Miracle-dz/UniFAR-FTUs huggingface dataset:
Essential Oil Composition and Antidiabetic, Anticancer Activity of Rosmarinus officinalis L. Leaves from Erbil (Iraq)

Abstract The essential oil of Rosmarinus officinalis L. leaves growing in Erbil, Iraq was investigated by GC/MS. The essential oil (EO) was extracted by hydro-distillation method. The EO of R. officinalis leaf was examined in-vitro for antidiabetic and anticancer effects. The in-vitro α-glucosidase enzyme inhibition assay was performed to determine antidiabetic effects of R. officinalis EO. MTT assay was carried out to determine the potential antiproliferative and cytotoxic properties of R. officinalis EO. The essential oil of R. officinalis leaf yielded 42 constituents amounting to 99.84 %. The major constituents of R. officinalis EO were verbenone (23.46 %), 1,8-cineol (15.96 %), α-pinene (12.10 %), camphor (10.98 %), and bornyl acetate (5.78%). The R. officinalis EO produces dose dependent inhibition of α-glucosidase enzymes which ranges from 31.01±3.99 to 74.66±1.44 % for concentration 3.125 to 100 µg/mL, respectively. The R. officinalis EO with IC50 value 9.64±2.44 µg/mLwas found comparable with acarbose (IC50 value 12.04±3.17 µg/mL) against α-glucosidase enzyme. The MTT test shows that R. officinalis EO produces dose dependant cytotoxicity against human breast adenocarcinoma MDA-MB-231cells with IC50 value 59.35 µg/mL. The present study confirmed that the EO of R. officinalis could be used for management of cancer and diabetes mellitus.
A hybrid meta-heuristic approach for optimization of routing and spectrum assignment in Elastic Optical Network (EON)

ABSTRACT In next-generation high-speed networks, Elastic Optical Networks (EONs) play a promising role due to its more flexibility and optimal spectrum management. Some of the key facts of EON that have to be addressed are Routing and Spectrum allocation. In this paper, an efficient routing algorithm is proposed along with optimization of spectrum allocation for EON. Improved Bellman Floyd Warshall (IBFW) shortest path routing and Enhanced Shuffled Frog Leaping Algorithm (ESFLA) are used in our proposed work. Simulation results are compared with recent RSA algorithms with appropriate metrics where it achieves better spectrum utilisation and reduced number of blocking.
FLEXURAL PERFORMANCE EVALUATION OF VARIOUS CARBON FIBRE FABRIC REINFORCED GEOPOLYMER COMPOSITE

In this paper, the results of an experimental investigation on the flexural behaviour, the mechanical properties, and the failure mode of a carbon textile reinforced geopolymer mortar composite subjected to four-point bending test are presented. The influence of various factors such as the type of the carbon fibre fabric, reinforcement ratio, dosage of the chopped basalt fibre on the flexural performance of the reinforced geopolymer composite is experimentally studied. The results reveal that the use of carbon fibre fabrics in the production of high-strength geopolymer matrix composites makes it possible for them to achieve a relatively high mechanical strength. Moreover, the value of the flexural strength and flexural toughness is strongly influenced by the reinforcement ratio and the mechanical properties of the fibre yarn of the carbon textile. The addition of the chopped basalt fibre (BF) plays an important role in both the improved mechanical strength and the failure mode of the geopolymer textile composites. The failure mode of all the specimens shows either a pure bending failure or a peeling off the concrete at the matrix/fibre interface due to the rupture of some filaments in the outer layer and the loss of the bonding strength of the fibre yarn in the matrix leading to the slippage of the fibre yarns within the matrix.
Group‐based guilt and shame in the context of intergroup conflict: The role of beliefs and meta‐beliefs about group malleability

