Miracle-dz/UniFAR-FTUs huggingface dataset:
Concise convolutional neural network model for fault detection

Fault detection is an urgent need for maintenance to obtain the optimal scheduling of production activities, improve system reliability, and reduce operation and maintenance costs. Many studies published in recent years focus on machine learning models to detect any system anomalies in line with the era of big data and the fourth industrial revolution (Industry 4.0). Say, a working condition of bearing can be monitored and then any fault can be detected using the vibration analysis of bearing acceleration data. Most of the published works are presented based upon the knowledge of signal processing in which the result depends heavily on feature extraction. It becomes a challenge then to apply a machine learning algorithm directly to the raw acceleration data as it has been successfully applied to raw data in other science and engineering domains. In this article, a concise Convolutional Neural Networks-based deep learning model is proposed for bearing fault detection. The proposed model was concise with 98% less number of parameters compared to other well-known models. It produced 21.21% and 7.03% better accuracy and fault detection rate, respectively. The model was also tested in different operating parameter environments and still gave an excellent result. Since the proposed concise architecture of the model needed short training time, it is deemed suitable for application on manufacturing floor where the pace of production moves fast and the change of the production machine configuration likely occurs.
On the evolution of the spiral galaxies in the Virgo cluster.

Integrated Balmer emission line fluxes have been measured for 26 spiral galaxies in the core of the Virgo cluster. They are combined with published 21-cm and UBV color data in order to compare the disk properties of the cluster galaxies with galaxies in the field. Virgo spirals of a given Hubble type possess less star formation, less neutral hydrogen, and are redder than their field counterparts. Various possible selection effects are examined, but they cannot explain the differences. The relationships between color, M/sub H/ /L and H.cap alpha. strengths, however, are indistinguishable in Virgo and the field. Some of the Virgo spirals may simply be normal spirals of slightly earlier type, but at least a few appear to be genuinely anemic galaxies, as suggested by van den Bergh.
ON A WEIGHTED QUASI-RESIDUAL MINIMIZATION STRATEGY FOR SOLVING COMPLEX SYMMETRIC SHIFTED LINEAR SYSTEMS

We consider the solution of complex symmetric shifted linear systems. Such systems arise in large- scale electronic structure simulations, and there is a stron g need of algorithms for their fast solution. With the aim of solving the systems efficiently, we consider a special case of the QMR method for non-Hermitian shifted linear systems and propose its weighted quasi-minimal residual approach. A numerical algorithm, referred to as shifted QMR SYM(B), is obtained by the choice of a weight which is particularly cost-effective. Numerical examples are presented to show the performance of the shifted QMR SYM(B) method.
Magnitude of Coagulation Abnormalities and Associated Factors Among Patients with Heart Diseases at the University of Gondar Comprehensive Specialized Hospital

Background Heart disease is a leading cause of hospitalization, death, and poor physical function due to comorbid conditions such as atrial fibrillation and stroke. It affects the blood hemostatic system, vasculature, and flow dynamics, causing both arterial and venous thrombosis. Thus, this study aimed to determine the magnitude of coagulation abnormalities among patients with heart disease attending the University of Gondar Comprehensive Specialized hospital. Methods A cross-sectional study was conducted on a total of 98 patients with heart disease. Pretested structured questionnaires were used to collect data on socio-demographic and clinical variables. About 6 mL of venous blood was collected with the vacutainer method and analyzed using Huma cue-due plus and Sysmex KX-21N hematology analyzers for assessing coagulation abnormalities. Stool samples were processed via a direct wet mount. Thin and thick blood films were examined to assess malaria parasites. Data was entered into EPI-Info version 3.5. 3 and then transported to SPSS version 20 for analysis. Descriptive statistics were summarized using frequency and percentage. Univariate and multivariate logistic regression models were fitted to identify factors associated with coagulopathy. P-value <0.05 was considered to be statistically significant. Results The overall magnitude of coagulation abnormalities (thrombocytopenia, prolonged prothrombin time, and activated partial thromboplastin time) in patients with heart diseases was 85.7% (95% CI: 81.96, 89.45). Besides, prolonged prothrombin time, prolonged activated partial thromboplastin time, and thrombocytopenia were detected in 83.7%, 33.7%, and 12.2% of the study participants, respectively. Participants who are taking medications for chronic disease (AOR = 0.17; 95% CI: 0.04, 0.69), participants with stroke (AOR = 20; 95% CI: 14.7, 35), and participants taking antibiotics (AOR = 8.17; 95% CI: 1.66, 40.27) were significantly associated with prolonged coagulation time. Conclusion This study showed that patients with heart disease had prolonged prothrombin time, activated partial thromboplastin time, and thrombocytopenia. Therefore, coagulation parameters are required to be checked regularly to monitor coagulation disorders and their complications in heart disease patients.
Coupling of the spatial distributions between sMRI and PET reveals the progression of Alzheimer’s disease

