Miracle-dz/UniFAR-FTUs huggingface dataset:
Balanced Score Card Implementation, Success Factors and Challenges in Ethiopian Financial Sector: the case of Ethiopian Insurance Corporation and Commercial Bank of Ethiopia

The purpose of the study was to assess the implementation of Balanced Scorecard (BSC) in Ethiopian Financial sector, the case of Ethiopian Insurance Corporation (EIC) and Commercial Bank of Ethiopia (CBE) and thereby to see the adequacy of the procedure followed to implement BSC, BSC implementation success and identify the major challenges encountered during the implementation. To attain these objectives, the study employed Descriptive research design. Accordingly, survey questionnaire and interview questions were administered to a sample of 351 respondents, 322 of them were properly filled and returned. The questionnaires were analysed using frequency distribution, mean scores and mode with the help of Statistical Package for Social Science (SPSS). The major findings of this study indicate the designing phase was done properly in terms of BSC assessment, Strategic plan, Strategic objectives, Strategic map, Performance measures, and Strategic initiatives. But, BSC implementation phases such as automation, cascading and evaluation the sector’s performance is not satisfactory. The following success stories were registered: BSC Make the strategic direction clear to the organization, it helped rewarding practice to be objective, It improve Communication of strategic objective, encourage learning and continuous improvement, The strategic map shows cause and effect relationship among the four perspective and it explicitly show owners of strategic initiatives. The following challenges were faced by the sector: resistance to Change, lack of knowledge on the use and importance of BSC, insufficient participation in the process of the implementation, lack of automating and cascading BSC to individual level, Poor linkage of the Performance appraisal with reward system and recognition, lack of readiness in terms of mentality, skill, competence and negative perception toward BSC. It is recommended that the sector has to increase employee participation, revise the cascaded objectives, automate BSC and organize discussion as well as awareness creation program.
Supplementary Material for “Data-Uncertainty Guided Multi-Phase Learning for Semi-Supervised Object Detection” 1. Visualization of Label Noise Overfitting Problem

We select some images to further explain the label noise overfitting problem. The examples are in Fig. 1. In the first case, the supervised model mislabels the aeroplane as a car, and we notice that the semi-supervised model trained with this pseudo label detects one more car that does not exist. In the second case, the supervised model thinks a part of the iron mesh is a person. This may be an accident mistake. However, in the results from the semi-supervised model, more parts of the iron mesh are detected as persons. The same thing also happens in other cases. The noisy pseudo labels generated by the FS model are regarded as the correct ones by the SSOD model. The SSOD then overfits to these noisy labels, a nature of deep learning neural networks. In the test stage, the SSOD model just tries to intimate the noisy labels used for training, thus generates more similar mistakes. These examples validate the label noise overfitting problem.
Explaining Corona Anxiety Based on Intolerance of Uncertainty, Psychological Hardiness, and Social Support with the Mediation of Rumination

The aim of this study investigation to the mediating function of rumination in the relationship between social support, psychological hardiness, and intolerance of indecision with corona anxiety. The present study was a descriptive correlation with equation structural analysis. The sample of that choose in Ardabil city, in which 300 people participated in the research online and through virtual networks. Questionnaires of rumination, uncertainty intolerance, corona anxiety, social support and psychological hardiness were used to gather data. Analysis were performed using equation structural modeling and SPSS. The results indicate that direction routes of social support, psychological hardiness, and intolerance to corona anxiety were significant (p
The Biology of Rattlesnakes II

