Miracle-dz/UniFAR-FTUs huggingface dataset:
PGST: A Persian gender style transfer method

Recent developments in text style transfer have led this field to be more highlighted than ever. There are many challenges associated with transferring the style of input text such as fluency and content preservation that need to be addressed. In this research, we present PGST, a novel Persian text style transfer approach in the gender domain, composed of different constituent elements. Established on the significance of parts of speech tags, our method is the first that successfully transfers the gendered linguistic style of Persian text. We have proceeded with a pre-trained word embedding for token replacement purposes, a character-based token classifier for gender exchange purposes, and a beam search algorithm for extracting the most fluent combination. Since different approaches are introduced in our research, we determine a trade-off value for evaluating different models’ success in faking our gender identification model with transferred text. Our research focuses primarily on Persian, but since there is no Persian baseline available, we applied our method to a highly studied gender-tagged English corpus and compared it to state-of-the-art English variants to demonstrate its applicability. Our final approach successfully defeated English and Persian gender identification models by 45.6% and 39.2%, respectively.
Discovering spurious links in multiplex networks based on interlayer relevance

Many real-world complex systems can be better modelled as multiplex networks, where the same individuals develop connections in multiple layers. Examples include social networks between individuals on multiple social networking platforms, and transportation networks between cities based on air, rail and road networks. Accurately predicting spurious links in multiplex networks is a challenging issue. In this article, we show that one can effectively use interlayer information to build an algorithm for spurious link prediction. We propose a similarity index that combines intralayer similarity with interlayer relevance for the link prediction purpose. The proposed similarity index is used to rank the node pairs, and identify those that are likely to be spurious. Our experimental results show that the proposed metric is much more accurate than intralayer similarity measures in correctly predicting the spurious links. The proposed method is an unsupervised method and has low computation complexity, and thus can be effectively applied for spurious link prediction in large-scale networks.
Assessment of microplastic pollution in the Gulf of Suez: Abundance and polymeric composition in beach sediments

The Gulf of Suez is a crucial shipping route and a hub for mining and oil drilling operations, making its area particularly susceptible to the accumulation of marine plastic waste. This study evaluates the abundance and composition of microplastics (MPs) along the Gulf of Suez shores. A total of 268 MPs particles were extracted from the
Islamic Economic Contribution In The Age of Globalization Trend

Conventional economics has not only weaknesses but also strengths. Its weakness mainly lies in its secular paradigm, which separates positive and normative economics, the absence of a solid relationship between micro and macroeconomics; and the neglect of moral and ethical values ​​in its descriptive and predictive functions. The advantage is the sophisticated achievement of conventional economic theories with mathematical models and calculus. The era of globalization and the phenomenon of the development trend in economics has given rise to many opportunities as well as challenges, especially in efforts to develop Islamic economics. Therefore, in the future development of the Islamic economy, apart from learning from the successes and failures of conventional economics, it is also necessary to utilize new creative and innovative approaches to truly realize an Islamic economy that is rahmatan lil'alamin in its various aspects.
Propolis-Based Nanostructured Lipid Carriers for α-Mangostin Delivery: Formulation, Characterization, and In Vitro Antioxidant Activity Evaluation

