Miracle-dz/UniFAR-FTUs huggingface dataset:
Low-Cost Water Quality Sensors for IoT: A Systematic Review

In many countries, water quality monitoring is limited due to the high cost of logistics and professional equipment such as multiparametric probes. However, low-cost sensors integrated with the Internet of Things can enable real-time environmental monitoring networks, providing valuable water quality information to the public. To facilitate the widespread adoption of these sensors, it is crucial to identify which sensors can accurately measure key water quality parameters, their manufacturers, and their reliability in different environments. Although there is an increasing body of work utilizing low-cost water quality sensors, many questions remain unanswered. To address this issue, a systematic literature review was conducted to determine which low-cost sensors are being used for remote water quality monitoring. The results show that there are three primary vendors for the sensors used in the selected papers. Most sensors range in price from US$6.9 to US$169.00 but can cost up to US$500.00. While many papers suggest that low-cost sensors are suitable for water quality monitoring, few compare low-cost sensors to reference devices. Therefore, further research is necessary to determine the reliability and accuracy of low-cost sensors compared to professional devices.
Transonic flutter analysis of an AGARD 445.6 wing in the frequency domain using the Euler method

ABSTRACT A method based on the Euler equations is proposed for solving transonic flutter problems. The transonic nonlinear flow field with local shock wave/boundary layer interaction is obtained by the Euler/boundary layer equations, and the aerodynamic forces are converted from the time domain to the frequency domain using system identification techniques. The structural dynamic equations in generalized coordinates are adopted for solving structure problems. The method is validated by a flutter boundary prediction of the AGARD 445.6 wing model. The simulation results show that the method presented in this paper is accurate for the prediction of transonic flutter boundary through comparison with experimental data and other simulation results. Furthermore, the present frequency domain method is also much more efficient than the time domain method.
Half a Century after the Outburst of the Symbiotic Nova V1016 Cyg

Abstract We present the results of our long-term UBV JHKLM photometry and spectroscopic monitoring of the symbiotic nova V1016 Cyg. After its outburst in 1964, the star showed fading in the U, B, V bands at a rate of about 0.03 mag per year. The behavior of the B − V and U − B color indices reflects variations of the emission lines, fading of the erupted component, weakening and reddening of the cool giant. Also, monotonic color and brightness variations in the infrared (IR) were observed at a scale of several thousand days. After 2004, the yearly mean IR brightness showed a decline and IR colors, reddening, due to the increase of the optical depth of the dust. The parameters of the cool star and of the dust envelope were estimated. The pulsation period of the Mira-type variable was refined, P = 465±5 days. The Mira’s photospheric temperature varied from 2100 to 2700 K in the pulsation cycle. The mass of the dust shell has grown twice during the recent decade, at a dust penetration rate of ∆Mdust ~ 10−7M⊙/yr. Our spectroscopic monitoring of V1016 Cyg over 1995−2013 showed variations in the emission line strengths. The absolute fluxes of most lines decreased after 2000, whereas the relative intensities of [O III], [Ar III], [Fe VII], [Ca VII] lines with respect to Hβ are increasing after the possible minimum that could happen in the 1990s. An essential flux decline (approximately ten-fold between 1995 and 2013) in the Raman scattered O VI line at λ6825 shows the change of conditions in its formation zone, due to absorption of O VI 1032 Å quanta in the new dust shell of the cool component.
Bubbling Phenomena in Liquid-Filled Transformers: Background and Assessment

