectives of African Union’s Agenda 2063, and based on the urban growth trends observed, the study recommends a prioritization of vertical expansion as opposed to the current horizontal urban growth trends in the study area.

Multicompartment compliance aids (MCAs) are devices with each discrete section denoting a single dosing occasion. The purpose of an MCA is to maximize patient adherence and thereby optimize the treatment benefits. These devices are widely employed throughout western Europe and UK and use appears to be rapidly increasing (2) although the RPS as moved away from these devices as a means to improve adherence. We analysed MCAs from various pharmacies over a wide geographic area in England and North Wales. We concluded that most MCA users are elderly patients. Also, most of the patients suffer of combined cardiovascular disease. However, a significant proportion of patients falls in the mental/ neurological disease category. Additionally, most of the externals added to MCAs are inhalers and painkillers. Moreover, SDIs are more frequent in female patients and these SDI are mainly related with mental health medication, cardiovascular disease medication and neurological medication. In conclusion, a directive for dispensing of MCAs in pharmacies by pharmacists through an enhanced service should be elaborated having in consideration PIMs, SDIs, drug stability and use of externals and MCA design and brand.

Infants’ avoidance of drop-offs has been described as an affordance learning that is not transferable between different locomotor postures. In addition, there is evidence that infants perceive and act similarly around real and water cliffs. This cross-sectional study investigated the effects of specific locomotor experiences on infants’ avoidance behaviour using the Real Cliff / Water Cliff paradigm. The experiments included 102 infants, 58 crawling, but pre-walking, infants (M_age= 11.57 months, SD = 1.65) with crawling experience ranging between 0.03 and 7.4 months (M = 2.16, SD = 1.71) and 44 walking infants (M_age = 14.82 months, SD = 1.99), with walking experience ranging between 0.13 and 5.2 months (M = 1.86, SD = 1.28). The association between crawling experience and crawlers’ avoidance of the real and water cliffs was confirmed. Importantly, crawling and total self-produced locomotor experience, and not walking experience, were associated with walkers’ avoidance behaviour on both cliffs. These results suggest that some degree of perceptual learning acquired through crawling experience was developmentally transferred to the walking posture. A longer duration of crawling experience facilitates a more rapid recalibration to the new walking capability. In addition, there was no difference in infants’ avoidance of falling on the real and the water cliff. However, infants explored the water cliff more than the real cliff, revealing more enticement to examine bodies of water than for drop-offs.

The effects of build orientation and heat treatment on the crack growth behavior of 316L stainless steel (SS) fabricated via a selective laser melting (SLM) additive manufacturing process were investigated. Significant growth of available research results of additively manufactured metallic parts still needs to be improved. The most important issue connected with properties after additive manufacturing is properties high anisotropy, especially from the fatigue point of view. The research included crack growth behavior of additively manufactured 316L in comparison to conventionally made reference material. Both groups of samples were obtained using precipitation heat treatment. Different build orientation in additively manufactured samples and rolling direction in reference samples were taken into account as well. Precipitation heat treatment of additively manufactured parts allowed to reach similar microstructure and tensile properties to elements conventionally made. The heat treatment positively affected fatigue properties. Additionally, precipitation heat treatment of additively manufactured elements significantly affected the reduction of fatigue cracking velocity and changed the fatigue cracking mechanism.

Hydrothermal /super critical processes are important process to synthesize materials which are otherwise difficult to form under normal conditions. A mathematical model is developed using standard transport equations to calculate the time for heating of hydrothermal reactor and computer simulation of the model was carried out in SOLIDWORKS® to validate it. The materials used to form reactor vessel were stainless steel (outer body) and TEFLON (PFA) (inner vessel). It was shown that composite wall, its geometry, construction & properties greatly affect the time and pattern of heat transfer. The time calculated and pattern generated were found to be in good agreement with experimental values.

Neuromuscular disorders cause progressive muscular weakness, which limits upper extremity mobility and performance during activities of daily life. A dynamic arm support can improve mobility and quality of life. However, their use is often discontinued over time for unclear reasons. This study aimed to evaluate whether users of dynamic arm supports demonstrate and perceive quantifiable mobility benefits over a period of two months. Nine users of dynamic arm supports were included in this observational study. They had different neuromuscular disorders and collectively used four different arm supports. They were observed for three consecutive weeks during which they were equipped with a multi-sensor network of accelerometers to assess the actual use of the arm support and they were asked to provide self-reports on the perceived benefits of the devices. Benefits were experienced mainly during anti-gravity activities and the measured use did not change over time. The self-reports provided contextual information in domains such as participation to social life, in addition to the sensor system. However self-reports overestimated the actual use by up to three-fold compared to the accelerometer measures. A combination of objective and subjective methods is recommended for meaningful and quantifiable mobility benefits during activities of daily life.

In this study, Mg-Al and Mg-Al-Ni - layered double hydroxides (LDHs) were successfully synthesized for efficient removal of Mn²⁺ from synthetically wastewater. LDH adsorbents (Mg-Al and Mg-Ni-Al) were prepared by co-precipitation method. The formation of the layered double hydroxide, the adsorption of manganese on both LDH (Mg-Al and Mg-Ni-Al) were observed by XRD, SEM and EDX analysis. The various parameters such as the effect of shaking time, initial Mn²⁺ concentration, temperature were controlled and optimized to removal of Mn²⁺ from synthetic wastewater. The kinetics and adsorption isotherms for Mn²⁺ removal from wastewater were studied in batch mode. At temperatures of 10 °C and 20 °C the adsorption equilibrium was reached after 24 h. Adsorption isotherms of Mn²⁺ are well fitted by Langmuir and Freundlich isotherm equation. The adsorption capacity of Mn²⁺ from synthetic wastewater of 80.607 mg/kg was obtained for (Mg-Al-Ni)-LDH. It is found that the adsorption kinetics is best described by the pseudo-second order model. These results prove that LDHs can be considered as a potential material for adsorption of Mn²⁺ from wastewater.

