Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship of Type D Personality to Herbal Product Use and Asthma Control in Asthma Patients

Amac: Bu tanimlayici calismanin amaci, astim hastalarinda D tipi kisiligin Bitkisel Urun (HP) kullanimi ve astim kontrolu ile iliskisini belirlemektir. Yontem: Arastirmanin evrenini 11/01/2019-11/03/2019 tarihleri arasinda bir universite hastanesi gogus hastaliklari poliklinigine basvuran astim hastaligi tanisi almis tum hastalar (n=408) orneklemini ise belirtilen tarihlerde bu poliklinige basvuran, 18 yas ustu, iletisim sorunu ve herhangi bir psikiyatrik bozukluk tanisi olmamis, calismaya katilmayi kabul eden (n=216) hastalar olusturmustur. Arastirma verileri hastalarin sosyodemografik ve HP kullanim ozelliklerini sorgulayan 17 maddeden olusan anket formu, D-14 Kisilik Tipi Olcegi (DS-14) ve Astim Kontrol Testi ile toplanmistir. Bulgular: Astim hastalarinin %74,1’i son bir yildir HP kullanmaktadir ve hastalarin yaklasik yarisi (%58,3) D tipi kisilige sahiptir. Gelir duzeyi yuksek olanlar (p=0,000), ek bir kronik hastaligi olanlar (p=0,001), D tipi kisilige sahip olanlar (p=0,000) ve hastaligi kontrol altina alinamayanlar (p=0,000) daha fazla HP kullanmaktadir. Ek bir kronik hastalik varligi ve D tipi kisilige sahip olma durumu HP kullaniminda %0,063 belirleyicidir. (R2=0,063, p=0,000) D tipi kisilige sahip olan hastalarin ev hanimi olduklari, sigara ictikleri, 2-3 inhaler kullandiklari ve astim kontrolunun kotu oldugu bulunmustur (p<0,05). Sonuc: Astim hastalarinin cogunlugu (%74,1) bitkisel urun kullanmakta olup, yaklasik yarisi (%58,3) D tipi kisilige sahiptir. Bitkisel urun kullananlarin ve D tipi kisilige sahip olanlarin astim kontrolu iyi degildir.
STUDI DESKRIPTIF INOVASI E-RETRIBUSI PASAR

The Salatiga City Government has launched an electronic market levy (market e-retribution) which is implemented by the Salatiga City Trade Office. Market e-retribution is an electronic market retribution management system innovation to improve the quality of services that are transparent and accountable, minimize revenue leakage and illegal levies, as well as orderly irregularities in market retribution for compulsory levies. Market e-retribution is included in the regional non-cash transaction implementation agenda in the City of Salatiga. The application of new market e-retribution innovations was carried out in two traditional markets, namely Blauran I Market and Pasar Raya I as a pilot project before being implemented in other traditional markets. This article is a qualitative research with a descriptive approach. This article will focus on discussing the innovation of market e-retribution in the City of Salatiga.
Information hiding algorithm based on edge detection and holographic watermarking

In order to improve the robustness of the image watermarking and reduce the influence of the overall image quality of the carrier when watermark is embedded on the carrier, an edge detection method combined with holographic watermarking was proposed to realize the hiding of watermark information. The carrier image is processed by edge detection, the watermark embedding area is segmented in the carrier image, and the suitable embedding area is filtered according to the size of the watermark; the original watermark is processed by a four-step phase shift algorithm to generate a holographic watermark, and the holographic watermark is embedded in the selection The embedding area is completed to embed the watermark, and the carrier image which the watermark is embedded in is carrier image with watermark. The watermark extraction method is to perform the same edge detection segmentation and region screening on the watermark carrier image, find the embedded area of the watermark, extract the holographic watermark, perform holographic inverse transformation to obtain the original watermark image, and complete the watermark recovery. The algorithm which is based on edge detection and holographic watermarking reduces the influence of embedded watermark on the carrier image, increases the flexibility and concealment of embedded position, and improves the robustness of the image when it is under geometric attacks.
Overdense plasma generation in a compact ion source

