Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the capabilities of machine learning (ML) for 1D blood flow: Application to coronary flow

The aim of this thesis is to explore the capabilities of deep neural networks to reproduce 1D computational models for the pressure in a coronary tree. A machine learning algorithm was implemented. The algorithm was trained with a synthetically generated database of coronary trees, where the anatomical data was retrieved from published literature. A grid search was performed to optimize the hyper-parameters in the machine learning model. Two different models were trained to solve a steady state; coronary blood flow model and Young and Tsai’s stenosis model. Correlation between the predicted values was excellent for both models with coefficient of determination, r2 = 1 for the steady state coronary blood flow model, and r2 = 0.997 for Young and Tsai’s stenosis model. The established ML models were tested with patient specific data. The prediction on the patient specific data showed that the synthetically generated database did not represent the pathological variation of coronary arteries. For a reduced patient specific database, the model predicted the pressure drop along the healthy vessels with a coefficient of determination, r2 = 0.799 and for the reduced database with the patient specific stenoses, r2 = 0.997.
Efficacy and safety of acupuncture therapy for urinary incontinence in women

Abstract Background: Urinary incontinence (UI), affects women more frequently than men, with a prevalence to 30–40% of perimenopausal women and almost 50% among women aged over 70 years. caused severe psychological burden and bringing negatively impact to the quality of life, increased caregiver burden and economic cost. Acupuncture is often used to treat them. We aim to conduct a systematic review to evaluate the efficacy of acupuncture for women experiencing UI. Methods: The following electronic databases will be searched from inception to Jan. 2020: Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, Web of Science, EMBASE, China National Knowledge Infrastructure (CNKI), Traditional Chinese Medicine, Chinese Biomedical Literature Database (CBM), Wan-Fang Database and Chinese Scientific Journal Database (VIP database). All published randomized controlled trials in English or Chinese related to acupuncture for urinary incontinence in women will be included. The primary outcome will be the change from baseline in the amount of urine leakage measured by the 1-hour pad test. Adverse events will be the secondary outcome. Study selection, data extraction, and assessment of study quality will be performed independently by two reviewers. RevMan V.5. 3.5 software will be used for the assessment of risk of bias and data synthesis. Results: This study will provide a high-quality synthesis of current evidence of acupuncture for UI from the 1-hour pad test. Conclusion: The conclusion of our study will provide an evidence to judge whether acupuncture is an effective intervention for patients suffered from UI. PROSPERO registration number: CRD42019133195
Peroxisome turnover and diurnal modulation of antioxidant activity in retinal pigment epithelia utilizes microtubule-associated protein 1 light chain 3B

The retinal pigment epithelium (RPE) supports the outer retina through essential roles in the retinoid the visual cycle, nutrient supply, ion exchange and waste removal. Each day the RPE removes the oldest ∼10% of photoreceptor outer segments through phagocytic uptake, which peaks in a synchronous burst following light onset. Impaired degradation of phagocytosed OS material by the RPE can lead to toxic accumulation of lipids, oxidative tissue damage, inflammation and cell death. OSs are rich in very long chain fatty acids which are preferentially catabolized in peroxisomes. Despite the importance of lipid degradation in RPE function, the regulation of peroxisome number and activity relative to diurnal OS ingestion is relatively unexplored. Using immunohistochemistry, immunoblotting and catalase activity assays, we investigated peroxisome abundance and activity at 6 am, 7 am (at lights on), 8 am, and 3 pm, in WT mice and mice lacking microtubule-associated protein 1 light chain 3B (LC3B), that have impaired degradation of phagosomes. We found that catalase activity, but not protein expression, is 50% higher in the morning compared with 3 pm, in RPE of WT but not LC3B-/- mice. Surprisingly, we found that peroxisome abundance was stable during the day, however numbers are elevated overall in LC3B-/- mice, implicating LC3B in autophagic organelle turnover in RPE. Our data suggest that RPE peroxisome function is regulated in coordination with phagocytosis, possibly through direct enzyme regulation, and may serve to prepare RPE peroxisomes for daily surges in ingested lipid-rich OS.
Factors influencing implementation of evidence-based interventions in public health systems - a model.

