The optical–neural-network logic gates using unsupervised learning method and supervised learning method are investigated. The structures of the optical neurons using self-connection configuration ...and interconnection configuration are proposed. The performance of the AND, OR, NAND, NOR and XOR logic gates are analyzed. According to our simulation results, the bit error ratio (BER) of the optical neurons using the interconnection configuration is lower than that using self-connection configuration. For OR logic gate, the best performance is BER = 6.54%. For XOR logic gate, the best performance is BER < 4.89 × 10−5. The results show that the proposed optical structure can work for different logic gates by tuning the parameters of the couplers and the phase shifters.
•The optical structures of our optical neural networks with interconnection and self-connection configurations are proposed. The synergy of two neurons which process the input data together is better than the neurons working independently.•The OR and XOR logic gates, which are trained by unsupervised learning method are designed using the same optical structure with different coupling ratios of couples and different phase delays of phase modulators. These two logic gates can be fabricated with the same manufacturing process.•Since the optical setup can achieve OR and XOR logic devices, the manufacturing process and the cost of this optical integrated circuit could be simpler and cheaper than electric circuits. Moreover, the computing speed of our optical logic gates could be higher than that of electronic circuits.
To date, there is limited evidence on the antidepressant effects of memantine in patients with major mental diseases. We conducted a systematic review and meta-analysis to assess the efficacy of ...memantine in such populations.
A literature search was performed for randomized controlled trials (RCTs) from the date of their inception until September 28, 2021, using PubMed, Medline, Embase, and the Cochrane Library. Changes in depression scores were the primary outcome. The response rate and remission rate to the treatment were secondary outcomes. We also assessed the dropout rate for tolerance.
Eleven double-blind RCTs were included with 899 participants. Memantine significantly reduced depressive symptom scores compared with the control group (k = 11, n = 899, Hedges' g = −0.17, 95% confidence interval CI = −0.30 to −0.04, p = 0.009) with a small effect size. For secondary outcomes, memantine did not show a significant effect on response rate nor remission rate. In the subgroup analysis, memantine significantly reduced depressive symptom scores in patients with mood disorders (k = 8, n = 673, Hedges' g = −0.17, 95% CI = −0.32 to −0.01, p = 0.035) with a small effect size, but not in patients with schizophrenia.
The present meta-analysis indicates that memantine effectively alleviates depressive symptoms in patients with mood disorders with a small effect size. Furthermore, memantine is well-tolerated and acceptable.
•Memantine improved depressive symptoms in patients with major mental diseases with a small effect size.•Memantine did not show a significant effect on response rate or remission rate in depressive symptoms in patients with major mental diseases.•Memantine improved the depressive symptoms in mood disorder, but only with a trend in schizophrenia.
We propose a design for an all-optical logic exclusive-OR (XOR) gate in terms of intensity-modulation or phase-modulation approaches. In this study, the unsupervised optical neuron networks (ONNs) ...are based on reservoir computing (RC) and the echo state networks (ESNs). Thanks to the optical interfering effect in the directional coupler, it provides a nonlinear function for the reservoir computing. By scanning the phase through the phase shifter in our optical neuron networks, we find the optimized results and demonstrate the relationship between the input and output signals. The simulated results match the truth logic table in XOR gate. We also demonstrate the bit error ratio (BER) of the all-optical logic XOR gate. The BER for intensity-modulation approach is 1.55% at 90 degree, and the phase-modulation approach is 1.78% at 91 degree. Thus, the simulated results also indicate that the optical neuron network has potential to achieve an optical integrated circuit. If this idea could be fabricated as an optical logic device, the processing rate in the ONN is in light frequency. It will help us to process the binary data sequence more efficiently.
Objective
We aimed to examine the factors associated with treatment outcomes in patients with Alzheimer's disease (AD) after 1 year of acetylcholinesterase inhibitors (AChEI) treatment.
Method
We ...obtained electronic medical records from a medical center in Southern Taiwan between January 2015 and September 2021. Participants aged ≥60 who were newly diagnosed with AD and had been prescribed AChEIs were included. Cognitive assessments were performed before the AChEIs were prescribed and at the 1 year follow‐up. Cognition progressors were defined as a Mini‐Mental State Examination decline of >3 or a Clinical Dementia Rating decline of ≥1 after 1 year of AChEI treatment. The relationship between the baseline characteristics and cognitive status after follow‐up was investigated using logistic regression analysis after adjusting for potential confounders.
Results
A total of 1370 patients were included in our study (mean age, 79.86 ± 8.14 years). After adjustment, the body mass index (BMI) was found to be significantly lower in the progressor group adjusted odds ratio (AOR): 0.970, 95% confidence intervals (95% CIs): 0.943 to 0.997, P = 0.033. The usage of antipsychotics was significantly higher in the progressor group (AOR: 1.599, 95% CIs: 1.202 to 2.202, P = 0.001). The usage of benzodiazepine receptor agonists also tended to be significantly higher in the progressor group (AOR: 1.290, 95% CIs: 0.996 to 1.697, p = 0.054).