Electron cyclotron resonance ion sources (ECRIS) are widely used plasma based machines for the production of intense ion beams in science and industry. The performance of modern devices is limited by the presence of the density cut-off, above which electromagnetic (EM) waves sustaining the plasma are reflected. We hereby discuss the systematic data analysis of electrostatic wave generation in an ECR prototype operating at 3.75 GHz–0.1 THz. In particular, electron Bernstein waves (EBW) have been excited. EBW have already been generated in large-scale plasma devices for thermonuclear fusion purposes. In ion sources where Lc ∼ λRF (Lc being the plasma chamber size and λRF the pumping wave wavelength) the EM field assumes a modal behaviour; thus both plasma and EM field self-organize so that no optical-like wave launching is possible (i.e. the cavity effect dominates on the optical path). The collected data, however, supported by 3D full-wave simulations, actually demonstrate that a Budden-type X-B conversion scenario can be established above some critical RF power thresholds, operating in an off-ECR regime. The generation and absorption of the EBW has been demonstrated by the presence of three peculiar signatures: along with the establishment of an overdense plasma, generation of supra-thermal electrons and modification (non-linear broadening) of the EM spectrum measured within the plasma have been observed. At the threshold establishing such a heating regime, the collected data provide evidence for a fast rotation of the electron fluid.
Comparison effects of titanium dioxide nanoparticles on immune cells in adaptive and innate immune system

Titanium dioxide nanoparticles (TiO2-NPs) have been increasingly mixed in food and daily use products. Therefore, the investigation of cytotoxic effects of TiO2-NPs is required to allay concerns of health effects related to contact with products containing TiO2-NPs. In this study, the authors demonstrated how TiO2-NPs impact on two main sub-types of immune cells that play a major role in adaptive and innate immune system. Human T-lymphocytes (Jurkat cells) and murine macrophages (RAW 264.7 cells) were used in this study. The authors results showed that cell viability of Jurkat and RAW 264.7 cells were significantly decreased, when cells were treated with TiO2-NPs at 250 and 500 µg/ml. However, the decrease of cell viability of RAW 264.7 cells was higher than that of Jurkat cells. A similar trend was also found in DNA fragmentation. An induction of reactive oxygen species was detected in both cells treated with TiO2-NPs at concentrations ≥25 µg/ml. A significant induction of tumour necrosis factor alpha (TNF-α) was found in Jurkat and RAW 264.7 cells treated with 25 µg/ml TiO2-NPs. In contrast, there was no significant induction of interleukin-6 (IL-6) in both cells that were treated with different concentrations of TiO2-NPs.
Stator and rotor turn‐to‐turn fault detection in wound rotor induction machines based on the air‐gap magnetic field distortion

: An efficient online flux-based diagnostic approach is proposed to detect turn-to-turn faults in the stator and rotor windings of wound rotor induction machines, at an early stage of development, which can be applied in the online mode. Some flux sensors are installed in the stator slots to detect the rotational magnetic field at various positions along the air-gap circumference. These sensors measure the flux linked to all winding coil groups, in the three phases. Any fault occurring either in the stator or rotor windings will disturb the air-gap flux and create an asymmetry in the rotational magnetic field, which is detectable through the difference of the induced voltages in the corresponding flux sensors. The proposed diagnostic technique is evaluated by finite element analysis as well as by multiple experimental tests. The obtained results show that such invasive technique is able to detect and discriminate various faults in the stator and rotor windings with high accuracy, low calculation burden, proper sensitivity and appropriate robustness in the face of machine load level variations.
Free convection flow of a magneto‐micropolarnanofluid over an orthogonal plate in a saturated porous medium

