Miracle-dz/UniFAR-FTUs huggingface dataset:
Customer Segmentation with Machine Learning for Online Retail Industry

In this study, a comparative analysis of various techniques is presented on customer segmentation methods based on online retail data. A few unsupervised machine learning (ML) clustering models such as K-means clustering model, hierarchical clustering model, Density-based Spatial Clustering of Applications with Noise (DBSCAN) model and a traditional model based on recency, frequency and monetary (RFM) clustering are evaluated in terms of the insight each model offers. The traditional model is included in the analysis since clustering models are not optimization models and the goodness of unsupervised models could only be evaluated with a practical business approach. The results are shared, and each model is assessed in terms of usability for marketing and communication strategies. At the end, the strengths and weaknesses of each model are discussed, and a methodology is proposed for selecting the best clustering method when facing the customer segmentation problem. A detailed literature review is also presented covering the developments in the field of artificial intelligence, clustering models in ML and examples of customer segmentation implementations in various industries.
Characterization of Peanut Protein Hydrolysate and Structural Identification of Umami-Enhancing Peptides

Umami peptides are naturally found in various foods and have been proven to be essential components contributing to food taste. Defatted peanut powder hydrolysate produced by a multiprotease (Flavorzyme, Alcalase, and Protamex) was found to elicit an umami taste and umami-enhancing effect. The taste profiles, hydrolysis efficiency, amino acids, molecular weight distribution, Fourier transform infrared spectroscopy (FT-IR), and separation fractions obtained by ultrafiltration were evaluated. The results showed that peanut protein was extensively hydrolyzed to give mainly (up to 96.84%) free amino acids and peptides with low molecular weights (<1000 Da). Furthermore, β-sheets were the major secondary structure. Fractions of 1–3000 Da and <1000 Da prominently contributed to the umami taste and umami enhancement. To obtain umami-enhancing peptides, these two fractions were further purified by gel filtration chromatography, followed by sensory evaluation. These peptides were identified as ADSYRLP, DPLKY, EAFRVL, EFHNR, and SDLYVR by ultra-performance liquid chromatography (UPLC), and had estimated thresholds of 0.107, 0.164, 0.134, 0.148, and 0.132 mmol/L, respectively. According to the results of this work, defatted peanut powder hydrolysate had an umami taste and umami-enhancing effect, and is a potential excellent umami peptide precursor material for the food industry.
Roles of Abscisic Acid and Gibberellins in Stem/Root Tuber Development

Root and tuber crops are of great importance. They not only contribute to feeding the population but also provide raw material for medicine and small-scale industries. The yield of the root and tuber crops is subject to the development of stem/root tubers, which involves the initiation, expansion, and maturation of storage organs. The formation of the storage organ is a highly intricate process, regulated by multiple phytohormones. Gibberellins (GAs) and abscisic acid (ABA), as antagonists, are essential regulators during stem/root tuber development. This review summarizes the current knowledge of the roles of GA and ABA during stem/root tuber development in various tuber crops.
Soil Acidity Conditioning the Productivity and Physiology of Wheat Inoculated with Azospirillum brasilense

ABSTRACT The increase in the world population creates the need for sustainable food production and the use of synthetic fertilizers with growth-promoting bacteria. The objective of this research was to evaluate the acidity on the physiological and productive variables of wheat inoculated with Azospirillum brasilense and treated with osmoprotective additives. Combinations of A. brasilense, osmoprotectant and chemical treatment were evaluated in wheat seeds planted in contrasting acidity soil (pHs: 4.8 and 6.5). Evaluations of the physiological parameters were carried out in the foliar tissue (hydrogen peroxide content, superoxide dismutase activity, lipid peroxidation, content of chlorophyll a, b, and total and carotenoid and nitrate reductase enzyme activity) during the vegetative period and flowering. The grain yield components were evaluated after the physiological maturation. Plants grown in uncorrected soil acidity (pH: 4.8) showed higher lipid peroxidation. The other plants (pH: 6.5) have higher levels of nitrate reductase. Higher nitrate reductase activity was also observed in plants inoculated with A. brasilense. Therefore, in soil acidity 6.5, both A. brasilense isolate or combined with osmoprotective additive increased the grain yield. Nevertheless, the osmoprotectant application did not attenuate the effects of the chemical treatment of seeds and exerted a negative effect to inoculation with A. brasilense. Graphical abstract
Prototheca Infections and Ecology from a One Health Perspective

