Miracle-dz/UniFAR-FTUs huggingface dataset:
Securing Smart Home IoT Network Against DNS Flooding Attack using P4

The rapid growth of the Internet of Things (IoT) has raised the possibility of various security attacks, including the VPNFilter, Mirai, and DNS flooding attacks. DNS has recently been a significant part of the smart home IoT infrastructure. Despite this, DNS traffic is primarily unencrypted, making it easy for adversaries to launch DNS flooding attacks. Particularly in highspeed networks, the DNS flooding attack detection mechanisms might become bottlenecks and are vulnerable to saturation attacks. The recent development of a Programmable Data Plane (PDP) can implement several security approaches at a line rate. This paper proposes a DNS flooding attack detection and mitigation framework for IoT networks by leveraging PDP. The proposed framework first recognizes DNS traffic flows by analyzing header field values of incoming IoT traffic. Subsequently, the DNS traffic rate is monitored by adjusting the threshold dynamically. Specifically, the Additive Increase and Multiplicative Decrease (AIMD) algorithm varied the threshold in real time, enhancing the detection capabilities of DNS flooding attacks within the PDP. After detecting the attack, drop the DNS traffic flows immediately to mitigate the attack. Further, the evaluation results show that the proposed framework reduces the DNS response time to 93.54%. Additionally, the proposed solution achieves high throughput of 89.101Mbps.
Implementation of medical image retrieval algorithm based on preference learning model

This paper utilizes the Stacked Denoising Auto Encoder (SDAE) model to capture the general edge features of images. Additionally, it employs the Convolutional Neural Networks model to extract fine edge features from medical images. By combining preference learning algorithms, the paper implements an image retrieval system and designs a medical image retrieval model termed SDAE+CNN+Preference Learning. In the design of the reconstruction residual function in the SDAE model, noise factors are introduced to ensure the accuracy of image feature extraction by accounting for the impact of noise. Adjustments have been made to the structure of the CNN model, specifically in the convolutional layers, pooling layers, and fully connected layers. These adjustments aim to further enhance the accuracy of image feature extraction and ensure the precision of image feature classification. By conducting learning training on key parameters, an optimal preference learning model is obtained. Following the rules for matching the category attributes of input images with those in the medical image database and optimizing the loss function of the preference learning model, the similarity of category attributes for images is ranked. Ultimately, images with higher category attribute similarity are listed as retrieval results. Relevant experiments indicate that the proposed SDAE+CNN image feature extraction module in this paper achieves high accuracy in extracting image features, effectively controlling the influence of image noise; The designed SDAE+CNN+Preference Learning medical image retrieval model achieves a retrieval similarity of 96%, a retrieval accuracy of 94%, and a retrieval recall rate of 95%, as per the conducted experiments.
FRACTAL ANALYSIS OF THE PORES IN AISI316L SS IMPLANTED WITH OXYGEN AND HELIUM IONS

Fractal analysis is used to numerically characterize the pores in AISI316L stainless steel to be able to study the shape, distribution and type of the pores. The fractal analysis uses two dimensionless parameters: fractal dimension D and Sphericity, β. The AISI316L stainless steel is widely used in medical field as an implant material due to its good corrosion resistance and biocompatibility. In this work AISI316L, stainless steel was implanted with two different ions: Oxygen and Helium separately at 100KeV with dose of 1×10 17 ions/cm 2 at room temperature. The crystallographic orientation and surface morphology were studied using x-ray diffraction analysis (XRD). The micro hardness was measured by Vickers method with varying load. The result indicated that the predominant pores in the virgin material are of spherical shapes with β 1. It was further observed that the pores are flake like type and clustered, thereby creating ease of linkage of the pores. The ion implantation showed a reduction in the pores, predominantly noodle-like types, (i.e. a shape change from spherical to round pores) and change in distribution from clustered to randomly spaced pores. The surface hardness is found to be 1202HV, 1020HV and 195HV for Helium, Oxygen and Virgin material respectively. There is a significant improvement in the shape, type, and distribution of the pores in AISI316L stainless steel implanted with Oxygen and Helium. The Vickers hardness test shows that the micro hardness of AISI316L stainless steel implanted with Oxygen and Helium is higher than that of the virgin material.
A new nucleotide-excision-repair gene associated with the disorder trichothiodystrophy.