This study presents a similar solution for a free convective flow of a micropolar nanofluid through an orthogonal plate in a saturated porous medium under the impact of magnetic field. The internal heating generation and without internal heating generation in the problem are explained. A set of nonlinear differential equations was converted into ordinary differential equations by appropriate conversions. This system of equations was numerically solved using bvp4c function in Matlab. Numerical results for the angular velocity, velocity, temperature, Nusselt number, and skin friction are discussed. Calculations were done by parametrizing volume fraction parameter, micropolar, magnetic field, Darcy number, and the Prandtl number. Finally, this study intends to develop an intuitive understanding of similar models by emphasizing the physical arguments, which may be applicable for coating materials in chemical engineering, for instance, robust paints, production of aerosol deposition, and water‐soluble solution thermal treatment.
THERMO-ACOUSTIC CHARACTERIZATION OF A HEAT EX- CHANGER IN CROSS FLOW USING COMPRESSIBLE AND WEAKLY COMPRESSIBLE NUMERICAL SIMULATION

In the present work, a heat exchanger as used for hot water supply in domestic boilers is investigated numerically. The objective of the study is to identify the frequency response of the heat transfer rate with respect to perturbations of flow velocity, and the acoustic scattering matrix of the heat exchanger. These response functions are determined by CFD simulation of flow with heat transfer combined with system identification. Unsteadiness is imposed on the simulations by broad-band excitation of the variables at the boundaries. The resulting time series are postprocessed to obtain the frequency responses. Particular emphasis is placed on the comparability between compressible and weakly compressible simulations in terms of heat release response. The response functions may be used subsequently in thermo-acoustic stability analysis of combustion systems.
Antibacterial Activity of Eight Medicinal Plants against Multidrug Resistant Escherichia coli and Salmonella spp. isolated from Broiler Meat

The excess use of antimicrobial agents in the poultry industry is a significant reason for the gradual spread and increasing level of multidrug resistance bacteria. This article is based on a study in which the antibacterial activity of aqueous, methanolic, ethanolic and acetonic extracts of eight medicinal plants were evaluated by standard disc diffusion method against multidrug resistant Escherichia coli and Salmonella spp. isolated from broiler meat. The multidrug resistance was checked by commercially available antibiotics using standard disc diffusion method. The results have indicated that the ethanolic extract of Boerhaavia diffusa showed maximum zone of inhibition against Escherichia coli, while Asparagus racemosus showed maximum zone of inhibition against Salmonella spp. Other experimental plant extracts had showed moderate activity against these multidrug-resistant bacteria, which can also be considered as potential source of active beneficial phytochemicals. Proper management and application of these plant extracts may be a wonderful alternative of commercially available antibiotic to minimize the risk.
Deep Neural Networks Capabilities for Semantic Segmentation of Noisy Aerial Images

Semantic segmentation is one of the important ways of extracting information about objects in images. State of the art neural network algorithms allow to perform highly accurate semantic segmentation of images, including aerial photos. However, in most of the works authors use high-quality low-noise images. In this work, we study the ability of neural networks to correctly segment images with intensive uncorrelated Gaussian noise. The study brings us three main conclusions. Firstly, it demonstrates that neural network algorithms are capable of working with extreme image distortions without using additional filtration or image recovery techniques. Secondly, the experiments quantitatively show that distortion intensity can be negated with increased training set size. Such process is similar to model’s quality improvement and generalization due to training dataset enlargement. Finally, we quantitatively demonstrate how image aggregation techniques affect training with noised data.
The Effects of Temporal Shut Down: A Proposed Mitigation on COVID-19 Perspectives

Notwithstanding various media reports on casualties in systems due to the emergence of COVID-19, it is envisaged to have a solution. By far, this study investigates how countries’ bilateral trade relationship is distorted due to COVID-19. More so, it examines the economic and financial divergence in systems from the capital perspectives. Finally, it considers the changes in various industries that are affected directly as a result of the COVID-19 outbreak and its distortion in the business model. Employing a case study approach, we conclude that there is a distortion in the supply chain system which has effects on trade relationships. While significant capital deploying strategies were found as mitigation during the pandemics, there is an indecisive business model for the future with inordinate changes in business models during the periods of COVID-19. There is also a risk exposure in both economic decisions and business models due to the uncertain signals of COVID-19. We discuss our findings within the theoretical framework of capital allocation, information/signaling, and adoption perspectives.
Multilevel Item Response Model with Heterogeneous Within-Cluster Variances

