Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelo de Otimização de Alocação de Recursos em LoRaWAN para Aplicações de Internet das Coisas

LoRaWAN is the most widely used long-range wireless IoT application that works with high density, as LoRaWAN connects devices that require low-cost, long-range communication services. However, LoRaWAN densification poses a number of challenges due to simultaneous transmission interference on the same channel or higher power consumption by the device. In this context, it is crucial to understand LoRaWAN’s resource allocation mechanisms to optimize the configuration of radio specific parameters, i.e., Spreading Factor (SF) and Carrier Frequency (CF), where the optimization of transmission parameters via models Optimization is an open challenge. This paper presents MARCO, a resource allocation optimization model for minimazing LoRaWAN QoS for IoT applications. The MARCO model considers mixed integer linear programming to define optimal SF and CF parameter settings, as well as overall network traffic specifications. Simulation results demonstrate the efficiency in terms of data extraction rate, number of collisions and energy compared to existing LoRaWAN resource allocation models. Resumo. O LoRaWAN é a tecnologia sem fio de longo alcance mais utilizada para aplicações de Internet das Coisas (IoT) que trabalham com alta densidade, pois é capaz de conectar dispositivos que requerem serviços de comunicação de longo alcance, baixo custo e menor consumo de energia. Contudo, a densificação do uso de LoRaWAN em serviços IoT traz uma série de desafios devido a interferência por transmissão simultânea no mesmo canal e/ou maior consumo de energia pelos dispositivos. Nesse contexto, é crucial entender os conceitos de alocação de recursos do LoRaWAN para otimizar a configuração de parâmetros especı́ficos do rádio, i.e., Fator de Espalhamento (SF) e Frequência de portadora (CF), em que a otimização dos parâmetros de transmissão via modelos de otimização é um desafio em aberto. Este artigo apresenta o MARCO, um modelo de otimização de alocação de recursos para minimizar a Qualidade de Serviço (QoS) do LoRaWAN para aplicações de IoT, além de contribuir para a melhora da eficiência enérgica dos dispositivos. O MARCO considera uma programação linear inteira mista para definir as configurações ideais dos parâmetros SF e CF, bem como especificações de trafego da rede como um todo. Resultados de simulação demonstram a eficiência em termos de taxa de extração de dados, número de colisões e consumo de energia do MARCO em comparação com as heurı́sticas de alocação de recursos para LoRaWAN existentes.
Service Migration in Edge Computing Environments for Connected Autonomous Vehicles

In Connected Autonomous Vehicles scenarios or CAV, ubiquitous connectivity will play a major role in the safety of the vehicles and passengers. The extensive amount of sensors in each vehicle will generate huge amounts of data that cannot be processed promptly by onboard units. Edge computing is a crucial solution to provide the required computation power and extremely low latency requirements for the future generation of CAVs. However, the high mobility of vehicles, together with dynamic 5G networking scenarios, poses a challenge to keep the services always close to the users, and therefore, keep the latency very low, such as expected by CAVs. In this paper, we propose MILT, a service migration algorithm for edge computing to perform predictive migration of services based on mobility prediction, available resources, and the quality level of the networks and applications. MILT supports a mobility-based handover prediction scheme to perform a pre-migration to the best available edge server while reducing the latency and increasing the processing capacity of the services of CAVs. Simulation results show the efficiency of the proposed algorithm in terms of latency, migration failures, and network throughput.
Knowledge Conversion: An Evaluation of BPPT KM Application Utilization as A Knowledge Management System