α-Mangostin (a xanthone derivative found in the pericarp of Garcinia mangostana L.) and propolis extract (which is rich in flavonoids and phenols) are known for their antioxidant properties, making them potential supplements for the treatment of oxidative stress-related conditions. However, these two potential substances have the same primary drawback, which is low solubility in water. The low water solubility of α-mangostin and propolis can be overcome by utilizing nanotechnology approaches. In this study, a propolis-based nanostructured lipid carrier (NLC) system was formulated to enhance the delivery of α-mangostin. The aim of this study was to characterize the formulation and investigate its influence on the antioxidant activity of α-mangostin. The results showed that both unloaded propolis-based NLC (NLC-P) and α-mangostin-loaded propolis-based NLC (NLC-P-α-M) had nanoscale particle sizes (72.7 ± 1.082 nm and 80.3 ± 1.015 nm, respectively), neutral surface zeta potential (ranging between +10 mV and −10 mV), and good particle size distribution (indicated by a polydispersity index of <0.3). The NLC-P-α-M exhibited good entrapment efficiency of 87.972 ± 0.246%. Dissolution testing indicated a ~13-fold increase in the solubility of α-mangostin compared to α-mangostin powder alone. The incorporation into the propolis-based NLC system correlated well with the enhanced antioxidant activity of α-mangostin (p < 0.01) compared to NLC-P and α-mangostin alone. Therefore, the modification of the delivery system by incorporating α-mangostin into the propolis-based NLC overcomes the physicochemical challenges of α-mangostin while enhancing its antioxidant effectiveness.
Incremental value of non-invasive myocardial work for the evaluation and prediction of coronary microvascular dysfunction in angina with no obstructive coronary artery disease

Background Evidence suggests that patients suffering from angina with no obstructive coronary artery disease (ANOCA) experience coronary microvascular dysfunction (CMD). We aimed to understand the diagnosis value of noninvasive myocardial work indices (MWIs) with left ventricular pressure-strain loop (LV PSL) by echocardiography in ANOCA patients with CMD. Methods 97 patients with ANOCA were recruited. All subjects underwent standard echocardiography with traditional ultrasound parameters, two-dimensional speckle-tracking echocardiography with global longitudinal strain (GLS), LV PSL with MWIs include global work index (GWI), global constructive work (GCW), global waste work (GWW) and global work efficiency (GWE). In addition, all enrolled cases underwent high-dose adenosine stress echocardiography (SE) with coronary flow velocity reserve (CFVR). CMD was defined as CFVR <2.0. Results Of the 97 patients with ANOCA, 52 were placed in the CMD group and 45 in the control group. GWI and GCW were decreased significantly in the CMD group compared with the control group (P < 0.001 for both). GWI and GCW were moderately correlated with CFVR (r = 0.430, P < 0.001 and r = 0.538, P < 0.001, respectively). In the multiple logistic regression analyses, GCW was identified as the only independent echocardiography parameter associated with CMD after adjusting for age and baseline APV [OR (95%CI) 1.009 (1.005–1.013); P < 0.001]. Moreover, the best predictor of CMD in patients with ANOCA using receiver operating characteristic (ROC) curve was GWI and GCW, with an area under the curve (AUC) of 0.800 and 0.832, sensitivity of 67.3% and 78.8%, specificity of 80.0% and 75.6%, respectively. Conclusion MWIs with LV PSL is a new method to detect LV systolic function noninvasively in ANOCA patients with CMD.
Race, Ethnicity, and Taxation of the Family: The Many Shades of the Marriage Penalty/Bonus

Recent events have increased the focus on racial justice. One aspect of this attention is the realization that race interacts in important — but often not fully understood — ways with taxation, including taxation of the family. In this paper, we quantify the racial disparity in the magnitude of the “marriage penalty” or “marriage bonus,” using individual micro-level data from the Current Population Survey for the years 1992–2019. We find that Black married couples nearly always face a higher averaged marriage penalty (or a smaller averaged marriage bonus) compared with white married couples, even when we compare couples with similar family earnings. This occurs primarily because the incomes of Black married couples tend to be more evenly split between spouses than the incomes of white married couples. The differences between white couples and Hispanic couples tend to be smaller, but nonetheless they are still present in many cases, with Hispanic couples also facing a marriage penalty. We conclude with suggestions for reform of the individual income tax that would reduce the disparate racial and ethnic treatments across families.
Kinetic Effects of Transferrin-Conjugated Gold Nanoparticles on the Antioxidant Glutathione-Thioredoxin Pathway

