Miracle-dz/UniFAR-FTUs huggingface dataset:
IDSX-Attention: Intrusion detection system (IDS) based hybrid MADE-SDAE and LSTM-Attention mechanism

An Intrusion Detection System (IDS) is essential for automatically monitoring cyber-attack activity. Adopting machine learning to develop automatic cyber attack detection has become an important research topic in the last decade. Deep learning is a popular machine learning algorithm recently applied in IDS applications. The adoption of complex layer algorithms in the term of deep learning has been applied in the last five years to increase IDS detection effectiveness. Unfortunately, most deep learning models generate a large number of false negatives, leading to dominant mistake detection that can affect the performance of IDS applications. This paper aims to integrate a statistical model to remove outliers in pre-processing, SDAE, responsible for reducing data dimensionality, and LSTM-Attention, responsible for producing attack classification tasks. The model was implemented into the NSL-KDD dataset and evaluated using Accuracy, F1, Recall, and Confusion metrics measures. The results showed that the proposed IDSX-Attention outperformed the baseline model, SDAE, LSTM, PCA-LSTM, and Mutual Information (MI)-LSTM, achieving more than a 2% improvement on average. This study demonstrates the potential of the proposed IDSX-Attention, particularly as a deep learning approach, in enhancing the effectiveness of IDS and addressing the challenges in cyber threat detection. It highlights the importance of integrating statistical models, deep learning, and dimensionality reduction mechanisms to improve IDS detection. Further research can explore the integration of other deep learning algorithms and datasets to validate the proposed model's effectiveness and improve the performance of IDS.
Writer Identification of Arabic Handwritten Digits

This paper addresses the identification of Arabic handwritten digits. In addition to digit identifiability, the paper presents digit recognition. The digit image is divided into grids based on the distribution of the black pixels in the image. Several types of features are extracted (viz. gradient, curvature, density, horizontal and vertical run lengths, stroke, and concavity features) from the grid segments. K-Nearest Neighbor and Nearest Mean classifiers are used. A database of 70000 of Arabic handwritten digit samples written by 700 writers is used in the analysis and experimentations. The identifiability of isolated and combined digits are tested. The analysis of the results indicates that Arabic digits 3 (٣), 4 (٤), 8 (٨), and 9 (٩) are more identifiable than other digits while Arabic digit 0 (٠) and 1 (١) are the least identifiable. In addition, the paper shows that combining the writer’s digits increases the discriminability power of Arabic handwritten digits. Combining the features of all digits, K-NN provided the best accuracy in textindependent writer identification with top-1 result of 88.14%, top-5 result of 94.81%, and top-10 results of 96.48%.
Therapeutic Potential of Albumin Nanoparticles Encapsulated Visnagin in MDA-MB-468 Triple-Negative Breast Cancer Cells

Breast cancer is among the most recurrent malignancies, and its prevalence is rising. With only a few treatment options available, there is an immediate need to search for better alternatives. In this regard, nanotechnology has been applied to develop potential chemotherapeutic techniques, particularly for cancer therapy. Specifically, albumin-based nanoparticles are a developing platform for the administration of diverse chemotherapy drugs owing to their biocompatibility and non-toxicity. Visnagin, a naturally derived furanochromone, treats cancers, epilepsy, angina, coughs, and inflammatory illnesses. In the current study, the synthesis and characterization of albumin visnagin (AV) nanoparticles (NPs) using a variety of techniques such as transmission electron microscopy, UV-visible, Fourier transform infrared, energy dispersive X-ray composition analysis, field emission scanning electron microscopy, photoluminescence, X-Ray diffraction, and dynamic light scattering analyses have been carried out. The MTT test, dual AO/EB, DCFH-DA, Annexin-V-FITC/PI, Propidium iodide staining techniques as well as analysis of apoptotic proteins, antioxidant enzymes, and PI3K/Akt/mTOR signaling analysis was performed to examine the NPs’ efficacy to suppress MDA-MB-468 cell lines. The NPs decreased cell viability increased the amount of ROS in the cells, disrupted membrane integrity, decreased the level of antioxidant enzymes, induced cell cycle arrest, and activated the PI3K/Akt/mTOR signaling cascade, ultimately leading to cell death. Thus, AV NPs possesses huge potential to be employed as a strong anticancer therapy alternative.
Numerical Study on the Thermal-elastoplastic Behaviors of Plate-type Dispersion Nuclear Fuel Elements

