An integrated neural network algorithm for optimum performance assessment of auto industry with multiple outputs and corrupted data and noise

In the real world encountering with noisy and corrupted data is unavoidable. Auto industry sector (AIS) as a one of the significant industry encounters with noisy and corrupted data regarding to its rapid development. Therefore, developing the performance assessment in this situation is so helpful for this industry. As Data envelopment Analysis (DEA) could not deal with noisy and corrupted data, the alternative method(s) is very important. As one of excellent and promising feature of artificial neural networks (ANNs) are theirs flexibility and robustness in noisy situation, they are a good alternative. This study proposes a non-parametric efficiency frontier analysis method based on the adaptive neural network technique for measuring efficiency as a complementary tool for the common techniques for efficiency assessment in the previous studies. The proposed computational method is able to find a stochastic frontier based on a set of input–output observational data and do not require explicit assumptions about the function structure of the stochastic frontier. In this algorithm, for calculating the efficiency scores of auto industry in various countries, a similar approach to econometric methods has been used. Moreover, the effect of the return to scale of AIS on its efficiency is included and the unit used for the correction is selected by notice of its scale (under constant return to scale assumption). Another feature of proposed algorithm is its ability to calculate efficiency for multiple outputs. An example using real data is presented for illustrative purposes. In the application to the auto industries, we find that the neural network provide more robust results and identifies more efficient units than the conventional methods since better performance patterns are explored. To test the robustness of the efficiency results of the proposed method, the ability of proposed ANN algorithm in dealing with noisy and corrupted data is compared with Data Envelopment Analysis (DEA). Results of the robustness check show that the proposed algorithm is much more robust to the noise and corruption in input data than DEA

Energy transfer and charge transfer between semiconducting nanocrystals and transition metal dichalcogenide monolayers

: Nowadays, as a result of the emergence of low-dimensional hybrid structures, the scientific community is interested in their interfacial carrier dynamics, including charge transfer and energy transfer. By combining the potential of transition metal dichalcogenides (TMDs) and nanocrystals (NCs) with low-dimensional extension, hybrid structures of semiconducting nanoscale matter can lead to fascinating new technological scenarios. Their characteristics make them intriguing candidates for electronic and optoelectronic devices, like transistors or photodetectors, bringing with them challenges but also opportunities. Here, we will review recent research on the combined TMD/NC hybrid system with an emphasis on two major interaction mechanisms: energy transfer and charge transfer. With a focus on the quantum well nature in these hybrid semiconductors, we will briefly highlight state-of-the-art protocols for their structure formation and discuss the interaction mechanisms of energy versus charge transfer, before concluding with a perspective section that highlights novel types of interactions between NCs and TMDs

Range resolution improvement in passive bistatic radars using nested FM channels and least squares approach

One of the main disadvantages of using commercial broadcasts in a Passive Bistatic Radar (PBR) system is the range resolution. Using multiple broadcast channels to improve the radar performance is offered as a solution to this problem. However, it suffers from detection performance due to the side-lobes that matched filter creates for using multiple channels. In this article, we introduce a deconvolution algorithm to suppress the side-lobes. The two-dimensional matched filter output of a PBR is further analyzed as a deconvolution problem. The deconvolution algorithm is based on making successive projections onto the hyperplanes representing the time delay of a target. Resulting iterative deconvolution algorithm is globally convergent because all constraint sets are closed and convex. Simulation results in an FM based PBR system are presented. © 2015 SPIE

Quartic Anomalous Couplings in γγ\gamma\gamma Colliders

We study the constraints on the vertices $W^+W^- Z\gamma$, $W^+W^-\gamma\gamma$, and $ZZ\gamma\gamma$ that can be obtained from triple-gauge-boson production at the next generation of linear $e^+e^-$ colliders operating in the $\gamma\gamma$ mode. We analyze the processes $\gamma\gamma \to W^+W^-V$ ($V=Z$, or $\gamma$) and show that these reactions increase the potential of $e^+e^-$ machines to search for anomalous four-gauge-boson interactions.Comment: 15 pages, Latex file using ReVteX, 4 uufiled figures include

