bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and miniaturization of a microsystem to power biomedical implants using grey wolf optimizer-based cuckoo search algorithm
Authors: Ouacha Brahim , Bouyghf Hamid , Nahid Mohammed , Abenna Said
Published: December 2022

One of the greatest techniques, inductive coupling is frequently utilized in the biomedical sector for wireless energy transfer to implants. The aim of this article is to develop and analyze the effect of inductor geometrical characteristics, distance between transmitter (TX) and receiver (RX) and also the operating frequency on the wireless power transfer system, using grey wolf optimizer-based cuckoo search (GWO-CS) algorithm. Power transfer efficiency (PTE), power provided to load, and other critical components must all be improved or maximized and miniaturaze the microsystem proposed. The invention, design, and optimization of coils square spirals in a wireless energy transfer system using a resonant inductive link are the emphasis of this paper. The GWO-CS approach is evaluated to existing methods, demonstrated by simulations and to demonstrate the effectiveness of the suggested strategy.
New methodology to detect the effects of emotions on different biometrics in real time
Authors: Abd Elgawad Yahia Zakria , Youssef Mohamed I. , Nasser Tarek Mahmoud
Published: December 2022

Recently, some problems have appeared among medical workers during the diagnosis of some diseases due to human errors or the lack of sufficient information for the diagnosis. In medical diagnosis, doctors always resort to separating human emotions and their impact on vital parameters. In this paper, a methodology is presented to measure vital parameters more accurately while studying the effect of different human emotions on vital signs. Two designs were implemented based on the microcontroller and National Instruments (NI) myRIO. Measurements of four different vital parameters are measured and recorded in real time. At the same time, the effects of different emotions on those vital parameters are recorded and stored for use in analysis and early diagnosis. The results proved that the proposed methodology can contribute to the prediction and diagnosis of the initial symptoms of some diseases such as the seventh nerve and Parkinson’s disease. The two proposed designs are compared with the reference device (beurer) results. The design using NI myRIO achieved more accurate results and a response time of 1.4 seconds for real-time measurements compared to its counterpart based on microcontrollers, which qualifies it to work in intensive care units.
Delay-efficient 4:3 counter design using two-bit reordering circuit for high-speed Wallace tree multiplier
Authors: Subbaiah Madaka Venkata , Reddy Galiveeti Umamaheswara
Published: December 2022

In many signal processing applications, multiplier is an important functional block that plays a crucial role in computation. It is always a challenging task to design the delay optimized multiplier at the system level. A new and delay-efficient structure for the 4:3 counter is proposed by making use of a two-bit reordering circuit. The proposed 4:3 counter along with the 7:3 counter, full adder (FA), and half adder (HA) circuits are employed in the design of delay-efficient 8-bit and 16-bit Wallace tree multipliers (WTMs). Using Xilinx Vivado 2017.2, the designed circuits are simulated and synthesized by targeting the device ‘xc7s50fgga484-1’ of Spartan 7 family. Further, in terms of lookup table (LUT) count, critical path delay (CPD), total on-chip power, and power-delay-product (PDP), the performance of the proposed multiplier circuit is compared with the existing multipliers.
Reducing torque ripple of induction motor control via direct torque control
Authors: Al Azze Qasim , Hameed Imad Abdul-Rida
Published: December 2022

The induction motor is extremely well known and used as an alternating current (AC) machine. Therefore, torque and speed regulations are very essential for this type of machine. This paper presents direct torque control (DTC) based on induction motors (IM). The mathematical model of IM is reported, and the machine is modeled in a synchronous coordinate farm. Classic DTC is applied to IM with two bandwidths of hysteresis controller for electromagnetic torque and stator flux. The system is simulated and investigated via MATLAB/Simulink and the results carry out a high ripple on the torque. There are numerous of improving torque response, one of them is adding a new loop for speed with proportional, integral, and derivative (PID) controllers. IM model with PID based on DTC is simulated through MATLAB. A contrast performance of IM is presented between traditional DTC and DTC with PID. As result, the new DTC with PID carries out improvement in the speed response as well reduces the ripples of torque.
Design and simulation of Arduino Nano controlled DC-DC converters for low and medium power applications
Authors: Nallusamy Sivasankar , Kaliaperumal Rukmani Devabalaji
Published: December 2022