The cutting-edge photovoltaic cells are an indispensable part of the ongoing progress of earth-friendly plans for daily life energy consumption. However, the continuous electrical demand that extends to the night time requires a prior deployment of efficient real-time storage systems. In this regard, metal-air batteries have presented themselves as the most suitable candidates for solar energy storage, combining extra lightweight with higher power outputs and promises of longer life cycles. Scientific research over non-precious functional catalysts has always been the milestone and still contributing significantly to exploring new advanced materials and moderating the cost of both complementary technologies. Metal-organic frameworks (MOFs) derived functional materials have found their way to the application as storage and conversion materials, owing to their structural variety, porous advantages, as well as the tunability and high reactivity. In this review, we provide a detailed overview of the latest progress of MOF-based materials operating in metal-air batteries and photovoltaic cells.

This paper reviews the current knowledge of pepper anthracnose in the Philippines. We present research outputs on pepper anthracnose from the last three years. Then, we present evidence of the widespread occurrence of C. acutatum sensu lato in the Philippines. Finally, we highlight some research prospects that would contribute towards developing an integrated anthracnose management program.

The integration of 3D city models with Building Information Models (BIM), abbreviated as GeoBIM, facilitates improved data support to several applications, e.g. 3D map updates, building permits issuing, detailed city analysis, infrastructure design, context-based building design, to name a few. To solve the integration, several issues need to be tackled and solved, i.e. harmonization of features, interoperability, format conversions, integration of procedures. The GeoBIM benchmark 2019, funded by ISPRS and EuroSDR, evaluated the state of implementation of tools addressing some of those issues. In particular, in the part of the benchmark described in this paper, the application of georeferencing to Industry Foundation Classes (IFC) models and making consistent conversions between 3D city models and BIM are investigated, considering the OGC CityGML and buildingSMART IFC as reference standards. In the benchmark, sample datasets in the two reference standards were provided. External volunteers were asked to describe and test georeferencing procedures for IFC models and conversion tools between CityGML and IFC. From the analysis of the delivered answers and processed datasets, it was possible to notice that while there are tools and procedures available to support georeferencing and data conversion, comprehensive definition of the requirements, clear rules to perform such two tasks, as well as solid technological solutions implementing them, are still lacking in functionalities. Those specific issues can be a sensible starting point for planning the next GeoBIM integration agendas.

SARS-CoV-2 is a newly emerging, highly transmissible, and pathogenic coronavirus in humans, which has caused global public health emergency and economic crisis. To date, millions of infections and thousands of deaths have been reported worldwide, and the numbers continue to rise. Currently, there is no specific drug or vaccine against this deadly virus; therefore, there is a pressing need to understand the mechanism through which this virus enters the host cell. Viral entry into the host cell is a multistep process in which SARS-CoV-2 utilizes the receptor binding domain of the spike glycoprotein (S) to recognize ACE2 receptors on the human cells; this initiates host cell entry by promoting viral-host cell membrane fusion through large scale conformational changes in the S protein. Receptor recognition and fusion are critical and essential steps of viral infections and are key determinants of the viral host range and cross-species transmission. In this review, we summarize the current knowledge on the origin and evolution of SARS-CoV-2 and the roles of key viral factors. We discuss the RNA dependent RNA polymerase structure of SARS-CoV-2, its significance in drug discovery, and explain the receptor recognition mechanisms of coronaviruses. We provide a comparative analysis of the SARS-CoV and SARS-CoV-2 S proteins, receptor-binding specificity, and discuss the differences in their antigenicity based on biophysical and structural characteristics.

Motivation: UCSC Xena platform provides huge amounts of processed cancer omics data from big public projects like TCGA or individual reserach groups for enabling unprecedented research opportunities. In 2019, we developed UCSCXenaTools, an R package for retrieval of UCSC Xena data. However, an easier dataset exploration and analysis tool is still lack, especially for researchers without programming experience. Results: We develop UCSCXenaShiny, an R Shiny package to quickly explore, download all datasets from UCSC Xena data hubs. In addiction, a module based analysis framework is constructed to analyze and visualize data. Availability: https://github.com/openbiox/UCSCXenaShiny or https://cran.r-project.org/package=UCSCXenaShiny.

In-cloud ice mass accretion on wind turbines is a common challenge faced by energy companies operating in cold climates. On-shore wind farms in Scandinavia are often located in regions near patches of forest, the heterogeneity length scales of which are often less than the resolution of many numerical weather prediction (NWP) models. The representation of these forests--including the cloud water response to surface roughness and albedo effects related to them--must therefore be parameterized in NWP models used as meteorological input in ice prediction systems, resulting in an uncertainty that is poorly understood and to present date not quantified. The sensitivity of ice accretion forecasts to the subgrid representation of forests is examined in this study. A single column version of the HARMONIE-AROME 3D NWP model is used to determine the sensitivity of the forecast of ice accretion on wind turbines to the subgrid forest fraction. Single column simulations of a variety of icing cases at a location in northern Sweden were examined in order to investigate the impact of vegetation cover on ice accretion in varying levels of solar insulation and wind magnitudes. In mid-winter cases, the wind speed response to surface roughness was the primary driver of the vegetation effect on ice accretion. In early season cases, the cloud water response to surface albedo effects plays a secondary role in the impact of in-cloud ice accretion, with the wind response to surface roughness remaining the primary driver for the surface vegetation impact on icing. Two different surface boundary layer (SBL) forest canopy subgrid parameterizations were tested in this study that feature different methods for calculating near-surface profiles of wind, temperature, and moisture, with the ice mass accretion again following the wind response to surface vegetation between both of these schemes.

Kim-Kim [19] studied the type 2 degenerate poly-Bernoulli numbers and polynomials by using modified degenerate polylogarithm function. In this paper, we construct the type 2 degenerate poly-Cauchy polynomials and numbers of the second kind, called degenerate poly-Cauchy polynomials and numbers of the second kind by using degenerate polylogarithm function and derive several properties on the degenerate poly-Cauchy polynomials and numbers of the second kind. Furthermore, we consider the degenerate unipoly-Cauchy polynomials of the second kind and discuss some properties of them.

