Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust stability analysis and control for fuzzy systems with uncertainties using the delta operator

Robust stability analysis and fuzzy control for the delta operator systems with uncertainties based on Takagi-Sugeno (T-S) model is studied. In terms of Lyapunov stability theorem in delta domain, the sufficient conditions for robust stability of the fuzzy systems are presented using the delta operator via LMI. The corresponding state feedback controller design is given. The proposed results can unify previous related conclusions of the continuous and discrete fuzzy systems with uncertainties. An illustrative example shows the feasibility of the proposed method.
Modeling torsional control of molecules with four-dimensional, two-dimensional, and one-dimensional approaches

Torsional control is studied theoretically using a four-dimensional (4D) model introduced recently [Phys. Rev. Lett. 107, 113004 (2011) and Phys. Rev. A 87, 043403 (2013)] for calculating energy levels and eigenfunctions of nonrigid biphenyl-like molecules undergoing internal rotation and subject to a strong electric field. The time-dependent Schr\"odinger equation is solved to determine the behavior of the molecule when submitted to a short laser pulse. Torsional alignment is investigated for four limiting hindering potentials and for several peak laser intensities. The results obtained with the 4D model are compared to those from already available 2D and 1D models. Similar results are found with the 4D and 2D model and are consistent with the molecule interacting the most with the electric field for the hindering potential displaying four minima with ${D}_{2d}$ symmetry staggered equilibrium configurations. Molecular axis alignment is also investigated and it is found that the one arising with the 4D model starts deviating substantially from the one arising with a rigid rotator for a value of the peak laser intensity of $3\ifmmode\times\else\texttimes\fi{}{10}^{13}$ ${\mathrm{W}/\mathrm{cm}}^{2}$.
Online Personalized Preference Learning Method Based on In-Formative Query for Lane Centering Control Trajectory

The personalization of autonomous vehicles or advanced driver assistance systems has been a widely researched topic, with many proposals aiming to achieve human-like or driver-imitating methods. However, these approaches rely on an implicit assumption that all drivers prefer the vehicle to drive like themselves, which may not hold true for all drivers. To address this issue, this study proposes an online personalized preference learning method (OPPLM) that utilizes a pairwise comparison group preference query and the Bayesian approach. The proposed OPPLM adopts a two-layer hierarchical structure model based on utility theory to represent driver preferences on the trajectory. To improve the accuracy of learning, the uncertainty of driver query answers is modeled. In addition, informative query and greedy query selection methods are used to improve learning speed. To determine when the driver’s preferred trajectory has been found, a convergence criterion is proposed. To evaluate the effectiveness of the OPPLM, a user study is conducted to learn the driver’s preferred trajectory in the curve of the lane centering control (LCC) system. The results show that the OPPLM can converge quickly, requiring only about 11 queries on average. Moreover, it accurately learned the driver’s favorite trajectory, and the estimated utility of the driver preference model is highly consistent with the subject evaluation score.
Brain Computer Interface for Emotion Recognition Based on EEG Signal

This paper presents an emotion recognition system based on electroencephalography (EEG) signals. This system helps medical practitioners to analyse the mental health of an individual. Eight healthy volunteers/ subjects had participated in this experiment. A specific feeling is evoked using particular songs and videos that are collected to present before the subjects. Total 6 emotions namely neutral, happy, sad, disgust, fear and motivate are captured and analysed. Data is classified using eighteen statistical features. The sampling rate is 1200Hz. Signals are filtered using pre-processing techniques. Frequency, time and timefrequency domain features are extracted. An array of 10 classifiers is used including Decision Tree, Random Forest, Optimised Random Forest, Logistic regression, Support Vector Machine (SVM) Polynomial, SVM Sigmoid, SVM RBF, K-Nearest Neighbours, Gaussian NB, Gradient Boosting Classifier. Accuracy, recall, precision, and F1 score are employed as performance metrics. The accuracy obtained for SVM classifier was 79.34%.
Socioeconomic deprivation is associated with reduced response and lower treatment persistence with TNF inhibitors in rheumatoid arthritis