Prototheca microalgae were only recognized as pathogens of both humans and animals in the 1960s; however, since then, these microbes have been drawing increasing interest in both human and veterinary medicine. The first human outbreak of protothecosis in a tertiary care chemotherapy ward in 2018 further highlighted the need to understand in more depth and detail their ecology, etiology, pathogenesis and routes of transmission between different hosts, environments and habitats from a One Health perspective. Protothecal infections have been reported in a growing number of cattle herds around the world in recent decades, and Prototheca has become an important bovine mastitis pathogen in certain countries and regions. The survival of Prototheca in the environment and its ability to spread in the herd pose a serious challenge to the management of infected dairy farms. Prevention of the disease is particularly important, as there is no effective and reliable treatment for it and the chances of self-healing are minimal. Therefore, the development of more effective drugs is needed for the treatment of human and animal protothecosis. The prudent use of antibiotics and their replacement by alternative or preventive measures, when possible, may further contribute to the control of protothecal infections.
Alleviation of Tris(2-chloroethyl) Phosphate Toxicity on the Marine Rotifer Brachionus plicatilis by Polystyrene Microplastics: Features and Molecular Evidence

As emerging pollutants, microplastics (MPs) and organophosphorus esters (OPEs) coexist in the aquatic environment, posing a potential threat to organisms. Although toxicological studies have been conducted individually, the effects of combined exposure are unknown since MPs can interact with OPEs acting as carriers. In this study, we assessed the response of marine rotifer, Brachionus plicatilis, to co-exposure to polystyrene MPs and tris(2-chloroethyl) phosphate (TCEP) at different concentrations, including population growth, oxidative status, and transcriptomics. Results indicated that 0.1 μm and 1 μm MPs were accumulated in the digestive system, and, even at up to 2000 μg/L, they did not exert obvious damage to the stomach morphology, survival, and reproduction of B. plicatilis. The presence of 1 μm MPs reversed the low population growth rate and high oxidative stress induced by TCEP to the normal level. Some genes involved in metabolic detoxification and stress response were upregulated, such as ABC and Hsp. Subsequent validation showed that P-glycoprotein efflux ability was activated by combined exposure, indicating its important role in the reversal of population growth inhibition. Such results challenge the common perception that MPs aggravate the toxicity of coexisting pollutants and elucidate the molecular mechanism of the limited toxic effects induced by MPs and TCEP.
A Novel Approach to the Design of an In-Wheel Semi-Anhysteretic Axial-Flux Switched-Reluctance Motor Drive System for Electric Vehicles

A NOVEL APPROACH TO THE DESIGN OF AN IN-WHEEL SEMI-ANHYSTERETIC AXIAL-FLUX SWITCHED-RELUCTANCE MOTOR DRIVE SYSTEM FOR ELECTRIC VEHICLES Tim Lambert Advisors: University of Guelph, 2013 Professor Shohel Mahmud Professor Mohammad Biglarbegian This thesis presents the development of an in-wheel drive system consisting of an axial-flux switched-reluctance motor and a hub suspension. The motor is designed using Maxwell’s stress tensor and numerical analysis techniques, including FEA and transient numerical simulations. A new integral inductance function is introduced that improves the accuracy of the motor model, and a new in-phase current-shaping technique is implemented using a fuzzy controller to extend the constant-power region of the motor. The hub suspension system is simulated using a half-car model with 6 degrees of freedom, and the overall torque, power, and efficiency of the drive system is calculated. A peak torque of 500[N ·m] is developed at the high end of the drive system’s speed range, and the hub suspension system is shown to eliminate the impact of the motor’s increased unsprung mass on
Technological competition: a path towards commoditization or differentiation?

