Miracle-dz/UniFAR-FTUs huggingface dataset:
A comparative study of knowledge sharing pattern among the undergraduate and postgraduate students of private universities in Bangladesh

Purpose – The aim of this inquiry is to uncover the pattern of knowledge-sharing behaviour among the undergraduate and postgraduate students of private universities in Bangladesh. Design/methodology/approach – This inquiry studied the knowledge-sharing pattern of undergraduate and graduate students by utilising a questionnaire-based open-ended survey from several private universities in Dhaka, Bangladesh. Apart from the descriptive statistics, the research used t-test to further explain the data. Findings – This research focussed on seven areas of knowledge-sharing pattern. The data collected from 350 respondents from different private universities suggest that there are significant differences in the knowledge-sharing pattern between undergraduate and graduate students. Overall, this research documents that the postgraduate students have shown higher perceived attitudes towards knowledge sharing, compared to undergraduate students. Research limitations/implications – This research applied a descriptive s.
Sleep Status and the Risk Factor of Drowsy-Related Accidents in Commercial Motor Vehicle Drivers

Background and ObjectiveaaThe purpose of this study was to describe prevalence of sleep problems including obstructive sleep apnea (OSA), insomnia, and sleep insufficiency in commercial motor vehicle (CMV) drivers, and to quantify risk of drowsy-related accidents in CMV drivers. MethodsaaCMV drivers were invited to participate in this study. Participants were asked to complete a questionnaire about sleep habits, sleep disorders, work environments, and experience of drowsy-related accidents. A home sleep test (Watch-PAT 200) was also undertaken to detect OSA. resultsaaAmong 110 participants, 89 with eligible data of questionnaires and home sleep tests were included in the analysis. 91.0% of participants had OSA with peripheral arterial tonometry respiratory distress index (pRDI) ≥ 5/h and 23.6% had moderate to severe OSA with pRDI ≥ 15/h. 55.1% perceived that their sleep is insufficient. 52.3% of participants experienced drowsy driving. Drowsy driving-related motor vehicle crashes (MVCs) and near miss MVCs were reported by 9.6% and 37.9% of participants, respectively. Multiple regression analysis showed that increased risk of drowsy driving was associated with perceived sleep insufficiency [odds ratio (OR) = 3.48, 95% confidence interval (CI) 1.26–9.64]. Increased risk of drowsy driving-related near miss MVC was associated with perceived sleep insufficiency (OR = 3.06, 95% CI 1.11–8.44) and continuous driving for more than 4 hours (OR = 3.10, 95% CI 1.00–9.58). ConclusionsaaOSA and perceived sleep insufficiency are prevalent in CMV drivers. Perceived sleep insufficiency and longer continuous driving hours increased risk of drowsy-related accidents. Sleep Med res 2018;9(2):97-103
Prevalence, Burden, and Treatment of Lower Urinary Tract Symptoms in Men Aged 50 and Older: A Systematic Review of the Literature

We conducted a systematic review of literature from the years 2000 through 2017 on the prevalence and burden of lower urinary tract symptoms (LUTS) in men aged 50 and older, and medical treatments of and alternative nonmedical approaches to LUTS. EBSCOhost (Medline with Full Text) was searched for observational, experimental, and review studies in peer-reviewed journals in the English language. Our review found that LUTS were highly prevalent in the world and estimated to affect 2.3 billion people in 2018, with 44.7% being men. Men with LUTS suffer from not only burdensome symptoms such as nocturia and urgency but also adverse psychological consequences (e.g., anxiety and depression) and financial burden. Current medical treatments are clinically effective, but their efficacy is compromised by side effects and low compliance rates. Alternative nonmedical treatments for LUTS were also sought worldwide. There is evidence that lifestyle modifications such as pelvic muscle exercises and bladder training, physical activity, dietary modification, and nutritional supplements can alleviate LUTS and improve patient quality of life; however, evidence based on rigorous methodology remains minimal and cannot be generalized across populations. Evidence of effectiveness of weight loss programs to reduce LUTS is inconclusive. We conclude that although behavioral treatment is a promising approach to alleviating LUTS, especially when combined with medical treatments, well-designed randomized controlled and longitudinal clinical trials on behavioral treatments of LUTS are still needed. Minimally invasive procedures and neuromodulation therapy also show positive results of alleviating LUTS but require further research as well.
Autonomous Exploration and Mapping System Using Heterogeneous UAVs and UGVs in GPS-Denied Environments