The literature, aimed at understanding the income-price elasticity of air passenger demand, bases its analysis on airport movement. The diversity of studies regarding the casualty between air transportation and economic growth are examples. Some studies covering this link, estimate the income-price relationship with the demand considering international traffic. Considering a domestic setting, where this traffic is significant in Brazil, studies related to remote regions are scarce, and the existing ones focus on governmental policies and subsidies. In addition, empirical studies on the theme consenter themselves in developed regions, such as Europe, North America, and Australia. For Brazil, where we find the Amazon region, there are no empirical researches. This paper analyses the price-income elasticity of the demand regarding domestic passengers in air links from remote cities of the Brazilian Amazon. This study uses panel data regression analysis method on a database of domestic scheduled flights of Brazil´s National Civil Aviation Agency. The results show that air passengers involving remote region flights present a lower sensitiveness regarding local income and airline´s price variations than those in flights among capitals. The higher difference is in income-elasticity of the remote city of origin, which is lower than that of the air traffic among capitals.

As the world endures the coronavirus disease 2019 (COVID-19) pandemic, conditions of 35 million vulnerable individuals struggling with substance use disorders (SUDs) worldwide have not received sufficient attention for their special health and medical needs. Many of these individuals are complicated by underlying health conditions, such as cardiovascular and lung diseases and undermined immune systems. During the pandemic, access to the healthcare systems and support groups is greatly diminished. Current research on COVID-19 has not addressed the unique challenges facing individuals with SUDs, including the heightened vulnerability and susceptibility to the disease. In this systematic review, we will discuss the pathogenesis and pathology of COVID-19, and highlight potential risk factors and complications to these individuals. We will also provide insights and considerations for COVID-19 treatment and prevention in patients with SUDs.

Investigating and classifying sentiments of social media users (e.g., positive, negative) towards an item, situation, and system are very popular among the researchers. However, they rarely discuss the underlying socioeconomic factor associations for such sentiments. This study attempts to explore the factors associated with positive and negative sentiments of the people about reopening the economy, in the United States (US) amidst the COVID-19 global crisis. It takes into consideration the situational uncertainties (i.e., changes in work and travel pattern due to lockdown policies), economic downturn and associated trauma, and emotional factors such as depression. To understand the sentiment of the people about the reopening economy, Twitter data was collected, representing the 51 states including Washington DC of the US. State-wide socioeconomic characteristics of the people (e.g., education, income, family size, and employment status), built environment data (e.g., population density), and the number of COVID-19 related cases were collected and integrated with Twitter data to perform the analysis. A binary logit model was used to identify the factors that influence people toward a positive or negative sentiment. The results from the logit model demonstrate that family households, people with low education levels, people in the labor force, low-income people, and people with higher house rent are more interested in reopening the economy. In contrast, households with a high number of members and high income are less interested to reopen the economy. The accuracy of the model is good (i.e., the model can correctly classify 56.18\% of the sentiments). The Pearson chi2 test indicates that overall this model has high goodness-of-fit. This study provides a clear indication to the policymakers where to allocate resources and what policy options they can undertake to improve the socioeconomic situations of the people and mitigate the impacts of pandemics in the current situation and as well as in the future.

The COVID-19 outbreak has severely affected the social and economic conditions across this globe. Little is known about the relationship of COVID-19 with countries’ economic and socio-demographic status. Publicly available data on COVID-19 test rate, attack rate, case fatality rate, and recovery rate were analyzed in relation to country’s economic status, population density, median age, and urban population ratio. We also conducted multinomial logistic regression analysis to predict the influence of countries’ social and economic factors on COVID-19. The results revealed that the median age had significant positive correlation with attack rate (r=0.2389, p=0.003), case fatality rate (r=0.3207, p=0.000) and recovery rate (r=0.4847, p=0.000). The urbanization has positive significant correlation with recovery rate (r=0.1957, p= 0.016). The multinomial logistic regression analysis revealed low-income countries are less likely to have an increased recovery rate (p=0.000) and attack rate (p=0.016) compare to high-income countries. The lower-middle-income and upper-middle-income countries are less likely to have an increased recovery rate (p=0.000 and p=0.001, respectively) compared to high-income countries. Based on the result of this study, these economic and socio-demographic factors should consider in designing appropriate preventive measures as a next step. The low and lower-middle-income countries should invest more in health care services to lower the case fatality rate and increase test and recovery rates as part of pandemic preparation like COVID-19. As the number of COVID-19 attacks, death and recovery rates are constantly changing; however, the intensive study is required to obtain a clear picture.

This short note proposes a national Geographic Information System (GIS) - based health infrastructure to deal with epidemics and pandemics. Currently, there is no pan-India health infrastructure available that can compile, update, and report the spread of epidemic diseases. It not only curtails the opportunity of finding the real-time data on the spatial distribution of a disease but prevents one to inquire into the causes of the disease through epidemiological analysis. The proposed infrastructure in this study is a pan-India one and can broadly be divided into two parts, hotspot mapping and accessibility to services. In the first part, hospitals are proposed to act as nodes of data collection, sending data to a national GIS portal. This portal shall have the capabilities of plotting the data using map rendering services such as Google and Bing Maps. This way, hotspots can be visualized in no time, benefitting the government and common citizenry alike. The second part deals with the accessibility of citizenry to a wide range of services, i.e., healthcare services, grocery outlets, emergency services, baby food, and many other essential services of the day to day life. In order to implement this, we propose that the government need to enforce a mandatory submission of locational coordinates of all Goods and Services Tax (GST) enrolled service providers. Once the coordinates are submitted, the government can effectively control the opening and closing of services and inform the citizenry at the same time. The proposed infrastructure is going to help deal with the extraordinary situations during epidemic and pandemics similar to what the world is currently facing in the form of Corona Virus Disease 2019 (COVID-19). Furthermore, the infrastructure can be scaled up or down as per the spread of a disease. The health-GIS platform proposed in this concept paper, shall help India in controlling and managing the epidemic more efficiently.

