Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Development of a Deep Learning-Based Model for Anomaly Detection in IoT Networks

The growing development of IoT (Internet of Things) devices creates a large attack surface for cybercriminals to conduct potentially more destructive cyberattacks; as a result, the security industry has seen an exponential increase in cyber-attacks. Many of these attacks have effectively accomplished their malicious goals because intruders conduct cyber-attacks using novel and innovative techniques. An anomaly-based IDS (Intrusion Detection System) uses machine learning techniques to detect and classify attacks in IoT networks. In the presence of unpredictable network technologies and various intrusion methods, traditional machine learning techniques appear inefficient. In many research areas, deep learning methods have shown their ability to identify anomalies accurately. Convolutional neural networks are an excellent alternative for anomaly detection and classification due to their ability to automatically categorize main characteristics in input data and their effectiveness in performing faster computations. In this paper, we design and develop a novel anomaly-based intrusion detection model for IoT networks. First, a convolutional neural network model is used to create a multiclass classification model. The proposed model is then implemented using convolutional neural networks in 1D, 2D, and 3D. The proposed convolutional neural network model is validated using the BoT-IoT, IoT Network Intrusion, MQTT-IoT-IDS2020, and IoT-23 intrusion detection datasets. Transfer learning is used to implement binary and multiclass classification using a convolutional neural network multiclass pre-trained model. Our proposed binary and multiclass classification models have achieved high accuracy, precision, recall, and F1 score compared to existing deep learning implementations.
Dynamic Power Electronic Load Model for Transient Stability Analyses

In this paper a dynamic power electronic load model for transient stability analyses is developed, especially for voltage stability investigations. Since the share of power electronic loads increases and their impact on stability in the phasor domain is rarely or insufficiently investigated, e.g. with constant loads, the need for appropriate dynamic model rises. Based on a detailed component-based approach, a dynamic model is developed in this work, where only the grid voltage is an input to calculate its fundamental power response. Furthermore, the calculation is based only on analytical expressions for computational efficiency. As the comparison with the detailed model shows, the power response of the developed models is accurate. In addition, an inclusion in transient stability programs is proposed to deal with different simulation step sizes. Concluding, a use case of the developed model shows that power electronic loads have a decisive impact on short and long-term voltage stability.
Al4SiC4 wurtzite crystal: Structural, optoelectronic, elastic, and piezoelectric properties

New experimental results supported by theoretical analyses are proposed for aluminum silicon carbide(Al4SiC4). A state of the art implementation of the density functional theory is used to analyze the experimental crystal structure, the Born charges, the elastic properties, and the piezoelectricproperties. The Born charge tensor is correlated to the local bonding environment for each atom. The electronic band structure is computed including self-consistent many-body corrections. Al4SiC4material properties are compared to other wide band gap wurtzite materials. From a comparison between an ellipsometry study of the optical properties and theoretical results, we conclude that the Al4SiC4material has indirect and direct band gapenergies of about 2.5 eV and 3.2 eV, respectively.
Flood Vulnerability Assessment in Kilembe, Uganda

On a global basis, there is evidence that the number of people affected by floods are on the rise. This research study assessed the level of community exposure, sensitivity and resilience and the households’ risks perceptions to floods in Kilembe. The research design for this study involved an index-based approach. The primary data was obtained using a semi-structured questionnaire, 194 households were purposefully selected. The study revealed that the community was highly exposed to floods. About 43.3% of the households were found living less than two kilometres from the flooding river. The households were also found highly susceptible to flood hazards with 78.9% of the households had a monthly average income of about US$52. However, the community had high capacities to cope with the effects of flood hazards. Only 17.0% of the households surveyed had gone to the local authority for assistance in the last 1 year. About 98.5% of the households thought that the frequency of occurrence and impacts of flooding had increased during the last decade, and 74.4% of the households felt very worried about the floods. The government should install early warning system, ensure active participation of the local communities, and timely and adequately respond to floods.
Modelling the speciation pattern of metals in Ondo coastal water with geochemical model – PHREEQCI

The speciation pattern of ten metals was studied in the coastal water of Ondo State, Nigeria using geochemical modelling software (PHREEQCI). The metals classified as macronutrients – Na, Ca, K, Mg; micronutrients – Fe, Cu, Mn, Zn; toxic metals – Cd, Pb were evaluated along with other general water quality parameters from ten sampling sites. The results served as input data for the modelling. The outcomes of the water speciation modelling revealed that the macronutrient metals exist as free ions which aid the reduction of free ion species of toxic metals. The micronutrients exist as neutral or complex salts which are less toxic according to free ion activity model theory. The self purification capacity of the coastal water was aided by the abundant formation of Fe-hydroxide precipitates; high alkalinity; pH; salinity of the coastal water which are responsible for the reduction of free ion specie of Pb and its ecotoxicity but increased the concentration of toxic Cd chloride species. Therefore, the prevailing biogeochemistry of the coast enhances demobilization of the metal contaminants and favours the reduction of their toxicity except Cd.
Adsorption of polycyclic aromatic hydrocarbons from wastewater by using silica-based organic–inorganic nanohybrid material