Conclusion
These results suggest that patients with AD who receive 1 year of AChEI treatment and have a lower BMI or concurrent treatment with antipsychotics and benzodiazepine receptor agonists are more likely to suffer from cognitive decline.
AD patient's who treated with acetylcholinesterase inhibitors and have a lower body mass index or concurrent treatment with antipsychotics and benzodiazepine receptor agonists are more likely to suffer from cognitive decline.
Objective
We aimed to investigate the efficacy and tolerability of cranial electrotherapy stimulation (CES) for patients with anxiety symptoms.
Method
We searched the Pubmed, Cochrane Central ...Register of Controlled Trials (CENTRAL), Embase and Medline for randomized control trials (RCTs) from the time of inception until November 15, 2021, following Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Data were pooled using a random-effects model. The primary outcomes were the mean change scores for anxiety symptoms. The secondary outcomes were the mean change scores for depressive symptoms.
Results
Eleven RCTs were eligible (
n
= 794, mean age: 41.4, mean population of female: 64.8%). CES significantly reduced the anxiety symptoms compared to the control group
k
= 11,
n
= 692, Hedge's g = −0.625, 95% confidence intervals (CIs) = −0.952 to −0.298,
P
< 0.001 with moderate effect size. The subgroup analysis showed that CES reduced both primary and secondary anxiety (primary anxiety,
k
=3,
n
= 288, Hedges' g = −1.218, 95% CIs = −1.418 to −0.968,
P
= 0.007; secondary anxiety,
k
= 8,
n
= 504, Hedges' g = −0.334, 95% CIs = −0.570 to −0.098,
P
= 0.006). After performing between group analysis, we found CES has significant better efficacy for patients with primary anxiety than those with secondary anxiety (
P
< 0.001). For secondary outcome, CES significantly reduced depressive symptoms in patients with anxiety disorders (
k
= 8,
n
= 552, Hedges' g = −0.648, 95% CIs = −1.062 to −0.234,
P
= 0.002). No severe side effects were reported and the most commonly reported adverse events were ear discomfort and ear pain.
Conclusion
We found CES is effective in reducing anxiety symptoms with moderate effect size in patients with both primary and secondary anxiety. Furthermore, CES was well-tolerated and acceptable.
Systematic Review Registration:
PROSPERO,
https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021267916
.
This study aimed to investigate the efficacy of repetitive transcranial magnetic stimulation (rTMS) in treating suicidal ideation in patients with mental illness.
We followed the Preferred Reporting ...Items for Systematic Reviews and Meta-Analyses guidelines. Major electronic databases were systematically searched from the time of their inception until July 22, 2021. The primary outcome was the mean change in the scores for suicidal ideation. The secondary outcome was the mean change in depression severity.
Ten randomized controlled trials were eligible with 415 participants in the active treatment group (mean age = 53.78 years; mean proportion of women = 54.5%) and 387 participants in the control group (mean age = 55.52 years; mean proportion of women = 51.78%). rTMS significantly reduced suicidal ideation (k = 10,
= 802, Hedges' g = -0.390, 95% confidence interval CI = -0.193 to -0.588,
<.001) and severity of depressive symptoms (k = 9,
= 761, Hedges' g = -0.698, 95% CI = -1.023 to -0.372,
< 0.001) in patients with major mental disorders. In the subgroup analysis, rTMS reduced suicidal ideation among patients with non-treatment-resistant depression (non-TRD) (-0.208) but not in those with TRD. rTMS as combination therapy had a larger effect than did monotherapy (-0.500 vs. -0.210). Suicidal ideation significantly reduced in patients receiving more than ten treatment sessions (-0.255). Importantly, the rTMS group showed favorable tolerability without major adverse events.
The study showed that rTMS was effective and well-tolerated in reducing suicidal ideation and depression severity in patients with major mental disorders.
The negative fixed charge density contributed by graphene oxide is estimated as high as 6 x 10 12 cm −2 . Graphene oxide is therefore a promising candidate for Si solar cell passivation. However, ...the high-temperature steps for manufacturing commercial Si solar cells would change the composition of graphene oxide. Therefore, graphene oxide cannot be directly adopted by commercial PERC manufacturers with the high-temperature firing step after the rear passivation step. To suppress the high-temperature degradation, we have deposited the graphene oxide on the rear surface of commercial IBC cells directly, and V oc , J sc and efficiency of the cell all improved after 100 μL graphene oxide deposition. Graphene oxide can be adopted as the passivation material of commercial cells as long as the high-temperature process on graphene oxide can be suppressed.