This paper mainly focuses on the controller of portable direct current to direct current (DC-DC) converter which may be simple, low cost and efficient. Nowadays, proportional integral (PI) controller and opto-isolator based circuits are used for switching control. The switching control through the controller makes the DC-DC converter into larger circuit and less efficient. This problem will be rectified using the Arduino Nano controller which is small and low cost-effective controller. It is useful for low and medium power applications like residential solar power system, electronic gadgets, and academic laboratories. Arduino Nano-based DC chopper has been developed, and the Proteus software used for simulation. The different topologies of DC choppers like buck, boost, and buck-boost converter have been designed with mathematical calculations and simulated.
Sensor fault detection and isolation for smart irrigation wireless sensor network based on parity space
Authors: Jihani Nassima , Kabbaj Mohammed Nabil , Benbrahim Mohammed
Published: December 2022

In the recent years, wireless sensor network technology (WSN) has been widely adopted in precision agriculture for determining the needs of the soil in term of water by monitoring some environmental parameters. To do this, WSN is constructed using several sensor nodes; these small sensing devices are prone to failure and may produce erroneous measurements. To ensure good management of freshwater, the network service quality is necessary. To avoid the degradation of service, the detection of the faulty sensor in WSN is required. In this paper, a fault detection and isolation (FDI) algorithm derived from a parity space approach and based on direct redundancy is proposed toward detecting and isolating sensor fault in WSN. In laboratory experiments, the proposed FDI algorithm proved its effectiveness.
Smart ports: towards a high performance, increased productivity, and a better environment
Authors: Al-Fatlawi Hayder Ali , Jassim Motlak Hassan
Published: December 2022

Ports are currently competing fiercely for capital and global investments in order to improve revenues, mostly by improving performance and lowering labor costs. Smart ports are a fantastic approach to realize these elements since they integrate information and communication technologies within smart applications, ultimately contributing to port management improvement. This leads to greater performance and lower operational expenses. As a result, several ports in Europe, Asia, Australia, and North America have gone smart. However, there are a lot of critical factors to consider when automating port operations, such as greenhouse gas emissions, which have reached alarming proportions. The purpose of this study is to define the most essential tasks conducted by smart ports, such as the smart ship industry, smart gantry and quayside container cranes, transport automation, smart containers, and energy efficiency. Furthermore, it gives a model of the smart port concept and highlights the critical current technologies on which the ports are based. Each technology’s most significant contributions to its development are noted. This technology is compared to more traditional technologies. It is hoped that this effort would pique the curiosity of fresh researchers in this sector.
Alpha-divergence two-dimensional nonnegative matrix factorization for biomedical blind source separation
Authors: Darsono Abd Majid , Chuan Toh Cheng , Manap Nurulfajar Abd , Hashim Nik Mohd Zarifie
Published: December 2022

An alpha-divergence two-dimensional nonnegative matrix factorization (NMF2D) for biomedical signal separation is presented. NMF2D is a popular approach for retrieving low-rank approximations of nonnegative data such as image pixel, audio signal, data mining, pattern recognition and so on. In this paper, we concentrate on biomedical signal separation by using NMF2D with alpha-divergence family which decomposes a mixture into two-dimensional convolution factor matrices that represent temporal code and the spectral basis. The proposed iterative estimation algorithm (alpha-divergence algorithm) is initialized with random values, and it updated using multiplicative update rules until the values converge. Simulation experiments were carried out by comparing the original and estimated signal in term of signal-to-distortion ratio (SDR). The performances have been evaluated by including and excluding the sparseness constraint which sparseness is favored by penalizing nonzero gains. As a result, the proposed algorithm improved the iteration speed and sparseness constraints produce slight improvement of SDR.
New fast Walsh–Hadamard–Hartley transform algorithm
Authors: Mardan Suha Suliman , Hamood Mounir Taha
Published: December 2022

This paper presents an efficient fast Walsh–Hadamard–Hartley transform (FWHT) algorithm that incorporates the computation of the Walsh-Hadamard transform (WHT) with the discrete Hartley transform (DHT) into an orthogonal, unitary single fast transform possesses the block diagonal structure. The proposed algorithm is implemented in an integrated butterfly structure utilizing the sparse matrices factorization approach and the Kronecker (tensor) product technique, which proved a valuable and fast tool for developing and analyzing the proposed algorithm. The proposed approach was distinguished by ease of implementation and reduced computational complexity compared to previous algorithms, which were based on the concatenation of WHT and FHT by saving up to 3N-4 of real multiplication and 7.5N-10 of real addition.
Liver segmentation using marker controlled watershed transform
Authors: Napte Kiran Malhari , Mahajan Anurag
Published: December 2022