Abstract Within-cluster variance homogeneity is one of the key assumptions of multilevel models; however, assuming a constant (i.e. equal) within-cluster variance may not be realistic. Moreover, existent within-cluster variance heterogeneity should be regarded as a source of additional information rather than a violation of a model assumption. This study extends the three-level Rasch item response model to estimate cluster-specific variances as random effects adopting the Bayesian approach. Data analysis results provided empirical evidence for the possible violations of the within-cluster variance heterogeneity, as well as the utility of the proposed heterogeneous model. A small-scale simulation study conducted to provide information about the estimation efficiency of the model parameters with varying degrees of within-cluster variance heterogeneity.
Design and analysis of efficient neural intrusion detection for wireless sensor networks

Wireless sensor networks (WSNs) are important building blocks of the communication infrastructure in smart cities, intelligent transportation systems, Industry, Energy, and Agriculture 4.0, the Internet of Things, and other areas quickly adopting the concepts of fog and edge computing. Their cybernetic security is a major issue and efficient methods to improve their safety and reliability are required. Intrusion detection systems (IDSs) are complex systems that discover cybernetic attacks, detect malicious network traffic, and, in general, protect computer systems. Artificial neural networks are used by a variety of advanced intrusion detection systems with outstanding results. Their successful use in the specific conditions of WSNs requires efficient learning, adaptation, and inference. In this work, the acceleration of a neural intrusion detection model, developed specifically for wireless sensor networks, is proposed and studied, especially from the learning and classification accuracy and energy consumption points of view.
Feed-in Tariff Optimization of Nuclear Power under the Electricity System Reform Based on Price Linkage Policy

Given in the phase of development and the cost element, Chinese nuclear power is not qualified temporarily for full participation in the market competition. The feed-in tariff (FIT) policies of nuclear power plants and portion of electricity in the market competition are the principal external factors determining. As the market reform deepens, the implementation of nuclear power FIT policies which have been carried out for 7-years tremendously differs from the expectation. And the policies of benchmark FIT for coal-fired plants have been changed to a market-based pricing mechanism of "base price + floating price". Based on the analysis of the pricing mechanism for nuclear power benchmark FIT and its implementation, this paper puts forward the overall idea of the regulation mechanism for electricity price. Besides, the paper discusses respective electricity price mechanisms for both guaranteed acquisition electricity and electricity for bidding. It describes a mechanism for construction investment and nuclear fuel price to be linked with FIT of nuclear power unit in detail. And it is suggested that the benchmark electricity price of nuclear power is no longer linked with that of coal-fired plants. This paper provides two methods to ensure the proportion of guaranteed acquisition electricity for performers’ reference and suggests to establish a mechanism for construction investment and nuclear fuel price to be linked with FIT. The analysis results of this paper will provide a theoretical basis for perfecting the pricing mechanism for FIT of nuclear power.
Validation of a Food Frequency Questionnaire (FFQ) for Assessing Dietary Lignans Intake in Hong Kong Chinese Women with Early-Stage Breast Cancer