Nanoparticle-based therapeutics are being clinically translated for treating cancer. Even when thought to be biocompatible, nanoparticles are being increasingly identified as altering cell regulation and homeostasis. Antioxidant pathways are important for maintaining cell redox homeostasis and play important roles by maintaining ROS levels within tolerable ranges. Here, we sought to understand how a model of a relatively inert nanoparticle without any therapeutic agent itself could antagonize a cancer cell lines’ antioxidant mechanism. A label-free protein expression approach was used to assess the glutathione-thioredoxin antioxidative pathway in a prostate cancer cell line (PC-3) after exposure to gold nanoparticles conjugated with a targeting moiety (transferrin). The impact of the nanoparticles was also corroborated through morphological analysis with TEM and classification of pro-apoptotic cells by way of the sub-G0/G1 population via the cell cycle and annexin V apoptosis assay. After a two-hour exposure to nanoparticles, major proteins associated with the glutathione-thioredoxin antioxidant pathway were downregulated. However, this response was acute, and in terms of protein expression, cells quickly recovered within 24 h once nanoparticle exposure ceased. The impact on PRDX-family proteins appears as the most influential factor in how these nanoparticles induced an oxidative stress response in the PC-3 cells. An apparent adaptive response was observed if exposure to nanoparticles continued. Acute exposure was observed to have a detrimental effect on cell viability compared to continuously exposed cells. Nanoparticle effects on cell regulation likely provide a compounding therapeutic advantage under some circumstances, in addition to the action of any cytotoxic agents; however, any therapeutic advantage offered by nanoparticles themselves with regard to vulnerabilities specific to the glutathione-thioredoxin antioxidative pathway is highly temporal.
Portal Analysis Approach Used for the Efficient Electromagnetic Transient (EMT) Simulation of Power Electronic Systems

Efficient electromagnetic transient (EMT) simulation is crucial for addressing the challenges associated with the modularity, cascading, and complex topologies of power electronics (PE) systems. This article introduces a novel portal analysis (PA) approach that adopts a unique “port-component” view, leveraging the characteristics of “ports”. Different from the classic nodal analysis (NA) method, the networks and the components are described based on the portal voltage equations with lower orders. Furthermore, a port tearing method is introduced to partition the circuit, resulting in a block-bordered-diagonal (BBD) matrix and a small number of boundary variables in the extended port equation. The parallel processing of the network solution is implemented by utilizing the BBD forms and the band features. To validate the effectiveness of the proposed PA approach in capturing dynamics, a down-scale dual active bridge (DAB) prototype is constructed. Additionally, a simulated microgrid comprising cascaded H-bridge-type-DAB (CHB-DAB), solar photovoltaic (PV), and energy storage system (ESS) is used to furtherly verify the accuracy and efficiency. The results demonstrate that compared with the NA-based methods, the proposed models exhibit high precision under various transient conditions, with maximum relative errors of less than 2%. Moreover, they achieve a remarkable acceleration of one to two orders of magnitude.
Localization of image fragments with high frequency intensity oscillation

The problem of detecting image fragments characterized by high-frequency fluctuations in spatial intensity in the general case has not been previously considered in the literature. The article researches a sequence of known and new algorithms that allows detection and localization of such fragments. The geometric localization of the fragments is based on the Hough transform of the pixel array of the external contours of the connected components. The components connecting becomes possible due to the use of the oscillation function proposed by the authors. The oscillation function turns out to be an effective tool for highlighting intensity fluctuations zones in an image and is superior in reliability to alternative methods for detecting such zones, based, for example, on gradient methods. The article demonstrates examples of localization of the image fragments with different levels of background complexity.
Physiological Signals as Predictors of Cognitive Load Induced by the Type of Automotive Head-Up Display

