Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Lockdown on Air Quality in Pakistan during the COVID-19 Pandemic Inferred from the Multi-sensor Remote Sensed Data

ABSTRACT The present study utilized multi-sensory gridded and reanalysis data in conjunction with the meteorological variables to evaluate the impact of lockdown due to the Coronavirus disease of 2019 (COVID-19) pandemic on the changes of concentration of atmospheric pollutants in Pakistan. We focused on assessing the significant changes of pollutant concentrations during March-May for the years 2019 and 2020 utilizing the satellite datasets observed from the Moderate Resolution Imaging Spectroradiometer (MODIS), Ozone Monitoring Instrument (OMI), Atmospheric Infrared Sounder (AIRS), and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis data. Low pollution levels were observed throughout the COVID-19 (March 25–May 31, 2020) compared to a similar period in 2019. The association of meteorology with air pollutants found that the periods of enhanced temperature and relative humidity likely contributed to a cleaner environment over the Indus Basin Region (IBR) and Balochistan Plateau (BP). The decrease in the mean planetary boundary layer Sulphur dioxide (SO2) during the lockdown period of 2020 (DLP-2020) was evident by -36% in BP, -34% in Khyber Pakhtunkhwa (KPK), and -15.15% in IBR when compared to before the lockdown period of 2019 (BLP-2019). This is attributed to the limited transportation and control action plans of industrial activities including combustion sources taken by the Government of Pakistan for the DLP-2020 phase. During DLP-2020, a variable and least significant decline in surface particulate matter of size 2.5 mm (PM2.5) concentration was observed in the urban regions of KPK (-19.17%) followed by IBR (-0.82%) and BP (-0.26%). Overall, a considerable reductions in Carbon monoxide (CO) and black carbon (BC) concentrations were smaller in rural and suburban areas of BP (-3.61%, -8.57%) followed by KPK (-0.79%, -11.39%) and IBR (-3.30%, -11.39 %), respectively. This is due to the reduction in local emissions related to the lockdown measures taken in the control of pandemic. However, the ozone (O3) concentrations witnessed an increase to a lower extent as 11.39%, 5.78%, and 4.74% in KPK, BP, and IBR, respectively attributed to rising in solar radiation intensity and temperature in hot summers, and decrease in NOx levels during the study period.
Identifying a Sustainable Food Procurement Strategy in Healthcare Systems: A Scoping Review

The healthcare system’s climate footprint is equivalent to 4.4% of global net emission. The food service offered, with subsequent food waste production and energy consumption, falls within the spectrum of environmentally harmful activities. The development of a Sustainable Food Procurement Strategy is an opportunity to counteract these negative effects. This article aims to identify the nature and extent of the evidence found in the literature on the processes related to food procurement within healthcare systems and analyse them from the perspective of sustainability dimensions. A scoping review is carried out using online databases to identify scientific and grey literature published in English during the period 2000–2019. An analytical-synthetic approach is used for charting the data. Twenty-six studies are included; 65% of them published in the last five years. These include research articles (n 11), an opinion article (n 1), policy handbooks and guides (n 2), project reports (n 4) and technical reports (n 3), policy forums (n 1), factsheet documents (n 3), and legislative directives (n 1). The outcomes framework highlights multilevel governance, a sustainable food supply system, and healthy and sustainable food services as the main action areas for a sustainable food procurement strategy, along with six transversal features: long-term commitment, investment, evaluation, communication, gender, and a holistic approach.
Spherical Droplet Deposition—Mechanistic Model