This paper presents how knowledge being converted through a knowledge management application called BPPT KM App that is managed by Pusat Manajemen Informasi – Badan Pengkajian dan Penerapan Teknologi, and its function used as a knowledge management system. The purpose of this paper is to explain the implementation of knowledge conversion in Badan Pengkajian dan Penerapan Teknologi and to know how the knowledge management system works and the effectiveness of the app. The method used in this paper is qualitative with participative observation approach and narrative review. With these approaches, researchers do the direct investigation of the subject research and involved in the process of knowledge conversion of the app. The result of this study shows that knowledge conversion can be implemented by BPPT employees, whether the employees located in MH Thamrin Jakarta or Puspiptek Serpong, and the SECI indicators have been conducted in the knowledge management system through the app. It can be concluded that BPPT KM App has facilitated knowledge conversion implementation to all BPPT employees remotely and it can be accessed anytime and anywhere, especially in this pandemic situation.
Children’s voluntary summer reading in Norway: Insights gained from the gamified library-initiated reading campaign Sommerles.no

Using gamification, the Norwegian library-initiated summer reading program Sommerles.no (lit: Summer reading.no) entices one-fifth of Norway’s primary school students to read for pleasure during their summer vacation. The current paper explores the characteristics of the 105,319 participants of the 2018 edition of Sommerles.no. This analysis demonstrates that the campaign is a success in terms of overall participation and, especially, in terms of the share of boys who participated (43%). However, the participation of children who speak Sami and non-Western European languages at home is under-represented. Children who speak Russian or other Western-European languages than Norwegian at home have the highest registered number of pages read, whereas children from non-Western European language backgrounds read fewer pages. As reading for pleasure during the summer most probably represents the most effective strategy for the groups with weak reading capabilities, the reading campaign has the potential to increase participation by these weak groups further.
Temporal and spatial variations in three-dimensional seismic
oceanography

Abstract. Seismic oceanography is a new cross-discipline between geophysics and oceanography that uses seismic reflection data to image and study the ocean water column. Previous works on seismic oceanography were largely limited to two-dimensional seismic data and methods. We present a complete three-dimensional (3D) oceanic seismic study and explore its imaging capability in seismic oceanography. From a 3D multichannel seismic survey acquired for oil and gas exploration in the Gulf of Mexico over six months period, a 3D water-column seismic volume was derived. The 3D seismic volume exhibits both temporal and spatial variations of the ocean, and theoretical and empirical analyses were performed to discriminate their contribution. Our analyses shows that temporal variation is largely embedded along crossline direction, hence deteriorating the quality of seismic images; however, inline sections, which can be seen as snapshot representation of the water column, allow to capture not only thermohaline structure but also the temporal evolution of the ocean dynamics. Our finding highlights that appropriately processed and analyzed 3D seismic data not only provide superior images of the ocean structure but also can be useful for investigation of temporal evolution of mesoscale ocean dynamics.
TEMPORAL TRENDS OF OVERWEIGHT AND OBESITY AMONG 4–14 YEAR-OLD CHILDREN IN LIECHTENSTEIN. RESULTS OF A MONITORING PROJECT FROM 2004 TO 2018

Monitoring data analysis forms a central basis for the assessment of the prevalence and development of overweight and obesity in children and adolescents, thus identifying a potential need for action and adopting preventive measures. Based on data of 5‘515 children and adolescents aged between 4 and 14, this article presents a current trend analysis for Liechtenstein for in the period between 2004 and 2018. This study is based on cross-sectional data from health screening examinations supervised by the national Office of Public Health. The Body Mass Index (BMI) was calculated from anthropometric measurements and classified with reference to the age and gender-specific cut-off criteria of the International Obesity Task Force (IOTF). Across the examined age groups, 15.6% of all children and adolescents in Liechtenstein are currently considered to be overweight or obese. This is a similiar prevalence as in neighbouring regions and shows a stable development over the 15-year monitoring period.
1. Challenges in Systems Epidemiology in Cancer

Systems epidemiology is a new research discipline that seeks to integrate pathways analyses into observational study designs to improve the understanding of biological processes in human organisms as time-dependent changes or trajectories of functional genomics. This chapter guides the reader on the different aspects of the book. The aim is to improve the understanding of the structures of data from complex study designs, data handling, new statistical methods and the interpretation of the results.
Image Fusion Metrics – A Systematic Study