Identifying the determinants of human behavior is useful to adjust interventions and lead the civil society towards a stronger commitment with climate change mitigation and adaptation objectives, achieving greater support for successfully implementing environmental policies. Existing research has largely focused on case studies of pro-environmental behaviors (PEBs) in developed economies but there is yet very little evidence for developing countries. This study provides estimations of the effect of internal factors, such as sociodemographic variables, and four psychological dimensions (climate change knowledge, environmental attitudes, self-efficacy, trust in sources of environmental information) on PEBs. Data was obtained through a survey applied with future decision makers - university students - from Colombia (n = 4769) and Nicaragua (n = 2354). Indices were generated for PEBs and the psychological dimensions using z-scores and Principal Component Analysis. Partial correlations were evaluated through the Ordinary Least Squares method. Our results suggest that, in order to reach the planned emission reduction targets, policy approaches should more strongly focus on educating and motivating citizens and prepare them for contributing to the environmental cause, as well as provide individual solutions to combat climate change, rather than providing only information on its causes and consequences.

Objective: SARS-Cov-2 infection or COVID-19 is a global pandemic. From the time of identification to till, multiple clinical symptoms and parameters have been identified by the researchers of various countries and regions regarding the diagnosis and presentations of COVID-19 disease. In this manuscript, we investigated the primary symptoms and basic hematological presentations of SARS-CoV-2 infection among the Bangladeshi patients. Methodology: We have collected the disease history of mild to moderate degree of COVID-19 patients; hematological and biochemical on admission reports of moderate degree COVID-19 patients. All of them were tested positive for SARS-CoV-2 by RT-PCR in different institutes in Bangladesh. Results: According to this study though COVID-19 patients in Bangladesh commonly presented with fever, cough, fatigue, shortness of breath, and sore throat, but symptoms like myalgia, diarrhea, skin rash, headache, Abdominal pain/cramp, nausea, vomiting, restlessness, and a higher temperature of >100⁰F have a greater presentation rate and more frequent than other published studies. CRP and Prothrombin time was found to increase in all the patients. Serum ferritin, ESR, SGPT, and D-Dimer were found increased among 53.85%, 80.43, 44%, and 25% patients respectively. 17.39% of the patients had leukocytosis and neutrophilia. 28.26% of patients presented with lymphocytopenia. 62.52% of patients had mild erythrocytopenia. Conclusion: Despite some similarities, our study has evaluated a different expression in presenting symptoms in the case of COVID-19 patients in Bangladesh. CRP, Prothrombin time, serum ferritin, ESR, SGPT, D-Dimer, erythrocytopenia, and lymphocytopenia can be initial diagnostic hematological findings and assessment for prognosis COVID-19 disease. Also, gender variations have a different scenario of clinical and laboratory appearance in this region.

In the present time, the biggest problem of the world is the outbreak of novel coronavirus. Novel coronavirus (COVID-19), this one name has become a part of our daily lives over the past few months. Beyond the boundaries of medical science, coronavirus is now the main subject of research in all fields like Applied Mathematics, Economy, Philosophy, Sociology, Politics upto living room. The epidemic has brought unimaginable changes in our traditional habits and daily routines. Thousands of people in our country are fighting with the rest of the world to survive in various new situations. There are different kinds of coronavirus appeared in different times. In this time, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is responsible for the coronavirus disease of 2019 (COVID-19). This virus was first identified towards the end of 2019 in the city of Wuhan in the province of Hubei in China. Within very short duration of time and very fast, it has spread throughout a large part of the world. In this study, the main aim is to investigate the spreading rate, death rate, recovery rate due to corona virus infection and to study the future of the coronavirus in India by using mathematical modeling based on the previous data. Mathematical models, in this situation, are the important tools in recruiting effective strategies to fight this epidemic. India is at high risk of spreading the disease and is facing many losses in socio-economic aspects. With current infection rates and existing levels of personal alertness, the number of infected people in India will increase at least in the next three months. Proper social awareness, maintain of social distance, large rate of testing and separation may break the chain of the Coronavirus-2.

Potato is among one of the most important food crops, yet maintaining plant productivity in this drought-sensitive crop has become a challenge. Competition for scarce water resources and the continued effects of global warming exacerbate current constraints on crop production. While plants’ response to drought in above-ground tissues has been well documented, the regulatory cascades in developing tubers have been largely unexplored. Using the commercial Canadian cultivar ‘Vigor’, plants were subjected to a drought treatment under high-tunnels causing a 4 ℃ increase in canopy temperature when compared to the well-watered control. Tubers were sampled for RNAseq and metabolite analysis. Approximately 2600 genes and 3898 transcripts were differentially expressed by at least four-fold in drought-stressed potato tubers, with 75 % and 69 % being down-regulated respectively. A further 229 small RNAs were implicated in gene regulation during drought. The comparison of protein homologues between Solanum tuberosum L. and Arabidopsis thaliana L. indicates that downregulated genes are associated with phenylpropanoid, carotenoid, and patatin biosynthesis. This suggests that there may be nutritive implications to drought stress occurring during the potato tuber bulking phase in sensitive cultivars.

More than 150 years ago, in 1866, Ernst Haeckel published a book in two volumes called "Generelle Morphologie der Organismen" (General Morphology of Organisms) in the first volume of which he formulated his Biogenetic law, famously stating that ontogeny recapitulates phylogeny (Rieppel 2019). Here we describe Haeckel´s original idea as first formulated in the “Generelle Morphologie der Organismen” and later further developed in other publications until the present situation in which molecular data are used to test the "hour-glass model", which can be seen as a modern version of the biogenetic law. We also tell the story about his discovery, while travelling in Norway, of an unknown organism, Magosphaera planula, that was important in that it helped to precipitate his ideas into what was to become the Gastraea theory. We also follow the further development and reformulations of the Gastraea theory by other scientists, notably the Russian school (Levit, 2007). Ilya Metchnikov developed the Phagocytella hypothesis for the origin of metazoans based on studies of a colonial flagellate. Alexey Zakhvatin focused on deducing the ancestral life cycle and the cell types of the last common ancestor of all metazoans, and Mikhailov recently pursued this line of research further.

