Miracle-dz/UniFAR-FTUs huggingface dataset:
IMPACT OF PORTLAND CEMENT ON GROWTH OF BEAN CROPS

Cement manufacturing industries are responsible for environmental degradation at regional and global level. This study was undertaken the effect of port land cement on three different legume crops in pot. The cement treatment differently influenced on germination and biomass of all studied bean crops. Statistically, the root length of Vigna radiata was decreased at 0.50 g cement level. The cement treatment at similar level significantly reduced shoot and seedling length of V. mungo. The total seedling dry weight of V. unguiculata was significantly affected with cement treatment at 1.0 g. The sprinkled treatment at 2 g reduced tolerance index in seedlings of V. unguiculata, V. mungo and V. radiata, respectively.
Depth of Anaesthesia Assessment Based on Spectral Entropy

Anaesthesia is a state of temporary controlled loss of awareness induced for medical purposes. An accurate assessment of the depth of anaesthesia (DoA) has always been required. However, the current DoA algorithms have limitations such as inaccuracy or inflexibility. In this study, for more reliable DoA assessment, pre-denoised electroencephalograph (EEG) signals are divided into ten frequency bands (α, β1, β2, β3, β4, β, βγ, γ, δ and θ), and the basic complexity measure is done by using spectral entropy (SE). SE from beta-gamma frequency band (21.5 - 38.5 Hz) and SE from beta frequency band show the highest R squared value (0.8458 and 0.7312, respectively) with currently the most popular DoA index, bispectral index (BIS). A new DoA index is developed based on these two SE values for monitoring the DoA and evaluated by comparing with the BIS index. The highest Pearson correlation coefficient is 0.918, and the average is 0.80. In addition, the proposed index shows an earlier reaction than BIS index when the patient from deep anaesthesia to moderate anaesthesia, and the consistency in the case of poor signal quality (SQ) while the BIS Index exhibits inflexibility with cases of poor SQ.
Liquid Metal Printing

Um den Forderungen der Märkte nach individuell angepassten und endkonturnahen Bauteilen gerecht zu werden, hat ein Werkzeugmaschinenspezialist mit „Liquid Metal Printing“ (LMP) ein zukunftsweisendes, wirtschaftliches und flexibles Fertigungsverfahren im Bereich der Additiven Fertigung entwickelt.
Mesostructured Pt/TiO2 Nanocomposites as Highly Active Photocatalysts for the Photooxidation of Dichloroacetic Acid

Mesoporous Pt/TiO2 nanocomposites have been synthesized by using two pathways: (1) the in-situ preparation of Pt/TiO2 nanocomposites was carried out using a one-step synthesis by dissolving the Pt and TiO2 precursors in the presence of a triblock copolymer as the structure-directing agent followed by drying, calcinations, and reduction under H2 gas. (2) Platinum particles have been photochemically deposited onto mesoporous TiO2. The TEM images of the mesoporous Pt/TiO2 nanocomposites calcined at 450 °C demonstrate that the TiO2 nanoparticles with an average diameter of about 10 nm are not agglomerated and are quite uniform in size and shape. Following the photodeposition process, the Pt nanoparticles are well-dispersed and highly uniform, exhibiting diameters of ∼3 nm; however, following the in situ preparation, the Pt particles are reaching diameters of approximately 15 nm, most likely as a result of the calcination and reduction at high temperatures. The photocatalytic activity of the newly synthesized .
Un enfoque de Análisis Inteligente de Datos para Apoyar la Relación con los Clientes

: Intelligent data analysis is an important component of the fourth industrial revolution. In particular, data generated by customers can be used to improve products and services. However, customer analysis has focused more on the use of structured data. Most companies are still not taking advantage of the full potential of unstructured data sources. This paper proposes an approach to extract customer service performance indicators integrating business intelligence and natural language processing (NLP) techniques to take advantage of unstructured data. To validate the proposal, a study case was carried out in a company that offers health services. Indicators were obtained from the analysis of phone calls and emails written in Spanish. The results obtained show the utility of the approach to support customer relationships.
Prognostic models for predicting overall survival and cancer-specific mortality in hepatocellular carcinoma: A competing risk analysis

