Miracle-dz/UniFAR-FTUs huggingface dataset:
Code Smell Detection Using Whale Optimization Algorithm

: Software systems have been employed in many fields as a means to reduce human efforts; consequently, stakeholders are interested in more updates of their capabilities. Code smells arise as one of the obstacles in the software industry. They are characteristics of software source code that indicate a deeper problem in design. These smells appear not only in the design but also in software implementation. Code smells introduce bugs, affect software maintainability, and lead to higher maintenance costs. Uncovering code smells can be formulated as an optimization problem of finding the best detection rules. Although researchers have recommended different techniques to improve the accuracy of code smell detection, these methods are still unsta-ble and need to be improved. Previous research has sought only to discover a few at a time (three or five types) and did not set rules for detecting their types. Our research improves code smell detection by applying a search-based technique; we use the Whale Optimization Algorithm as a classifier to find ideal detection rules. Applying this algorithm, the Fisher criterion is utilized as a Additionally, the resulting classification rules are analyzed to find the software metrics that differentiate the nine code smells.
FifthNet: Structured Compact Neural Networks for Automatic Chord Recognition

Deep learning has become popular for many music processing tasks with Convolutional Neural Networks (CNNs) often applied. CNNs can be computationally expensive, a problem that may be alleviated through design of compact network elements or by compressing trained networks. CNNs assemble high-level structure in a hierarchical fashion, starting from small simple local patterns. On the other hand, much structure found in music spectra, such as harmonicity, is already well-defined. Both signal representations and processing methods have previously exploited such structure. We propose FifthNet, a compact neural network that is applied to the task of Automatic Chord Recognition (ACR). The compactness of FifthNet is effected through exploiting known data structure; first by arranging the network inputs according to expected data structures, then by separating processing of the semantically meaningful dimensions of the data. FifthNet is then seen to perform similar to a state-of-the-art CNN for ACR while employing only a small percentage of the parameters and computational expense used by the CNN.
HUMAN BEHAVIOR RECOGNITION BASED ON CONVOLUTIONAL NEURAL NETWORK (CNN)

Individually working up on collection of human behaviour identification structure supported the Convolution Neural Network created for the precise behaviour of human in publicly places. Essentially, a video with some behaviors of human information sets are divided into pictures. Subsequently, we have a tendency to method all the pictures by using a vigorous mechanism called background subtraction which detects the changes in order of images that helps in finding many applications. For instance the coaching information set area unit are up skilled with an outline of CNN model, and the deep learning networks are made of random Gradient descent used for updating the framework of our model. Ultimately, assorted behaviors with samples area unit are systematized and known with the acquired system replica. Therefore, area unit will equate the present thought ways. Upshot displays that Convolutional Neural Network will analyse the human behaviour model mechanically and determine the behaviour of human without any metadata.
Multiplexing of Fabry-Pérot Sensor by Frequency Modulated Continuous Wave Interferometry for Quais-Distributed Sensing Application

Fiber Fabry-Pérot (FP) sensor, as an optical sensor with simple structure and the most application fields, has attracted a lot of attention in recent decades, but it also faces the difficulty of multiplexing. In this paper, we propose and demonstrate a novel multiplexing method of FP sensor with multi-branch configuration interrogated with frequency modulated continuous wave interferometry. By an algorithm based on Fourier transform, the sub-sensors are addressable and their interference spectrum can be demodulated independently. For demonstration, the quasi-distributed refractive index (RI) sensing experiment is realized. The experiment results inherit high RI sensitivity of the traditional FP sensor around 1200 nm/RIU and high RI resolution smaller than 5 × 10−6 RIU. Besides, thanks to the advantage of coherence detection, the spectrum can be demodulated from the reflection signal of <2 pW, which provides the possibility for a huge multiplexing amount, about 8000 in theory. The proposed multiplexing method is significant for practical applications of the traditional FP sensor.
Novel Interpenetrating Polymer Network Hydrogel Microspheres of Chitosan and Poly(acrylamide)-grafted-Guar Gum for Controlled Release of Ciprofloxacin