COVID-19 is now a major global health crisis, can lead to severe food crisis unless proper measures are not taken. Though a number of scientific studies have addressed the possible impacts of COVID-19 in Bangladesh on variety of issues, problems and food crises associated with aquatic resources and communities are missing. Therefore, this study aimed at bridging the gap in the existing situation and challenges of COVID-19 by linking its impact on aquatic food sector and small-scale fisheries with dependent population. The study was conducted based on secondary data analysis and primary fieldwork. Secondary data focused on COVID-19 overview and number of confirmed, recovered and death cases in Bangladesh; at the same time its connection with small-scale fisheries, aquatic food production, demand and supply was analyzed. Community perceptions were elicited to present how the changes felt and how they affected aquatic food system and small-scale fisheries and found devastating impact. Sudden illness, reduced income, complication to start production and input collection, labor crisis, transportation abstraction, complexity in food supply, weak value chain, low consumer demand, rising commodity prices, creditor’s pressure were identified as the primary affecting drivers. Dependent people felt the measures taken by the Government should be based on protecting the health and food security, although it could be detrimental to economic growth in the short term. The study provides insight into policies adopted by the policy makers to mitigate the effects of the pandemic on aquatic food sector and small-scale fisheries.

It is highly likely that the wearing of face masks reduces the rate of respiratory infections (e.g. SARS-CoV-2), to protect both the user and those around them. This paper sets out to review the areas that effect the efficacy of masks, the materials, design, hygiene and fit testing, in order to make recommendations as to how to make mask from resources found in most homes for when commercial models are unavailable. This paper finds that a mask constructed with a filter made from high thread count cotton is likely to provide a reasonable level of protection (~70% filtration) and that if a layers of other materials such as chiffon or silk is added the filtration may be much higher (~90%). There is also some promise in less available materials such as vacuum cleaner bags and air conditioner filters. Examples of fabric and rigid designs are reviewed but most are limited by the fit to the users which is hard to determine in a home setting. It would be extremely helpful if a method was devised for people to test or be tested for the fit of home made masks. In the mean time careful thought should be given to whether the user judges a good fit. Users should also be careful to practice other means of hygiene and distancing.

The COVID-19 pandemic has disrupted the supply chain for personal protective equipment (PPE) for medical professionals, including N95-type respiratory protective masks. To address this shortage, many have looked to the agility and accessibility of additive manufacturing (AM) systems to provide a democratized, decentralized solution to producing respirators with equivalent protection for last-resort measures. However, there are concerns about the viability and safety in deploying this localized download, print, and wear strategy. Several polymer-based AM processes produce porous parts, and inherent process variation between printers and materials also threaten the integrity of tolerances and seals within the printed respirator assembly. The goal of this paper is to quantitatively measure particle transmission through printed respirators of different designs, materials, and AM processes, and assess the viability of printed respirators as N95 equivalents. Results from this study show that respirators printed using desktop/industrial-scale fused filament fabrication processes and industrial-scale powder bed fusion processes have insufficient filtration efficiency at the size of the SARS-CoV-2 virus, even while assuming a perfect seal between the respirator and the user’s face. Almost all printed respirators provided <60% filtration efficiency at the 100-300 nm particle range. Only one respirator, printed on an industrial-scale fused filament fabrication system provided >90% efficiency as-printed. Post-processing procedures including cleaning, sealing surfaces, and reinforcing the filter cap seal generally improved performance, but no respirator sustained the filtration efficiency of an N95 respirator, which filters 95% of SARS-CoV-2 virus particles. Instead, the printed respirators showed similar performance to various cloth masks. While continued optimization of printing process parameters and design tolerances could be implemented to directly print respirators that provide the requisite 95% filtration efficiency, AM processes are not sufficiently reliable for widespread distribution and local production of N95-type respiratory protection without commensurate quality assurance processes in place. Certain design/printer/material combinations may provide sufficient protection for specific users, but the respirators should not be trusted without quantitative filtration efficiency testing. It is currently not advised to expect printed respirators originating from distributed designs to replicate performance across different printers and materials.

The application of instrumented indentation to assess material properties like Young’s modulus and micro-hardness has become a standard method. In recent developments, indentation experiments and simulations have been combined to inverse methods, from which further material parameters as yield strength, work hardening rate, and tensile strength can be determined. In this work, an inverse method is introduced by which material parameters for cyclic plasticity, i.e. kinematic hardening parameters, can be determined. To accomplish this, cyclic Vickers indentation experiments are combined with finite element simulations of the indentation with unknown material properties, which are then determined by inverse analysis. To validate the proposed method, these parameters are subsequently applied to predict the uniaxial stress-strain response of a material with success. The method has been validated successfully for a quenched and tempered martensitic steel and for technically pure copper, where an excellent agreement between measured and predicted cyclic stress-strain-curves has been achieved. Hence, the proposed inverse method based on cyclic nanoindentation, as a quasi-non-destructive method, could complement or even substitute the resource-intensive conventional fatigue testing in the future for some applications.

There is a new public health crisis threatening the world with the emergence and spread of novel coronavirus (SARS-CoV-2). The outbreak of coronavirus disease 2019 (COVID-19), which originated in Wuhan, China, in December 2019, has been declared a public health emergency of international concern by WHO. Most patients infected with SARS-CoV-2 exhibited symptoms of fever, cough, myalgia, fatigue and shortness of breath. Many infected people may be asymptomatic. It is generally believed that airway exposure to respiratory droplets from an infected patient is the main transmission route of this disease. However, apart from respiratory source, other source specimens like faecal matter and urine could be possible for COVID-19 infectivity. The spreading other routes of the virus has been alarming sign, both for public and health care professionals. Understanding the spreading routes of SARS-CoV-2 is crucial for patient management and defining biosafety strategies for public and health care workers.

This paper deals with the service performance analysis and improvement using discrete event simulation has been used. The simulation of the heath care has been done by arena master development 14-version software. The performance measurement for this study are patients output, service rate, service efficiency and it is directly related to waiting time of patients in each service station, work in progress, resource utilization.Simulation model was building for Bahir Dar clinic and then, prepared the proposed model for the system. Based on the simulation model run result, the output of the existing healthcare service system is low due to presence of bottlenecks on the service system. Moreover, the station with the largest queue and high resource utilization are identified as a bottleneck. The bottlenecks, which have identified are reduced by using reassigning the existing resources and add new resources and merging the similar services, which has under low resource utilization (nurses). Finally, the researchers have proposed a developed model from different scenarios. Moreover, the best scenario is developed by combining scenario 2 and 3. And then, service efficiency of the healthcare has increased by 9.86 percent, the work in progress (WIP) are reduced by 3 patients from the system and the service capacity of the system is increased 34 to 40 patients per day due to the reduction of bottleneck stations.

