Miracle-dz/UniFAR-FTUs huggingface dataset:
A comparative Analysis on De-Noising ECG Signals using Discrete and Stationary Wavelet Transforms

---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Electrocardiographic (ECG) signal is used in heart rate monitoring (HRM) devices to analyze the heart rate of a person. High processing speed along with accurate results is a requirement for this purpose. But due to various noises such as baseline noise, white Gaussian noise and muscular movement, it is necessary to remove the noises to accurately measure the heart rate. This paper compares algorithms which use Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT) to detect the heart rate to de-noise ECG. The MIT-BIH Arrhythmia Database is used for reference in this work. Simulation results and its analysis using Signal to Noise Ratio (SNR) and Root Mean Square Error (RMSE) show that the SWT method is better than the DWT method.
Into the great wide open: do alien plants spread from rivers to dry savanna in the Kruger National Park?

Protected areas play an important role as refuges from invasive species impacts on biodiversity. Within the MOSAIK (Monitoring Savanna Biodiversity in the Kruger National Park) project, plant species were recorded in a representative set of 60 plots, 50 × 50 m in size, across the entire KNP, distributed so as to cover a range of savanna habitats, i.e. perennial rivers, seasonal rivers and dry crests, and two main bedrock types (granite and basalt). The data were used to assess the role of rivers in the dispersal of alien plants and study whether the alien plant species spread from rivers to open dry savanna. The resulting dataset provided the first thorough information on the spatial distribution of naturalised alien plants in KNP. In total, we recorded 20 plant species that are alien to the park, four of them considered invasive: Parthenium hysterophorus, Opuntia stricta, Xanthium strumarium and Zinnia peruviana. The most widespread species in KNP was Tridax procumbens, recorded in 11 plots (i.e. 18% of all sampled), four other species were found in > 10% of the plots. One species, Bidens bipinnata, was not previously reported from the park and represents a new record. The majority of aliens were concentrated along perennial rivers (60% of all occurrences), but some were repeatedly recorded at seasonal rivers as well and two of the most invasive species in KNP, Opuntia stricta and Parthenium hysterophorus, occurred also on dry crests away from water. The average number of alien species per plot was low (1.6), as was their mean percentage contribution to all species in a plot (2.2%), but some plots harboured as many as seven species and contributed up to 11.9%. Moreover, only 21 plots (35%) were alien-species free. In terms of the total species number per habitat, perennial rivers had significantly more aliens than crests and were marginally significantly richer than seasonal rivers. By recording all naturalised alien species occurring in the plots – many of them are not invasive but may become so in the future – and by using the GloNAF database of global distribution of naturalised species, we assessed the invasion potential of the recorded species.
Ship Target Detection Based on Improved YOLO Network

Ship target detection is an important guarantee for the safe passage of ships on the river. However, the ship image in the river is difficult to recognize due to the factors such as clouds, buildings on the bank, and small volume. In order to improve the accuracy of ship target detection and the robustness of the system, we improve YOLOv3 network and present a new method, called Ship-YOLOv3. Firstly, we preprocess the inputting image through guided filtering and gray enhancement. Secondly, we use k-means++ clustering on the dimensions of bounding boxes to get good priors for our model. Then, we change the YOLOv3 network structure by reducing part of convolution operation and adding the jump join mechanism to decrease feature redundancy. Finally, we load the weight of PASCAL VOC dataset into the model and train it on the ship dataset. The experiment shows that the proposed method can accelerate the convergence speed of the network, compared with the existing YOLO algorithm. On the premise of ensuring real-time performance, the precision of ship identification is improved by 12.5%, and the recall rate is increased by 11.5%.
The Effects of Organisational Climate, Psychological Contract Breach and Communication on Individual Research Productivity

This study examined the effects of organisational climate, psychological contract breach, and effective communication on individual research productivity at the National University of Lesotho. It also investigated the relative importance of personal factors and perceptions of contextual factors on research productivity. Data were collected through self-administered questionnaires distributed to 160 faculty members. Hierarchical regression analysis, partial least squares structural equation modelling, usefulness analysis and relative weight analysis were used to analyse the data. The results show that organisational climate was positively related to effective communication and negatively related to psychological contract breach. Effective communication mediated the relationship between organisational climate and research productivity. Contrary to expectations, organisational climate and psychological contract breach were negatively and positively related to research productivity, respectively. Furthermore, personal factors demonstrated incrementally higher variance than contextual factors in explaining research productivity. These findings imply that university administrators can improve research productivity through effective communication. For instance, university management should communicate the goals of research to all employees.
Food Consumption Patterns and Predictors of Dietary Diversity in Pastoral Communities of Ngorongoro District, Tanzania

