Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing quality parameters obtained using destructive and optical methods in grading tomatoes

- Optical methods for analysing fruit quality have various advantages compared to conventional methods, including not destroying the sample and the possibility of automating the quality control process. The aim of this study was to compare arti ﬁ cial neural networks developed from biological activity indices obtained using the biospeckle laser optical technique, and from physico-chemical variables obtained by conventional destructive techniques, through an evaluation of their precision in classifying ripe tomatoes, using as a reference an earlier classi ﬁ cation carried out by visual inspection. A total of 150 tomatoes were used in the experiment, divided into three ripening stages. Multivariate principal component analysis was used to evaluate interaction of the variance within the groups of data obtained using the biospeckle laser technique and destructive laboratory methods. Two arti ﬁ cial neural networks were developed, the ﬁ rst generated using biological activity indices as input vectors, and the second using physico-chemical variables. The precision of the two neural networks was compared using the Kappa index and overall accuracy, and was based on a reference classi ﬁ cation. The variation in ripening as a function of the biological activity indices was explained by the ﬁ rst principal component. The neural network generated from the biological activity indices showed the best performance in classifying the tomatoes into the three ripening stages, with a signi ﬁ cant Kappa index and an overall accuracy of 67.5%.
Scientific knowledge produced in the Nursing area about violence: an integrative review

Objetivo: identificar o conhecimento científico acerca da violência produzido por enfermeiros em duas bases de dados. Métodos: pesquisa qualitativa, do tipo revisão integrativa da literatura. Foi realizada busca de artigos em português, inglês e espanhol, publicados nos últimos cinco anos, com descritores associados por operador booleano. Depois de aplicado os critérios de inclusão e exclusão, foram selecionados 35 artigos. Resultados: identificaram-se quatro categorias temáticas, referentes à violência contra crianças e/ou adolescentes, idosos, mulheres e profissionais, além da conduta desses nas situações de violência. Verificou-se que a cultura da violência está arraigada na sociedade como uma forma de resolução de conflito. Para romper com esse ciclo, os estudos evidenciaram, por exemplo, a importância da formação e capacitação profissional, uma vez que se observou carência na formação acadêmica e também a insegurança gerada pelo receio de retaliações, já que os profissionais também podem acabar se tornando vítimas da violência. Conclusão: considera-se que ainda existem poucas evidências acerca dessa temática, principalmente no que refere à conduta dos profissionais e as estratégias de prevenção e enfrentamento à violência. Logo, destaca-se a importância de fomentar a produção tanto acerca da violência quanto dos cuidados de enfermagem frente a essa situação.
Complement C3a activates astrocytes to promote medulloblastoma progression through TNF-α

Background Medulloblastoma (MB) is the most common malignant brain tumor in children. Approximately one-third of MB patients remain incurable. Understanding the molecular mechanism of MB tumorigenesis is, therefore, critical for developing specific and effective treatment strategies. Our previous work demonstrated that astrocytes constitute the tumor microenvironment (TME) of MB and play an indispensable role in MB progression. However, the underlying mechanisms by which astrocytes are regulated and activated to promote MB remain elusive. Methods By taking advantage of Math1-Cre/Ptch1 loxp/loxp mice, which spontaneously develop MB, primary MB cells and astrocytes were isolated and then subjected to administration and coculture in vitro. Immunohistochemistry was utilized to determine the presence of C3a in MB sections. MB cell proliferation was evaluated by immunofluorescent staining. GFAP and cytokine expression levels in C3a-stimulated astrocytes were assessed by immunofluorescent staining, western blotting, q-PCR and ELISA. C3a receptor and TNF-α receptor expression was determined by PCR and immunofluorescent staining. p38 MAPK pathway activation was detected by western blotting. Transplanted MB mice were treated with a C3a receptor antagonist or TNF-α receptor antagonist to investigate their role in MB progression in vivo. Results We found that complement C3a, a fragment released from intact complement C3 following complement activation, was enriched in both human and murine MB tumor tissue, and its receptor was highly expressed on tumor-associated astrocytes (TAAs). We demonstrated that C3a activated astrocytes and promoted MB cell proliferation via the p38 MAPK pathway. Moreover, we discovered that C3a upregulated the production of proinflammatory cytokines, such as IL-6 and TNF-α in astrocytes. Application of the conditioned medium of C3a-stimulated astrocytes promoted MB cell proliferation, which was abolished by preincubation with a TNF-α receptor antagonist, indicating a TNF-α-dependent event. Indeed, we further demonstrated that administration of a selective C3a receptor or TNF-α receptor antagonist to mice subcutaneously transplanted with MB suppressed tumor progression in vivo. Conclusions C3a was released during MB development. C3a triggered astrocyte activation and TNF-α production via the p38 pathway, which promoted MB cell proliferation. Our findings revealed the novel role of C3a-mediated TNF-α production by astrocytes in MB progression. These findings imply that targeting C3a and TNF-α may represent a potential novel therapeutic approach for human MB.
Detection of industrial storage tanks at the city-level from optical satellite remote sensing images

