Miracle-dz/UniFAR-FTUs huggingface dataset:
Preliminary Assessment of the Influence of Salitre Basin Rainfall on the Pumping Operation of Salitre Wastewater Treatment Plant (Bogota)

Operations in wastewater treatment facilities often result in a more or less empirical practice depending on the acquired field experience of a red uced group of persons and how good the track of the different processes in the plant is in real time. This situation conducts to a great constraint of the treatment systems, limits the opt imization process and obstacles economical efficiency regarding environmental objectives. This work consists in identifying hydrological stations near the Salitre basin (Bogota, Colombia), and associated to them, the most influent variables on the Salitre Waste Water Treatment Plant (Salitre WWTP), as basis of a possible implementation of a real-time operating system. To achieve this objective, correlations (Pearson and Spearman) as well as Partial Least Squ ares Regressions (PLSR) were calculated between hydrological and pumping operational variables of the plant. The results indicate that the variables with the highest correlation to the p umping operation of Salitre WWTP are maximum precipitation registered in two hours and t otal time of rainfall events. Moreover, the hydrological stations with more influence are Camavieja , Salitre Casa de Bombas and Cerros de Suba .
A Fusion Approach for Pre-Crash Scenarios based on Lidar and Camera Sensors

The use and development of new Advanced Driver Assistance Systems (ADAS) based on fusion of various sensors, aiming to achieve a higher robustness, are becoming more common. In pre-crash scenarios, the extraction of information from an incoming vehicle should be done as near as possible to the moment of impact "t0", where relevant issues such as disturbances in the sensor signal and partial occlusion of the vehicle play an important role. The presented work introduces a novel fusion approach between a Lidar and a camera to extract the distance and the approach angle of an oncoming vehicle. It detects the bullet vehicle’s license plate using a deep learning neural network and fuses the Lidar information to estimate its distance and approach angle. The proposed architecture was evaluated on data from a benchmark dataset - KITTI, and with a pre-crash scenario dataset collected inside the CARISSMA Research Center indoor hall facilities. The algorithm reached an accuracy of 0.16m±0.26m for the distance and 5.48°±4.99° for the angle estimation on the benchmark dataset. On the pre-crash dataset, the experimental results yielded an accuracy of 0.022m ± 0.022m and 2.82°± 1.98° for the distance and angle, respectively. The system can extract parameters until 0.4m before a collision, and can overcome blurriness and partial occlusion conditions, being also easily reproducible in other sensor setups.
Institutional responses to the COVID-19 pandemic: Faculty and administrator experiences

The onset of the COVID-19 pandemic required shifts in operations for institutions of higher education everywhere. Faculty and administrators were asked to adapt to meet the needs of students. We conducted a qualitative content analysis to understand institutional responses and examine the experiences of faculty and administrators during the COVID-19 pandemic through the lens of chaos theory. Institutional responses to the pandemic varied. Participants identified supports and resources deemed helpful, as well as those found to be inadequate or unwanted. We also found that the pandemic resulted in some positive outcomes for faculty and administrators, which led to growth in teaching and self-care. Implications for strategic planning and future directions for research are explored.
Bactericidal Activity of Multilayered Hybrid Structures Comprising Titania Nanoparticles and CdSe Quantum Dots under Visible Light

Titania nanoparticle/CdSe quantum dot hybrid structures are a promising bactericidal coating that exhibits a pronounced effect against light-sensitive bacteria. Here, we report the results of a comprehensive study of the photophysical properties and bactericidal functionality of these hybrid structures on various bacterial strains. We found that our structures provide the efficient generation of superoxide anions under the action of visible light due to electron transfer from QDs to titania nanoparticles with ~60% efficiency. We also tested the antibacterial activity of hybrid structures on five strains of bacteria. The formed structures combined with visible light irradiation effectively inhibit the growth of Escherichia coli, Bacillus subtilis, and Mycobacterium smegmatis bacteria, the last of which is a photosensitive causative agent model of tuberculosis.
TRIPILLAR: Miniature magnetic caterpillar climbing robot with plane transition ability