When two input images with different focus areas are combined in such a way that resultant image is leveraged with all the required and pertinent information to fulfil the purpose of study and research as well as per the observer, then all this process is known as multi-focus image fusion procedure. But how will be able to know that fused image is as per the required standard? To fulfil this objective, having performance metrics in the field of image fusion. To assess the quality of the resultant image, performance metrics are used as an evaluation parameter estimators. After completing fusion process, the resultant fused image is whether as per the requirement or not, whether it possesses all the pertinent information, to make sure there is no loss of information in the final resultant image, the need of fusion performance metrics comes into the picture. In this paper, subjective as well as objective fusion metrics have been studied to have an in-depth understanding of the suitability of the respective performance parameters so that it can be easily concluded that at what stage which metrics will provide the better results.
Analysis and Verification of the Operation of the Stabilizing Robust Controller's Electrical Circuit of the Rotor Flux-Linkage Control System

On the basis of the classical theory of robust control, the theory of stability and the theory of continued fractions, the linearized mathematical model, the procedure for calculating and designing an analog electrical circuit of the H∞-suboptimal robust controller of the flux-linkage control system of the rotor of an asynchronous electric drive, protected by Ukrainian Patent no.137157, were built. The circuit contains three operational amplifiers, several resistors and capacitors. The proposed mathematical model, the procedure for calculating and choosing the parameters of the resistors and capacitors of the circuit take into account the random variations of the object and the controller within the specified boundaries. An analytical relationship between the transfer function coefficients and the resistances of the resistors and the capacitances of the capacitors of the controller's electrical circuit was established. On a specific example, by calculation according to the developed algorithm, the limiting values of the tolerances of the circuit's resistances of the resistors and capacitances of the capacitors were identified and these values were selected with a margin from the standard series. Analysis of noise filtering by the electrical circuit of the controller in the Multisim package shows its insensitivity to noise spreads within fairly wide boundaries.
Evaluation of Linear and Machine Learning Models for Determining Pedotransfer Functions

Modelling of water content and the transport of water in soil has become a useful tool in simulating agricultural productivity or in solving various hydrological analyses. For instance, optimum irrigation management requires a systematic estimation of the soil-moisture to determine both the appropriate amount and timing of irrigation. Soil characteristics appear as an essential input in the numerical simulation of a soil-water regime. A critical physical property used in the description of a soil-water regime in such modelling is a soil water retention curve. This paper aims to evaluate so-called pedotransfer functions, which helps to assess the soil water retention curve easier than by standard complex and lengthy procedure involving both field and laboratory work. As a case study Zahorska Lowland, which is located in central Europe in the western part of Slovakia, was selected. The frequent occurrence of dry years in this area results in the necessity to construct irrigation systems in this area, so modelling water content in the soil is an important task here. This study aims to support such modelling with determining pedotransfer functions. Authors compare linear methods (multiple linear regression, LASSO regularized regression) and CatBoost machine learning model.
Text Classification on Large Scale Chinese News Corpus using Character-level Convolutional Neural Network

In view of the current problems in the field of Chinese news, such as chaotic news data and lack of automatic and efficient management, most of the existing Chinese text classification methods take word characteristics as the basic unit of text representation, but ignore the beneficial performance of character characteristics. In this paper, an automatic classification method of Chinese news based on character-level convolutional neural networks(char-CNN) is proposed. In order to compare with traditional models and deep learning models, we constructed a large scale Chinese news corpus to show that character-level convolutional neural networks could achieve the most advanced or competitive results.
Assessments of Dietary Characteristics, Adherence and Glycemic Control in Individuals with Type 2 Diabetes: A Sampled from a Selected Public Hospital in Malaysia

