Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and evaluation of an open-source, low-cost distributed sensor network for environmental monitoring applications

Over the last decade there has been a proliferation of low-cost sensor networks that enable highly distributed sensor deployments in environmental applications. The technology is easily accessible and rapidly advancing due to the use of open-source microcontrollers. While this trend is extremely exciting, and the technology provides unprecedented spatial coverage, these sensors and associated microcontroller systems have not been well evaluated in the literature. Given the large number of new deployments and proposed research efforts using these technologies, it is necessary to quantify the overall instrument and microcontroller performance for specific applications. In this paper, an Arduino-based weather station system is presented in detail. These low-cost energy-budget measurement stations, or LEMS, have now been deployed for continuous measurements as part of several different field campaigns, which are described herein. The LEMS are low-cost, flexible, and simple to maintain. In addition to presenting the technical details of the LEMS, its errors are quantified in laboratory and field settings. A simple artificial neural network-based radiation-error correction scheme is also presented. Finally, challenges and possible improvements to microcontroller-based atmospheric sensing systems are discussed.
Approximate solutions for a fractional thermostat model boundary value problem via Bernstein's collocation method with Legendre polynomials

Numerous classical models of thermostats have been analyzed in the literature, and while existence and uniqueness results have been established, the investigation of other properties, such as stability, can present significant challenges. Therefore, there is a need for fractional mathematical models that are nonlocal problems and allow for the straightforward study of the asymptotic behavior of their solutions. However, solving these problems is often exceedingly complex or even impossible, necessitating the use of numerical methods to obtain approximate solutions. The focus of this research is a generalized boundary value problem that is based on a classical thermostat model. Our initial step involves determining the associated integral equation for the problem at hand. The properties of existence and uniqueness are proved by exploiting the classical contraction principle of Banach together with another kind called ν$$ \nu $$ ‐ Φ$$ \Phi $$ ‐contraction. Afterwards, thanks to the Bernstein polynomials and fractional matrix of derivative, the approximate solutions of our nonlinear fractional thermostat model problem are obtained. This approach utilizes the Legendre operational matrix of fractional derivatives in combination with a truncated Legendre series for the numerical integration of fractional differential equations. By doing so, the problem can be reduced to solving a system of algebraic equations, resulting in significant simplification. This method has been successfully used to solve both linear and nonlinear fractional differential equations. Finally, an example on this type of problem have been studied and the approximate solution are plotted.
Indirect Signatures of Unstable Dark Matter in Cosmic-Ray Antimatter and in the Gamma-Ray Sky

We study the indirect signatures of a class of models of particle dark matter where the dark matter is unstable but decays with lifetimes far in excess of the age of the Universe. Due to the large amounts of dark matter in the Galactic halo and in the Universe at large, even for such long lifetimes this can lead to observable signatures in cosmic rays as well as gamma rays and neutrinos. We derive constraints on dark matter stability in different decay channels and interpret recent anomalous results regarding the abundance of positrons in the cosmic radiation in terms of dark matter decay. Furthermore, we examine two supersymmetric models of dark matter, namely the gravitino with broken R-parity and the gaugino of a hidden gauge symmetry.
On the Variability of the Ionospheric F2-Layer During the Quietest Days in December 2009

Copyright © The Korean Space Science Society http://janss.kr plSSN: 2093-5587 elSSN: 2093-1409 Received 4 OCT 2016 Revised 15 NOV 2016 Accepted 16 NOV 2016 †Corresponding Author E-mail: hegai@izmiran.ru, ORCID: 0000-0003-0843-9096 Tel: +7-4958-519780, Fax: +7-4958-510124 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Research Paper J. Astron. Space Sci. 33(4), 273-278 (2016) http://dx.doi. org/10.5140/JASS.2016. 33.4. 273
Detection and prevention of username enumeration attack on SSH protocol: machine learning approach

Over the last two decades (2000–2020), the Internet has rapidly evolved, resulting in symmetrical and asymmetrical Internet consumption patterns and billions of users worldwide. With the immense rise of the Internet, attacks and malicious behaviors pose a huge threat to our computing environment. Brute-force attack is among the most prominent and commonly used attacks, achieved out using password-attack tools, a wordlist dictionary, and a usernames list – obtained through a so – called an enumeration attack. In this study, we investigate username enumeration attack detection on SSH protocol by using machine-learning classifiers. We apply four asymmetrical classifiers on our generated dataset collected from a closed environment network to build machine-learning-based models for attack detection. The use of several machine-learners offers a wider investigation spectrum of the classifiers’ ability in attack detection. Additionally, we investigate how beneficial it is to include or exclude network ports information as features-set in the process of learning. We evaluated and compared the performances of machine-learning models for both cases. The models used are k-nearest neighbor (KNN), naïve Bayes (NB), random forest (RF) and decision tree (DT) with and without ports information. Our results show that machine-learning approaches to detect SSH username enumeration attacks were quite successful, with KNN having an accuracy of 99.93%, NB 95.70%, RF 99.92%, and DT 99.88%. Furthermore, the results improved when using ports information. The best selected model was then deployed into intrusion detection and prevention system (IDS/IPS) to automatically detect and prevent username enumeration attack. Study also recommends the use of Deep Learning in future studies.
CVD growth of monolayer MoS2: Role of growth zone configuration and precursors ratio