—Although Prairie Rattlesnakes (Crotalus v. viridis) are known to make lengthy migrations from communal hibernacula to summer foraging habitat, it is largely unknown how these patterns are influenced by mountainous topography. The objectives of this study were to determine how Prairie Rattlesnake movement patterns in a mountainous landscape were influenced by topography, habitat, and prey activity. We used radio telemetry to monitor the movements of 16 male and four nonpregnant female Prairie Rattlesnakes in the Frank Church Wilderness in central Idaho during the summer of 2008. We used GIS to test for selection for topographic features and habitats at multiple spatial scales and compared small mammal activity among habitats. Rattlesnakes moved across a wide range of topographic features including ridges, steep slopes, rivers, and creeks. Rattlesnakes appeared somewhat restricted by topography, particularly elevation, within three kilometers of their hibernacula while topography appeared to have little restrictive effect within their home ranges. Although rattlesnakes showed the greatest selection for riparian habitats at all spatial scales, we failed to detect a significant difference in small mammal activity among habitats. Our results indicate that topography does influence rattlesnake movement and that these effects vary by spatial scale. Although habitat and prey abundance likely influence rattlesnake movements in this system, topography may impose the greatest constraints on rattlesnake movements. Bauder, J. M. , H. Akenson, and C. R. Peterson. 2017. Factors Influencing the Movement Patterns of Prairie Rattlesnakes (Crotalus v. viridis) across a Mountainous Landscape in a Designated Wilderness Area. Pp. 154–167 in Dreslik, M. J., W. K. Hayes, S. J. Beaupre, and S. P. Mackessy (eds.), The Biology of Rattlesnakes II. ECO Herpetological Publishing and Distribution, Rodeo, New Mexico. 2 Correspondence e-mail: javanvonherp@gmail.com 3 Present address: Department of Environmental Conservation, University of Massachusetts, Amherst, Massachusetts, USA
A Quantitative Analysis of Point Clouds from Automotive Lidars Exposed to Artificial Rain and Fog

Light Detection And Ranging sensors (lidar) are key to autonomous driving, but their data is severely impacted by weather events (rain, fog, snow). To increase the safety and availability of self-driving vehicles, the analysis of the phenomena consequences at stake is necessary. This paper presents experiments performed in a climatic chamber with lidars of different technologies (spinning, Risley prisms, micro-motion and MEMS) that are compared in various artificial rain and fog conditions. A specific target with calibrated reflectance is used to make a first quantitative analysis. We observe different results depending on the sensors, valuable multi-echo information, and unexpected behaviors in the analysis with artificial rain are seen where higher rain rates do not necessarily mean higher degradations on lidar data.
Deep Fuzzy Ontology for Travel User Interest Discovery Based on Visual Shared Data in Social Networks

: In the present research, a novel system for travel interest discovery from visual shared data through social networks is discussed. The proposed Deep Fuzzy System is based on neural features extracted from well-known CNN architecture. GoogleNet to learn the inference system based on fuzzy ontology. Deep fuzzy ontology is a new framework that includes essentially two phases. The first consists of image conceptualization by existing objects found in shared images. In the second phase, we use the concepts issued from ImageNet classes to design our Tree-based ontology for travel interest discovery.To evaluate our deep fuzzy CNN ontology system, we construct a new database of visual shared data on Facebook coming from Sudanese citizens. Our proposed system has shown a very impressive result for travel Sudanese user’s interest.
The Effect of Unit-of-Translation on Iranian Upper-Intermediate EFL Learners’ Achievement in Bizarre News Translation

The current study was an attempt to investigate whether the Unit-ofTranslation has any effect on Iranian upper-intermediate EFL learners’ achievement in Bizarre News translation. In addition, it investigated whether there was any difference across gender regarding the effect of Unit-ofTranslation on Iranian upper-intermediate EFL learners’ achievement in Bizarre News translation. To this end, 45 out of 88 EFL learners from three upper-intermediate language learners at two Language Institutes in Boumehen, Iran were selected based on Oxford Placement Test. Then, they were divided randomly into three groups; one control group (N=15) and two experimental groups (N=30). The first experimental group was male. The second experimental was female, and the third group was administered as the control group. The experimental groups received the instruction for unit of translation. The instruction was given in five sequential sessions about 50 minutes. In contrast, the control group received no special instruction. At the end of the course, a post-test was administered. To analyze the data, oneway ANOVA and independent samples t-test were run. The findings revealed that the Unit-of-Translation had a positively significant effect on Iranian upper-intermediate EFL learners’ achievement in Bizarre News translation. The results also indicated that concerning the effect of Unit-ofTranslation on Iranian male upper-intermediate EFL learners had a better achievement in Bizarre News translation compared to their counterparts in the female group.
Cause-related marketing