Abstract Objective To investigate the association between socioeconomic deprivation and outcomes following TNF inhibitor (TNFi) treatment. Methods Individuals commencing their first TNFi in the British Society for Rheumatology Biologics Register for RA (BSRBR-RA) and Biologics in RA Genetics and Genomics Study Syndicate (BRAGGSS) cohort were included. Socioeconomic deprivation was proxied using the Index of Multiple Deprivation and categorized as 20% most deprived, middle 40% or 40% least deprived. DAS28-derived outcomes at 6 months (BSRBR-RA) and 3 months (BRAGGSS) were compared using regression models with the least deprived as referent. Risks of all-cause and cause-specific drug discontinuation were compared using Cox models in the BSRBR-RA. Additional analyses adjusted for lifestyle factors (e.g. smoking, BMI) as potential mediators. Results 16 085 individuals in the BSRBR-RA were included (mean age 56 years, 76% female), of whom 18%, 41% and 41% were in the most, middle and least deprived groups, respectively. Of 3459 included in BRAGGSS (mean age 57, 77% female), proportions were 22%, 36% and 41%, respectively. The most deprived group had 0.3-unit higher 6-month DAS28 (95% CI 0.22, 0.37) and were less likely to achieve low disease activity (odds ratio [OR] 0.76; 95% CI 0.68, 0.84) in unadjusted models. Results were similar for 3-month DAS28 (β = 0.23; 95% CI 0.11, 0.36) and low disease activity (OR 0.77; 95% CI 0.63, 0.94). The most deprived were more likely to discontinue treatment (hazard ratio 1.18; 95% CI 1.12, 1.25), driven by ineffectiveness rather than adverse events. Adjusted estimates were generally attenuated. Conclusion Socioeconomic deprivation is associated with reduced response to TNFi. Improvements in determinants of health other than lifestyle factors are needed to address socioeconomic inequities.
Plant growth regulators improved cutting induced physio-biochemical responses to postponement senescence in chrysanthemum

The marketability of cut flowers relies on its postharvest longevity, making it crucial to develop technologies that can extend its vase life. The vase life in chrysanthemum is dependent upon floret senescence and leaf yellowing. In view of extending the vase life, the present study elucidates the implication of plant growth regulators viz. benzyl adenine (BA), thidiazuron (TDZ) and salicylic acid (SA) on postharvest performance and flower longevity of chrysanthemum stems. The harvested stems were treated with various concentrations viz. BA and SA at 50,100,150 and 200 µM and TDZ at 5,10,15 and 20 µM. Treatments containing 10 µM TDZ and 100 µM BA were most effective in improving the longevity (23.35 and 20.32 days respectively) of cut chrysanthemum stems. However, TDZ outplayed BA followed by SA extends the flower longevity through the maintenance of higher physiological and biochemical characteristics. Cluster analysis inferred that the treatments of 50 and100 µM BA and 5 and10 µM TDZ were found to be efficient in delaying floret senescence (24.01 days) and leaf yellowing (20.54 days) in cut chrysanthemum stems. Postharvest longevity exhibited a positive correlation with antioxidant activities, total soluble sugars and proteins, while it showed a negative correlation with anthocyanin and carotenoid contents. The results have demonstrated that use of growth regulators such as benzyl adenine, thidiazuron and salicylic acid may preserve the quality of cut chrysanthemum stems and delay their senescence
Sacrificial Doping as an Approach to Controlling the Energy Properties of Adsorption Sites in Gas-Sensitive ZnO Nanowires

