Miracle-dz/UniFAR-FTUs huggingface dataset:
Shared-Aperture Slot-Based Sub-6-GHz and mm-Wave IoT Antenna for 5G Applications

In this article, a square concentric slot-based antenna is presented for sub-6-GHz and millimeter-wave (mm-wave) 5G-enabled Internet of Things (IoT) devices. The proposed antenna design exhibits an octaband operation for the sub-6-GHz spectrum while resonates at 28 GHz as well. The unique feature of the proposed design is the shared radiating aperture for both sub-6-GHz as well as mm-wave bands. The antenna consists of three concentric square slots etched out from a ground (GND) plane dimensions of <inline-formula> <tex-math notation="LaTeX">$50\,{\times }\, 50\,{\times }\,0.508{\mathrm{ mm}}^{3}$ </tex-math></inline-formula>. For the sub-6-GHz band, the antenna is excited by a single open-ended microstrip transmission line, while <inline-formula> <tex-math notation="LaTeX">$1\,{\times }\,8$ </tex-math></inline-formula> power divider (PD) is used to excite the planar connected antenna arrays at the mm-wave band. The proposed antenna covers the following eight bands for sub-6-GHz operation: 1.05–1.23 GHz, 1.4–1.55 GHz, 1.9–2.3 GHz, 2.3–2.7 GHz, 3.1–3.7 GHz, 4.04–4.511 GHz, 4.83–5.2 GHz, and 5.66–6.151 GHz. The mm-wave band covers 27.4–28.4 GHz with the minimum bandwidth (BW) of 1 GHz. The proposed antenna covers most of the IoT bands, thus, it is a potential candidate for next-generation 5G-enabled IoT devices.
PENGGUNAAN MODEL UNIFIED OF ACCEPTANCE AND USE TECHNOLOGY (UTAUT) UNTUK MENGANALISA FACTOR DETERMINAN FINTECH DI INDONESIA

This Study aims to contribute to reviewing existing literature of Unified of Acceptance and Use Technology (UTAUT) as an updated model to explain Behavior Intention dan Use Behavior of Technology Acceptance to analyze Determinant Factors for novelty technology of Fintech Industry in Indonesia. The result produced in this study based on analysis of UTAUT model benefit compare to another technology acceptance model, included Technology Acceptance Model, Theory of Reasoned Action and Theory of Planned Behavior. These reviews will share UTAUT Model for future researchers to conceptualize, distinguish and comprehend the underlying technology models and theories that may affect the previous, current and future application of technology acceptance for Fintech adoption in Indonesia. Keywords: UTAUT, Fintech, Behavior Intention, Use Behavior
Experimental indoor validation of weak intensity fluctuations over free-space optical communication link

In this paper, we present experimental results for characterizing turbulence phenomena in free-space optical (FSO) communication under laboratory controlled conditions. Collected data is used for statistical determination of the probability density function (PDF) of irradiance signal fluctuations. In literature, there are a number of empirical models for variety of turbulence regimes. Thus, obtained PDF is compared with selected models from the bibliography in order to describe properly statistical properties of real turbulent channel and help improving of FSO system performance calculation. In overall, analysis has shown that the results obtained under given constraints fit well with the exponentiated Weibull turbulence model.
Malignant Transformation of Heterotopic Pancreatic Tissue in a Patient with BRCA2 Mutation

Background: Malignant transformation of heterotopic pancreatic tissue is a rare entity with only several case reports published in the scientific literature. Adjuvant chemotherapy following oncological resection for lesions with nodal metastasis has not been well described and there are no guidelines available to guide the management of these patients. Case Presentation: We present a case of gastric heterotopic pancreatic carcinoma with nodal metastasis in a young patient with breast cancer gene (BRCA) 2 mutation. He had undergone a laparoscopic wedge resection for a gastric lesion initially thought to be a gastrointestinal stroma tumor. Given the involvement of the wedge resection margins, the patient underwent a distal gastrectomy with oncological lymph nodal clearance. One out of the 33 harvested lymph nodes harboured micrometastasis while the main gastrectomy specimen did not have any residual malignancy. Following the histological diagnosis, he received an adjuvant chemotherapy regime akin to that prescribed for locally advanced pancreatic adenocarcinoma with good response. This is, to our knowledge, also the first such case report in a patient with BRCA2 mutation. Conclusions: Pre-operative diagnostic confirmation is challenging and endoscopic procedures pose significant false negatives. Reports of nodal metastasis following oncological resection are limited and there are no guidelines regarding adjuvant therapies. We would recommend a chemotherapy regimen similar to that for primary locally advanced pancreatic carcinoma in patients found to have nodal metastasis.
Preparation and Property of Strontium-substituted Hydroxyapatite