Monitoring glycosylation changes within cells upon response to stimuli remains challenging because of the complexity of this large family of post-translational modifications (PTMs). We have developed an original tool enabling labeling and visualization of the cell cycle key-regulator b-catenin in its O-GlcNAcylated form based on intramolecular Förster resonance energy transfer (FRET) technology in cells. We opted for a bioorthogonal chemical reporter strategy based on the dual-labeling of b-catenin with a green fluorescent protein (GFP) for protein sequence combined with a chemically-clicked imaging probe for PTM resulting in a fast and easy to monitor qualitative FRET assay. We validated this technology by imaging the O-GlcNAcylation status of b-catenin in HeLa cells. Moreover, the changes in O-GlcNAcylation of b-catenin were varied by perturbing global cellular O-GlcNAc levels with inhibitors of O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA). Finally, we provided a flowchart demonstrating how this technology is transposable to any kind of glycosylation.

Thermal sterilization is generally avoided for 3-D printed components because of the relatively low deformation temperatures for common thermoplastics used for material extrusion-based additive manufacturing. 3-D printing materials required for high-temperature heat sterilizable components for COVID-19 and other applications demands 3-D printers with heated beds, hot ends that can reach higher temperatures than polytetrafluoroethylene (PTFE) hot ends and heated chambers to avoid part warping and delamination. There are several high temperature printers on the market, but their high costs make them inaccessible for full home-based distributed manufacturing required during pandemic lockdowns. To allow for all these requirements to be met for under $1,000, the Cerberus – an open source three-headed self-replicating rapid prototyper (RepRap) was designed and tested with the following capabilities: i) 200^oC-capable heated bed, ii) 500^oC-capabel hot end, iii) isolated heated chamber with 1kW space heater core and iv) mains voltage chamber and bed heating for rapid start. The Cereberus successfully prints polyetherketoneketone (PEKK) and polyetherimide (PEI, ULTEM) with tensile strengths of 77.5 and 80.5 MPa, respectively. As a case study, open source face masks were 3-D printed in PEKK and shown not to warp upon widely home-accessible oven-based sterilization.

With the widespread of embedded sensing capabilities of mobile devices, there has been unprecedented development of context-aware solutions. This allows the proliferation of various intelligent applications such as those for remote health and lifestyle monitoring, intelligent personalized services, etc. However, activity context recognition based on multivariate time series signals obtained from mobile devices in unconstrained conditions is naturally prone to imbalance class problems. This means that recognition models tend to predict classes with the majority number of samples whilst ignoring classes with the least number of samples, resulting in poor generalization. To address this problem, we propose to augment the time series signals from inertia sensors with signals from ambient sensing to train deep convolutional neural networks (DCNN) models. DCNN provides the characteristics that capture local dependency and scale invariance of these combined sensor signals. Consequently, we developed a DCNN model using only inertial sensor signals and then developed another model that combined signals from both inertia and ambient sensors aiming to investigate the class imbalance problem by improving the performance of the recognition model. Evaluation and analysis of the proposed system using data with imbalanced classes show that the system achieved better recognition accuracy when data from inertial sensors are combined with those from ambient sensors such as environment noise level and illumination, with an overall improvement of 5.3% accuracy.

Over the course of the pandemic due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), multiple new clinical manifestations, as the consequence of the tropism of the virus, have been recognized. That includes now the neurological manifestations and conditions, such as headache, encephalitis, as well as olfactory and taste disorders. We present a series of ten cases of RT-PCR confirmed SARS-CoV-2 infected patients diagnosed with viral-associated olfactory and taste loss from four different countries.

The evolution of metals micro/nano-structure upon severe plastic deformation (SPD) is still far to be theoretically explained, while experimental datasets are persistently growing for several decades. Major problem associated with understanding of SPD is related to a fact that the latter is a synergetic product of several competing physical effects which alter the material micro/nano-structure. In attempt to find deformational boundaries, where predominantly one mechanism determines the micro/nano-structure, in this paper we propose a continuous piecewise model for the analysis of experiments on material hardness vs strain of SPD processed materials. The novelty of this approach lies in its ability to find, as free-fitting parameters, the strain breakpoints which separate different micro/nano-structure modes generated upon SPD process. The model is applied to analyse experimental data for polycrystalline samples of pure iron and two distinctive strain breakpoints are revealed with good accuracies. This finding is in a good agreement with our earlier results on TEM microscopy studies on pure iron polycrystals after SPD treatment.

A growing number of studies suggest that SARS-CoV-2 could interfere with homeostatic mechanisms in the lung but the implications of this possible interference have not been fully explored in the literature. In this work, we examine the consequences that can be drawn from this hypothesis according to currently available knowledge. We suggest that one such consequence is the potential disruption of normal ventilation and perfusion of lung regions that may be distant from the infection sites. Loss of ventilation might result in local alveolar hypoxia and contribute to hypoxemia, which in turn could trigger homeostatic responses that enhance blood oxygenation by redistributing pulmonary blood circulation. Sudden changes in perfusion might then lead to the development of hydrostatic edema and eventually to vascular remodeling and inflammation. Therefore, the immune response might not be the only source of the substantial inflammation observed in lung tissues of patients with severe COVID-19, as is often assumed in the literature. The balance between the homeostatic and the immune reaction in each patient could account for the observed heterogeneity of the clinical manifestations of COVID-19.

The utility of ICTs for providing market information to rural smallholder farmers is growing rapidly, and access to reliable information and sources is considered crucial for beneficial market interaction. This study explored critical factors contributing to usage of electronic sources for market information search among rural smallholder livestock farmers. Using data collected from 129 respondents through a non-random sampling technique; descriptive and regression analysis was applied to identify key factors responsible for their awareness and use of ICT-based market information sources. Level of education was found to be a driver of awareness of ICT-based sources, and use of these sources was influenced by farmer-specific characteristics such as household size, education, income, membership of cooperatives and herd-size. The key ICT tools used was radio and mobile phones, widely available in the study area. Identified constraints to use of these ICTs include cost and patchy network signals in some areas. Policy interventions to reduce cost of mobile phone services and expansion of base stations; including practical recommendations for improved programming in radio and television offerings, are considered indispensable for greater uptake of e-information sources among smallholder livestock farmers.

