Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Assessed Competence of Experienced Expatriate Nurses in a Rural and Remote Setting

We aimed to measure the self-assessed level of competence among nurses working in the public hospitals of Al-Gharbia Region, a remote rural region of United Arab Emirates, and to explore the factors associated with the nurses’ self-perceived competency. The Nurse Competency Scale, which measures the self-assessed level of competency of nurses, has been validated in a variety of clinical settings, in facilities of various sizes, and in small and large cohorts. However, its application among an expatriate nursing workforce working in small hospitals and health facilities in remote and rural areas has not been examined. We used the Nurse Competency Scale to survey the nursing workforce in Al-Gharbia’s public hospitals in United Arab Emirates. All 435 practicing registered nurses with more than 3 months clinical experience in the network were invited to participate. Data were collected electronically and analyzed by international collaborators. Statistical analysis included analysis of variance, Kruskal–Wallis, multiple linear regression, χ2 test of independence, and Cronbach’s α. Totally, 189 responses were analyzed (43.4% response rate). Overall self-assessed levels of competence were uniformly “very good” across all competence categories. The overall score (84.3) was higher than those found in most other studies. Frequency of use was the most outstanding variable influencing self-assessed competence. Total years of experience were the next significant variable. Some items of the scale were not yet applicable to activities in the region, particularly those relating to supervision of students. The high scores achieved by expatriate nurses in the small hospitals of Al-Gharbia reflect well on the rigor of the recruitment process, ongoing cross-training and functional competency assessment. Policies and practices aimed at recruiting experienced expatriate nurses and providing opportunities to use competencies continue to be critical in providing a quality nursing service in a rural and remote region.
GAN Generate Adversarial Examples to Fool Deep Networks

State-of-the-art deep neural networks have achieved impressive results on many image classi-ﬁcation tasks. However, these neural networks consistently misclassify adversarial examples that humans can clarify correctly classiﬁed, the adversarial examples result in the model outputting an incorrect answer with high conﬁdence. Therefore, a black box attack method for eﬃciently generating a large number of adversarial samples using GAN is proposed. These attack samples are very similar to real images and can fool deep neural networks. Extensive experimental results show that our approach perform well in the task of generate samples of adversarial attacks.
Medicolegal considerations on the concept of inability according to the law no 222/84 (INPS) and the law no 118/71 (Civil Invalidity): similarities, differences and operational practices in the medicolegal evaluation of oncological diseases

Introduction: the law 222/1984, on which the INPS (Italian National Welfare Institute) social security concept is based and which sets the unfit-to-work person as the one who “is in the total and permanent inability to perform any work activity”, is compared with the similar concept in the Civil Invalidity, which sets the unfit-to-work person as the one who has lost the “general working
IaaS Reservation Optimization for Multi-QoS Level based SaaS Provisioning

We design an evolutionary computation based solution for SaaS providers to optimize the cost of reserved IaaS instance subscription. The services provisioned by SaaS providers have multiple options of Quality of Service (QoS) levels. A Bayesian network model is designed to map between the QoS levels of SaaS instances and their actual resource consumption on IaaS instances. A genetic algorithm with heuristics is designed to optimize the reserved IaaS instance subscription. The proposed solution is evaluated via a set of simulated experiments.
Masquerade Attacks Against Security Software Exclusion Lists

Security software, commonly known as Antivirus, has evolved from simple virus scanners to become multi-functional security suites. To combat ever-growing malware threats, modern security software utilizes both static and dynamic analysis to assess malware threats, inevitably leading to occasional false positive and false negative reports. To mitigate this, existing state-of-the-art security software oﬀers the feature of Exclusion Lists to allow users to exclude speciﬁed ﬁles and folders from being scanned or monitored. Through rigorous evaluation, however, we found that some of such products stored their Exclusion Lists as unencrypted cleartexts either in known or predictable locations. In this paper we empirically demonstrate how easy it is to exploit the Exclusion Lists by launching masquerade attacks. We argue that the Exclusion Lists should be better implemented such as using application whitelisting, the contents of the lists to be better safeguarded, and only be readable by authorized entities within a strong access control scheme.
Exploring the Evolution of Science with Pivot Topic Graphs

