Miracle-dz/UniFAR-FTUs huggingface dataset:
Power Allocation in NOMA-CR for 5G Enabled IoT Networks

: In the power domain, non-orthogonal multiple access (NOMA) supports multiple users on the same time-frequency resources, assigns different transmission powers to different users, and differentiates users by user channel gains. Multi-user signals are superimposed and transmitted in the power domain at the transmitting end by actively implementing con-trollable interference information, and multi-user detection algorithms, such as successive interference cancellation (SIC) is performed at the receiving end to demodulate the necessary user signals. In contrast to the orthogonal transmission method, the non-orthogonal method can achieve higher spectrum utilization. However, it will increase the receiver complexity. With the development of microelectronics technology, chip processing capabilities continue to increase, laying the foundation for the practical application of non-orthogonal transmission technology. In NOMA, different users are differentiated by different power levels. Therefore, the power allocation has a considerable impact on the NOMA system performance. To address this issue, the idea of splitting power into two portions, intra-subbands and inter-subbands, is proposed in this study as a useful algorithm. Then, such optimization problems are solved using proportional fair scheduling and water-filling algorithms. Finally, the error propagation was modeled and analyzed for the residual interference. The proposed technique effectively increased the system throughput and performance under various operating settings according to simulation findings. A comparison is performed with existing algorithms for performance evaluation.
Cost-effectiveness of CT perfusion for patients with acute ischemic stroke (CLEOPATRA)-Study protocol for a healthcare evaluation study

Introduction: Computed tomography perfusion (CTP) is variably considered to assess eligibility for endovascular thrombectomy (EVT) in acute ischemic (AIS) stroke patients. Although CTP is recommended for patient selection in later (6–24 h) time window, it is currently not recommended in the earlier (0–6 h) time window and the costs and health effects of including CTP for EVT selection remain unknown. We aim to estimate the costs and health effects of using CTP for EVT selection in AIS patients compared to conventional selection. Patients and methods: CLEOPATRA is a healthcare evaluation study using clinical and imaging data from multiple, prospective EVT trials and registries in both the earlier and later time windows. To study the long-term health and cost effects, we will construct a (“Markov”) health state transition model simulating the clinical outcome over a 5-year follow-up period for CTP-based and conventional selection for EVT. Clinical data acquired within the current study and estimates from the literature will be used as input for probabilities of events, costs, and Quality-Adjusted Life Years (QALYs) per modified Rankin Scale (mRS) subscore. Primary outcome for the cost-effectiveness analysis will be the Incremental Cost-Effectiveness Ratio (ICER) in terms of costs per QALY gained over the simulated follow-up period. Study outcomes: Outcome measures will be reported as cumulative values over a 5-year follow-up period. Discussion: This study will provide preliminary insight into costs and health effects of including CTP in the selection for EVT for AIS patients, presenting between 0 and 24 h after time last known well. The results may be used to develop recommendations and inform further implementation projects and studies.
Trust in and Risk of Technology in Organizational Digitalization

Organizational transformation for digitalization is a daily challenge for organizations. Successful change can be defined as the combined result of a number of factors, in which the attitude, trust and/or distrust of employees towards technology is of paramount importance. The aim of this study was to explore which factors most influence employees’ trust in technology and how the risk they pose can be mitigated. The quantitative research analyzed 473 respondents (Smart PLS3, using SEM model) and came to the following conclusions. Employees’ trust in technology depends primarily on the supportive role of management, and to a lesser extent on the digital readiness of the company and the training provided in the organization. The supportive role of management is a key element in the model, as it affects trust not only in a direct way, but also indirectly, through several pathways in the model. This means that the supportive role of leadership is clearly a decisive influence and its importance helps to assess the risk of trust or lack of trust.
A simulation benchmark for evaluating advanced control strategies in wastewater treatment plants

To enhance development and acceptance of new control strategies in wastewater treatment plants, modeling and computer simulation are. key tools. In this paper, a simulation benchmark of a biological wastewater treatment plant has been developed in order to evaluate different control strategies through simulation. The benchmark based on the COST 624 is a platform-independent simulation environment defining a plant layout, a simulation model, influent loads, test protocols and evaluation criteria. And to enhance practicability of the benchmark, a data based approach to benchmark any specific full-scale wastewater treatment plants has been introduced. Finally, an example of control applications in the benchmark is implemented using conventional PI control and generic model control for dissolved oxygen concentration. Simulation studies are provided to validate the effectiveness of the presented approach.
Patterns of Online Information Seeking and Avoidance about SARS-CoV-2 and COVID-19

