Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of processing parameters on weld forming in double-pulse MIG welding of aluminum alloy

Double-pulse MIG welding of aluminum alloy can improve the efficiency of welding and meanwhile get beautiful weld surface with scaly figures.Based on single-pulse welding,the experiments of double-pulse MIG welding of aluminum alloy were carried out by changing the current,high-frequency,low-frequency and welding velocity of the power which is the self-developed double-pulse MIG welding inverter power.Tests shows that strong/weak pulse peak current and high-frequency have great influence on the stability of welding process and spatters.When the difference between strong and weak pulse peak current is 40 A and high-frequency is 250 Hz,the weld forming is good.To a certain extent,the width of the scaly figure on the weld surface is directly related to low-frequency and welding velocity: the width of the scaly figure will decrease with the improvement of low-frequency and widen with acceleration of welding velocity.An empirical formula reflecting the relationship between low-frequency,welding velocity and the width of the scaly figure through statistical methods is obtained,and the results show that when the ratio of welding velocity to low-frequency is from 0.19 to 0.30,the width of the scaly figure is from 2 to 3 mm,which means good welding performance.
Fluorescent sensors of PARP-1 structural dynamics and allosteric regulation in response to DNA damage

Poly(ADP-ribose) (PAR) is a posttranslational modification predominantly synthesized by PAR polymerase-1 (PARP-1) in genome maintenance. PARP-1 detects DNA damage, and damage detection is coupled to a massive increase PAR production, primarily attached to PARP-1 (automodification). Automodified PARP-1 then recruits repair factors to DNA damage sites. PARP-1 automodification eventually leads to release from DNA damage thus turning off catalytic activity, although the effects of PAR on PARP-1 structure are poorly understood. The multiple domains of PARP-1 are organized upon detecting DNA damage, creating a network of domain contacts that imposes a major conformational transition in the catalytic domain that increases PAR production. Presented here are two novel fluorescent sensors that monitor the global and local structural transitions of PARP-1 that are associated with DNA damage detection and catalytic activation. These sensors display real-time monitoring of PARP-1 structural transitions upon DNA damage detection, and their reversal upon PARP-1 automodification. The fluorescent sensors are further used to investigate intramolecular and intermolecular PARP-1 activation, followed by the observation that intramolecular activation of PARP-1 is the predominant response to DNA strand breaks in cells. These results provide a unique perspective on the interplay between PARP-1 DNA damage recognition, allosteric regulation, and catalytic activity.
Estimating the prevalence of multiple diseases from two‐stage hierarchical pooling

Testing protocols in large‐scale sexually transmitted disease screening applications often involve pooling biospecimens (e.g., blood, urine, and swabs) to lower costs and to increase the number of individuals who can be tested. With the recent development of assays that detect multiple diseases, it is now common to test biospecimen pools for multiple infections simultaneously. Recent work has developed an expectation–maximization algorithm to estimate the prevalence of two infections using a two‐stage, Dorfman‐type testing algorithm motivated by current screening practices for chlamydia and gonorrhea in the USA. In this article, we have the same goal but instead take a more flexible Bayesian approach. Doing so allows us to incorporate information about assay uncertainty during the testing process, which involves testing both pools and individuals, and also to update information as individuals are tested. Overall, our approach provides reliable inference for disease probabilities and accurately estimates assay sensitivity and specificity even when little or no information is provided in the prior distributions. We illustrate the performance of our estimation methods using simulation and by applying them to chlamydia and gonorrhea data collected in Nebraska. Copyright © 2016 John Wiley & Sons, Ltd.
Towards robustness and self-organization of ESB-based solutions using service life-cycle management

Enterprise Service Bus (ESB) is a middleware infrastructure that provides a way to integrate loosely-coupled heterogeneous software applications based on the services principles. The life-cycle management of services in such environments is a critical issue for the component's reuse, maintenance and operation. This paper introduces a service life-cycle management module that extends the traditional functionalities with advanced monitoring and data analytics to contribute for the robustness, reliability and self-organization of networks of clusters based on ESB platforms. The realization of this module was embedded in the JBoss ESB, considering a sniffer mechanism to collect the service messages crossing the bus and a Liferay portal to display relevant information related to the services' health.
Human cytomegalovirus infection and colorectal cancer risk: a meta-analysis