Intergroup conflicts have detrimental effects on individuals, collectives, and the international community more broadly. During such conflicts, in-group members of each adversarial group behave destructively against members of the rival out-group, sometimes in ways that would be considered by the in-group as violations of accepted moral values and norms (Halperin, 2016). When this occurs, some members of the groups immersed in conflict may experience moral emotions like group-based guilt and shame (Branscombe & Doosje, 2004; Giner-Sorolla, 2013; Lickel, Steele, & Schmader, 2011). These emotions are experienced as a result of the individuals’ identification with a group or a social category (Mackie, Devos, & Smith, 2000; Smith & Mackie, 2008; Yzerbyt, Dumont, Wigboldus, & Gordijn, 2003), and have been extensively studied, due to their potentially pivotal role in promoting intergroup conflict resolution and reconciliation. Furthermore, these moral emotions can generate constructive behavioral tendencies oriented toward repairing the damage done to rival group members (Brown & Čehajić, 2008; Brown, González, Zagefka, Manzi, & Čehajić, 2008) or supporting conciliatory actions required for intergroup reconciliation (e.g., Wohl & Branscombe, 2008). Received: 14 April 2019 | Revised: 12 November 2019 | Accepted: 17 December 2019 DOI: 10.1111/jasp.12651
A Classification Method for E-mail Spam Using a Hybrid Approach for Feature Selection Optimization

Spam is an unwanted email that is harmful to communications around the world. Spam leads to a growing problem in a personal email, so it would be essential to detect it. Machine learning is very useful to solve this problem as it shows good results in order to learn all the requisite patterns for classification due to its adaptive existence. Nonetheless, in spam detection, there are a large number of features to attend as they play an essential role in detection efficiency. In this article, we're working on a feature selection method to e-mail spam. This approach is considered a hybrid of optimization algorithms and classifiers in machine learning. Binary Whale Optimization (BWO) and Binary Grey Wolf Optimization (BGWO) algorithms are used for feature selection and K-Nearest Neighbor (KNN) and Fuzzy K-Nearest Neighbor (FKNN) algorithms are applied as the classifiers in this research. The proposed method is tested on the "SPAMBASE" datasets from UCI Machine learning Repesotries and the experimental results revealed the highest accuracy of 97.61% on this dataset. The obtained results indicateed that the proposed method is suitable and capable to provide excellent performance in comparison with other methods.
Refined reverse correlation : a technique for investigating the power of faces

People effortlessly and rapidly form a first impression of an individual’s personality based on their facial appearance. Forming an impression based on facial cues can have real world implications, for example, for the outcome of elections, courtroom decisions or work-place interviews. Research using traditional methods has, however, failed to identify the facial features that are related to specific personality traits in a reliable and valid way. This challenge can be overcome using a reverse correlation method. Here I present a refinement of the traditional reverse correlation image classification technique. Over the course of four projects I highlight the different possibilities that the refined technique offers. In the first project I will present how the technique was used to extract the facial prototype of someone that is likely to be ostracized. In the second project, I show how we extracted prototypes that evoke different emotions, applied them to real facial photographs and set the different prototypes in relation with each other. The third project offers insights into how the technique was used to investigate self-perception without any external standard of comparison except the participants’ own face. Finally, I present a fourth project where the technique was used to investigate whether the belief about how two personality traits co-occur on a conceptual level is reflected in the facial characteristics that are used to form an impression from faces. The here presented refined technique adds to the traditional reverse correlation technique in that internal representations can be visualized without visible artifacts, that the extracted prototypes can be applied to real photographs, and set in relation with each other. The discussion focuses on the reliability and validity of the method and presents future research possibilities.
High sensitivity-c reactive protein as an additional marker for increased risk of cardiovascular disease in patients of polycystic ovary syndrome