OBJECTIVES Evidence that health interventions work is not enough to ensure implementation into policy and practice. The complexity of public health systems requires more diverse actions. This paper proposes a conceptual model to enhance understanding of interlinking factors that influence the evidence implementation process. METHODS A literature review was conducted to explore factors that influence the process of evidence implementation in complex public health systems, including research findings and observations from 32 case studies of injury prevention interventions underway in 24 countries and results from evidence research networks. Concepts and themes identified through a critical review were organised, ordered and interlinked to build the model. RESULTS An Evidence Implementation Model for Public Health Systems and four concepts or themes: Evidence implementation target; Actors involved in implementation; Knowledge transfer; and Barriers and facilitators to evidence implementation were developed to provide a simplified, yet broad framework that highlights multiple factors and back and forth inter-linkages within and between the concepts that influence the uptake of evidence into public health systems policy and practice. CONCLUSIONS Understanding the factors discussed within and amongst the four concepts of this model should ultimately help to positively influence the uptake of evidence into real world public health systems. This model has relevance for decision makers, researchers, knowledge brokers, and implementers.
The Role of Work Engagement in Agile Software Development: Investigating Job Demands and Job Resources

Agile software development projects still show a high failure rate. Despite a growing amount of research, underlying reasons for project performance currently remain rare. Drawing on the job demands-resources theory, we propose a theoretical model of work engagement in agile software development teams. Using structural equation modeling, we found that agile practices diminish job demands (perceived workload and role ambiguity) and support job resources (perceived meaningfulness and job autonomy). Job resources have been found to be positively related to work engagement in agile software development teams. Our research contributes to the limited empirical understanding on work engagement in agile software development. For practitioners, our model provides tools to effectively manage team members’ work engagement.
Real‐time multi‐directional flow MRI using model‐based reconstructions of undersampled radial FLASH – A feasibility study

The purpose of this work was to develop an acquisition and reconstruction technique for two‐ and three‐directional (2d and 3d) phase‐contrast flow MRI in real time. A previous real‐time MRI technique for one‐directional (1d) through‐plane flow was extended to 2d and 3d flow MRI by introducing in‐plane flow sensitivity. The method employs highly undersampled radial FLASH sequences with sequential acquisitions of two or three flow‐encoding datasets and one flow‐compensated dataset. Echo times are minimized by merging the waveforms of flow‐encoding and radial imaging gradients. For each velocity direction individually, model‐based reconstructions by regularized nonlinear inversion jointly estimate an anatomical image, a set of coil sensitivities and a phase‐contrast velocity map directly. The reconstructions take advantage of a dynamic phase reference obtained by interpolating consecutive flow‐compensated acquisitions. Validations include pulsatile flow phantoms as well as in vivo studies of the human aorta at 3 T. The proposed method offers cross‐sectional 2d and 3d flow MRI of the human aortic arch at 53 and 67 ms resolution, respectively, without ECG synchronization and during free breathing. The in‐plane resolution was 1.5 × 1.5 mm2 and the slice thickness 6 mm. In conclusion, real‐time multi‐directional flow MRI offers new opportunities to study complex human blood flow without the risk of combining differential phase (i.e., velocity) information from multiple heartbeats as for ECG‐gated data. The method would benefit from a further reduction of acquisition time and accelerated computing to allow for extended clinical trials.
Does reduced E-cadherin expression correlate with poor prognosis in patients with upper tract urothelial cell carcinoma?