The sun-sensitive, cancer-prone genetic disorder xeroderma pigmentosum (XP) is associated in most cases with a defect in the ability to carry out excision repair of UV damage. Seven genetically distinct complementation groups (i.e., A-G) have been identified. A large proportion of patients with the unrelated disorder trichothiodystrophy (TTD), which is characterized by hair-shaft abnormalities, as well as by physical and mental retardation, are also deficient in excision repair of UV damage. In most of these cases the repair deficiency is in the same complementation group as is XP group D. We report here on cells from a patient, TTD1BR, in which the repair defect complements all known XP groups (including XP-D). Furthermore, microinjection of various cloned human repair genes fails to correct the repair defect in this cell strain. The defect in TTD1BR cells is therefore in a new gene involved in excision repair in human cells. The finding of a second DNA repair gene that is associated with the clinical features of TTD argues strongly for an involvement of repair proteins in hair-shaft development.
Persepsi Nasabah terhadap Aplikasi M-Banking pada Bank Swasta dan Bank Pemerintah

Information and communication technology has revolutionized the banking sector and at its peak during the Covid 19 pandemic, most transactions can be carried out without the need to visit a bank and using mobile banking applications. In Indonesia, there are two banks that are most popular in using m-banking, m-BCA which is managed by a private bank and Livin by Mandiri which is managed by a state-owned company. The aim of this research is to analyze whether there are differences of trust, service quality and perceived risk on customer satisfaction in private and government managed m-Banking. The research method uses a quantitative approach based on data collected through online surveys. There are 180 active m-Banking customers with generation Z and Millennial demographics, students and productive workers. The results show that the factors that influence customer satisfaction in using m-Banking lie in the aspects of service quality and trust, while perceived risk has no effect. Furthermore, differences in the influence of m-banking application service quality determine customer satisfaction. Where, m-BCA customers are relatively more satisfied because the service is in accordance with the promises, transaction speed, security, attractive visual appearance, the application is more responsive and easier than the Livin by Mandiri. For generation Z and millennials, the use of digital banking applications is more influenced by the application's ability to meet transaction needs rather than threat factors such as the speed of computing personal data, cyber-crime and bank system errors.
Signs of proinflammatory/genotoxic switch (adipogenotoxicosis) in mammary fat of breast cancer patients: Role of menopausal status, estrogens and hyperglycemia

The abundance of fat tissue surrounding normal and malignant epithelial mammary cells raises the questions whether such “adipose milieu” is important in the local proinflammatory/genotoxic shift, which apparently promotes tumor development and worsens prognosis, and what conditions stimulate this shift, or “adipogenotoxicosis. ” We studied 95 mammary fat samples from 70 postmenopausal and 25 premenopausal breast cancer (BC) patients at a distance of 1.5–2.0 cm from tumors. The levels of leptin, adiponectin, TNFα and IL‐6 release after 4‐hr incubation of the samples were evaluated with ELISA, nitric oxide (NO) production by Griess reaction and lipid peroxidation by determination of thiobarbiturate‐reactive products (TBRP). Infiltration of fat with macrophages (CD68‐positive cells) and expression of cytochrome P450 1B1/estrogen 4‐hydroxylase (CYP1B1) were detected by immunohistochemistry. Aromatase (CYP19) activity in mammary fat was measured by 3H2O release from 3H‐1β‐androstenedione. In the postmenopausal BC patients, NO and TNFα production by adipose tissue explants increased independent of BMI and in parallel with decreasing leptin and, especially, adiponectin release. In the premenopausal patients, higher CYP1B1 expression and TBRP level were found in mammary fat, while higher aromatase activity was combined with higher CYP1B1 expression as well as NO and IL‐6 production. In the postmenopausal group, impaired glucose tolerance was associated with higher IL‐6 release production by fat and with higher IL‐6/adiponectin ratio. Thus, signs of adipogenotoxicosis in mammary fat can be found in both pre‐ and postmenopausal BC patients. This condition is likely being maintained through estrogen‐ and glucose‐related factors and mechanisms presumably associated with less favorable types of hormonal carcinogenesis. © 2007 Wiley‐Liss, Inc.
Surface Defect Detection Based on Label Reassembling