Background Lignans intake has been suggested to have effects on breast cancer outcomes based on some studies from the West. However, the relationship of lignans consumption and breast cancer outcomes in Chinese population has not been investigated. The development of a culture-specific lignan food frequency questionnaire (LFFQ) is necessary in order to assess dietary lignans intake among Chinese breast cancer patients. This study was designed to validate a newly developed LFFQ to specially assess lignans intake among Chinese subjects. Methods The original study cohort consisted of 1,462 patients with early-stage breast cancer. 133 of these patients were recruited from the original study cohort; 103 of them completed all the assessments from 2015 to 2017 and were included in the present analysis. Two face-to-face interviews were conducted one year apart using a newly developed LFFQ (LFFQ1, LFFQ2). Twelve monthly 24-hour dietary recalls (24-h DRs) were conducted through telephone interview during the same 1-year period. Total lignans intake derived from the LFFQs and 24-h DRs, correlation coefficients and cross classification between the two LFFQs and between LFFQ and 24-h DR were examined. Results Median (IQR) intakes of total lignans for LFFQ1, LFFQ2 and 24-h DRs were 1.66 (1.17–2.15), 1.38 (1.01–2.01), and 0.97 (0.70–1.31) mg/day, respectively. The energy-adjusted validity between LFFQ2 and 24-h DRs was 0.67 (P < 0.001) for log-transformed lignans intake. The reproducibility between lignans intake assessed by the two LFFQs was 0.43 (P < 0.001) for energy-adjusted lignans intake after log transformation. Bland-Altman analysis showed an acceptable agreement between methods (LFFQ and 24-h DR). Correct classification of participants into the same quartiles of energy-adjusted lignans intake after log transformation between LFFQ2 and 24-h DRs and between LFFQs were 42.7% and 37.9%, respectively. Misclassification rates of participants into extreme quartiles were 1.0% and 4.9%, respectively. Conclusion The newly developed LFFQ has acceptable validity and reproducibility, and thus could be regarded as a reasonable and useful instrument in the assessment of dietary lignans intake among Hong Kong Chinese women with early-stage breast cancer.
Time Series Forecasting of the Austrian Traded Index (ATX) Using Artificial Neural Network Model

: This paper analyses the Austrian Traded Index (ATX) of the Vienna Stock Exchange (Wiener Börse) in the period from 2009 to 2017, using the method of the artificial neural network (ANN). Sampling data are taken from the web page of the Wiener Börse and filtered on weekly basis to comply with weekly seasonality in eight years range. The aim is to construct several AAN models that meet certain criteria and evaluate them on the holdout subsample. Furthermore, the goal is to find the best model that can predict new upcoming yet unseen data with high accuracy. A data frame for testing forecasting performance is one month, a quartile, a half year, and one year period for which last year of the data sample is retained (August, 2016- August 2017). Using various criteria and different parameters, the total of thirty networks were built and tested and top five networks were analysed in more details. Results confirm high accuracy of using method of artificial neural networks, which is consistent to studies conducted on similar cases. Correlation of top three selected networks by validation subsample is over 0,9. The mean absolute percentage errors (MAPE) for the best selected network are 1,76% (month); 2,11% (quartile); 2,21% (half-year); 2,13% (year). Once again, ANN method has proven to be a powerful forecasting tool.
Monolayer honeycomb structures of group-IV elements and III-V binary compounds: First-principles calculations

Using first-principles plane-wave calculations, we investigate two-dimensional 2D honeycomb structure of group-IV elements and their binary compounds as well as the compounds of group III-V elements. Based on structure optimization and phonon-mode calculations, we determine that 22 different honeycomb materials are stable and correspond to local minima on the Born-Oppenheimer surface. We also find that all the binary compounds containing one of the first row elements, B, C, or N have planar stable structures. On the other hand, in the honeycomb structures of Si, Ge, and other binary compounds the alternating atoms of hexagons are buckled since the stability is maintained by puckering. For those honeycomb materials which were found stable, we calculated optimized structures, cohesive energies, phonon modes, electronic-band structures, effective cation and anion charges, and some elastic constants. The band gaps calculated within density functional theory using local density approximation are corrected by GW0 method. Si and Ge in honeycomb structure are semimetal and have linear band crossing at the Fermi level which attributes massless Fermion character to charge carriers as in graphene. However, all binary compounds are found to be semiconductor with band gaps depending on the constituent atoms. We present a method to reveal elastic constants of 2D honeycomb structures from the strain energy and calculate the Poisson’s ratio as well as in-plane stiffness values. Preliminary results show that the nearly lattice matched heterostructures of these compounds can offer alternatives for nanoscale electronic devices. Similar to those of the three-dimensional group-IV and group III-V compound semiconductors, one deduces interesting correlations among the calculated properties of present honeycomb structures.