The aim of this study was to assess the patterns of household food consumption and examine the factors influencing dietary diversity. Data were collected from 238 randomly selected households. Food consumption was assessed in terms of Dietary Diversity Score (DDS) with a range of 0-12. The minimum and maximum DDS were one and eight, respectively. Groups of food consumed were classified into four Quantiles (Q) and households were categorized based on quartile cut-points: Q1 (1-3 DDS), Q2 (4), Q3 (5-6) and Q4 (7-8). Chi square test was used to assess the association between the food groups and quartile level. Ordered probit regression was employed to examine determinants for household dietary diversity. Results show that more than four in ten households (43.3%) consumed less than the minimum recommended four groups of food. Proportions of households consistently decreased with increasing quartile level (43.3% in Q1 to 6.7% in Q4). Only 18% of the households were in the upper quartiles (Q3 and Q4). The DDS means by quartiles were 2.47 (Q1), 4.00 (Q2), 5.00 (Q3) and 5.89 (Q4) with the overall mean DDS of 3.52. While cereal (96.2% of the households) was the most consumed food group, there was limited consumption of vegetables (12.6%), fruits (4.2%) and fish (2.9%). Food accessibility and livelihood diversification were the major determinants of dietary diversity. Demographic and socio-economic factors mediated household’s dietary diversity at varying degree of influence.
A Model for Mammogram Image Segmentation based on Hybrid Enhancement

MIAS dataset are taken which are enhanced to create enhanced images dataset. The enhanced images data set will act as a source of input images for the segmentation block. The . ABSTRACT Introduction: Detection of breast cancer at early stages is very important and it helps in saving the life of the patient. The mammography is one of the techniques which is used worldwide by radiologists to detect breast cancer. It is very important to detect breast cancer correctly as human life is associated with correct detection. So, nowadays computer-aided diagnose (CAD) systems are used to detect breast cancer from a mammography image. In this work, a transfer learning-based method is used to train the system for the detection of breast cancer. The proposed model is based on a hybrid technique of image enhancement and segmentation for the pre-processing. The pre-processing is done to improve the peak signal to noise ratio (PSNR) value of originally acquired images. The Mammography Image Analysis Society (MIAS) dataset is used in this work along with other clinical images which result in the creation of around 928 images in the dataset. Aim: This work aims to segment the affected area image from the original image. Then enhanced the segmented image by using PSNR so that better result is helpful to identify the affected area. The correct detection is associated with a life decision. Result: Mammogram image has been segmented from the affected area. Various type of noises may be induced in the black and white image. The image represents the original, enhanced and segmented image. The PSNR value for an image varies from 33 to 36. The segmented image is representing the affected regions to limit the image and to eliminate useless details. Conclusion: This paper put forward the methodology which will segment the affected area from the image. The image has been enhanced based on LCM and CLAHE. Morphology technique has been used along with the Otsu threshold for accurate segmentation. The proposed network is promising as it is trained for mammogram dataset for higher accuracy.
Comparison of different approaches to reduce the number of parameters in Deep Neural Networks

Deep neural networks contain a large number of parameters. For this reason the training and testing of these networks have a high computational cost. [8] Moreover these deep networks also require a lot of memory. [2] As a result compression and efficiency have become more important in recent research. [1] Therefore many pruning methods have been proposed to obtain compact models with negligible accuracy loss. In this thesis three different pruning approaches are analyzed. First singular value decomposition is presented. Then a pruning technique called neuron importance score propagation is introduced. And finally ε-ResNet is analyzed. To examine whether the techniques achieve reduction while retaining the predictive power experiments on image classification are performed. All three pruning techniques successfully reduced the examined networks with only a small decrease in accuracy. However combining two methods leads to even more reduction. The best pruning result is achieved by applying neuron importance score propagation after the network was already pruned using ε-ResNet. In the performed experiments up to 98.56% of the parameters can be reduced while obtaining almost the initial accuracy. Therefore pruning methods are very effective and can achieve significant compression. Model compression not only accelerates testing time, but also reduces the required memory which allows the networks to run on hardware limited devices such as smart phones, robots or cars. [1]
Aqueous and Microwave Assisted Extraction of Pectin from Grapefruit and Nagpur Mandarin

Pectins are methylated ester of polygalacturonic acid that contain 1,4-linked α-D-galacturonic acid residues. It is a part of soluble dietary fibre and widely used in the food industry as a thickener, emulsifier, texturizer and stabilizer (Levigne et al., 2002). Fresh weight of plant material contains 0.5-4.0% of pectin substances (Faravash and Ashtiani, 2008). These are the biopolymers found in the primary cell walls of most plant cells but most concentrated in citrus fruits (oranges, lemons, grapefruits) and apples. Worldwide currently commercial pectin is extracted from citrus peel and apple pomace, International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 7 (2020) Journal homepage: http://www.ijcmas. com
An Approach of Securing Data using Combined Cryptography and Steganography