To investigate the Green House Gas (GHG) emissions from rivers in Taiwan, environmental conditions, water qualities, and emissions of CO2 and CH4 were determined in the Tanswei River of Northern ...Taiwan, and the correlations between GHG emissions and water quality were also studied. Atmospheric CO2 concentrations were 347.4-409.7, 342.8-417.3 and 348.5-417.0 ppm in the up–, mid– and down–stream areas, respectively; while atmospheric CH4 concentrations were 1.59-1.98, 1.74-2.20 and 1.60-2.43 ppm, respectively. Using the headspace method with brown color bottle, CO2 concentrations were 665–6 917, 1 485–9 369 and 1 443–9 637 ppm, respectively; while CH4 concentrations fell into the range of 11.8-309.0, 66.0-6 288.2 and 24.1-4 627.5 ppm, respectively. Using the static–chamber method, CO2 emission rates were -22.3-140.5, -31.7-194.7 and -27.5-226.6mg m-2 h-1, respectively; and CH4 emission rates were 0.02-5.52, 1.55-144.54 and 0.11-14.10mg m-2 h-1, respectively. CO2 and CH4 emission rates had higher values in the mid– and down–stream areas than those in the up–stream area because of the input of industrial, livestock and domestic wastewaters in mid– and down–stream areas. CO2 emission rates were negative might be because of the measurement times were at noon and some photosynthetic microbes and microalgae in the water were undergoing active photosynthesis. There is a good correlation between the results of headspace and static–chamber methods. CO2 emissions had very significant positive correlations with Biochemical Oxygen Demand (BOD) and Suspended Organic Matter (SOM); and significant negative correlation with Dissolved Oxygen (DO). CH4 emission had very significant positive correlations with BOD, SOM and ammonium nitrogen (NH4-N); significant positive correlation with Suspended Inorganic Matter (SIM); very significant negative correlation with DO; and significant negative correlation with redox potential (Eh). DO, Eh, SOM, SIM and NH4-N were the major factors that affected CO2 and CH4 emissions from water. In the assessment of carbon deposited amount from river to ocean, the annual carbon flows of Tanswei River were estimated with the annual flow amounts and COD, it were 8.9×103, 1.8×104, 3.9×104, 2.7×104 and 1.2×104 tons in 2003, 2004, 2005, 2006 and 2007, respectively.
Rather than detecting defects at an early stage to reduce their impact, defect prevention means that defects are prevented from occurring in advance. Causal analysis is a common approach to discover ...the causes of defects and take corrective actions. However, selecting defects to analyze among large amounts of reported defects is time consuming, and requires significant effort. To address this problem, this study proposes a defect prediction approach where the reported defects and performed actions are utilized to discover the patterns of actions which are likely to cause defects. The approach proposed in this study is adapted from the Action-Based Defect Prediction (ABDP), an approach uses the classification with decision tree technique to build a prediction model, and performs association rule mining on the records of actions and defects. An action is defined as a basic operation used to perform a software project, while a defect is defined as software flaws and can arise at any stage of the software process. The association rule mining finds the maximum rule set with specific minimum support and confidence and thus the discovered knowledge can be utilized to interpret the prediction models and software process behaviors. The discovered patterns then can be applied to predict the defects generated by the subsequent actions and take necessary corrective actions to avoid defects.
The proposed defect prediction approach applies association rule mining to discover defect patterns, and multi-interval discretization to handle the continuous attributes of actions. The proposed approach is applied to a business project, giving excellent prediction results and revealing the efficiency of the proposed approach. The main benefit of using this approach is that the discovered defect patterns can be used to evaluate subsequent actions for in-process projects, and reduce variance of the reported data resulting from different projects. Additionally, the discovered patterns can be used in causal analysis to identify the causes of defects for software process improvement.
In addition to degrading the quality of software products, software defects also require additional efforts in rewriting software and jeopardize the success of software projects. Software defects ...should be prevented to reduce the variance of projects and increase the stability of the software process. Factors causing defects vary according to the different attributes of a project, including the experience of the developers, the product complexity, the development tools and the schedule. The most significant challenge for a project manager is to identify actions that may incur defects before the action is performed. Actions performed in different projects may yield different results, which are hard to predict in advance. To alleviate this problem, this study proposes an Action-Based Defect Prevention (ABDP) approach, which applies the classification and Feature Subset Selection (FSS) technologies to project data during execution.
Accurately predicting actions that cause many defects by mining records of performed actions is a challenging task due to the rarity of such actions. To address this problem, the under-sampling is applied to the data set to increase the precision of predictions for subsequence actions. To demonstrate the efficiency of this approach, it is applied to a business project, revealing that under-sampling with FSS successfully predicts the problematic actions during project execution. The main advantage utilizing ABDP is that the actions likely to produce defects can be predicted prior to their execution. The detected actions not only provide the information to avoid possible defects, but also facilitate the software process improvement.
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