Acrylamide-grafted-guar gum (pAAm-g-GG) was prepared and blended with chitosan (CS) to form interpenetrating polymer network (IPN) hydrogel microspheres by the emulsion cross-linking method using glutaraldehyde (GA) as a cross-linker. The microspheres encapsulated up to 74% of ciprofloxacin (CFX), an antibiotic drug, having a plasma half-life of 4 h and the release of CFX was extended up to 12 h. Scanning electron microscopy (SEM) confirmed their spherical structure with smooth surfaces; Fourier transform infrared spectroscopy (FTIR) confirmed the grafting reaction as well as chemical stability of CFX in the blend IPN hydrogel microspheres. Differential scanning calorimetry (DSC) and X-ray diffraction (XRD) techniques confirmed the molecular level dispersion of CFX in the matrix. Swelling of microspheres performed in pH 7.4 buffer media was used to understand the drug release kinetics. In vitro release of CFX in pH 1.2 and 7.4 media showed a dependence on blend composition of the IPN, extent of cross-link.
Simultaneous Lot Sizing and Scheduling of Multistage Batch Processes Handling Multiple Orders per Product

A pair of precedence-based continuous-time formulations addressing the combined lot sizing and scheduling of order-driven multistage batch facilities is presented. The proposed mixed-integer linear programming (MILP) models can handle multiple orders per product with different delivery dates, variable processing times, and sequence-dependent changeovers. As each order may be filled by one or more batches, enough batches for each order ensuring optimality are initially defined. The two monolithic formulations are intended for sequential batch processes where batch integrity is preserved throughout the entire production system. However, lots of final products can be split to satisfy two or more orders. One of the approaches is based on a detailed MILP formulation allocating individual batches to units and ordering them in every unit. In contrast, the second methodology is specially designed for large scheduling problems. It first gathers batches for the same order into clusters, and then assigns clusters to.
Management of Downy Mildew of Onion Through Selective Fungicides in the Field Condition

Efficacy of variousfungicides against powdery mildew of onion all chemical treated 1st, 2nd, 3rd and 4th observation Score observation in plants (out of 15) were0.97, 2.89, 2.44 and 2.22 against 2.33, 9.00, 10.00 and 10.33 in control; disease infection 6.47, 20.00, 16.30 and 14.07% against 15.56, 60.00, 66.67 and 68.89% in control; infected leaves/plant 0.20, 2.04, 2.38 and 2.02 against 1.04, 4.36,4.99 and 4.04leaves in control, respectively. The Cabriotop observation resulted in infected plants 1.00, 2.56, 1.89 and 1.67 against 2.32, 9.00, 10.00 and 10.33 in control; disease infection 6.67, 17.04, 12.59 and 11.11 against 15.56, 60.00, 66.67 and 68.89% in control, infected leaves 0.41, 2.22, 2.62 and 2.07 against 1.04, 4.36, 4.99 and 4.04 in control, respectively with average bulb weight of 126.50g. The Relly observation in infected plants 0.96, 3.33, 2.78 and 3.11 against 2.33, 9.00, 10.00 and 10.33 in control; disease infection 6.42, 22.22, 18.52 and 20.74% against 15.56, 60.00, 66.67 and 68.89% in control; infected leaves 0.41, 2.22, 2.62 and 2.07 against 1.04, 4.36, 4.99 and 4.04 in control, respectively with average bulb weight of 116.38g against 74.34g in control. Defer plus at observation resulted ininfected plants of 0.95, 2.78, 2.56 and 2.78 against 2.33, 9.00, 10.00 and 10.33 in control; disease infection 6.33, 18.52, 17.04 and 18.52% against 15.56, 60.00, 66.67 and 68.89% in control; infected leaves 0.50, 2.10, 2.48 and 1.96 against 1.04, 4.36, 4.99 and 4.04/plant in control; with average bulb weight of 101.63g, 106.97g and 112.61g overall average bulb weight of 107.07g against 74.34g bulb weight on average in control
The Voice of Senior High School Alumni in Border Area

This research aims to minimize the undergraduate students of FTTE problem by figuring out the alumni of Senior High School experience and expectations in the EFL classroom as the initial information for undergraduate students before conducting the program. 177 alumni of senior high school from five regencies in North Borneo were the respondent. The data collected was an open question questionnaire distributed through a Google form. The result shows most of the alumni of Senior High School argued the class atmosphere was incapable of motivating students to take part. They found the class holding with monotones, traditional settings, and unclear explanations. This condition led them to off mode. Also, an opportunity to practice orally was less because they were just asked to work on the worksheet. An interactive interaction between teachers and students and among students can be found in group discussion. An appropriate language used in explaining allows the students to grab the material better. Providing students opportunities to practice orally and individually makes potential progress. The critical point is learners crave fun and helpful teacher. These responses indicated that a teaching mechanism and the educator's personality would create a conducive learning atmosphere.
Fatherhood & Children’s Remote Learning During Covid-19 Pandemic:

Relational power supremacy is determined by culture, which impacts women's and men's capacity to make decisions in the family and community. As a part of strong patriarchal culture, Balinese men's involvement in parenthood deals with their self-concept and identity. Although there has been a growing literature discussing fatherhood in many cultural settings, a limited study focusing on how men in strong patriarchal culture transmit their full-time fatherhood has been conducted. Besides, the emergency shifting of learning due to the COVID-19 pandemic conveys more hitches to shelter. The present study examined whether and how Balinese fathers' parenting styles may influence attachment style and their children's remote learning activities. By using attachment theory, a qualitative approach of analysis was carried out using a narrative inquiry. A father with children who are having remote learning activities was recruited as the participant of this study. Unstructured interviews were used for data collection and recorded using a voice recorder only. The recording was then transcribed and analyzed using collaborative thematic narrative analysis. The results indicate that fathers' parenting style, their perception about the fatherhoods, their coping strategies, and responses from the society were related to the attachment style and children's remote learning activities during the COVID-19 pandemic.
Predictive echocardiographic factors of severe obstructive sleep apnea

Introduction obstructive sleep apnea (OSA) is a common chronic pulmonary disease, characterized by repetitive collapse of the upper respiratory airways, leading to oxygen desaturation. This condition is recognized to be associated with cardiovascular disease. Several studies have shown the effects of OSA on both geometry and cardiac function, with conflicting results. We aimed to investigate the relationship between echocardiographic abnormalities and the severity of OSA. Methods this is a cross-sectional single center study including patients, without any cardiovascular or pulmonary comorbidities, with polygraphy proven OSA. All participants underwent a detailed transthoracic echocardiography (TTE). Results a total of 93 patients were included in the study, with 62.2% (n=56) females. According to the apnea hypopnea index (AHI), patients were divided into two groups: mild to moderate OSA (5≤ AHI< 30/H) and severe OSA (AHI≥ 30/H). There were no differences in baseline characteristics between the two groups. The assessment of echocardiographic parameters demonstrated that severe OSA have a higher left ventricular end-systolic (LVES) (47.6±7.2 VS 46.2±4.7), left ventricular end-diastolic (LVED) (31.3±6.2 VS 28.9±4.5) diameters and interventricular septum (IVS) thickness (12.7±2.4 VS11.7±2.5) diameters rather than mild to moderate OSA without a significant difference between the two groups. Furthermore, severe OSA patients had lower mean value of left ventricular ejection fraction (LVEF) and fractional shortening (FS) equal to 62.1±9.7 and 32.5±6.3 respectively. The difference between the two groups was not statistically significant. However, a significant association was shown between severity of OSA and left ventricular (LV) diastolic dysfunction, right ventricular internal diameter (RVID) and systolic pulmonary artery pressure (sPAP), with p=0.05, p=0.05 and p= 0.03 respectively. The RVID was also independently associated to the severity of the OSA (aOR 1.33, 95%CI: 0.99-1.79; p=0.05). Conclusion using bidimensional echocardiography showed a relationship between severe OSA and right ventricular parameters (diastolic dysfunction and RVID) and sPAP.
Finite-Time Fuzzy Control for Nonlinear Singularly Perturbed Systems With Input Constraints

Singularly perturbed systems have found widespread applications in practice. The existing results on singularly perturbed systems mainly focused on the Lyapunov asymptotic stability, which are unable to deal with the cases that the system states cannot exceed a given threshold during a fixed time interval. This article addresses the finite-time fuzzy control issue for discrete-time nonlinear singularly perturbed systems with input constraints. The aim is to guarantee the boundedness of the states of singularly perturbed systems during a finite-time interval. Based on the matrix inequality technique, some conditions are established to guarantee the finite-time boundedness of the fuzzy singularly perturbed systems, where the singularly perturbed parameter is independent so as to avoid the ill-conditioned problem caused by the small singularly perturbed parameter. The gains of the finite-time fuzzy controller can be obtained by solving some singularly perturbed parameter independent linear matrix inequalities. Finally, the proposed finite-time fuzzy controller design approach for nonlinear singularly perturbed systems is illustrated via the Van der Pol circuit.
Cooperative Blind Spectrum Detection With Doolittle Decomposition and PCA-SVM Classification in Hybrid GEO-LEO Satellite Constellation Networks