Abstract Background: E-cadherin has emerged as a prognostic factor of urothelial cell carcinoma. In the present work we investigate the relationship between expression of E-cadherin and clinical outcomes, following radical nephroureterectomy for upper tract urothelial cell carcinoma. Methods: We systematically searched PubMed, Embase, Cochrane Library, and Web of Science databases to identify eligible studies published until July 2017. Result: Six studies were included in the meta-analysis, with a total of 1014 patients. The pooled hazard ratio (HR) for recurrence-free survivor was 0.69 (95% confidence interval [CI], 0.44–1.09, I2 = 63%, P = .04). Also, reduced E-cadherin was not significantly associated with poor cancer-specific survivor (pooled HR, 1.40; 95% CI, 0.66–1.43, I2 = 54%, P = .11). The pooled HR for overall survivor was not statistically significant (pooled HR, 0.68; 95% CI, 0.32–1.46, I2 = 80%, P = .007). The results of the Begg and Egger tests suggested that publication bias was not evident in this meta-analysis. Conclusions: Reduced E-cadherin expression did not appear to be significantly associated with disease prognosis after nephroureterectomy in the meta-analysis. However, further high quality, prospective studies are warranted to better address this issue.
Long-Term Evaluation of Functional Outcomes Following Rat Volumetric Muscle Loss Injury and Repair.

Volumetric muscle loss (VML) injuries, by definition, exceed the endogenous repair capacity of skeletal muscle resulting in permanent structural and functional deficits. VML injuries present a significant burden for both civilian and military medicine. Despite progress, there is still considerable room for therapeutic improvement. In this regard, tissue engineered constructs show promise for VML repair, as they provide an opportunity to introduce both scaffolding and cellular components. We have pioneered the development of a Tissue Engineered Muscle Repair (TEMR) technology created by seeding muscle progenitor cells (MPCs) onto a porcine derived bladder acellular matrix (BAM) followed by cyclic stretch preconditioning prior to implantation. Our work to date has demonstrated significant functional repair (60-90% functional recovery) in progressively larger rodent models of VML injury following TEMR implantation. Notwithstanding this success, TEMR implantation in cylindrically shaped VML injuries in the tibialis anterior (TA) muscle was associated with more variable functional outcomes than has been observed in sheet-like muscles such as the latissimus dorsi. In fact, previous observations documented a dichotomy of responses following TEMR implantation in a rodent TA VML injury model; with a ≈61% functional improvement observed in fewer than half (46%) of TEMR-implanted animals at 12 weeks post-injury. This current study builds directly from those observations as we modified the geometry of both the VML injury and the TEMR construct to determine if improved matching of the implanted TEMR construct to the surgically created VML injury resulted in increased functional recovery post-treatment. Following these modifications, we observed a comparable degree of functional improvement in a larger proportion of animals (≈67%) that was durable up to 24 weeks post-TEMR implantation. Moreover, in ≈25% of all TEMR-implanted animals, functional recovery was virtually complete (TEMR Max Responders), and further, the functional recovery in all 67% of responding animals was accompanied by the presence of native-like muscle properties within the repaired TA muscle, including fiber cross sectional area, fiber type, vascularization, and innervation. This study emphasizes the importance of "tuning" the application of tissue engineering technology platforms to the specific requirements of diverse VML injuries in order to improve functional outcomes.
Capsid expansion of bacteriophage T5 revealed by high resolution cryoelectron microscopy

Significance Tailed DNA bacteriophages are the most ubiquitous viruses on earth. They are highly diverse but related to the medically important herpesviruses. We studied the protein shell, or capsid, that contains and protects the viral genome. One bacteriophage, called T5, has a large capsid made using about 800 copies of a protein organized with icosahedral geometry. Using state-of-the-art cryo-EM, we determined the structure of the T5 capsid in molecular detail as well as intermediates in its formation. This sequence of capsid structures reveals dramatic changes that take place during the crucial capsid assembly step in the bacteriophage T5 life cycle and allow us to observe essential widely conserved steps of virus assembly on a scale never observed before. The large (90-nm) icosahedral capsid of bacteriophage T5 is composed of 775 copies of the major capsid protein (mcp) together with portal, protease, and decoration proteins. Its assembly is a regulated process that involves several intermediates, including a thick-walled round precursor prohead that expands as the viral DNA is packaged to yield a thin-walled and angular mature capsid. We investigated capsid maturation by comparing cryoelectron microscopy (cryo-EM) structures of the prohead, the empty expanded capsid both with and without decoration protein, and the virion capsid at a resolution of 3.8 Å for the latter. We detail the molecular structure of the mcp, its complex pattern of interactions, and their evolution during maturation. The bacteriophage T5 mcp is a variant of the canonical HK97-fold with a high level of plasticity that allows for the precise assembly of a giant macromolecule and the adaptability needed to interact with other proteins and the packaged DNA.
New library of pyrazole–imidazo[1,2‐α]pyridine molecular conjugates: Synthesis, antibacterial activity and molecular docking studies

