Miracle-dz/UniFAR-FTUs huggingface dataset:
Downlink outage probability analysis of UAV base stations

— Over the previous few years, the use of unmanned aerial vehicles (UAVs) as floating base stations (BSs) has drawn increasing interest. Floating UAV BSs can provide reliable uplink and downlink facilities for ground users, possibly enhancing network ability, eliminating coverage holes in current cellular systems, and addressing the steep rise in communication demands in hotspot fields. Compared to long-term terrain-based BSs deployed at a fixed place, UAVs can quickly alter their roles to provide temporary on-demand service. Unlike terrestrial transmissions, communications to unmanned drones have some benefits, such as line-of-sight (LoS) atmosphere and flexible mobility. Interference will be natural, though. Our UAV communication analysis deals with the effect of interference on UAV communications by considering the probability of LoS and different channel fading for LoS and non-line-of-sight (NLoS) links that are affected by the elevation angle of the communication link. It analyzes the effectiveness of unmanned aerial vehicles (UAVs) acting as wireless base stations providing ground users coverage. The probability of downlink error in ground users is evaluated for variable threshold values, drone altitudes, coverage radii, analysis for all possible main and interference link scenarios and configurations in the presence of an interfering node. Having considered the impacts of transmitting and interfering node parameters on the likelihood of outage, we show the existence of the optimal UAV height minimizing
RECORDS OF PHARMACEUTICAL AND BIOMEDICAL SCIENCES Detection and quantification of active pharmaceutical ingredients as adulterants in Garcinia cambogia slimming preparations using NIR spectroscopy combined with chemometrics

A rapid, simple and efficient method with minimal sample treatment was developed for authentication of Garcinia cambogia fruit peel powder, along with determining undeclared active pharmaceutical ingredients (APIs) in its herbal slimming dietary supplements using near infrared spectroscopy combined with chemometrics. Five featured adulterants, including sibutramine, metformin, orlistat, ephedrine, and theophylline are selected as target compounds. The Near infrared spectral data matrix of authentic Garcinia cambogia fruit peel and specimens degraded by intentional contamination with the five selected APIs was subjected to hierarchical clustering analysis to investigate their bundling figure. SIMCA models were established to ensure the genuiness of Garcinia cambogia fruit peel which resulted in perfect classification of all tested specimens. Adulterated samples were utilized for construction of PLSR models based on different APIs contents at minute levels of fraud practices (LOQ < 0.2% w/w). The suggested approach can be applied to enhance and guarantee the safety and quality of Garcinia fruit peel powder as raw material and in dietary supplements.
Citizen Participation as a Strategic Tool for Enhancing Service Delivery in Urban Local Authorities in Developing Countries: Fantasy or Reality?

The paper examined the role of citizen participation in local authority service delivery in developing countries as these are generally characterised by deteriorating service delivery in the form of poor refuse collection and disposal, potholed road infrastructure and erratic water supply and poor sanitation services. It emerged from the presentation that where local authorities employed active citizen participation, several benefits were enjoyed, including improved service delivery. It was however, observed that despite the multiple benefits arising from citizen participation, local authorities in developing countries generally lack a participative culture. It is thus, critical that local authorities develop and promote citizen participation since it has immense capacity to transform municipal service delivery.
Reliable And Energy Efficient Scheduling Model For Tsch Enabled Mobile Adhoc Network

: the future Industrial Internet of Things (IIOT’s) application is composed of wearable sensor for real-time monitoring human activity. These wearable sensor generate continuous stream of data at much high data rate and are powered by battery. Thus, they are limited to use wireless protocol such as Bluetooth Low Energy and IEEE 802.15. 4. Time-Slotted Channel Hopping (TSCH) Medium Access Control (MAC) is a promising technology for provisioning IIOT’s application that are deployed in environment condition that are prone to interference. This work aims to overcome the issues and challenges in building Reliable and Energy Efficient Scheduling (REES) model for TSCH mobile adhoc network (MANET). The unpredictable nature of wireless link and data source locations makes scheduling challenging. Further, it waste to reserve resources for the worst-case scenario (i.e., high expected data rate). The REES model allows both dedicated slots and shared slots. Along with, allow each communicating device pair to adaptively activate their assigned slots. Thus, aid in increasing overall access fairness, packet delivery rate and reducing the idle listening overhead of unutilized slots. Further, for catering high traffic load a MANET device can dynamically activate additional slots, without the requirement of reorganizing new schedule. Experiment outcome shows REES model minimize energy consumption and maximize data transmission performance.
Fear of Childbirth, Fatigue, and Well-being in Pregnant Women

