Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrospinning of polymethyl methacrylate nanofibers: optimization of processing parameters using the Taguchi design of experiments

The effects of polymer concentration and electrospinning parameters on the diameter of electrospun polymethyl methacrylate (PMMA) fibers were experimentally investigated. It was also studied how the controlled factors would affect the output with the intention of finding the optimal electrospinning settings in order to obtain the smallest PMMA fiber diameter. Subsequently the solution feed rate, needle gauge diameter, supply voltage, polymer concentration and tip-to-collector distance were considered as the control factors. To achieve these aims, Taguchi’s mixed-level parameter design (L18) was employed for the experimental design. Optimal electrospinning conditions were determined using the signal-to-noise (S/N) ratio that was calculated from the electrospun PMMA fiber diameter according to “the-smaller-the-better” approach. Accordingly, the smallest fiber diameter observed was 228 (±76) nm and it was yielded at 15 wt% polymer concentration, 20 kV of supply voltage, 1 ml/h feed rate, 15 cm tip-to-distance and 19 needle gauge. Moreover, the S/N ratio response showed that the polymer concentration was the most effective parameter on determination of fiber diameter followed by feed rate, tip-to distance, needle gauge and voltage, respectively. The Taguchi design of experiments method has been found to be an effective approach to statistically optimize the critical parameters used in electrospinning so as to effectively tailor the resulting electrospun fiber diameters and morphology.
Increased Risk of Severe Hypoglycemic Events Before and After Cardiovascular Outcomes in TECOS Suggests an At-Risk Type 2 Diabetes Frail Patient Phenotype

OBJECTIVE Severe hypoglycemic events (SHEs) in type 2 diabetes are associated with subsequent cardiovascular (CV) event risk. We examined whether CV events were associated with subsequent SHE risk. RESEARCH DESIGN AND METHODS Time-dependent associations between SHEs and a composite CV end point (fatal/nonfatal myocardial infarction or stroke, hospitalization for unstable angina, hospitalization for heart failure [hHF]) were examined post hoc in 14,671 TECOS (Trial Evaluating Cardiovascular Outcomes With Sitagliptin) participants with type 2 diabetes and CV disease followed for a median of 3.0 years. RESULTS SHEs were uncommon and unassociated with sitagliptin therapy (N = 160 [2.2%], 0.78/100 patient-years vs. N = 143 [1.9%], 0.70/100 patient-years for placebo; hazard ratio [HR] 1.12 [95% CI 0.89, 1.40], P = 0.33). Patients with (versus without) SHEs were older with longer diabetes duration, lower body weight, and lower estimated glomerular filtration rate; were more frequently women, nonwhite, and insulin treated; and more often had microalbuminuria or macroalbuminuria. Analyses adjusted for clinical factors showed SHEs were associated with increased risk of the primary composite CV end point (1.55 [1.06, 2.28], P = 0.025), all-cause death (1.83 [1.22, 2.75], P = 0.004), and CV death (1.72 [1.02, 2.87], P = 0.040). Conversely, nonfatal myocardial infarction (3.02 [1.83, 4.96], P < 0.001), nonfatal stroke (2.77 [1.36, 5.63], P = 0.005), and hHF (3.68 [2.13, 6.36], P < 0.001) were associated with increased risk of SHEs. Fully adjusted models showed no association between SHEs and subsequent CV or hHF events, but the association between CV events and subsequent SHEs remained robust. CONCLUSIONS These findings, showing greater risk of SHEs after CV events and greater risk of CV events after SHEs, suggest a common at-risk type 2 diabetes frail patient phenotype.
Vitamin K antagonists and emergencies