The degradation of the insulation system in liquid-filled power transformers is a serious concern for electric power utilities. The insulation system’s ageing is accelerated by moisture, acids, oxidation products, and other decay particles (soluble and colloidal). The presence of these ageing by-products is detrimental to the insulation system and may further lead to premature ageing and serious consequences. The ageing mechanisms of oil-paper insulation are complex, highly interrelated, and strongly temperature-dependent. The operating temperature of the transformer insulating system has a direct relationship with the loading profile. The major aspect that is witnessed with the fluctuating temperatures is moisture migration and subsequent bubble evolution. In other words, gas bubbles evolve from the release of water vapor from the cellulosic insulation wrapped around the transformer windings. The models presented in the existing standards, such as the IEC Std. 60076-7:2018 and the IEEE Std. C57.91:2011, are mainly based on the insulation temperature, which acts as a key parameter. Several studies have investigated the moisture dynamics and bubbling phenomenon as a function of the water content in the paper and the state of the insulation system. Some studies have reported different prototypes for the estimation of the bubble inception temperatures under selected conditions. However, there are various attributes of the insulation system that are to be considered, especially when expanding the models for the alternative liquids. This paper reviews various evaluation models reported in the literature that help understand the bubbling phenomenon in transformer insulation. The discussions also keep us in the loop on the estimation of bubbling behavior in alternative dielectric liquids and key attributable factors for use in transformers. In addition, useful tutorial elements focusing on the bubbling issue in transformers as well as some critical analyses are addressed for future research on this topic.
Plasticity in crystalline-amorphous core-shell Si nanowires controlled by native interface defects

Experimentally the silicon nanowires or nanopillars are naturally recovered by a thin oxide layer as soon as they are exposed to the air or present an amorphous layer of silicon when they are milled by focused ion beam (FIB) techniques. Here we investigate the role of the silicon amorphous shell on the plasticity of Si nanowires (NWs), thanks to molecular dynamics simulations. It is shown that the yield strain for the nucleation of the first dislocation is decreased for NWs with an amorphous shell when compared to pristine nanowires. For NWs with circular cross-sections, it is shown that the shell thickness has no influence on the yield strain. Besides, through the investigation of various rhombic cross-sections we observe that when an amorphous shell is present, the yield strain is independent of the cross-section shape. All these results can be explained by the presence of native atomic defects at the crystalline/amorphous interface, as revealed by a detailed atomistic analysis. These defects act as seeds for the dislocation nucleation. As a consequence this work raises the question about the role of point defects created in microand nanopillars milled by FIB techniques, in particular when they are used to study the mechanical properties at the nanoscale.
Community Detection in Networks: A Comparative study

In this paper, various approaches for community detection in complex networks are studied. The existence of community structure is most important features for community detection algorithms in a complex network. These algorithms are based on order to unmask the structural properties of the network and dynamic behaviors with the maximization of modularity. As a result, one of the most challenging problems in network is community detection i.e. NP-hard in modern network science. In this paper an improved Louvain Algorithm has been embodied that reduces the computational time and also maximize the modularity due to resolution limit.
Interaction effects of multiple input parameters on the integrity of safety instrumented systems with the k‐out‐of‐n redundancy arrangement under uncertainties

A safety instrumented system (SIS) is extensively used to prevent or reduce risk. The Probability of Failure to perform its intended functions on Demand (PFD) of a practical SIS may vary within multiple safety integrity levels (SIL) due to uncertainties relevant to input parameters. An SIS will be considered to be unsafe when its PFD is greater than a prescribed value, and unsafety probability (UP) is employed to measure the unsafety degree of the investigated SIS in this work. Redundancy architecture is commonly employed to improve the reliability of an SIS. This paper investigates the effects of multiple uncertain input parameters on the UP of an SIS with the k‐out‐of‐n redundancy arrangement. We derive the detailed formulations of the sensitivity for such effects and we also discuss the physical meaning of the proposed sensitivity. An example is employed to demonstrate the proposed sensitivity and the results show that the estimated sensitivity values will be kept to be unchanged with respect to the redundancy when the redundancy is high, whereas the results will vary with the redundancy when the redundancy is low. Meanwhile, we provide a comparison of the results for the truncated uncertain parameters and the non‐truncated uncertain parameters. The results for truncated uncertain parameters and non‐truncated uncertain parameters will approach the same values as the truncated region of the uncertain parameter reduces to zero. The results show that we can approximate the sensitivities of the truncated parameters by the ones of the non‐truncated parameters with less computation time when the truncated region is less than 10−3.
Patterning of graphene on silicon-on-insulator waveguides through laser ablation and plasma etching

