Novel parallel inputs shift registers with terminals in nanotechnology.

This paper was focused on logic gates, D-latch, parallel-parallel shift-registers, and parallel-series shift registers, which are used as basic circuits in numerous circuits as well as computational and comparative units. To design proposed shift registers, D-latch which is the vital gate, is designed carefully for minimum size, decreasing number of cells and good performance for delay. The proposed level-sensitive parallel-in parallel-out () shift registers with reset terminal and with both set and reset terminals (single-layer and multi-layer), edge-sensitive shift registers with reset and set/reset abilities (single-layer and multi-layer), and the parallel-in serial-out () shift registers were designed using the proposed D-latches.

Design of a Low-Complexity Deep Learning Model for Diagnosis of Type 2 Diabetes.

Background: Recent research demonstrates that diabetes can lead to heart problems, neurological damage, and other illnesses.

Method: In this paper, we design a low-complexity Deep Learning (DL)-based model for the diagnosis of type 2 diabetes. In our experiments, we use the publicly available PIMA Indian Diabetes Dataset (PIDD).

Stochastic economic sizing and placement of renewable integrated energy system with combined hydrogen and power technology in the active distribution network.

The current study concentrates on the planning (sitting and sizing) of a renewable integrated energy system that incorporates power-to-hydrogen (P2H) and hydrogen-to-power (H2P) technologies within an active distribution network. This is expressed in the form of an optimization model, in which the objective function is to reduce the annual costs of construction and maintenance of integrated energy systems. The model takes into account the planning and operation model of wind, solar, and bio-waste resources, as well as hydrogen storage (a combination of P2H, H2P, and hydrogen tank), and the optimal power flow constraints of the distribution network.

Multi-objective economic operation of smart distribution network with renewable-flexible virtual power plants considering voltage security index.

This paper discusses the simultaneous management of active and reactive power of a flexible renewable energy-based virtual power plant placed in a smart distribution system, based on the economic, operational, and voltage security objectives of the distribution system operator. The formulated problem aims to specify the minimum weighted sum of energy cost, energy loss, and voltage security index, considering the optimal power flow model, voltage security formulation, and the operating model of the virtual power plant. The virtual unit includes renewable sources, like wind systems, photovoltaic, and bio-waste units.

Non-dialyzable uremic toxins and renal tubular cell damage in CKD patients: a systems biology approach.

Background: Chronic kidney disease presents global health challenges, with hemodialysis as a common treatment. However, non-dialyzable uremic toxins demand further investigation for new therapeutic approaches. Renal tubular cells require scrutiny due to their vulnerability to uremic toxins.

Numerical examination of expanding the effectiveness of thermal photovoltaic framework by changing the level of heat transfer conveyance.

In photovoltaic systems, only a tiny portion of solar radiation reaches the module's surface and is converted to electrical energy. The remaining solar radiation is wasted, which raises cell temperature and reduces electrical efficiency. This research focused on examining the effects of different factors on nanofluids.

Numerical analysis of potential in electrostatic amplitude caused by paint splashing.

In this research, the behavior of an electric field caused by the mechanism of electrostatic painting has been investigated using the finite element method and FLEXPDE software. The aim of this study is to optimize the electrostatic spraying performance of the paint sprayer by investigating the potential field in the paint nozzle. The results show that the potential and the electric field can be solved at any given point and displayed graphically.

Multi-functional voltage and current based enhancement of power quality in grid-connected microgrids considering harmonics.

The introduction of a renewable energy source (RES) based multi-functional grid-tied inverter (MFGTI) stands as a favorable remedy for addressing power quality concerns within distributed generation (DG) systems and microgrids. Nonetheless, the effectiveness of a traditional MFGTI will be restricted in addressing power quality issues based on voltage. The presented research proposes a novel structure for MFGTI to enhance power quality concerns associated with voltage, current, and harmonic distortions resulting from both grid and loads.

Students' happiness and ranking of its dimensions in Mazandaran University of Science and Technology during the COVID-19 crisis.

Background: Happiness and life satisfaction are positive indicators of mental health that should be considered by higher education and health officials. The aim of this study was to investigate the status of happiness and life satisfaction in students of Mazandaran University of Science and Technology during the outbreak of Coronavirus disease 2019 (COVID-19).

Materials And Methods: This research is practical in terms of purpose and descriptive survey in terms of nature.

Hybrid CNN-LSTM for Predicting Diabetes: A Review.

Background: Diabetes is a common and deadly chronic disease caused by high blood glucose levels that can cause heart problems, neurological damage, and other illnesses. Through the early detection of diabetes, patients can live healthier lives. Many machine learning and deep learning techniques have been applied for noninvasive diabetes prediction.

Perceived challenges and barriers for medical students in the COVID-19 crisis.

Background: Unpredictable and immediate changes, especially in the clinical and practical fields of medical sciences following the coronavirus disease (COVID-19) epidemic, have posed many challenges for medical students. This study was conducted to identify the experiences and students' understanding of the challenges in the COVID-19 crisis.

Materials And Methods: The present qualitative research was conducted by performing semi-structured interviews with the students along with holding a student panel.

Buckling analysis of laminated composite elliptical shells using the spline finite strip procedure.

According to the first order shear deformation plate assumption, current paper numerically investigates the buckling problem of cylindrical shells with oval cross-section under simply supported boundary condition subjecting to uniform and non-uniform loads via spline finite strip method. Equilibrium governing equations are generated based upon the virtual work's principle. Shell displacement function is assumed to be as dual development of degree 3 spline functions and Lagrange polynomial functions.