In the currently existing physical models of wetting a solid substrate by a liquid drop, the contact angle is determined on the basis of the equilibrium of forces acting tangentially to the wetted surface at any point in the perimeter of the wetted area, ignoring the forces (or their components) acting perpendicular to this area. In the solution shown in the paper, the equilibrium state of forces acting on a droplet was determined based on the minimum mechanical energy that the droplet achieves in the state of equilibrium. This approach allows one to take into account in the model, in addition to the forces tangential to the wetted surface, also forces perpendicular to it (also the force of adhesion), moreover, these may be dispersed forces acting on the entire interface, not on a single point. The correctness of this approach is confirmed by the derived equations concerning the forces acting on the liquid both tangentially and perpendicularly to the wetted surface. The paper also identifies the areas of solutions in which the obtained equilibrium of forces is stable and areas of unstable equilibrium of forces. The solution is formulated both for isothermal and isochoric system. Based on the experimental data accessible in the literature, the condition that has to be met by the droplets (and their surroundings) during measurements performed under gravity conditions was formulated.
Effective classification of android malware families through dynamic features and neural networks

Due to their open nature and popularity, Android-based devices have attracted several end-users around the World and are one of the main targets for attackers. Because of the reasons given above, it is necessary to build tools that can reliably detect zero-day malware on these devices. At the moment, many of the frameworks that have been proposed to detect malware applications leverage Machine Learning (ML) techniques. However, an essential requirement to build these frameworks consists of using very large and sophisticated datasets for model construction and training purposes. Their success, indeed, strongly depends on the choice of the right features used for building a classification model providing adequate generalisation capability. Furthermore, the creation of a training dataset that well represents the malware properties and behaviour is one of the most critical challenges in malware analysis. Therefore, the main aim of this paper is proposing a new dataset called Unisa Malware Dataset (UMD) available on http://antlab.di. unisa.it/malware/, which is based on the extraction of static and dynamic features characterising the malware activities. Additionally, we will show some experiments concerning common ML tools to demonstrate how it is possible to build efficient ML-based malware classification frameworks using the proposed dataset.
Control and optimisation of networked microgrids: A review

Microgrids (MGs) have become an integral part of smart grid initiatives for future power system networks. Networked microgrids consist of several neighbouring microgrids connected in a low/medium distribution network. The primary objective of a network is to share surplus/shortage power with neighbouring microgrids to achieve mutual cost‐effective operation, utilising green energy from renewable energy resources in the network and increasing the reliability of customer service. This article classifies networked microgrids on the basis of network formation and provides an overview of recent research on control of networked microgrids. In addition, a state‐of‐the‐art review of optimisation methods is provided to solve the energy optimisation problem in networked microgrids. Furthermore, the advantages and challenges of the networked operation of microgrids are presented as for possible research directions in the future.
Efficient Oblivious Query Processing for Range and kNN Queries

Increasingly, individuals and companies adopt a cloud service provider as a primary data and IT infrastructure platform. The remote access of the data inevitably brings the issue of trust. Data encryption is necessary to keep sensitive information secure and private on the cloud. Yet adversaries can still learn valuable information regarding encrypted data by observing data access patterns. To solve such problem, Oblivious RAMs (ORAMs) are proposed to completely hide access patterns. However, most ORAM constructions are expensive and not suitable to deploy in a database for supporting query processing over large data. Furthermore, an ORAM processes queries <italic>synchronously</italic>, hence, does not provide high throughput for <italic>concurrent query processing</italic>. In this article, we design a practical <italic>oblivious query processing framework</italic> to enable efficient query processing over a cloud database. In particular, we focus on processing multiple range and <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="chang-ieq1-3060757.gif"/></alternatives></inline-formula>NN queries <italic>asynchronously and concurrently with high throughput</italic>. The key idea is to integrate indices into ORAM which leverages a suite of optimization techniques (e.g., oblivious batch processing and caching). The effectiveness and efficiency of our oblivious query processing framework is demonstrated through extensive evaluations over large datasets. Our construction shows an order of magnitude speedup in comparison with other baselines.
An Introductory Tutorial on Brain–Computer Interfaces and Their Applications

The prospect and potentiality of interfacing minds with machines has long captured human imagination. Recent advances in biomedical engineering, computer science, and neuroscience are making brain–computer interfaces a reality, paving the way to restoring and potentially augmenting human physical and mental capabilities. Applications of brain–computer interfaces are being explored in applications as diverse as security, lie detection, alertness monitoring, gaming, education, art, and human cognition augmentation. The present tutorial aims to survey the principal features and challenges of brain–computer interfaces (such as reliable acquisition of brain signals, filtering and processing of the acquired brainwaves, ethical and legal issues related to brain–computer interface (BCI), data privacy, and performance assessment) with special emphasis to biomedical engineering and automation engineering applications. The content of this paper is aimed at students, researchers, and practitioners to glimpse the multifaceted world of brain–computer interfacing.
Semiotics Approach on Verbal Signs in Would You Care More IF I Was A Panda?