We present the use of femtosecond laser ablation for the removal of monolayer graphene from silicon-on-insulator (SOI) waveguides, and the use of oxygen plasma etching through a metal mask to peel off graphene from the grating couplers attached to the waveguides. Through Raman spectroscopy and atomic force microscopy, we show that the removal of graphene is successful with minimal damage to the underlying SOI waveguides. Finally, we employ both removal techniques to measure the contribution of graphene to the loss of grating-coupled graphene-covered SOI waveguides using the cut-back method. This loss contribution is measured to be 0.132 dB/μm.
Estimating the Global Geographical Distribution Patterns of the Invasive Crop Pest Diuraphis noxia Kurdjumov under Current and Future Climatic Scenarios

Simple Summary Diuraphis noxia Kurdjumov is one of the most destructive invasive crop pests, reducing crop yield and quality and posing a great threat to global food security. Estimating the global geographical distribution patterns of D. noxia under climatic change is critical for its early warning and control and global food security. Here, the optimized MaxEnt model was used to predict the potential global geographical distribution of D. noxia. Our results showed that the potential geographical distribution of D. noxia was mainly located in Asia, Europe, and North America, showing a general tendency to move to higher latitudes under future climate. The increased suitable area of D. noxia was mainly located in northwestern Asia, western Europe, and North America. The development of ecomanagement and cross-country early warning strategies is warranted in the above area to mitigate the future impacts of the expansion of D. noxia on food security. Abstract Invasive crop pests (ICPs) are a major cause of crop losses and adversely affect global food security. Diuraphis noxia Kurdjumov is a significant ICP that feeds on the sap of crops, reducing crop yield and quality. Although estimating the geographical distribution patterns of D. noxia under climate change is critical for its management and global food security, such information remains unclear. Based on 533 global occurrence records and 9 bioclimatic variables, an optimized MaxEnt model was used to predict the potential global geographical distribution of D. noxia. The results showed that Bio1, Bio2, Bio7, and Bio12 were significant bioclimatic variables that influenced the potential geographical distribution of D. noxia. Under current climatic conditions, D. noxia was mainly distributed in west-central Asia, most of Europe, central North America, southern South America, southern and northern Africa, and southern Oceania. Under the SSP 1-2.6, SSP 2-4.5, and SSP 5-8.5 scenarios for the 2030s and 2050s, the potential suitable areas increased, and the centroid migrated to higher latitudes. The early warning of D. noxia in northwestern Asia, western Europe, and North America should be attended to further. Our results provide a theoretical basis for early monitoring and warning of D. noxia worldwide.
A Dark Septate Endophyte Improves Cadmium Tolerance of Maize by Modifying Root Morphology and Promoting Cadmium Binding to the Cell Wall and Phosphate

Dark septate endophytes (DSEs) can improve the performance of host plants grown in heavy metal-polluted soils, but the mechanism is still unclear. A sand culture experiment was performed to investigate the effects of a DSE strain (Exophiala pisciphila) on maize growth, root morphology, and cadmium (Cd) uptake under Cd stress at different concentrations (0, 5, 10, and 20 mg·kg−1). The results indicated that the DSE significantly improved the Cd tolerance of maize, causing increases in biomass, plant height, and root morphology (length, tips, branch, and crossing number); enhancing the Cd retention in roots with a decrease in the transfer coefficient of Cd in maize plants; and increasing the Cd proportion in the cell wall by 16.0–25.6%. In addition, DSE significantly changed the chemical forms of Cd in maize roots, resulting in decreases in the proportions of pectates and protein-integrated Cd by 15.6–32.4%, but an increase in the proportion of insoluble phosphate Cd by 33.3–83.3%. The correlation analysis revealed a significantly positive relationship between the root morphology and the proportions of insoluble phosphate Cd and Cd in the cell wall. Therefore, the DSE improved the Cd tolerance of plants both by modifying root morphology, and by promoting Cd binding to the cell walls and forming an insoluble phosphate Cd of lower activity. These results of this study provide comprehensive evidence for the mechanisms by which DSE colonization enhances Cd tolerance in maize in root morphology with Cd subcellular distribution and chemical forms.
Self-Calibrating Circuit for Implantable Current Stimulators