Prior to lockdown the spread of COVID-19 in UK is found to be exponential, with an exponent α=0.207 In case of COVID-19 this spreading patterns is quantitatively better described with mobility-driven SIR-SEIR model [2] rather than the homogenous mixing models Lockdown has dramatically slowed down the spread of COVID-19 in UK, and even more significantly has changed the growth in the total number of infected from exponential to quadratic. This significant change is due a transition from a mobility-driven epidemic spreading to a spatial epidemic which is dominated by slow growth of spatially isolated clusters of infected population. Our results strongly indicated that, to avoid a return to exponential growth of COVID-19 (also known as “second wave”) mobility restrictions should not be prematurely lifted. Instead mobility should be kept restricted while new measures, such as wearing mask and contact tracing, get implemented in order to allow a safe exit from lockdown.

To address the expression pattern of the SARS-CoV-2 receptor ACE2 and the viral priming protease, TMPRSS2, in the respiratory tract, this study investigated RNA sequencing transcriptome profiling of samples of airway and oral mucosa. As shown, ACE2 has medium levels of expression in both small airway epithelium and masticatory mucosa, and high levels of expression in nasal epithelium. The expression of ACE2 is low in mucosal associated invariant T (MAIT) cells, and can’t be detected in alveolar macrophages. TMPRSS2 is highly expressed in small airway epithelium and nasal epithelium, and has lower expression in masticatory mucosa. Our results provide the molecular basis that the nasal mucosa is the most susceptible locus in the respiratory tract for SARS-CoV-2 infection and consequently for subsequent droplet transmission and should be the focus for protection against SARS-CoV-2 infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an etiologic agent of the respiratory disease in humans that is known as coronavirus disease 2019 (COVID19). The first outbreak of the disease was initially documented in Wuhan, Hubei Province, China in late December 2019 where people had experienced SARS pneumonia-like symptoms with unknown etiology. Since then it has been observed that COVID-19 positive patients have been showing mild to severe upper respiratory illness symptoms. The type of virus is known to make its transfer from animals to humans and for the concerned virus; researchers have claimed its origin from bat coronavirus at whole-genome level with a 96 % sequence identity. The COVID-19 virus is very contagious and communicable in nature and has been spread throughout the globe since its first outbreak in China. On March 9, 2020, WHO declared it as a Pandemic, and within a month it was already reported to have shown its presence in 213 countries and territories or areas. As of April 29, 2020, this novel virus infected 3,218,183 people and caused 228,029 mortalities worldwide with a variable mortality rate from 3-13 % across the planet and also varied by age and gender. Diagnosis of the disease is a key component in understanding and controlling the spread of the virus and several techniques have been devised including RT-PCR, ELISA, and sequencing-based approaches. To cure COVID-19 patients as of now we do not have proven to be a safe and effective treatment. Therapeutic options currently under investigation in various parts of the world. However, there are various effective therapeutic targets to repurpose the present antiviral therapy for developing potential interventions against SARS-CoV-2. Boosting the immune system can also help to prevent and spread of COVID-19 using various medication and exercises. In this review, our goal to summarize and discussed the present scientific advancements to fight against this novel pandemic.

BackgroundThe novel virus COVID-19, also known as SARS-CoV‑2, is currently rapidly spreading around the globe and pushing healthcare systems to the limits of their capacity. One of the functions of predictive models is to timely act for epidemic preparedness including hospital preparedness. In Egypt, like many other countries in the world, the epidemic situation and forecasting have not yet sufficiently studied. ObjectiveThe study was carried out to develop a short-term forecast scenario for the COVID-19 epidemic situation in Egypt and predict the hospital needs to accommodate the growing number of cases.MethodsSecondary data from the COVID-2019 daily reports and the report issued 8^th of April by the Egyptian Ministry of Health and Population were used. Due to the daily changing level of knowledge and data, the article reflects the status up to 18 April 2020. The prediction was based on the exponential growth rate model. For the depiction of the situation, the full length of the epidemic timeline was analyzed (from February 14^th till April 18^th). The growth rates and their rates of decline during the period from the 22^nd of March till the 18^th of April were calculated and extrapolated in the coming 7 weeks. The predicted hospital needs were assessed against the announced allocated resources.ResultsThe epidemic curve in Egypt is on the ascending arm as of April, 18. The active cases showed exponential growth from the start of the epidemic till April, 18. At the end of this period time, the recovery rate was 23.12% and the case fatality rate (CFR) was7.39. The case fatality rate median level during the last four weeks was 6.64. The active cases are expected to reach more than 20,000 by late May then starts to decline. The allocated regular hospital beds are predicted to show shortage by the time of the release of the paper. The intensive care units (ICU) beds and ventilators are predicted to show insufficiency on May 6.Conclusions: The COVID-19 epidemic in Egypt is expected to continue on the rise for the next few weeks and expected to start to decline late in May, 2020. Our estimates should be useful in preparedness planning. Serious actions should be taken to provide ICU beds and ventilators enough for the predicted number of cases that would need them, not later than the end of April. Mitigation actions have to continue for the coming 6 weeks or until the epidemic situation is more clearly seen.

The past years saw the rise of genomic biobanks and mega-scale meta-analysis of genomic data that promise to reveal the genetic underpinnings of health and disease. However, the over-representation of Europeans in genomic studies not only limit the global understanding of disease risk and intervention efficacy, but also inhibit viable research into the genomic differences between carriers and patients. Whilst the community has agreed that more diverse samples are required, it is not enough to blindly increase diversity; the diversity must be quantified, compared, and annotated to lead to insight. Genetic annotations from separate biobanks need to be comparable, computable, operate without access to raw data due to privacy concerns. But they must be comparable, both for regular research and to allow international comparison in response to pandemics. Here, we evaluate the appropriateness of commonly used genomic tools used to depict population structure in a standardized and comparable manner. The end goal is to reduce the effects of confounding and learn from genuine variation in genetic effects on phenotypes across populations, which will improve the value of biobanks, locally and internationally, increase the accuracy of association analyses, and inform developmental efforts.