Background: Mortality due to hepatocellular carcinoma (HCC), which is the most common liver cancer, is often overestimated because of deaths from other causes. This study was conducted to estimate the probability of cancer-specific mortality (CSM) of patients with HCC and establish a competing risk nomogram for predicting the CSM of among these patients HCC using a large population-based cohort. Methods: Patients diagnosed with HCC between 2004 and 2015 were identified from the Surveillance Epidemiology and End Results Program. CSM and overall survival (OS) were the endpoints of the study. A competing risk nomogram for predicting CSM was built using the Fine and Gray regression model, and the nomogram for predicting OS was constructed with the Cox proportional hazard regression model, and 10-fold cross-validation was performed for the entire set. Results: A total of 34,957 patients were included in the study and randomly divided into a training set and validation set at a ratio of 7:3. Multivariate analysis identified age, race, surgical therapy, chemotherapy, radiotherapy, tumour diameter, and tumour staging as the independent predictive factors of CSM. In addition to these factors, sex and marital status were also identified as independent predictive factors of OS. Using these factors, corresponding nomograms were constructed for CSM and OS. In the validation set, the 5 year concordance-indices of the two nomogram models were estimated as 0.746 and 0.74. Calibration curves revealed good consistency between model predictions and observed outcomes. Furthermore, based on the results of cumulative incidence function analysis and Kaplan-Meier analysis, patients were categorised into four distinct risk subgroups, supporting the predictive performance of the models. Conclusions: In this population-based analysis, we developed and validated nomograms for individualized prediction of CSM and OS in patients with HCC.
The impact of combined nutraceutical supplementation on work-related stress, mood and eating disorders during the menopausal transition: A pilot study

Objectives: Menopause represents a “window of vulnerability” in women’s life. This transition comprehends many changes: physical, metabolical and psychological. It could, also, cause difficulties at work and the most problematic symptoms are poor concentration and memory, tiredness, feeling depressed and lowered confidence. Moreover food becomes, often, a practical, easy and fast solution to manage negative emotions. The aims of this pilot study were: to analyze the existence of a possible link between menopausal transition, mood, eating behavior and well-being perception on the workplace and to verify the possible influence of nutraceutical supplementation on the above mentioned factors. Method: 40 women, with mean age 52 years old and mean BMI 33.27 were enrolled and divided into two groups: diet + behavioral advices (D), or diet + behavioral advices and a nutraceutical compound (D+N) (Assist Forte Retard® 1 cp in the evening) for four months. The following psychological questionnaires were administrated at the beginning and after four months: Zung depression scale, (ZDS); Binge Eating Scale (BES); Job Content Questionnaire ( JCQ) used to measure the investigate job related stress. After the test, each woman had an individual psychological interview aimed to investigate her personal experiences, related to what come out from the results. Results: After four months: women (D+N) achieved a statistically significant improvement in both tests (ZDS p <0.0001 Bes p <0.0083). The women (D) had no statistically significant changes in BES, even if there was better management of feeding behavior, and ZDS did not show an improvement in mood. JCQ analysis showed: women (D+N) had a moderate increase of decision-making capacity (DL 64 to 66) compared with an unchanged workload ( JD 33 to 33.5); social-support perception (SS ) showed a slight improvement even if it remained below the median line of the reference sample. In the (D) group we observed a slight increase of the workload , accompanied by a reduction of the decision-making capacity (DL 74 to 69) and by a tiny lowering of the perception of the social support (SS). Conclusions: the combination of a diet program, behavioural advice and nutraceuticals, compared to the sole diet, made it possible to relieve the emotional and eating disturbs related to the menopause and to improve the perception of a satisfactory work.
Quantum-inspired satin bowerbird algorithm with Bloch spherical search for constrained structural optimization