In this paper, we present a novel integrated vehicular system using collaborative unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) for autonomous exploration, mapping, and navigation in GPS-denied 3-dimensional (3-D) unknown environments. The system implements a novel two-layered exploration strategy to decompose the perception task into a coarse exploration layer and a fine mapping layer. The coarse exploration makes use of a UGV to carry out fast autonomous exploration and active 2.5D simultaneous localization and mapping (SLAM) to generate a coarse environment model, which serves as a navigation reference for subsequent complementary 3-D fine mapping conducted by a UAV. The two layers share a novel optimized exploration path planning and navigation framework, which provides optimal exploration paths and integrates the collaborative exploration and mapping efforts through an OctoMap-based volumetric motion planning interface. The proposed system provides an efficient pipeline of fast environment perception taking advantages of the agility of the UAVs as well as the powerful computation resource aboard UGVs, also allowing assistive local perception with augmented object information when necessary. The effectiveness of our system is verified by both simulations and experiments, which demonstrate its capability of implementing heterogeneous UAV and UGV collaborative exploration and structural reconstruction of the environments through active SLAM, providing optimized perception for navigation tasks.
Bevacizumab in the neoadjuvant treatment of human epidermal growth factor receptor 2-negative breast cancer: A meta-analysis of randomized controlled trials

Several randomized clinical trials have suggested the effectiveness of bevacizumab (Bev) in early and advanced breast cancer; however, due to the increased toxicity and lack of a clear long-term survival benefit, there is currently no defined role for Bev in breast cancer in the USA, while it has been approved in Europe. We herein sought to conduct a meta-analysis of large randomized trials comparing the efficacy and long-term outcome of neoadjuvant chemotherapy with Bev compared with chemotherapy without Bev in human epidermal factor receptor 2 (HER2)-negative breast cancer. A search was conducted through PubMed and Ovid Medline databases. Among the 279 articles identified, 5 met the eligibility criteria and were included in the present analysis. A total of 2,268 patients treated with Bev and 2,278 treated without Bev were analyzed. Pathological complete response (pCR) was obtained in 35% of patients treated with Bev and in 26% of those treated without Bev. A statistically significant increase (26%) in the incidence of pCR was observed in the Bev-treated group. However, patients treated with Bev exhibited no significant difference in the risk of disease recurrence or death. To the best of our knowledge, this is the first meta-analysis addressing the long-term outcomes of Bev in combination with chemotherapy in the neoadjuvant treatment of HER2-negative breast cancer. The results confirmed the significant benefit of Bev combined with chemotherapy compared with chemotherapy alone on breast cancer response, in both triple-negative and hormone receptor-positive cases. However, this benefit does not translate into a long-term disease-free or definitive overall survival advantage. Optimizing patient selection is desirable for maximizing the long-term benefits of Bev, while reducing cost and treatment-related adverse effects. Future efforts directed toward the discovery of predictive markers would be crucial for identifying the subset(s) of breast cancer patients who are most likely to benefit from Bev therapy.
Focused Diffusion-Weighted Imaging in Prostate Cancer FODIP