In this article we propose a data model for the visualisation and exploration of topic evolution networks representing the research progress in scientific document archives. Our model is independent of a particular topic extraction and alignment method and proposes a set of semantic and structural metrics for characterizing and filtering meaningful topic evolution patterns. These metrics are particularly useful for the visualization and the exploration of large topic evolution graphs. We also present a first implementation of our model on top of Apache Spark and experimental results obtained for three well-known document archives.
Validation of Cariogram as a Tool for Caries Risk Prediction Among 12-Year-Old Institutionalized Children - A Longitudinal Follow-up Study

Aim: To evaluate cariogram as a tool for caries risk prediction among 12- year-old institutionalized children and to validate it against the new increment of caries lesions. Materials and Methods: A longitudinal follow-up study was conducted among 36 institutionalized children. Baseline data were collected in the month of January 2012. Children were individually interviewed to record the nonclinical information necessary to complete the cariogram. Clinical information for the assessment of visible plaque was recorded using the Silness and Loe plaque index and evidence of decalcification and caries was recorded using ICDAS criteria. The children underwent the follow-up examination in July 2013 to determine the new increment of dental caries. Results: 52.77% of the participants were classified as low risk and very low risk for future development of dental caries, remainder of the subjects were fairly equally distributed in the medium (19.44%) and high (19.44%) risk groups. Very few (8.33%) participants were classified under very high risk group. Highest odds ratio for disease indicators was 4.20 for past caries experience. Highest odds ratio for pathological factors was 7.15 and 5.54 for the association of M streptococci and visible heavy plaque respectively. Mean caries increment noted from the time of the initial examination to the follow-up was 0.55 ± 0.80 for the total sample. A trend could be noted in which caries increment increased with elevated risk classification, mean caries increment was 1.66 ± 0.57for very high risk, 0.85 ± 0.89 for high risk, 0.71 ± 0.75 for medium risk and 0.27 ± 0.64 for low risk. Sensitivity for CAMBRA was found to be 47.62% with a specificity of 80%, and the area under the ROC curve was found to be 0.638. Conclusion: Cariogram was valid and highly predictive in determining the caries risk among institutionalised children.
A study on prevalence of metabolic syndrome in general population in Western Uttar Pradesh, India

Background: A global transition in the disease pattern has been observed, where the relative impact of infectious disease is decreasing while chronic disease like cardiovascular disease and diabetes are increasingly dominating the disease pattern. Metabolic syndrome (MetS) is a complex web of metabolic factors that are associated with a 2-fold increased risk of CVD and 5-fold risk of diabetes. Methods: A total of 350 patients were included and a cross sectional study was conducted to identify metabolic syndrome prevalence and to evaluate risk factor for development of metabolic syndrome. Results: 48% of participants were male and 52% were female our results showed a BMI of 22.11±3.57 in male and 22.16±2.82 in females. The overall prevalence of overweight was 31%. This study also showed significantly higher rate of metabolic syndrome in older age group i.e. 9.38% in age group of 30-39 years and 26.98% in 60-70 age group. Proportionally more subjects with MetS (74%) have sedentary life style as compared to those without MetS (54%). Conclusions: The prevalence of Metabolic syndrome varies among ethnic groups. Indians are at high risk for ASCVD and their predisposition. The high prevalence of overweight and obesity was one of the major driving force in the development of MetS.
SeqDLF: Deep Local Feature-Based Image Sequence Representation for Visual Loop Closure Detection

In visual simultaneous localization and mapping (SLAM), loop closure detection is used to ﬁnd the global topology among the different locations for eliminating accumulated odometry error and relocalization. Traditional methods treat the loop closure detection as image retrieval problem. However, a single image based method cannot perform well when two places have similar appearances, which is known as the perceptual aliasing problem. In this paper, the loop closure detection is treated as sequence matching problem, which is solved by the proposed deep local features-based image sequence representation (seqDLF). For each image sequence, local features are extracted by a Convolutional Neural Network (CNN) and further encoded into a single vector by Vector Locally Aggregated Descriptors (VLAD) or spatiotemporal VLAD (ST-VLAD). The proposed seqDLF-based method enables to match the current image sequence (current observation) with the historic image sequence, which is more robust to the variations in appearance between images. The experimental results show that the performance of the proposed seqDLF-based loop closure detection is competitive to that of the state-of-art RTAB-MAP method.
Effect of Static Magnetic Fields on Proliferation and Apoptosis of Gallbladder Cancer Cells: An in vitro and in vivo study

