An analysis of task assignment and cycle times when robots are added to human-operated assembly lines, using mathematical programming models

Abstract Adding robots to a human-operated assembly line influences both the short- and long-term operation of the line. However, the effects of robots on assembly line capacity and on cycle time can only be studied if appropriate task assignment models are available. This paper shows how traditional assembly line balancing models can be changed in order to determine the optimal number of workstations and cycle time when robots with different technological capabilities are able to perform a predetermined set of tasks. The mathematical programming models for the following three cases are presented and analysed: i) only workers are assigned to the workstations; ii) either a worker or a robot is assigned to a workstation; iii) a robot and a worker are also assigned to specific workstations. The data of an assembly line producing power inverters is used to illustrate the proposed calculations. Both the assignment of tasks and the changes of cycle time are analysed within the AIMMS modelling environment. The computational characteristics of the proposed mathematical programming models are also examined and tested using benchmark problems. The models presented in this paper can assist operations management in making decisions relating to assembly line configuration

Exponential Random Graph Modeling for Complex Brain Networks

Exponential random graph models (ERGMs), also known as p* models, have been utilized extensively in the social science literature to study complex networks and how their global structure depends on underlying structural components. However, the literature on their use in biological networks (especially brain networks) has remained sparse. Descriptive models based on a specific feature of the graph (clustering coefficient, degree distribution, etc.) have dominated connectivity research in neuroscience. Corresponding generative models have been developed to reproduce one of these features. However, the complexity inherent in whole-brain network data necessitates the development and use of tools that allow the systematic exploration of several features simultaneously and how they interact to form the global network architecture. ERGMs provide a statistically principled approach to the assessment of how a set of interacting local brain network features gives rise to the global structure. We illustrate the utility of ERGMs for modeling, analyzing, and simulating complex whole-brain networks with network data from normal subjects. We also provide a foundation for the selection of important local features through the implementation and assessment of three selection approaches: a traditional p-value based backward selection approach, an information criterion approach (AIC), and a graphical goodness of fit (GOF) approach. The graphical GOF approach serves as the best method given the scientific interest in being able to capture and reproduce the structure of fitted brain networks

EEG Reactivity Predicts Individual Efficacy of Vagal Nerve Stimulation in Intractable Epileptics.

Background: Chronic vagal nerve stimulation (VNS) is a well-established non-pharmacological treatment option for drug-resistant epilepsy. This study sought to develop a statistical model for prediction of VNS efficacy. We hypothesized that reactivity of the electroencephalogram (EEG) to external stimuli measured during routine preoperative evaluation differs between VNS responders and non-responders. Materials and Methods: Power spectral analyses were computed retrospectively on pre-operative EEG recordings from 60 epileptic patients with VNS. Thirty five responders and 25 non-responders were compared on the relative power values in four standard frequency bands and eight conditions of clinical assessment—eyes opening/closing, photic stimulation, and hyperventilation. Using logistic regression, groups of electrodes within anatomical areas identified as maximally discriminative by n leave-one-out iterations were used to classify patients. The reliability of the predictive model was verified with an independent data-set from 22 additional patients. Results: Power spectral analyses revealed significant differences in EEG reactivity between responders and non-responders; specifically, the dynamics of alpha and gamma activity strongly reflected VNS efficacy. Using individual EEG reactivity to develop and validate a predictive model, we discriminated between responders and non-responders with 86% accuracy, 83% sensitivity, and 90% specificity. Conclusion: We present a new statistical model with which EEG reactivity to external stimuli during routine presurgical evaluation can be seen as a promising avenue for the identification of patients with favorable VNS outcome. This novel method for the prediction of VNS efficacy might represent a breakthrough in the management of drug-resistant epilepsy, with wide-reaching medical and economic implications