Introduction: Adherence to dietary recommendations among individuals with type 2 diabetes (T2DM) is critical in achieving optimal glycemic control, yet the status is relatively scarce. This crosssectional study was conducted to describe the dietary characteristics, adherence, and glycemic control among patients with T2DM. Methods: A total of 80 respondents with a confirmed diagnosis of T2DM (Age = 58.8 ± 12.4 years, Diabetes duration= 11.91 ± 9.4 years) were sampled from a selected public hospital in Malaysia. Sociodemographic characteristics, medical profiles, and glycemic control (assessed using HbA1c) were obtained from the medical records. Dietary characteristic was assessed using the Food Frequency Questionnaire, and dietary adherence was determined using the Summary of Diabetes Self-Care Activities (SDSCA) questionnaire. Results: The average HbA1c was 8.9 ± 2.7%, with 81.2% of them not optimal glycemic control. Respondents achieved daily food recommendations for cereal, meat, and legume. However, most of them did not consume sufficient fruits, vegetables, fish, and milk. The overall dietary adherence rates were relatively low, with only 7.5% adhered to dietary recommendations. Followed a healthful eating plan (r = -0.249, p= 0.026) and eat fewer sweets (r= -0.230, p= 0.04) were associated with glycemic control. Conclusion: Poor glycemic control is highly prevalent, with most of the individuals with T2DM did not achieve daily recommendations for the food groups based on the recommended eating patterns for International Journal of Academic Research in Business and Social Sciences Vol. 1 0 , No. 16, Youth and Community Wellbeing: Issues, Challenges and Opportunities for Empowerment V2. 2020, E-ISSN: 2222-6990 © 2020 HRMARS 98 diabetes. Adherence to the dietary recommendation is not optimal and does associate with poor glycemic control suggesting the importance of having continuous diabetes nutrition education in assisting individuals with T2DM to achieve optimal glycemic control.
Phytochemical and Biological Studies on Bark Extract of Aporosa wallichii Hook.f.

The ethyl acetate extract of bark of Aporosa wallichii Hook.f. was extensively investigated for the chemical characterization of secondary metabolites and for biological activities. After repeated chromatographic separation and purification, two compounds were elucidated as a phenolic compound ferulic acid (1) and an uncommon triterpene glut-5(6)-en-3β-ol (2) from the ethyl acetate extract of barks of A. wallichii by using high field NMR analyses. This is the first report of isolation of both compounds from this plant species. No significant antimicrobial activity was observed for any fraction after Kupchan partitioning of the extract. During the antioxidant activity assay, the ethyl acetate soluble fraction of A. wallichii demonstrated significant DPPH radical scavenging capacity with an IC50 value of 1.25 μg/mL. The other fractions viz. petroleum ether, aqueous and chloroform soluble fractions exhibited moderate, mild, and weak activity respectively. The petroleum ether soluble fraction demonstrated maximum thrombolytic property (51.33%) which was similar to that of standard streptokinase (66.81%). Dhaka Univ. J. Pharm. Sci. 19(2): 139-143, 2020 (December)
Evaluation of the Relationship Between Vitamin D Levels and Related Serum Markers as Well as Disease Activity in Patients With Rheumatoid Arthritis: A Cross-sectional Study in Western Iran

Introduction: Many studies have reported the role of vitamin D in rheumatoid arthritis (RA) which is related to several serum autoantibodies such as RF and Anti CCP. It also has been shown that vitamin D deficiency affect the DAS28 and VAS score inversely. Therefore, we aim to assess the relationship between vitamin D deficiency and RA-related autoantibodies including Anti CCP and RF levels and also evaluate the association between these parameters and the severity of disease.Methods: In this cross-sectional study, RA patients over 16 years of age were enrolled. The severity of diseases was assessed via the DAS28 scoring system. Serum levels of 25(OH) vitamin D were determined by the ELISA method, along with other rheumatoid related laboratory evaluations including Anti CCP, RF and CRPResults: A total of 100 patients with a mean age of 45.27± 14.14 were included and evaluated; of them, 75% were female and 77% lived in the city. Most of the patients (66%) had moderate DAS28 levels; however, no substantial relationship was observed between DAS28 and vitamin D levels. A significant positive relation between serum 25(OH)D level and disease duration, as well as the level of education, was observed. There was also no significant correlation between RA-related autoantibodies and inflammatory serum marker with 25(OH)D.Conclusion: Due to vitamin deficiency in the majority of cases (73%) and the relationship between serum 25(OH)D levels and the duration of disease, it can be concluded that vitamin D levels should be checked in those patients.
Prediction of stability constants of Cu2+ complexes with organic fluorescent ligands using thermodynamic cycle in combination with DFT theory and SMD solvent model