In this work, a self-calibrating circuit aimed at balancing biphasic current stimulators for Implantable Medical Devices (IMDs) is presented. Mismatched biphasic pulses cause a charge-unbalanced stimulation leading to tissue damage over time. The proposed module is an integrating, precision current comparator capable of detecting a 0.6% typical charge mismatch between the stimulating phases. The circuit's output can be used by a trimmable current stimulator to protect the tissue by reducing the injected net charge error. The total current consumption of the circuit is 1.5 $\upmu \mathrm{A}$ during a 430 $\upmu\mathrm{S}$ operating cycle. It was designed and fabricated in a 0.18 $\upmu\mathrm{m}$ CMOS-HV technology, occupying a total area of 0.30 mm2. The circuit can also be adapted to measure Electrode-Tissue Interface (ETI) impedance.
The Relationship between Mindfulness and Readiness to Change in Alcohol Drinkers

Mindfulness is a multi-faceted construct that involves paying attention to thoughts and emotions without automatically reacting and being critical of them. Recent research has suggested that mindfulness might play an important role in reducing problematic alcohol use. Further, Readiness to Change (RTC) is related to motivation to change drinking behaviours. The RTC scale identifies motivation to change drinking behaviours including Precontemplation, Contemplation, and Action stages. The current study investigated, for the first time, the relationship between mindfulness (and its facets) and RTC in relation to drinking behaviours. Undergraduate students from Western Sydney University (N = 279) were screened for drinking levels using the Alcohol Use Disorder Identification Test (AUDIT) and then completed the Readiness to Change Questionnaire (RCT) and the Five Facets Mindfulness Questionnaire (FFMQ), which includes the following facets: Acting with Awareness, Non-Judging of Inner Experience, Non-Reactivity to Inner Experience, Describing, and Observing. Results show that overall, mindfulness and its facets negatively correlated with RTC. Multiple regression analysis further showed that Awareness and Non-Judgement facets negatively predicted RTC. These findings provide insight into how the facets of mindfulness interact with the drinking motives of individuals and their intentions to change drinking behaviours. Based on these findings, we recommend the incorporation of mindfulness techniques in interventions targeting problematic drinking.
GeMS/GSAOI performances from a user perspective

Ground-based near-IR imagers assisted by Multi Conjugate Adaptive Optics (MCAO) systems are the technological frontier to obtain high-quality stellar photometry in crowded fields at the highest possible spatial resolution. The Gemini MCAO System (GeMS) feeding the Gemini South Adaptive Optics Imager (GSAOI) is the only facility of this kind currently available to the Community. We used a set of images obtained in the J and Ks bands of the central regions of two Galactic bulge globular clusters (Liller 1 and NGC 6624) with GeMS/GSAOI, under significantly different atmospheric conditions. We characterized the performances of the system in terms of efficiency and uniformity of the Point Spread Function (PSF) over the field of view with varying seeing, airmass and tip-tilt star asterisms. We also compared the PSF performances of GeMS/GSAOI with the HST/ACS ones in the F606W and F814W bands.
Hysteresis Behavior Modeling of Magnetorheological Elastomers under Impact Loading Using a Multilayer Exponential-Based Preisach Model Enhanced with Particle Swarm Optimization

Magnetorheological elastomers (MREs) are a type of smart material that can change their mechanical properties in response to external magnetic fields. These unique properties make them ideal for various applications, including vibration control, noise reduction, and shock absorption. This paper presents an approach for modeling the impact behavior of MREs. The proposed model uses a combination of exponential functions arranged in a multi-layer Preisach model to capture the nonlinear behavior of MREs under impact loads. The model is trained using particle swarm optimization (PSO) and validated using experimental data from drop impact tests conducted on MRE samples under various magnetic field strengths. The results demonstrate that the proposed model can accurately predict the impact behavior of MREs, making it a useful tool for designing MRE-based devices that require precise control of their impact response. The model’s response closely matches the experimental data with a maximum prediction error of 10% or less. Furthermore, the interpolated model’s response is in agreement with the experimental data with a maximum percentage error of less than 8.5%.
Motor-Related Mu/Beta Rhythm in Older Adults: A Comprehensive Review