The recent emergence of ‘non-VKA’ oral anticoagulants may have led to some forgetting that vitamin K antagonists (VKA) are by far the most widely prescribed oral anticoagulants worldwide. Consequently, we decided to summarize the information available on them. This paper presents the problems facing emergency physicians confronted with patients on VKAs in 10 points, from pharmacological data to emergency management. Vitamin K antagonists remain preferable in many situations including in the elderly, in patients with extreme body weights, severe chronic kidney or liver disease or valvular heart disease, and in patients taking VKAs with well-controlled international normalized ratios (INRs). Given the way VKAs work, a stable anticoagulant state can only be achieved at the earliest 5 days after starting therapy. The induction phase of VKA treatment is associated with the highest risk of bleeding; validated algorithms based on INR values have to be followed. VKA asymptomatic overdoses and ‘non-severe’ hemorrhage are managed by omitting a dose or stopping treatment plus administering vitamin K depending on the INR. Major bleeding is managed using a VKA reversal strategy. A prothrombin complex concentrate infusion plus vitamin K is preferred to rapidly achieve an INR of up to 1.5 and maintain a normal coagulation profile. The INR must be measured 30 min after the infusion. Before an invasive procedure, if an INR of less than 1.5 (<1.3 in neurosurgery) is required, it can be achieved by combining prothrombin complex concentrate and vitamin K. A well-codified strategy is essential for managing patients requiring emergency invasive procedures or presenting bleeding complications.
Analysis of a Hybrid Field-Modulated Linear Generator For Wave Energy Conversion

Direct-drive wave energy converter (DD-WEC) is limited by low power density caused by low direct-drive speed. A tubular hybrid field-modulated linear generator is proposed to improve the performance of DD-WEC. The generator adopted a field-modulated design to increase the output voltage of the linear generator. A hybrid excited field coil can be used to adapt to different wave situations and effectively improve the output performance of this kind of generator. The operation of the proposed generator is analyzed, and the generator performance is evaluated through finite element method and compared with those of three other generators, namely, a field modulated linear generator with parallel magnetic-circuit, a secondary surface PM field modulated linear generator, and a secondary surface PM fractional-slot linear generator. Results show that the proposed generator exhibits high power density and low cogging force. The steady output power and output voltage of are marginally higher in the proposed generator than in the conventional generators.
Review of the health effects of berries and their phytochemicals on the digestive and immune systems

Berries are generally considered beneficial to health. This health-promoting potential has mainly been ascribed to berries' phytochemical and vitamin content, and little attention has been paid to the potential benefits of berries for the digestive tract, despite this being the first point of contact. In vivo studies that described the health effects of berries on individual parts of the digestive tract (ie, the mouth, esophagus, stomach, small and large intestine, microbiome, and immune system) were reviewed. Immune effects were included because a large part of the immune system is located in the intestine. Beneficial health effects were mainly observed for whole berry extracts, not individual berry components. These effects ranged from support of the immune system and beneficial microbiota to reduction in the number and size of premalignant and malignant lesions. These results demonstrate the potency of berries and suggest berries can serve as a strong adjuvant to established treatments or therapies for a variety of gastrointestinal and immune-related illnesses.
A Hybrid Algorithm for Estimating Origin-Destination Flows

With the development of intelligent transportation systems, the estimation of traffic flow in urban areas has attracted a great attention of researchers. The timely and accurate travel information of urban residents could assist users in planning their travel strategies and improve the operational efficiency of intelligent transportation systems. Currently, the origin-destination (OD) flows of urban residents are formulated as an OD matrix, which is used to denote the travel patterns of urban residents. In this paper, a simple and effective model, called NMF-AR, is proposed for predicting the OD matrices through combining the nonnegative matrix factorization (NMF) algorithm and the Autoregressive (AR) model. The basic characteristics of travel flows are first revealed based on the NMF algorithm. Then, the nonlinear time series coefficient matrix, extracted from the NMF algorithm, is estimated based on the AR model. Finally, we predict OD matrices based on the estimated coefficient matrix and the basis matrix of NMF. Extensive experiments have been implemented, in collected real data about taxi GPS information in Beijing, for comparing our proposed algorithm with some known methods, such as different kinds of $K$ -nearest neighbor algorithms, neural network algorithms and classification algorithms. The results show that our proposed NMF-AR algorithm have a more effective capability in predicting OD matrices than other models.
A study of deep learning networks on mobile traffic forecasting