DOI: https://doi.org/10.24843/JH.2 021.v25. i01.p09 This study is aimed at identifying the verbal signs with their mode and connotative meaning of an advertisement. The data of this study was a wildlife advertisement entitled Would You Care More IF I Was A Panda? (2011) created by Ogilvy and published by World Wild Life. The data were collected using documentation method with note-taking technique. The data were analyzed qualitatively using Peirce’s semiotic theory to identify the verbal signs with their mode and Leech meaning theory to analyze the connotative meaning of the sign. The result of this study shown that there were three verbal signs found in the advertisements that belong to symbolic signs in the form of the combination of alphabets. The verbal signs consist of representamen, interpretant, and object. The connotative meanings are expressed in words, phrases, or sentences with the interpretation based on knowledge, emotion, and imagination.
Career Decision-Making Difficulties and Life Satisfaction: The Role of Career-Related Parental Behaviors and Career Adaptability

According to the Career Construction Model of Adaptation, career decision-making difficulties (CDD) and life satisfaction are important adaptation results, and career adaptability is a crucial resource to attain positive adaptation results. This study focused on the influence of parental career-related behaviors on career adaptability, CDD and life satisfaction, and the mediating role of career adaptability between parental career-related behaviors and CDD and life satisfaction. Five hundred thirteen Italian students (182 of middle school, 141 of high school, and 190 of university) were involved. The results showed that parental support influences CDD and life satisfaction both directly and indirectly through the mediation of career adaptability. Parental interference and lack of engagement have a positive direct effect on CDD. Finally, CDD and life satisfaction are significantly and negatively associated. The data support the key role of parental support and career adaptability in CDD and life satisfaction. Practical implications are discussed.
Effect of remote exercise education on psychological status and body awareness

The curfew restrictions applied during the pandemic period have had negative physical and psychological effects on people all over the world. Therefore, the aim of the study is examining the effect of distance exercise education on psychological state and body awareness. Twenty-one sedentary women aged 20-30 years participated in the study. Exercises were carried out for 6 weeks, 3 days a week, 1 hour daily. The exercise program sent to the participants digitally consists of a total of 8 moves: plank, crunch, leg raise, flutter kicks, mountain climbers, arms-high partial sit up, heel touches, half push up. 10 minutes of warm-up at the beginning of each exercise and 5 minutes of active cooling with 5 minutes of stretching at the end. All participants had the Body Awareness Questionarre (BAQ) and Beck Depression Inventory (BDI) filled digitally 6 weeks before and 6 weeks later. SPSS 20.00 program was used to analyze the data. The shapiro wilk test was used to determine whether the data showed normal distribution. Wilcoxon signed ranks test was used as the data did not show normal distribution in the analyzes. Significance level was accepted as p < 0.05. A statistically significant difference was found in all data as a result of the pre-test and post-test comparison of body weight, BDI and BAQ values (p < 0.05). As a result, it can be said that the exercise program applied to sedentary individuals has a positive effect on psychological state and body awareness.
Fortified-Chain: A Blockchain-Based Framework for Security and Privacy-Assured Internet of Medical Things With Effective Access Control