The recent advance in information technology field forcing us to ensure the privacy of the digital data. It is very important to develop the method that may satisfy the needs. Many methods/techniques applied to reach that goal. One of efficient way to reach that secrecy can be achieved by combining Cryptography and Steganography. In this paper, a new RGB shuffling method proposed. The concept of encryption using RGB Shuffling is shuffling all of RGB element to distort the image. RGB Shuffling method will shuffle the RGB each pixel of image depends on the input password from user. The basic step of RGB shuffling is adding RGB element with ASCII password, invers and shuffle it
Studying the Relationship of Mental Health and Other Factors with Preference of Delivery Method in Women Referred to Qamar Bani Hashem Hospital, Khoy, Iran

Background: Childbirth is a fundamental physical and emotional struggle. This study is an attempt to investigate the psychological factors related to the first delivery, and its relationship with the preference of the type of subsequent deliveries in women. Materials and Methods: This is a descriptive-analytical study in which 380 pregnant mothers referred to Qamar Bani Hashem Hospital in Khoy, Iran, who were hospitalized for childbirth, were selected by simple random sampling. Participants were first asked about their preference for the next type of delivery. Afterwards, the Individual and Social Profile Questionnaire, the Edinburgh Depression Questionnaire, the overt and covert anxiety of Spielberger, and the Wake-Forest questionnaire in the interview method were completed. All data were analyzed using SPSS software version 22.0. Results: There was no significant statistical relationship between psychological variables and the preferred type of delivery. Age, spouse's education level, and income were among the predictors of preference for delivery. These factors had a statistically significant relationship with confidence in the physician in participating women. Apart from income, there was a statistically significant relationship between other social factors with preference of the type of delivery. There was also another significant relationship between complications during childbirth and postpartum with a preference for the type of the next delivery (P<0.05). Conclusion: Based on the results,there was a relationship between socio-individual factors and complications during and/or after childbirth with a preference for the next type of delivery in women. Further studies are needed.
Diversity of fungal communities inhabiting symptomatic leaves of Cape gooseberry (Physalis peruviana) in the Ecuadorian Andes

espanolUtilizamos metodos cultivo-dependientes para evaluar la ocurrencia y diversidad de comunidades fungicas que habitan en tejido foliar sintomatico de uvilla (Physalis peruviana) en cuatro localidades del norte de los Andes ecuatorianos. Categorizamos los aislados basandonos en las caracteristicas morfologicas de los cultivos obtenidos in vitro, los cuales identificamos al secuenciar la region de ADNr ITS. En total, recuperamos un total de 75 hongos ascomycetos que comprendian 13 generos y 20 taxa. Encontramos que la mayoria de hongos recuperados de tejidos necroticos o cloroticos pertenecian al genero Alternaria. Otros taxa que encontramos con frecuencia fueron Epicoccum, Diaporthe y Xylaria. A nuestro conocimiento, este es el primer estudio en reportar la micobiota asociada a plantas de P. peruviana que presenten hojas con sintomas de enfermedad, de la cual reportamos 2 generos de hongos nuevos para el Ecuador. Esperamos que nuestros resultados provean informacion util para futuros estudios sobre control biologico aplicado a cultivos comerciales en los tropicos. EnglishWe used microbial culture specific methods to assess the occurrence and diversity of fungal communities inhabiting symptomatic foliar tissue of Cape gooseberry (Physalis peruviana) at four different field plots in the northern Ecuadorian Andes. We categorized the isolated fungi based on their morphological characteristics and subsequently identified them through rDNA sequencing of the ITS region. We recovered 75 ascomycetous isolates which represented 13 genera, revealing a total of 20 taxa. We found most isolates recovered from necrotic and straw-colored tissues to belong to the genus Alternaria, while other fungal taxa frequently found were Epicoccum, Diaporthe, and Xylaria. To our knowledge, this is the first study to report the mycobiota associated to P. peruviana plants showing disease symptoms, from which we record 2 new genera of fungi for the first time in Ecuador. Our results are expected to provide useful information for future assessments of biological control on tropical commercial.
Neighbourhood Impacts on Wellbeing: The Role of Housing among Low-Income Tenants