Based on the uncertainty management theory considering different information-based coping strategies that are relevant during health crises, the purpose of the present study is to understand how individuals seek and avoid information during the COVID-19 pandemic. We focus on online information seeking and avoidance because of the high share of people searching for information about the pandemic online and the questionable quality of information about the virus available online. Data for this qualitative exploratory study were collected in semi-structured interviews with 21 participants. Our findings revealed four information-seeking patterns that can be located on a continuum between more active, targeted, and less purposeful acquisitions of information, and three avoidance patterns that are distinguished by different motives to avoid certain information. The findings on specific factors involved in individuals’ choices between seeking and avoiding information will help to design better information environments and to identify barriers to the adequate use of information during such crises.
Impact of Wearing on Filtration Performance of Electrostatic Filter Face Masks

Certified disposable respirators afford important protection from hazardous aerosols but lose performance as they are worn. This study examines the effect of wear time on filtration efficiency. Disposable respirators were worn by CSIRO staff over a period of 4 weeks in early 2020. Participants wore the respirator masks for given times up to eight hours whilst working in laboratory/office environments. At that time COVID-19 precautions required staff to wear surgical (or other) masks and increase use of hand sanitizer from dispenser stations. Results obtained from a test group of ten individuals without health preconditions show an increasing number of masks failing with wear time, while the remainder continue to perform nearly unaffected for up to 8 h. Some masks were found to retain filtration performance better than others, possibly due to the type of challenge they were subjected to by the wearer. However, the rate and extent of decay are expected to differ between environments since there are many contributing factors and properties of the aerosol challenge cannot be controlled in a live trial. Penetration and variability increased during wear; the longer the wear time, the more deleterious to particle removal, particularly after approximately 2 h of wear. This behavior is captured in a descriptive statistical model based on results from a trial with this test group. The effectiveness of the masks in preventing the penetration of KCl particles was determined before and after wearing, with the analysis focusing on the most penetrating particles in a size range of 0.3–0.5 µm diameter where respirator masks are most vulnerable. The basic elements of the study, including the approach to filter testing and sample sanitization, are broadly applicable. Conclusions also have applicability to typical commercially available single-use respirator masks manufactured from melt blown polypropylene as they are reliant on the same physical principles for particle capture and electrostatic enhancement was comparable for the particle size range used for detection.
SELEKSI PENERIMA BANTUAN SOSIAL MENGGUNAKAN METODE FUZZY AHP

The high level of poverty in Indonesia encourages the government and social institutions to seek to provide social assistance to the community in improving welfare, especially during the COVID-19 pandemic, in the form of basic necessities, cash, and other forms of subsidies. However, sometimes the distribution of social assistance is not well-targeted so that some people should receive the assistance but are not touched at all. Then the data obtained are also still manual so it takes time in making decisions. Therefore we need a method that can assist in making decisions quickly with the help of computers. One of the methods used in making these decisions is the Fuzzy Analytic Hierarchy Process (FAHP) which is widely used for solving decision-making problems with many criteria. Fuzzy AHP itself is a combination of the analytic hierarchy process (AHP) method and fuzzy theory. In this study, several criteria were determined in the selection of recipients of social assistance, namely employment, expenditure, clothing, food, and housing. Furthermore, the alternative recipients of social assistance that will be selected are compared based on predetermined criteria. The highest value which is the result of Fuzzy AHP calculations can be used as a recommendation for decision-makers in selecting social assistance recipients. Keywords: fuzzy, ahp, decision support system.
Lock-In Effects on the Energy Sector: Evidence from Hydrogen Patenting Activities

The aim of the paper is to analyze how regulatory design and its framework’s topics, other than macroeconomic factors, might impact green innovation by taking into consideration a brand-new renewable source of energy that is becoming more and more important in recent years: hydrogen and fuel cell patenting activities. Such activities have been used as a proxy for green technological change in a panel data of 52 countries over a 6-year period. A series of sectorial, energy regulation, and macroeconomic variables were tested to assess their impact on that technological frontier of green energy transition policy. As might have been expected, the empirical analysis carried out with the model that was prefigured confirms significant evidence of lock-in effects on fossil fuel policies. The model confirms, however, another evidence: countries already investing in renewables might be willing to invest in hydrogen projects. A sort of reinforcement to the further development of green sustainable strategies seems to derive from having already concretely undertaken this direction. Future research should exploit different approaches to the research question and address the econometric criticalities mentioned in the paper, along with exploiting results of the paper with further investigations.
Flow rule‐based routing protocol management system in software‐defined IoT sensor network for IoT applications