The rapid developments in the Internet of Medical Things (IoMT) help the smart healthcare systems to deliver more sophisticated real-time services. At the same time, IoMT also raises many privacy and security issues. Also, the heterogeneous nature of these devices makes it challenging to develop a common security standard solution. Furthermore, the existing cloud-centric IoMT healthcare systems depend on cloud computing for electrical health records (EHR) and medical services, which is not suggestible for a decentralized IoMT healthcare systems. In this article, we have proposed a blockchain-based novel architecture that provides a decentralized EHR and smart-contract-based service automation without compromising with the system security and privacy. In this architecture, we have introduced the hybrid computing paradigm with the blockchain-based distributed data storage system to overcome blockchain-based cloud-centric IoMT healthcare system drawbacks, such as high latency, high storage cost, and single point of failure. A decentralized selective ring-based access control mechanism is introduced along with device authentication and patient records anonymity algorithms to improve the proposed system’s security capabilities. We have evaluated the latency and cost effectiveness of data sharing on the proposed system using Blockchain. Also, we conducted a logical system analysis, which reveals that our architecture-based security and privacy mechanisms are capable of fulfilling the requirements of decentralized IoMT smart healthcare systems. Experimental analysis proves that our fortified-chain-based H-CPS needs insignificant storage and has a response time in the order of milliseconds as compared to traditional centralized H-CPS while providing decentralized automated access control, security, and privacy.
Tandem Cycloaddition-Cycloreversion of 2-pyrone and 1,4-oxazinone with Acetylene - A DFT Insight

Reaction of either 2-pyrone or 1,4-oxazinone with acetylene follows the sequence of cycloaddition - cycloreversion through concerted mechanism. Transition states for both cycloaddition and cycloreversion pathways have been obtained in both the cases by modelling the reactions at B3LYP/6-31g (d) level. Cycloreversion is faster than cycloaddition in the case of 2-pyrone due to the enhancement of aromaticity resulting the product as benzene. In contrast, oxazinone has rapid cycloaddition. It is ascribed to the presence of nitrogen in this system. Removal of either CO2 or HCN is plausible in this mechanism to complete the reaction. Even though two pathways are feasible for cycloreversion, CO2 extrusion is more preferable than HCN elimination. In these two studied molecules, there is an enhancement of aromaticity up to transition states like any other pericyclic reaction and further it diminishes during cycloaddition. Further, aromaticity is specifically augmented in cycloreversion phase during CO2 elimination resulting to yield pyridine whereas competitive HCN elimination results in the formation of 2-pyrone which is less facile. In both the molecules the aromatic enhancement of the cycloreversion is substantiated through the study of magnetic susceptibility of the ring fragment along the reaction coordinate. Further the study also reveals the effect of halogen substituted at different carbons of 2-pyrone ring.
Oat genotypic requirement for intercropping with vetch under Mediterranean conditions

Abstract Oat (Avena spp. L.) intercropped with common vetch (Vicia sativa L.) has shown high forage yield and crude protein content (CP) in rainfed Mediterranean environments of Greece. The objective was to study the oat genotypic interactions for yield, quality and agronomic traits of four oat accessions (cv. Flega and lines B2, B3 and B4) grown as intercrops with a common vetch cultivar (Pegasus) and as monocrops without or with nitrogen (N) supplementation (100 kg N/ha). In all mixtures, the land equivalent ratio exceeded the unit indicating that there was a yield advantage. Intercrops produced, on average, 5.0% less dry matter (DM) and 38.9% more crude protein yield (CPY) compared to monocropped oats with N fertilization and 3.4% more DM and 75.5% more CPY compared to monocropped oats without N fertilization. The DM, CP and quality differences between the intercropped and monocropped oats were attributed to oats by vetch cultivar interactions. The oat B2 intercropped was the shortest, the latest flowering and the less vigorous early in the season, a trait that allowed common vetch to dominate in the intercrop (vetch participation 770 g/kg). The high vetch fragment in the intercrop contributed to high CP, CPY, acid detergent lignin, total digestible nutrients, relative feeding value, relative forage quality, net energy for lactation and to low neutral detergent fibre, acid detergent fibre and hemicellulose. The replacement value index indicated that the intercrop was 21% more economically viable in comparison to the fertilized monocrop.
Purification and Characterization of Lipase Enzyme From Endophytic Bacillus Pumilus WSS5 for Application in Detergent Industry