Materials & Methods: This descriptive cross-sectional study followed by a correlation design was carried out on 525 pregnant women who referred to Sabzevar healthcare in 2017. Based on a cluster sampling method data collection was performed using demographic characteristics form, the Wijma Delivery Expectancy Questionnaire (WDEQ-A), the 5-item World Health Organization Well-Being Index (WHO-5), and the Multidimensional Assessment of Fatigue (MAF) scale. The data were analyzed by SPSS 16, using descriptive statistics, independent t-test, and Pearson correlation coefficient.
A new method for operating a continuous flow diffusion chamber to investigate immersion freezing: assessment and performance study

Glaciation in mixed-phase clouds predominantly occurs through the immersion-freezing mode where icenucleating particles (INPs) immersed within supercooled droplets induce the nucleation of ice. Model representations of this process currently are a large source of uncertainty in simulating cloud radiative properties, so to constrain these estimates, continuous-flow diffusion chamber (CFDC)-style INP devices are commonly used to assess the immersionfreezing efficiencies of INPs. This study explored a new approach to operating such an ice chamber that provides maximum activation of particles without droplet breakthrough and correction factor ambiguity to obtain high-quality INP measurements in a manner that previously had not been demonstrated to be possible. The conditioning section of the chamber was maintained at −20 C and water relative humidity (RHw) conditions of 113 % to maximize the droplet activation, and the droplets were supercooled with an independently temperature-controlled nucleation section at a steady cooling rate (0.5 C min−1) to induce the freezing of droplets and evaporation of unfrozen droplets. The performance of the modified compact ice chamber (MCIC) was evaluated using four INP species: K-feldspar, illite-NX, Argentinian soil dust, and airborne soil dusts from an arable region that had shown ice nucleation over a wide span of supercooled temperatures. Dry-dispersed and size-selected K-feldspar particles were generated in the laboratory. Illite-NX and soil dust particles were sampled during the second phase of the Fifth International Ice Nucleation Workshop (FIN-02) campaign, and airborne soil dust particles were sampled from an ambient aerosol inlet. The measured ice nucleation efficiencies of model aerosols that had a surface active site density (ns) metric were higher but mostly agreed within 1 order of magnitude compared to results reported in the literature.
Steel slag promoted electrocoagulation process for the treatment of produced water

Produced water is a by-product produced from the oil and gas industry. It poses a significant threat to the environment due to its high salinity and high pollutant concentration. In this paper, steel slag was used to enhance the efficiency of the electrocoagulation process for the treatment of produced water. The impact of current density, residence time and quantity of steel slag were studied. Results revealed that the slag particles introduced an adsorption surface for the pollutants to adhere to and produced extra coagulating agents which resulted in higher pollutant removal efficiency. For a residence time and current density of 10 min and 10 mA/cm2, respectively, the steel slag containing system (with slag concentration of 5 g/L) achieved 89.7% removal for total suspended solids compared to 55.7% for the conventional system without steel slag. The total operating cost which is comprised of the electrical energy and electrode material costs was maintained minimal at 0.039 $/m3.
Quantile Non‑parametric Additive Models

Quantile regression allows us to assess different possible impacts of covariates on different quantiles of a response variable. Additive models for quantile functions provide an attractive frame‐ work for non‐parametric regression applications focused on functions of the response instead of its central tendency. Total variation smoothing penalties can be used to control the smoothness of ad‐ ditive components. We write down a general approach to estimation and inference for additive mod‐ els of this type. Quantile regression as a risk measure has been applied in sector portfolio analysis for a data set from the Warsaw Stock Exchange.
Endoscopic Ultrasound–Guided Pancreatic Core Biopsy: A Clinician’s Perspective

Abstract Routine endoscopic ultrasound (EUS)–guided biopsy of the pancreas typically utilizes fine-needle aspiration (FNA) to acquire a sample for cytologic analysis. The development of EUS-guided FNA biopsy techniques, which aims to obtain a histological core of tissue, has many potential benefits compared with EUS-FNA. The goals of this review are to review the need, indications, and techniques for EUS-FNA biopsy and review the current literature as it pertains to pancreatic disease.
Formulation and development of dental gel containing clove oil for the treatment of human periodontal diseases