Owing to the complexity of surface defect morphologies, deep learning framework-based algorithms are usually able to obtain higher accuracy compared to traditional methods with hand-crafted features and gradually attract researchers' attention. However, considering the existing defect image data sets are usually small samples, overfitting is particularly liable to occur when the general classification model is adopted directly. To tackle this problem, we present a label reassembling-based surface defect detection. Specifically, the original label is reassigned to constructing a multi-task learning model, where the recombined label corresponds to the upstream auxiliary task to alleviate the overfitting problem. Finally, the experimental results on public datasets indicate that the improved method can reach better performance compared with MobileNetV2 which is used as the base model in this paper.
Curd, seed yield and disease resistance of cauliflower are enhanced by oligosaccharides

Background Oligosaccharides have been demonstrated as promoters for enhancing plant growth across several crops by elevating their secondary metabolites. However, the exploration of employing diverse oligosaccharides for qualitative trait improvements in cauliflower largely unknown. This study was intended to uncover the unexplored potential, evaluating the stimulatory effects of three oligosaccharides on cauliflower’s curd and seed production. Methods Two experiments were initiated in the early (15 September) and mid-season (15 October). Four treatments were implemented, encompassing a control (water) alongside chitosan oligosaccharide (COS 50 mg.L–1) with a degree of polymerization (DP) 2–10, oligo galacturonic acid (OGA 50 mg.L−1) with DP 2–10 and alginate oligosaccharide (AOS 50 mg.L−1) with DP 2–7. Results Oligosaccharides accelerated plant height (4–17.6%), leaf number (17–43%), curd (5–14.55%), and seed yield (17.8–64.5%) in both early and mid-season compared to control. These enhancements were even more pronounced in the mid-season (7.6–17.6%, 21.37–43%, 7.27–14.55%, 25.89–64.5%) than in the early season. Additionally, three oligosaccharides demonstrated significant disease resistance against black rot in both seasons, outperforming the control. As a surprise, the early season experienced better growth parameters than the mid-season. However, performance patterns remained more or less consistent in both seasons under the same treatments. COS and OGA promoted plant biomass and curd yield by promoting Soil Plant Analysis Development (SPAD) value and phenol content. Meanwhile, AOS increased seed yield (56.8–64.5%) and elevated levels of chlorophyll, ascorbic acid, flavonoids, while decreasing levels of hydrogen per oxide (H2O2), malondialdehyde (MDA), half maximal inhibitory concentration (IC50), and disease index. The correlation matrix and principal component analysis (PCA) supported these relations and findings. Therefore, COS and OGA could be suggested for curd production and AOS for seed production in the early season, offering resistance to both biotic and abiotic stresses for cauliflower cultivation under field conditions.
Statistically measuring the amount of pitch angle scattering that energetic electrons undergo as they drift across the plasmaspheric drainage plume at geosynchronous orbit