Objectives: The knowledge on how static magnetic fields (SMF) of magnetic implants affect living cells and tissues is limited while these magnetic devices are more and more frequently adopted in certain surgical approaches. Methods: In this study, we exposed cultures of human gallbladder cancer cells to SMF continuously for up to 7 days, trying to simulate the exposure pattern of surgical magnetic implants, and implanted magnetic devices into tumor-bearing nude mice for 1 month, then evaluated the effect on proliferation and apoptosis of cancer cells and tissues. Results: It showed that after SMF exposure, whereas in vitro study showed decreased cell proliferation and increased apoptosis of the gallbladder cancer cells, in vivo study showed no significant differences both on proliferation and on apoptosis. Conclusions: Our findings indicate that with current magnetic biliary anastomosis devices, the SMF from magnetic implants shows little effects on proliferative and apoptotic activities of gallbladder cancer cells in vivo, while there are still possibilities that long-term continuous SMF exposure from surgical magnetic implants may interact with living cells, probably in a feeble manner.
Exploring the Auto Model Competition Patterns in China's Auto Market based on Complex Networks Theory

Understanding the competition pattern of auto models is critical for stakeholders including automakers and dealers. However, the traditional methods mainly rely on the experience and analytical dimensions of the analyst, which lack reliable methodology and ignore the value of user behavior. In this paper, we propose a novel method based on complex network theory, construct an auto model competition network with users’ sales leads, and analyze the static characteristics of the network. Besides, by us-ing different community detection algorithms and constructing predictive models, we discovered that there are six major communities in the network, and that price, popularity, model level, as well as model asset ownership, are the main factors affecting community division.
Air pollution: A new challenge for anaesthesiologists!

1. Population Based Cancer Registry. National Cancer Registry Programme (NCRP), Indian Council of Medical Research (ICMR). Available from: http://www.ncrpindia. org. [Last accessed on 2019 Nov 12]. 2. Fecho K, Miller N, Merritt S, KlauberDemore N, Hultman C, Blau WS. Acute and persistent postoperative pain after breast surgery. Pain Med 2009;10:708-15. 3. Stollings LM, Jia LJ, Tang P, Dou H, Lu B, Xu Y, et al. Immune modulation by volatile anesthetics. Anesthesiology 2016;125:399-411. 4. Singh S, Chowdhary NK. Erector spinae plane block an effective block for post-operative analgesia in modified radical mastectomy. Indian J Anaesth 2018;62:142-50. 5. Khemka R, Chakrborty A, Agrawal S, Ahmed R. Is COMBIPECS the answer to perioperative analgesia for breast surgery? A double blinded randomized controlled trial. Indian J Anaesth 2019;63:530-6. 6. Nagy MT, Macfarlane RJ, Khan Y, Waseem M. The frozen shoulder: Myths and realities. Open Orthop J 2013;7:352-5. 7. Singh S, Kumar G, Akhileshwar. Ultrasound-guided erector spinae plane block for postoperative analgesia in modified radical mastectomy: A randomized control study. Indian J Anaesth 2019;63:200-4. 8. Gurkan Y, Aksu C, Kuş A, Yörükoğlu UH, Kılıç CT. Ultrasound guided erector spinae plane block reduces postoperative opioid consumption following breast surgery: A randomized controlled study. J Clin Anesth 2018;50:65-8. 9. Kimachi PP, Martins EG, Peng P, Forero M. The erector spinae plane block provides complete surgical anesthesia in breast surgery: A case report. A A Pract 2018;11:186-8. 10. Nair AS, Seelam S, Naik V, Rayani BK. Opioid-free mastectomy in combination with ultrasound-guided erector spinae block: A series of five cases. Indian J Anaesth 2018;62:632-4. 11. Adhikary SD, Bernard S, Lopez H, Chin KJ. Erector spinae plane block versus retrolaminar block: A Magnetic resonance imaging and anatomical study. Reg Anesth Pain Med 2018;43:756-62. 12. Hannig KE, Jessen C, Soni UK, Borglum J, Bendtsen TF. Erector spinae plane block for elective laparoscopic cholecystectomy in the ambulatory surgical setting. Case Rep Anesthesiol 2018;2018:5492527. 13. Aksu C, Gurkan Y. Ultrasound-guided bilateral erector spinae block could provide effective postoperative analgesia in laparoscopic cholecystectomy in paediatric patients. Anesth Crit Care Pain Med 2019;38:87-8. 14. Fujii Y. Prophylaxis of postoperative nausea and vomiting in patients scheduled for breast surgery. Clin Drug Investig 2006;26:427-37.
Dynamic Wi-Fi RSSI normalization in unmapped locations

