1960s Europe saw a large number of residential neighborhoods built to house those migrating from the countryside. Today, more than 50 years later, these neighborhoods suffer high levels of functional, social, and technical obsolescence. In response to this, University of Seville developed the Aura Strategy as an intervention methodology to find global solutions to issues in outdated neighborhoods. To provide visibility to this aspect of the Aura strategy, the retrofit proposal presented in this article provides a solution to improve the roofing of buildings in a case study neighborhood (Polígono de San Pablo, Seville) and an analysis of the results in terms of energy and financial savings for local residents. The results show that for a population of roughly 18,000 (in 2018), net savings, including energy and retrofitting costs, ranging from nearly 6.5 to over 8.6 million can be made over the 20-year life cycle span. Likewise, the results obtained on the reduction of thermal loads indicate a 72% decrease in energy consumption, equivalent to a saving of close to 4,500 tons of greenhouse gas emissions for the district and the entire life cycle time period, with the consequent benefits on the impact on air quality and and the fight against climate change. climate change.

Advanced machine learning algorithms, have the potential to be successfully applied to many areas of system modelling. In the present study the capability of ten machine learning algorithms in predicting the structural damage of an 8-storey reinforced concrete frame building subjected to single and successive ground motions is examined. From this point of view, the initial damage state of the structural system, as well as 16 well known ground motion intensity measures are adopted as the features of the machine-learning algorithms that aim to predict the structural damage after each seismic event. The structural analyses are performed considering both real and artificial mainshock–aftershock sequences, while the structural damage is expressed in terms of two overall damage indices. The comparative study results in the most efficient damage index, as well as the most promising machine learning algorithm in predicting the structural response of a reinforced concrete building under single or multiple seismic events. Finally, the configured methodology deployed in a user-friendly web-application.

Background: Objectives. The objective of this study was to compare the efficacy of direct current stimulation (DCS) applied at the transcranial, suboccipital and spinal level on experimental sensory modalities and pain outcome measures in healthy subjects. The hypothesis of this study was that systematic analysis of the efficacy of DCS on modulating evoked thermal and mechanical pain modalities and mechanisms such as endogenous pain modulation in healthy individuals would reveal sensitive outcome measures help develop this technique for the control of chronic pain. Materials and Methods. Database searches were conducted up to December 2019 for randomized controlled trials that performed sham-controlled DCS of experimental sensory modalities and pain outcomes following transcranial, suboccipital and spinal locations in healthy participants. Standardized mean differences with 95% confidence intervals were calculated for sensory modalities, including random-effect metanalysis. Results: Thirty-one studies were included for analysis (647 participants). A significant decrease in pain intensity for active vs sham transcranial stimulation was identified for pain intensity (n=158; SMD=0.79; 95% CI=0.56 to 1.02), a significant increase in heat pain threshold (n=222; SMD=1.16; 95% CI=0.95 to 1.37), and a significant increase in cold pain threshold (n = 155; SMD = 0.77, 95% CI 0.53 to 1.01). No significant modulation of pressure pain threshold was identified with DCS and only a limited number of studies focused on experimental pain modulation following neuromodulation at the suboccipital or spinal level. Conclusions: These results show significant transcranial DCS neuromodulation of pain intensity and on thermal pain modalities. Future studies should focus on endogenous pain and sensory modality modulation with sham-controlled DCS applied at transcranial, suboccipital and spinal locations.

Abstract: The marketing of Sugar-Sweetened Beverages (SSBs) within grocers is an obesogenic factor that negatively impacts children’s nutritional behavior, specifically regarding people from racial and ethnic minority groups. We aimed to develop and employ a methodology that more precisely assesses the availability, price, and promotion of SSBs to young immigrant children within independently owned grocery stores. A case comparison design was used to explore the differences in the grocery store landscape of SSB marketing by conducting an enhanced Nutrition Environment Measures Survey-SSB (NEMS-SSB) within 30 grocery stores in the Hispanic and Latino enclaves in Southwest Detroit, in the Arab and Chaldean enclaves in North-central Detroit, and in Warren, Hamtramck, and Dearborn, in comparison with 48 grocers in Metro Detroit. Organic, plant-based, and unsweetened toddler and infant beverages, as well as questions about marketing, were added to the original NEMS-S to capture the promotion tactics used in marketing SSBs. NEMS-SSB scores revealed in the immigrant enclaves there was a significantly higher availability of SSBs in grocery stores (−2.38), and they had lower prices than those in the comparison group (−0.52). Availability of unsweetened and organic beverages was zero in 97% of all participating grocery stores. Signage featuring cartoon characters was the most frequent in-store SSB marketing tactic. Widespread SSB marketing towards toddlers within the grocery stores in immigrant enclaves could be linked with the higher childhood obesity prevalence among this population. Our findings can assist local and national organizations in developing and implementing healthy eating interventions. This study can be repeated in other states to provide comparable results.