Using five spacecraft in geosynchronous orbit, plasmaspheric drainage plumes are located in the dayside magnetosphere and the measured pitch angle anisotropies of radiation belt electrons are compared duskward and dawnward of the plumes. Two hundred twenty‐six plume crossings are analyzed. It is found that the radiation belt anisotropy is systematically greater dawnward of plumes (before the electrons cross the plumes) than it is duskward of plumes (after the electrons have crossed the plumes). This change in anisotropy is attributed to pitch angle scattering of the radiation belt electrons during their passage through the plumes. A test database in the absence of plumes finds no equivalent change in the radiation belt anisotropy. The amount of pitch angle scattering by the plume is quantified, scattering times are estimated, and effective pitch angle diffusion coefficients within the plume are estimated. The pitch angle diffusion coefficients obtained from the scattering measurements are of the same magnitude as expected values for electromagnetic ion cyclotron (EMIC) waves at high electron energies (1.5 MeV); however, expected EMIC diffusion coefficients do not extend to pitch angles of 90° and would have difficulties explaining the observed isotropization of electrons. The pitch angle diffusion coefficients obtained from the scattering measurements are of the same magnitude as expected values for whistler mode hiss at lower electron energies (150 keV). Outward radial transport of the radiation belt caused by the pitch angle scattering in the plume is discussed.
Multiple Time Scale Variability of the Sea Surface Salinity Dipole Mode in the Tropical Indian Ocean

AbstractIn this study, multiple time scale variability of the salinity dipole mode in the tropical Indian Ocean (S-IOD) is revealed based on the 57-yr Ocean Reanalysis System 4 (ORAS4) sea surface salinity (SSS) reanalysis product and associated observations. On the interannual time scale, S-IOD is highly correlated with strong Indian Ocean dipole (IOD) and ENSO variability, with ocean advection forced by wind anomalies along the equator and precipitation anomalies in the southeastern tropical Indian Ocean (IO) dominating the SSS variations in the northern and southern poles of the S-IOD, respectively. S-IOD variability is also associated with the decadal modulation of the Indo-Pacific Walker circulation, with a stronger signature at its southern pole. Decadal variations of the equatorial IO winds and precipitations in the central IO force zonal ocean advection anomalies that contribute to the SSS variability in the northern pole of S-IOD on the decadal time scale. Meanwhile, oceanic dynamics dominates th.
Epigenetic Aspects of Posttraumatic Stress Disorder

Development of psychiatric diseases such as posttraumatic stress disorder (PTSD) invokes, as with most complex diseases, both genetic and environmental factors. The era of genome-wide high throughput technologies has sparked the initiation of genotype screenings in large cohorts of diseased and control individuals, but had limited success in identification of disease causing genetic variants. It has become evident that these efforts at the genomic level need to be complemented with endeavours in elucidating the proteome, transcriptome and epigenetic profiles. Epigenetics is attractive in particular because there is accumulating evidence that the lasting impact of adverse life events is reflected in certain covalent modifications of the chromatin. In this review, we outline the characteristics of PTSD as a stress-related disease and survey recent developments revealing epigenetic aspects of stress-related disorders in general. There is also increasing direct evidence for gene programming and epigenetic components in PTSD. Finally, we discuss treatment options in the light of recent discoveries of epigenetic mechanisms of psychotropic drugs.
Nursing Educational Program for Improving Older Persons' Hydration Status

Background: Dehydration is a serious public health concern occurred due to the imbalance between water intake and loss which increased in the climate change and Egypt's hot weather, lead to the morbidity and mortality rate raise among the older persons. Aim: To evaluate the effect of nursing educational program for improving older persons' hydration status. Subjects and Method: One group pre-post intervention research design. Setting: The study conducted at the (internal medicine and urology) clinics at the Assuit University hospitals. Sample: Total number of 130 older persons was included. Study tools: Contained four tools; Tool (I): Consisted of four parts; personal data, El-Gilany scale for measurement of socioeconomic status, health condition and knowledge of older persons regarding dehydration. Tool (II): Dehydration screening. Tool (III): Hydration knowledge scale and Tool (IV): Hydration facilitators and barriers attitude. Results: Mean ± SD and (range) of participant age: 69.28±7.65 (60-91). It was found that, more than half (56.9% &53.1% respectively) of them were male and had very low socioeconomic status. There was statistically significant effect of the educational program on the older persons' dehydration status; also there was improvement of older person's hydration & dehydration knowledge and attitude of older persons about hydration facilitators and barriers after the application of the educational program. Conclusion and recommendations : These results support that the nursing educational program improved the hydration status, hydration & dehydration knowledge and attitude toward hydration facilitators and barriers among older persons. Continuous educational programs about hydration status of older persons are recommended.
Ontological User Profiles for Personalized Web Search