Polycyclic aromatic hydrocarbons (PAHs) are a group of priority pollutants, which are classified as persistent hazardous contaminants. Herein, the adsorption of three PAHs, naphthalene (NAP), acenaphthylene (ACN), and phenanthrene (PHN), from wastewater onto NH 2 -SBA-15 organic–inorganic nanohybrid material as a function of pH of the media (2–10), sorbent dosage (0.5–3.5 g L −1 ), PAH concentration (1–18 mg g −1 ), and temperature (25–45 °C) were elucidated. The prepared adsorbents were characterized by scanning electron microscope, transmission electron microscopy, X-ray diffractions, and thermogravimetric analysis. Among Langmuir, Freundlich, and Temkin isotherms models, it was found that the Langmuir model gave an excellent overall fit ( R 2 > 0.97). The maximum adsorption capacity of 1.92, 1.41, and 0.76 mg g −1 was obtained for NAP, ACN, and PHN, respectively. Adsorption kinetics of PAHs onto NH 2 -SBA-15 was in accordance with the pseudo-second-order model, providing evidence that pore mass transferring was involved. PAHs9 adsorption was strongly dependent on temperature, and confirmed the spontaneous and endothermic nature of the process. The optimized sorption condition was successfully applied to the real petroleum refinery wastewater samples and the adsorption capacity of NH 2 -SBA-15 was satisfactory for PAHs9 studies as 1.67, 1.06, and 0.24 mg g −1 for NAP, ACN and PHN, respectively. Furthermore, reusability was successfully tested by five sequential recoveries.
Indomethacin : Capillary gas chromatographic-electron capture detection analysis and pharmacokinetic studies in the fetal lamb

Indomethacin is currently used in the treatment of patent ductus arteriosus, preterm labour, and for polyhydramnios. In order to investigate its clearance and disposition in the chronically instrumented ovine fetus, a sensitive assay was required. The developed GC-ECD method involves the extraction of indomethacin and a-methyl indomethacin, the internal standard, from acidified plasma, urine, amniotic and tracheal fluids using a simple one-step liquid-liquid extraction procedure with ethyl acetate. The organic extract is evaporated and the residue derivatised with N-methyl-N-(tert-butyldimethylsilyl)-trifluoroacetamide (MTBSTFA). The derivatised samples were reconstituted with toluene and aliquots of 2 jxL injected into the GC. Calibration curves were linear over the working range of 1-32 ng of indomethacin/mL with a coefficient of determination (r ) > 0.99, following extraction of 0.1 mL of plasma, and 0.1-1.0 mL of urine, amniotic and tracheal fluids. Mean recoveries from plasma and urine were 96.99 ± 9.25 % and 94.74 ± 6.75 %, respectively. The limit of quantitation is 1 ng/mL (< 10% C.V., S/N > 10). Interand intra-day variabilities at each concentration point were < 11 % for concentrations between 2-32 ng/mL and < 20 % at the LOQ of 1 ng/mL.
Appendix for: 3D Self-Supervised Methods for Medical Imaging

It is noteworthy that our attached implementations are flexible enough to allow for evaluating several types of network architectures for encoders, decoders, and classifiers. We also provide implementations for multiple losses, augmentation techniques, and evaluation metrics. More information can be found in the README.md file in our attached code-base. We rely on tensorflow v2.1 [1] with Keras API in our implementations. Below, we provide the training details we used in implementing our 3D self-supervised tasks (and their 2D counterparts), and when fine-tuning them in subsequent downstream tasks.
Iris Localization Algorithm based on Effective Area

Iris localization is the most crucial part of the iris processing because its accuracy can directly affect the accuracy of biometric identification in subsequent steps. Yet, the quality of iris images may be sharply degraded due to interference from eyelashes and reflections during image acquisition, which can affect the localization accuracy adversely. To solve the problem, an iris localization algorithm based on effective area is proposed. First, YOLOv4 is used to crop the image to obtain the effective iris area, which is beneficial in improving the accuracy of subsequent localization. Furthermore, a method to remove reflective noise is proposed, which can effectively avoid the problem of noise interference in the process of inner boundary determination. Finally, aiming at the edge deviation caused by eyelashes, an outer boundary adjustment method is proposed. The experimental results show that the proposed method achieves good performance in the localization of iris images of both good quality and noise interference and outperforms other state-of-the-art methods.
Laser Micromachining-A Review

