Miracle-dz/UniFAR-FTUs huggingface dataset:
Patterns of Periodontal Destruction among Smokeless Tobacco Users in a Central Indian Population

Background: Findings of studies testing the association between smokeless tobacco (SLT) use and periodontal health have shown varying results in different populations. Considering the high prevalence of SLT use in India, the present study was conducted to understand the pattern of periodontal destruction within different areas of the dentition among SLT users. Methods: Age, gender, oral hygiene habits, the frequency and duration of SLT consumption, the type of SLT product used, and the site of retention of the SLT product in the oral cavity were recorded among 90 SLT users. Probing depth (PD), recession (REC), and clinical attachment loss (CAL) at SLT-associated and non SLT-associated teeth of the mandibular arch were compared based on the site of retention of the SLT product, the type of product used, and the duration of the habit. Results: REC and CAL were significantly higher at the SLT-associated zones compared to non SLT-associated zones and at both interproximal and mid-buccal sites of SLT-associated teeth. Among individuals who had the habit for more than 5 years and also among those who had the habit for 5–10 years, PD, REC, and CAL were significantly higher at SLT-associated teeth than at non SLT-associated teeth. Significantly greater periodontal destruction was observed at SLT-associated teeth among khaini users and gutkha users. Conclusions: Smokeless tobacco consumption resulted in greater destruction of periodontal tissues. The severity of periodontal destruction at SLT-associated sites differed depending on the type of smokeless tobacco used, the site of retention of the SLT, and the duration of the habit.
Optimizing Blockchains Structures Based on Entropy and TOPSIS Model

In this study, a new and applicable model is proposed which represents the opportunities of implementing blockchains into IoT framework in the sensor data acquisition. We aim to propose a simple perspective of blockchain in IoT which is flexible with high throughput in sensor networks. This method is based on probabilities that use the combination of the Entropy and TOPSIS model and the blockchain parameter configuration used in the proposed model in this study includes: Parameters, Block, Epoch Time, Consensus Protocol, Throughput Queuing, Network Topology and Containerization. We selected Hyperledger Fabric as our blockchain solution to deploy across our network with the use of Docker Swarm. Our framework leverages the containerization of Fabric so that the network can operate between the edge devices and the cloud in a single, private system. This model contains some areas in security, such as privacy policy and delay versus the value of the task to be processed.
Self-healing and shape memory functions exhibited by supramolecular liquid-crystalline networks formed by combination of hydrogen bonding interactions and coordination bonding

We here report a new approach to develop self-healing shape memory supramolecular liquid-crystalline (LC) networks through self-assembly of molecular building blocks via combination of hydrogen bonding and coordination bonding. We have designed and synthesized supramolecular LC polymers and networks based on the complexation of a forklike mesogenic ligand with Ag+ ions and carboxylic acids. Unidirectionally aligned fibers and free-standing films forming layered LC nanostructures have been obtained for the supramolecular LC networks. We have found that hybrid supramolecular LC networks formed through metal–ligand interactions and hydrogen bonding exhibit both self-healing properties and shape memory functions, while hydrogen-bonded LC networks only show self-healing properties. The combination of hydrogen bonds and metal–ligand interactions allows the tuning of intermolecular interactions and self-assembled structures, leading to the formation of the dynamic supramolecular LC materials. The new material design presented here has potential for the development of smart LC materials and functional LC membranes with tunable responsiveness.
Progress on Preparation of pH/Temperature-Sensitive Intelligent Hydrogels and Applications in Target Transport and Controlled Release of Drugs

Hydrogels with three-dimensional network structure, hydrophilic, and insoluble in water which are ideal carrier materials for intelligent drug delivery systems. Intelligent hydrogel has become a research frontier and hotspot because of its intelligence, high efficiency, safety, and convenience in drug controlled and prolonged release. It has a broad application prospect in the medicine and biomedicine fields and can lead the medicine fields into a new era of “precise treatment. ” Based on the latest research progress, the main preparation methods of hydrogel and the development of the drug delivery system are briefly introduced. The most promising three intelligent hydrogels in the human physiological environment, namely, pH responsiveness, temperature responsiveness, and pH/temperature dual responsiveness, are emphatically reviewed. Their release mechanisms, targeting transport, and controlled-prolonged release of drug are also discussed. In addition, some suggestions for the main problems and future development were given.
Assessing the Performance of Modal Interchange for Ensuring Seamless and Sustainable Mobility in European Cities