The goal of Web search personalization is to tailor search results to a particular user based on that user’s interests and preferences, thus allowing for more efficient information access. One of the key factors for effective personalization of information access is the user context. We present an approach to personalized search that involves building models of users context as ontological profiles by assigning implicitly derived interest scores to existing concepts in a domain ontology. A spreading activation algorithm is used to maintain the interest scores based on the user’s ongoing behavior. Our experiments show that re-ranking the search results based on the interest scores and the semantic evidence in an ontological user profile is effective in presenting the most relevant results to the user.
Design Optimization in Automotive Product Development Using AI/ML Algorithms

The use of physical testing and simulation process for product development of effective design is a well-established practice in industry. Engineers rely on this process to explore the feasible design space and optimize product for future design configurations. Designers and researchers can use the data from existing designs to develop future designs. In this context, this paper presents an effective solution by using physical test and simulation data for day-to-day design problems such as Plastic Snap design and Chassis Section deflection. A high degree of accuracy is achieved in validating test data using machine learning algorithms. By using ML algorithms in product design, we can optimize the parameters in a shorter time & reduce development cost.
Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients

A decrease in the abundance and biodiversity of intestinal bacteria within the dominant phylum Firmicutes has been observed repeatedly in Crohn disease (CD) patients. In this study, we determined the composition of the mucosa-associated microbiota of CD patients at the time of surgical resection and 6 months later using FISH analysis. We found that a reduction of a major member of Firmicutes, Faecalibacterium prausnitzii, is associated with a higher risk of postoperative recurrence of ileal CD. A lower proportion of F. prausnitzii on resected ileal Crohn mucosa also was associated with endoscopic recurrence at 6 months. To evaluate the immunomodulatory properties of F. prausnitzii we analyzed the anti-inflammatory effects of F. prausnitzii in both in vitro (cellular models) and in vivo [2,4,6-trinitrobenzenesulphonic acid (TNBS)-induced] colitis in mice. In Caco-2 cells transfected with a reporter gene for NF-κB activity, F. prausnitzii had no effect on IL-1β-induced NF-κB activity, whereas the supernatant abolished it. In vitro peripheral blood mononuclear cell stimulation by F. prausnitzii led to significantly lower IL-12 and IFN-γ production levels and higher secretion of IL-10. Oral administration of either live F. prausnitzii or its supernatant markedly reduced the severity of TNBS colitis and tended to correct the dysbiosis associated with TNBS colitis, as demonstrated by real-time quantitative PCR (qPCR) analysis. F. prausnitzii exhibits anti-inflammatory effects on cellular and TNBS colitis models, partly due to secreted metabolites able to block NF-κB activation and IL-8 production. These results suggest that counterbalancing dysbiosis using F. prausnitzii as a probiotic is a promising strategy in CD treatment.
Lung Field Segmentation in Chest Radiographs From Boundary Maps by a Structured Edge Detector

Lung field segmentation in chest radiographs (CXRs) is an essential preprocessing step in automatically analyzing such images. We present a method for lung field segmentation that is built on a high-quality boundary map detected by an efficient modern boundary detector, namely a structured edge detector (SED). A SED is trained beforehand to detect lung boundaries in CXRs with manually outlined lung fields. Then, an ultrametric contour map (UCM) is transformed from the masked and marked boundary map. Finally, the contours with the highest confidence level in the UCM are extracted as lung contours. Our method is evaluated using the public Japanese Society of Radiological Technology database of scanned films. The average Jaccard index of our method is 95.2%, which is comparable with those of other state-of-the-art methods (95.4%). The computation time of our method is less than 0.1 s for a $256\,\times \,256$ CXR when executed on an ordinary laptop. Our method is also validated on CXRs acquired with different digital radiography units. The results demonstrate the generalization of the trained SED model and the usefulness of our method.