In this paper, we describe a miniature climbing robot, 96 x 46 x 64 [mm3], able to climb ferromagnetic surfaces and to make inner plane to plane transition using only two degrees of freedom. Our robot, named TRIPILLAR, combines magnetic caterpillars and magnets to climb planar ferromagnetic surfaces. Two triangular tracks are mounted in a differential drive mode, which allows squid steering and on spot turning. Exploiting the particular geometry and magnetic properties of this arrangement, TRIPILLAR is able to transit between intersecting surfaces. The intersection angle ranges from -10° to 90° on the pitch angle of the coordinate system of the robot regardless of the orientation of gravity. A possible path is to move from ground to ceiling and back. This achievement opens new avenues for mobile robotics inspection of ferromagnetic industrial structure with stringent size restriction, like the one encountered in power plants.
Fat, oil and grease - Sewer contamination prevention strategies and double-dosage concept for fat traps and pressure mains

Disposal of fat, oil and grease (FOG) in sewer systems cause blockages, fatal errors of pumping stations, increased maintenance, odours, hydrogen sulphide (H 2 S) emissions and corrosion. Hence, solutions to prevent FOG disposals are desirable. Challenges are prevention of FOG contamination of sewer systems and removal of FOG disposals. A survey and lab as well as full scale tests were performed. In the first place fat traps and grease inceptors should be installed to prevent FOG contamination what is documented as being very effective. A case study shows that the operation of fat traps may indeed produce further problems, especially H 2 S emissions, what demands an additional treatment. Removal of FOG disposals can be handled by applying enzymes to the affected sewer network. It was found that enzymes are preferable towards surfactants to remove FOG disposals. It appears to be a solution to have one dosing site that is equipped with separately controlled dosing pumps for conditioners for H 2 S removal as well as FOG removal.
Online Capacity Estimation for Lithium-Ion Batteries Based on Semi-Supervised Convolutional Neural Network

Accurate capacity estimation can ensure the safe and reliable operation of lithium-ion batteries in practical applications. Recently, deep learning-based capacity estimation methods have demonstrated impressive advances. However, such methods suffer from limited labeled data for training, i.e., the capacity ground-truth of lithium-ion batteries. A capacity estimation method is proposed based on a semi-supervised convolutional neural network (SS-CNN). This method can automatically extract features from battery partial-charge information for capacity estimation. Furthermore, a semi-supervised training strategy is developed to take advantage of the extra unlabeled sample, which can improve the generalization of the model and the accuracy of capacity estimation even in the presence of limited labeled data. Compared with artificial neural networks and convolutional neural networks, the proposed method is demonstrated to improve capacity estimation accuracy.
Application of BOTDA in Mass Concrete Temperature Monitoring

In order to study the application of distributed optical fiber in temperature monitoring of mass concrete, monitoring instruments are embedded in pile cap to carry out the field experiment. The results show that the distributed temperature fiber which is based on brillouin optical time-domain analysis (BOTDA) has the superiority of anti-jamming, corrosion resistance, high precision and continuous measurement. It can accurately reflect the temperature change, effectively guide the construction, and play a positive role in preventing the emergence of concrete cracks caused by temperature change. What’s more, optical fiber has small volume and less influence on engineering, which make it have a good application prospect.
Hotspot detection on post-OPC layout using full-chip simulation-based verification tool: a case study with aerial image simulation

OPC (Optical Proximity Correction) improves the feature CD (critical dimension) uniformity and pattern fidelity in general. However, since model calibration only takes CD measurements at optimum exposure dose and best focus condition, the correction result may not be desirable at non-optimum conditions due to significant sub-resolution process distortion. Certain specific patterns are prone to bridging or pinching (we refer this type of location as hotspot in this paper) when process drifts a little from optimum condition. Simulation based full-chip verification became the method of choice for capturing hotspots on post-OPC layouts prior to mask tape-out to save development time and cost. In this paper, a complete simulation and analysis flow using SiVL was experimented to capture hotspots for a 100nm node process. Calibrated process model and multiple optical models with different focus/threshold conditions were applied for simulation. The method and effectiveness of filtering and analyzing fatal errors from output error database was discussed. The analysis results were then correlated to actual wafer printing. A good match between prediction and experiment was found.
The particle dynamics simulation in non-stationary models of CFD