Background: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder affecting women of reproductive age group with a worldwide prevalence of about 4 to12%1,2. PCOS is seen in up to 25% of the Caucasians and 50% of the South Asian women respectively3,4. It is a heterogeneous disorder of unknown aetiology with a strong genetic element5. PCOS does not exclusively involve the reproductive apparatus; it has a complex number of systemic relevancy symptoms. It leads to Metabolic Syndrome with severe consequences on the cardiovascular system6. The precise cardiovascular disease (CVD) risk in women with PCOS remains unclear because there are no longitudinal studies pertaining to cardiovascular events. There is a paucity of data in regard to cardiovascular event rates and mortality in PCOS hence the present study was aimed to assess cardiovascular disease risk in women with PCOS. Aim: To evaluate cardiovascular disease risk in women with Polycystic ovary syndrome. Materials and Methods: 50 diagnosed cases of PCOS and 50 age matched healthy females were included in this study. Cases were diagnosed based on new Rotterdam criteria formulated by the American Society for Reproductive Medicine (ASRM) and the European Society for Human Reproduction and Embryology (ESHRE). Blood samples were collected after overnight fasting. Serum High sensitivity-C Reactive Protein (hs-CRP), Total Cholesterol(TC), Triglycerides(TG), HDL Cholesterol(HDL-C), VLDL Cholesterol(VLDL-C), LDL Cholesterol (LDL-C) were estimated. Body Mass Index (BMI) was calculated for women in both the groups. Statistical analysis: Results were analyzed using unpaired t-test and p-value was calculated. BMI was correlated with hs-CRP using one way ANOVA test. Statistically non-significant increased levels of serum total cholesterol, Triglycerides, HDL cholesterol, LDL cholesterol, VLDL cholesterol and hs-CRP in PCOS cases as compared with control were observed. BMI was found to be significantly inc
Abstract 18647: Functional Evaluation of a Patient-specific 3D Printed Model of Aortic Regurgitation

Introduction: Quantification of aortic regurgitation (AR) can be challenging using non-invasive imaging methods. In vitro simulation of patient-specific AR would allow reference standard measurement of the regurgitant flow volume and a comparison against Doppler methods of AR quantification. Hypothesis: We sought to build a functional patient-specific 3D printed model of the aortic valve (AV) and to replicate AR Doppler parameters recorded during a clinical echocardiogram. Methods: We identified a clinical multi-detector CT dataset (mid-diastolic phase) of a selected patient with generative AV disease and mild AR. Segmentation software was used to segment the calcified and non-calcified components of the aortic root. Fused-material 3D printed was used to create a patient-specific physical model of the aortic root, AV cusps, regional calcification and left ventricle. The 3D model was coupled to a flow loop to replicate the trans-valvular hemodynamic conditions recorded during a clinical echocardiogram. The accuracy of hemodynamic replication was evaluated using Doppler imaging and compared to the clinical study. Results: Functional Doppler imaging of the 3D printed model demonstrated similar quantitative parameters to the clinical Doppler findings, respectively; peak velocity 4.6 vs 4.7 m/s; regurgitant time 460 vs 458 ms; pressure half time 312 vs 331 ms; time-velocity index 167vs 162 cm. Regurgitant jets were qualitatively similar. Doppler velocity profiles for the patient and the 3D model, shown in Figure 1. We demonstrate an in vitro method to mimic and quantify AR using patient-specific anatomic and functional 3D modeling. Conclusion: We describe the development of a functional patient-specific 3D printed model of the AV replicating both the geometry and function of AV regurgitation. This initial functional modeling may extend to studies of AR severity using novel imaging modalities (e.g. 3D color Doppler) or structural heart interventions.
Diode laser treatment of an oral squamous papilloma of soft palate

Oral squamous papilloma is one of the most common benign epithelial neoplasm, frequently seen on the tongue, palate, uvula, and gingiva; and found to be associated with human papillomavirus (HPV) 6 and 11. Treatment laser-assisted surgery is common because of several advantages such as successful hemostasis, devoid of sutures, wound sterilization, and minimal postoperative pain and edema. The aim of this report is to present the case of oral squamous papilloma of the soft palate in a 57-year-old male patient and its management with a diode laser.
PERSONAL COST OF REPORTING AND STATUS OF WRONGDOER: EXPERIMENTAL STUDY OF WHISTLEBLOWING INTENTION