In the European Union, more than 70% of the population lives in urban areas. Achieving more efficient and low-carbon mobility is crucial to ensuring urban systems are sustainable and tackling important challenges, such as reduction of CO2 emissions, air and noise pollution, and traffic congestion. Identifying effective strategies and design solutions that boost multimodal mobility and effective interchange among different sustainable means of transport can be a significant contribution in this area. This paper presents an easy-to-use methodology to assess the performance of policy measures and design solutions-oriented to foster modal interchange, with special regard to the configuration of the interchange hubs. The methodology is based on identifying key factors necessary to ensure an efficient multimodal interchange and the different types of interchanges that are frequently present in the urban realm. By grouping the key factors into nine different domains, and by weighing the key factors in relation to their importance, the methodology creates a decision support system to assess the performance of the current interchange, as well as of different planning and design scenarios. This methodology has been developed in the framework of the Interreg Europe MATCH-UP project and is conceived to support both designers and decision-makers whenever they have to reorganise existing transport hubs and policies, or design and plan new ones.
Overview of the updated management of inguinal hernia

Inguinal hernias are the most common type of hernias with a worldwide prevalence of 5%, yet limited data on the updated management is available. In this study, an overview of the different classic and updated management ways of the case of inguinal hernia around the world was carried out. This systematic review study was based on PubMed database searches for published articles about the management of inguinal hernias. After applying the inclusion and exclusion criteria, the 32 identified articles were further reduced to 22 articles for full-text assessment, and only 11 articles were included. Many researches on inguinal hernia were of poor quality. However, it was concluded that it is important for general practitioners to diagnose correctly and distinguish between inguinal and femoral hernias to best avoid complications. Eligibility for surgery is not procedure- specific and patient’s quality of life must be considered. The data supported the surgical mesh repair as the best technique in surgical repair of inguinal hernia.
Clinical, Cognitive and Behavioural Assessment in Children with Cerebellar Disorder

Cerebellar disorders are characterised clinically by specific signs and symptoms, often associated with neurodevelopmental disorder. While the clinical signs of cerebellar disorders are clearly recognisable in adults and have a precise anatomo-functional correlation, in children the semiotics are less clear and vary with age because of the particular nature of the cerebellum’s maturation. Unlike other structures of the central nervous system, this begins at a later stage of foetal development and extends over a longer period of time, even after birth. As a result, the typical signs of cerebellar dysfunction will only become evident when the cerebellar functions have become integrated into the complex circuits of the central nervous system. This means that poor motor coordination in the very early years of life may not necessarily correlate with cerebellar dysfunction, and this may also be encountered in healthy children. The cerebellum’s role in cognitive and emotional functions relies on its structure and the complexity of its connections. Cognitive and behavioral impairment in cerebellar disorders can be the results of acquired lesions or the action of genetic and environmental risk factors, to which the cerebellum is particularly vulnerable considering its pattern of development. In the pathological setting, early evidence of cerebellar damage may be very vague, due, partly, to spontaneous compensation phenomena and the vicarious role of the connecting structures (an expression of the brain’s plasticity). Careful clinical assessment will nonetheless enable appropriate instrumental procedures to be arranged. It is common knowledge that the contribution of neuroimaging is crucial for diagnosis of cerebellar conditions, and neurophysiological investigations can also have a significant role. The ultimate goal of clinicians is to combine clinical data and instrumental findings to formulate a precise diagnostic hypothesis, and thus request a specific genetic test in order to confirm their findings, wherever possible.
Impact of consumer innovativeness on really new product adoption

Purpose – This study explores consumer innovativeness as a personality trait and addresses the hedonic, social, cognitive, and functional motivational elements that lie behind consumer innovativeness. It explores the weak relationship between consumer innovativeness and really new product (novel innovation) adoption and challenges the classic relationship between consumer learning, attitude and intention. Design/methodology/approach – This study adopts a quantitative approach, gathering survey data via an institutional online platform. 300 participants were recruited. Participants were directed to a website presenting the information of the product with the inclusion of 2D and 3D images and an avatar. For data analysis, CFA and Structural Equation Modelling (SEM) were used. Findings – Results indicate a positive impact of attitude on comprehension and intention. In addition, hedonic innovativeness positively impacts customer’s attitude, whereas there is a negative relationship between social innovativeness and attitude. Motivational elements of innovation, with the exception of hedonic motivation, positively influence purchase intention. Research limitations/implications – The main limitation of the study lies in the measurement of purchase intention, as actual purchases cannot be assessed as the products are not yet available. The findings encourage marketers to target innovators first, ideally innovators motivated by hedonic needs. Originality/value – This study challenges the classic theories identifying the link between comprehension, attitude and purchase intention within the field of innovation. The findings indicate that while interacting with Really New Products, comprehension does not necessarily lead to attitude and intention, but attitude does positively influence both intention and comprehension.
In-Situ Growth of Few-Layered MoS2 Nanosheets on Highly Porous Carbon Aerogel as Advanced Electrocatalysts for Hydrogen Evolution Reaction