Using the concept of meso-mechanics, microscopic thermal stress and strain fields of the dispersion nuclear fuel plates are studied. With the assumption that the microstructures of fuel plates are periodic along the length and width directions, the corresponding three-dimensional Representative Volume Elements are developed, and the effects of the microstructures on the thermal-elastoplastic behaviors are investigated numerically. It is concluded that the microstructures of fuel plates can remarkably affect their mechanical properties. This study lays a foundation for optimal design of dispersion nuclear fuel elements.
FHAP: Fast Handover Authentication Protocol for High-Speed Mobile Terminals in 5G Satellite–Terrestrial-Integrated Networks

The integration of satellite and terrestrial networks presents new opportunities and challenges for high speed rail (HSR) communications. Since the HSR runs vary fast, user terminals on the HSR have to perform handover authentication when the HSR passes through different terrestrial base stations or satellite coverage areas. To improve the security and robustness of HSR communication services, a fast handover authentication protocol (FHAP) for high-speed mobile terminals in the 5G satellite–terrestrial-integrated networks (STNs) is proposed. In the FHAP, user terminals in the same carriage form a temporary group managed by a relay node. The prehandover authentication mechanism is employed, in which the terrestrial 5G core network configures the preauthentication information to multiple access nodes based on the Chinese Remainder Theorem according to the location information of the HSR. Thus, group members and one of the access nodes can achieve fast handover authentication with the preconfigured information. Considering that HSR has a high running speed, when handover authentication fails, user terminals can perform handover authentication with other access nodes, and the probability of handover authentication failure caused by a single access node can be effectively reduced. We use the protocol verification tool Scyther and the Burrows–Abadi–Needham (BAN) logic to prove the security of the FHAP and compare it with other similar protocols in terms of signaling, bandwidth, and computational overhead. The analysis results show that the FHAP satisfies better security properties and has excellent performance.
Low dielectric and thermal properties of polyimides based on PMDA, BPADA, TPE-Q and TPE-R

Abstract The polyimides were prepared by pyromellitic dianhydride (PMDA) or 4,4'-(4,4'-Isopropylidenediphenoxy)diphthalic anhydride (BPADA) as dianhydride monomer and 1,4-bis(4-aminophenoxy)benzene(TPE-Q) or 1,3-bis(4-aminophenoxy)benzene(TPE-R) as diamine monomer. The polyimides were well characterized by FT-IR, thermogravimetric analysis, dynamic thermomechanical analysis, dielectric measurement and tensile test. The flexibility of polyimide molecular chain was judged by the comparison of molecular volumes, molecular length and conformation transition energy through molecular simulations. Graphical Abstract
Numerals and scalar implicatures

In this paper we explore the relation between the meaning of number denoting determiners (‘numerals’) and the polarity of the context in which they occur. We claim that when numerals are embedded in positive (i.e. Upward Entailing) contexts they are given an upper bounded (‘exactly’) reading more often than when they are embedded in minimally different Downward Entailing contexts. Since this corresponds to the behavior of scalar triggers, we suggest that the stronger interpretation of a numeral is really due to a Scalar Implicature. We review the outcome of two experiments, a questionnaire and a reading task where eye movements were recorded, which tested this claim empirically. Finally, we discuss these findings in light of the current approaches on the semantics of numerals, analyzing in detail the relation between the meaning of a numeral and scalar strenghtening.
Evaluation of near-wall solution approaches for large-eddy simulations of flow in a centrifugal pump impeller

