Miracle-dz/UniFAR-FTUs huggingface dataset:
The Investigation of Cytokines and Bacterial Isolates in the Patient with Thyroid Gland Disorders

The study included the collection of 175 samples from patients diagnosed with thyroid disorder with different ages from during the period from October, 2016 to February, 2017 in Imamin Al-Kadiman medical city and Al-Kindi Teaching Hospital Results found a bacterial growth in the samples of urine, 80% were positive for bacterial growth while 20% were with negative growth for bacterial. All isolated diagnosed by microscopic and morphological characteristics, while API system was used for biochemical detection. The percentage of bacteria in isolates was 50% of Staphylococcus aureus, 20% of Staphylococcus, 12.5% of both E. coli and Pseudomonas aeruginosa, 5% of Serratia marcescens. The serum levels of IL-6 significantly increased in the patients (341.65±34.44 pg/ml) compared with healthy group (169.62±72.55 pg/ml). Although, TNF-α levels significantly decreased in the patients (228.55±18. pg/ml) compared with healthy group (317.09±24.53 pg/ml). Moreover, a positive correlation was observed between the levels IL-6 and TNF-α with correlation coefficient of 0.452.
Building Detection from Satellite Imagery using Ensemble of Size-Specific Detectors

In recent years, convolutional neural networks (CNNs) show remarkably high performance in building detection tasks. While much progress has been made, there are two aspects that have not been considered well in the past: how to address a wide variation in building size, and how to well incorporate with context information such as roads. To answer these questions, we propose a simple, but effective multi-task model. The model learns multiple detectors each of which is dedicated to a specific size of buildings. Moreover, the model implicitly utilizes context information by simultaneously training road extraction task along with building detection task. The road extractor is trained by distilling knowledge from another pre-trained CNN, requiring no labels for roads in its training. Our experiments show that the proposed model significantly improves the building detection accuracy.
A Simple Neural Network For Evaluating Semantic Textual Similarity

This paper describes a simple neural network sys-tem for Semantic Textual Similarity (STS) task. The basic type of the system took part in the STS task of SemEval 2017 and ranked 3 rd in the primary track. More variant neural network structures and experiments are explored in this paper. Semantic similarity score between two sentences is calculated by comparing their semantic vectors in our system. Semantic vector of every sentence is generated by max pooling over every dimen-sion of their word vectors. There are mainly two trick points in our system. One is that we trained a convolutional neural network (CNN) to transfer GloVe word vectors to a more proper form for STS task before pooling. Another is that we trained a fully-connected neural network (FCNN) to transfer difference of two semantic vectors to the probability distribution over similarity scores. In spite of the simplicity of our neural network system, the best variant neural network achieved a Pearson correlation coefﬁcient result of 0.7930 on the STS benchmark test dataset and ranked 3 rd 1 .
Forecasting growth and inflation in an enlarged euro area

We compare models for forecasting growth and inflation in the enlarged euro area. Forecasts are built from univariate autoregressive and single-equation models. The analysis is undertaken for both individual countries and EU aggregate variables. Aggregate forecasts are constructed by both employing aggregate variables and by aggregating country-specific forecasts. Using financial variables for country-specific forecasts tends to add little to the predictive ability of a simple AR model. However, they do help to predict EU aggregates. Furthermore, forecasts from pooling individual country models usually outperform those of the aggregate itself, particularly for the EU25 grouping. This is particularly interesting from the perspective of the European Central Bank, who require forecasts of economic activity and inflation to formulate appropriate economic policy across the enlarged group. Copyright © 2008 John Wiley & Sons, Ltd.
A Sophisticated Approach to Detect Email Frauds

Electronic mail is a probably the most convenient way of transferring messages electronically from one person to another to any part of the world. Important features of e-mail such as its speed, reliability, efficient storage options and a huge number of added facilities make it highly popular among people from all sectors of business and society. Large amount of private and sensitive information is exchange using emails. But being popular has negative aspects too. Securing email has forever been an important issue. It can be used for both legitimate and illegitimate activities. Email frauds can be used for purposes such as spreading viruses, launch phishing attacks taking sensitive business data and other industrial espionage activities. Emails can be sent to a person from different address and it is not validated at any stage without being noticed by the receiver. Here presenting a new sophisticated approach to detect email frauds. This is the efficient method for providing integrity to emails.
Improvement of defect detection in shearography by using principal component analysis