Currently, devices for environmental gas analyses are required in many areas of application. Among such devices, semiconductor-resistive gas sensors differ advantageously. However, their characteristics need further improvement. The development of methods for controlling the surface properties of nanostructured metal oxides for their use as gas sensors is of great interest. In this paper, a method involving the sacrificial doping of ZnO nanowires to control the content of their surface defects (oxygen vacancies) was proposed. Zinc oxide nanowires were synthesized using the hydrothermal method with sodium iodide or bromide as an additional precursor. The surface composition was studied using X-ray photoelectron spectroscopy. The sensor properties of the isopropyl alcohol vapors at 150 °C were studied. It was shown that a higher concentration of oxygen vacancies/hydroxyl groups was observed on the surfaces of the samples synthesized with the addition of iodine and bromine precursors compared to the pure zinc oxide nanowires. It was also found out that these samples were more sensitive to isopropyl alcohol vapors. A model was proposed to explain the appearance of additional oxygen vacancies in the subsurface layer of the zinc oxide nanowires when sodium iodide or sodium bromide was added to the initial solution. The roles of oxygen vacancies and surface hydroxyl groups in providing the samples with an increased sensitivity were explained. Thus, a method involving the sacrificial doping of zinc oxide nanowires has been developed, which led to an improvement in their gas sensor characteristics due to an increase in the concentration of oxygen vacancies on their surface. The results are promising for percolation gas sensors equipped with additional water vapor traps that work stably in a high humidity.
Using Landsat to Identify Thunderstorm Damage in Agricultural Regions

Abstract During 12 and 18 August 1999, severe thunderstorms produced damaging winds and hail that caused an estimated $50 million in damage to agriculture in west-central Illinois. Landsat-7 imagery was obtained to determine the arealextent of damage and produce a crop damage dollar estimate. The normalized difference vegetation index (NDVI) was calculated for images taken “before” and “after” the severe thunderstorm events in order to examine the changes in NDVI, or vegetation vigor. A differenced image was also produced by subtracting the NDVI of the two images. Landsat-7 data was found to be useful for identifying the areal extent of severe thunderstorm damage in west-central Illinois. In comparing the detection of damage produced by high winds and hail, it was found that hail damage was considerably easier to identify. This is due to the fact that large hail typically destroys the crops while high winds blow over corn plants that can remain rooted and survive. Additionally, county estimates of dollar .
Social support from family, associated factors and relationship with glycemic control among diabetic patients in Uganda: a cross-sectional study

Introduction social support from family members in diabetes management is a predictor of optimal glucose control. There is limited evidence of the relationship in Uganda. The objective was to determine association of social support from family and glycemic control, and association of social demographic and clinical characteristics with family support among diabetic patients in eastern Uganda. Methods this was a cross-sectional study involving 405 adult patients attending diabetic clinics between May 2021 and June 2021. Socio-demographics, clinical characteristics, social support from family, and glycemic control data were collected. Descriptive statistics were done and associations were determined using Pearson chi-square and Fisher´s exact tests. Generalized linear model was used to determine independent association with social support from family. Results the mean age was 52 years, (60%) were female, majority (49.4%) were 45-64 years old. Perceived social support from family (PSS-fa) and good glucose control were found in; (95.3%) and (20.99%) respectively. PSS-fa was associated with good glucose control. Financial contribution from family members to cost of care, cohesion among family members in support of care, being (married/cohabiting) and monthly income ≥28 USD were associated with PSS-fa. Factors independently associated with PSS-fa were; female gender, financial contribution to cost of care and cohesion among family in support of care. Conclusion social support from family was associated with good glycemic control. Factors associated with PSS-fa were; female gender, financial contribution from family to cost of care and cohesion among family in support of care.
Filter sterilized carcass rinsate for recovery of Salmonella species with various concentrations of cetylpyridinium chloride