A cooperative blind spectrum detection with the Doolittle decomposition and support vector machine (SVM) classification is proposed to improve the performance and reduce the complexity and latency of spectrum detection in hybrid Geostationary Earth Orbit and Low Earth Orbit (GEO-LEO) satellite constellation networks. First, a principal component analysis (PCA) algorithm is adopted to process perceive signals. Second, the maximum-to-minimum eigenvalue ratio of a covariance matrix is utilized to construct statistics with self-learning ability by using the Doolittle decomposition. Third, primary user and noise signals are labeled with “+1” and “$-$1” as training labels, respectively. Finally, a high-performance PCA-SVM classification is generated by training the labels and the corresponding statistics. Innovations mainly include the Doolittle decomposition of the covariance matrix in the SVM and the PCA to preprocess the perceived signals. Simulation results show that the detection probability of the proposed scheme outperforms the energy detection and the SVM algorithm by 55 and 15% at a signal-to-noise ratio (SNR) of $-$15 dB, respectively. The average error probability of the proposed scheme is 20% lower than that of the SVM at an SNR of $-$20 dB. Therefore, in hybrid GEO-LEO satellite constellation networks, the cooperative blind spectrum detection with the Doolittle decomposition and SVM classification can detect the spectrum with low complexity and high performance effectively.
Effective SiN$_{\bf x}$ :H Capping Layers on 1-nm Al2O3 for p$^{\bf +}$ Surface Passivation

Passivation of p<sup>+</sup> regions is typically achieved by Al<sub>2</sub>O<sub>3</sub> layers with thicknesses in excess of 10 nm. Given the expense of commonly used Al<sub>2</sub>O<sub>3</sub> precursors and, in some cases, the deposition time, it is desirable to minimize the layer thickness. We achieve recombination factor J<sub>0p+</sub> in the order of 22 fA/cm<sup>2</sup> with 1 nm of Al<sub>2</sub>O<sub>3</sub> capped with ~70-nm amorphous silicon nitride (SiNx :H) films on 85 Ω/□ boron diffusions. The passivation performance of ultrathin-Al<sub>2</sub>O<sub>3</sub>/SiN<sub>x</sub> :H stacks depends critically on both the alumina thickness and the SiN<sub>x</sub> :H composition. It was found that to achieve low J<sub>0p+</sub> with 1-nm-Al<sub>2</sub>O<sub>3</sub>/SiN<sub>x</sub> :H stacks, the SiNx :H hydrogen concentration ([Si-H]+[N-H]) was required to be low: less than 8×1021 cm<sup>-3</sup>. Fourier transform infrared measurements indicated that the initial hydrogen content is more appropriate to evaluate the hydrogen release process of SiNx :H layers than Si-N bond density, at least in this study. Both the Al<sub>2</sub>O<sub>3</sub>-Si interface and charge density of 1-nm-Al<sub>2</sub>O<sub>3</sub>/SiN<sub>x</sub> :H stacks can be impacted by the SiN<sub>x</sub> :H capping layer. The outstanding passivation quality of 1-nm-Al<sub>2</sub>O<sub>3</sub>/SiN<sub>x</sub> :H stacks is due to a combination of both chemical and electrostatic passivation.
Inequality and the changing nature of work in Peru

This paper identifies the socioeconomic drivers of earnings inequality in Peru in the period 2004–18. Using the ENAHO household surveys and data on routine task content of occupations, we apply inequality decomposition methods to the real earnings distribution, its quantiles, and the Gini index. We find that in this period inequality has reduced, with great improvement attributed to reductions in the gender wage gap and macroeconomic factors. However, we did not find strong evidence for factors related to changes in workers’ attributes or shifts in job characteristics, except for a slight enhancing effect of the task content of occupations, which increases in importance as we move from ‘poorer’ to ‘richer’ deciles.
The C-terminal fragment of LRRK2 with the G2019S substitution increases the neurotoxicity of mutant A53T α-synuclein in dopaminergic neurons in vivo