Human cytomegalovirus infection (HCMV) has been recently considered as a factor for tumorigenesis. The current study used meta-analytical techniques to explore the prevalence of HCMV in tumor tissues and the relationship between human cytomegalovirus and colorectal cancer (CRC) risk. 11 studies detecting HCMV DNA in tumor tissues were included in meta-analysis. The prevalence rate and odds ratio (OR) were two main parameters. The overall prevalence of human cytomegalovirus DNA in tumor tissues were 27.5% (95% CI = 17.2%−37.8%). Binary logistic regression showed that the studies reported before 2010 involving formalin-fixed specimens from patients in developed region represented a lower proportion of HCMV. The tumor tissues had a significantly higher rate of virus infection compared with normal tissues (OR = 6.59, 95% CI = 4.48−9.69, I2 = 0%, P = 0.71). Subgroup analysis revealed the prevalence of the virus didn't differ in patients with different tumor stages, in tumor cells with different histologic grades, also in different kinds of specimen (polyp and adenocarcinoma). The results of current study suggested a statistically association between the virus infection and an increased risk of colorectal cancer.
On Dynamic Service Function Chain Deployment and Readjustment

Network function virtualization (NFV) is a promising technology to decouple the network functions from dedicated hardware elements, leading to the significant cost reduction in network service provisioning. As more and more users are trying to access their services wherever and whenever, we expect the NFV-related service function chains (SFCs) to be dynamic and adaptive, i.e., they can be readjusted to adapt to the service requests’ dynamics for better user experience. In this paper, we study how to optimize SFC deployment and readjustment in the dynamic situation. Specifically, we try to jointly optimize the deployment of new users’ SFCs and the readjustment of in-service users’ SFCs while considering the trade-off between resource consumption and operational overhead. We first formulate an integer linear programming (ILP) model to solve the problem exactly. Then, to reduce the time complexity, we design a column generation (CG) model for the optimization. Simulation results show that the proposed CG-based algorithm can approximate the performance of the ILP and outperform an existing benchmark in terms of the profit from service provisioning.
A differential memristive synapse circuit for on-line learning in neuromorphic computing systems

Spike-based learning with memristive devices in neuromorphic computing architectures typically uses learning circuits that require overlapping pulses from pre- and post-synaptic nodes. This imposes severe constraints on the length of the pulses transmitted in the network, and on the network’s throughput. Furthermore, most of these circuits do not decouple the currents flowing through memristive devices from the one stimulating the target neuron. This can be a problem when using devices with high conductance values, because of the resulting large currents. In this paper, we propose a novel circuit that decouples the current produced by the memristive device from the one used to stimulate the post-synaptic neuron, by using a novel differential scheme based on the Gilbert normalizer circuit. We show how this circuit is useful for reducing the effect of variability in the memristive devices, and how it is ideally suited for spike-based learning mechanisms that do not require overlapping pre- and post-synaptic pulses. We demonstrate the features of the proposed synapse circuit with SPICE simulations, and validate its learning properties with high-level behavioral network simulations which use a stochastic gradient descent learning rule in two benchmark classification tasks.
Changes in Brain Lateralization in Patients with Mild Cognitive Impairment and Alzheimer’s Disease: A Resting-State Functional Magnetic Resonance Study from Alzheimer’s Disease Neuroimaging Initiative

Purpose To detect changes in brain lateralization in patients with mild cognitive impairment (MCI) and Alzheimer’s disease (AD) using resting-state functional magnetic resonance imaging (fMRI). Materials and methods Data from 61 well-matched right-handed subjects were obtained from the Alzheimer’s Disease Neuroimaging Initiative, including 19 healthy controls (HCs), 25 patients with MCI, and 17 patients with AD. First, we divided 256 pairs of seed regions from each hemisphere covering the entire cerebral gray matter. Then, we used the intrinsic laterality index (iLI) approach to quantify the functional laterality using fMRI. One-way ANOVA was employed to estimate the differences in iLI among the three groups. The sum, number and mean value of the iLI were calculated within the thresholds of 0 < |iLI| < 0.2, 0.2 ≤ |iLI| < 0.4, 0.4 ≤ |iLI| < 0.8, and |iLI| ≥ 0.8, to explore the changes in the lateralization of resting-state brain function in patients with MCI and AD. Results One-way ANOVA revealed that the iLIs of the three groups were significantly different. The HCs showed a significant leftward interhemispheric difference within |iLI| ≥ 0.8. Compared with the HCs, the patients with MCI manifested a distinct abnormal rightward interhemispheric asymmetry, mainly within the thresholds of 0.2 ≤ |iLI| < 0.4 and 0.4 ≤ |iLI| < 0.8; in the patients with AD, the normal leftward lateralization that was observed in the HCs disappeared, and an abnormal rightward laterality was expressed within 0.4 ≤ |iLI| < 0.8. By directly comparing the patients with MCI with the patients with AD, an exclusive abnormal rightward laterality was observed in the patients with MCI within the 0.2 ≤ |iLI| < 0.4 threshold, and the normal leftward asymmetry vanished in the patients with AD within the |iLI| ≥ 0.8 threshold. Conclusion Global brain lateralization was different among three groups. The abnormal rightward dominance observed in the patients with MCI and AD may indicate that these patients use additional brain resources to compensate for the loss of cognitive function, and the observed disappearance of the leftward laterality in the patients with AD was likely associated with the damage in the left hemisphere. The observed disappearance of the rightward asymmetry in the patients with AD using the 0.2 ≤ |iLI| < 0.4 threshold was likely a sign of decompensation. Our study provides new insights that may improve our understanding of MCI and AD.
Using online social networks to build healthy communities: a design-based research investigation 1 Usando redes sociais online para a construção de comunidades saudáveis: um projeto de pesquisa