Introduction. Strontium-82/Rubidium-82 (⁸²Sr/⁸²Rb) generators are used widely for positron emission tomography (PET) imaging of myocardial perfusion. In this study, the ⁸²Rb isotope yield and production efficiency of two FDA-approved ⁸²Sr/⁸²Rb generators were compared.Methods. N=515 sequential daily quality assurance (QA) reports from 9 CardioGen-82® and 9 RUBY-FILL® generators were reviewed over a period of 2 years. A series of test elutions was performed at different flow-rates on the RUBY-FILL® system to determine an empirical correction-factor used to convert CardioGen-82® daily QA values of ⁸²Rb activity (dose-calibrator ‘maximum’ of 50 mL elution at 50 mL/min) to RUBY-FILL® equivalent values (integrated ‘total’ of 35 mL elution at 20 mL/min). The generator yield (⁸²Rb) and production efficiency (⁸²Rb yield / ⁸²Sr parent activity) were measured and compared after this conversion to a common scale. Results. At the start of clinical use, the system reported ⁸²Rb activity from daily QA was lower for CardioGen-82® vs RUBY-FILL® (2.3 ± 0.2 vs 3.0 ± 0.2 GBq, p<0.001) despite having similar ⁸²Sr activity. Dose-calibrator ‘maximum’ (CardioGen-82®) values were found to under-estimate the integrated ‘total’ (RUBY-FILL®) activity by ~24% at 50 mL/min. When these data were used to convert the CardioGen-82 values to a common measurement scale (integrated total activity) the CardioGen-82® efficiency remained slightly lower than the RUBY-FILL® system on average (88 ± 4% vs 95 ± 4%, p<0.001). The efficiency of ⁸²Rb production improved for both systems over the respective periods of clinical use.Conclusions. ⁸²Rb generator yield was significantly under-estimated using the CardioGen-82® vs RUBY-FILL® daily QA procedure. When generator yield was expressed as the integrated total activity for both systems, the estimated ⁸²Rb production efficiency of the CardioGen-82® system was ~7% lower than RUBY-FILL® over the full period of clinical use.

The Gauss model for the time evolution of the first corona pandemic wave allows to draw conclusions on the dark number of infections, the amount of heard immunization, the used maximum capacity of breathing apparati and the effectiveness of various non-pharmaceutical interventions in different countries. In Germany, Switzerland and Sweden the dark numbers are 7.4 +/- 6.1, 11.1 +/- 8.5 and 25 +/- 25, respectively. Our method of estimating dark numbers from modeling both, infection and death rates simultaneously spares these countries the laborious, time-consuming and costly medical testing for antibodies of large portions of the population. In Germany the total number of infected persons, including the dark number of infections by the first wave is estimated to be 1.06 +/- 0.60 million, corresponding to 1.28 +/- 0.72 percent of the German population. We work out direct implications from these predictions for managing the 2nd and further corona waves.

Quinine and its less toxic derivatives have served humanity for decades as potent antimalarial drugs. Emergence of drug resistance has narrowed the usage of these drugs in malaria prevention and treatment. Fortunately, these drugs have roles in the treatment of other diseases as well including rheumatic disorders and viral infections. Quinine derivatives have proven antiviral effects, especially against human immunodeficiency virus (HIV), Zika virus (ZiKV), herpes simplex virus (HSV), Ebola virus and dengue virus (DENV). The prophylactic and therapeutic role of Chloroquine/hydroxychroquine has become a topic of interest after the recent outbreak of novel Corona virus-19 (nCoV-19). This virus is also named severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and WHO has officially named this disease as Corona virus disease 2019 (COVID-19). This lethal virus has affected almost 186 countries of the world till to date just in a period of four months of its outbreak. No approved antiviral drug is existed for the treatment of COVID-19. Therefore, this review is focused on potential prophylactic and therapeutic role of chloroquine/hydroxychlroquine for COVID-19.

A big race for the search for novel lead has begun due to the emergence of COVID-19 across the globe. More than 6,00,000 cases of afflicted patients worldwide has been reported till date with high mortality and morbidity. At present no approved drugs are known for COVID-19. Phylogenetic analysis present strong nucleotide sequence similarity of around 80% with SARS-CoV. Therefore, the drugs used for treating SARS-CoV and MERS are being used for SARS-CoV-2 also. Recently, the crystal structure of COVID-19 is reported and hence, we have used this tom predict the binding affinity with SARS-CoV-2-main protease and prepared a pharmacophore that may be used for future design of novel inhibitors.

Cervical cancer is known as one of the most important cancers in women worldwide. Chemotherapy is a standard treatment for advanced/recurrent cervical cancer in which the prognosis of the disease is really poor and the 1-year survival chance in these patients is maximally 20%. However, resistance to anticancer drugs is a major problem in treating cancer. Cervical cancer stem cells are considered as a fundamental cause of chemo and radio-resistance and also relapse after primary successful treatment. Signaling pathways include a wide range of molecular mechanisms contribute to drug resistance. Recently, microRNAs (miRNAs) are announced as a group of molecular biomarkers involving in response to chemotherapy in cancer patients. As the miRNAs, there are some long non-coding RNAs (LncRNAs) which their aberrant expression is considered as a biomarker for monitoring chemoresistance. In this review, we summarized current reports about the involvement of signaling pathways during chemoresistance in cervical cancer. Then, genes that have been demonstrated their involvement during drug resistance in cervical cancer were tabulated. Further, miRNAs that have been reported as biomarkers during treatment are listed. By bioinformatic analysis, we predictedmiR-335-5p and miR-16-5p as the most potential biomarkers for monitoring resistance to chemotherapy. Finally, long non-coding RNAs that have been introduced in recent studies as novel biomarkers during the response to chemotherapy were mentioned.

A literature review was conducted to summarize the frequency of the D-allele of the angiotensin-converting enzyme-1 in all countries with available data. Using an ecological study design limited to high income countries, we found that the country-level frequency of the D-allele was associated with increased COVID-19 incidence and mortality.