To enhance the optimization ability of the satin bowerbird optimization (SBO) algorithm, in this paper, a novel quantum-inspired SBO with Bloch spherical search is proposed. In this algorithm, satin bowerbirds are encoded using qubits described on the Bloch sphere, each satin bowerbird occupies three locations in the search space and each location represents an optimization solution. Using the search method of general SBO to adjust the two parameters of the qubit, qubit rotation is performed on the Bloch sphere, which simultaneously updates the three locations occupied by a qubit and quickly approaches the global optimal solution. Finally, the experimental results of five examples of structural engineering design show that the proposed algorithm is superior to other state-of-the-art metaheuristic algorithms in terms of the performance measures.
Effect of Alkali and Alkaline Earth Metals on in-Situ Catalytic Fast Pyrolysis of Lignocellulosic Biomass: A Microreactor Study

In-situ catalytic fast pyrolysis (CFP) is considered to be a promising pathway to produce aromatic hydrocarbons from lignocellulosic biomass. However, the presence of variable amounts of inorganic ash in biomass in the form of alkali and alkaline earth metals (AAEMs) is a concern while using in situ catalysts because AAEMs could influence product distribution from CFP while also being a major reason for catalyst deactivation. In this study, the effect of four alkali and alkaline earth metals (K, Na, Mg, and Ca) commonly found in biomass was investigated to understand their individual influence on the fate of primary pyrolysis products as well as their effect on the selectivity of products from in situ CFP using ZSM-5 catalyst. Experiments were performed in a microreactor (Py-GC/MS) with ZSM-5 catalyst using AAEM-impregnated biomass. It was found that the type of AAEM as well as the concentration were significant, with Mg appearing to be relatively inert when compared to the stronger catalytic activity of .
Robust Cultivated Land Extraction Using Encoder-Decoder

: Cultivated land extraction is essential for sustainable development and agriculture. In this paper, the network we propose is based on the encoder-decoder structure, which extracts the semantic segmentation neural network of cultivated land from satellite images and uses it for agricultural automation solutions. The encoder consists of two part: the first is the modified Xception, it can used as the feature extraction network, and the second is the atrous convolution, it can used to expand the receptive field and the context information to extract richer feature information. The decoder part uses the conventional upsampling operation to restore the original resolution. In addition, we use the combination of BCE and Loves-hinge as a loss function to optimize the Intersection over Union (IoU). Experimental results show that the proposed network structure can solve the problem of cultivated land extraction in Yinchuan City.
Cognitive, language and behavioral outcomes in children in middle childhood with autism spectrum disorders exposed to early comprehensive treatment models: A meta-analysis and meta-regression

Background Early comprehensive treatment models (CTMs) have developed as effective treatments for children with autism spectrum disorder (ASD). Numerous studies have suggested that they can improve short-term outcomes, but little is known about middle childhood outcomes. The current meta-analysis reviewed studies reporting broader outcomes in middle childhood in children with ASD who ever participated in a CTM and examined the predictors of primary outcomes. Methods We searched eight databases up to June 13, 2019, for relevant trials and natural experiments. Longitudinal studies were selected if they investigated the outcomes of CTMs in middle childhood in children with ASD. Two meta-analyses were undertaken to determine a summary estimate of change in treatment outcomes and evaluate the effect of CTMs; one used the standardized mean change between the pretest and posttest, and the other a classical meta-analysis. Stratified and random effects meta-regression analyses were performed to search for outcome differences among studies. Results Eighteen intervention studies (involving 495 children with ASD) met all the inclusion criteria: 12 used early intensive behavioral intervention (EIBI) and two the Early Start Denver Model (ESDM). Outcomes were categorized into three parts: cognitive, language and behavioral (e.g., adaptive functioning and symptomatology). Overall, most children with ASD in middle childhood who participated in an early CTM make gains in many areas of functioning, especially with regard to symptom and language-related outcomes. Stratified analyses indicated that the ESDM displayed the largest effect on IQ improvement (ES=1.37, 95% CI: 0.95-1.80), while EIBI was more effective for symptom reduction (ES=-1.27, 95% CI: -1.96 to -0.58). Further meta-regression suggested that interventions with parent involvement and longer treatment hours yielded greater improvements in IQ and social adaptive functioning, respectively. Conclusion The results demonstrate a positive association between CTMs and better prognosis in middle childhood, especially regarding symptoms and language. However, most of the extant research involves small, non-randomized studies, preventing definitive conclusions from being drawn. What is certain is that the outcomes in middle childhood of children with ASD are still far from normal, especially for adaptive functioning, and the three mediating variables were treatment elements: approach, implementer and total treatment hours.
Modelling and computation of optimal multiple investment timing in multi-stage capacity expansion infrastructure projects

