Miracle-dz/UniFAR-FTUs huggingface dataset:
Octagonal Shaped Fractal Slot Loop Antenna Loaded with Dielectric Resonator

--This paper presents the design and fabrication of multiband fractal co-planer waveguide (CPW)-fed slot antenna having defected ground structure (DGS) which confirms the multiple wireless standards. Minkowski fractal geometry is applied on an octagon which provides a miniaturized design and generates multiple bands. Defected ground structure is used to improve the bandwidth and gain of the antenna. The slot loop formed is acting as a hybrid antenna as it performs both the task of antenna and also of a feed mechanism which is required by a dielectric slab to radiate. The proposed antenna exhibit multiple frequency bands, thus we can call it as multi-band antenna.
Survey Paper on PAPR Reduction Techniques in WiMax OFDM MODEL

-Multipath reflects the signal with different phases and time arrivals . The best solution of the multipath fading is OFDM. Orthogonal Frequency Division Multiplexing (OFDM) is a multicarrier modulation technique for high speed data transmission over multipath fading channels for wireless communication. One of the main problem is high peak to average power ratio (PAPR) which leads to power inefficiency in RF section of the transmitter. Several methods have been proposed to reduce the PAPR.
Accounting for stakeholders in a Catholic charity at the edge of the nineteenth century

Using the positive model of stakeholder theory, this study analyzes accounting and accountability in a charity founded in the late eighteenth century by the Catholic Church. The findings show that accounting was developed to satisfy the heterogeneous accountability demands of the salient stakeholders inside a particular sociocultural domain where Catholic beliefs were prominent, accounting and business rationales were embedded in everyday life, and Enlightenment and liberal ideas flowed among the population. Particularly salient stakeholders conferring legitimacy and funds were the beneficiaries (poor sick people) and donors (believers), who had rights to demand information about the charity’s activities and achievements. The findings also suggest that (1) ecclesiastics attributed to accounting the ability to promote religious fervor, binding together the poor and donors as believers; (2) accounting disclosure also played a major nonspiritual role reflecting the alignment of the Church with Enlightenment principles, supporting the Church’s position in the public aid system, and favoring the interests of both the charity and stakeholder groups; and (3) the Church used accounting to support its traditional influence on social groups’ status and promotion.
Temporal Face Embedding as Biometric Tokenization for Decentralized IoT

—With IoT proliferation, a decentralized biometric access control system is crucial to ensure the identity consistency in cyber physical space. In this paper, a biometric secure modality is proposed based on temporal domain that is often available in IoT systems. A Novel neural network architecture, named LSTM-ResNet, is designed to learn the temporal dynamics of human biometrics such as face for authentication. The model is designed to implement as a device-embedded temporal face embedding as biometrics tokenization to keep data securely decentralized on IoT devices for real-time on-line and off-line identiﬁcation. The combined novel Temporal Face Embedding, LSTM-ResNet and decentralized embedded IoT approaches prevent tampering and spooﬁng unauthorized access. The preliminary results are promising for decentralized biometrics IoT and motivate future work in this area.
Evaluation of the Effect of Aerobic Exercise and Curcumin Consumption on HPG Axis (Hypothalamus-Pituitary-Gonadotropic) in Alcohol Binge Drinking Rats