Technological rivalry is recognized as a key dimension of competition and innovation strategies in the digital era. It is particularly important in strategies focused on disruptive and repeated innovations, where each step contributes to shaping the design of the offering, the structuring of the market and the value chain. These technological trajectories are built on the basis of tensions between two contradictory objectives: specialization aimed at creating proprietary systems and standardization aimed at supplying the overall market. In the former case, successive innovations support competition between exclusive and proprietary ecosystems. In the latter case, commoditized devices create opportunities for alternative actors to engage in innovation and value creation. The e-book reader market serves as a key example of the issues at stake in terms of technological rivalry among technology suppliers, digital platforms, and publishers.
Atrial Fibrillation and Heart Failure

Atrial fibrillation (AF) is the most common sustained arrhythmia worldwide and has a strong association with heart failure (HF). It often remains unclear if HF is the cause or consequence of AF due to the complexity of the processes that are involved in both the perpetuation of AF and the development of HF. To date, two therapeutic strategies are accepted as the standard of care in AF patients with heart failure. Rhythm control aims to permanently restore sinus rhythm, whereas a rate-control strategy aims to slow ventricular rate without the termination of AF. In the last 5 years a tremendous number of important studies have been published investigating the optimal therapeutic strategy in HF patients. This review highlights the important studies with respect to the involvement of AF in promoting left-ventricular dysfunction and discusses the optimal strategy in HF patients suffering from AF.
A novel flame retardant consisting of functionalized Salen-Ni based polyphosphazene microspheres

A functionalized cross-linked polyphosphazenes microsphere (Salen-PZN-Ni@DHPP-PTS) was prepared by wrapping Salen-Ni basis polyphosphazenes (Salen-PZN-Ni) with a kind of hybrid flame retardant (DHPP-PTS) to improve the flame retardancy and smoke suppression properties of epoxy (EP) composites. Thermogravimetric analysis showed that the addition of Salen-PZN-Ni@DHPP-PTS greatly improved the thermal stability of the EP composites. The addition of 5 wt% Salen-PZN-Ni@DHPP-PTS remarkably improved the fire safety of EP, which was illustrated by the results of the cone calorimeter. For example, the peak heat release rate and total heat release rate of the EP composites were reduced by 44.2% and 33.1%, respectively. The limiting oxygen index value of 5% Salen-PZN-Ni@DHPP-PTS/EP composite reached 29.8% and UL-94 achieved V-1 rating. In addition, the introduction of Salen-PZN-Ni@DHPP-PTS effectively suppressed the production of toxic CO and other volatiles. Meantime, the synergistic effect between Salen-PZN-Ni and DHPP-PTS was found. The potential flame retardant mechanism of Salen-PZN-Ni@DHPP-PTS is regarded as the synergistic catalytic carbonization effect and the extremely thermally stable components forming. Enhanced fire safety of EP composites by synergistic interaction of various components (nickel and DHPP-PTS) with polyphosphazenes microspheres.
Estimating the Analytical Performance of Raman Spectroscopy for Quantification of Active Ingredients in Human Stratum Corneum