Industrial storage tanks are widely used in petroleum, chemical industry, metallurgy and other process industries. The use of storage tanks are important in ensuring industrial safety production and product storage. Recently, concerns are rising over leaks and spills which leads to potential environmental and public health risks, for example, air pollution. Thus, there is a need to detect and monitor the tanks, which has become a regulatory requirement in most countries. The monitoring of industrial storage tanks in a city is of great practical significance to the planning and construction of the city. With the recent development of remote sensing technology, computer vision and image processing, it is possible to automatically detect industrial storage tanks from optical remote sensing images. This paper mainly studies the automatic detection of urban industrial storage tanks using deep learning based algorithm, aiming to help people manage and monitor the urban environment and resources. In this paper, we collected optical satellite remote sensing images of the city as a unit and created a city-level dataset including three cities of Guangdong province in south China by utilising satellite image data obtained from Google Earth imagery. To explore the effect of the deep learning object detection algorithm for the industrial storage tanks detection at the city-level, a deep learning model built with SSD (Single-Shot Detector) was trained based on our collected dataset. To further improve the detection accuracy of industrial storage tanks, Hough transform was used to reduce the false alarm in the deep learning results. The experimental results show that the combination of deep learning target detection model and Hough transform is effective in detecting of industrial storage tank on the collected city-level dataset and can achieve promising detection results.
Degradation kinetics in different polymer–fullerene blends investigated by electron spin resonance

We investigate the photostability of a set of organic semiconductor blends comprising a conjugated polymer as the donor and a fullerene as the acceptor using electron spin resonance (ESR). In the absence of oxygen, all blends show excellent stability. Even after several hundred hours of exposure to solar or UV radiation, the ESR spectra and the recombination of photoinduced charges recorded at low temperature are found to be unchanged. By contrast, the presence of oxygen leads to a fast light-induced degradation rendering the ability of the donor/acceptor system to form photoinduced charge carriers. Our findings suggest that conjugated polymer–fullerene blends exhibit very good photostability and that oxygen needs to be excluded in optoelectronic applications. Our findings also suggest that at low temperature, a universal recombination process of long-lived photoinduced charges is active, which does not depend on the electronic structure or the morphology of the investigated materials.
Investigations on the thermal cracking and pyrolysis mechanism of China No.3 aviation kerosene under supercritical conditions

Abstract In this research, a global reaction model for the thermal cracking of China No.3 aviation kerosene was modeled based on experimental investigations under supercritical pressure. The result indicates that, when the conversion is lower than 50%, small molecules of products were generated nearly in a constant ratio and the selectivities of them were approximately identical. Therefore, a molecular kinetic model was developed using plug flow reactor model and an isothermal hypothesis. In order to estimate the kinetic parameters, a novel method of online density measuring was used to obtain the precise resident time. The reliability of this molecular kinetic model was validated through the comparison of experimental results with simulated values.
Assessment of the Efficiency of Aliquat 336+Rice Bran Oil for Separation of Acrylic Acid from Aqueous Solution Using Reactive Extraction