With the growing availability of open access WLAN networks, we assisted to the increase of marketing services that are based on the data collected from the WLAN access points. The identification of visitors of a commercial venue using WLAN data is one of the issues to create successful marketing products. One of the ways to separate visitors is to analyse the RSSI of the mobile devices signals coming to various access points at the venue. Nevertheless, the indoor signal distortion makes RSSI based methods unreliable. Inthiswork we propose the algorithm for the WLAN based RSSI normalization in uncontrolled environments. Our approach is based on the two steps, where at first based on the collected data we detect the devices whose RSSI can be taken as a basic one. At the second step the algorithm allows based on the previously detected basic RSSI to normalize the received signal from mobile devices. We provide the analysis of a real dataset of WLAN probes collected in several real commercial venues in Italy.
Amlodipine besylate impairs the morphology of bone marrow in adult male wistar rats

Amlodipine is a long-acting calcium channel blocker used in the treatment of hypertension and angina. In adult man, the treatment regimen is 5 or 10 mg daily. This study evaluated the effects of prolonged oral administration of Amlodipine Besylate on the morphology of bone marrow in adult male Wistar rats. Sixteen rats (140 - 190 g) comprising of four groups were employed in the study. Rats of Control Group I received physiological saline orally while rats of Experimental Groups II - IV received oral administrations of 5, 10 and 15 mg/kg bodyweight of Amlodipine Besylate respectively for nine weeks. Histo-pathological examinations of the bone marrow showed normal cytoarchitecture of erythrocytes and leukocytes in rats of Control Group I. However, dose-dependent degeneration and lyses of erythrocytes and leukocytes were observed in amlodipine-treated rats. In conclusion, impaired morphology of the bone marrow were observed in amlodipine-treated adult male Wistar rats Key words : Amlodipine Besylate, bone marrow, morphology, rats.
Uncovering vessel movement patterns from AIS data with graph evolution analysis

The availability of the large amount of Automatic Identification System (AIS) data has fostered many studies on maritime vessel traffic during the recent years, often representing vessels and ports relationships as graphs. Although the continuous research effort, only a few works explicitly study the evolution of such graphs and often consider coarse-grained time intervals. In this context, our ultimate goal is to fill this gap by providing a systematic study in the graph evolution by considering voyages over time. a three years of AIS data from the coastal waters of United States. By mining the arrivals and departures of vessels from ports, we build a graph consisting of vessel voyages between ports. We then provide a study on topological features calculated from such graphs with a strong focus on their temporal evolution. Finally, we discuss the main limitations of our approach and the future perspectives that will spawn from this work.
Chains of Truncated Beta Distributions and Benford’s Law

Abstract It was proved by Jang et al. that various chains of one-parameter distributions converge to Benford’s law. We study chains of truncated distributions and propose another approach, using a recent convergence result of the Lerch transcendent function, to proving that they converge to Benford’s law for initial Beta distributions with parameters α and 1.
A 79 dBΩ 1.2 GHz Low-Noise Single-Ended CMOS Transimpedance Amplifier for High-Performance OTDR Applications