Background and Objectives: Alcohol consumption has many health side effects. It is well known male gender is a serious risk factor to be an alcohol consumption and finding a way to reduce these complications in the short term is essential. The aim of this study was to investigate the interaction effects of aerobic exercise and curcumin on LH, FSH, Ts and GnRH following alcohol-induced rats. Materials and Methods: 30 adult male Sprague Dawley rats with weighting 220-250 g and 8 weeks of age were obtained for this study, and randomly assigned into five groups (n=6) including: Dextrose-Saline control (Dext-Con), ethanol-control (Eth-Con), ethanol–curcumin (Eth-Cur), ethanol-swimming training (Eth-SWT) and ethanol– SWT+curcumin (Eth-SWT+Cur). The project duration consisted of 4 days of addiction, 6 days of quitting, 14 days of swimming training (60 min/day) and curcumin (50 mg/kg) interventions, and finally animal sacrificed. Blood sample was collected and LH, FSH, Ts, and GnRH level were measured by using ELISA (enzyme-linked immunosorbent assay) kit. Analysis of variance (ANOVA) was performed using SPSS version 21. Results: In the Eth-Con group, alcohol reduced the level of LH, FSH, Ts, and GnRH compared to other specially the Dext-Con group (p=0.001). In the Eth-SWT+Cur group, significantly increased of these hormones was observed (p=0.001). Exercise alone had no significantly effect on FSH and GnRH level. Conclusions: Likely curcumin along exercise could improve HPG axis biomarker after a decline due to excessive alcohol consumption in rat. Lack of exercise effect alone can be due to Exercise-induced oxidative stress.
Influence of Carbonic Maceration on Acid Reduction and Quality of a Pennsylvania Dry Red Table Wine

Carbonic maceration was compared with a more traditional method of producing red table wines and was found to produce wines with higher pH, less total acidity, malate, tartrate, and tannin, and a different sensory quality. The young wines produced by the special process were softer tasting and possessed a special "spicy" odor not present in the wines made with the traditional process. The wines produced by the special process were also more susceptible to induced malo-lactic fermentation.
HOW DO INDIVIDUALS MOBILISE SUPPORT IN EMERGENCIES?

This research is concerned with the question of what role informal support networks play in the welfare mix of social welfare states. Lone mothers rely particularly on social support. Therefore, 116 interviews with lone mothers in Germany and the United Kingdom were carried out. Empirical evidence for an interdependence between informal and formal support mobilisation was provided. Informal support was clearly the dominant support source that contributed to the alleviation of social exclusion.
Large-Scale Hydrological Changes in Tropical Asia: Prospects for Riverine Biodiversity

biodiversity of rivers and their associated wetlands at global and regional (Asian) scales and may well impair or significantly reduce the ecosystem services those rivers and wetlands provide. These threats can be placed in four categories: flow alteration or regulation (including impoundment by dams, water extraction for irrigation, and so on); pollution; drainage-basin alteration (especially deforestation); and overharvesting (mainly of fishes). Researchers, increasingly aware of the potential impact of hydrologic alterations on biodiversity, have begun to focus on the environmental and social consequences of large-scale hydroelectric development (Rosenberg et al. 1997). Their attempts to predict the consequences of flow alterations on biodiversity in Asia, however, are confounded by the trend in the region toward more, and bigger, dams, as exemplified by the Three Gorges Scheme in China (Dudgeon 1995a). In 1950 Asia had 1541 large dams (more than 15 m high), accounting for 30% of the global total (van der Leeden et al. 1990); by 1982 that figure had grown to 22,701 (65% of the global total). Most—18,595, or 82%—were in China. India, ranked fifth in the world (and second in tropical Asia) in number of large dams, had a comparatively modest total of 1085. Absolute numbers of dams have changed over the last several years, of course, but Asia’s proportionate share of the global total of dams remains high.
An Information Theory Approach to Detect Media Bias in News Websites

News websites and portals are, together with social media, major sources of information nowadays. However, such types of media may be biased regarding, especially, political and ideological leaning/orientation. Hence, the awareness of such bias, leaning, or orientation is a key factor for the readers (content consumers) to decide how much content/opinion they accept or reject from a given source. Over the years, especially nowadays, biased information has been used as a tool to control and manipulate public opinion, ultimately leading to the proliferation of fake news. Consequently, it is important to develop methods to automatically identify and inform the reader about the eventual political and ideological bias of the sources. The majority of current research focuses on polarity detection or a bi-class problem, such as left vs. right-wing leaning or Democratic vs. Republican. In addition, most of them are based on a large number of features (lexical or bag-of-words), resulting in computationally intensive methods. In this work, we introduce Poll (POLitical Leaning detector), a strategy based on Information Theory concepts to detect media bias in news websites/portals considering bi-class and multi-class problems. Our strategy reduces the feature space to as little as the number of classes being considered, significantly reducing the overall computational cost. Compared to a representative baseline, our strategy yields a macro accuracy of up to 76% for a four-class problem compared to 22% for the baseline under the same conditions. For some classes, we could reach an F1 of 0.80 against 0.28 from the baseline.
Optimization of enzymatic hydrolysis condition of snakehead (Channa striata) protein hydrolysate based on yield and antioxidant activity