ABSTRACT The turbulent flow in a centrifugal pump impeller is bounded by complex surfaces, including blades, a hub and a shroud. The primary challenge of the flow simulation arises from the generation of a boundary layer between the surface of the impeller and the moving fluid. The principal objective is to evaluate the near-wall solution approaches that are typically used to deal with the flow in the boundary layer for the large-eddy simulation (LES) of a centrifugal pump impeller. Three near-wall solution approaches –the wall-function approach, the wall-resolved approach and the hybrid Reynolds averaged Navier–Stoke (RANS) and LES approach – are tested. The simulation results are compared with experimental results conducted through particle imaging velocimetry (PIV) and laser Doppler velocimetry (LDV). It is found that the wall-function approach is more sparing of computational resources, while the other two approaches have the important advantage of providing highly accurate boundary layer flow prediction. The hybrid RANS/LES approach is suitable for predicting steady-flow features, such as time-averaged velocities and hydraulic losses. Despite the fact that the wall-resolved approach is expensive in terms of computing resources, it exhibits a strong ability to capture a small-scale vortex and predict instantaneous velocity in the near-wall region in the impeller. The wall-resolved approach is thus recommended for the transient simulation of flows in centrifugal pump impellers.
Blue Water Scarcity Assessment in Banas River Basin using Water Footprint Approach

In order to increase water availability, improve water quality, and ensure long-term sustainability, river basin-scale planning and management of water resources is crucial. Using the blue water scarcity index and the water footprint concept, this study assesses blue water scarcity in the Banas river basin from 2008 to 2020. Banas basin experiences considerable scarcity, with the value of the average annual blue water scarcity index being 140.9% which can be characterized as moderate. Banas river basin typically experiences significant blue water scarcity for three months of the year (November, December and January). Compared to these months, it is low for three months (August, September, and October), moderate for four (April, May, June, and July), and significant for two months of the year (February and March). Farmers in the basin should adopt improved water management practices to ensure sustainability and address water scarcity issues. This study can provide a framework for policy to solve some policy and water management related issues in the basin. It can also help with more effective water resource allocation and utilization.
A Survey on In-Vehicle Time-Sensitive Networking

With the continued evolution of autonomous driving, the communication demand for in-vehicle networks (IVNs) has dramatically increased, and the traditional IVN solutions have become ineligible for the needs of new in-vehicle applications. Time-sensitive network (TSN) with the characteristics of determinism, low latency, high reliability, large bandwidth, and open industry standards, has been considered as the most promising technology for the next-generation IVNs. This article summarizes the current state and methodologies of in-vehicle TSN research through the following five aspects: 1) Quality of Service (QoS) strategy; 2) reliability; 3) clock synchronization; 4) network planning; and 5) network management. The corresponding research priorities and technical challenges are also addressed, respectively.
The Impact of Mukbang Live Streaming Commerce on Consumers’ Overconsumption Behavior

Food live streaming shopping, which features a host eating and promoting the products to viewers, has become a new form of food marketing. In three studies, the authors examine the impact of content, influencer, and channel factors of mukbang live streaming on consumers’ perceived value and subsequent impulse purchase and food consumption behavior. Study 1, an experiment with 216 participants, reveals that a non–autonomous sensory meridian response (non-ASMR) video in which the mukbanger talks to viewers while eating regular (i.e., nonjunk) food is more influential in enhancing the video's perceived value and increasing impulse purchase and consumption. Study 2, with 624 participants, introduces influencer factors into the experiment. It shows that a credible and parasocial influencer significantly affects consumers’ perceived value, regardless of the food featured, resulting in impulse purchase and consumption. Study 3, which excludes the content factors fully mediated by influencer factors, examines the impact of the live streaming influencer and the shopping platform on perceived value and food well-being. A cross-sectional survey of 630 respondents finds that channel factors (food product offerings and convenience) and influencer factors (credibility and parasocial relationship) significantly enhance consumers’ perceived value, leading to impulse purchase and overconsumption. The authors provide theoretical and practical implications to enrich future research and responsible business practices in online food marketing.
Dielectric Resonator Reflectarray as High-Efficiency Nonuniform Terahertz Metasurface

Advances in terahertz technology rely on the combination of novel materials and designs. As new devices are demonstrated to address the terahertz gap, the ability to perform high-efficiency beam control will be integral to making terahertz radiation a practical technology. Here, we use a metasurface composed of nonuniform dielectric resonator antennas on a ground plane to achieve efficient beam focusing at 1 THz. The dielectric resonators are made of high-resistivity silicon, which is a low-loss, nondispersive material for terahertz waves. The resonators operate around the resonance of the displacement current in the silicon, which is crucial to attaining high efficiency. The reflectarray’s capacity to focus terahertz radiation is experimentally verified, and hence by the principle of antenna reciprocity, it can also be employed as a terahertz collimator. The demonstrated device can therefore be deployed for high-gain terahertz antennas. Further measurements show that the loss of the reflectarray is negli.
Strong ferromagnetism induced by canted antiferromagnetic order in double perovskite iridates (La1−xSrx)2ZnIrO6