Abstract Amyloid-beta (Aβ) deposition and altered brain structure are the most relevant neuroimaging biomarkers for Alzheimer’s disease (AD). However, their spatial inconsistency was always confusing and misleading. Furthermore, the relationship between this spatial inconsistency and AD progression is unclear. The current study introduced a regional radiomics similarity network (R2SN) to map structural MRI and Aβ positron emission tomography (PET) images to study their cross-modal interregional coupling. A total of 790 participants (248 normal controls, 390 mild cognitive impaired patients, and 152 AD patients) with their structural MRI and PET images were studied. The results showed that global and regional R2SN coupling significantly decreased according to the severity of cognitive decline, from mild cognitive impairment to AD dementia. The global coupling patterns are discriminative between different APOE ε4, Aβ, and Tau subgroups. R2SN coupling was probed for relationships with neuropsychiatric measures and peripheral biomarkers. Kaplan–Meier analysis showed that lower global coupling scores could reveal worse clinical progression of dementia. The R2SN coupling scores derived from the coupling between Aβ and atrophy over individual brain regions could reflect the specific pathway of AD progression, which would be a reliable biomarker for AD.
Simulations of aerosol pH in China using WRF-Chem (v4.0): sensitivities of aerosol pH and its temporal variations during haze episodes

Abstract. Aerosol pH is a fundamental property of aerosols in terms of atmospheric chemistry and its impact on air quality, climate, and health. Precise estimation of aerosol pH in chemical transport models (CTMs) is critical for aerosol modeling and thus influences policy development that partially relies on results from model simulations. We report the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) simulated PM2.5 pH over China during a period with heavy haze episodes in Beijing, and explore the sensitivity of the modeled aerosol pH to factors including emissions of nonvolatile cations (NVCs) and NH3, aerosol phase state assumption, and heterogeneous production of sulfate. We find that default WRF-Chem could predict spatial patterns of PM2.5 pH over China similar to other CTMs, but with generally lower pH values, largely due to the underestimation of alkaline species (NVCs and NH3) and the difference in thermodynamic treatments between different models. Increasing NH3 emissions in the model would improve the modeled pH in comparison with offline thermodynamic model calculations of pH constrained by observations. In addition, we find that the aerosol phase state assumption and heterogeneous sulfate production are important in aerosol pH predictions for regions with low relative humidity (RH) and high anthropogenic SO2 emissions, respectively. These factors should be better constrained in model simulations of aerosol pH in the future. Analysis of the modeled temporal trend of PM2.5 pH in Beijing over a haze episode reveals a clear decrease in pH from 5.2 ± 0.9 in a clean period to 3.6 ± 0.5 in a heavily polluted period. The increased acidity under more polluted conditions is largely due to the formation and accumulation of secondary species including sulfuric acid and nitric acid, even though being modified by alkaline species (NVCs, NH3). Our result suggests that NO2 oxidation is unlikely to be important for heterogeneous sulfate production during the Beijing haze as the effective pH for NO2 oxidation of S(IV) is at a higher pH of ∼ 6.
Ku‐band gap waveguide filter design with improved out of band response