Background: MRI of the prostate is used to detect and localise prostate cancer and diffusion weighted imaging (DWI) is a routine sequence. The purpose of the study was to determine the diagnostic accuracy of high b-value DWI through meta-analyses. Additionally, the aim was to determine the diagnostic accuracy of a novel combined small field-of-view (FOV) and high b-value DWI sequence for detecting and localising prostate cancer. Material and Methods: Meta-analyses of diagnostic test accuracy of high b-value DWI, and T2WI and DWI combined, were performed conforming to the PRISMA statement. A prospective observational diagnostic test accuracy study of 40 patients who underwent 3T MRI with small- (sDWI) and conventional (cDWI) FOV and subsequent radical prostatectomy were included. Two blinded readers assessed the lesion and sectoral-based accuracy of both sequences using radical prostatectomy (RP) specimens as reference standard. Apparent Diffusion Coefficient (ADC) of benign and malignant tissue was assessed. Results: The sensitivity, specificity and area-under-curve (AUC) of the high b-value DWI, and T2WI and DWI meta-analyses were 0.59, 0.92, and 0.92; and 0.68, 0.84 and 0.83, respectively. There were 83 prostate cancers detected in the RP specimens and half of prostate sectors contained tumour. Sensitivity of cDWI alone was significantly higher than sDWI (0.62 vs 0.45, p=<0.001), but specificity was lower (0.88 vs 0.92, p=<0.001). The AUC was not significantly different (0.76 vs 0.73, p=0.164). The interobserver reliability of cDWI was substantial (κ = 0.63) and sDWI was moderate (κ = 0.59). The median mean ADC of tumours was significantly lower than non-tumour tissue for both sequences (p=<0.001). The ADC of tumour was significantly lower with sDWI (960 x 10-6 mm2/sec vs 766 x 10-6 mm2/sec, p=<0.001). Conclusion: Conventional DWI outperformed small-FOV DWI imaging at lesion detection, but there may be clinical benefit for small-FOV at excluding tumour, particularly in a pre-biopsy population.
The Miniature Optical Communication Transceiver—A Compact, Power-Efficient Lasercom System for Deep Space Nanosatellites

Optical communication is becoming more prevalent in orbit due to the need for increased data throughput. Nanosatellites, which are satellites that typically weigh less than 10 kg, are also becoming more common due to lower launch costs that enable the rapid testing of technology in a space environment. Nanosatellites are cheaper to launch than their larger counterparts and may be a viable option for communicating beyond Earth’s orbit, but have strict Size,Weight, and Power (SWaP) requirements. The Miniature Optical Communication Transceiver (MOCT) is a compact optical transceiver designed to provide modest data rates to SWaP constrained platforms, like nanosatellites. This paper will cover the optical amplifier characterization and simulated performance of the MOCT amplifier design that produces 1 kW peak power pulses and closes three optical links which include Low Earth Orbit (LEO) to Earth, LEO to LEO, and Moon to Earth. Additionally, a benchtop version of the amplifier design was constructed and was able to produce amplified pulses with 1.37 W peak power, including a 35.7% transmit optics loss, at a pump power of 500 mW. Finally, the modulator, seed laser, amplifier, receiver, and time-to-digital converter were all used together to measure the Bit Error Ratio (BER), which was 0.00257 for a received optical peak power of 176 nW.
Moments in Nursing Practice: An Interpretive Analysis

What is a nursing moment? This hermeneutic, phenomenological text describes the lived experience of a nursing moment as interpreted from 3 nurses’ stories that depict memorable experiences in their nursing practice. The themes that emerged are a moment of understanding, a moment of being present, a moment of comforting, a moment of touching, and a moment of encouraging. These moments reflect moments of genuine encounters, moments that may bring about profound changes in the lived experiences of patients. In the lived world of nurses, these moments may bring a sense of professional fulfillment and satisfaction.
The effectiveness of structured exercise programmes on psychological and physiological outcomes for patients with psychotic disorders: A systematic review and meta-analysis