Confocal Raman microscopy (CRM) has become a versatile technique that can be applied routinely to monitor skin penetration of active molecules. In the present study, CRM coupled to multivariate analysis (namely PLSR—partial least squares regression) is used for the quantitative measurement of an active ingredient (AI) applied to isolated (ex vivo) human stratum corneum (SC), using systematically varied doses of resorcinol, as model compound, and the performance is quantified according to key figures of merit defined by regulatory bodies (ICH, FDA, and EMA). A methodology is thus demonstrated to establish the limit of detection (LOD), precision, accuracy, sensitivity (SEN), and selectivity (SEL) of the technique, and the performance according to these key figures of merit is compared to that of similar established methodologies, based on studies available in literature. First, principal components analysis (PCA) was used to examine the variability within the spectral data set collected. Second, ratios calculated from the area under the curve (AUC) of characteristic resorcinol and proteins/lipids bands (1400–1500 cm−1) were used to perform linear regression analysis of the Raman spectra. Third, cross-validated PLSR analysis was applied to perform quantitative analysis in the fingerprint region. The AUC results show clearly that the intensities of Raman features in the spectra collected are linearly correlated to resorcinol concentrations in the SC (R2 = 0.999) despite a heterogeneity in the distribution of the active molecule in the samples. The Root Mean Square Error of Cross-Validation (RMSECV) (0.017 mg resorcinol/mg SC), The Root Mean Square of Prediction (RMSEP) (0.015 mg resorcinol/mg SC), and R2 (0.971) demonstrate the reliability of the linear regression constructed, enabling accurate quantification of resorcinol. Furthermore, the results have enabled the determination, for the first time, of numerical criteria to estimate analytical performances of CRM, including LOD, precision using bias corrected mean square error prediction (BCMSEP), sensitivity, and selectivity, for quantification of the performance of the analytical technique. This is one step further towards demonstrating that Raman spectroscopy complies with international guidelines and to establishing the technique as a reference and approved tool for permeation studies.
Microbiological Spectrum, Antibiogram and Bacteraemia in Biliary Tract Infections- A Study from Tertiary Centre of North India

Objectives: The present study was undertaken to understand the microbiological profile, clinical presentation, associated bacteraemia and present antibiogram pattern of various isolates from patients with biliary tract infection admitted in a tertiary care centre in India. Methods: In this retrospective study, Bile samples were collected from adult patients admitted in our hospital and were processed as per standard protocol. The results were interpreted as per Clinical Laboratory Standards Institute (CLSI) 2020 guidelines. Bacterial isolates were categorised as MDR and PDR as per CDC. Results: 326 bile samples were sent for aerobic culture and susceptibly testing. 197 (60.42%) of these samples were culture-positive, and the remaining 129 (39.57%) were sterile in nature. A total of 289 pathogens were isolated; Escherichia coli (37.37 % n=108) was predominant, followed by Klebsiella pneumoniae (25.60%, n=74). 170 (60.49%) isolates were resis­tant and the remaining 111 (39.50%) were susceptible to various drugs tested. 27 ESBL producing strains of E.coli( n= 20) and Klebsiella spp (n= 7) and 21 CRE producing strains of E coli ( n= 12) and Klebsiella spp( n=9) were reported . 5 isolates of Klebsie­lla spp. and a single E.coli were PDR and susceptible to colis­tin (MIC =0.5 mcg/ml) by microbroth dilution test. Conclusion: The soaring rates of infection mainly by gram-negative bacteria are a red flag with the emergence of multidrug resistant organisms and change in the anti-microbiological spectrum and pattern of biliary tract infections, there is an urgent need for the empirical and prophylactic an­timicrobial therapy in every clinical setting.
Experimental Study of the Effect of Air Filter Pressure Drop on Internal Combustion Engine Performance