In this paper, a Ku‐band filter was designed based on the Gap Waveguide (GW) technology with improved out‐of‐band response. After extracting an appropriate circuit model for the intended filter, different parts of it such as the resonators, couplers between resonators as well as input and output couplers to resonators were implemented using the GW structures. After the filter was designed in the operating frequency band, its out‐of‐band behavior, which occurs due to the excitation of higher modes, was examined and the characteristics of the filter were improved in out‐of‐operating frequency band. Finally, the filter was fabricated and a comparison of the simulation results with the measurement results confirmed the validity of the designed method.
Evaluation of Drought Vulnerability of Maize and Influencing Factors in Songliao Plain Based on the SE-DEA-Tobit Model

Rain-fed agriculture is easily affected by meteorological disasters, especially drought. As an important factor of risk formation, actively carrying out agricultural drought vulnerability assessments is conducive to improving food security and reducing economic losses. In this study, an SE-DEA model with regional exposure and drought risk as input factors and the maize yield reduction rate and drought-affected area as output factors is established. The aim is to evaluate and zone the drought vulnerability of the maize belt in the Songliao Plain. The results show the following: (1) From 2000 to 2019, the drought vulnerability of maize showed a fluctuating increasing trend. The vulnerability in Harbin and central Jilin Province is high, which is extremely unfavorable for maize production. (2) Comparing the historical disaster data with the drought vulnerability map generated using the SE-DEA model, it could be found that the results obtained using the SE-DEA model are reliable. (3) The Tobit model shows that the proportion of the effective irrigated area is more important to alleviate vulnerability. For drought vulnerability zoning using a cluster analysis, we suggest that regulated deficit irrigation should be actively developed in high-vulnerability areas to ensure maize yield while improving water efficiency. The results of this study can provide a basis for the development of drought mitigation and loss reduction strategies, and they provide new ideas for future research.
Compact spiral band pass filter with low group delay

A complementary coupled spiral transmission line with center via is proposed to design band pass filter with compact and simple profile, low group delay, and low insertion loss. A compact wideband band pass filter is designed and fabricated for demonstration which has 26% bandwidth, 0.3 dB insertion loss, and compact size as 0.41 × 0.23 λg with very low group delay, 0.28 ns. These good specifications prove the capability of the proposed approach to design of band pass filter compared with the literatures.
Sensitisation to molecular components of mites in atopic dermatitis patients

ABSTRACT Background and aim: To analyse the sensitisation profile to molecular components of mites allergens with the use of ALEX2 Allergy Explorer test in Atopic dermatitis (AD) patients. Method: The complete dermatological and allergological examination including the examination of the sensitisation to molecular components with ALEX2 Allergy Explorer testing was performed. For the statistical analysis, we used Fisher's Exact. Results and conclusion: The sensitisation to mites increases with AD severity. The central role in atopic march may play the molecular component Der f 2 and Der p 23. The results of our study confirm the important role of Der p 5 and Der p 7 in subgroup of patients suffering from bronchial asthma. The specific immunotherapy should focus on the components of NPC2 family and Der p 23 in AD patients. Our results may be helpful in planning hyposensitisation, treatment and immunotherapy.
One-Bit Statistical ECSI Learning for Single-Group Multicast Secure Beamforming

This letter investigates a binary learning mechanism for statistical eavesdroppers’ channel state information (SECSI), in which the transmitter utilizes one-bit signal-to-noise-ratio feedback to constantly learn the channel correlation matrices of the eavesdropping links without any prior SECSI. Correspondingly, with the updated SECSI estimate, the optimal single-group multicast secure beamforming (SGMC-SBF) is determined and probed continually for multicast secrecy rate maximization. Simulation results show that this convergent cognitive strategy could not only achieve higher ergodic multicast secrecy rate than the worst-case robust SGMC-SBF with imperfect SECSI, but also approach the ideal performance achieved by perfect SECSI.
A Data-Driven Stackelberg Market Strategy for Demand Response-Enabled Distribution Systems