The visual information complexity of automotive head-up displays (HUDs) may affect cognitive load and reduce driver performance in critical situations. This study investigated whether physiological indicators of cognitive load can predict the type of HUD while driving. Physiological signals of heart rate variability (HRV), electrodermal activity (EDA), skin temperature, and pupil dilation were recorded from 28 participants using a motion-based driving simulator. Two types of HUD with different information complexities were compared: baseline HUD and augmented reality HUD. Heart rate and EDA were processed to create standardized biomedical features. Time-series analysis and basic statistics generated two sets of features for pupil dilation and skin temperature. The effect of signal combinations on classification performance was tested using signal fusion. Three gradient boosting classifiers (LGBM, HGBC, and XGB) were trained on physiological signals to predict HUD type. The fusion of HRV, EDA, and time-series features for skin temperature and pupil dilation yielded moderate performance, with average AUC ROC scores of XGB = 0.67, LGBM = 0.69, and HGBC = 0.70. Combining HRV, EDA, and basic statistical features for skin temperature and pupil dilation, the classifiers achieved an improved average AUC ROC score of 0.76. The best scores were 0.96 (LGBM and XGB) and 0.98 (HGBC). These results demonstrate the potential of physiological signals for modeling HUD-induced cognitive load and dynamically regulating its effects in real-time.
Evaluating the Bioremediation Capacity of the Polychaete Perinereis gualpensis (Jeldes, 1963) for Atlantic Salmon Aquaculture Sludge

The potential of polychaetes for the bioremediation of aquaculture sludge gained more attention in recent years. These organisms can reduce organic matter and nutrients contained in the sludge of several aquaculture species, improving the sustainability of these activities. The aim of this study was to evaluate the removal performance of Perinereis gualpensis (Jeldes, 1963) being fed with aquaculture sludge produced by a recirculating system cultivating Atlantic salmon. The experiment involved adding different amounts of sludge (10% and 20% with respect to total substrate) at a density of 300 organisms m−2 during 30 days. A treatment without sludge served as a control, using natural substrate. The highest removal rate of total organic matter (TOM) (23.95 ± 13.19 g m−2 day−1) was achieved by P. gualpensis with 20% sludge addition, a reduction of about 36% compared to the total amount added at the beginning of the trials. The organisms fed with aquaculture sludge presented higher nitrogen (8–9%) and carbon (40–43%) contents, with a maximum organic carbon assimilation of 32% in relation to the total content in the sludge. The high survival (88–95%) and positive growth rates (0.28% day−1) achieved by P. gualpensis indicated that this species can be sustained with salmon sludge as the only source of food. These results indicate that P. gualpensis is a promising candidate for removing nutrients from salmon effluents. Moreover, the protein contents achieved by the organisms (52–58%) meet the dietary protein requirements of several aquaculture species. Further research is needed to determine the maximum bioremediation capacity of this species and to evaluate the lipid content and fatty acid profiles of P. gualpensis to determine its potential application in aquaculture feed.
Domain Adaptation With Discriminative Distribution and Manifold Embedding for Hyperspectral Image Classification

Hyperspectral remote sensing image classification has drawn a great attention in recent years due to the development of remote sensing technology. To build a high confident classifier, the large number of labeled data is very important, e.g., the success of deep learning technique. Indeed, the acquisition of labeled data is usually very expensive, especially for the remote sensing images, which usually needs to survey outside. To address this problem, in this letter, we propose a domain adaptation method by learning the manifold embedding and matching the discriminative distribution in source domain with neural networks for hyperspectral image classification. Specifically, we use the discriminative information of source image to train the classifier for the source and target images. To make the classifier can work well on both domains, we minimize the distribution shift between the two domains in an embedding space with prior class distribution in the source domain. Meanwhile, to avoid the distortion mapping of the target domain in the embedding space, we try to keep the manifold relation of the samples in the embedding space. Then, we learn the embedding on source domain and target domain by minimizing the three criteria simultaneously based on a neural network. The experimental results on two hyperspectral remote sensing images have shown that our proposed method can outperform several baseline methods.
Multimodal Medical Image registration using Discrete Wavelet Transform