With evolution toward the fifth generation (5G) cellular technologies, forecasting and understanding of mobile Internet traffic based on big data is the foundation to enable intelligent management features. To take full advantage of machine learning, a more comprehensive investigation on a mobile traffic dataset with the latest deep learning models is desired. Therefore, a multitask learning architecture using deep learning networks for mobile traffic forecasting is presented in this work. State-of-the-art deep learning models are studied, including 1) recurrent neural network (RNN), 2) three-dimensional convolutional neural network (3D cNn), and 3) combination of CNN and RNN (CNN-RNN). The experiments reveal that CNN and RNN can extract geographical and temporal traffic features respectively. Comparing with either deep or non-deep learning approaches, CNN-RNN is a reliable model leading in all tasks with 70 to 80% forecasting accuracy.
Enhanced light-matter interaction at the nanoscale using localized plasmon modes on disordered metallic films

Disordered semi-continuous metallic films are a particularly striking example of complex photonic systems. They exhibit peculiar optical properties that cannot be explained from the behavior of bulk metals or ensembles of isolated nanoparticles [1]. The interplay between surface-plasmon excitations and scattering by multiscale (fractal) metallic clusters leads to spatial localization of the electromagnetic field in subwavelength areas (hot spots). A feature of these “hot-spots modes” is the expected coexistence of both localized and delocalized modes at the same frequency [2,3], a situation referred to as inhomogeneous localization.
Public Health Triangulation to inform decision-making in Belgium

We assessed the impact of a nation-wide ambulatory care complex intervention (the "care trajectory program") on quality of care in Belgium. We used the three-step public health triangulation method described in this paper and data from four different data sources: a national reimbursement database, an electronic patient record-based general practitioner network, the Belgian general practitioner sentinel network, and a new national registry for care trajectory patients. By applying our method and using the available evidence, we identified key findings that have been accepted by experts and stakeholders. We also produced timely recommendations for the decision-making process, four years after the start of the care trajectory program.
Cluster-Based Cooperative MIMO-OFDMA Cellular Networks: Scheduling and Resource Allocation

In this work, a cross-layer framework is proposed for scheduling and resource allocation in the context of cooperative wideband wireless cellular systems supporting heterogeneous traffic. To this end, the network is partitioned into clusters, each comprising a small number of base stations that share data and/or control information and thus are able to apply cluster-wide cooperative multiple-antenna techniques such as network MIMO (N-MIMO) or large-scale MIMO (LS-MIMO). In contrast to previous works whose main goal was the study of purely physical layer metrics, the framework proposed here serves to evaluate the network performance in terms of operator-relevant metrics such as the average user throughput, the average delay, or different fairness indices. The cross-layer design introduced here is general enough to encompass various forms of power allocation or scheduling policies while being able to incorporate per-cluster or per-base power constraints. Remarkably, different greedy algorithms are introduced for both N-MIMO and LS-MIMO that effectively exploit the multiuser and frequency diversity of the system while remaining computationally feasible. A particularly interesting application of the proposed framework, explored in detail in this paper, is a thorough and realistic comparison of the performance of N-MIMO and LS-MIMO that reveals the strengths and weaknesses of each strategy in terms of different performance metrics.
The EMBERS architecture for streaming predictive analytics

Developed under the IARPA Open Source Initiative program, EMBERS (Early Model Based Event Recognition using Surrogates) is a large-scale Big-Data analytics system for forecasting significant societal events, such as civil unrest incidents and disease outbreaks on the basis of continuous, automated analysis of large volumes of publicly available data. It has been operational since November of 2012, delivering approximately 50 predictions each day. EMBERS is built on a streaming, scalable, share-nothing architecture and is deployed on Amazon Web Services (AWS).
Preparation of Antibacterial Cotton Fabric Containing Patchouli Oil Microcapsules by Chemical Crosslinking Method