The biological HA in the body differs from that of pure HA in stoichiometry, composition, physical properties and mechanical properties, because this HA is particularly prone to ion substitution. As a cation that can substitute for calcium in the structure of hydroxyapatite, strontium provokes an increasing interest because of its beneficial effect on bone formation, and prevention of bone resorption. Here, strontium-substituted HA powders were prepared by the hydrothermal method at 180℃ for 8 h using Ca(NO3)2·4H2O, (NH4)2HPO4 and Sr(NO3)2 as reagents. X-ray diffraction, Fourier transform infrared spectroscope, transmission electron microscope, energy dis- persive X-ray, and thermogravimetric-differential thermal analysis were employed to investigate the crystalline phase, chemical composition, morphology, and thermal stability of the Sr-HA. And the cytotoxicity of Sr-HA was analyzed through MTT assay. The results show that Sr is incorporated into the HA crystal structure and the crystal grain size of the Sr-HA decreases as the Sr content (under 50wt%) is increased. Moreover, the HA thermal stability decreases. However, there's no apparent difference between the pure hydroxyapatite and all of the Sr-HA groups in cytotoxicity, which may have good biocompatibility.
Impact of Cellulase and Lactic Acid Bacteria Inoculant to Modify Ensiling Characteristics and In Vitro Digestibility of Sweet Corn Stover and Cassava Pulp Silage

Improving the productive performance of agricultural residue silage has practical relevance to sustaining livestock production. Sweet corn stover (SCS) and cassava pulp (CSVP) are widespread in the tropics as low-cost feed resources. To efficiently prepare SCS and CSVP silage, the impact of adding Acremonium cellulase (AC), Lactobacillus casei strain TH14 inoculant (TH14), and their combination (AC+TH14) on ensiling characteristics, microbial population, chemical compositions, and in vitro digestibility were tested in comparison to control (no additive). After 60 d of ensiling, the pH value and ammonia nitrogen content of silage were lower (p < 0.05) when AC was used as the additive. Compared with other treatments, TH14 provided abundant lactic acid fermentation in silage. All tested additives increased the crude protein (CP) content and decreased the neutral detergent fiber (NDF) content of SCS silage. In CSVP silage, only AC and AC+TH14 altered the CP and NDF content. In addition, AC and AC+TH14 provided greater in vitro dry matter digestibility and a lower in vitro fiber digestibility. Overall, optimized either AC or TH14 can be recommended as an attractive additive to improve the ensiling characteristics of SCS and CSVP silage. AC significantly modifies the in vitro digestibility of silage.
Characterization of custard apple seeds for the separation of prebiotic low molecular weight carbohydrates (LMWC)

The concept of waste to wealth is gaining lot of importance in the recent days. In this context, the present study was undertaken to identify the potential prebiotics present in the custard apple seeds. Among the different components identified, the Low Molecular Weight Carbohydrates (LMWC) were chosen for the study and the extraction was performed using Ethanol at three different concentrations (50%, 75% and 95%) and different combination of temperature, time and speed of rotation. The maximum yield of 9.16% was obtained with 50% Ethanol, 37 0C, 72h and 60 rpm. The probiotic organism Lactobacillus bulgaricus displayed a positive growth of 7.54±0.04 log cfu/ml on LMWC over a period of 24 hours which confirmed the prebiotic functionality of LMWC. Scanning Electron Microscopy and FTIR analysis were done to confirm the morphological characteristics. Therefore, all the results obtained showed that LMWC can be used as potential prebiotics in the food industry and the commercial utilization of custard apple seeds.
Coaching style, sport enjoyment, and intent to continue participation among artistic swimmers