Background: Alpha-synuclein (α-syn) and leucine-rich repeat kinase 2 (LRRK2) likely play crucial roles both in sporadic and familial forms of Parkinson’s disease (PD). The most prevalent mutation in LRRK2 is the G2019S substitution, which induces neurotoxicity through increased kinase activity. There is likely an interplay between LRRK2 and α-syn involved in the neurodegeneration of dopaminergic (DA) neurons in the substantia nigra (SNpc) in PD. However, the mechanisms underlying this interplay are ill-defined. Here, we investigated whether LRRK2 G2019S can increase the neurotoxicity induced by a mutant form of α-syn (A53T mutation) in DA neurons in vivo . Methods: We used a co-transduction approach with adeno-associated virus (AAV), AAV2/6 vectors encoding human α-syn A53T and the C-terminal portion of LRRK2 (ΔLRRK2), which contains the kinase domain, with either the G2019S mutation (ΔLRRK2 G2019S ) alone or the D1994A mutation (ΔLRRK2 G2019S/D1994A ), which inactivates the kinase activity of LRRK2. The AAVs were co-injected into the rat SNpc and histological evaluation was performed at 6- and 15-weeks post-injection (PI). Results: The majority of SNpc neurons co-expressed ΔLRRK2 and human α-syn A53T after transduction. ΔLRRK2 G2019S alone produced no cell loss at 15-weeks PI. Injection of AAV-α-syn A53T alone or mixed with a control AAV coding for GFP produced a significant loss of DA neurons. Co-injection of AAV-α-syn A53T with AAV-ΔLRRK2 G2019S instead of GFP slightly exacerbated that neuronal loss We also studied the inactive form, ΔLRRK2 G2019S/D1994A at 6 weeks PI. Injection of AAV-ΔLRRK2 G2019S mixed with AAV-α-syn A53T produced a neurotoxic effect that was stronger than that produced by the co-injection of AAV-DLRRK2 G2019S/D1994A and AAV-α-syn A53T . Conclusion: Thus, these results show that mutant LRRK2 may selectively facilitate α-syn toxicity in DA neurons through a cell-autonomous mechanism involving its kinase domain. However, considering that the effect of ΔLRRK2 G2019S upon human α-syn A53T is moderate in our paradigm where pathological proteins are overexpressed, the study supports the hypothesis that the interplay between LRRK2 and α-syn may also implicate non-cell-autonomous mechanisms such as those involved in neuroinflammation and spreading of α-syn aggregated species.
Assessment of Carotid Body Tumor by Superb Micro-Vascular Imaging in a Preoperative Evaluation

Background: Superb micro-vascular imaging (SMI) provided new advances in vascular imaging, resulting in revealing the overall vascularity detection of small or microflow states without the use of contrast media. This study aimed to explore the blood supply andfeeding artery of carotid body tumor (CBT) on SMI for providing more accurate information for surgery.Results: Twenty-six CBT lesions underwent color Doppler flow imaging (CDFI) and SMI, and were confirmed later by pathology. The blood flow patterns and feeding artery of CBTson CDFI and SMI were graded and compared.Compared with the application of CDFI, the pattern of more CBT lesionschanged to a higher Adler category by SMI (P<0.001). Thefeeding artery of two CBT lesions, which fail to show by CDFI, was internal carotid artery(ICA) by SMI and compared with CDFI the feeding artery of three changed from ICA or external carotid artery(ECA) to MIX (both ICA and ECA) by SMI. We classified the feeding artery of CBTs into originating from ICA or others (including ECA and MIX). For all the lesions, threelesions that stemmed from ICA and 23lesions that stemmed from ECAor MIX. CBT lesions stemming from ECA or MIX with Adler II or Adler III blood flow patterns accounted for 30.4% (7/23) or 69.6% (16/23), respectively, while CBT lesions stemming from ICA with Adler I or Adler II blood flow patterns accounted for 66.7% (2/3) or 33.3% (1/3), respectively. Conclusions: SMI is superior to CDFI in detecting vascularity of CBTs, and SMI could better investigate the origin of feeding vessels of CBTs in comparison to CDFI.Compared with those originating from ECA, CBTs from ICA has less vascularity.