The modern method of particle motion simulation in crossed-field devices is described. It is intended for spectral and non-stationary particle models of CFD. The motion equation is solved by the one-step method. For charge distribution and field interpolation the new four-dimensional method PWS (polynoms with smoothing) is used.
Individual risky and protective factors influencing university new graduates’ career adaptability during COVID-19: A moderated mediation model

This study examined the characteristics of university new graduates’ career adaptability and the effects of individual internal factors during COVID-19. In January 2021, 1160 Chinese university new graduates completed self-report measures. Career adaptability was related to less intolerance of uncertainty and anxiety sensitivity and higher levels of proactive personality and resilience. Resilience mediated the relationships between intolerance of uncertainty, anxiety sensitivity, and career adaptability. Proactive personality buffered the negative effect of anxiety sensitivity on career adaptability. Implications for promoting career adaptability and alleviating the effects of intolerance of uncertainty and anxiety sensitivity in the COVID-19 epidemic and beyond are discussed.
Machine learning models of tobacco susceptibility and current use among adolescents from 97 countries in the Global Youth Tobacco Survey, 2013-2017

Adolescents are particularly vulnerable to tobacco initiation and escalation. Identifying factors associated with adolescent tobacco susceptibility and use can guide tobacco prevention efforts. Novel machine learning (ML) approaches efficiently identify interactive relations among factors of tobacco risks and identify high-risk subpopulations that may benefit from targeted prevention interventions. Nationally representative cross-sectional 2013–2017 Global Youth Tobacco Survey (GYTS) data from 97 countries (28 high-income and 69 low-and middle-income countries) from 342,481 adolescents aged 13–15 years (weighted N = 52,817,455) were analyzed using ML regression tree models, accounting for sampling weights. Predictors included demographics (sex, age), geography (region, country-income), and self-reported exposure to tobacco marketing, secondhand smoke, and tobacco control policies. 11.9% (95% CI 11.1%-12.6%) of tobacco-naïve adolescents were susceptible to tobacco use and 11.7% (11.0%-12.5%) of adolescents reported using any tobacco product (cigarettes, other smoked tobacco, smokeless tobacco) in the past 30 days. Regression tree models found that exposure or receptivity to tobacco industry promotions and secondhand smoke exposure predicted increased risks of susceptibility and use, while support for smoke-free air policies predicted decreased risks of tobacco susceptibility and use. Anti-tobacco school education and health warning messages on product packs predicted susceptibility or use, but their protective effects were not evident across all adolescent subgroups. Sex, region, and country-income moderated the effects of tobacco promotion and control factors on susceptibility or use, showing higher rates of susceptibility and use in males and high-income countries, Africa and the Americas (susceptibility), and Europe and Southeast Asia (use). Tobacco policy-related factors robustly predicted both tobacco susceptibility and use in global adolescents, and interacted with adolescent characteristics and other environments in complex ways that stratified adolescents based on their tobacco risk. These findings emphasize the importance of efficient ML modeling of interactions in tobacco risk prediction and suggest a role for targeted prevention strategies for high-risk adolescents.
Technology Forecasting of Green Energy Using Patent Analysis and Simulation Modeling

Green energy (GE) is natural energy that does not endanger humankind. Thus, precise knowledge about GE is very important to the future of humanity. The development of GE has been focused on renewable energy that avoids the emission of greenhouse gases. This paper proposes a technology forecasting (TF) model of GE technology that accurately explains GE. In this study, we retrieve patent documents concerning GE for application in our experiment, and we conduct patent analysis and simulation modeling in order to construct a TF model of GE technology. To verify the performance of our model, we forecast future aspects of GE technology.
Effective Mobility Enhancement Through Asymmetric Strain Channels on Extremely Thin Body (100) GOI pMOSFETs