In this article, a software‐defined (SDN)‐based Internet of things (IoT) sensor network (S‐ISN) architecture is proposed to fulfill the IoT applications in real time. The proposed system's architecture contains three planes, namely, data plane, control plane, and application plane, to enrich SDN in IoT applications. An IoT application‐based SDN controller is designed exclusively with two management rules—IoT application device management and IoT application‐based topology management. IoT application device management engages in controlling the functions of physical devices that lie on the data plane—path formation of the sensor (proactive, reactive, and hybrid) and reporting scheme management (query, time, and event) of the IoT sensor node. Likewise, IoT application topology management facilitates controlling network topology‐related issues using network structure management (data, location, group, and hierarchical) and next‐hop selection management (broadcast, location, and probabilistic) of the IoT sensor network. The above said management policies are achieved in real time to meet the applications of IoT. Hence, this S‐ISN scheme focuses on IoT application‐related issues with great flexibility in real time. Experimental results show that the network metrics have been improved by the proposed approach as compared with existing methods.
Separating Scholte Wave and Body Wave in OBN Data Using Wave-Equation Migration

The ocean bottom nodes (OBNs) acquire seismic data at a challenging depth to explore the subsurface structures. The recorded body wave and Scholte wave are highly mixed and are difficult to be separated. The strong body wave would influence the high-order modes extraction using the Scholte wave, while the Scholte wave would degrade the imaging of sedimentary structures using body wave. The lacking of effective methods for separating both waves prevents their application. We developed a migration-based method to accurately separate the Scholte wave and body wave in the OBN data. First, we use high-pass filtering to divide the original OBN data into three parts: background noise, high-frequency body wave, and the mixture of Scholte wave and low-frequency body wave. Then, we separate the Scholte wave and low-frequency body wave using migration and demigration based on the fact that they have different limits of reversible-migration velocity. Finally, we generate the separated body wave by subtracting the Scholte wave from the denoised OBN data. For the off-line data, the local orthogonalization method is required to retrieve the weak leakage of Scholte wave around the apices. Theoretical analyses and numerical experiments show that the proposed method can accurately separate Scholte wave and body wave without any visible artifacts while retaining most of their inherent properties. The separated body wave provides a high-quality input for imaging sedimentary structures, and the separated Scholte wave enables the extraction of high-order modes of dispersion curve that are crucial for high-resolution surface-wave inversion.
Characterization of the complete chloroplast genome sequence of Potentilla gageodoensis (rosaceae), endemic to the continental islands of Korea

Abstract This study reports the complete chloroplast genome sequence of a continental island endemic, Potentilla gageodoensis. The total plastome size was 156,397 bp, comprising one large single-copy (LSC; 85,768 bp), one small single-copy (SSC; 18,589 bp), and two inverted repeat (IR) regions (IRa and IRb, each with 26,020 bp). The overall GC content was 36.92%, and the plastome contained 131 genes, comprising 84 protein-coding genes with two pseudogenes (infA and ycf1), 37 transfer RNA genes, and eight ribosomal RNA genes. Phylogenetic analysis performed using 27 representative Rosoideae plastomes suggests that the genus Potentilla is not monophyletic and that P. gageodoensis is sister to the clade containing four taxa of Potentilla (P. freyniana, P. freyniana var. chejuensis, P. stolonifera, and P. stolonifera var. quelpaertensis). The present study reveals the taxonomic distinction of P. gageodoensis from its congeneric species in Korea and the plastome sequence obtained from this study can be used to study phylogenetic relationships and taxonomic status.
Ultra-compact post-compressor on-shot wavefront measurement for beam correction at PHELIX

Abstract In order to reach the highest intensities, modern laser systems use adaptive optics to control their beam quality. Ideally, the focal spot is optimized after the compression stage of the system in order to avoid spatio-temporal couplings. This also requires a wavefront sensor after the compressor, which should be able to measure the wavefront on-shot. At PHELIX, we have developed an ultra-compact post-compressor beam diagnostic due to strict space constraints, measuring the wavefront over the full aperture of 28 cm. This system features all-reflective imaging beam transport and a high dynamic range in order to measure the wavefront in alignment mode as well as on shot.
Do They Always Have Wounded Selves: Moderating Impact of Job-worth on Burnout and Self-worth of Indian Call Centre Employees

Numerous researches in call centres indicate the negative psychological impact in the form of burnout experiences of the customer service representatives. The present study argues that burnout experiences do not always have a negative impact on the employee’s self-worth. The relationship is, instead, moderated by the impact of job-worth, which acts as a potential individual resource. The results of the present study conducted on 312 call centre representatives partially confirm our hypotheses. Results indicate that representatives who have high job-worth maintain their self-worth, even when emotionally exhausted. The results also show that employees possessing high job-worth, even with low personal accomplishments on their jobs, maintain their self-worth. We discuss the findings in the Indian call centre context from the perspective of self and identity literature and provide broader implications for practice and research.
A Test Bench to Study Bioinspired Control for Robot Walking