Periodontal disease is recognized as a major public health problem throughout the world and occurs in all groups, ethnicities, races, genders and socioeconomic levels. It is characterized by inflammation and degeneration of the gums, supporting bone, periodontal ligament and cementum and accumulation of bacterial pathogens, mainly within the periodontal pockets [1]. The periodontal disease commonly refers to inflammatory diseases that are plaque induced i.e. gingivitis and periodontitis. Gingivitis, the moderate stage of disease caused by an accumulation of supragingival plaque and characterized by swelling, light bleeding and redness of the marginal gingival. Gingivitis is associated with a change in the microflora, shifting from a Gram-positive anaerobic flora to a more Gram negative one. Periodontitis, a more severe stage of periodontal disease, results in the resorption of the alveolar bone and detachment of the periodontal ligament supporting tooth [2]. Periodontitis is an inflammatory response to the overgrowth of anaerobic organisms such as Porphyromonas gingivalis, Prevotella intermedia, Fusobacterium nucleatum, Campylobacter rectus, Prevotella melaninogenica and Actinobacillus actinomycetem comitans. The conventional method of treatment the periodontal disease like oral, topical and systemic dosage forms have major disadvantages like superinfection, low or non-compliance, low gingival crevicular fluid levels of antibiotics, systemic side effects, short duration and high relative cost [3]. Periodontal treatment aims to cure inflamed tissue, reduce the number of pathogenic bacteria and eliminate the diseased pockets. Recent advances in the field of dentistry have promoted the use of herbal and natural Journal of Comprehensive Pharmacy
A novel distributed architecture for IoT image processing using low-cost devices and open internet standards

Industry 4.0 can be defined as the integration of computers and automation to current industrial processes, with addition of smart and autonomous systems leveraged by machine learning techniques. In this scenario, a compact, dependable and fast controller is desired, featuring low energy consumption, easily programming and maintenance, with no mobile parts. Nowadays, computing power in single board computers, e.g. the Raspberry Pi among others, has been increased at a very important rate. In just three generations, Pi computers offer almost a two-fold speed gain, when compared to first models. Its design, an underlying video driver with general capabilities of regular OSes, makes them quite suitable to build image processing systems at very low cost, with no mobile parts and low energy consumption. However, designing such a system for industrial image processing is a tough challenge, since it implies to integrate cameras, image processing libraries, database servers and application software with graphical user interface, in an already resource-constrained device. This work presents a new architecture for this kind of systems, by means of open internet standards, using a self-contained, high performance web server to publish a RESTful API and a set of web pages that use latest HTML5 capabilities to manage USB webcams and system data. This proposal also integrates OpenCV as a compiled script on client-side using the new WASM paradigm, with an optimized storage for images using -industry-standard RDBMS and a modular design that can target Windows and Linux as well.
The Environmental Management System Framework of the Industrial Facility: A Case Study in the UAE Aluminium Industry

An Environmental Management System (EMS) manages the environmental aspects of the industrial sector by minimizing, controlling and mitigating the impacts of the industry. The United Arab Emirates (UAE) as a world leader in the aluminium industry has introduced EMS in its aluminium industrial sites to manage the environmental impact of this energy-intensive and environmentally challenging industry. This paper investigates the sustainability and environmental performance of the aluminium manufacturing and production process by analyzing the efficiency of the EMS in controlling the impact of the industrial processes on the environment. By analyzing gaps in implementation of EMS and understanding the strengths and weaknesses of the framework already existing at the case study sites, this study proposes an efficient framework for implementing EMS for the context of aluminium industry in the UAE. The proposed EMS framework is validated qualitatively and quantitatively to ensure its applicability, efficiency and usefulness. The paper recommends linking environmental planning and management outputs for the aluminium industry through a life cycle approach
NON-GRAFTED MAXILLARY SINUS LIFTING TECHNIQUE UTILIZING THERMOPLASTIC BIORESORBABLE SPACE MAINTAINING MESH

Non-grafted maxillary sinus floor elevation which is based on the concept of membrane elevation and support either by tenting technique or space maintaining mesh solved the problem of maxillary sinus pneumatization by creating a space for new bone formation with subsequent implant placement in the edentulous posterior maxilla. The aim of this study is to evaluate the predictability of new bone formation after sinus floor elevation using a bioresorpable mesh. Eight patients with sinus pneumatization were selected for implant placement in the edentulous posterior maxilla. Pneumatized sinuses were approached through lateral window technique and the membrane was elevated and sustained with a bioresorbable mesh. All patients were clinically and radiographically evaluated immediately and at 6 months postoperatively. At six months post-operatively, core bone biopsy was performed for histological examination of the formed bone using a trephine drill at the planned implant position. All patients showed uneventful healing and radiographic, clinical and histological evidence of new bone formation and it was concluded that the bioresorpable mesh was reliable and predictable as a space maintaining device.
Multi-layer Cloud Conditions in Trade Wind Shallow Cumulus – Confronting Models with Airborne Observations