Molybdenum disulfide-based hybrids, acting as cost-effective and acid-stable electrocatalysts for hydrogen evolution reaction (HER), have been developed fast for providing sustainable hydrogen energy in recent years. Herein, few-layered molybdenum disulfide (MoS2) nanosheets/carbon aerogel (CA) hybrids were successfully obtained through the combination of sol–gel process, aging, freeze-drying, high temperature carbonization, and solvothermal reaction. CA with highly continuous porosity and high specific surface area is used as a matrix material for construction of hierarchical MoS2/CA hybrids where few-layered MoS2 nanosheets are uniformly covered on a CA surface. In this heterostructured system, CAs not only provide three-dimensional (3D) conductive pathway for fast transportation of electrons and ions, but also offer highly active regions for the growth of MoS2, greatly preventing the aggregation of MoS2 nanosheets. Due to the rationally designed hybrids with 3D porous nanostructures, the as-prepared Mo.
Building information modelling application of material, water, and climate footprint analysis

ABSTRACT Buildings are considered major drivers of resource use and climate change. This has initiated the development of design tools that could better reflect the environmental performance of buildings. This article describes the extension of building information modelling (BIM) through the development of the sustainable resource application (SURAP) that can be used to determine the material, water, and climate footprints of buildings at the design stage. The Python application programming interface (API) of openLCA software was used with the GaBi construction materials database for the preparation of footprint data. Footprints of construction materials were determined through life cycle assessments (LCA) on a cradle-to-gate basis, and the application was developed as a new tab in the Autodesk Revit software. The Revit API was used for data exchange between the Revit core system and the developed plug-in. The application prototype was tested for the design of a multifamily building. The results show that the developed tool can support building designers in quantifying and visualizing cradle-to-gate material, water, and the climate footprints of buildings within the BIM environment. The promotion of sustainability in the building industry and its current limitations are discussed.
A Survey of Computerization of Selected Community Pharmacies in Southwestern Nigeria

Background: The use of computers has had impact in all professions including pharmacy. Computers have found lots of application in the management of inventories, electronic prescribing and counting machines for tablets and capsules.Objective: This research was designed to identify the types of technology devices and programs in use by community pharmacies, capabilities of software in use, as well as to identify the challenges faced by community pharmacists in the use of computerized systems in their premises.Method: A cross-sectional survey of 217 community pharmacies in 6 Southwestern Nigerian states was done using a set of questionnaires. Data gathered was subjected to statistical analysis using SPSS version 17.Results: Some community pharmacies in Southwestern Nigeria used inventory management software (47.0%). The reported capabilities of the software packages in use included sales processing (99.0%), account processing (88.2%) and POS link (62.7%). The reasons why some community pharmacies have not computerized their outlets were erratic power supply (56.2%), high cost of the devices (48.4%) and low turnover (35.9%). The major challenges faced by community pharmacists in the use of computer devices in their premises included erratic power supply (90.2%) and high cost of fuel (83.3%). Conclusion: The level of computerization of community pharmacies in Southwestern Nigeria was observed to be generally low. Erratic power supply and cost of device were major challenges to the computerization of community pharmacies in Southwestern Nigeria. Keywords: Community Pharmacy, Software, Computerization
Coordinated Optimal Power Flow for Integrated Active Distribution Network and Virtual Power Plants Using Decentralized Algorithm

With the wide application of distributed energy technology in active distribution networks (ADNs), virtual power plants (VPPs) are introduced as a promising integration and management technology. To coordinate their operation schedule and ensure confidentiality, we establish a coordinated optimal power flow (OPF) model and propose an efficient decentralized algorithm based on multi-parametric quadratic programming and Benders decomposition. In feasible sub-problems, the quadratic exchanging functions are built, which greatly accelerates the convergence process. In infeasible sub-problems, feasible cut sets can be calculated based on benders decomposition. Besides, an effective relaxation method is developed to address the degeneracy problem. To eliminate redundant feasible cut sets, a predetermined feasible region is constructed according to the characteristics of each VPP. The effectiveness of the proposed method is demonstrated via numerical tests using two cases of different scales. The results show that the proposed method converges much faster than some prevailing methods. Furthermore, the coordinated OPF has a better fuel economy than the conventional OPF scheme.
Using a Genetic Algorithm to Build a Volume Weighted Average Price Model in a Stock Market