A data-based Stackelberg market strategy for a distribution market operator (DMO) is proposed to coordinate power dispatch among different virtual power plants, i.e., demand response (DR) aggregators (DRAs). The proposed strategy has a two-stage framework. In the first stage, a data-driven method based on noisy inverse optimization estimates the complicated price-response characteristics of customer loads. The estimated load information of the DRAs is delivered to the second stage, where a one-leader multiple-follower stochastic Stackelberg game is formulated to represent the practical market interaction between the DMO and the DRAs that considers the uncertainty of renewables and the operational security. The proposed data-driven game model is solved by a new penalty algorithm and a customized distributed hybrid dual decomposition-gradient descent algorithm. Case studies on a practical DR project in China and a distribution test system demonstrate the effectiveness of the proposed methodology.
An evidence for enhanced star formation rate in IRAS-detected Arakelian galaxies.

The IR emission of 182 Arakelian galaxies (AKN), included in the IRAS Survey, is considered as an evidence of enhanced star formation rate (SFR) in them. About 63%. of the AKNs have far Infrared luminosities ( 10 erg-s) in 1-500 mkm IR spectral band. The distribution of log (f60/f100), peaked at about 45 K, shows that IRAS AKNs ire considerably warmer than "normal" S galaxies. IRAS AKSs have a tendency to extend the relation f100/f60 vs LIR/LBl for "normal" S galaxies. They emit IR energy in 40-100 mkm band up to seven times more than in optics. The mean ratio < LFIR/LBl> for 148 IRAS AKNs with known redshifts is 3.63. It is suggested that there are two IR emitting components in the IRAS AKNs a warm one connected with the UV-fluxes of the new-born massive stars, reradiated by dust, and a cool one, originated from the dust in galactic disks and heated by the general interstellar radiation field. The warm IR luminosities and warm IR fractions are determinated on the basis of IR color-color diagrams (25/12), (60/25), and (100/60). The mean warm IR fraction is 0.55 when the grain mass absorption coefficient model with n=1.0 is used (or 0.72 if n=0.0 is adopted). The dust mass responsible for IR flux at 60 mkm is derived to be about 10mQ, assuming the dust clouds are optically thin, and using the dust temperature d 36 (deduced from the f60/f100ratio). There is a relation between LIR and LBl which points out that the most IRAS AKHs have rather enhanced SFR.
MTPA Control Method for MIDP SPMSM Drive System Using Angle Difference Controller and P&O Algorithm

This study presents a maximum torque per ampere (MTPA) control method for a mono inverter dual parallel (MIDP) surface-mounted permanent-magnet synchronous motor (SPMSM) drive system. The multimotor drive system has been extensively studied, because it can drive moreover two motors using only one inverter, reducing the costly power conversion circuit. However, existing studies concerning MIDP permanent-magnet synchronous motor drive systems focus on stabilizing the system, and studies regarding efficiency optimization are difficult to find. Some studies have shown the efficiency-optimizing method, but implementing is challenging because of the complicated calculations and algorithm. The proposed control method can achieve efficiency-optimizing operation using the angle difference controller. The angle difference controller controls the angle difference of two motors to an optimal value. Furthermore, the optimal angle difference of two motors can be easily obtained regardless of parameter errors, using the perturbation and observation algorithm. The proposed MTPA strategy is verified by performing simulations using matlab Simulink and applying the method to an actual MIDP SPMSM drive system.
Correlation between Psychological Distress with Level of Methamphetamine Dependence in Male Chronic Methamphetamine Users in the Rehabilitation Center of North Sumatra Province

: The aim of this study was to find the correlation between psychological distress and level of methamphetamine dependence in male chronic methamphetamine users. Drug users have fulfilled the inclusion criteria, has been done detoxification, male, methamphetamine use disorder, not psychotic. The exclusion criteria are those who have general medical illnesses based on the history of the disease, have a history of previous head trauma and organic mental illnesses. Structured interviews with MINI ICD-10 to determine subject is indeed a substance use disorder. To know the psychological distress, we determine it with the Hospital Anxiety and Depression Scale (HADS), and to see the score level of dependence, we used WHO ASSIST (The Alcohol, Smoking and Substance Involvement). The study found that out of 88 males subjects with methamphetamine use disorder. The median of dependency level score is 30.5 (6-41), and mean of HADS score is 15.67 (4.76). This study obtained Pearson correlation of psychological distress level scores and dependency level scores with r = 0.242, p = 0.023. There is a significant weak correlation between psychological distress level scores and dependency level scores.
Virulence determinants of Malassezia pachydermatis isolated from cases of canine dermatitis