In this paper, a new kind of antibacterial cotton fabric containing patchouli oil microcapsules was investigated. The patchouli oil microcapsules were prepared using a complex coacervation procedure and grafted onto cotton fabric by chemical crosslinking method, along with 1,2,3,4-butanetetracarboxylic acid (BTCA) was utilized as the crosslinking agent. The surface and morphology of fabrics were characterized by using scanning electron microscope (SEM). Fourier transform infrared spectrometry (FTIR) was used to study the formation of ester bonds between BTCA and hydroxyl groups of cotton and patchouli oil microcapsules. The releasing characteristics and antimicrobial durability of the antibacterial fabrics were also investigated by releasing test and laundering test. The results showed that the patchouli oil microcapsules were grafted onto cotton fabric by the role of crosslinking agent BTCA and the treated fabric represented persistent effect, slow releasing performance and washable antibacterial properties. After 30 days, the patchouli oil in the microcapsules was still remained on the fabric and the releasing amount was near 50%. About 72% antibacterial rate of the fabric for staphylococcus aureus and candida albicans could be obtained after washed 30 times, furthermore, no formaldehyde releasing can be found. It is suggested that chemical crosslinking method would provide a potential application in functional finishing by microcapsules for cotton fabric.
Disparities in Diabetes Self-management Education for Uninsured and Underinsured Adults

Purpose To examine accessibility, availability, and quality of diabetes self-management education (DSME) for uninsured adults or those utilizing Medicaid in a community with a high poverty rate. Methods A descriptive needs assessment was conducted in 8 health care agencies serving the uninsured. Face-to-face audiotaped interviews were conducted with 22 health care providers, educators, and administrators to capture descriptive characteristics about clinical care, DSME, continuity of care, and organizational function. Results Twenty-nine percent of adults with diabetes were reported to be uninsured or utilizing Medicaid in these settings. Only 4% of adults received the American Diabetes Association’s DSME standards of care. At 5 agencies, there was no direct access to DSME. Uninsured individuals had access to 2 programs; individuals utilizing Medicaid had access to 1 program. Certified diabetes educators were available at only 3 agencies. There were DSME programs that adhered to recommended guidelines but limited availability for these adults. The majority of education (86%) was limited to clinical encounters with providers, which were infrequent and variable in duration. Time spent on education ranged from 2 to 120 minutes depending on agency type. Education topics addressed by providers varied by agency. Conclusions Findings of this study suggest that adults who are utilizing Medicaid or are uninsured do not get the amount, type, or quality of DSME needed to sustain successful self-management. Limited availability and inadequate access to quality DSME place vulnerable adults at increased risk for devastating and costly complications despite the known benefits.
(1, 2)-Hamiltonian Completion on a Matching

We consider the problem of computing a minimum-weight Hamiltonian cycle on an undirected graph with edges' weights from set {0, 1, 2}, where 0-weight edges create a perfect matching of the graph. We provide a (4/3)-approximation algorithm and show that the problem is APX-complete.
Laser ablation for MEMS microfabrication on Si and Kapton substrates

Laser-ablation-based microfabrication technology is applied to fabricate micro-electro-mechanical-systems (MEMS) devices on polymer substrates. A micromachining apparatus is designed and developed which includes a 355 nm laser, an uncoated focusing lens, computer-controlled precision x-y-z stages and in-situ process monitoring systems. Concentric rings microstructures are formed by efficiently changing the laser intensity distribution. Tiny via holes and micro-nozzles with different diameters have been obtained by low power laser direct drilling. Optical microscopy and scanning electron microscopy (SEM) are used to evaluate the processing results at different laser processing parameters. This method has the advantages of low-cost and time-saving in circle via holes fabrications. Potential applications of this novel MEMS fabrication technique are also briefed.
Nondestructive Evaluation of Naval Munitions Using X-Ray CT