This paper discusses the design and evaluation of an online social network used within twenty- two established after school programs across three major urban areas in the Northeastern United States. The overall goal of this initiative is to empower students in grades K-8 to prevent obesity through healthy eating and exercise. The online social network was designed to support communication between program participants. Results from the related evaluation indicate that the online social network has potential for advancing awareness and community action around health related issues; however, greater attention is needed to professional development programs for program facilitators, and design features could better support critical thinking, social presence, and social activity.
Predicting Acute Exacerbations in Chronic Obstructive Pulmonary Disease

BACKGROUND: With increasing health care costs that have outpaced those of other industries, payers of health care are moving from a fee-for-service payment model to one in which reimbursement is tied to outcomes. Chronic obstructive pulmonary disease (COPD) is a disease where this payment model has been implemented by some payers, and COPD exacerbations are a quality metric that is used. Under an outcomes-based payment model, it is important for health systems to be able to identify patients at risk for poor outcomes so that they can target interventions to improve outcomes. OBJECTIVE: To develop and evaluate predictive models that could be used to identify patients at high risk for COPD exacerbations. METHODS: This study was retrospective and observational and included COPD patients treated with a bronchodilator-based combination therapy. We used health insurance claims data to obtain demographics, enrollment information, comorbidities, medication use, and health care resource utilization for each patient over a 6-month baseline period. Exacerbations were examined over a 6-month outcome period and included inpatient (primary discharge diagnosis for COPD), outpatient, and emergency department (outpatient/emergency department visits with a COPD diagnosis plus an acute prescription for an antibiotic or corticosteroid within 5 days) exacerbations. The cohort was split into training (75%) and validation (25%) sets. Within the training cohort, stepwise logistic regression models were created to evaluate risk of exacerbations based on factors measured during the baseline period. Models were evaluated using sensitivity, specificity, and positive and negative predictive values. The base model included all confounding or effect modifier covariates. Several other models were explored using different sets of observations and variables to determine the best predictive model. RESULTS: There were 478,772 patients included in the analytic sample, of which 40.5% had exacerbations during the outcome period. Patients with exacerbations had slightly more comorbidities, medication use, and health care resource utilization compared with patients without exacerbations. In the base model, sensitivity was 41.6% and specificity was 85.5%. Positive and negative predictive values were 66.2% and 68.2%, respectively. Other models that were evaluated resulted in similar test characteristics as the base model. CONCLUSIONS: In this study, we were not able to predict COPD exacerbations with a high level of accuracy using health insurance claims data from COPD patients treated with bronchodilator-based combination therapy. Future studies should be done to explore predictive models for exacerbations.
Generalized carrier based pulse width modulation technique for a three to n-phase dual matrix converter

This paper presents a novel topology for a dual three to n-phase direct matrix converter. The term "n" can be used for any number of output phases. The dual matrix converter topology is applied for open-end winding drive system in order to enhance output voltage and simultaneously eliminate common-mode voltage at the machine terminals. The input to each of the matrix converter is three phase utility grid system, whereas the output can be configured to any number of phases with variable voltage and frequency. Generalized carrier based pulse width modulation (PWM) technique is developed to control the dual matrix converters. A dual three to nine-phase matrix converter is utilized for discussion and analysis. The two matrix converters feeding the nine-phase open-end load are supplied from a common single three-phase utility source of 50 Hz. A simple R-L load is considered in the paper. The paper presents an analytical approach to obtain the expression of modulating signals that are used to generate switching pulses for the matrix converter. Simulation and experimental results are presented to support the idea of the proposed modulation scheme.
Learning to select computations

Efficient use of limited computational resources is essential to intelligence. Selecting computations optimally according to rational metareasoning would achieve this, but rational metareasoning is computationally intractable. Inspired by psychology and neuroscience, we propose the first learning algorithm for approximating the optimal selection of computations. We derive a general, sample-efficient reinforcement learning algorithm for learning to select computations from the insight that the value of computation lies between the myopic value of computation and the value of perfect information. We evaluate the performance of our method against two state-of-the-art methods for approximate metareasoning--the meta-greedy heuristic and the blinkered policy--on three increasingly difficult metareasoning problems: metareasoning about when to terminate computation, metareasoning about how to choose between multiple actions, and metareasoning about planning. Across all three domains, our method achieved near-optimal performance and significantly outperformed the meta-greedy heuristic. The blinkered policy performed on par with our method in metareasoning about decision-making, but it is not directly applicable to metareasoning about planning where our method outperformed both the meta-greedy heuristic and a generalization of the blinkered policy. Our results are a step towards building self-improving AI systems that can learn to make optimal use of their limited computational resources to efficiently solve complex problems in real-time.
Modified Descemet's Stripping Automated Endothelial Keratoplasty: The Use of Ophthalmic Viscoelastic Devices in Hypotonic Eyes That Had Undergone Glaucoma Filtering Surgeries