The paper presents the problem of the effect of air filter pressure drop on the operating parameters of a modern internal combustion engine with compression ignition. A literature analysis of the results of investigations of the effect of air filter pressure drop on the filling, power and fuel consumption of carburetor and diesel engines with classical injection system was carried out. It was shown that each increase in the air filter pressure drop Δpf by 1 kPa results in an average decrease in engine power by SI 1–1.5% and an increase in specific fuel consumption by about 0.7. For compression ignition engines, the values are 0.4–0.6% decrease in power and 0.3–0.5% increase in specific fuel consumption. The values of the permissible resistance of the air filter flow Δpfdop determined from the condition of 3% decrease in engine power are given, which are at the level of 2.5–4.0 kPa—passenger car engines, 4–7 kPa—truck engines and 9–12 kPa—special purpose vehicles. Possibilities of decreasing the pressure drop of the inlet system, which result in the increase of the engine filling and power, were analyzed. The program and conditions of dynamometer engine tests were worked out in respect to the influence of the air filter pressure drop on the operation parameters of the six-cylinder engine of the swept volume Vss = 15.8 dm3 and power rating of 226 kW. Three technical states of the air filter were modeled by increasing the pressure drop of the filter element. For each technical state of the air filter, measurements and calculations of engine operating parameters, including power, hourly and specific fuel consumption, boost pressure and temperature, were carried out in the speed range n = 1000–2100 rpm. It was shown that the increase in air filter pressure drop causes a decrease in power (9.31%), hourly fuel consumption (7.87%), exhaust temperature (5.1%) and boost pressure (3.11%). At the same time, there is an increase in specific fuel consumption (2.52%) and the smoke of exhaust gases, which does not exceed the permissible values resulting from the technical conditions for admission of vehicles to traffic.
Sustainable Entrepreneurship in Malaysian Companies

Sustainable entrepreneurship is considered to be combined with economic, social, and environmental value creation, and is considered a combination of social enterprise and environmental enterprise. When creating sustainable entrepreneurs in the community, small and medium-sized enterprises (SMEs) are significant substances that can't be overlooked. This is because they have made significant commitments to the economic advancement of a nation. The SMEs in Malaysia are without exception. When creating sustainable entrepreneurs in Malaysia, SMEs are significant elements that can't be disregarded. However, due to the lack of research, the existing literature has not yet provided sufficient explanation in the establishment of sustainable entrepreneurship in Malaysian SMEs. This research included an introduction that gives an overview of the research, continued by the review of existing literature that correlates to the research topic followed by the methodology adopted for this research. Specifically, this research extends the Entrepreneurial Event Model, Social Identity Theory, and Social Capital Theory to test the proposed framework. To test the research framework and achieve the research objectives, the survey questionnaire was used to distribute the primary data to 400 respondents (entrepreneurs from Malaysian SMEs). The research used Analysis of Moment Structure (AMOS) and Statistical Package of Social Science (SPSS) to encode and analyse the main data collected in this study. Furthermore, the research also provides references for future practical and theoretical contributions. This research provide new and important insights for SMEs, entrepreneurs, employees, and institutions through empirical testing of the testing framework, thereby contributing to knowledge. Keywords: Small and Medium-Sized Enterprises (SMEs), Sustainable Entrepreneurship, Perceived Behavioural Control, Age, Perceived Desirability, Perceived Feasibility, Propensity to Act, Environmental Awareness, Psychological Capital, Self- Categorization, Social Networks, Reciprocity
Research of U-Net-Based CNN Architectures for Metal Surface Defect Detection

The quality, wear and safety of metal structures can be controlled effectively, provided that surface defects, which occur on metal structures, are detected at the right time. Over the past 10 years, researchers have proposed a number of neural network architectures that have shown high efficiency in various areas, including image classification, segmentation and recognition. However, choosing the best architecture for this particular task is often problematic. In order to compare various techniques for detecting defects such as “scratch abrasion”, we created and investigated U-Net-like architectures with encoders such as ResNet, SEResNet, SEResNeXt, DenseNet, InceptionV3, Inception-ResNetV2, MobileNet and EfficientNet. The relationship between training validation metrics and final segmentation test metrics was investigated. The correlation between the loss function, the , , , and validation metrics and test metrics was calculated. Recognition accuracy was analyzed as affected by the optimizer during neural network training. In the context of this problem, neural networks trained using the stochastic gradient descent optimizer with Nesterov momentum were found to have the best generalizing properties. To select the best model during its training on the basis of the validation metrics, the main test metrics of recognition quality (Dice similarity coefficient) were analyzed depending on the validation metrics. The ResNet and DenseNet models were found to achieve the best generalizing properties for our task. The highest recognition accuracy was attained using the U-Net model with a ResNet152 backbone. The results obtained on the test dataset were and .