Accurately predicting the stability constant (β) of the Cu2+ complex with organic fluorescent ligands provides an important basis to design molecular fluorescent sensors for selective detection of Cu2+. With appropriate reference complexes, the calculated stability constants are in good agreement with experimental values. The logβ values of the predicted stability constants of Cu2+ complexes with Calcein blue (H3Cb) and FluoZin-1 (H2Fz) are 13.33 (exp. 14.27) and 6.59 (exp. 6.01), respectively. More importantly, the results could be applied to the investigation of complexes.
Application of Information and Technology in Supply Chain Management: Case Study of Artificial Intelligence – A Mini Review

It is wide known that the world has been moving towards a digital future over the years, and Industry 4.0 technologies are considered to be the way of the future. One of the most prominent of these technologies (including Block Chain, Internet of Things, Cloud Computing, Big Data, etc.) is Artificial Intelligence (AI), was introduced to develop and create “thinking machines” that are capable of mimicking, learning, and replacing human intelligence. However, its widespread acceptance as a decision-aid tool, AI has seen limited application in supply chain management (SCM). The purpose of this work is to identify the contributions of AI to SCM through a brief review of the existing literature. Besides, this paper reviews the past record of success in AI applications to SCM and identifies the most subfields of SCM in which to apply AI.
Effects of different concentrations of NPK fertilisers on growth and development of wild okra (Corchorus olitorius)

Wild okra (ligusha) [Corchorus olitorius L. ] is an important indigenous vegetable in Swaziland. Although the crop is a popular vegetable among rural communities, not much has been done to produce it using nitrogen, phosphorus and potassium fertilisers. The purpose of this study was to investigate the effects of different concentrations of NPK fertilisers on growth and development of Corchorus olitorius (ligusha). Different concentrations of NPK fertilisers (2.3.2(22), (2.3.2(37) and 2.3. 4(39) were applied in an experiment laid in a Randomized Complete Block Design (RCBD) whereby in the control, no fertilizer was applied. It was noticed that there were significant (P<0.05) increases in all the growth parameters that were measured in the pots where 2.3. 4(39) fertiliser was applied followed in decreasing order by 2.3. 2(37), 2.3. 2(22) and lastly the control. There were also significant (P<0.05) differences of yield fresh mass and dry mass of ligusha. The plants grown in the 2.3. 4(39) applied pots had the highest fresh (142.7 g) and dry yield (31.0 g) mass followed in decreasing order by 2.3. 2(37), 2.3. 2(22) and lastly the control. The least fresh (14.8 g) and dry yield (3.3 g) mass was recorded in plants grown in the control pots. Plants that grew in the 2.3. 4(39) applied fertiliser gave the highest yield of wild okra, under the conditions of this experiment.
In vitro shoot Proliferation from Nodal Explants of Aegiceras corniculatum L. (Blanco.)

Aegiceras corniculatum L. (Blanco.) is a tropical, small evergreen, true mangrove, and woody shrub or tree species, that grow in the intertidal zone, belonging to the Myrsinaceae family, commonly known as river mangrove and Khalsi in Bengali. It is also known as a crypto viviparous species of mangrove and is one of the pioneer mangroves which can thrive in 3% salinity (6) by secreting salt though its leaf glands (3) . Moreover, it is an important honey-producing mangrove species in the Sundarban of West Bengal and International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 11 (2020) Journal homepage: http://www.ijcmas. com