Abstract The work reports on the design and performance of a low-noise low-cost CMOS transimpedance amplifier (TIA). The proposed circuit shall be employed in optical time-domain reflectometers and is implemented using an affordable 0.18 µm 1.8 V CMOS process. The approach preserves the benefits of a classical feedback structure while addressing the noise problem of conventional feed-forward and resistive feedback architectures via the usage of noise-efficient capacitive feedback. Circuit-level modifications are proposed to mitigate the voltage headroom and DC current issues. The suggested design achieves a total gain of 82 dBΩ (79 dBΩ after the output buffer) within the bandwidth of 1.2 GHz while operating with a total input capacitance of 0.7 pF. The simulated average input-referred noise current density is below 1.8 pA/sqrt(Hz) with the power consumption of the complete amplifier including the output buffer being 21 mW.
A Practical Statistical Approach to the Reconstruction Problem Using a Single Slice Rebinning Method

Abstract The paper presented here describes a new practical approach to the reconstruction problem applied to 3D spiral x-ray tomography. The concept we propose is based on a continuous-to-continuous data model, and the reconstruction problem is formulated as a shift invariant system. This original reconstruction method is formulated taking into consideration the statistical properties of signals obtained by the 3D geometry of a CT scanner. It belongs to the class of nutating reconstruction methods and is based on the advanced single slice rebinning (ASSR) methodology. The concept shown here significantly improves the quality of the images obtained after reconstruction and decreases the complexity of the reconstruction problem in comparison with other approaches. Computer simulations have been performed, which prove that the reconstruction algorithm described here does indeed significantly outperforms conventional analytical methods in the quality of the images obtained.
An Investigation of Chinese Undergraduates’ Ability to Translate Chinese Cultural Items into English and Predictors of Such Ability

Abstract College English teaching in China has long focused on importing cultures of English countries while neglecting to enhance students’ English competence in home culture. The present research aims to investigate Chinese non-English major undergraduates’ competence in translating Chinese cultural items into English and the significant predictors of such competence. With a test and a questionnaire as research instruments, this study was conducted to assess 82 undergraduates’ ability to translate three different levels of Chinese culture-specific items into English and explored the factors which might have affected the students’ home culture translation ability. The results show that the participants did well in translating the surface layer cultural items, but their performance in sub-surface and deep layer culture translation tasks was far from being satisfactory. It was also found that students had positive attitudes towards Chinese culture and were willing to learn to express Chinese culture in English, but their English learning motivation in general was not strong enough, and they were not given much input on Chinese culture in their English class. Students’ Chinese cultural knowledge and their awareness of the importance of learning Chinese culture in English were found to be the two significant factors that can predict their performance in the translation tasks. These findings have implications for the teaching of culture and cross-cultural communications in EFL classes.
Effects of dietary vegetable oils on growth, lipogenic enzyme activities and tissue fatty acid composition of Heterobranchus longifilis

Abstract Feasibility of total replacement of fish oil (FO) with vegetable oils (palm oil (PO) and soybean oil (SO)) in practical diet for Heterobranchus longifilis fingerlings was evaluated. Six iso-nitrogenous and iso-caloric diets were prepared. Control diet (A) used FO as the lipid source, diets B–F contained various blends of palm and soybean oils. Fish were fed to apparent satiation twice daily for twelve weeks. No significant (P > 0.05) differences were observed for feed intake, weight gain, feed conversion ratio or specific growth rates among dietary treatments. Activities of glucose-6-phospate dehydrogenase (G6PDH) and malic enzyme (ME) were significantly (P < 0.05) higher in fish fed diet C (1.5 % PO). Generally, hepatic G6PDH activity was about 3-4 times higher than ME activity in fish fed the experimental diets. The tissue fatty acid (FA) profiles in fillet and liver reflected the dietary FA compositions. However, the concentrations of eicosapentaenoic acid and docosahexaenoic acid were higher in fish tissue (fillet and liver) than in the diets. Results from the present study indicate that replacement of fish oil with vegetable oil resulted in satisfactory growth and body composition characteristics in Heterobranchus longifilis. Compared with soybean oil, palm oil is relatively cheap and readily available; therefore, diet F (6 % PO) is recommended for use in H. longifilis diet.