Mu rhythm, also known as the mu wave, occurs on sensorimotor cortex activity at rest, and the frequency range is defined as 8–13Hz, the same frequency as the alpha band. Mu rhythm is a cortical oscillation that can be recorded from the scalp over the primary sensorimotor cortex by electroencephalogram (EEG) and magnetoencephalography (MEG). The subjects of previous mu/beta rhythm studies ranged widely from infants to young and older adults. Furthermore, these subjects were not only healthy people but also patients with various neurological and psychiatric diseases. However, very few studies have referred to the effect of mu/beta rhythm with aging, and there was no literature review about this theme. It is important to review the details of the characteristics of mu/beta rhythm activity in older adults compared with young adults, focusing on age-related mu rhythm changes. By comprehensive review, we found that, compared with young adults, older adults showed mu/beta activity change in four characteristics during voluntary movement, increased event-related desynchronization (ERD), earlier beginning and later end, symmetric pattern of ERD and increased recruitment of cortical areas, and substantially reduced beta event-related desynchronization (ERS). It was also found that mu/beta rhythm patterns of action observation were changing with aging. Future work is needed in order to investigate not only the localization but also the network of mu/beta rhythm in older adults.
Glutamate Transporters GltS, GltP and GltI Are Involved in Escherichia coli Tolerance In Vitro and Pathogenicity in Mouse Urinary Tract Infections

To verify the roles of GltS, GltP, and GltI in E. coli tolerance and pathogenicity, we quantified and compared the relative abundance of gltS, gltP, and gltI in log-phase and stationary-phase E. coli and constructed their knockout mutant strains in E. coli BW25113 and uropathogenic E. coli (UPEC) separately, followed by analysis of their abilities to tolerate antibiotics and stressors, their capacity for adhesion to and invasion of human bladder epithelial cells, and their survival ability in mouse urinary tracts. Our results showed that gltS, gltP, and gltI transcripts were higher in stationary phase E. coli than in log-phase incubation. Furthermore, deletion of gltS, gltP, and gltI genes in E. coli BW25113 results in decreased tolerance to antibiotics (levofloxacin and ofloxacin) and stressors (acid pH, hyperosmosis, and heat), and loss of gltS, gltP, and gltI in uropathogenic E. coli UTI89 caused attenuated adhesion and invasion in human bladder epithelial cells and markedly reduced survival in mice. The results showed the important roles of the glutamate transporter genes gltI, gltP, and gltS in E. coli tolerance to antibiotics (levofloxacin and ofloxacin) and stressors (acid pH, hyperosmosis, and heat) in vitro and in pathogenicity in mouse urinary tracts and human bladder epithelial cells, as shown by reduced survival and colonization, which improves our understanding of the molecular mechanisms of bacterial tolerance and pathogenicity.
Superconducting Hyperdimensional Associative Memory Circuit for Scalable Machine Learning

We propose a generalized architecture for the first rapid-single-flux-quantum (RSFQ) associative memory circuit. The circuit employs hyperdimensional computing (HDC), a machine learning (ML) paradigm utilizing vectors with dimensionality in the thousands to represent information. HDC designs have small memory footprints, simple computations, and simple training algorithms compared to superconducting neural network accelerators (SNNAs), making them a better option for scalable SFQ machine learning (ML) solutions. The proposed superconducting HDC (SHDC) circuit uses entirely on-chip RSFQ memory which is tightly integrated with logic, operates at 33.3 GHz, is applicable to general ML tasks, and is manufacturable at practically useful scales given current SFQ fabrication limits. Tailored to a language recognition task, SHDC consists of $\sim$2–20 M Josephson junctions (JJs) and consumes up to three times less power than an analogous CMOS HDC circuit while achieving 78–84% higher throughput. SHDC is capable of outperforming the state of the art RSFQ SNNA, SuperNPU, by 48-99% for all benchmark NN architectures tested while occupying up to 90% less area and consuming up to nine times less power. To the best of the authors' knowledge, SHDC is currently the only superconducting ML approach feasible at practically useful scales for real-world ML tasks and capable of online learning.