The impact of asymmetric compressive strain on electrical properties of (100) Ge-on-insulator (GOI) pMOSFFETs with body thickness (<inline-formula> <tex-math notation="LaTeX">${T}_{\text {body}}$ </tex-math></inline-formula>) ranging from 10.6 to 3.0 nm thick is experimentally investigated. The asymmetric compressive strain channels are realized by using a Ge condensation technique and patterning channels with narrow channel width (<inline-formula> <tex-math notation="LaTeX">${W}_{\text {ch}}$ </tex-math></inline-formula>), resulting in over 85% relaxation of transverse stress at <inline-formula> <tex-math notation="LaTeX">${W}_{\text {ch}}$ </tex-math></inline-formula> less than 75 nm, which is reaching quasi-uniaxial strain Ge channels. It is found that the electrical properties of the <inline-formula> <tex-math notation="LaTeX">${I}_{ \mathrm{\scriptscriptstyle ON}}/{I}_{ \mathrm{\scriptscriptstyle OFF}}$ </tex-math></inline-formula> ratio and the subthreshold swing (SS) are much improved as the GOI channel strain approaches uniaxial one. Moreover, the maximum effective hole mobility (<inline-formula> <tex-math notation="LaTeX">$\mu _{\text {eff}}$ </tex-math></inline-formula>) up to 1120 and 181 cm<sup>2</sup>/Vs is achieved on 10.6- and 3.0-nm-thick GOI pMOSFETs, respectively, with quasi-uniaxial strain along <inline-formula> <tex-math notation="LaTeX">$\langle 110\rangle $ </tex-math></inline-formula> direction, leading to <inline-formula> <tex-math notation="LaTeX">$3.1\times $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$2.4\times $ </tex-math></inline-formula> mobility enhancement against biaxial strain channels at <inline-formula> <tex-math notation="LaTeX">${N}_{s}$ </tex-math></inline-formula> of <inline-formula> <tex-math notation="LaTeX">${1}\times {10}^{{13}}\,\,{\text {cm}}^{-{2}}$ </tex-math></inline-formula>, attributable to strong valence band warping and effective mass reduction.
On the Security of RC4 in TLS and WPA

The Transport Layer Security (TLS) protocol aims to provide condentiality and integrity of data in transit across untrusted networks. TLS has become the de facto protocol standard for secured Internet and mobile applications. TLS supports several symmetric encryption options, including a scheme based on the RC4 stream cipher. In this paper, we present ciphertext-only plaintext recovery attacks against TLS when RC4 is selected for encryption. Variants of these attacks also apply to WPA, a prominent IEEE standard for wireless network encryption. Our attacks build on recent advances in the statistical analysis of RC4, and on new ndings announced in this paper. Our results are supported by an experimental evaluation of the feasibility of the attacks. We also discuss countermeasures.
Laser Diode Active Height Control for Near Field Optical Storage

The use of commercial laser diodes as near field, nano-scale position sensors for feedback control systems was experimentally investigated. A static experimental setup was constructed to measure and characterize the laser diode feedback mechanism. Experiments show that the lasers, which act as miniature interferometers, provide a high accuracy, high signal-to-noise ratio (SNR) signal both in the near and far field. The laser diodes were then mounted in commercial digital versatile disc (DVD) actuators and a control system was constructed. The control system can operate both in the near and far field, and a controlled approach from the far to near field is demonstrated using a fringe jump controller. Finally, using the experimentally gathered feedback data, the residual control error of ±1 nm was estimated for this system.
Effect of Surface Elasticity on Scattering of Plane P-Waves by an Elastic Half-Plane with a Semi-Cylindrical Cavity

When the characteristic sizes of materials and elements reduce to nanometers, the inﬂuence of surface energy becomes prominent in its mechanical behavior. In the frame of surface elasticity, the scattering of of plane compressional waves (P-waves) by a semi-cylindrical cavity embedded in an elastic half-plane is investigated in this paper. By using the wave function expansion method, we obtain the analytical solutions of elastci fields. The results show that surface energy has a signiﬁcant effect on the diffractions of P-waves as the radius of the semi-cylindrical cavity shrinks to nanoscale. For incident waves with different frequencies, radius of semi-cylindrical cavity, the effects of surface elasticity on the dynamic stress concentration around the semi-cylindrical cavity are discussed in detail.
A subharmonic front-end in SiGe:C technology for 94-GHz imaging arrays