In the current manufacturing scenario, micromachining is state-of-the-art technology for precision manufacturing. Laser micromachining (LMM) utilizes a laser beam for producing complex shapes and miniature devices on any known material. This process eliminates the use of a physical tool, thereby reducing the problems of tool wear and minimizing the cutting forces on the work material. In LMM, material removal occurs by the localized heating, melting, and subsequent vaporization. Several process parameters govern the process and have a major influence on the machining quality. Therefore, investigating the optimal parameters for achieving the best machining quality is required. In this paper, an attempt is made to review the literature on Laser micromachining process optimization and the most focused process parameters and performance measures have been identified. Furthermore, an attempt is also made to recognize the most used on which LMM has been performed. Finally, this work tries to point out the process parameters, performance measures, materials, and machining operations which have future scope for research in Laser micromachining. IndexTerms Laser Micromachining, Heat affected zone (HAZ), Pulsed lasers, Pulse frequency
Are Active Labor Market Policies Directed at Firms Effective? Evidence from a Randomized Evaluation with Local Employment Agencies

We evaluate the effect of an innovative active labor market policy (ALMP) implemented by the French Public Employment Service (PES) that targeted the vacancy costs of thousands of small and medium sized firms. We find that this policy increased labor demand among treatment firms on average: a 24% increase in vacancy postings with the PES and a 10% increase in permanent contract hires of registered jobseekers, a large proportion of which were still in employment after 12 months. The increase in firm labor demand is consistent with a drop in vacancy costs due to a shift in the prescreening and filtering burden of the recruitment process away from the firm to the PES counselor. These results suggest that ALMPs directed at firm recruiting costs may be a valuable addition to the labor policy toolkit, yet theory and simulations illustrate that care must be taken when targeting future interventions of this type due to equilibrium effects.
Checklist of mammals from Goiás, central Brazil

The state of Goiás, in central Brazil, is covered mainly by the Cerrado domain, with the Alto Paraná Atlantic Forest occupying its central-southern portion. Goiás is one of the 20 Brazilian federative units without a mammal checklist. In this study, we provide the first checklist of mammals from Goiás state. We recorded mammal species based primarily on the analysis of specimens housed in scientific collections as well as on literature with associated voucher material. We listed 191 mammalian species belonging to 125 genera, 31 families and 10 orders, which represents 25.2% of the mammal species occurring in Brazil. The most speciose orders were Chiroptera (90 spp.), followed by Rodentia (43 spp.), Carnivora (19 spp.) and Didelphimorphia (17 spp.). The following orders accounted for a smaller portion of the state diversity: Cetartiodactyla (7 spp.), Cingulata (7 spp.), Primates (4 spp.), Pilosa (2 spp.), Lagomorpha (1 sp.), and Perissodactyla (1 sp.). A total of 28 species (14.7%), mainly represented by medium and large-sized mammals, are nationally threatened while 12 (6.3%) are globally threatened. Our results indicate great portions of the state lacking a proper survey of mammals, especially the northwestern portion. We discuss species richness, distribution and conservation status of the mammals of Goiás state in national and regional scenarios. We highlight the need for mammal inventories based on complementary survey techniques with the collection of vouchers in order to provide karyologic, molecular, morphologic, parasitologic, and ecological data. These informations are the basis for integrative studies that lead to the understanding of current mammalian richness and diversity. Indeed, knowledge on species richness distribution in the state will guide conservation strategies, especially in areas undergoing habitat loss and fragmentation, such as the central-southern portion of Goiás.
Vitamin D Status among Obese Children and Its Relation to Insulin Resistance

Background and Aims: We aimed to assess the relation between insulin resistance and serum 25hydroxy vitamin D (25[OH]D) levels in both obese and non-obese children. Methods and Results: This crosssectional study determined vitamin D levels of overweight children and their associations with insulin sensitivity, resistance, and glucose homeostasis. The study was conducted at the Childhood Obesity Clinic and Clinical Pathology Department, National Nutrition Institute, Cairo, Egypt, during January 1 2015 to June 1 2016. Obese participants had lower concentrations of 25(OH)D than non-obese participants but that was not notably different. The overweight group's 2-hour postprandial blood glucose level (2HRPP), fasting insulin, homeostatic model assessment of insulin resistance (HOMA-IR), and HOMA-B were all significantly higher than the control group's values, and then were linked to adiposity measures. Fasting blood sugar and hemoglobin A1c showed no statistically relevant differences in between the obese and non-obese groups. In the overweight group, 25(OH)D deficiency, insufficiency, and sufficiency (25[OH]D < 20 ng/dl, < 30, >20 ng/dl; ≥30 ng/dl, respectively) were not linked with insulin sensitivity or resistance indices. Blood pressure was positively associated with adiposity indices. Conclusion: The study showed no notably difference in vitamin D status among obese and normal, non-obese participants, but there was significant difference between obese and normal weight subjects regarding insulin sensitivity and resistance. Measures and 2-hour postprandial blood glucose level (insulin sensitivity and resistance indices were related to adiposity indices) and the increase in systolic and diastolic blood pressure was related to adiposity indices and insulin resistance. [Sayed A. Amin, Ahmed M. Abd El Moktader, Esam El Din Gad El Rab, Hala M. Abd El Salam, Mona E. Ahmed. Vitamin D Status among Obese Children and Its Relation to Insulin Resistance Am Sci 2021;17(6):30-39]. ISSN 15451003 (print); ISSN 23757264 (online). http://www.jofamericanscience. org 4.doi:10.7537/marsjas190621.04.
Amplification of Surface Plasmon Coupled Emission from Graphene–Ag Hybrid Films