Abstract Controlling Salmonella in poultry processing continues to be important to processors and consumers. Cetylpyridinium chloride (CPC) has proven to be effective in vitro in controlling Salmonella. This study evaluated the recovery of Salmonella after overnight storage in 4°C filter‐sterilized carcass rinsate containing CPC from 0.44 to 909 ppm (μg/mL). Ten Salmonella serotypes (18 strains), of which 6 serotypes are commonly isolated from poultry products, were grown in Bacto‐Tryptic Soy Broth overnight at 37°C. Serial dilutions of a CPC/propylene glycol solution were prepared in 24‐well tissue culture plates containing filter‐sterilized carcass rinsate. Approximately 107 cfu/mL of each Salmonella serotype was added to the appropriate wells. Inoculated plates were stored overnight at 4°C. After storage, triplicate plates of brilliant green agar with sulfapyridine (BGS) were surface inoculated with 10 μL of the contents for each well, streaked for isolation, and incubated at 37°C for 24 h. Three replications were conducted. The presence of typical colonies on BGS plates was recorded as growth and verified through biochemical and serological testing. Of the serotypes chosen, Salmonella Kentucky, Dublin, and Enteritidis were the least resistant to CPC with a median minimum inhibitory concentration (MIC) of 14.22 μg/mL (range from 3.55 to 56.88 μg/mL); S. Typhimurium demonstrated a median MIC of 114.00 μg/mL (range from 28.44 to 114.00 μg/mL). Residual CPC potentially remaining attached to a carcass or in the weep after processing could potentially alter which Salmonella serotype is recovered from a carcass rinse due to different growth patterns during regulatory testing, with a potential for more virulent strains not to be recovered.
Efficient Gated Convolutional Recurrent Neural Networks for Real-Time Speech Enhancement

Deep learning (DL) networks have grown into powerful alternatives for speech enhancement and have achieved excellent results by improving speech quality, intelligibility, and background noise suppression. Due to high computational load, most of the DL models for speech enhancement are difficult to implement for real-time processing. It is challenging to formulate resource efficient and compact networks. In order to address this problem, we propose a resource efficient convolutional recurrent network to learn the complex ratio mask for real-time speech enhancement. Convolutional encoder-decoder and gated recurrent units (GRUs) are integrated into the Convolutional recurrent network architecture, thereby formulating a causal system appropriate for real-time speech processing. Parallel GRU grouping and efficient skipped connection techniques are engaged to achieve a compact network. In the proposed network, the causal encoder-decoder is composed of five convolutional (Conv2D) and deconvolutional (Deconv2D) layers. Leaky linear rectified unit (ReLU) is applied to all layers apart from the output layer where softplus activation to confine the network output to positive is utilized. Furthermore, batch normalization is adopted after every convolution (or deconvolution) and prior to activation. In the proposed network, different noise types and speakers can be used in training and testing. With the LibriSpeech dataset, the experiments show that the proposed real-time approach leads to improved objective perceptual quality and intelligibility with much fewer trainable parameters than existing LSTM and GRU models. The proposed model obtained an average of 83.53% STOI scores and 2.52 PESQ scores, respectively. The quality and intelligibility are improved by 31.61% and 17.18% respectively over noisy speech.
Cognitive impairment in type 2 diabetes mellitus: prospects for the use of metformin

Literature data on epidemiology, mechanisms of development, features of the course of cognitive disorders in type 2 diabetes mellitus (T2DM), as well as prospects for their treatment and prevention were analyzed. Diabetes mellitus is recognized as an independent factor for cognitive impairment and is associated with an increased risk of dementia, the main causes of which are Alzheimer’s disease and vascular dementia. Results of recent research have shown that T2DM due to insulin resistance and a number of other mechanisms accelerates the aging of the brain and the decline of cognitive functions from mild cognitive impairment to dementia, the risk of which is almost doubled. Epidemiological, neuroimaging, and autopsy studies confirm the presence of both cerebrovascular and neurodegenerative mechanisms of brain damage in T2DM. Poor glycemic control is associated with cognitive decline while longer course of diabetes — with deterioration of cognitive functions. According to current guidelines, annual screening is indicated for adults aged 65 and older for early detection of mild cognitive impairment or dementia. The strategy for the treatment and prevention of cognitive impairment in diabetes should be individualized in such a way as to minimize the occurrence of both hyperglycemia and hypoglycemia, and should also be effective in preventing the deve­lopment of vascular complications. Elderly patients with cognitive impairment should have less stringent glycemic goals (such as glycated hemoglobin < 8.0 %). The results of experimental and clinical studies proved that metformin has a whole range of neurospecific properties, which generally prevent the progression of diabetic cerebral disorders and provide a nootropic effect. It has been found that the drug can improve cognitive functions and mood in patients with T2DM, and also prevents the development of dementia, including Alzheimer’s type. The use of metformin allows you to preserve cognitive functions due to a powerful hypoglycemic effect, a low risk of hypoglycemia, as well as a positive effect on other pathogenetic links in the development of diabetic cerebral changes — insulin resistance, hyperinsulinemia, dyslipidemia, inflammation, micro- and macrovascular disorders, which makes it a priority in the treatment of patients with diabetes of any age.
Mathematical modeling of the temperature regime in industrial premises