The existing literature on neighbourhood effects suggests that a number of factors within local areas can have an impact on health, including environmental hazards, social networks and the socio-economic status of the area. However, there is minimal evidence regarding the role of housing organisations in shaping these effects. This article sets out the findings from a three-year longitudinal, mixed methods study of tenants of three housing organisations operating in the social and private rented sectors, examining different aspects of neighbourhood experience and their relationship to health and wellbeing outcomes. The findings demonstrate impacts of the immediate environment in terms of close neighbours, the wider neighbourhood environment, and social support networks, which are heavily influenced by tenant characteristics, previous experience and expectations. The services provided by housing organisations, themselves shaped by regulation and market factors, are also important. The findings will have relevance for tenants, housing providers, public health professionals and policy makers.
A Numerical Study on the Aeroacoustic Radiation from a Finite Length Rotating Cylinder

Rotating cylinders have wide applications in different areas, especially the aerodynamic area. However, the acoustic behaviors of these components have not been widely studied. The generating noise from a spinning cylinder is mainly due to the detached vortices from the leeward of the body. In this study, the large eddy simulation technique is used to simulate the flow field over a three-dimensional cylinder. In the following, the Ffowcs Williams and Hawkings equation is used to estimate the noise at the specified locations using the oscillating pressure components on the cylinder wall. The acoustic behavior of both stationary and rotating cylinders are studied. Results show that the acoustic behaviors of cylinders rotating with smaller frequencies (up to f=16f0, where f0 is the dominant detaching frequency of vortices on a stationary cylinder) are nearly the same. However, at higher rotational frequencies (24f0) where vortices are omitted, OASPL of the generated noise is reduced considerably (about 20 dB at different angles with constant radial positions, r=26D, at mid-span plane). On the other hand, when the rotational frequency is increased over this limit, the pressure oscillation on the wall becomes significant and the OASPL approaches higher values.
Decreases in the number of repetitions between sets is indicative of concentric failure in strength training with trained men

The practice of strength training (ST) promotes several benefits such as increased strength, endurance, muscle strength, hypertrophy, as well as changes in body composition. Concentric failure (CF)Several studies show that exercise until CF may be more efficient in promoting positive adaptations about hypertrophy and muscle strength, however, it is still unclear at which time of the exercise CF is achieved. The number of repetitions (NR) performed in each set may be influenced by fatigue caused by CF training. The objective was to analyze the response of the NR between sets as indicative of CF within a session of ST. The study included fourteen trained men (25.0 ± 3.5 years old) (5 ± 4 years) who performed three sets with 75% of 1(repetition maximum) (RM) until CF with fixed rest interval between sets. Statistical analysis: Data normality was tested according to the Shapiro-Wilk test. Subsequently the one-way ANOVA of repeated measures was used to compare the variance of the means between the moments and, when necessary, the post hoc test was used for multiple comparisons using Bonferroni correction. Percentage variations of decreasing NR between sets were found, being from the 1st vs. 2nd set (45,3  14,6 %;), 2nd vs. 3rd set (41,4  19,5%), and 1st vs. 3rd set (67,8  15,1%). The NR can be used to identify if the exercise is being performed up to the CF, considering that the NR between sets decreases substantially due to acute metabolic changes.
Tomato waste extract (Lycopersicon esculentum) as a natural antioxidant in soybean oil under heating

The tomato processing industry generates a large amount of waste, usually composed of peels and seeds. It is known that the tomato is rich in bioactive compounds, mainly carotenoids (lycopene and ? -carotene), however, studies on the functionality of its residues are scarce. Thus, these residues are discarded without the knowledge of possible antioxidant potential. The objective of this work was to determine the stability of bioactive in soybean oil added to the extract of agroindustrial tomato waste under heating. The extract obtained with ethyl alcohol at the ratio of 1: 5 (w/v) was initially analyzed for total phenolic compounds, lycopene, ? -carotene, and antioxidant activity using the DPPH and ? - carotene / linoleic acid. Subsequently, the extract and the synthetic antioxidants, butylhydroxytoluene (BHT) and tert-butylhydroquinone (TBHQ) were applied in soybean oil, and the treatments subjected to heating in Rancimat (180oC/5 h). The thermoxidated samples were analyzed for the composition of tocopherols by high-performance liquid chromatography (HPLC), phytosterols, and fatty acid profile by gas chromatography (GC). The extract of agro-industrial tomato residues showed moderate results concerning its antioxidant activity, 68% by the DPPH method, and 26.2% of auto-oxidation of the ? -carotene / linoleic acid system. The synthetic antioxidant TBHQ had a greater protective effect on soybean oil when compared to the control, providing greater retention of phytosterols (85%) and tocopherols (93%). Tomato extract can be used as a natural antioxidant in industrialized oils, but with less effectiveness than the antioxidant TBHQ.