Using situational leadership models, the current study examined direct and indirect relationships between coaching styles (i.e., democratic and autocratic) and athletes’ intent to continue participation via enjoyment in the sport of artistic swimming. Data were collected using an online survey with a snowball sampling method. A total of 202 artistic swimmers at the elite level from 22 countries participated in this study. The findings showed that participants who trained with democratic-style coaches reported higher levels of athletic enjoyment and intent to continue their athletic careers. There was no mediating effect of athletic enjoyment between coaching styles and intent to continue via athletic enjoyment; instead, the results revealed that the direct path between athletic enjoyment and intent to continue was not significant. However, the results supported the direct relationships between both coaching styles and athletic enjoyment and between autocratic coaching style and intent to continue an athletic career.
The Influence of Enterprise Resource Planning (ERP) Implementation System on Company Performance Mediated by Organizational Capabilities

Research aims: This study aims to examine the effect of Enterprise Resource Planning (ERP) system implementation on company performance with organizational capabilities as a mediating variable.Design/Methodology/Approach: This research is a quantitative study using 117 samples of manufacturing companies listed on the IDX from 2013 to 2018. Analysis and testing in this study employed SEM-PLS to test the effect of Enterprise Resource Planning (ERP) system implementation on company performance with organizational capabilities as a mediating variable.Research findings: The results showed that the ERP system's implementation had a significant positive effect on company performance and organizational capabilities. Organizational capabilities also had a significant positive effect on company performance. Besides, it was found that organizational capabilities mediated the relationship between ERP system implementation and company performance.Theoretical contribution/Originality: This study utilized a cybernetics approach theory, RBV theory, and organizational capabilities theory to investigate the mediating role of organizational capabilities in increasing the impact of ERP systems on company performance.Practitioner/Policy implication: This study provides evidence that ERP implementation makes an integrated operating system and can increase organizational capabilities by utilizing existing resources, and ultimately will also increase company performance.Research limitation/Implication: In this research, it is challenging to find organizational capability measures, such as marketing capability and process improvement. This study only used one intervening variable so that the information obtained from the results is still limited.
A New Multi-Agent Feature Wrapper Machine Learning Approach for Heart Disease Diagnosis

Heart disease (HD) is a serious widespread life-threatening disease. The heart of patients with HD fails to pump suf cient amounts of blood to the entire body. Diagnosing the occurrence of HD early and ef ciently may prevent the manifestation of the debilitating effects of this disease and aid in its effective treatment. Classical methods for diagnosing HD are sometimes unreliable and insuf cient in analyzing the related symptoms. As an alternative, noninvasive medical procedures based on machine learning (ML) methods provide reliable HD diagnosis and ef cient prediction of HD conditions. However, the existing models of automated ML-based HD diagnostic methods cannot satisfy clinical evaluation criteria because of their inability to recognize anomalies in extracted symptoms represented as classi cation features from patients with HD. In this study, we propose an automated heart disease diagnosis (AHDD) system that integrates a binary convolutional neural network (CNN) with a new multi-agent feature wrapper (MAFW) model. The MAFW model consists of four software agents that operate a genetic algorithm (GA), a support vector machine (SVM), and Naïve Bayes (NB). The agents instruct the GA to perform a global search on HD features and adjust the weights of SVM and BN during initial classi cation. A nal tuning to CNN is then performed to ensure that the best set of features are included in HD identi cation. The CNN consists of ve layers that categorize patients as healthy or with HD according to the analysis of optimized HD features. We evaluate the classi cation performance of the proposed AHDD system via 12 common ML techniques and conventional CNN models by using a This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 52 CMC, 2021, vol.67, no.1 cross-validation technique and by assessing six evaluation criteria. The AHDD system achieves the highest accuracy of 90.1%, whereas the other ML and conventional CNN models attain only 72.3%–83.8% accuracy on average. Therefore, the AHDD system proposed herein has the highest capability to identify patients with HD. This system can be used by medical practitioners to diagnose HD ef ciently.
Kinetic study of carbazole degradation by free and immobilized Thalassospira profundimaris