A post-processing technique based on principal components analysis (PCA) is proposed for shearography for defect detection. PCA allows decomposing a time series of images into a set of images called Empirical Orthogonal Functions (EOF), each showing features with a given variability in the time series. We have applied PCA on composite samples containing various defects at different depths and which undergo transient thermal wave. Analyzing the temporal series shows the shallow defects appearing first whereas the deeper ones appear later. With PCA all the defects appear in one or two of the EOF, easing the identification of defects.
The Bolzano-Weierstrass theorem in generalised analysis

Let κ be an uncountable regular cardinal with κ<κ= κ. We consider two totally ordered fields κ–ℝ and ℝκ, due to Sikorski and the second author, respectively, that serve as the κ-analogues of the real line and consider generalisations of the Bolzano-Weierstrass theorem for them, showing that for ℝκ, the weak κ-Bolzano-Weierstrass theorem is closely related to the tree property of κ.
Towards Building a Frame-Based Ontology for the Arabic Language

This paper proposes a framework for building a frame-based ontology for the Arabic language. The proposed framework consists of two main phases. The first phase involves manual construction of a seed frame-based ontology. This is followed by the second phase in which the seed frame-based ontology is enriched with new lexical fields (only if they do exist), and/or enriching it with binary relations between existing or new lexical fields. The binary relations considered are synonyms/antonyms, hyponyms/hypernyms, and holonyms/meronyms. In addition, the paper presents a comprehensive introduction of lexical semantics providing examples from the Arabic language, and then surveys works of researchers aiming to build ontologies for the Arabic language. Keywords—Arabic ontology; lexical semantics; natural
Kinds of Blue ∗ Diversity in U . N . Peacekeeping Missions and Civilian Protection Vincenzo Bove

For a given number of troops in a peace operation, is it advisable to have soldiers from one country, or should the U.N. recruit peacekeepers from a variety of donors? Since 1990, the number of contributors to peace operations has grown threefold and most operations have carried the mandate to protect civilians. We explore the effect of diversity in the composition of a mission, measured by fractionalization and polarization indices, on its performance in protecting civilians in Africa in the period 1991-2008. We find that diversity decreases the level of violence against civilians, a result that holds when geographic and linguistic distances between countries are considered.
Ghana and Zambia : Achieving equity in the distribution of insecticide-treated bednets through links with measles vaccination campaigns

This discussion paper makes an in depth analysis of the integration of the delivery of insecticide-treated nets (ITN) with vaccination campaigns for measles and malaria control in Africa. In populations where measles vaccination campaigns are conducted, malaria is frequently the greatest health risk to children, particularly after the campaign reduces measles mortality. If each child vaccinated against measles during a campaign also received an ITN, ITN coverage will increase rapidly and equitably. The potential benefits of this approach have prompted recent global policy changes to encourage increased integration of ITN delivery and vaccination (WHO-UNICEF 2004). However, linking ITN distribution with measles vaccination presents many operational challenges. The findings from these Phase I and II studies suggest that integrating ITN distribution into vaccination campaigns can achieve higher and more equitable ITN coverage than other delivery strategies at a lower cost to both providers and consumers. Linking ITNs to measles campaigns presents an important opportunity for reaching malaria control goals and merits larger scale implementation and evaluation.
Global hypoellipticity, global solvability and normal form for a class of real vector fields on a torus and application

The main purpose of this paper is to present a class of real vector fields defined on a torus for which the concepts of global hypoellipticity and global smooth solvability are equivalent. Furthermore, such a vector field is globally hypoelliptic if and only if its adjoint is globally hypoelliptic, and therefore we can reduce it to its normal form. As an application, we study global C∞ solvability for certain classes of sub-Laplacians.
The Effects of Context Richness and Different Task-demands on Incidental Vocabulary Acquisition and Retention

Incidental learning in reading is an effective way to expand vocabulary acquisition and there are many factors influencing the effect of it. This proposed paper will make an attempt to explore how and to what extent different kinds of tasks based on reading and different contextual richness affect the recognition and retention of vocabulary encountered in reading. 50 sophomore English majors at the same English proficiency level from a university in Xi’an will be selected and be asked to complete different reading processes, which aim to investigate the role of context richness and task demands respectively in incidental learning. The data will be collected from the scores from every task and be analyzed with one-way ANOVA and multi-way
CONCEPT OF GROUP TECHNOLOGY ACCOMPLISHMENT IN THE FIELD OF CELLULAR MANUFACTURING SYSTEMS