A library of novel pyrazole–imidazo[1,2‐α]pyridine scaffolds was designed and synthesized through a one‐pot three‐component tandem reaction. The structures of synthesized conjugates were confirmed by spectroscopic techniques (NMR, IR and HRMS). In vitro antibacterial evaluation of the twelve synthesized molecules (7a, 8a–k) against methicillin‐resistant Staphylococcus aureus and normal strains of Escherichia coli, Salmonella typhimurium, Klebsiella pneumonia and Pseudomonas aeruginosa established 8b, 8d, 8e, 8h and 8i as potent antibacterial agents with superior minimum bactericidal concentration, compared with standard drug ciprofloxacin. Molecular docking studies of all active compounds into the binding site of glucosamine‐6‐phosphate synthase were further performed in order to have a comprehensive understanding of putative binding modes within the active sites of the receptor.
In Silico Investigation of the Binding of MCoTI-II Plant Defense Knottin to the γ-NGFserine Protease of the 7S Nerve Growth Factor Complex and Biological Activity of Its NGF Mimetic Properties.

Nerve Growth Factor (NGF) induces neurotrophic effects primarily through the tropomyosin-related kinase receptor TrkA NGF. While trophic proteins hold promise for the treatment of neuronal injury and disease, use of NGF is limited by its large molecular weight, lack of permeability through the blood brain barrier and peripheral side effects. High throughput screening on > 1000 natural plant based substances using a PC-12 neurite outgrowth model found only a single NGF mimetic hit, the seed pit of bitter gourd Momordica cochinchinensis. Bioactivity guided fractioning of the M. cochinchinensis seed extract confirmed the active component to be a protein of approximately 17kD MW, and not of chemical nature. By a theoretical understanding, it has been shown that in vivo, NGF exists as an inactive high molecular weight complex known as 7S NGF, which comprises pairs of two serine proteinases α-NGF and γ-NGF, and the trypsin inhibitor β-NGF. Active NGF is comprised of the free β-NGF dimer. Here we use computational modeling, which demonstrates that MCoTI-II can bind stably to the serine protease γ-NGF within the 7S NGF complex. This interaction may inhibit 7S NGF complex formation, potentially freeing the active NFG protein, and may explain the neuritogenic NGF mimetic activity of M. cochinchinensis seed extract. Recombinant purified MCoTI-II tested in rat PC-12 cells grown on collagen failed to initiate outgrowth relative to the control. While theoretical dockings studies show a plausible hypothetical explanation for trophic effects, biological studies do not support a role in neurotrophic activity of the pure MCoTI-II protein.
A Scalable and Adaptable ILP-Based Approach for Task Mapping on MPSoC Considering Load Balance and Communication Optimization

Task mapping has been a hot topic in multiprocessor system-on-chip software design for decades. During the mapping process, load balance (LB) and communication optimization have been two important performance optimization factors. This paper studies the relations between LB, interprocessor communications, and communication pipeline technique during the mapping process, and proposes an integer linear programming (ILP)-based static task mapping approach, which considers both LB and communication optimization. The approach consists of an optimized ILP model for task mapping with fewer variables compared to previous ILP mapping works. Moreover, to enhance the scalability of the ILP task mapping, the task-processor-cluster algorithm is proposed to reduce the scale of the task graph and the number of processors and then solve the coarse-grained input by the ILP mapping. To increase the adaptability of the ILP task mapping, the improved augmented $\epsilon $ -constraint method is further integrated with the ILP formulations to select the best mapping for different applications. Experimental results on a 2/4/8/16/24-CPU platform of both synthetic and real-life benchmarks demonstrate the efficiency of the proposed approach.
Spectrum Decision Framework to Support Cognitive Radio Based IoT in 5G