Iridates represent a unique material system that possesses both strong spin-orbit coupling and electron correlation. The interplay between spin-orbit coupling and correlation could facilitate the emergence of novel electronic and magnetic states. In this work, we report on a systematic study of magnetism in the double perovskite iridate ${\mathrm{La}}_{2}{\mathrm{ZnIrO}}_{6}$ and its hole-doped compounds $({\mathrm{La}}_{1\ensuremath{-}x}{\mathrm{Sr}}_{x}){}_{2}{\mathrm{ZnIrO}}_{6}$ via dc magnetization measurement, heat capacity characterization, electron spin resonance spectroscopy, and simple modeling. Undoped ${\mathrm{La}}_{2}{\mathrm{ZnIrO}}_{6}$ undergoes two magnetic transitions, at ${T}_{1}\ensuremath{\sim}7.3$ K and ${T}_{2}\ensuremath{\sim}8.5$ K, respectively. While magnetic hysteresis loops with large remnant moments are observed below these two transition temperatures, the corresponding magnetic states are shown to be canted antiferromagnetic by the linear increase in magnetization in the high field region along with the observation of antiferromagnetic resonance. The nature of the canted antiferromagnetic states with large canting angles can be understood by a simple model that includes both the Heisenberg exchange interaction and the Dzyaloshinskii-Moriya interaction. With the introduction of ${\mathrm{Ir}}^{5+}$ by ${\mathrm{Sr}}^{2+}$ doping, the canted antiferromagnetic phases are suppressed, accompanied by an enhancement of electrical conductivity.
High-Throughput Polynomial Multiplier for Accelerating Saber on FPGA

Saber was once one of the most promising candidates for the post-quantum cryptography standardization, which relies on lattice-based hard mathematical problems. Polynomial multiplication is time-consuming within the Saber architecture and there is still a lack of designs targeting the high throughput applications whose parameters support Schoolbook polynomial multiplier. In this brief, we propose a high-performance Schoolbook polynomial multiplier with a balanced hardware efficiency. The Schoolbook algorithm is transformed into a Toeplitz matrix-vector product, and its symmetry is exploited to reconstruct the Schoolbook multiplier to satisfy the need for high parallelism. Combined with compact data loading structure and a centralizing multiplication, the multiplier achieves <inline-formula> <tex-math notation="LaTeX">$3.33\times $ </tex-math></inline-formula> higher throughput and <inline-formula> <tex-math notation="LaTeX">$1.58\times $ </tex-math></inline-formula> higher throughput-per-slice compared with the state-of-the-art implementation of polynomial multiplier for Saber on Xilinx FPGA. The experimental results also demonstrate that the proposed structure provides a better trade-off between performance and area.
Characterization of Delonix regia Flowers’ Pigment and Polysaccharides: Evaluating Their Antibacterial, Anticancer, and Antioxidant Activities and Their Application as a Natural Colorant and Sweetener in Beverages