Abstract Biomass is an attractive target in process development for the emerging renewable resources based bio-refinery industry. Due to the ample range of application of acrylic acid, its production through bio-route received more awareness in scientific fraternity. In this view, an attempted was made to study the reactive extraction of acrylic acid with aliquat 336 in rice bran oil. Moreover, Box-Behnken matrix was employed to corroborate the effects of process variables viz. concentration of acrylic acid [CAA]aq, concentration of aliquat 336 [CR4N+Cl], and temperature on the extraction efficiency (η%). In physical extraction, average extraction efficiency was found in the order as: 43.55 > 35.36 > 29.14 at 303 K, 323 K, and 343 K respectively in rice bran oil. The correlation coefficient, R2 = 0.988 % indicates the appropriateness of proposed model to predict the extraction efficiency in terms of independent variables, and the predicted values were found in close agreement with that of experimental results. Further, R2(Pred) = 0.806 is in reasonable agreement with the R2(Adj) = 0.972. The optimum conditions for extraction of acrylic acid using aliquat 336 as an extractant in rice bran oil are [CAA]aq = 0.0. 5 (mol/kg); [CR4N+Cl] = 1.98 (mol/kg); temperature = 323 K and the model predicted extraction efficiency 77.5 % was found to be an excellent fit with the experimental value 75 %. Further, number of theoretical stages was found to be 3 and S/F ratio 0.247.
Censored count data regression with missing censoring information

: We investigate estimation in Poisson regression model when the count response is right-censored and the censoring indicators are missing at random. We propose several estimators based on the regression calibration, multiple imputation and augmented inverse probability weighting methods. Under appropriate regularity conditions, we prove the consistency of our estimators and we derive their asymptotic distributions. Simulation experiments are carried out to investigate the ﬁnite sample behaviour and relative performance of the proposed estimates. These estimates are illustrated on a real data set.
Application of Intramolecular FlAsH-BRET to the Classi�cation Arrestin Activation Modes

Intermolecular bioluminescence resonance energy transfer \(BRET) is a widely used method to detect protein-protein interactions in live cells. Intramolecular �uorescent arsenical hairpin \(FlAsH) BRET, wherein a Renilla luciferase \(Rluc) donor excites a �uorescent arsenical acceptor placed within the protein by mutational insertion of a tetracysteine tag motif, can be used to monitor stimulus-induced changes in protein conformation. Here, we describe a protocol using a series of Rluc-arrestin3-FlAsH-BRET biosensors to measure changes in arrestin conformation following G protein-coupled receptor \ (GPCR) activation as viewed from multiple vantage points within the protein. Changes in net BRET upon GPCR stimulation can be used to develop an arrestin3 “conformational signature” that is receptor-and ligand-specic. This method can be used to determine how differences in GPCR and ligand structure in�uence information transfer across the plasma membrane and to classify GPCRs and/or ligands based on their capacity to induce different arrestin3 activation modes.
Analysis and Identification of Polyphenolic Compounds in Green Foods Using a Combination of HPLC-ESI-IT-TOF-MS/MS

Abstract The beneficial effects of green foods on human health are well known. These benefits are mainly due to polyphenol content. The aim of this work was the development and utilization of an advanced mass spectrometry (MS) technique combined with high-performance liquid chromatography (HPLC) for the analysis and identification of polyphenolic compounds in green foods. HPLC-ESI-MS/MS analyses of selected extracts prepared from various types of green food (Urtica dioica L. and Allium ursinum L.) and their polyphenolic profiles were performed by an LCMS-IT-TOF analyzer equipped with electrospray ionization. HPLC separation was conducted by a Kinetex XB-C18 column (100µ2.1 mm; 2.6 µm) using gradient elution (water + 0.1% formic acid: acetonitrile + 0.1% formic acid) with a flow rate of 0.2 mL/min. The MS1-MS3 analyses were performed within a 50-1000 m/z range in both positive and negative ionization modes. The total analysis time was 20 minutes and injected volumes were 2 µL and 5 µL, respectively
High-performance piezoelectric-energy-harvester and self-powered mechanosensing using lead-free potassium–sodium niobate flexible piezoelectric composites