Structured exercise has been utilised as complementary therapy for patients with psychotic disorders. This review aims to determine the efficacy of structured exercise on both psychological and physiological variables. Applying PRISMA guidelines and keyword search terms, studies were systematically searched in CINAHL, EMBASE, Medline, PsychInfo, SportDiscus and Web of Science databases from earliest record to December 2017. Eligibility criteria included studies who examined adolescents and adult populations with psychotic disorders, and who implemented modalities of structured exercise. 23 studies were included. Aerobic, resistance and combination interventions led to favourable changes in psychological/physiological outcomes relative to controls. Meta-analysis of ten combinable studies examining psychotic symptom severity using the PANSS identified a pooled mean difference estimate of −0.54 (95%CI = −0.83 to –0.25); Z = −3.65, p > . 001) in favour of structured exercise interventions. Inspection of the funnel plot suggested publication bias was present (Egger test intercept = −2.13, SE = 0.83, p = .03), and an adjusted estimate = −0.34 (95%CI = −0.66 to −0.01). Systematic review results suggest structured exercise can improve psychological and physiological indices, though with likely variable effect magnitudes based on multiple factors. Meta-analytical findings identified that structured exercise interventions can reduce symptom severity indices associated with diagnosed psychotic disorders.
Antiviral Drug Discovery for Emerging Diseases and Bioterrorism Threats: Torrence/Antiviral Drug Discovery for Emerging Diseases and Bioterrorism Threats

Preface. Contributors. 1. Introduction: Pestilence, Plague, Bioterrorism (Paul F. Torrence). 2. Viral Bioterrorism and Antiviral Countermeasures (Mike Bray). 3. Overview of Antiviral Drug Discovery and Development (Christopher K. Tseng). 4. Antiviral Drug Targets and Strategies for Emerging Viral Diseases and Bioterrorism Threats (Erik De Clercq). 5. Perspectives for the Therapy Against Arenavirus Infections (Elsa B. Damonte and Cybele C. Garcia). 6. S-Adenosylhomocysteine Hydrolase Inhibitors as a Source of Anti-Filovirus Agents (Stewart W. Schneller and Minmin Yang). 7. Antiviral Strategies for Ebola Virus (Jillian M. Licata and Ronald N. Harty). 8. IMPDH Inhibitors: Discovery of Antiviral Agents Against Emerging Diseases (Vasu Nair). 9. Lethal Mutagenesis: Exploiting Error-Prone Replication of Riboviruses for Antiviral Therapy (Jason D. Graci and Craig E. Cameron). 10. Structural Biology of Flaviviral Replication and Opportunities for Drug Design (Krishna Murthy). 11. Confronting New and Old Antiviral Threats: Broad Spectrum Potential of Prenylation Inhibitors (Menashe Elazar and Jeffrey S. Glenn). 12. West Nile Virus: New Targets for Potential Antivirals (Matthias Kalitzky, Holger Rohde, and Peter Borowski). 13. The Emergence of Pandemic Influenza A: Bioterrorist Versus Mother Nature (John S. Oxford, Alison Boyers, Alex Mann, and R. Lambkin). 14. Discovery and Development of New Antivirals for Smallpox (Earl R. Kern). 15. Viral Countermeasures to the Host Interferon Response: Role of the Vaccinia Virus E3L and K3L Genes (Jeffrey O. Langland, Vanessa Lancaster, and Bertram L. Jacobs). 16. Broad-Spectrum Antiviral Prophylaxis: Inhibition of Viral Infection by Polymer Grafting with Methoxypoly(ethylene glycol) (Lori L. McCoy and Mark D. Scott). 17. Viral Evasion of the Interferon System: Novel Targets for Drug Discovery (Paul F. Torrence and Linda Powell). Index.
Operations Management : An Integrated Approach Ed. 5

In the 5th Edition of Operations Management, Dan Reid and Nada Sanders have strengthened their commitment to improve the teaching and learning experience in the introductory operations management course. The text provides a solid foundation of Operations Management with clear, guided instruction and a balance between quantitative and qualitative concepts. Through an integrated approach, the authors illustrate how all business students will interact with Operations Management in future careers. And, with increased support for students through new pedagogy, worked out examples and WileyPLUS, the 5th Edition provides the help students need to complete the course with greater success.
Street-Frontage-Net: urban image classification using deep convolutional neural networks