Surface plasmon coupled emission (SPCE) is a novel analytical technique in which the isotropic emission of a fluorophore is combined with the surface plasmon resonance of a Ag (or Au) thin film to yield highly directional emission from the so-called plasmaphore and thus greatly increased sensitivity. Here we report a 40-fold amplification of rhodamine B (RhB) fluorophore when graphene is used as the spacer layer in a conventional Ag-based SPCE setup. In addition to protecting the Ag thin film from oxidation, the highly impermeable graphene facilitated π–π stacking interactions with the RhB molecules that resulted in an efficient radiated emission from the plasmaphore. In addition, we found that the plasmaphore emission was more sensitively dependent on the in-plane crystallinity (measured by coherence length La) of the graphene spacer layer than its thickness. This study describes the unique features of graphene as a spacer layer for SPCE-based analytical platforms and its potential applications in chem-b.
The Automation of Critical Path Method using Machine Learning: A Conceptual Study

This research aims to shed light on the use of machine learning in improving, developing and automating the critical path method, solving its problems, studying this effect and its dimensions, and discussing that from many aspects. The research is divided into two theoretical and practical parts. The theoretical part is concerned with studying the critical path method and its advantages, problems and challenges, as well as studying machine learning and artificial intelligence and its dimensions, reviewing materials and sources related to this, and then presenting suggestions and future solutions based on this study. As for the practical section, it is a questionnaire that targeted a segment of engineers, in particular, and others who have sufficient experience in both the critical path method and machine learning, and seeking their opinions on both topics. The result of the theoretical research was 14 theories or proposals that were presented based on the foregoing study. As for the practical questionnaire, a sample of 127 was taken. Through statistical analysis, the results were analyzed and discussed separately, and then a conclusion was drawn regarding them.
The paradoxes of love in the Spanish family: a sociological approach

This article defines the Spanish family in the context of the “Mediterranean model” and the “individualization society”. The former is characterised by strong social interrelationships between family members and their emotional ties, while the latter is defined by the separateness of citizens and by institutionalising the basis of society in individuals rather than in the family. The work also describes how modern forms of love, both romantic and confluent, are institutionalized in this society, discussing if they coexist or not, how they exist, and which is the dominant form. Finally, it analyzes the degree of strength or fragility of the family institution and the affective relationships that sustain it. The work concludes that the Spanish family is balancing between the strong resistance to disappear as an institution and its eclipse, crisis, or complete end. This is because, although the Spanish family still retains a large part of its former functions, at the same time as divorce is on the increase and family members are decreasing, it is increasingly ephemeral and a plurality of family forms have emerged that have broken with the traditional dominant model of lifelong romantic marriage. Moreover, the Spanish family is also among the “familist” model and the individual, while the way of loving fluctuates between the traditional patriarchal and the democratic, individual, and communitary. Thus, the thesis I propose qualifies and questions the majority of theoretical works on love and the Spanish family, which argue that the family is inscribed in the “Mediterranean model”. As will be seen, the romantic relationships that have been institutionalised in the Spanish family are more paradoxical, insofar as they are still inscribed in that model, but they are rapidly approaching those of Northern Europe.
The Volatility Puzzle of the Low-Risk Anomaly

This paper shows that leading theories of the low-risk anomaly fail to provide a complete explanation for the anomaly’s conditional performance. Sharpe ratios and abnormal returns of betting-against-beta (BAB) and -idiosyncratic volatility (BAV) factors rise significantly following low volatility months, even when controlling for lottery preferences, and in the case of BAB, also controlling for mispricing and limits to arbitrage. Moreover, the leverage constraints theory counterfactually predicts that market and BAB Sharpe ratios increase with volatility. We also show that highly active institutions shift from high- to low-beta stocks as volatility increases, suggesting their demand contributes to the performance of BAB.