Carbazole, polycyclic aromatic hydrocarbon (PAH), is a hazardous compound and a pollutant that can mainly be found in the petroleum industry. This pollutant can be treated in many ways and one of it is known as bioremediation. A method of using degrading-cell-organism, Thalassospira profundimaris, that is able to consume the pollutant as its food source and produce metabolite, harmless substance in exchange, splits into two ways which are using the cell as free cell and the other is using it as immobilized cell. There are many factors that are affecting the performance of the cell degradation. In this study, initial concentration of carbazole and agitation speed parameters have been tested and kinetic models built based on the results of this study. This study found that in term of initial concentration of carbazole, the performance of degradation cell is better on immobilized cell but not so significant based on kinetic models built. However, addition of good mixing quality enhanced the degradation performance significantly when the agitation speed is in range of 100 revolution per minute (rpm) and below.
Path-Based Sensors: Paths as Sensors, Bayesian Updates, and Shannon Information Gathering

Consider a sensor that reports whether or not an event has occurred somewhere along a path, but that has no conception of where along the path that event has occurred. We name this type of sensor a path-based sensor and describe the recursive Bayesian update that can be used to calculate posterior beliefs about the presence of a sensor triggering phenomenon given a path-based sensor observation. We show how the Bayesian update can be leveraged to calculate the expected Shannon information that will be gained along a particular path. We formalize two iterative information-gathering problems that result from this scenario and present path-planning algorithms to solve them. These include: 1) gathering information about the path-based sensor triggering phenomena and 2) assuming the path-based sensor triggering event is “robot destruction,” simultaneously gather information about: 1) hazards using a path-based sensor and 2) information about another environmental phenomenon using a standard sensor, such as the locations of search and rescue targets with a camera. We evaluate our methods using Monte Carlo simulations and observe that they outperform other techniques with respect to the new problems that we consider. Note to Practitioners—This work is motivated by the problem of searching for robot-destroying hazards that are otherwise invisible to the robots. That is, we can observe whether or not a robot survives a path, but, if a robot is destroyed, then we have no idea where, along the path, its destruction has occurred. A mathematically equivalent problem happens in any scenario, in which an agent is equipped with an event sensor that can only be set/triggered once, but that requires postprocessing to figure out if the sensor has been triggered or not. For example, postprocessing is needed if the determination of whether or not a biological specimen was obtained requires a manual laboratory inspection. We also consider an extension of the hazard detection problem, in which we simultaneously collect information about search-and-rescue victims using a “victim sensor,” such as a camera. In this problem, hazards indirectly affect information gathered about victims because new information about victims is lost whenever a robot is destroyed. We provide algorithms to solve these types of problems. The algorithms work even in cases with noise such that false positives and false negatives are possible. This work is useful in any application where observations take the form of a cumulative “yes” or “no” along a path.
Development of simple HPLC-UV method for discrimination of Adenophorae Radix

Adenophorae Radix (AR) is a frequently used medicinal herb; because of its popularity, products containing similar herbal products are often sold as substitutes, especially if their morphology is similar. However, any analytical method to identify AR based on quantitative analysis is not registered in Korea, Japan and China Pharmacopoeias. This study developed a simple HPLC method to discriminate between authentic AR and substitutes. Linoleic acid was used as a marker compound of AR. Our optimized HPLC-UV conditions included a mobile phase of 90 % acetonitrile under isocratic condition, and a flow rate of 1.0 mL/min at room temperature. Detection wavelength was set at 205 nm. Linoleic acid was detected at 13.5 minutes for a total analysis time of 20 minutes. The standard herb of AR contained 0.025 % of linoleic acid, while four authentic AR samples and eight substitutes contained 0.040~0.071 % and 0.004~0.014 %, respectively. Comparison of the linoleic acid concentrations of the sample types to reference AR showed that among 12 samples, only the four samples were authentic. Thus, our HPLC-UV method, along with our suggested content criterion for linoleic acid concentration, can be used for the quick and accurate determination whether the herbal products are authentic AR or substitute.
Etude expérimentale et numérique de la cinétique d'oxydation de biocarburants lignocellulosiques : cétones, éthers et lévulinates