Effect of weight loss on HDL-apoA-II kinetics in the metabolic syndrome

Reduced HDL (high-density lipoprotein) concentration in the MetS (metabolic syndrome) is associated with increased risk of cardiovascular disease and is related to defects in HDL-apoA-II (apolipoprotein A-II) kinetics. Dietary restriction is the most commonly used weight loss strategy. In the present study, we examined the effect of weight loss on HDL-apoA-II kinetics in men with the MetS at the start and end of a 16-week intervention trial of a hypocaloric low-fat diet (n=20) compared with a weight maintenance diet (n=15), using a stable isotope technique and compartmental modelling. The low-fat diet achieved a significant reduction (P<0.01) in BMI (body mass index), abdominal fat compartments and HOMA (homoeostasis model assessment) score compared with weight maintenance. Weight loss also significantly (P<0.05) decreased both the production rate (−23%) and FCR (fractional catabolic rate) (−12%) of HDL-apoA-II, accounting for a net decrease in apoA-II concentration (−9%). Reductions in the HDL-apoA-II production rate were significantly associated with changes in body weight (r=0.683, P<0.01), plasma triacylglycerols (triglycerides) (r=0.607, P<0.01) and, to a lesser extent, plasma insulin (r=0.440, P=0.059) and HOMA-IR (HOMA of insulin resistance) (r=0.425, P=0.069). Changes in the apoA-II FCR were also significantly associated with reductions in visceral adipose tissue mass (r=0.561, P=0.010). In conclusion, in obese men with the MetS, short-term weight loss with a low-fat low-caloric diet lowers plasma apoA-II concentrations by decreasing both the production and catabolism of HDL-apoA-II. The cardiometabolic significance of this effect on HDL metabolism remains to be investigated further

Low Adiponectin Levels Are an Independent Predictor of Mixed and Non-Calcified Coronary Atherosclerotic Plaques

Atherosclerosis is the primary cause of coronary artery disease (CAD). There is increasing recognition that lesion composition rather than size determines the acute complications of atherosclerotic disease. Low serum adiponectin levels were reported to be associated with coronary artery disease and future incidence of acute coronary syndrome (ACS). The impact of adiponectin on lesion composition still remains to be determined. We measured serum adiponectin levels in 303 patients with stable typical or atypical chest pain, who underwent dual-source multi-slice CT-angiography to exclude coronary artery stenosis. Atherosclerotic plaques were classified as calcified, mixed or non-calcified. In bivariate analysis adiponectin levels were inversely correlated with total coronary plaque burden (r = -0.21, p = 0.0004), mixed (r = -0.20, p = 0.0007) and non-calcified plaques (r = -0.18, p = 0.003). No correlation was seen with calcified plaques (r = -0.05, p = 0.39). In a fully adjusted multivariate model adiponectin levels remained predictive of total plaque burden (estimate: -0.036, 95%CI: -0.052 to -0.020, p<0.0001), mixed (estimate: -0.087, 95%CI: -0.132 to -0.042, p = 0.0001) and non-calcified plaques (estimate: -0.076, 95%CI: -0.115 to -0.038, p = 0.0001). Adiponectin levels were not associated with calcified plaques (estimate: -0.021, 95% CI: -0.043 to -0.001, p = 0.06). Since the majority of coronary plaques was calcified, adiponectin levels account for only 3% of the variability in total plaque number. In contrast, adiponectin accounts for approximately 20% of the variability in mixed and non-calcified plaque burden. Adiponectin levels predict mixed and non-calcified coronary atherosclerotic plaque burden. Low adiponectin levels may contribute to coronary plaque vulnerability and may thus play a role in the pathophysiology of ACS

The impact of intragenic CpG content on gene expression

The development of vaccine components or recombinant therapeutics critically depends on sustained expression of the corresponding transgene. This study aimed to determine the contribution of intragenic CpG content to expression efficiency in transiently and stably transfected mammalian cells. Based upon a humanized version of green fluorescent protein (GFP) containing 60 CpGs within its coding sequence, a CpG-depleted variant of the GFP reporter was established by carefully modulating the codon usage. Interestingly, GFP reporter activity and detectable protein amounts in stably transfected CHO and 293 cells were significantly decreased upon CpG depletion and independent from promoter usage (CMV, EF1α). The reduction in protein expression associated with CpG depletion was likewise observed for other unrelated reporter genes and was clearly reflected by a decline in mRNA copy numbers rather than translational efficiency. Moreover, decreased mRNA levels were neither due to nuclear export restrictions nor alternative splicing or mRNA instability. Rather, the intragenic CpG content influenced de novo transcriptional activity thus implying a common transcription-based mechanism of gene regulation via CpGs. Increased high CpG transcription correlated with changed nucleosomal positions in vitro albeit histone density at the two genes did not change in vivo as monitored by ChIP