The design of a subharmonic downconverter for 94-GHz imaging arrays in SiGe:C technology is presented. A three-stage differential low-noise amplifier (LNA) with lumped matching networks is used together with a subharmonic mixer driven by a single-pole local-oscillator poly-phase network to form the front-end. The LNA yields 15 dB gain at 94 GHz, while the mixer provides 5 dB conversion gain over a 10 GHz IF bandwidth. The integrated downconverter provides 20 dB conversion gain at 94 GHz with an input 1-dB compression point of −31 dBm and has a current consumption of 45 mA at a 3.3 V supply voltage. The total required die area of the complete downconverter (excluding pad frame) is 0.1 mm, thus making it particularly suitable as a front-end in multi-channel receiver systems.
Identification of Drug Transporter Genomic Variants and Inhibitors That Protect Against Doxorubicin-Induced Cardiotoxicity

Supplemental Digital Content is available in the text. Background: Multiple pharmacogenomic studies have identified the synonymous genomic variant rs7853758 (G > A, L461L) and the intronic variant rs885004 in SLC28A3 (solute carrier family 28 member 3) as statistically associated with a lower incidence of anthracycline-induced cardiotoxicity. However, the true causal variant(s), the cardioprotective mechanism of this locus, the role of SLC28A3 and other solute carrier (SLC) transporters in anthracycline-induced cardiotoxicity, and the suitability of SLC transporters as targets for cardioprotective drugs has not been investigated. Methods: Six well-phenotyped, doxorubicin-treated pediatric patients from the original association study cohort were recruited again, and human induced pluripotent stem cell–derived cardiomyocytes were generated. Patient-specific doxorubicin-induced cardiotoxicity (DIC) was then characterized using assays of cell viability, activated caspase 3/7, and doxorubicin uptake. The role of SLC28A3 in DIC was then queried using overexpression and knockout of SLC28A3 in isogenic human-induced pluripotent stem cell–derived cardiomyocytes using a CRISPR/Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9). Fine-mapping of the SLC28A3 locus was then completed after SLC28A3 resequencing and an extended in silico haplotype and functional analysis. Genome editing of the potential causal variant was done using cytosine base editor. SLC28A3-AS1 overexpression was done using a lentiviral plasmid-based transduction and was validated using stranded RNA-sequencing after ribosomal RNA depletion. Drug screening was done using the Prestwick Chemical Library (n = 1200), followed by in vivo validation in mice. The effect of desipramine on doxorubicin cytotoxicity was also investigated in 8 cancer cell lines. Results: Here, using the most commonly used anthracycline, doxorubicin, we demonstrate that patient-derived cardiomyocytes recapitulate the cardioprotective effect of the SLC28A3 locus and that SLC28A3 expression influences the severity of DIC. Using Nanopore-based fine-mapping and base editing, we identify a novel cardioprotective single nucleotide polymorphism, rs11140490, in the SLC28A3 locus; its effect is exerted via regulation of an antisense long noncoding RNA (SLC28A3-AS1) that overlaps with SLC28A3. Using high-throughput drug screening in patient-derived cardiomyocytes and whole organism validation in mice, we identify the SLC competitive inhibitor desipramine as protective against DIC. Conclusions: This work demonstrates the power of the human induced pluripotent stem cell model to take a single nucleotide polymorphism from a statistical association through to drug discovery, providing human cell-tested data for clinical trials to attenuate DIC.
Developing the Persian version of the Anticipated Turnover Scale (P-ATS) and measuring its psychometric properties among Iranian industrial workers

Abstract The aim of this cross-sectional study was to measure the psychometric properties of the Persian version of Anticipated Turnover Scale (P-ATS) using a large sample of workers in the oil industry in Iran (N = 443). The psychometric properties of the scale were assessed using face, content, convergent, and construct validity, internal consistency, and test-retest reliability methods. A two-factor solution emerged from exploratory then confirmatory factor analyses. Content validity index and ratio were . 93 and . 98, respectively. There were high significant correlations between P-ATS and both perceived stress and workability. The Cronbach’s alpha was . 90 and test-retest correlation coefficient was . 87. The P-ATS exhibited very good psychometric properties and can be applied as a useful tool to predict job turnover among Iranian employees.