SqueezeNet for the forecasting of the energy demand using a combined version of the sewing training-based optimization algorithm.

With the introduction of various loads and dispersed production units to the system in recent years, the significance of precise forecasting for short, long, and medium loads have already been recognized. It is important to analyze the power system's performance in real-time and the appropriate response to changes in the electric load to make the best use of energy systems. Electric load forecasting for a long period in the time domain enables energy producers to increase grid stability, reduce equipment failures and production unit outages, and guarantee the dependability of electricity output.

Evaluation of AGM and FEM method for thermal radiation on nanofluid flow between two tubes in nearness of magnetism field.

The nanofluid flow through two orbicular cylinders is explored utilizing the overall Koo-Kleinstreuer-Li (KKL) model within the nearness of a magnetic field. The impact of thermal radiation is considered in the energy equation. The novelty of this study is examining convective heat transfer for nanofluid flow between two flat tubes with the Akbari-Ganji method and Finite Element Techniques to examine the heat flux field by implies of 2D forms of temperature and velocity at unprecedented Reynolds numbers.

Event prediction in social network through Twitter messages analysis.

Event detection using social media analysis has attracted researchers' attention. Prediction of events especially in the management of social crises can be of particular significance. In this study, events are predicted through analyzing Twitter messages and examining the changes in the rate of Tweets in a specified subject.

A possibilistic-robust-fuzzy programming model for designing a game theory based blood supply chain network.

This paper presents a bi-level blood supply chain network under uncertainty during the COVID-19 pandemic outbreak using a Stackelberg game theory technique. A new two-phase bi-level mixed-integer linear programming model is developed in which the total costs are minimized and the utility of donors is maximized. To cope with the uncertain nature of some of the input parameters, a novel mixed possibilistic-robust-fuzzy programming approach is developed.

A heuristic-based hybrid algorithm to configure a sustainable supply chain network for medical devices considering information-sharing systems.

In today's hyper-competitive marketplace, the crucial role of the sustainability concept has been highlighted more. Hence, managers' attention has been attracted to the concept of sustainable supply chains. On the other hand, after the COVID-19 outbreak, the importance of medical devices and their demand has drastically enhanced, which has led to shifting the attention of researchers toward this industry.

Application of artificial intelligence techniques for automated detection of myocardial infarction: a review.

Myocardial infarction (MI) results in heart muscle injury due to receiving insufficient blood flow. MI is the most common cause of mortality in middle-aged and elderly individuals worldwide. To diagnose MI, clinicians need to interpret electrocardiography (ECG) signals, which requires expertise and is subject to observer bias.

Digital twin-based fault tolerance approach for Cyber-Physical Production System.

Cyber-Physical Production Systems (CPPSs) as distributed Systems of Systems (SoS) are at the center of attention from different industries. CPPSs face different categories of errors. These errors will cause failures of the entire production chain.

Robust design of a green-responsive closed-loop supply chain network for the ventilator device.

This study aims to investigate the closed-loop supply chain network design problem considering the environmental and responsiveness features. For this purpose, a multi-objective mathematical model is suggested that minimizes the carbon emissions and the total costs and maximizes the responsiveness of the system. Due to the dynamic space of the business environment, uncertainty is an integral part of the supply chain problem.

Causal associations of genetic factors with clinical progression in amyotrophic lateral sclerosis.

Background And Objective: Recent advances in the genetic causes of ALS reveals that about 10% of ALS patients have a genetic origin and that more than 30 genes are likely to contribute to this disease. However, four genes are more frequently associated with ALS: C9ORF72, TARDBP, SOD1, and FUS. The relationship between genetic factors and ALS progression rate is not clear.

Robust optimization of uncertainty-based preventive maintenance model for scheduling series-parallel production systems (real case: disposable appliances production).

Industrial companies would attempt to keep themselves agile in the dynamic market. Given the competition among industries, lean methods are employed to reduce costs in the system. Among them, maintenance is significant to have a system available for manufacturing tasks.

Game theory and evolutionary optimization approaches applied to resource allocation problems in computing environments: A survey.

Today's intelligent computing environments, including the Internet of Things (IoT), Cloud Computing (CC), Fog Computing (FC), and Edge Computing (EC), allow many organizations worldwide to optimize their resource allocation regarding the quality of service and energy consumption. Due to the acute conditions of utilizing resources by users and the real-time nature of the data, a comprehensive and integrated computing environment has not yet provided a robust and reliable capability for proper resource allocation. Although traditional resource allocation approaches in a low-capacity hardware resource system are efficient for small-scale resource providers, for a complex system in the conditions of dynamic computing resources and fierce competition in obtaining resources, they cannot develop and adaptively manage the conditions optimally.

The green-agile supplier selection problem for the medical devices: a hybrid fuzzy decision-making approach.

The supplier selection problem (SSP) is known as one of the major issues in the supply chain management area. In this field, the literature shows that the combination of green and agile indicators has been ignored by researchers. Hence, this research attempts to study the SSP considering green and agile aspects, simultaneously.

A robust fuzzy multi-objective programming model to design a sustainable hospital waste management network considering resiliency and uncertainty: A case study.

With the increase in the number of patients and activity of hospitals, the issue of hospital waste management (HWM) is becoming more and more challenging and worrying. In addition to financial losses, there will be irreparable damage to the ecosystem and environment which will create many problems for people (because the job of some people in the area is livestock and agriculture and they have a lot to do with their surroundings). It also doubles the need to pay attention to the issue of sustainable development (simultaneous attention to social, economic and environmental dimensions) in waste management.