Single-layer, large-scale two-dimensional material growth is still a challenge for their wide-range usage. Therefore, we carried out a comprehensive study of monolayer MoS2 growth by CVD investigating the influence of growth zone configuration and precursors ratio. We first compared the two commonly used approaches regarding the relative substrate and precursor positions, namely, horizontal and face-down configurations where face-down approach is found to be more favorable to obtain larger flakes under identical growth conditions. Secondly, we used different types of substrate holders to investigate the influence of the Mo and S vapor confinement on the resulting diffusion environment. We suggest that local changes of the S to Mo vapor ratio in the growth zone is a key factor for the change of shape, size and uniformity of the resulting MoS2 formations, which is also confirmed by performing depositions under different precursor ratios. Therefore, to obtain continuous monolayer films, the S to Mo vapor ratio is needed to be kept within a certain range throughout the substrate. As a conclusion, we obtained monolayer triangles with a side length of 90 µm and circles with a diameter of 500 µm and continuous films with an area of 850 µm × 1 cm when the S-to-Mo vapor ratio is optimized.
Platform Development for CMOS-MEMS Multi-Gap Capacitive Transducers

This work, for the first time, presents a platform for designing microelectromechanical system (MEMS) capacitive transducers featuring multiple transduction gaps implemented by a traditional $0.18~\mu \text{m}$ 1-Poly-6-Metal (1P6M) complementary metal-oxide-semiconductor (CMOS) technology. As a capacitive transducer, different sizes of the transduction gap will bring distinct pros and cons, and designers often need to make trade-off among various performance metrics. The proposed CMOS-MEMS platform provides three types of transduction gap spacing that cover from narrow to large in single chip with excellent circuit integration capability. Based on a partial etching technique applied on back-end-of-line (BEOL) metal layers while utilizing anti-reflective coating (titanium nitride, TiN) as electrodes, transduction gap spacing of 125 nm, 400 nm, and 930 nm can be fabricated simultaneously without damaging the integrated circuit. Among these three devices, the latest metal-insulator-metal (MIM) device, which features a 125 nm transduction gap and provides a record-low motional resistance, is introduced with detail design guideline and layout tutorial for the first time. The post-CMOS fabrication process of the multi-gap platform is validated using three simple clamped-clamped beam structures being verified as capacitive resonators with similar frequency for extracting their mechanical and electromechanical coupling characteristics. Finally, a dual-gap capacitive micromachined ultrasonic transducer (CMUT) array is illustrated as a feasible application of the proposed platform offering different transduction gaps for signal transmission and reception. [2023-0073]
The Education-Health Gradient: Revisiting the Role of Socio-Emotional Skills

IZA DP No. 16300 JULY 2023 The Education-Health Gradient: Revisiting the Role of Socio-Emotional Skills Is the education-health gradient inflated because both education and health are associated with unobserved socio-emotional skills? Revisiting the literature, we find that the gradient is reduced by 30-45% by fine-grained personality facets and Locus of Control. Traditional aggregated Big-Five scales, in contrast, have a much smaller and mostly insignificant contribution to the gradient. We decompose the gradient into its components with an order-invariant method, and use sibling-fixed effects to address that much of the observed education-health gradient reflects associations rather than causal relationships. There are education-health gradients even within sibling pairs; personality facets reduce these gradients by 30% or more. Our analyses use an extraordinarily large survey (N=28,261) linked to high-quality administrative registers with information on SES background and objective health outcomes. JEL Classification: I14, I12, I24, I31
Anticoagulant therapy during cardiovascular implantable electronic device procedures