Objectives to assess COVID-19 mortality rates per country population. To determine what if any independent country-specific variables from 9 different databases were correlated. Design population based retrospective cohort study. Setting analysis of global COVID-19 treatment and containment strategies using data from 9 worldwide websites. Participants 108 countries worldwide. Interventions none. Main Outcome Measures were COVID-19 death rates per country population analyzed by univariate and multivariate analysis. The main outcome parameters were to determine if there are any correlations between the percentage of countrywide COVID-19 deaths/population by the countries’ percent vaccinated. Secondary outcome measures include the effect of other independent variables on COVID-19 death rates per country population including: health expenditures per capita, annual income per capita, COVID-19 tests per 1000 people, stringency index (a measure of each countries containment strategies), hydroxychloroquine score (a measure of each countries use), ivermectin score (a measure of each countries use), hypertension, obesity, diabetes, and specific countries and geographic locations. Results COVID-19 vaccination rates ranged from 0-99% in 108 countries. Univariate analysis demonstrates the following independent variables to correlate with COVID-19 deaths/population (correlation coefficient, p value): countrywide COVID-19 vaccination rates (+0.2936, p=0.002); healthcare costs per capita (+0.3212, p=0.0007), income per capita (+0.3051, p=0.0013), COVID-19 tests per 1000 population (+0.6981 p=0.0307); stringency index (+0.3098, p=0.0011); hydroxychloroquine index (-0.1337, p=0.0678); and ivermectin index (-0.1383, p=0.1535). Conclusions Increasing rates of COVID-19 vaccination are associated with increase COVID-19 death rates per country population (p=0.002). Other variables associated include healthcare costs per capita (+0.3212, p=0.0007), income per capita (+0.3051, p=0.0013), COVID-19 tests per 1000 population (+0.6981 p=0.0307); and stringency index (+0.3098, p=0.0011).

There is little understanding of patients' experiences and perceptions with satisfaction by health professionals such as medical and dental clinicians. Furthermore, patient satisfaction is not well understood. The objective of this article is to better understand patients' satisfaction with their medical and dental care. The methods of the current article are based on a narrative review of the literature strategy. Patient satisfaction's multidimensional nature has been established since the perceived reasons for satisfaction varied widely among patients. Many aspects of the treatment influence participant satisfaction at different stages of the intervention's process. An improved understanding of the basis for managing patients' expectations with information reiteratively and efficiently may ultimately reduce patients' potential for negative feelings toward the medical and dental treatment experience. The consumerist method may misrepresent the concept of satisfaction in health service.

Background: COVID-19 pandemic has pulled us all a few steps back, were we never shake hands or hug each other when we meet our friends and family after a gap, but instead we greet them by saying Namaste and joining our hands together. As we all know, COVID-19 spreads through air and the only way to shield ourselves is by maintaining a safe distance from one another. Methodology: In order to conduct a meta-analysis on the number of COVID-19 cases in Kerala and India, the data was retrieved from various sites hosted by the government bodies. The data for analysis was collected from May 2020 to July 2020. The average number of days required to reach every 5000 fresh cases were also calculated using this data. COVID-19 has affected all the economy holistically regardless of financial, behavioral, or societal aspects. Conclusion: Lifting of the lockdown in a step by step process keeping in mind the necessities for the nation was a thoughtful act, but the people who mistook this opportunity and did not remain in quarantine after coming from abroad was recognized as the reasons behind the sudden and uncontrolled rise in the number of COVID-19 cases in Kerala, India. The government authorities had no other option but to lift the restrictions to reduce the economic burdens that had already affected the daily wage worker and farmers prompting them to give up their lives.

This paper presents a method of fusion of identification (attribute) information provided by two types of sensors: combined primary and secondary (IFF) surveillance radars and ESM (Electronic Support Measures). In the first section, the basic taxonomy of attribute identification is adopted in accordance with the standards of STANAG 1241 ed. 5 and STANAG 1241 ed. 6 (draft). These standards provide the following basic values of the attribute identifications: FRIEND, HOSTILE, NEUTRAL, UNKNOWN and additional values: ASSUMED FRIEND and SUSPECT. The basis of theoretical considerations is Dezert-Smarandache theory (DSmT) of inference. The paper presents and practically uses for combining identification information from different ESM sensors and radars six information fusion rules proposed by DSmT - the Proportional Conflict Redistribution rules (PCR1, PCR2, PCR3, PCR4, PCR5 and PCR6). In the paper, rules of determining attribute information by ESM sensor equipped with the data base of radar emitters are presented. It was proposed that each signal vector sent by the ESM sensor contained an extension specifying a randomized identification declaration (hypothesis) - basic belief assignment (BBA). The paper also presents a model for determining the basic belief assignment for a combined primary and secondary radar. Results of the PCR rules of sensor information combining for different scenarios of radio-electronic situation (deterministic and Monte Carlo) are presented in the final part of the paper. They confirm the legitimacy of the use of Dezert-Smarandache theory into information fusion for primary radars, secondary radars and ESM sensors.