PurposeCause-related marketing (CRM) focuses on the use of marketing tools to publicize a firm’s corporate social responsibility (CSR) activities. Drawing on legitimacy theory, the purpose of this paper is to investigate the impact of CRM-led CSR in international business-to-business (B2B) markets. In particular, the authors examine the relationship between supplier CRM-led philanthropic CSR reputation and foreign customer business engagement in an international B2B setting. The authors also test how the foreign customer’s host-country sustainable development level moderates this relationship.Design/methodology/approachThe authors collect and analyze dyadic data from multiple sources including: dyadic data from a supplier and its 90 foreign customers; the supplier’s internal company records; and publically available data.FindingsThe authors find that supplier CRM-led philanthropic CSR reputation positively affects foreign customer business engagement. Furthermore, the authors find that this positive relationship is stronger when host-country environments are characterized by achieving higher level of environmental well-being development. In contrast, this positive relationship is weaker when the foreign customer host-country environment is characterized by achieving higher level of economic well-being development.Originality/valueThe authors examine that impacts of CRM-led CSR in international B2B markets and differentiate the contingent roles of foreign customer host-country sustainable development in moderating such impacts.
Association Between Blood Pressure Control and Arterial Stiffness in Middle-Aged and Elderly Chinese Patients with Hypertension

Background The severity of arterial stiffness can be evaluated by pulse wave velocity (PWV). This study investigated the association between blood pressure (BP) control and arterial stiffness in middle-aged and elderly Chinese patients with hypertension. Material/Methods Three hundred and twelve hypertensive patients were divided according to whether their hypertension was well-controlled or uncontrolled and stratified according to age. Arterial stiffness was evaluated by brachial-ankle pulse wave velocity (baPWV). The effect of BP control on arterial stiffness and its severity was assessed by multivariate linear and logistic regression analyses. Results Moderate and severe arterial stiffness was detected significantly more often in patients with uncontrolled hypertension than in those with well-controlled hypertension, regardless of age. BaPWV increased by 8.467 cm/s in the study population overall for every 1-mmHg increment in systolic BP and by 8.584, 8.616, and 8.199 cm/s, respectively, in patients aged 45–65, 65–80, and ≥80 years. Regardless of age, the risk of arterial stiffness was 5.93 times higher (95% confidence interval 2.78–12.64) and the risk of a one-grade increase in the severity of arterial stiffness was 4.01 times higher (95% confidence interval 2.51–6.42) in patients with uncontrolled hypertension than in those with well-controlled hypertension. Conclusions This study found a positive relationship between baPWV and BP and identified uncontrolled BP as a risk factor for arterial stiffness and its severity. Management of BP within a reasonable range may help to ameliorate arterial stiffness.
Attention Based LSTM with Multi Tasks Learning for Predictive Process Monitoring

Today, in the artificial intelligence research field, Deep Learning (DL) is one of the fastest-growing techniques because of the power of learning features, that gives a higher level of abstraction of the raw attributes; and related research in Recurrent Neural Networks (RNN) and Long Short-Term Memory Networks (LSTM) have shown exemplary results in neural machine translation, neural image caption generation, NLP and so on. For our research, in order to detect potential problems and to facilitate proactive management, we focus on predictive process monitoring (PPM) as domain area, by predicting business behaviour from historical event logs. Recent research works, LSTM networks have gained attention in PPM and have been proved that they can highly improve prediction accuracy in PPM. According to the literature, we have learned that PPM resembles to an early sequence classification problem in NLP. And, recent trends in DL based NLP, attention mechanism is mostly embedded in neural networks. Inspired by these results, this paper proposes to firstly use Attention Based LSTM with Multi Tasks Learning for PPM.
Abundance fluctuation of Spirura rytipleurites seurati Chabaud, 1954 (Nematoda Spiruridae) parasite of Desert Hedgehog Hemiechinus aethiopicus (Ehrenberg, 1833) (Insectivora Erinaceidae) in the Region of Merigha (Laghouat, Algeria)