This study was aimed to optimize the enzymatic hydrolysis process of snakehead (Channa striata) protein on antioxidant activity by using Response Surface Methodology (RSM). A three- level factors face centered central composite design (CCD) was adapted to assess effects from four independent variables, namely time (60, 120 and 180 mins), temperature (45, 55 and 65ºC), pH (8, 9 and 10), and enzyme to substrate ratio (1, 2 and 3%). The CCD consisted of 30 experimental points and six replicates of the central points. The antioxidant activity of the snakehead protein hydrolysates (SPH) obtained under optimized conditions was then evaluated using various assays such as chelating effects on ferrous ion, hydroxyl and DPPH radical scavenging activity. The experimental conditions of SPH were optimized at a time of 154.26 min, temperature of 46. 84ºC, pH of 8.46 and enzyme to substrate ratio of 1.04. The predicted response values obtained for DPPH antioxidant activity (15.29%) were close to the validated response values (15.05%). The optimized SPH possessed chelating effects of 30.93% and hydroxyl radical scavenging activity of 88.57%, while the value of DPPH radical scavenging activity was 65.94%. The high values obtained via hydroxyl and DPPH radical scavenging activity suggest that snakehead protein hydrolysate has potential as a natural antioxidant.
Pedestrian Detection System Using Deep Convolutional Neural Networks

—Pedestrian recognition is a key problem for a number of application domains namely autonomous driving, search and rescue, surveillance and robotics. Real-time pedestrian recognition entails determining if a pedestrian is in an image frame. State-of-art pedestrian detection convolution neural networks(CNN) such as Fast R-CNN depend on computationally expensive region detection algorithms to hypothesize pedestrian locations. This paper presents a simple, fast and very accurate approach by cascading fast regional detection and deep convolution networks. Convolution networks have been shown to excel at image classiﬁcation. However, convolution networks are notoriously slow at inference time. In this work, we introduce a fast regional detection cascaded with deep convolution networks that enables real-time pedestrian detection that could be used to alert a driver if a pedestrian is on the roadway. The classiﬁcation CNN has given an accuracy of 95.7%, with a processing rate of about 15 frames per second on a low performance system without a graphical processing unit (GPU).
The Effect of Helicobacter pylori Infection on Prolactin Levels in Child-bearing Females at El-Ingaz Medical Center, Khartoum State-Sudan

1 Department of Medical Laboratory and blood bank, National Cancer Institute, Gezira University-Sudan 2 Department of Clinical Chemistry, College of Medical Laboratory Sciences, Gezira University-Sudan 3 Department of Parasitology, College of Medical Laboratory Sciences, Gezira University-Sudan 4 Department of Medical Laboratory and blood bank, National Cancer Institute, Gezira University-Sudan 5 Laboratory director, Al Motakamil Medical Center, Khartoum –Sudan 6 Department of Medical Laboratory Sciences, Elsheikh Abdallah Elbadri University, Sudan
Differential responsiveness between broiler and layer embryos upon different doses of L-carnitine administration. 1. Hatchability and blood parameters