So far, the optimal investment timing to maximize the total profit of multi-stage capacity expansion infrastructure projects is not clear. In the case of uncertain demands, the optimal multiple stopping time theory is adopted to model the optimal decision-making of investment timing for multi-stage expansion infrastructure projects in a finite time horizon. In this context, the first-stage of the project involves a dedicated asset investment for later expansion, and the capacity of the project at each stage is constrained, which makes the cash flow of the project exhibit the characteristic of bull call spread. The upwind finite difference method and multi-least squares Monte Carlo simulation are combined to solve the project value and determine the optimal exercise boundaries at all stages described by a sequence of demand thresholds. A multi-stage power plant project is taken as an example to validate the model. Through the example, the optimal investment strategies and the value of the multi-stage project are provided; the effects of the dedicated asset and capacity constraint are illustrated. This study novelly reveals the effect of the capacity constraints on the project value using the bull call spread theory.
University Students’ intention to quit substace abuse in Ethiopian: Application of Theory of Planned Behavior

Background Currently, substance abuse is one of the most burning public health problems in Ethiopia. However, the magnitude of substance abuse and intention to quit is not yet properly studied, Therefore, this study aims to assess University students’ intention to quit substace abuse in Ethiopian:Application of Theory of Planned Behavior (TPB) Methods Institution based cross-sectional study was conducted using self-administered questioners. A stratified sampling technique was used to select the study participants. Descriptive statistics were computed and a multivariate logistic regression model was fitted. A p-value of less than 0.05 was used to declare statistical significance. Result From a total of 392 respondents, 175 (44.6%) were fulfilled the criteria of psychoactive substance abuse (CAGE ≥ 2). Socio-demographic variables such as male respondents (Adjusted Odds Ratio (AOR) =2.34, 95% confidence interval, CI [1.22, 4.51]; P=0.000), Respondents among age category of 25-29 years (Adjusted Odds Ratio(AOR)=21.93, 95% confidence interval CI[16.19; 33.11]; P=0.000) and students with five and above years of study (Adjusted Odds Ratio (AOR)=5.71, 95% confidence interval, CI[2.41-13.52]; P=0.000) had significant association with the psychoactive substance abuse. Theory of Planned Behavior constructs such as positive attitude (Adjusted Odds Ratio[AOR]=1.81,95% confidence interval, CI[1.11,2.96]; P =0.018),supportive Subjective Norm (Adjusted Odds Ratio[AOR]=2.05, 95% confidence interval, CI[1.26,3.47]; P =0.004) and positive Perceived Behavioral Control (Adjusted Odds Ratio [AOR]=6.16, 95% confidence interval, CI[3.75,10.14]; P =0.000) had significant association with quitting psychoactive substance abuse. Conclusion This study illustrated that intention to quit psychoactive substance abuse was predicted by a positive attitude, supportive subjective norm, and positive perceived behavioral control. Therefore, applying health communication strategies focusing on attitude, subjective norm and perceived behavioral control by segmenting students based on sex, age and years of studies are important to bring desired behavioral changes.
Magneto-Inductive HF RFID System