Angiotensin enzyme inhibitors and angiotensin receptor blockers as protective factors in COVID-19 mortality: a retrospective cohort study

Targeting the renin-angiotensin system is proposed to affect mortality due to coronavirus disease 2019 (COVID-19). We aimed to compare the mortality rates in COVID-19 patients who received angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (ACEIs/ARBs) and those who did not. In this retrospective cohort study, mortality was considered as the main outcome measure. All underlying diseases were assessed by the chronic use of medications related to each condition. We defined two main groups based on the ACEIs/ARBs administration. A logistic regression model was designed to define independent predictors of mortality as well as a Cox regression analysis. In total, 2553 patients were included in this study. The mortality frequency was higher in patients with a history of underlying diseases (22.4 vs 12.7, P value < 0.001). The mortality rate in patients who received ACEIs/ARBs were higher than non-receivers (29.3 vs. 19.5, P value = 0.013, OR = 1.3, 95 CI 1.1, 1.7) in the univariate analysis. However, the use of ACEIs/ARBs was a protective factor against mortality in the model when adjusted for underlying conditions, length of stay, age, gender, and ICU admission (P value < 0.001, OR = 0.5, 95 CI 0.3, 0.7). The Kaplan�Meier curve showed an overall survival of approximately 85.7 after a 120-day follow-up. ACEIs/ARBs are protective factors against mortality in COVID-19 patients with HTN, and these agents can be considered potential therapeutic options in this disease. The survival probability is higher in ACEIs/ARBs receivers than non-receivers. © 2020, Società Italiana di Medicina Interna (SIMI)

Probing Anomalous Quartic Couplings in e-gamma and gamma-gamma Colliders

We analyze the potential of the e+e- Linear Colliders, operating in the e-gamma and gamma-gamma modes, to probe anomalous quartic vector--boson interactions through the multiple production of W's and Z's. We examine all $SU(2)_L \otimes U(1)_Y$ chiral operators of order p^4 that lead to new four--gauge--boson interactions but do not alter trilinear vertices. We show that the e-gamma and gamma-gamma modes are able not only to establish the existence of a strongly interacting symmetry breaking sector but also to probe for anomalous quartic couplings of the order of 10^{-2} at 90% CL. Moreover, the information gathered in the e-gamma mode can be used to reduced the ambiguities of the e+e- mode.Comment: Revtex, 18 pages, 6 figure

A Person-Centered Approach to Commitment Research: Theory, Research, and Methodology

There has been a recent increase in the application of person-centered research strategies in the investigation of workplace commitments. To date, research has focused primarily on the identification, within a population, of subgroups presenting different cross-sectional or longitudinal configurations of commitment mindsets (affective, normative, continuance) and/or targets (e.g., organization, occupation, supervisor), but other applications are possible. In an effort to promote a substantive-methodological synergy, we begin by explaining why some aspects of commitment theory are best tested using a person-centered approach. We then summarize the result of existing research and suggest applications to other research questions. Next, we turn our attention to methodological issues, including strategies for identifying the best profile structure, testing for invariance across samples, time, culture, etc., and incorporating other variables in the models to test theory regarding profile development, consequences, and change trajectories. We conclude with a discussion of the practical implications of taking a person-centered approach to the study of commitment as a complement to the more traditional variable-centered approach

Novel VIPAS39 mutation in a syndromic patient with arthrogryposis, renal tubular dysfunction and intrahepatic cholestasis

ARC syndrome is a rare autosomal recessive disease, characterized by arthrogryposis, renal tubular dysfunction and cholestasis. Herein a 2.5 month old infant with dysmorphic features, including small anterior fontanel, low set ears, beaked nose and high arched palate is presented who was referred because of icterus. He also suffered from some additional anomalies, including unilateral choanal atresia, club foot, and bilateral developmental dislocation of hip, while further studies showed renal tubular acidosis and hearing impairment in addition to cholestasis. Genetic studies showed a homozygous mutation in the VIPAS39 gene. Making the definite diagnosis of the syndrome is important, while increased risk of mutation in other siblings highlights the importance of prenatal diagnosis