In this paper we have planned to give the detailed examination of group technology (GT) and its principle of implementation in the field of cellular manufacturing to achieve the drastic change in output of production. Cellular manufacturing system has been proved a vital approach for batch, job shop production and some extend to process industries and group technology has been an essential tool for developing a cellular manufacturing system. With the principle implementation of group technology act as a traditional concept and still plays significant role in new manufacturing concepts like just in time, total quality management and technologies such as optimized production technology, computer integrated manufacturing in manufacturing system concept of group technology helps to achieve reduction in setup time, inventory levels and logistics of goods and also gives effective control of production and also we narrate some examples to easily understand the group technology concept by produce the basic ideas about GT in the field of cellular manufacturing also decision- making and accountability are more locally focused, often resulting in quality and productivity improvements.
Peer assessment as a method of improving student engagement

To encourage increased student attendance and engagement in a third-year economics unit, the curriculum was redesigned to incorporate continuous assessment throughout the semester. A component of group project marks were allocated to peer assessment, in an attempt to address concerns about free-riding colleagues sharing a common mark. This study investigated the consistency of marks awarded to peers within teams, and the acceptance by students of marks awarded by peers. Students were asked to provide ratings and explanatory comments for each of their group peers. Focus groups were conducted to determine students’ acceptance of this strategy. Eighty student ratings were compared to determine consistency of assessment. Within groups, students who received higher marks from their peers generally awarded marks to their peers across a wider range, whereas students who received lower average grades often awarded the same mark to all team members. These results might indicate that students who were attending class regularly and/or contributing at a higher level were more discriminating in the marks awarded to their peers. Similarly, non-contributors (as identified by their peers) assigned the same or similar grades to each of their peers, possibly due to a lack of knowledge about their peers’ contributions.
Tax Aggressive Behaviour in Private Family Firms - The Effect of the CEO and Board of Directors

Tax aggressiveness is defined as downward management of taxable income through tax planning activities which can be legal or illegal or may lie in between. Given that taxes are an important cost for each firm, tax aggressiveness may be desired by its shareholders. In this paper, we investigate to what extent CEO ownership and governance (e.g. composition of the board of directors) affect tax aggressive behavior decisions in private family firms. More specifically, we extend prior knowledge by studying how board’s monitoring behavior may moderate the relationship between the CEO’s involvement in the firm and tax aggressive behaviour of the firm. The data, collected through a private survey, consist of 600 Finnish family and non family SMEs and is a panel with observations from the years 2000-2005. The model is estimated based on robust Ordinary Least Squares estimations including several moderating effects. In this paper, we find that private family firms appear to be less tax aggressive than private non family firms. Even though tax aggressive behaviour provides tax savings and allows the CEO to mask rent extraction (e.g. earnings management, perquisite consumption, excessive salaries…) to the detriment of other shareholders, the non financial costs being the possible reputation damage and loss of socioemotional wealth seem to outweigh the benefits. Within the group of private family firms, results show that family firms with a lower CEO ownership share are more eager to engage in tax aggressive behaviour. This result highlights the importance of the unique agency conflict between the CEO (agent and possibly principal) and (other) shareholders (principals) in determining family firms’ tax reporting. Finally, our results show that the presence of an outside director in the board of directors improves the monitoring effectiveness which reduces the tax aggressive behavior of those private family firms with low CEO ownership shares.
Mechanical–Structural Investigation of Ion-Exchanged Lithium Silicate Glass using Micro-Raman Spectroscopy

Micro-Raman spectroscopy was used to determine the structural modifications occurring in a simple ion-exchanged glass. The base lithium silicate composition 30Li2O–70SiO2 was studied as it underwent ion exchange, Li+ ↔ K+, at six temperatures spanning the glass transition point. Using a well-developed relationship between the Si–O–Si bond angle, the Si–O bond length, and Raman shifts, the reduction in network molar volume and increase in compressive stress were estimated. On the basis of the effect of the ion-exchange temperature, the existence of a threshold energy below which the compressive stress manifests as the reorientation of silica tetrahedra only and above which the system relaxes by increasing the Si–O bond length is proposed. Finally, the linear network dilation coefficient is revisited in terms of these new data and an explanation given for its underestimation and overestimation of stress at low and high temperatures, respectively.
Efficiency of Buccal DNA Sampling Device in the Mortuary