Comfortable temperature conditions in any room are provided by heating systems, thermal insulation properties of enclosing structures, external environmental conditions. Practical experience, literature analysis show that the existing temperature control systems in industrial premises have disadvantages. Eliminating is possible by using a multi-circuit functional control structure, allowing to reduce the inertia of the temperature control system by taking into account the outdoor temperature, the influence of natural light on the temperature inside the production facility. For its operation, a practically oriented mathematical model is needed, which allows taking into account the influence of a large number of external factors on the temperature regime with minimal delay. A mathematical model has been developed for use as a program in industrial electronics devices for predicting, correcting the temperature field, regulating the temperature regime in the production areas of a room at any point. Based on experimental data, the analysis of the results of the adequacy of the mathematical model shows that the temperature values obtained by the mathematical model of forecasting, correction of the temperature regime fall within the confidence interval and are within the standard deviation. The mechanism of technical implementation is proposed and the prospects of its use are shown.
When the President Endorses the Nation’s Next Leader: Detecting the Concept of Power in Javanese Culture Through Presidential Communication

This article examines how President Joko Widodo (Jokowi) exercises his power through his presidential communication. It focuses on Jokowi’s statement when he endorses presidential candidates by using simple language, codes, and symbols. The purpose of this study is to decipher the possible meaning within the statement of Jokowi regarding his endorsement of presidential candidates. It also attempts to contextualize it within the larger setting of political public relations by using soft propaganda techniques. This study uses a qualitative case study approach that uses the lens of Benedict Anderson’s concept of power in Javanese culture and Eric Louw’s premise about the hype maker or messenger. Researchers argue that Jokowi's communication, in this case, can be interpreted as a political game where the president tries to show his power by deliberately violating political procedures to remove uncertainty among the political elite. The president’s power may also be seen in his soft propaganda communication, which employs “oversimplification” and “logical fallacies” techniques to stir up public emotion and resonance in the media and political elite. This article offers some critical insights on presidential communication strategy from different perspectives, particularly through the concept of power in the Javanese culture, the president’s role as a hype maker, and how political public relations strategies can be harnessed to modify a political process.
Study of a pH-Sensitive Hologram for Biosensing Applications

: Photopolymers are widely utilized as holographic recording media due to their ease of preparation and lack of wet chemistry post-processing. Holographic sensors constructed from a pH-sensitive photopolymer ﬁlm have several applications in biosensors and the medical diagnostic ﬁeld. However, the stability of photopolymer ﬁlms in an aqueous medium is one of the most important challenges in their application for biosensing. Furthermore, the pH of the solution is another important parameter for biochemical reactions. In this work, we compared the pH sensitivity and stability of our holographic grating against two widely utilized classes of buffers; Phosphate Buffered Saline (PBS) and Tris-Acetate-EDTA (TAE) at two different pH values of 7.36 and pH 8.3, respectively. It was observed that a physiological pH (pH 7.4) had a negligible effect on the diffraction efﬁciency of the holographic sensor while it signiﬁcantly deteriorated at a higher value of ~pH 8.3. This high sensitivity towards the minute pH difference of our holographic sensor could potentially be exploited for pH-based biosensing applications such as urea detection.
Turing Algorithms in Art

Exemplifying with sculptures the author created, the article shows that ontological algorithms can yield aesthetic content, while epistemological algorithms can capture it. Bridging the gap between art and logic creates new and exciting aesthetic opportunities, allaying Henry Moore’s fears of ‘paralysis by analysis. ’ On the flip side, appreciating all that algorithmic art has to offer poses intellectual challenges that run counter to subjectivist approaches to art and its education.