Malassezia is a commensal organism known to cause disease under favourable conditions, and has been isolated from many animals as well as human beings. Malassezia pachydermatis is the most common cause of yeast dermatitis in dogs and there are many determinants involved in the production of disease in the host. This study aims to deterimine the presence of virulent determinants of the organisms isolated from fifteen dogs with dermatitis that may be involved in the pathogenic mechanism of Malassezia. The virulence determinants of M. pachydermatis viz; adherence, cellular surface hydrophobicity and biofilm formation were investigated. All the isolates studied were shown to produce all the virulent factors investigated in vitro which can be compared to the biological system. Adherence of organism on polystyrene plates was evident in all the isolates and the values ranged from 0.14 to 63 per cent with five isolates showing high adherence values. Hydrophobicity was variable and ranged from 1.78 to 69.46 per cent by two phase system with seven isolates showing moderate property. All the isolates were shown to produce biofilm by crystal violet staining technique and the optical density values ranged from 0.075 to 0.56 at 620 nm. No significant correlation was observed between the three virulent determinants examined. The presence of three virulent determinants investigated warrants their consideration in further studies for assessing the pathogenicity of Malassezia dermatitis in dogs.
Model-Based Compensation of Rate-Dependent Hysteresis in a Piezoresistive Strain Sensor

This paper is concerned with modeling of smart textiles, aimed at compensating their intrinsic nonlinearities. In particular, a new model is proposed to compensate for hysteresis and relaxation in strain sensors made of Electrolycra. These sensors are increasingly employed in emerging areas such as wearable electronics and soft robotics for their simple transduction mechanism and low cost. However, being intrinsically nonlinear, the signals measured from these devices need some processing, in order to increase their sensing accuracy. Here, we propose a new model for the compensation of the main distortions intrinsic to these soft sensors, which are mainly caused by hysteresis and relaxation, whose combined effect produces rate-dependent hysteresis. The model capabilities are tested on experimental data measured on Electrolycra. The comparisons with the results obtained with two different models witness the good behavior of the proposed model.
A Highly Linear Ka-Band GaN-on-Si Active Balanced Mixer for Radar Applications

A highly linear active mixer in Gallium Nitride on Silicon (GaN-on-Si) monolithic microwave integrated circuit (MMIC) technology, operating in Ka-band for radar applications is introduced. It exhibits a local oscillator (LO) balanced topology of gate-pumped mixers based on high-electron mobility transistors (HEMT) and operates in down-conversion mode. Its design principles and the theoretical foundation of its linearity features resulting from both the high power handling capability of GaN-on-Si HEMTs and the corresponding high applied LO level are presented. An extensive characterization based on excitation of a prototype by broadband continuous wave signals and frequency modulated continuous wave signals validates both the analytical treatment of its linearity and the design of the prototype of the mixer. In the 35–40 GHz operating band, this prototype exhibits a state-of-the-art input referred third order intercept point that reaches 39.1 dBm, and a maximum input referred second order intercept point of 39.4 dBm, with a corresponding conversion gain of −5.2 dB, and LO level of 24 dBm.
Efficient predictive model-based and fuzzy control for green urban mobility

In this thesis, we develop efficient predictive model-based control approaches, including model-predictive control (MPC) andmodel-based fuzzy control, for application in urban traffic networks with the aim of reducing a combination of the total time spent by the vehicles within the network and the total emissions. The thesis includes three main parts, where in the first part the main focus is on accurate approaches for estimating the macroscopic traffic variables, such as the temporal-spatial averages, from a microscopic point-of-view. The second part includes efficient approaches for solving the optimization problem of the nonlinear MPC controller. The third and last part of the thesis proposes an adaptive and predictivemodel-based type-2 fuzzy control scheme that can be implementedwithin amulti-agent control architecture.