Several factors in newly hatched chicks can influence post-hatch growth including embryonic parameters. For instance, yolk sac is an important source of energy in developing embryo. Energy of chick during the first days of life is provided by oxidation of fatty acids of yolk sac content (PUVADOLPIROD et al., 1997). It is also assumed that yolk sac is involved in initiation of the growth process for chicks (BIGOT et al., 2001) and carries immunoglobulins which are transferred from hen to chick. Efficient utilization of yolk sac content can be enhanced by administration of substances that are involved in fatty acid metabolism. L-carnitine is well known for its enhancing metabolic use of fatty acids (REBOUCHE, 1992 and HEO et al., 2001) and in addition for its anti-oxydant activity. Indeed, L-carnitine enhances long chain fatty acids’ uptake through mitochondrial membrane. According to CASILLAS and NEWBURGH (1969), L-carnitine facilitates the transfer of fatty acyl groups from yolk into tissues of embryonic chicks via the yolk sac membrane. At d 18 of incubation, the ratio of esterified short chain L-carnitine/free L-carnitine of avian embryos is highest in the tissues suggesting that fatty acid oxidation for energy production in embryos is important (RINAUDO et al., 1991). But, freshly laid eggs have low concentrations of L-carnitine (CHIODI et al., 1994) and chicken embryo has a limited capacity to synthesize L-carnitine during incubation (CASILLAS and NEWBURGH, 1969). However, during hatching process, energy needs of the embryo increase speedily. Therefore, L-carnitine level could be a limiting factor for oxidation of fatty acids during hatching process. Thus, in ovo administration of L-carnitine during the last stage of incubation of chicken eggs may 1) provide additional energy source for hatching activities and 2) lead to changes in some physiological parameters during peri-natal period. The aim of this study was to investigate the effects of in ovo injection of different doses of L-carnitine in egg air chamber at d 18 of incubation on hatchability and physiological parameters. Also, comparison effects of administration of L-carnitine between layer-type and broiler embryos/ chicks were investigated. Material and Methods
Quantitative Genetic Models for Genomic Imprinting

Expression of an imprinted gene depends on the sex of the parent from which it was inherited. Consequently, reciprocal heterozygotes may display different mean phenotypes and this difference affects many genetic properties of both natural populations and experimental crosses. Although the mammalian genome contains a relatively small number of imprinted genes, many of these contribute significantly to important aspects of the phenotype, including growth and development. The past few years has seen development of an increasing number of methods aiming to identify imprinting at loci involved in the development of complex traits. This review considers a number of such approaches, including cases where marker information is and is not available. The application and utility of these approaches is also discussed. Introduction A gene is imprinted when its level of expression is dependent on the sex of the parent from which it was inherited. Imprinted loci are characterized by the reduced or absence of expression of either the paternally or maternally derived allele at a particular developmental stage or in a specific tissue type. Complete inactivation of an imprinted gene results in functional haploidy, with only one of the two copies of a gene expressed. More generally, however, imprinting results in the functional nonequivalence of reciprocal heterozygotes: inheriting an A1 allele from one’s mother and an A2 allele from one’s father gives a different phenotype, on average, than the reverse inheritance pattern. Approximately 83 imprinted genes have been identified in mammals, including 41 in humans, and many of these genes are thought to be involved in traits such as growth and development [Morison et al., 2005]. A number of approaches have been used to demonstrate imprinting of specific genes or chromosomal regions, including examining differences between gynogenetic and androgenetic embryos, differences between triploids where the extra set of chromosomes are maternally or paternally derived, chromosome deletions, uniparental disomies, transgene expression
Learnable receptive fields scheme in deep networks for image categorization

: An increasing interest in computer vision and machine learning has focused on visual categorization as it is a fundamental task for image retrieval, organization and robotic vision. Over the past decade, various deep learning-based models have been proposed and broadly applied to visual recognition and categorization. In this paper, the proposed approach learns features from scratch rather than employ hand-crafted (SIFT) and (HOG) descriptors. Deep hierarchical architecture for learning effective image representations can be built up layer by layer. Speciﬁcally, K--SVD and OMP are used for training and encoding phase respectively due to their simplicity and efﬁciency. In addition, sum, average and max operators are three commonly strategies for pooling in modern categorization models. We aim to apply an improved scheme which learns the receptive ﬁelds for pooling together with classiﬁer instead of traditional pooling pattern. We provide a detailed analysis in deep networks for event and object tasks respectively and compare our novel method with several state-of-the-art algorithms comprising kernel-based feature learning and saliency-weighted hierarchical sparse coding. Finally, experimental results show that our algorithm performs better on UIUC--sports and Oxford ﬂowers datasets.
Reducing Word Embedding Bias Using Learned Latent Structure