In image processing, image registration develops a relationship between two images using optimal transformation where the images could have been taken at various times, sources or devices, or from different perspectives. It aligns the reference and moving image using geometric transformations. This research study evaluates the performance of multimodal(images acquired from different sources)image registration technique using Discrete Wavelet Transform (DWT). The reference and the target images are decomposed into their respective DWT coefficients and then are processed for image registration. After registration, the resultant DWT coefficients are transformed back using Inverse DWT into their spatial coordinates in order to retrieve the registered image. The similarity of the two input images for image registration is calculated and investigated using a similarity metric known as Mutual Information (MI) which is maximized. The quality of registration is measured using cross-correlation coefficient (CCC) of the registered image with respect to the reference image. Finally the time taken for image registration in wavelet domain is analyzed and compared with the image registration taking place in spatial domain.
Highly Accurate Analytical Approximate Solutions of the Electrostatically Actuated Parallel Plates

This paper is concerned with highly accurate analytical approximate solutions to dynamic oscillation of the parallel-plates model of an electrostatic micro-actuator. A potential difference is applied between the two electrodes to obtain a desired oscillatory effect, and the top movable electrode is suspended over the bottom fixed electrode by a linear suspension. The periodic oscillation solutions are obtained by generalizing the second-order Newton-harmonic balance (HB) method. The procedure obtains brief and accurate analytical approximate solutions for a large range of oscillation amplitudes with only one iteration step, the analytical approximate solutions show excellent agreement with the “exact” solution yielded by numerical integration. These analytical approximate solutions can be applied to analyze and design micro- and nano-devices employing electrostatic parallel plates.
Achieving Maximum Urgency-Dependent Throughput in Random Access

Designing efficient random access is a vital problem for urgency-constrained packet delivery in uplink Internet of Things (IoT), which has not been investigated in depth so far. In this paper, we focus on unpredictable frame-synchronized traffic, which captures a number of scenarios in IoT communications, and generalize prior studies on this issue by considering a general ALOHA-like protocol, a general single-packet reception (SPR) channel, urgency-dependent throughput (UDT) based on a general urgency function, and the dynamic programming optimality. With a complete knowledge of the number of active users, we use the theory of Markov Decision Process (MDP) to explicitly obtain optimal policies for maximizing the UDT, and prove that a myopic policy is in general optimal. With an incomplete knowledge of the number of active users, we use the theory of Partially Observable MDP (POMDP) to seek optimal policies, and show that a myopic policy is in general not optimal by presenting a counterexample. Because of the prohibitive complexity to obtain optimal or near-optimal policies for this case, we propose two practical policies that utilize the inherent property of our MDP framework and channel model. Simulation results show that both outperform other alternatives. The robustness under relaxed system settings is also examined.
A wet impregnation approach to synthesize MIL-101(Cr) with open metal sites and their application in the adsorption of volatile organic compounds

The simple wet impregnation method reported a series of MIL-101(Cr) materials doped with copper acetate paddle wheel species. Powder X-ray diffraction and SEM studies showed the MOF frameworks remained intact during wet impregnation, and SEM- EDX, XPS, and N2 adsorption analyses confirmed the successful copper acetate loading. Volatile organic compounds adsorption capabilities of these materials were further examined, and it found that copper acetate doped MIL-101 (Cr) possesses up to 61% improvement in toluene uptake as compared to pristine MIL-101 (Cr) at a low partial pressure of P/P0 = 0.10 under 298.1 K. This performance improvement is attributed to the unsaturated open metal sites introduced by molecular copper acetate with a paddle wheel structure. This study provides not only a new series of promising VOC removal MOFs with unsaturated Cu(II) open metal sites but also a simple, widely applicable method for introducing Cu(II) open metal sites into MOFs by using molecular copper species with predefined paddle wheel structure.