A Study of Test Suite Reduction Based on Ant Lion Optimizer

The development of smart meters to Internet of Things is the infrastructure for the Internet to carry out user electricity management and enhance user experience with electricity. As the iteration of smart home service system based on smart meters continues to accelerate, the development process is becoming more and more demanding for software testing. Test suite reduction is one of the common methods to improve the efficiency of software testing. In this paper, we proposed an optimization algorithm based on the Ant Lion Optimizer applied to test suite reduction problem of smart IoT meters. The algorithm improved the traditional Ant Lion Optimizer by converting the smart IoT meter test suite reduction problem into a binary coverage problem and combining the Greedy Algorithm to obtain the optimal test case subset. The experimental results showed that the algorithm based on Ant Lion Optimizer performed better on the test suite reduction problems compared to similar algorithms

The effects of apoptosis vulnerability markers on the myocardium in depression after myocardial infarction

Background : There is an increased incidence of major depressive disorder (MDD) in individuals after myocardial infarction (MI), but the pathophysiological processes mediating this association are unclear. Our previous study demonstrated an increase in pro-apoptotic pathways in the myocardium and hippocampus in MDD, which was reversed by venlafaxine. This study aimed to attempt to confirm the effects of apoptosis vulnerability markers on the myocardium in a model of depression after myocardial infarction. Methods : Rats were divided into four groups: sham (N = 8), depression (N = 8, chronic mild unpredictable stress and separation were used in the depression group), MI (N = 13) and post-MI depression (N = 7). The rats in all four groups underwent the same open field and sucrose preference behavioral tests. Evan Blue staining was used to determine the area at risk of myocardial infarction in the left ventricle, and 2,3,5-triphenyl tetrazolium chloride (1.5% TTC) dye was used to detect the size of the myocardial infarction. The expression of bax and bcl-2 protein in the myocardium was investigated by immunohistochemistry, and the mRNA expression of bax, bcl-2 and caspase-3 in the myocardium was investigated by real time RT-PCR. Apoptosis was estimated in the myocardium by measuring the Bax:Bcl-2 ratio. Results : In the depression and post-MI depression rats, there were significantly decreased movements and total sucrose consumption, modeling behavioral deficits and an anhedonic-like state. In terms of myocardial infarction size, no difference was seen between the MI and post-MI depression groups. There was an up-regulated Bax:Bcl-2 ratio in the depression, MI and post-MI depression groups. Furthermore, in the latter group, there was a greater up-regulated Bax:Bcl-2 ratio. However, caspase-3 did not differ among the four groups. Conclusions : These results of this animal model suggest that active pro-apoptotic pathways may be involved in the nexus between myocardial infarction and depression. This mechanism may be germane to understanding this relationship in humans

Test Case Prioritization Based on Artificial Immune Algorithm

Regression testing is an essential and critical part of smart terminal program development. The test case suite is usually preprocessed by test case prioritization technology to improve the efficiency of regression testing. To address the problems of traditional genetic algorithm in solving the test case prioritization problem, this paper proposed a test case prioritization algorithm for intelligent terminal based on artificial immune algorithm. Firstly, different sequences of test case sets were used as the encoding of antibodies to initialize the antibody population; secondly, the Hemming distance was introduced as the concentration index of antibodies to calculate the incentive degree; finally, the antibodies were immunized to find the optimal test case set sequence. The experimental results showed that the algorithm based on the artificial immune algorithm was more capable of global search and less likely to fall into local optimum than the genetic algorithm, which indicated that the artificial immune algorithm was more stable and could better solve the test case prioritization problem

Assessing regional cerebral blood flow in depression using 320-slice computed tomography

While there is evidence that the development and course of major depressive disorder (MDD) symptomatology is associated with vascular disease, and that there are changes in energy utilization in the disorder, the extent to which cerebral blood flow is changed in this condition is not clear. This study utilized a novel imaging technique previously used in coronary and stroke patients, 320-slice Computed-Tomography (CT), to assess regional cerebral blood flow (rCBF) in those with MDD and examine the pattern of regional cerebral perfusion. Thirty nine participants with depressive symptoms (Hamilton Depression Rating Scale 24 (HAMD24) score >20, and Self-Rating Depression Scale (SDS) score >53) and 41 healthy volunteers were studied. For all subjects, 3 ml of venous blood was collected to assess hematological parameters. Trancranial Doppler (TCD) ultrasound was utilized to measure parameters of cerebral artery rCBFV and analyse the Pulsatility Index (PI). 16 subjects (8 =  MDD; 8 =  healthy) also had rCBF measured in different cerebral artery regions using 320-slice CT. Differences among groups were analyzed using ANOVA and Pearson\u27s tests were employed in our statistical analyses. Compared with the control group, whole blood viscosity (including high\middle\low shear rate)and hematocrit (HCT) were significantly increased in the MDD group. PI values in different cerebral artery regions and parameters of rCBFV in the cerebral arteries were decreased in depressive participants, and there was a positive relationship between rCBFV and the corresponding vascular rCBF in both gray and white matter. rCBF of the left gray matter was lower than that of the right in MDD. Major depression is characterized by a wide range of CBF impairments and prominent changes in gray matter blood flow. 320-slice CT appears to be a valid and promising tool for measuring rCBF, and could thus be employed in psychiatric settings for biomarker and treatment response purposes