Abstract. Airborne remote sensing observations over the tropical Atlantic Ocean upstream of Barbados are used to characterize trade wind shallow cumulus clouds and to benchmark two cloud-resolving ICON (ICOsahedral Nonhydrostatic) model simulations at kilo- and hectometer scales. The clouds were observed by an airborne nadir pointing backscatter lidar, a cloud radar, and a microwave radiometer in the tropical dry winter season during daytime. For the model benchmark, forward operators convert the model data into the observational space for considering instrument specific cloud detection thresholds. The forward simulations reveal the different detection limits of the lidar and radar observations, i.e., most clouds with cloud liquid water content greater than 10−7 kg/kg are detectable by the lidar, whereas the radar is primarily sensitive to the rain -category hydrometeors in the models and can detect even low amounts of rain. The observations reveal two prominent modes of cumulus cloud top heights separating the clouds into two layers. The lower mode relates to boundary layer convection with tops closely above the lifted condensation level, which is at about 700 m above sea level. The upper mode is driven by shallow moist convection, also contains shallow outflow anvils, and is closely related to the trade inversion at about 2.3 km above sea level. The two cumulus modes are reflected differently by the lidar and the radar observations and under different liquid water path (LWP) conditions. The storm-resolving model (SRM) at kilometer scale reproduces the cloud modes barely and shows the most cloud tops slightly above the observed lower mode. The large-eddy model (LEM) at hectometer scale reproduces better the observed cloudiness distribution with a clear bimodal separation. We hypothesize that slight differences in the autoconversion parametrizations could have caused the different cloud development in the models. Neither model seems to account for in-cloud drizzle particles that do not precipitate down to the surface but generate a stronger radar signal even in scenes with low LWP. Our findings suggest that even if the SRM is a step forward for better cloud representation in climate research, the LEM can better reproduce the observed shallow cumulus convection and should therefore in principle represent cloud radiative effects and water cycle better.
Does Okun’s Law Explain the Relationship between Economic Growth and Unemployment in Nigeria?

Okun (1962) statistically established a negative association between growth and unemployment. This is known as Okun’s Law. This paper investigates, if Okun’s law holds in Nigeria considering the nature of its system of governance, and the study employs an ARDL bounds test approach using data covering the period of 22 years between 1996 and 2017. The results show that unemployment, efforts to reduce corruption and political stability have a negative relationship with growth, although only political stability is significant, whereas, unemployment and corruption are not. The role control of corruption and political stability are contrary to the expected effect which was a positive one. This result is thus contrary to Okun’s law, which states that “1% decrease in unemployment will lead to 2% increase in GDP”, even though the relationship is shown to be negative. Measures and policies to enhance stable and conducive environments were recommended.
Knowledge Management Practices, Challenges and Coping Strategies Adopted by Public Agricultural Extension: A Case of Nandi-Hills Sub-County, Nandi County, Kenya

Aims: Knowledge Management (KM) in agriculture is a core aspect of agricultural productivity and profitability, but is one area with scanty literature. The aim of the current study was to determine the knowledge management practices, challenges and coping strategies adopted by public agricultural extension agents in Nandi-hills Sub-county, Nandi County, Kenya under a fairly new devolved system put in place by the constitution of Kenya in 2010. Study Design: Descriptive cross sectional case study survey design was adopted for the study. Place and Duration of Study: The study was conducted in Nandi-hills Sub-County, Nandi County, Kenya. Data were collected between January and April, 2019. Methodology: All the Extension agents in the Sub-county were targeted. A questionnaire with closed and open ended questions was used to collect data from the 32 participants in the Subcounty and the data was analysed using Statistical Package for Social Sciences (SPSS) version Original Research Article Cheruiyot et al.; AJAEES, 38(2): 1-13, 2020; Article no.AJAEES. 54896 2 20. Descriptive statistics were utilized to document the practises based on their frequencies and associations. 7% of the respondents were certificate holders, 37% were diploma holders while a majority; 56% were degree holders. Associations between attributes was analysed by running Goodman and Kruskals’ gamma. Results: Findings indicated that lack of organized knowledge sharing fora, poor ICT infrastructure, lack of budgetary support and transport were the major challenges facing knowledge management. There was strong negative correlation between education levels with rating of knowledge storage (Gamma = 0.647, p = 0.001) and with access to stored information (Gamma = 0.824, p = 0.001). Conclusion: Diverse methods of knowledge capture and storage were utilized and faced varied challenges mostly attributed to inadequate facilitation to support knowledge capture and storage in modern forms such as ICT. Cooperation and collaboration with private sector players was adopted as a strategy to cope with the challenges.
A Review On Modeling Approaches For Stochastic Unit Commitment

Due to the incorporation of intermittent renewable resource uncertainty level is increasing in power system which in turn affects overall schedules of a generating unit, results in load shedding, expensive generation schedule in unit commitment. Recent challenge is to provide the model uncertainty level with in power system. As the operational reliability depends on the uncertainty level of intermittent sources, the effective modeling gives effective scheduling. Most of the recent work is based on developing a new model for this stochastic unit commitment approach. Many scenarios generation methods and reduction methods have developed in recent years. This paper gives about the survey of various methodologies to model the stochastic nature of unit commitment and various solution methodologies to solve stochastic optimization problems. This literature may pave a new way for both regulated and deregulated market and also provide a good pathway to develop the effective smart grid technology with greater reliability.