Toxoplasmosis is a zoonosis of warm-blooded animals, affecting also humans, caused by Toxo-plasma gondii, an obligate intracellular parasite with a complex biological cycle. Toxoplasmosis is considered a re-emerging zoonosis and an important public health threat, also for the absence, up to now, of efficient vaccines and preventive measures. Sources of transmission to humans are environmental or food-borne, mainly through the consumption of raw and undercooked meat, predominantly of Sus scrofa, considered highly susceptible to T. gondii. Mainly in the last dec-ades, an effective strategy to counter animal infectious diseases was based on the discovery of resistance immuno-genetic markers, possibly to be used for association studies between geno-typic and phenotypic traits and consequently in Marker Assisted Selection. Until now, this gen-otyping approach has never been adopted for T. gondii infection, so this study aimed, for the first time, to fill this gap. In particular, pigs, reared in different farms of Central Italy, were serologically characterized by an ELISA assay performed on diaphragm meat juice. Out of 179 tested animals, 98 resulted seropositive (54.74%), 57 seronegative (31.84%) and 24 doubtful (10.6%), underlining a possible re-emerging diffusion of this protozoan in the investigated areas. Atten-tion was firstly focused on IL-18 gene, encoding for a pro-inflammatory cytokine that plays a key role starting from the upstream steps of the immunity pathway towards T. gondii. A RT-PCR assay followed by Sanger sequencing of IL-18 cDNA was de novo developed. For this interleukin, at this stage, genetic analysis has not highlighted significant polymorphic variations compared to the reference sequence, except for a seropositive animal. However, the outcomes of this pre-liminary innovative study will be investigated in depth analyzing other relevant genetic re-gions and other target genes.

Number of studies claim that tobacco control (TC) regulations are associated with reductions in smoking-related hospitalisation rates, however very few have estimated the impact of TC laws (TCL) at both countrywide and regional levels, and none of them - in relation to compliance with TC regulations. This study evaluates the effects of Russian TCL on hospital admission (HA) rates for pneumonia countrywide and in 10 Russian regions and the extent of these effects in connection with the compliance to TCL. Methods: HA rates for pneumonia during 2005–2019 were analysed to compare the periods before and after the adoption of TCL in 2013. An interrupted time series design and a Poisson regression model were used to estimate the immediate and long-term effects of TCL on pneumonia annual hospitalisation rates after the TCL adoption, compared with the pre-law period. The 10 Russian regions were compared using the TCL Implementation Scale (TCIS) developed on the basis of the results of Russian TC policy evaluation survey; Spearman’s rank correlation and linear regression models were employed. Results showed a 14.3% reduction in HA rates for pneumonia (RR 0.88; p=0.01) after the adoption of TCL in Russia with significant long-term effect after 2013 (RR 0.86; p=0.006). Regions with better enforcement of TCL exhibited greater reductions in pneumonia HA rates (rsp=−0.55; p=0.04); (=−4.21; p=0.02). Conclusions: TCL resulted in a sustained reduction in pneumonia hospitalisation rates, but these effects, varying by region, may depend on the scale of the TCL enforcement.

The increase in arrivals of new forest pests highlights the need for effective phytosanitary legislation and measures. This paper introduces legislation targeted at prevention and management of potential introductions of forest pests and pathogens. A summary is given on plant health regulations on a global and regional level with detailed information on the situation in the European Union (EU). The current and new European legislation is discussed and a particular focus is given on eradication and contingency plans for Fusarium circinatum.

Using assembly theory, we investigate the assembly pathways of fixed-length binary strings formed by joining the individual bits present in the assembly pool and the strings that entered the pool as a result of previous joining operations. We show that the string assembly index is bounded from below and above, and we conjecture about the form of the upper bound. We show that a string having the smallest assembly index can be assembled by an elegant trivial program of length equal to this index, if the length of the string is expressible as a product of Fibonacci numbers. We conjecture that there is no binary program that has a length shorter than the length of the string having the largest assembly index that could assemble this string. We conjecture that a black hole surface is defined by a balanced distinct string that satisfies the upper bound of a distinct string assembly index. The results confirm that four Planck areas provide a minimum information capacity that provides a minimum thermodynamic (Bekenstein-Hawking) entropy. Knowing that the problem of determining the assembly index is at least NP-complete, we conjecture that the problem of determining the assembly index of a given binary string is NP-complete, while the problem of creating the string so that it would have a predetermined maximum assembly index is NP-hard. Therefore, once the new information is assembled by a dissipative structure or by a human, increasing the information entropy according to the second law of infodynamics, it is subject to the second law of thermodynamics, and nature seeks to optimize its assembly pathway.

After reviewing the history of the struggle between human beings and plant diseases, insects and weeds, especially reviewing the thoughts of plant protection in ancient Chinese agricultural books, the target recognition of plant pests and the six types of plant protection methods and 36 subdi-vision measures were summarized. Then the development overview of pesticide application technology was focused and reviewed systematically by combining the development timeline of pesticide application and the key technologies including the performance measurement and the simulation and modeling of pesticide spraying system. And three suggestions for further research were proposed from the perspectives of human-being and environmental health, the sustainable and eco-friendly application medium, and the efficiently application equipment system in plant protection.