ABSTRACT Quantifying aspects of urban design on a massive scale is crucial to help develop a deeper understanding of urban designs elements that contribute to the success of a public space. In this study, we further develop the Street-Frontage-Net (SFN), a convolutional neural network (CNN) that can successfully evaluate the quality of street frontage as either being active (frontage containing windows and doors) or blank (frontage containing walls, fences and garages). Small-scale studies have indicated that the more active the frontage, the livelier and safer a street feels. However, collecting the city-level data necessary to evaluate street frontage quality is costly. The SFN model uses a deep CNN to classify the frontage of a street. This study expands on the previous research via five experiments. We find robust results in classifying frontage quality for an out-of-sample test set that achieves an accuracy of up to 92.0%. We also find active frontages in a neighbourhood has a significant link with increased house prices. Lastly, we find that active frontage is associated with more scenicness compared to blank frontage. While further research is needed, the results indicate the great potential for using deep learning methods in geographic information extraction and urban design.
Unlocking the potential of neural networks in resource and data constrained environments

Data driven methods based on deep neural networks (DNNs) have ushered in a new era in the field of machine learning computer vision. Conventional algorithmic approaches are being replaced by end-to-end deep learning systems that can leverage big data. Deep learning has begun revolutionizing human centric fields such as health-care and finance, finding its way into automated screening and diagnoses. At present, developing and training artificial neural network architectures requires both human expertise and labor, requiring millions of labeled data-points to train and hours of engineering effort to develop best performing architectures. In this dissertation, my goal is to make deep learning more accessible by developing algorithms for low shot learning (learning from a few examples). This work includes new semi-supervised approaches to learn from unlabeled datasets with only a fraction of labeled examples, deep learning methods to learn from generated data using simulation based techniques, and learning to optimize neural networks for smaller data sets. Specifically, this dissertation focuses on two proposed directions which will contribute towards both technical and conceptual advances in literature. – How can we use invariant-based approaches when training from small datasets ? – How to enable training from multiple data sources carrying very small amounts of data ? – How to use meta-modeling approach to automatically generate high-performing DNNs ? To address these questions, this dissertation describes machine learning algorithms as follows (a) an action recognition autoencoder which learns over very small datasets; (b) an algorithm to train deep neural networks over multiple entities; (c) a meta-modeling approach to automatically generate high-performing architectures. We also provide a dataset of neural network topologies used for predicting accuracy of a deep neural network.
Prevalence And Antimicrobial Susceptibility Patterns Of Bacteria Isolated From Urinary Tract Infections (UTIs) In Children At Children Hospital In Baghdad

Background: First six to twelve months after initial urinary tract infection, most infections are caused by Escherichiacoli, although in the first year of life Klebsiella pneumoniae, Pseudomonas, Enterobacter spp andEnterococcus spp, are more frequent than later in life, and there is a higher risk of urosepsis compared with adulthood Objectives: To determine the prevalence of bacterial isolates from Urinary Tract Infections of children at a children hospital in Baghdad and their antimicrobial susceptibility patterns. Type of the study: Cross-sectional study. Methods: During six months of study (1 June to 31 December, 2016), 117urine specimens were collected from a children hospital in Baghdad. Results: Out 38 isolates of Gram positive and Gram negative bacteria were obtained from urine specimens in a percentage of 5(13.2%) and 33(86.8%),respectively. The lowest incidence was among the 11-15 years old age group (11.9%) whereas the highest incidence was among the 1-5 years old age group (43.6%)(P≤0.05). Also out of 38positive cultures, the incidence was higher in females 31(81.6%)than that of males 7(18.4%). Out of 38 positive cultures, the isolation rate was 5(13.2%) for Gram positive isolates and 33(86.8%)for Gram negative isolates. The most frequently isolated bacteria was Escherichia coli19(50%)(P-value ≤ 0.05), while the only isolated Gram positive was Staphylococcus aureus5(42.86%) isolates.The most effective antibiotics for Staphylococcus aureus isolates were Vancomycin and Amikacinfor (100%) and for Gram negative isolates wasimipenem (100%). Ampicillin showed the highest resistance rate for both Gram positive and Gram negative isolates(100%) and Pesudomonas aeruginsa isolates showed the highest resistant rates to most antibiotics under study. Conclusions: The most frequently isolated bacteria was E. coli from all urine cultures and the most effective antibiotics for Staphylococcus aureus isolates were Vancomycin and Amikacinfor