In the present study, an attempt was made to investigate the in vitro antioxidant, anticancer, and antibacterial activities of Delonix regia, then in vivo evaluate its safety as a natural colorant and sweetener in beverages compared to synthetic colorant and sweetener in rats, then serve the beverages for sensory evaluation. Delonix regia flowers had high protein, polysaccharide, Ca, Na, Mg, K, and Fe contents. The Delonix regia pigment extract (DRPE) polysaccharides were separated and purified by gel permeation chromatography on Sephacryl S-200, characterized by rich polysaccharides (13.6 g/L). The HPLC sugar profile detected the monosaccharides in the extracted polysaccharides, composed of mannose, galactose, glucose, arabinose, and gluconic acid, and the structure of saccharides was confirmed by FTIR, which showed three active groups: carbonyl, hydrocarbon, and hydroxyl. On the other hand, the red pigment constituents of DRPE were detected by HPLC; the main compounds were delphinidin and cyanidin at 15 µg/mL. The DRPE contained a considerable amount (26.33 mg/g) of anthocyanins, phenolic compounds (64.7 mg/g), and flavonoids (10.30 mg/g), thus influencing the antioxidant activity of the DRPE, which scavenged 92% of DPPH free radicals. Additionally, it inhibited the population of pathogenic bacteria, including Staphylococcus aureus, Listeria monocyogenes, Salmonella typhimurum, and Pseudomonas aeruginosa, in the range of 30–90 μg/mL, in addition to inhibiting 85% of pancreatic cancer cell lines. On the in vivo level, the rats that were delivered a diet containing DRPE showed regular liver markers (AST, ALP, and ALT); kidney markers (urea and creatinine); high TP, TA, and GSH; and low MDA, while rats treated with synthetic dye and aspartame showed higher liver and kidney markers; lowered TP, TA, and GSH; and high MDA. After proving the safety of DRPE, it can be safely added to strawberry beverages. Significant sensorial traits, enhanced red color, and taste characterize the strawberry beverages supplemented with DRPE. The lightness and redness of strawberries were enhanced, and the color change ΔE values in DRPE-supplemented beverages ranged from 1.1 to 1.35 compared to 1.69 in controls, indicating the preservative role of DRPE on color. So, including DRPE in food formulation as a natural colorant and sweetener is recommended for preserving health and the environment.
Study of different hydrographic variables at Ennore and Chennai fisheries harbour region of Chennai, India

The knowledge of hydrographic variables is very important in determining the abundant availability of fishes in a particular region. The study site selected includes an industrially polluted area, Ennore and Chennai fisheries harbour region. The hydrographic variables selected for study includes temperature, salinity, pH, dissolved oxygen, chlorophyll a, b and c, primary productivity, gross and net and the nutrients, phosphate, ammonia and nitrate. The important hydrographic variables and its effect on the region and that influence the fish abundance throughout the year are discussed. At Ennore, the salinity level was maximum during the month of July, 37.00 ppt at a lowest temperature of 27.00 °C and at a highest temperature of 31.00 °C in the month of Sept’09, the salinity level was 32.00 ppt. At Chennai fisheries harbour, the lowest temperature recorded was 26.40 ºC at Jan’09 and the highest temperature was 30.0 ºC at April’09, lowest salinity level was 26.80 ppt at Feb’09 and highest salinity level was 38.50 ppt at July’09. The variations among months and from 2 different locations viz. Ennore and Chennai Fisheries harbour were studied during the entire year. The interaction effects between the two locations were also studied. Temperature, salinity, chlorophyll a, b and c primary productivity, gross and net are non significant p0.05 at Ennore and at Chennai Fisheries harbour location. The response optimization of the different hydrographic variables viz. temperature, 28.14 °C, salinity, 30.80 ppt, pH, 6.37, dissolved oxygen, 3.12 ml/l, and total soluble solids, 0.40 mg/l for a predicted response of chlorophyll a of 3.35mg/m3 at Ennore and at Chennai Fisheries harbour region the hydrographic variables viz. temperature, 30.00 °C, salinity, 26.80 ppt, pH, 6.38 dissolved oxygen, 2.86 ml/l and total soluble solids of 0.40 mg/l for a predicted chlorophyll a response of 1.88mg/m3 were worked out.
D2IFLN: Disentangled Domain-Invariant Feature Learning Networks for Domain Generalization

Domain generalization (DG) aims to learn a model that generalizes well to an unseen test distribution. Mainstream methods follow the domain-invariant representational learning philosophy to achieve this goal. However, due to the lack of priori knowledge to determine which features are domain specific and task-independent, and which features are domain invariant and task relevant, existing methods typically learn entangled representations, limiting their capacity to generalize to the distribution-shifted target domain. To address this issue, in this article, we propose novel disentangled domain-invariant feature learning networks (D2IFLN) to realize feature disentanglement and facilitate domain-invariant feature learning. Specifically, we introduce a semantic disentanglement network and a domain disentanglement network, disentangling the learned domain-invariant features from both domain-specific class-irrelevant features and domain-discriminative features. To avoid the semantic confusion in adversarial learning for domain-invariant feature learning, we further introduce a graph neural network to aggregate different domain semantic features during model training. Extensive experiments on three DG benchmarks show that the proposed D2IFLN performs better than the state of the art.