RF Spectrum Decision in Cognitive Radio enables unlicensed users of wireless communication systems to occupy the vacant spectrum slots as a solution to scarce spectrum. Internet of Things (IoT) is a wide-reaching network of unified entities. IoT capable things will be interconnected through wireless communication technologies offering cost-effectiveness and accessibility to remote users making quality life style. IoT implementation suffers from challenges of vulnerabilities to dynamic environmental conditions, ease of access, bandwidth allocation and utilization, and cost to purchase RF spectrum. As RF spectrum is a precious commodity and there is a dearth of RF spectrum, hence IoT connections are drifting towards Cognitive Radio Networks (CRNs). Permeating things with cognitive abilities will be able to make RF spectrum decisions to achieve interference-free and wireless connectivity as per their QoS requirements. The wireless systems are rapidly advancing. The leap from packet switching along with circuit switching with 144 kbps data rate (2G and 2.5G) to Long Term Evolution Advanced (LTE-A), i.e., 4G occurred in one decade time frame. As the current wireless connectivity is aimed at higher capacity, higher data rate, low end-to-end latency, massive device connectivity, reduced cost and consistent Quality of Experience (QoE) provision, therefore, 4G is being replaced with 5G. Presently
IoT Smart Health Security Threats

The Internet of things (IoT) is an active area in the current research community due to the improvement in mobile computing and wireless networks. Currently, the IoT is involved in many fields like smart cities, smart health monitoring, smart tracking, and smart factory; therefore, it is introducing new research opportunities and industrial revolutions. Smart health, in particular, is very important and trendy domain for researchers and practitioners due to its continuous monitoring of health of patients. The objective of smart health is to provide medical facilities to patients at anytime and anywhere. The smart health monitoring systems are mostly connected with the wireless network medium that is extremely vulnerable for threats. However various attacks are observed that can endanger these health monitoring applications and systems. These attacks include Denial of Service (DoS) Attack, Fingerprint and Timing-based Snooping, Router Attack, Select and Forwarding attack, Sensor attack and Replay Attack. In this paper, we discuss these attacks with their impact on health monitoring systems with some suggestive measures from our research findings.
Neighborhood Graph Embedding for Nodes Clustering of Social Network

Graph embedding is an important dimension reduction method for high-dimensional data. In this paper, a neighborhood graph embedding algorithm is proposed and it is applied in data clustering. Different from the traditional graph embedding algorithms, a dependence degree of node is defined and it represents the dependence of two nodes; the adjacency matrix of graph is determined by dependence degree. Then a new graph embedding is proposed. After transformation matrix is solved, the weight of each attribute can also be determined from transformation matrix. Finally, the data is partitioned into clusters by clustering algorithm with weighting distance. The proposed algorithm and comparison algorithms are executed on the real social network data sets. The experimental results show that the proposed algorithm outperformances the comparison algorithms and it proves that the proposed algorithm is effective for data clustering in social network.
Molecular Fingerprint Sensing using Ge-on-Si Waveguides

Germanium-on-silicon, mid-infrared waveguides are used to demonstrate molecular fingerprint sensing of poly(methyl methacrylate) between 7.5 and 10 μm wavelength. The results are compared to Fourier transform infrared spectroscopy measurements, highlighting the potential of the platform for the identification of analytes.
Performance Analysis of Machine Learning Classifiers for ASD Screening

Several machine learning classifiers have been used for Autism Spectrum Disorder screening, however, literature in finding the best classifier for this application domain is inadequate. Hence, this paper presents a comparison of five (5) supervised machine learning algorithms: Decision Tree, Naïve Bayes, k-nn, Random Tree, and Deep Learning using small datasets (n=1100) on child, adolescent and adult ASD screening in finding the most appropriate classifier. These algorithms, which are evaluated using a broad set of prediction performance metrics including accuracy, precision/recall measures, and Receiver Operating Characteristics, are compared against each other. The experiment result suggests that the Deep Learning classifier gives the best performance (with more than 96%) in almost all metrics while the Random Tree classifier came out as the least performing classifier in all the performance metrics.