In this manuscript, we present experimental results from a nondestructive evaluation (NDE) system that is being used to inspect naval munition components, such as missile rocket motors. The X-ray computed tomography–based NDE (CT-NDE) system was developed by the NDE group at the Indian Head Division, Naval Surface Warfare Center (NSWC) in Indian Head, MD. The maximum likelihood (ML) method has been used successfully to reconstruct transmission images in a medical imaging modality known as positron emission tomography. Motivated by this fact, we use the ML method to reconstruct transmission images for the CT-NDE system at the Indian Head Division, NSWC and investigate its performance using experimental studies. From these studies, we preliminarily conclude that the ML method reconstructs transmission images with good quantitative accuracy and significant detail, even when there is limited angular sampling.
High strength bulk amorphous alloys with low critical cooling rates (overview)

This paper aims to review our recent research results on new amorphous alloys. The main topics consist of the following five parts ; (1) the finding of new amorphous alloys with extremely large glass-forming ability in a number of alloy systems, (2) the mechanism for the achievement of the large glass-forming ability, (3) the clarification of fundamental properties of the new amorphous alloys, (4) the successful examples of producing bulk amorphous alloys by four different techniques of water quenching, metallic mold casting, arc melting and unidirectional zone melting, and (5) the high tensile strength of the bulk amorphous alloys. These new results enable the elimination of the limitation of sample shape which has prevented the development of amorphous alloys as engineering materials and are expected to give rise to the revisit age to amorphous alloys.
Cognitive cooperative-jamming decision method based on bee colony algorithm

For the future information warfare, a single jamming mode is not effective due to the complex electromagnetic environment. With the rapid development of cognitive radio technology, collaborative jamming based on cognitive radio, namely cognitive jamming, has attracted wide attention in the field of electronic warfare. In collaborative jamming, the problem of decision-making based on collaboration becomes one of the key issues. Traditional decision-making based on ant colony algorithm takes too many iterations, which cannot always ensure the probability of optimization. Against the issue, this paper proposes a cognitive cooperative-jamming decision method based on bee colony algorithm, which searches the global optimum solution according to the process of the honey bee group looking for high quality sources. In the case of lack of prior condition, the proposed algorithm generates fitness function according to jamming effect. Then by the rule of greed, jamming decision matrix is decided according to jammer task allocation form. The role of bees in the proposed algorithm are changed between collection and observation, which is benefit to improve the convergence speed. By this way, it can improve the speed of convergence and find an optimal decision making scheme in the scenario with multiple jammer and multiple radar. Simulation results show that the proposed decision-making method can find the optimal decision scheme with the best jamming effect and has a fast convergence speed comparing with decision-making based on ant colony algorithm. The application of bee colony algorithm in the field of cooperative-jamming decision provides a new idea for jamming decision making.
Software Adaptation in Wireless Sensor Networks

We present design concepts, programming constructs, and automatic verification techniques to support the development of adaptive Wireless Sensor Network (WSN) software. WSNs operate at the interface between the physical world and the computing machine and are hence exposed to unpredictable environment dynamics. WSN software must adapt to these dynamics to maintain dependable and efficient operation. However, developers are left without proper support to develop adaptive functionality in WSN software. Our work fills this gap with three key contributions: (i) design concepts help developers organize the necessary adaptive functionality and understand their relations, (ii) dedicated programming constructs simplify the implementations, (iii) custom verification techniques allow developers to check the correctness of their design before deployment. We implement dedicated tool support to tie the three contributions, facilitating their practical application. Our evaluation considers representative WSN applications to analyze code metrics, synthetic simulations, and cycle-accurate emulation of popular WSN platforms. The results indicate that our work is effective in simplifying the development of adaptive WSN software; for example, implementations are provably easier to test and to maintain, the run-time overhead of our dedicated programming constructs is negligible, and our verification techniques return results in a matter of seconds.