Lead-free piezoelectric materials have recently drawn extensive attention because of their high piezoelectric properties and for being harmless to the human body. We explored a high-output flexible lead-free piezoelectric nanogenerator (PENG) based on new inorganic piezoelectric 0.91K0. 48Na0.52NbO3–0.04Bi0. 5Na0.5ZrO3–0.05AgSbO3–0.2% Fe2O3 (KNN–BNZ–AS–Fe) particles for the first time and which had an ultrahigh piezoelectric coefficient (d33) of ∼500 pC N−1. The PENG was fabricated from KNN–BNZ–AS–Fe particles and a PDMS matrix, and exhibited a linear relation between the output voltage and input pressure within a certain pressure range. An optimal output with a large recordable open-circuit voltage (VOC) of 52 V and a short-circuit (ISC) current of 4.8 μA was obtained under a vertical force of 25 N at 2 Hz. The PENG was demonstrated to be able to successfully drive commercial light emitting diodes (LEDs) without any storage unit, which suggests that the biocompatible KNN–BNZ–AS–Fe-based PENG has realistic application prospects as a power source. Furthermore, the PENG could also potentially be utilized as a mechanical sensing counter and in collision alarm equipment. This work provides a new direction for lead-free piezoelectric materials in the field of self-powered mechanosensation for potential applications in areas such as artificial intelligence, soft robotics, and biomedical devices.
A Less-Disturbed Ecological Driving Strategy for Connected and Automated Vehicles

This paper proposes a less-disturbed ecological driving strategy for connected and automated vehicles (CAVs). The proposed strategy integrates the offline planning and the online tracking. In offline planning, an energy efficient reference speed is created based on traffic information (such as the average traffic speed) and characteristics of the vehicle (such as the engine efficiency map) via dynamic programming. The consideration of average traffic speed in speed planning avoids selfish optimisations. In online tracking, model predictive control is employed to update the vehicle speed in real-time to track the reference speed. A key challenge in applying ecological driving strategies in real driving is that the vehicle has to consider other traffic participants when tracking the reference speed. Therefore, this paper combines both longitudinal control and lateral control to achieve better speed tracking by overtaking the preceding vehicle when necessary. The proposed less-disturbed ecological driving strategy has been evaluated in simulations in both single road segment scenario and real traffic environment. Comparisons of the proposed method with benchmark strategies and human drivers are made. The results demonstrate that the proposed less-disturbed ecological driving strategy is more effective in energy saving. Compared to human drivers, the less-disturbed eco-driving strategy improves the fuel efficiency of CAVs by 4.53%.
Chemical compositions, extraction technology, and antioxidant activity of petroleum ether extract from Abutilon theophrasti Medic. leaves

ABSTRACT Petroleum ether extract from Abutilon theophrasti Medic. leaves was optimized by response surface methodology, and the optimal extraction conditions were as follows: ratio of solvent to material (20.12 mL/g), extraction time (5.45 h), and Soxhlet extraction temperature (61.32°C). And the yield of petroleum ether extract collected in August, September, and October was (2.05 ± 0.02)%, (2.39 ± 0.01)%, and (2.32 ± 0.02)%, respectively. The September and October extracts exhibited a better antioxidant activity, which was proved by DPPH·scavenging ability (IC50 value of 327.5 and 331.5 μg/mL), ABTS·+ scavenging ability (IC50 value of 170.1 and 182.1 μg/mL), and reducing power (0.31 and 0.28 mmol Fe2+/100 μg/mL). Meanwhile, the gas chromatograph-mass spectrometry analysis revealed that the main antioxidant components contained 9, 12, 15-octadecatrienoic acid and 9, 12, 15-octadecatrienoic acid, ethyl ester (Z,Z,Z) in three petroleum ether extracts. Therefore, petroleum ether extract from Abutilon theophrasti Medic. leaves can be a potential resource of natural antioxidants in pharmaceutical, medicine, food, and chemical industries.
Types of Solidarity in a Hybrid Regime: The Hungarian Case