Received 20.12. 2020; accepted 25.02. 2021; published online 30.03. 2021 The study has been undertaken for three consecutive years on the diet of the desert hedgehog Hemiechinus aethiopicus (Ehrenberg, 1833) (Insectivora Erinaceidae) in Merigha (Laghouat). It highlighted a great abundance of a parasitic nematode of the digestive tube: Spirura rytipleurites seurati Chabaud, 1954. The helminths are sparsely abundant in the droppings in April; while their numbers increase until June-July, then decrease drastically in August. They increase again and reach a second abundance peak in October. The droppings infestation rate varies in the same way, where these variations are interpreted in relation to the parasite cycle and to the variations of the hedgehog diet’s composition.
The Influence of Cigarette Moisture to the Chemistry of Particulate Phase Smoke of a Common Commercial Cigarette

Abstract This study presents the results on the influence of cigarette moisture content to the chemical composition of particulate phase smoke. Seventy-five selected compounds were monitored for the comparison of particulate phase smoke of a commercial full-flavored (FF) cigarette with three different moisture contents at 7.8%, 14.5% and 20.4%, respectively. It was demonstrated that the smoke of a dry cigarette is richer in lower molecular mass compounds than a regular cigarette. On the other hand, the smoke of a moist cigarette is richer in higher molecular mass compounds than a regular cigarette. To maximize the influence of cigarette moisture to the chemical composition, a separate set of measurements were done using only the first three puffs of smoke. The accumulation of moisture in the tobacco column of a burning cigarette may influence the smoke composition, as generated during burning. The differences between dry, regular and moist cigarettes were more obvious for the first three puffs.
Exploring Multi-label Classi(cid:12)cation Using Text Graph Convolutional Networks on the NTCIR-13 MedWeb Dataset

The NTCIR-13 Medical Natural Language Processing for Web Document (MedWeb) task requires participant systems to perform multi-label text classi(cid:12)cation, where labels representing eight diﬀerent diseases or symptoms are assigned to each pseudo-tweet. While a recent study showed that a method based on Text Graph Convolutional Networks outperforms previous approaches in text classi(cid:12)cation, its performance on multi-label text classi(cid:12)cation remains unclear. Hence, in this study, we construct a model based on Text Graph Convolutional Networks (Text GCN) and evaluate its performance on multi-label classi(cid:12)cation. Our experimental results show that Text GCN could not outperform the baseline system on the NTCIR-13 MedWeb task.
Higher risk of hypertensive disorders of pregnancy and preeclampsia in pregnancies following frozen embryo transfer: a systematic review and meta-analysis

Background and purpose: Does frozen-thawed embryo transfer (FET), compared with fresh embryo transfer (ET), increase the risk of hypertensive disorders of pregnancy (HDP) in women who become pregnant through in vitro fertilization? Methods: Through a systematic review and meta-analysis the authors assessed the risk of HDP following FET versus fresh ET. An electronic literature search of the PubMed, Embase and Cochrane databases was performed. The primary outcome was HDP. Other aspects analyzed included preeclampsia and gestational hypertension. Results: Five studies were included. FET was found to be associated with a higher risk of HDP (RR 1.71; 95% CI 1.22, 2.39) and of preeclampsia (RR 1.92; 95% CI 1.28, 2.89). A subgroup analysis indicated that in PCOS/hyper-responder patients, FET increased the risk of HDP (RR 1.98; 95% CI 1.11–3.51) and preeclampsia (RR 2.86; 95% CI 1.54–5.32). However, non-PCOS/normo-responders showed no significant difference in HDP (RR 1.44; 95% CI 0.97–2.14). No statistical differences in the risk of gestational hypertension were noted. Conclusions: Compared with fresh ET, FET resulted in a higher risk of HDP only in PCOS/hyper-responder patients, and a higher risk of preeclampsia both in non-PCOS/normo-responders and PCOS/hyper-responder patients. Unknown mechanisms related to altered hormonal concentrations and their influence on the placental development of pregnancies after artificial FET cycles could explain these differences.
Immunomodulatory Effects Of Mesenchymal Stem Cells Derived From Bone Marrow, Adipose Tissue, And Umbilical Cord Tissue In Rheumatoid Arthritis