Regional Cerebral Blood Flow in Mania: Assessment Using 320-Slice Computed Tomography

Objectives: While evidence that episodes of mania in bipolar I are associated with changes in bioenergetic and regional cerebral blood flow (rCBF) and cerebral blood flow velocity (rCBFV), both the regions and the extent of these changes have not yet been defined. Therefore, we determined the pattern of regional cerebral perfusion mania patients and using patients with major depressive disorder (MDD) as positive controls and healthy participants as negative controls.Methods: Twenty participants with mania, together with 22 MDD patients and 24 healthy volunteers, were recruited for this study. On all participants, Transcranial Doppler (TCD) was conducted to measure rCBFV parameters, 320-slice CT was conducted to measure rCBF in the different cerebral artery regions, and hematological parameters were assessed. ANOVA and Pearson's tests were used for the statistical analysis.Results: Our data indicated that rCBF in the medial temporal lobe and hippocampus, especially in the left medial temporal lobe and the right hippocampus, was increased in the mania group compared with the control and MDD groups (p < 0.01). In contrast, rCBF in the medial temporal lobe and hippocampus was decreased in the depression group (p < 0.01) compared with healthy controls. In addition, values of rCBFV in the bilateral internal carotid arteries (ICAs) and middle cerebral arteries (MCA) were increased in mania (p < 0.01) in comparison to the MDD group. Whole blood viscosity and hematocrit as well as red blood cell sedimentation rate remained unchanged in all group (p > 0.05).Conclusions: In mania, rCBF is increased in the medial temporal lobe and hippocampus, with a corresponding increase in rCBFV in the same regions

Altered cardiac autonomic nervous function in depression

Background:Depression is an independent risk factor for coronary artery disease. Autonomic instability may play a mediating or moderating role in this relationship; however this is not well understood. The objective of this study was to explore cardiac autonomic function and cardiac arrhythmia in depression, the correlation between depression severity and Heart Rate Variability (HRV) related indices, and the prevalence of arrhythmia.Methods:Individuals (n = 53) with major depression as assessed by the Diagnostic and Statistical Manual of Mental Disorders, who had a Hamilton Rating Scale for Depression (HAMD) score ≥20 and a Zung Self-Rating Depression Scale score > 53 were compared to 53 healthy individuals, matched for age and gender. Multichannel Electrocardiograph ECG-92C data were collected over 24 hours. Long-term changes in HRV were used to assess the following vagally mediated changes in autonomic tone, expressed as time domain indices: Standard deviation of the NN intervals (SDNN), standard deviation of 5 min averaged NN intervals (SDANN), Root Mean Square of the Successive Differences (RMSSD) and percentage of NN intervals > 50 ms different from preceding interval (pNN50). Pearson’s correlations were conducted to explore the strength of the association between depression severity (using the SDS and HRV related indices, specifically SDNN and low frequency domain / high frequency domain (LF/HF)).Results:The values of SDNN, SDANN, RMSSD, PNN50 and HF were lower in the depression group compared to the control group (P<.05). The mean value of the LF in the depression group was higher than the in control group (P<.05). Furthermore the ratio of LF/HF was higher among the depression group than the control group (P<.05). A linear relationship was shown to exist between the severity of the depression and HRV indices. In the depression group, the prevalence of arrhythmia was significantly higher than in the control group (P<.05), particularly supraventricular arrhythmias.Conclusions:Our findings suggest that depression is accompanied by dysfunction of the cardiac autonomic nervous system, and further, that depression severity is linked to severity of this dysfunction. Individuals with depression appear to be susceptible to premature atrial and/or ventricular disease

Optimization of Process Parameters for Pellet Production from Corn Stalk Rinds Using Box–Behnken Design

In the current study, corn stalk rinds were used as feedstock for the production of solid-fuel pellets. In an effort to comprehensively analyze the effects of different operational parameters on the physical properties of pellets, response surface methodology (RSM) was employed in conjunction with a Box–Behnken experimental design (BBD). By assessing multiple variables simultaneously and examining their interactions, BBD facilitates the development of a reliable response model that can predict how changes in independent variables will impact response variables. The recorded responses included relaxed density, mechanical durability, and compressive strength. Based on the results, greater R2 values of 0.9467, 0.8669, and 0.9196, could be, respectively, attained for the quadratic regression models. The analysis of variance revealed that all independent variables had significant effects on the responses. The optimal processing condition for the pellets was established by determining the ideal combination of operational parameters. The process entailed the choice of a particle dimension measuring 0.5 mm, a moisture level of 11.35%, the application of heat at 125.7 °C on the die, and the utilization of a molding pressure of 154.2 MPa. Based on these factors, the predicted response values were determined to be 1639.61 kg/m3 for relaxed density, 97.95% for mechanical durability, and 10.18 MPa for compressive strength. The values obtained experimentally under the optimized conditions were similar to the predicted values with a desirability value of 1.00