Abstract Our aim in this article is to show the stance on solidarity present in a hybrid regime. Taking Hungary as an example, we give individual-level explanations for attitudes towards solidarity and inclusion/exclusion in times when populist parties are in power. By creating typical solidarity groups, we explain who belongs to different solidarity clusters and why, what political orientations can be linked to solidarity groups and whether people's attitudes reflect the values/solidarity conceptions propagated by the Orbán government. With this, we point to the social and political polarization of Hungarian society. We found that the appreciated, satisfied and politically trustful far-right exclusive groups – independent of their social status – make up not only the majority of society but also the crucial system-justifying basis of the Orbán regime. However, in an ethnically rather homogeneous society foreigners could be seen as cultural and economic threats to the decisive majority, including a significant part of the inclusive groups.
Proximate and Functional Properties of Bambara Groundnut, African Arrowroot Lily and Soybean Flour Blends

This study determined the proximate and functional properties of bambara groundnut, African arrowroot lily and soybean flour blends. The flour blends were prepared in the ratios 90:5:5, 80:10:10, 70:15:15, 60:20:20, 50:25:25, 40:30:30 of Bambara groundnut, African arrowroot lily and Soybean respectively. They were blended in a 2L blender operated for 10mins at speed 3. The flour blends were stored in airtight containers until required. Proximate composition of the flour blends showed significant differences with increase in protein (22.09% to 30.58%), fat (8.16% to 12.94%), moisture (7.04% to 7.65%) and ash (1.83% to 2.56%) content while carbohydrate decreases (58.92% to 45.20%). The functional properties include bulk density (0.71g/ml to 0.96g/ml), water absorption capacity (21.36% to 53.66%), oil absorption capacity (48.63% to 79.85%), swelling power (32.56% to 33.52%), foaming capacity (21.66% to 45.27%) and emulsion capacity (42.65% to 74.26%). There was an improvement in the proximate and functional properties of Bambara groundnut, African arrowroot lily and Soybean flour blends; therefore, the flours could be adopted in complementary feeding to alleviate malnutrition. Keywords: Proximate, Functional, Flour blends, African arrowroot Lily, Bambara groundnut, soybean
Optimization of non-linear conductance modulation based on metal oxide memristors

Abstract As memristor-simulating synaptic devices have become available in recent years, the optimization on non-linearity degree (NL, related to adjacent conductance values) is unignorable in the promotion of the learning accuracy of systems. Importantly, based on the theoretical support of the Mott theory and the three partial differential equations, and the model of conductive filaments (CFs), we analyzed and summarized the optimization schemes on the physical structure and the extra stimulus signal from the internal factor and external influence, two aspects, respectively. It is worth noting that we divided the extra stimulus signals into two categories, the combined pulse signal and the feedback pulse signal. The former has an internal logical optimized phenomenon, and the composition of only two parts in each cycle leads to a simple peripheral circuit. The latter can obtain an almost linear NL curve in software stimulation because of its feature in real-time adjustment of signals, but it is complex in hardware implementation. In consideration of space and energy consumption, achieving memristor with different resistive switching (RS) layers can be another optimization scheme. Special attention should be paid to the weaker NL, which could improve learning accuracy at the system level only when the value of other non-ideal properties such as the on/off ratio is within a certain range.
Apple Variety Identification Using Near-Infrared Spectroscopy

Near-infrared (NIR) spectra of apple samples were submitted in this paper to principal component analysis (PCA) and successive projections algorithm (SPA) to conduct variable selection. Three pattern recognition methods, backpropagation neural network (BPNN), support vector machine (SVM), and extreme learning machine (ELM), were applied to establish models for distinguishing apples of different varieties and geographical origins. Experimental results show that ELM models performed better on identifying apple variety and geographical origin than others. Especially, the SPA-ELM model could reach 98.33% identification accuracy on the calibration set and 96.67% on the prediction set. This study suggests that it is feasible to identify apple variety and cultivation region by using NIR spectroscopy.