Rheumatoid Arthritis (RA) is an autoimmune disease that targets the synovial joints of the body that holds a massive burden on healthcare worldwide. The progression of the disease is mediated in congruence of the adaptive immune cells (Tand Bcells) and synovial fibroblast activation. In the last decade, standard treatment options for RA have demonstrated significant improvements but often fail to deliver a long-term therapeutic outcome and, in some cases, cause adverse effects leading to treatment termination. Treatment with mesenchymal stem cells (MSCs) has been recently studied in RA because of the unique immunomodulatory and anti-inflammatory capacities of the MSCs needed to combat RA. Pre-clinical and clinical trials have demonstrated that MSCs derived from adipose tissue, bone marrow, and umbilical cord tissue possess immunomodulatory capabilities that alter the dysfunctional immune cells involved with the pathogenesis of autoimmune diseases including RA. Specifically, these trials have demonstrated the immunomodulation ability of MSCs on the proliferation of memory T cells as well as their ability to migrate to inflamed tissue associated with synovitis in RA.
Thermodynamics of mixing in an isostructural solid solution: Simulation methodologies and application to the rutile-cassiterite system

Abstract The accuracies of two different approaches to model thermodynamic mixing properties of solid solutions are explored using the rutile-cassiterite solid solution as an example. Both methods employ an expansion of the configurational enthalpy in terms of pairwise interactions energies. In the first method the partition function is directly computed from the excess energies of all Ti/Sn configurations within a 2 × 2 × 4 supercell. In the second method the free energy of mixing is calculated by a thermodynamic integration of the thermally averaged enthalpies computed with the Monte Carlo method using an 8 × 12 × 16 supercell. The phase relations derived from Monte Carlo simulations agree well with the available experimental data, under the condition that the free energy is corrected for the effect of the excess vibrational entropy. The direct calculation of the partition function provides reasonable phase relations only when the configurational entropy is corrected to be consistent with the ideal mixing in the high-temperature limit. Advantages and drawbacks of the both approaches are discussed. The findings are generally applicable to models of isostructural solid solutions.
Likes are not Likes A Crowdworking Platform Analysis

Many Internet users rely on Online Social Networks (OSNs) in their daily lives to read news, ﬁnd local restaurant recommendations, or learn about products. But lately OSNs have come under scrutiny for allowing misinformation to spread. Compared to the widely discussed problems of fake news and bots, inauthentic likes by real users have not seen much attention in the research community. They have their origin in real accounts that offer likes in exchange for micro-payments through crowd-working platforms. Our analysis of these fake likes from real users is based on almost 90,000 manipulation campaigns managed by a crowd-working company in Germany containing a diverse set ranging from politics to products and services. An additional study on ten users of these crowd-working platforms shows that they merely earn some pocket money and, although they do not like things they politically oppose, do not generally feel responsible for manipulations of recommendations. Our analysis shows that likes should not be trusted and the detection of fake accounts is not sufﬁcient to prevent fake likes in general.
Chapter 10. Forcing prediction increases priming and adaptation in second language production

This paper presents a priming experiment with Korean learners of English designed to test the hypothesis that engagement in prediction and the consequent computation of prediction error will lead to increased priming and adaptation. Participants in the guessing-game condition, who had to predict a virtual partner's description of prime pictures, showed marginally greater immediate priming and significantly greater adaptation in terms of change from baseline to post-test than those in a standard repetition priming condition, consistent with error-based learning accounts of structural priming. Effects were largest for learners in the middle of the proficiency range. Findings from this study suggest that priming best facilitates L2 learning when learners are engaged in the proactive creation of expectations about upcoming information. Forcing prediction increases priming