Research on stock market prediction has been actively conducted over time. Pertaining to investment, stock prices and trading volume are important indicators. While extensive research on stocks has focused on predicting stock prices, not much focus has been applied to predicting trading volume. The extensive trading volume by large institutions, such as pension funds, has a great impact on the market liquidity. To reduce the impact on the stock market, it is essential for large institutions to correctly predict the intraday trading volume using the volume weighted average price (VWAP) method. In this study, we predict the intraday trading volume using various methods to properly conduct VWAP trading. With the trading volume data of the Korean stock price index 200 (KOSPI 200) futures index from December 2006 to September 2020, we predicted the trading volume using dynamic time warping (DTW) and a genetic algorithm (GA). The empirical results show that the model using the simple average of the trading volume during the optimal period constructed by GA achieved the best performance. As a result of this study, we expect that large institutions will perform more appropriate VWAP trading in a sustainable manner, leading the stock market to be revitalized by enhanced liquidity. In this sense, the model proposed in this paper would contribute to creating efficient stock markets and help to achieve sustainable economic growth.
A new early warning indicator of abrupt climate change based on the changing normalized dynamic range

An abrupt change will occur when the system is forced to across a critical threshold. This study presents a novel early warning indicator—the changing normalized dynamic range. We use a one‐variable climate model and three simple folding models to test the performance of the new early warning indicator. The results show that the present indicator exhibits a statistically significant increase or decrease in all of tests at a significance level of α = . 05 before a dynamical system with a folding bifurcation approaches a tipping point. Comparing the well‐known autocorrelation coefficient with the normalized dynamic range, it is found that autocorrelation coefficient performs well in most of tests, which shows an almost monotonous increasing or decreasing trend for an upcoming abrupt change. However, autocorrelation coefficient exhibits a diametrically opposite trend for a noise‐induced abrupt change in a two‐dimensional vegetable model. The kurtosis coefficient can perform well in most of the tests used in this study, however, fails to give an early warning in a particular case. Moreover, the magnitude of change of the autocorrelation and kurtosis is much smaller than that of the normalized dynamic range before the four folding models approach its tipping point. Therefore, the performance of the new indicator for warning an abrupt change in advance is better than that of the autocorrelation coefficient as well as kurtosis coefficient, which can make up for the deficiency of the kurtosis coefficient and autocorrelation coefficient to some extent.
Comparison of Secondary Metabolite Contents and Metabolic Profiles of Six Lycoris Species

Quantitative HPLC analysis was performed on six different species of Lycoris herbs to investigate variation in phytochemical content, especially galantamine and phenylpropanoid-derived compounds. The contents of these compounds differed widely among the Lycoris species, with L. radiata and L. chinensis containing the lowest and highest galantamine contents, respectively. Specifically, the galantamine content of L. radiata was 62.5% higher than that of L. chinensis. Following L. radiata, L. sanguinea contained the next highest galantamine content, which was 59.1% higher than that of L. chinensis. Furthermore, a total of 12 phenylpropanoid-derived compounds were found in the different Lycoris species, where L. sanguinea, L. squamigera, and L. uydoensis had the largest accumulation of these compounds. The total phenylpropanoid content of L. sanguinea was the highest, while that of L. radiata was the lowest. Seven of the phenylpropanoid-derived compounds, rutin, quercetin, catechin, epicatechin gallate, chlorogenic acid, benzoic acid, and kaempferol, were dominant. L. sanguinea, L. uydoensis, and L. squamigera showed amounts of these seven compounds that were 5–6 times greater than those of the other species in the study. To the best of our knowledge, our results provide the most detailed phytochemical information on these species to date, which is valuable for future applications using these medicinal plants.
Ensemble Inhomogeneity of Dielectric Functions in Cs-Doped Tungsten Oxide Nanoparticles

Ensembles of Cs-doped tungsten bronze nanoparticles (NPs) derived from breakdown process exhibit near-infrared absorption of localized surface plasmon resonance with highly broadened bandwidth. The dominant cause of this effect, after evaluating conventional factors such as particle size, shape, dipolar interactions, etc., has been identified as the ensemble inhomogeneity of dielectric functions of individual particles. A novel analysis method has been developed that can take into account the inhomogeneity of physical properties over a molar-order number of particles. Various variables to describe dielectric functions are numerically made scattered by randomly generated numbers, and Mie scattering wave, each with scattered variables, is calculated and integrated. The developed method successfully reproduced experimental absorption profiles. The analysis indicates that the dielectric functions are modified with a decrease in both plasma frequency and polaron transition energy and an increase in the band ga.