Les carburants synthetises a partir de la biomasse representent une alternative credible aux carburants conventionnels. La biomasse lignocellulosique presente en effet une importante disponibilite et son traitement physico-chimique permet d’obtenir une grande variete de composes aux proprietes interessantes. La structure de ces biocarburants fait cependant intervenir des fonctions oxygenees, qui rendent la comprehension des phenomenes d’oxydation complexes. Le projet 2G-CSAFE, dans lequel s’inscrit le travail presente ici, a pour objectif d’explorer la cinetique d’oxydation de certains de ces carburants. Les fonctions chimiques etudiees lors de ce travail sont les fonctions cetone, ether et ester. La combinaison de deux de ces fonctions (comme dans le cas des levulinates) est egalement etudiee. Apres une etude bibliographique qui vise a identifier les informations apportees par les etudes passees sur les composes les plus simples de chaque famille (acetone, dimethyl-ether et formiate de methyle), l’accent est mis sur les rares travaux disponibles lies a la butanone, la cyclopentanone, la cyclohexanone, le dibutyl-ether, le formiate de butyle et le levulinate de methyle. La cinetique d’oxydation de ces composes est ensuite etudiee par des approches numeriques et experimentales. Des calculs de chimie theorique sont menes dans un premier temps pour etudier l’impact des fonctions oxygenees sur la structure du carburant et pour obtenir les constantes de vitesse relatives aux principales reactions mises en jeu. Des experiences en reacteur auto-agite par jets gazeux sont ensuite realisees sur une gamme de temperature pouvant aller de 450 a 1250 K, a des pressions de 1 ou 10 atm et pour des richesses allant de 0,5 a 2. Les donnees ainsi collectees sont enfin utilisees pour developper des mecanismes cinetiques. L’accord entre les simulations et les donnees experimentales est globalement satisfaisant pour des composes aussi complexes et les resultats presentes ici pourront etre source d’analogies pour la modelisation d’autres carburants oxygenes.
Correlation-based Oversampling aided Cost Sensitive Ensemble learning technique for Treatment of Class Imbalance

ABSTRACT The issue of class imbalance and its consequences over the conventional learning models is a well-investigated topic, as it highly influences performances of real-life classification tasks. Amongst the available solutions, Synthetic Minority Oversampling Technique (SMOTE) imprints efficacy in balancing the data through synthetic minority instance generation. However, SMOTE suffers from the drawback of redundant data generation owing to uniform oversampling rate in regard to which, SMOTE with a customised oversampling rate has been investigated recently. In parallel to this, ensemble learning approaches are quite effective in improving prediction abilities of a set of weak classifiers through adaptive-weighted training. However, it does not account the imbalanced nature of the data during training. Through this paper, Correlation-based Oversampling aided Cost Sensitive Ensemble learning (CorrOV-CSEn) is proposed by integrating correlation-based oversampling with the AdaBoost ensemble learning model. The correlation-based oversampling entails to define a customised oversampling rate and a suitable oversampling zone while a misclassification ratio-based cost-function is introduced in the AdaBoost model to administer adaptive learning of imbalanced cases. CorrOV-CSEn is evaluated against 13 state-of-the-art methods by using 8 simulation datasets. The experimental results establish CorrOV-CSEn to be effective than the state-of-the-art methods in resolving the concerned issues.
Spinal Region Segmentation for Intervertebral Distance of X-Ray Images Using Spectral Analysis

Physics plays a vital role in cultivating the knowledge of natural sciences and establishing the foundation oflogistic and scientific method. The application of physics to medical sciences has been developed in practicefor centuries. X-Ray, CT scan and MRI images of the spine provide a practical approach for detectingand assessing vertebral abnormalities. For accurate vertebra detection number of features of an image canbe extracted and meaningful information can be obtain from low level information in the image usingsegmentation. In this paper a method is proposed for making treatment of spinal traction efficient and feasibleby using image processing algorithm based on the data obtained from the survey and images of the patients.