Whistleblowing is an important action for the organization as a form of internal control of illegal actions that cause losses. This study aimed to test of causality of the personal cost of reporting and status of the wrongdoer on whistleblowing intention. This study used a true experimental design between subjects 2x2. The subjects of this study were 95 accounting study program students. The students acted as the government’s internal auditor. The results of this study indicate that whistleblowing intentions will be higher in personal cost of reporting and the status of the wrongdoer low compared to personal cost of reporting and status of wrongdoer high. A whistleblower prefers not to perform whistleblowing when the wrongdoer has a higher position and sanctions to be received are severe.
The Relationship between Liquidity and Profitability in Emerging Countries: Evidence from Bangladesh

The relationship between liquidity and profitability has become an important issue among any organization. It is all about managing current assets and current liabilities in such a way so as to maximize profitability. Liquidity is perceived as the debt paying ability of going concern. Hence, it is important to keep a constant eye on the liquidity position of the company as without it the company cannot survive. The concern of business owners and managers are to devise a strategy that will help maintain liquidity as well as to increase profitability. Liquidity and profitability are closely related because one increases, and the other decreases. This study aims to reveal the relationship between liquidity and firm’s profitability by using the data of the cement industry listed on the Dhaka Stock Exchange Ltd in Bangladesh. Annual data of 6 out of 7 companies are used for the period 2013-2017 in the study. The relationship between liquidity and firm’s profitability were examined by the Pearson’s correlation analysis using the SPSS-23 version. The dependent variable is defined by net profit, return on assets and return on equity and the independent variables are the current ratio, quick ratio, and the cash conversion cycle. The results in the correlation matrix show the existence of the relationship between liquidity and profitability. The study found that the cash conversion cycle has a strong negative relationship with all profitability ratios (NPM, ROA, and ROE). Moreover, the study also observed that the liquidity ratio (CR, and QR) have positive relationship with all profitability ratios of the cement industry in Bangladesh.
Initial Reliability and Validity for the Critical Hire - Personality Assessment

ABSTRACT The use of personality testing during the hiring process has become a common practice in general business settings. However, their use has been rather non-existent in the field of corrections. This limited use may stem from a lack of awareness about preemployment personality tests in corrections, as well as a lack of measures normed and validated for use with correctional applicants. The present study outlines reliability and validity for the Critical Hire – Personality Assessment, a Five Factor Model based assessment of personality developed for probation, parole, and other correctional officer job applicants. This study provides initial empirical support for the Critical Hire – Personality Assessment’s internal consistency, test-retest reliability, convergent validity, and criterion validity when measuring job performance ratings. Results provide practical application of the Critical Hire – Personality Assessment for correctional agencies as a tool complementing existing hiring practices.
Exploring groundwater microbial communities for natural attenuation potential of micropollutants

Groundwater is a key water resource, with 45.7% of all drinking water globally being extracted from groundwater. Maintaining good groundwater quality is thus crucial to secure drinking water. Micropollutants, such as pesticides, threaten groundwater quality which can be mitigated by biodegradation. Hence, exploring microbial communities in aquifers used for drinking water production is essential for understanding micropollutants biodegradation capacity. This study aimed at understanding the interaction between groundwater geochemistry, pesticide presence, and microbial communities in aquifers used for drinking water production. Two groundwater monitoring wells located in the northeast of The Netherlands and at 500 m distance from each other were sampled in 2014, 2015, 2016 and 2018. In both wells, water was extracted from five discrete depths ranging from 13 to 54 m and used to analyze geochemical parameters, pesticide concentrations and microbial community dynamics using 16S rRNA gene sequencing and qPCR. Groundwater geochemistry was stable throughout the study period and pesticides were heterogeneously distributed at low concentrations (μg/L range). Integration of the groundwater chemical and microbial data showed that geochemical parameters and pesticides exerted selective pressure on microbial communities. Furthermore, microbial communities in both wells showed a more similar composition in the deeper part of the aquifer as compared to shallow sections, suggesting vertical differences in hydrological connection. This study provides initial insights into microbial community composition and distribution in groundwater systems in relation to geochemical parameters. This information can contribute for the implementation of bioremediation technologies that guarantee safe drinking water production from clean aquifers. Importance section Groundwater is an essential source of drinking water. However, its quality is threathened by the presence of micropollutants. Certain microorganisms are capable of degrading micropollutants. However, groundwater is an unexplored environment, where the biodegradation potential of naturally-present microorganisms is unknown. We thus explore how groundwater microbial ecology in shaped by groundwater composition, namely geochemical parameters and micropollutants. This is a first step towards understanding which microbial communities and environmental conditions support natural attenuation of micropollutants. This study thus provides a first step towards developing in situ bioremediation strategies to remove micropollutants from groundwater used for drinking water production.
The rheology of crystallizing basaltic lavas from Nyiragongo and Nyamuragira volcanoes, D.R.C.