Word embeddings learned from collections of data have demonstrated a signiﬁcant level of biases. When these embeddings are used in machine learning tasks it often ampliﬁes the bias. We propose a debiasing method that uses (Figure 1) a hybrid classiﬁcation - variational autoencoder network. In this work, we developed a semi-supervised classiﬁ-cation algorithm based on variational autoencoders which learns the latent structure within the dataset and then based on learned latent structure adaptively re-weights the importance of certain data points while training. Experimental results have shown that the proposed approach works better than existing SoTA methods for debiasing word embeddings.
Using Ni isotopes as biosignatures

Nickel (Ni) is a key element in metabolic pathways of methanogenic Archaea due to its use in Ni­enzymes. Ni is strongly fractionated during its absorption by methanogens. Δ​Ni values (δ​Ni​cell​­δ​ Ni​environment​) as low as ­2‰ have been reported in methanogenic cultures. However, Ni sorption to particles, e.g. clays and Fe oxides, and organic ligands can yield similar fractionation patterns. The usefulness of Ni as a biomarker has been proposed and debated. Cell culture experiments confirm general negativeΔ​Ni values on the order of 1 to 2‰. In some cases cells do not display the well known negative Δ​Ni signature, most likely due to simultaneous abiotic fractionation by organic ligands. Experiments suggest increasing fractionation with increased Ni concentrations in growth media. To assess Ni as a viable biomarker for methanogens, we provide new Ni isotope data from rocks and fluids from an outcrop of the Tekirova ophiolite, Turkey, a system undergoing serpentinization with active CH​4 and fluid seeps. Methanogen presence and hence a partially biogenic origin of the CH​4​are confirmed. In one locality, methanogen presence can be linked to a negative excursion in δ​C and a significantly lower δ​Ni value. There is no mineralogical explanation for the negativeδ​Ni excursion, hence we suggest that the fractionation of Ni may be a true Ni biosignature. The viability of Ni as a biomarker for extraterrestrial or early terrestrial life is doubtful, due to the large number of Ni fractionating processes and our limited understanding of the Ni budget in e.g. the oceans and the biosphere. Future research should focus on revealing abiotic fractionation in relevant processes, such as serpentinization and the formation of BIFs and on in­situ analysis of Ni isotopes of microfossils.
Detection of Uterus Fibroids in Ultrasound Images: a survey

Uterine fibroids are an abnormal growth of smooth muscle in the wall of the uterus. These growths are benign tumors that occur as a single large mass or many smaller masses. Although it is very rare, this can become malignant (cancerous) and the presence of fibroid can cause infertility and repeated miscarriage. Ultrasound images are an appropriate tool for diagnosing uterus related disorders. Extracting the fibroid from ultrasound scanned uterus image is a challenging task because of size, location and low contrast boundaries. In this paper, a study of various ultrasound image segmentation and uterus fibroid detection methods is given. A survey on detection of fibroid is clarified with a comparative study.
A comparative study of various color image segmentation methods

This paper has presented a review on different image segmentation techniques. The image segmentation; segments a given image into separate regions and objects. It is widely used in various vision applications like face detections, motion detection etc. The overall objective of this paper is to review various techniques of image segmentation. The short comings of image segmentation techniques will also be evaluated. This paper ends up with the analytical solution to overcome the problems of the existing techniques
Footstep Detection with HoloLens

: This paper presents results on using AR/MR device (HoloLens) and machine learning approach for detecting whether a user wearing the device is touching the ground with the left or the right foot while walking at different speeds and in different directions. The accuracy of the prediction reached 88% even after the user’s gait data had been collected for less than 1 minute. Applications include rendering footprints in games in real time, body movement recognition for personalization, recording and replaying guided tours by experts.