Lipolytic enzymes from endophytic microbes have been the focus of intense and growing research in view of the applicability of such enzymes in various industrial applications and endophytic microorganisms may emerge as a potential source of lipases with distinct characteristics. The current work involved purification and characterization of the lipase from an endophytic-bacteria isolated from the stem of Withania somnifera L. Dunal. Based on the analysis of morphology and 16S rDNA sequence, the endophytic bacteria was identified as Bacillus pumilus and designated as B. pumilus WSS5. Purified lipase from the B. pumilus WSS5 was found to be of 28 KDa as revealed by SDS-PAGE with optimum activity at 37°C and pH 8. The enzyme was found to be stable over a broad pH range of 6.0–9.0 and temperature stability was in the range of 10°C to 60°C. The enzyme activity was enhanced in the presence of organic solvents like Ethyl acetate, Methanol, 2-propanol, acetone, and ethanol. The stability of the enzyme in presence of various metal ions, surfactants, inhibitors, and kinetic parameters value suggested that this enzyme could be exploited in leather and detergent industries.In addition, the stain removal potential of the crude and purified lipase was determined on cotton fabric pieces stained with vegetable oil. Lipase added to water along with detergent significantly enhanced the stain removal efficiency of a commercially available detergent. The current findings suggest the potential of B. pumilus WSS5 lipase owing to promising properties such as the alkali-thermostability, organic solvent-tolerance, and broad substrate specificity that makes it a strong candidate for application in detergent formulations, biotransformation, industries, and medicine. To our knowledge, this is the first report on the purification and characterization of lipase from bacterial endophyte isolated from the stem of Withania somnifera L. Dunal.
Learning to Cycle: From Training Wheels to Balance Bike

Background: Learning to cycle is an important milestone in a child’s life, so it is important to allow them to explore cycling as soon as possible. The use of a bicycle with training wheels (BTW) for learning to cycling is an old approach practiced worldwide. Most recently, a new approach using the balance bike (BB) has received increased attention, and several entities believe that this could be most efficient. Drawing on the work of Bronfenbrenner (1995) and Newel (1986), this study aimed to analyse the effect of BB’s use on the learning process of cycling independently. Methods: Data were collected in Portugal from an online structured survey between November 2019 and June 2020. Results: A total of 2005 responses were obtained for adults and children (parental response). Results revealed that when the BB’s approach was used, learning age (LA) occurred earlier (M = 4.16 ± 1.34 years) than with the BTW’s approach (M = 5.97 ± 2.16 years) (p < 0.001); or than when there was only the single use of the traditional bicycle (M =7.27 ± 3.74 years) (p < 0.001). Conclusions: Children who used the BB as the first bike had a significantly lower LA than children who did not use it (p < 0.001). To maximize its effects, the BB should be used in the beginning of the learning process.
Layered Perovskite Pb2Bi4Ti5O18 for Excellent Visible Light-Driven Photocatalytic NO Removal

A grand challenge in photocatalysis is to seek chemically stable photcatalysts with minimized recombination of photoinduced charges in order to maximize the efficiency of the subsequent redox reactions. Because of the structural noncentrosymmetry, TiO2-based and lead-containing perovskite-type photocatalysts exhibit excellence in both stability and ferroelectricity to facilitate charge separation state. To extend their visible light activity, we use molten salts synthesis methodology to prepare Pb2Bi4Ti5O18 perovskites with various nanoscale morphologies and evaluated their visible light-driven photocatalytic activity for NO removal. The results show that perovskite Pb2Bi4Ti5O18 samples exhibit excellent stability as well as display over 50% NO removal efficiency under visible light in contrast to no more than 15% for commercial P25. A set of radical scavengers were used to probe the reaction mechanism. A bond-valence method was used to calculate the direction and magnitude of the dipole moments of the as.