Identification of forensic DNA samples by short tandem repeat (STR) profiling is currently an essential component of criminal investigations and can aid in linking perpetrators to crimes as well as identifying missing individuals or unidentified remains. In South Africa, recent amendments to legislation have allowed for the mandatory acquisition of reference DNA samples from certain offenders in order to populate the new National Forensic DNA Database. A novel method for the collection of buccal samples, the EasiCollect device, has been proposed to facilitate the collection of these DNA samples, replacing blood collecting devices as the standard method of DNA collection. Subsequently, this device has been introduced into South African state mortuaries to assist in the identification of deceased individuals. In order to ascertain if this device is suitable for use in the postmortem setting, an investigation was performed to compare the main methodology currently utilised within South African mortuaries, namely femoral blood transferred to ‘Fast Technology for Analysis of nucleic acids’ (FTA) cards, and buccal cells obtained using the EasiCollect device. DNA yields and STR genotyping results were compared between the two collection methods in thirty deceased individuals. Buccal samples provided a significantly greater DNA yield than blood samples, while no significant difference was observed between the qualities of the sample types as measured by the 260/280 nm ratio. Full STR profiles were obtained from all blood and buccal samples, with amplification efficiency showing limited DNA degradation and PCR inhibition in these samples, and only 3% of samples giving potentially disputable results. Numerous issues surrounding the collection of blood samples, however, indicated that this method is not optimal for use in the mortuary, with the EasiCollect device providing a more practical and robust method for the collection of DNA samples in the mortuary.
The Hepato-Protective Potentials of Aqueous Leaf Extract of Cassia Occidentalis against Paracetamol Induced Hepatotoxicity in Adult Wistar Rats

This study investigates the hepato-protective potentials of aqueous leaf extract of Cassia occidentalis on paracetamol-induced hepatotoxicity in adult Wistar rats. Twenty adult rats weighing between 150 – 300g were used for this study. They were randomly divided into four groups (A, B, C, and D), whereby group A served as the control, while groups B, C and D served as test groups. Hepatotoxicity was induced in the test groups via oral administration of paracetamol (800mg/kg bw). However, while groups C and D were treated for 21 days with 250mg/kg and 500mg/kg/BW of Cassia occidentalis leaf extract respectively, group B was left untreated and served as the test control. Using standard laboratory procedures, the livers were harvested, histologically processed, and examined. Microscopy revealed normal histological hepatocytes in the control animals while those of test control were severe vascular congestion, periportal infiltrates of chronic inflammatory cells and periportal oedema. However, hepatic sections from groups C and D presented a dose dependent healing actions compared to the features observed for group B (untreated hepatotoxic group). Judging by these findings therefore, one can assert that aqueous leaves extract of Cassia occidentalis may be hepato-protective against hepatotoxicity. Keywords : Cassia occidentalis, Hepatotoxicity, Paracetamol, Liver.
Real Time Single Image Dehazing and Soil Removal Using CNNs

Removal of atmospheric haze and soil from a single image captured via monocular camera is very challenging and computationally ill-posed phenomenon in the advanced driver assistance systems (ADAS). The recent development in the field of deep learning has made it possible for the researchers to train a model using various available on-the-shelf tools. However, such models are not adapted to embedded platforms due to their deep architecture design. In this paper, we propose a new Convolutional Neural Network (CNN) based architecture design, which inspires from EVD-Net j-level fusion and AOD-Net for real-time single image dehazing and soil removal for an embedded platform. The CNN is designed based on a reformulated atmospheric scattering model for haze and soil removal called Haze and Soil Removal Using Convolutional Neural Network (HSRCNN). This is a first fully end-to-end CNN model for real-time single image dehazing and soil removal. The model is trained and tested using our own generated dataset for both haze and soil. Furthermore, a pre-trained faster R-CNN is used to verify the performance difference between haze and soil images as compared to clean images. Lastly, we witnessed a great improvement especially, in image quality and object detection. HSRCNN is applicable to a variety of distinct scenarios like ADAS, medical imaging, night imaging and underwater imaging. The lightweight design makes it easier to cascade with other neural networks. The model is also tested and evaluated using different public datasets such as RESIDE.
Tell don’t just show: Narratives improve insight more than interactivity in communicative visualizations

Communicative visualizations incorporating narratives and/or interactivity are increasingly commonplace. However, the relative importance of narrative versus interactivity in improving readers’ understanding is unclear. We designed visualizations which vary in presence of interactivity (static or interactive) and narrative (non-narrative or narrative), presented them to Turkers, and measured recall using an 11 item True/False questionnaire. We find a weak positive effect on recall—an increase of ~8.4 percentage points (95% CI: [4.5, 12.7])—from the presence of narratives, but little or no effect from interactivity (95%CI: [-1.1, 5.1]). We argue that narratives can better facilitate insight generation for viewers of communicative visualizations, but that interactivity may not. We discuss implications for the broader definition of information visualization itself: contrary to well-known existing definitions, we question whether interactivity is a necessary component of any information visualization, rather than a subordinate component that is useful if and when a design calls for it.