TM6SF2 rs58542926 influences hepatic fibrosis progression in patients with non-alcoholic fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) is an increasingly common condition, strongly associated with the metabolic syndrome, that can lead to progressive hepatic fibrosis, cirrhosis and hepatic failure. Subtle inter-patient genetic variation and environmental factors combine to determine variation in disease progression. A common non-synonymous polymorphism in TM6SF2 (rs58542926 c.449 C>T, p.Glu167Lys) was recently associated with increased hepatic triglyceride content, but whether this variant promotes clinically relevant hepatic fibrosis is unknown. Here we confirm that TM6SF2 minor allele carriage is associated with NAFLD and is causally related to a previously reported chromosome 19 GWAS signal that was ascribed to the gene NCAN. Furthermore, using two histologically characterized cohorts encompassing steatosis, steatohepatitis, fibrosis and cirrhosis (combined n=1,074), we demonstrate a new association, independent of potential confounding factors (age, BMI, type 2 diabetes mellitus and PNPLA3 rs738409 genotype), with advanced hepatic fibrosis/cirrhosis. These findings establish new and important clinical relevance to TM6SF2 in NAFLD

On the Role of the Striatum in Response Inhibition

BACKGROUND: Stopping a manual response requires suppression of the primary motor cortex (M1) and has been linked to activation of the striatum. Here, we test three hypotheses regarding the role of the striatum in stopping: striatum activation during successful stopping may reflect suppression of M1, anticipation of a stop-signal occurring, or a slower response build-up. METHODOLOGY/PRINCIPAL FINDINGS: Twenty-four healthy volunteers underwent functional magnetic resonance imaging (fMRI) while performing a stop-signal paradigm, in which anticipation of stopping was manipulated using a visual cue indicating stop-signal probability, with their right hand. We observed activation of the striatum and deactivation of left M1 during successful versus unsuccessful stopping. In addition, striatum activation was proportional to the degree of left M1 deactivation during successful stopping, implicating the striatum in response suppression. Furthermore, striatum activation increased as a function of stop-signal probability and was to linked to activation in the supplementary motor complex (SMC) and right inferior frontal cortex (rIFC) during successful stopping, suggesting a role in anticipation of stopping. Finally, trial-to-trial variations in response time did not affect striatum activation. CONCLUSIONS/SIGNIFICANCE: The results identify the striatum as a critical node in the neural network associated with stopping motor responses. As striatum activation was related to both suppression of M1 and anticipation of a stop-signal occurring, these findings suggest that the striatum is involved in proactive inhibitory control over M1, most likely in interaction with SMC and rIFC

Recent Advances in Conjugated Polymers for Light Emitting Devices

A recent advance in the field of light emitting polymers has been the discovery of electroluminescent conjugated polymers, that is, kind of fluorescent polymers that emit light when excited by the flow of an electric current. These new generation fluorescent materials may now challenge the domination by inorganic semiconductor materials of the commercial market in light-emitting devices such as light-emitting diodes (LED) and polymer laser devices. This review provides information on unique properties of conjugated polymers and how they have been optimized to generate these properties. The review is organized in three sections focusing on the major advances in light emitting materials, recent literature survey and understanding the desirable properties as well as modern solid state lighting and displays. Recently, developed conjugated polymers are also functioning as roll-up displays for computers and mobile phones, flexible solar panels for power portable equipment as well as organic light emitting diodes in displays, in which television screens, luminous traffic, information signs, and light-emitting wallpaper in homes are also expected to broaden the use of conjugated polymers as light emitting polymers. The purpose of this review paper is to examine conjugated polymers in light emitting diodes (LEDs) in addition to organic solid state laser. Furthermore, since conjugated polymers have been approved as light-emitting organic materials similar to inorganic semiconductors, it is clear to motivate these organic light-emitting devices (OLEDs) and organic lasers for modern lighting in terms of energy saving ability. In addition, future aspects of conjugated polymers in LEDs were also highlighted in this review