Test bench to study robot walking within the predicted structures of biological control systems is discussed. Physical system is briefly presented with components. Kinematic model and evolutionary way of gait generation for the leg structure in test bench is discussed. Different forms of gaits can be found by genetic optimization using patterns formed by central pattern generators.
The Influence of China’s Local Fiscal Revenue Targets on House Price Growth

ABSTRACT China’s administrative system practices a unique phenomenon of setting fiscal revenue targets that are often regarded as political tasks by local government officials. As land is the core resource of local government, land finance becomes the best strategy for local governments facing high fiscal revenue targets. With rising land value, house prices will continue to rise. Thus, the fiscal revenue target is an important political factor affecting house price growth, but the existing literature does not attend to this point. This article uses panel data on 35 large and medium-sized cities in China from 2011 to 2016 to study the influence of local fiscal revenue targets on house prices and its underlying mechanism. The results show that these targets are an important political factor in driving up house prices, and the intervening mechanism is local land finance. As gross domestic product per capita increases, the influence of fiscal revenue targets on house prices declines. Conversely, in areas where housing purchases are restricted and house prices are controlled, the influence of fiscal revenue targets on the fiscal burden for the public increases.
Antimalarial activity of Virgin Coconut Oil against Plasmodium berghei ANKA in mice

Malaria remains a health problem in various parts of the world. A decrease in antioxidant levels during malaria infection cause oxidative stress, therefore exogenous antioxidant is needed. Virgin Coconut Oil (VCO) can be a source of exogenous antioxidants due to the antioxidant activity of VCO, which was contributed majority by phenolic acids content. Antioxidants play a role in countering the effects of free radicals by inhibiting fat peroxidation that cause erythrocyte cell wall stronger and not easily ruptured. Pharmacological properties of VCO including anti-inflammatory, anti-oxidant, antiviral, and antiprotozoal properties have been reported. Therefore, this study aimed to find out the antimalarial activity of VCO by evaluating the parasitemia and percentage of inhibition to the growth of parasite. Thirty male BALB/c mice were infected intraperitonially with 1×106 Plasmodium berghei ANKA-infected erythrocytes. The mice were than randomly divided into five groups: positive control (PC) group was given 187.2m g/kg BW of dihydroartemisinin phosphate, negative control (NC) group was only given sterile water; G1, G2, and G3 groups were given 1 ml, 5 ml, and 10 ml/kg BW of VCO, respectively. VCO treatments were given for 4 consecutive days started from 24 hours post infection. Parasitemia was determined daily on Giemsa-stained tail blood smear, further the percentage inhibition was calculated. The results showed that parasitemia in VCO-treated mice were lower than that of NC group, but higher than that of PC group, indicated the antimalarial activity of VCO. The inhibition of VCO to the growth of parasite showed that G2 was higher (48.70%) than that of G1 (13.04%) and G3 (33.9%). The use of antioxidant therapy as a supportive therapy is one of alternatives in supporting the healing process of malaria patients and may reduce various risks that could potentially occur in patients.
Analisis Kehandalan Ekstraksi Garis Tepi Bangunan dari Data Foto Udara Menggunakan Pendekatan Deep Learning Berbasis Mask R-CNN

: The need of large-scale base map, especially in 1:5,000, is increasing in Indonesia. Furthermore, as the Government of Indonesia has declared 1:5,000 RBI mapping acceleration as one of main priorities of One Map Policy implementation, the need of large-scale topographic map production is also rising. Generally, topographic map feature extraction, including building extraction, is conducted through digitization or manually through feature stereoplotting either from satellite imagery or aerial photography. However, this method is usually time-consuming especially for high building density area mapping. Detection and extraction of building footprint automatically using computer vision of optical imagery have been favoured in recent years due to the time effective process. One of the technologies that have been developed is deep learning approach. However, the building line resulted from deep learning has disadvantage, i.e., irregular building footprint. This study attempts to assess the accuracy of polygon regularization resulted from automatically extracted building footprint using Mask Region-base Convolutional Neural Networks (Mask R-CNN) from aerial photography. The study finds that in high building density area with regular roof shape (AoI 1), the intersection over union (IoU) index is 87.8%. Whereas in high building density area with irregular roof shape (AoI 2) has the IoU index of 82.6%. This study also assesses the positional accuracy of 25 building corner point samples and resulting CE90 of 1.183 m and 1.303 m in AoI 1 and AoI 2 respectively. The geometric horizontal accuracy is classified as the class 1 in accordance with 1:5,000 RBI map accuracy standard. Therefore, this study concludes that geometrically, the building line resulted from the regularization is appropriate as feature in 1:5,000 RBI.