Aim The objective of the study is to systematically evaluate the safety and efficacy of peri-procedural utilization of anticoagulation therapy during cardiovascular implantable electronic device procedures. Material and methods The review materials were based on comprehensive retrieval of randomized controlled trials and observational studies published until April 2023. Studies which compared different management strategies of long-term anticoagulation therapy during peri-procedural cardiac rhythm device implantation and compared the complications of bleeding and/or thromboembolic events were selected and reviewed. Results Studies analysing non-vitamin K oral anticoagulants interruption versus continuation during peri-procedural implantable cardiac device surgery found no statistically significant difference in bleeding or thromboembolic complications between these strategies. Studies comparing non-vitamin K oral anticoagulants with vitamin K antagonists also showed no statistically significant difference. One study comparing uninterrupted warfarin with interrupted warfarin with heparin bridging reported a reduced incidence of clinically significant device pocket haematoma in patients with continued warfarin treatment (relative risk = 0.19; 95% confidence interval: 0.10 to 0.36; p < 0.001). A sub-analysis of one study comparing dabigatran versus warfarin with heparin bridging and without bridging reported a lower risk of pocket haematoma with dabigatran when compared to warfarin with heparin bridging (risk difference: –8.62%, 95% confidence interval: –24.15 to –0.51%; p = 0.034). Both bleeding and thromboembolic complications were rare. Conclusions The traditional method of vitamin K antagonists interruption with heparin bridging is less safe than continuing vitamin K antagonists at therapeutic levels. Both continuation and interruption strategies of non-vitamin K anticoagulants during cardiac device surgery seem to be safe and appropriate.
PERFIL DE MORTALIDADE DE CÂNCER DE PRÓSTATA NO CONTEXTO DA PANDEMIA DE COVID-19 ENTRE 2019 E 2020

Estudo desenvolvido com o objetivo de evidenciar o perfil de mortalidade de câncer de próstata no contexto da pandemia de covid-19 entre 2019 e 2020 nas cinco regiões brasileiras. Trata-se de um estudo descritivo com abordagem ecológica. A coleta de dados foi realizada no período de março a abril de 2022 na plataforma de Informática do Sistema Único de Saúde (DATASUS), proveniente do sistema de informação sobre mortalidade (SIM) e do Sistema de Informação de Agravos de Notificação (SINAN). Verificou-se que a ocorrência de óbitos tendo como causa o câncer prostático em 2019 está assim distribuído: Norte (891 casos); Sudeste de óbitos e já no ano de 2020 (com pandemia), houve 881 casos de mortes. Na região sudeste, no ano de 2019, houve 6.829 (7,31 óbitos por 100.000 homens) e em 2020 (com pandemia), houve 6.586 (7,05 óbitos por 100.000 homens). O quantitativo de todas as regiões em 2019 chega a 15.983 (17,11 óbitos por 100.000 homens) e em 2020, chega a 15.841 (16,95 óbitos por 100.000 homens). A partir deste trabalho, foi possível demonstrar que o declínio nos diagnósticos de câncer de próstata se deve a uma combinação de vários fatores como dificuldade de rastreamento da doença e, principalmente, isolamento social causado pela pandemia. Com isso, podemos dizer que a pandemia de Covid-19 afetou os indicadores epidemiológicos de mortalidade por câncer de próstata durante 2019-2020.
General Adaptive Lossless Compression for Multi-Channel Sensor Signals

The storage and transmission of multi-channel high-rate sensor data have emerged as new challenges in real-time sensor signal acquisition. To address these challenges, a multi-channel compression algorithm can be utilized to decrease data storage and transmission bandwidth requirements. We propose a general adaptive lossless multi-channel compression architecture that leverages inter-channel and intra-channel correlation to improve the compression efficiency. Additionally, a high-throughput hardware implementation of the compression architecture is proposed. The experimental results on multiple open-source datasets demonstrate that our multi-channel lossless compression architecture outperforms reported single-channel and multi-channel compression architectures in terms of compression efficiency. Experiments show that it can deliver a competitive throughput rate for each channel in FPGA for a 16-channel compression implementation.
Accuracy Assessment of Planetary Boundary Layer Height for the WRF Model Using Temporal High Resolution Radio-sonde Observations

Understanding limitation of simulation for Planetary Boundary Layer (PBL) height in mesoscale meteorological model is important for accurate meteorological variable and diffusion of air pollution. This study examined the accuracy for simulated PBL heights using two different PBL schemes (MYJ, YSU) in Weather Research and Forecasting (WRF) model during the radiosonde observation period. The simulated PBL height were verified using atmospheric sounding data obtained from radiosonde observations that were conducted during 5 months from August to December 2014 over the Gumi weir in Nakdong river. Four Dimensional Data Assimilation (FDDA) using radiosonde observation data were conducted to reduce error of PBL height in WRF model. The assessment result of PBL height showed that RMSE with YSU scheme were lower than that with MYJ scheme in the day and night time, respectively. Especially, the WRF model with YSU scheme produced lower PBL height than with the MYJ scheme during night time. The YSU scheme showed lower RMSE than the MYJ scheme on sunny, cloudy and rainy day, too. The experiment result of FDDA showed that PBL height error were reduced by FDDA and PBL height at the nudging coefficient of 3.0 × 10 − 1 (YSU_FDDA_2) were similar to observation compared to the nudging coefficient of 3.0 × 10 − 4 (YSU_FDDA_1).
Indirect adaptive fuzzy prescribed performance control of feedback linearisable MIMO non-linear systems with unknown control direction