Purpose Descemet's stripping automated endothelial keratoplasty (DSAEK) is more difficult in hypotonic eyes with filtering bleb, due to the difficulties in elevating the intraocular pressure (IOP). We report a new method that uses ophthalmic viscoelastic devices (OVDs) to achieve good graft adhesion. Case Presentation We performed modified DSAEK surgery on 2 eyes of 2 patients, who had previously undergone a trabeculectomy. Both eyes had functioning filtering blebs; the IOP was lower than 10 mmHg without medication. After the graft was inserted into the anterior chamber, the conjunctiva was penetrated, apart from the bleb, using a 30 G needle, and Healon V® was injected into the bleb until the encapsulated space was filled completely. Air was subsequently injected into the anterior chamber to promote the graft attachment to the back surface of the cornea. The IOP was elevated above 40 mmHg in both eyes 1 h after surgery and then decreased to less than 30 mmHg over the subsequent 3 h period. The implanted graft showed good adhesion and no dislocation. Conclusions Our novel DSAEK procedure that adds one step of OVD injection into the filtering bleb may be useful for hypotonic eyes that had undergone filtering surgeries.
Continuous Glucose Monitoring

The necessity of strict glycemic control is unquestionable. However, hypoglycemia remains a major limiting factor in achieving satisfactory glucose control, and evidence is mounting to show that hypoglycemia is not benign. Over the past decade, evidence has consistently shown that real-time continuous glucose monitoring improves glycemic control in terms of lowering glycated hemoglobin levels. However, real-time continuous glucose monitoring has not met the expectations of the diabetes community with regard to hypoglycemia prevention. The earlier trials did not demonstrate any effect on either mild or severe hypoglycemia and the effect of real-time continuous glucose monitoring on nocturnal hypoglycemia was often not reported. However, trials specifically designed to reduce hypoglycemia in patients with a high hypoglycemia risk have demonstrated a reduction in hypoglycemia, suggesting that real-time continuous glucose monitoring can prevent hypoglycemia when it is specifically used for that purpose. Moreover, the newest generation of diabetes technology currently available commercially, namely sensor-augmented pump therapy with a (predictive) low glucose suspend feature, has provided more convincing evidence for hypoglycemia prevention. This article provides an overview of the hypoglycemia outcomes of randomized controlled trials that investigate the effect of real-time continuous glucose monitoring alone or sensor-augmented pump therapy with a (predictive) low glucose suspend feature. Furthermore, several possible explanations are provided why trials have not shown a reduction in severe hypoglycemia. In addition, existing evidence is presented of real-time continuous glucose monitoring in patients with impaired awareness of hypoglycemia who have the highest risk of severe hypoglycemia.
Role of &ggr;-glutamyl cyclotransferase as a therapeutic target for colorectal cancer based on the lentivirus-mediated system

Human GGCT (&ggr;-glutamyl cyclotransferase) has been shown to be upregulated in most tumors, but its role in colorectal cancer (CRC) is poorly understood. Thus, CRC cell lines, including HCT116 and SW1116, were chosen to investigate the role of GGCT by constructing a GGCT silencing cells model using lentivirus-mediated RNA interference. The knockdown efficiency was confirmed by reverse transcription-quantitative PCR and a western blot assay. Then, a set of biological functions of GGCT silencing on CRC cell was assessed by MTT, colony-formation assay, and flow cytometry analysis. Further, western blot and Pathscan intracellular signaling were used to detect intracellular signaling associated with cell growth and apoptosis induced by GGCT knockdown. In addition, the clinical chemotherapeutic drug 5-fluorouracil was used to investigate the impact of GGCT silencing on drug sensitivity by an Annexin V/7-AAD double-staining assay. The results of the analysis indicated that GGCT silencing significantly suppressed cell proliferation and arrested cell cycle at the G0/G1 phase by regulating the expression of p21, p27, and cyclin E. Moreover, GGCT silencing triggered the apoptosis of CRC cells by activating caspase-3 and cleaved poly-ADP-ribose polymerase pathways and downregulating the phosphorylation proline-rich Akt substrate of 40 kDa (PRAS40) expression levels. Furthermore, GGCT silencing combined with 5-fluorouracil treatment further induced the apoptotic rate of CRC cells. These findings suggest that GGCT may be a promising diagnostic and therapeutic target for CRC by activating the apoptotic pathway.