Efforts to increase read range in passive HF RFID systems are hampered by the poor range scaling law of inductive coupling. An alternative approach to enlarging capture volume—increasing the lateral extent of the antenna—is proposed, using a magneto-inductive (MI) travelling wave arrangement to allow larger antenna sizes. A theory of load modulation in MI systems is first presented, together with field simulations in the capture volume. A 2.3 metre-long MI antenna is then constructed, and an active tag emulator is used to demonstrate load modulation. RFID is then demonstrated, with the antenna in both reflection and transmission modes, using a custom reader constructed from laboratory equipment. A transverse read range of 0.5 m is obtained using commercial off-the-shelf RFID cards with 10 W RF power, with high uniformity along the length of the antenna.
Comprehensive miRNA expression analysis for histological subtypes of soft tissue sarcoma

Sarcoma is a rare mesenchymal malignancy that comprises more than 50 histological subtypes. Because of the rarity and diversity of sarcomas, their differential diagnosis is difficult, and there is still a need for biomarkers to support pathological diagnoses. Micro RNAs (miRNAs) are small noncoding RNAs that regulate the behavior of tumors, such as invasion and metastasis. The expression patterns of miRNAs reflect the origin of malignancy and are considered to be candidate biomarkers. To understand the molecular background of those histological subtypes, we investigated the miRNA expression in 89 tumor tissues of eight subtypes. The correlation coefficients between each sarcoma subtype on the basis of miRNA expression values were mostly higher than 0.7, reflecting the common mesenchymal origin. By contrast, hierarchical clustering and principal component analysis showed that three types of sarcoma with chromosomal translocation (i.e., dermatofibrosarcoma protuberans, myxoid liposarcoma, and synovial sarcoma) were grouped according to their histological subtypes, whereas five types with complex karyotypes (i.e., myxofibrosarcoma, malignant peripheral nerve sheath tumor, undifferentiated pleomorphic sarcoma, dedifferentiated liposarcoma, and pleomorphic liposarcoma) were not. Notably, the number of miRNAs whose expression pattern was unique to histological subtypes with statistical significance was higher in sarcomas with chromosome translocation than in those with complex karyotypes. Hence, it can be concluded that the miRNAs unique to histological subtypes are candidate biomarkers for the differential diagnosis of sarcomas, particularly in those with chromosomal translocation.
CHANGES OF ELECTROPHORETICAL FRACTIONS IN SIMULTANEOUS EXPOSURE TO GAMMA RADIATION AND HYPERBARISM

Hyperbaric exposure gives rise to an increase of oxygen free radicals concentration in living organisms. Meanwhile the exposure of the organism to gamma radiations, accidentally or during radiological treatment provides the same effects. Nowadays studies describe treatment methods, where treatment with radiation is followed by hyperbar ic therapy with an increase concentration of oxygen. Our study presents the cummulative effects of hyperbaric exposure and therapeutical gamma irradiation. The results we got from both exposures evidence that the cumulative exposure to those two factors gives rise to a significant change in electrophoretical fractions: significant damage of alpha and beta proteins.
Application of support vector machine in a traffic lights control

This article presents the process of adapting support vector machine model’s parameters used for studying the effect of traffic light cycle length parameter’s value on traffic quality. The survey is carried out using data collected during running simulations in author’s traffic simulator. The article shows results of searching for optimum traffic light cycle length parameter’s value.
Selecting a Suitable Image Enhancement Tool for Near-Infrared Urban Scenes

Computer vision application such as scene segmentation and object detection all require sharp distinction between various regions in an image. Image segmentation through clustering is one such approach that can effectively enhance contrast, sharpness and retain colour of urban scene. However, most of the literary works use FCM based image segmentation for enhancing medical images. In the current article, a study is being carried out by implementing two FCM based algorithms i.e. FAAGKFCM and GIFMRCM algorithms on five near infrared (NIR) image samples. NIR spectrum has a higher tendency to reflect textures of naturally occurring objects such as trees, water, cloud, road, etc. in comparison to its visible spectrum counterpart. A limitation of it is that they are grayscale in nature and usually has faint intensity which makes instant differentiation and recognition difficult. To remedy these situations, an empirical analysis is made to determine which among the two image segmentation algorithms mentioned above is best suitable for enhancing urban NIR scene.