Nyiragongo (Democratic Republic of Congo) erupts fluid, fast-moving, foidite lavas. Nearby Nyamuragira frequently erupts less mobile tephrite lavas. Nyamuragira flows rarely threaten urbanized areas, but Nyiragongo flows threaten Goma (pop. ~900,000) and surrounding villages, resulting in fatalities in 1977 and 2002. We report new laboratory measurements of viscosity evolution during cooling and crystallization from both volcanoes by concentric cylinder viscometry. Melt viscosity is ~33 Pa s at the liquidus (~1220°C) for Nyiragongo lavas, similar to Hawaiian basalts. Lavas remain fluid over ~75°C of undercooling (ϕc 10 ms-1 even at subliquidus temperatures on low slopes, posing great risk to Goma.
EASY-M: Evaluation System for Multilingual Summarizers

Automatic text summarization aims at producing a shorter version of a document (or a document set). Evaluation of summarization quality is a challenging task. Because human evaluations are expensive and evaluators often disagree between themselves, many researchers prefer to evaluate their systems automatically, with help of software tools. Such a tool usually requires a point of reference in the form of one or more human-written summaries for each text in the corpus. Then, a system-generated summary is compared to one or more human-written summaries, according to selected metrics. However, a single metric cannot reflect all quality-related aspects of a summary. In this paper we present the EvAluation SYstem for Multilingual Summarization (EASY-M), which enables the evaluation of system-generated summaries in 17 different languages with several quality measures, based on comparison with their human-generated counterparts. The system also provides comparative results with two built-in baselines. The source code and both online and offline versions of EASY-M is freely available for the NLP community.
Managerial Leadership Style and Employee Commitment: Evidence from the Financial Sector

Employees’ poor performance within the banking sector has become evident in recent times, and studies on how leadership styles affect employee commitment in the Ghanaian banking sector is scanty. The purpose of this article is to examine the effect of leadership styles on employee commitment after controlling for demographic and institutional factors. The study also examines whether there is a difference in the leadership style due to the gender of leaders and determines the dominant leadership style among bank managers. A sample of 160 leaders and subordinates were selected from 10 commercial banks. The study employed hierarchical regression as well as independent sample t-test techniques. Financial organizations were chosen because much of the existing studies on leadership styles have focussed on non-financial sectors. The findings of the study indicate that transactional leadership is the most dominant leadership style practised within the banking sector. After controlling for demographic and institutional variables, laissez-faire and transformational leadership behaviours have significant positive effects on employee commitment. Although transactional leadership style is dominant, it contributes only 4.8 per cent to employee commitment as compared to 51 per cent by transformational leadership style in eliciting employee commitment. There is an evidence that, married employees are more likely to be committed employees than the unmarried, but as the employee’s number of children increases, commitment level falls. Although all the three leadership styles have positive effects on employee commitment, transactional and laissez-faire leadership styles are most significant. This is the first study in Ghana to show that there is no significant difference between the sexes when it comes to exhibiting leadership styles in the banking sector. The findings of this study provide useful information for policy-makers to improve employees’ commitment levels and their performance by means of stimulating the right leadership styles in the managers.