An indirect adaptive fuzzy prescribed performance control scheme is developed for a class of uncertain multi-input and multi-output feedback linearisable non-linear systems with unknown control direction and external disturbances. The properties of symmetric matrix and hyperbolic tangent function are exploited and the predefined tracking performance boundary is used to design the adaptive fuzzy prescribed performance controller, which can avoid the possible singularity problem and calculating the inverse of matrix. A robust controller equipped with a Nussbaum-type function is constructed to compensate for the lumped errors and solve the unknown control direction problem. The proposed scheme guarantees that all the signals in the resulting closed-loop system are bounded and that the tracking errors converge to a small residual set with the prescribed performance bounds. Simulation results are used to demonstrate the effectiveness of the proposed approach.
Ethnolect speakers and Dutch partitive adjectival inflection. A corpus analysis

This study applies the methodology described by Gries & Deshors (2014) within the framework of the Contrastive Interlanguage Analysis (Granger, 1996) to the partitive genitive inflection in post-quantifier adjectives in the Moroccan Dutch ethnolect. This implies fitting a logistic regression model on data from the complementary ConDiv and Moroccorp corpora to investigate the differences between the L1 variety and the (early L2/2L1) ethnolect variety. It was found that the Moroccan Dutch language users do not differ from ‘ordinary’Dutch language users in the realisation of the partitive genitive -s suffix, neither through an outspoken preference for one of the inflectional variants, nor in the factors determining the alternation. This is considered a rather surprising result, as such differences do exist for a number of other grammatical phenomena (Cornips and Rooij, 2003; Van de Velde and Weerman, 2014). This finding can tell us something about the inflectional status of the partitive genitive. It appears that it is less non-transparent than other quirks in adjectival inflection.
Selective-area growth of InAs nanowire arrays on Si3N4/Si(111) by molecular beam epitaxy

InAs nanowires directly integrated on Si platform show great promise in fabricating next generation mid-infrared optoelectronic devices. In this study we demonstrated the growth of catalyst-free, selective-area InAs nanowire arrays on electron beam patterned Si3N4/Si(111) by molecular beam epitaxy. Growth parameters were studied, and nanowire growth kinetics dependence on patterned mask opening diameter and interwire distance was investigated. Under certain growth conditions, nanowire diameter was found to be relatively independent of nanohole diameter and pitch. We also realized the growth of randomly-nucleated, self-assembled nanowires on Si(111) and investigated the temperature, flux influence on nanowire morphology.
Automated Android Malware Detection Using Optimal Ensemble Learning Approach for Cybersecurity

Current technological advancement in computer systems has transformed the lives of humans from real to virtual environments. Malware is unnecessary software that is often utilized to launch cyber-attacks. Malware variants are still evolving by using advanced packing and obfuscation methods. These approaches make malware classification and detection more challenging. New techniques that are different from conventional systems should be utilized for effectively combating new malware variants. Machine learning (ML) methods are ineffective in identifying all complex and new malware variants. The deep learning (DL) method can be a promising solution to detect all malware variants. This paper presents an Automated Android Malware Detection using Optimal Ensemble Learning Approach for Cybersecurity (AAMD-OELAC) technique. The major aim of the AAMD-OELAC technique lies in the automated classification and identification of Android malware. To achieve this, the AAMD-OELAC technique performs data preprocessing at the preliminary stage. For the Android malware detection process, the AAMD-OELAC technique follows an ensemble learning process using three ML models, namely Least Square Support Vector Machine (LS-SVM), kernel extreme learning machine (KELM), and Regularized random vector functional link neural network (RRVFLN). Finally, the hunter-prey optimization (HPO) approach is exploited for the optimal parameter tuning of the three DL models, and it helps accomplish improved malware detection results. To denote the supremacy of the AAMD-OELAC method, a comprehensive experimental analysis is conducted. The simulation results portrayed the supremacy of the AAMD-OELAC technique over other existing approaches.
Total polarization-dependent loss of cascaded optical components for optical space applications

Photonics-based communication systems can provide increasing data rates to meet the users’ requirements. Coherent optical communication system was implemented to satisfy the current and future applications, in which the transmission of optical signal over two polarizations can mainly achieve a double Baud rate as compared to a s ingle polarization. However, dual polarization systems have some hindrances whichare represented by polarization rotation, polarization-dependent loss (PDL), and polarization mode dispersion (PMD). In this paper, those impairments are demonstrated and investigated for either a single component or multiple components in the optical system. The theoretical and mathematical discussions reveal that the polarization rotation and PDL can cause a loss in the optical signal power and loss in the orthogonality between two polarization tributaries. Furthermore, simulations are carried out for 10 GBaud dual-polarization-quadrature phase shift keying (DP-QPSK) as an example of optical application. The simulation measurements in term of bit-error-rate (BER) show how the polarization impairments can significantly degrade the system performance.