The largest organ in the body is the liver and primarily helps in metabolism and detoxification. Liver segmentation is a crucial step in liver cancer detection in computer vision-based biomedical image analysis. Liver segmentation is a critical task and results in under-segmentation and over-segmentation due to the complex structure of abdominal computed tomography (CT) images, noise, and textural variations over the image. This paper presents liver segmentation in abdominal CT images using marker-based watershed transforms. In the pre-processing stage, a modified double stage gaussian filter (MDSGF) is used to enhance the contrast, and preserve the edge and texture information of liver CT images. Further, marker controlled watershed transform is utilized for the segmentation of liver images from the abdominal CT images. Liver segmentation using suggested MDSGF and marker-based watershed transform help to diminish the under-segmentation and over-segmentation of the liver object. The performance of the proposed system is evaluated on the LiTS dataset based on Dice score (DS), relative volume difference (RVD), volumetric overlapping error (VOE), and Jaccard index (JI). The proposed method gives (Dice score of 0.959, RVD of 0.09, VOE of 0.089, and JI of 0.921).
Anti-resonant based nested terahertz fiber design for illicit drugs detection
Authors: Tahhan Shaymaa Riyadh , Aljobouri Hadeel K. , Altahan Baraa Riyadh
Published: December 2022

Anti-resonant hollow-core fibers (AR-HCFs) have gotten a lot of interest lately because of their potential uses in different medical sensing applications. In this work, an anti-resonant THz fiber (ATF) biosensor is implemented to check for illicit drugs and identify them at airport borders. Three different unlawful medicines have been chosen for the proposed design, Cocaine, Amphetamine, and Ketamine. A novel hollow-core anti-resonant fibers (HC-ARF) Matryoshka shape sensor has been designed for detecting the illegal drugs. The proposed design shows a robust sensitivity ranging from 99.8-99.9% and shallow confinement losses compared to other articles in the same field, as the higher losses are 9.3×10-4 dB/m with cocaine. Bending loss lessens as the bending radius rises while it is still below 1 dB/cm for radius more than 10 cm. The numerical simulation outcomes displayed that the designed HC-ARF has 0.0643±0.0238 ps/THz/cm flat dispersion at 0.6-2 THz. As the first application in this field, this work will be the first published in the literature.
Octa-band reconfigurable monopole antenna frequency diversity 5G wireless
Authors: Abd Ali Kadhum , Rasool Jamal Mohammed
Published: December 2022

An octa-band frequency-reconfigurable antenna (28×14×1.5 mm3) with a broad tuning range is shown. Antenna mode1 (4.31 GHz) works in one single-band mode and two dual-band in modes 2 and 3 (i.e., 3.91 and 5.9 GHz) as well as one tri-band in mode 4 (i.e., 3.09, 5.65, and 7.92 GHz) based on the switching situation of the antenna. Changing capacitance for frequency reconfigurability is accomplished with the use of lumped components. The antenna’s observed tuning spans from 3.09 GHz to 7.92 GHz. for all the resonant bands, the suggested antenna has a voltage standing waves ratio (VSWR)<1.45 except for one band with a VSWR<1.85. From 70.57% to 97.93%, the suggested structure’s radiation efficiency may be calculated. For a better understanding proposed antenna’s far field and scattering characteristics, we used CST Microwave Studio 2021. We may conclude that our suggested antenna is suitable for today’s wireless applications, which need multiband and multimode small antennas. Using a small stainless-steel wire as a switch, a prototype of the antenna design is built and tested to verify the simulation findings. The suggested reconfigurable antenna’s strong concordance between simulated and measured findings.
The use of reversible logic gates in the design of residue number systems
Authors: Asadpour Ailin , Molahosseini Amir Sabbagh , Emrani Zarandi Azadeh Alsadat
Published: December 2022

Reversible computing is an emerging technique to achieve ultra-low-power circuits. Reversible arithmetic circuits allow for achieving energy-efficient high-performance computational systems. Residue number systems (RNS) provide parallel and fault-tolerant additions and multiplications without carry propagation between residue digits. The parallelism and fault-tolerance features of RNS can be leveraged to achieve high-performance reversible computing. This paper proposed RNS full reversible circuits, including forward converters, modular adders and multipliers, and reverse converters used for a class of RNS moduli sets with the composite form {2k, 2p-1}. Modulo 2n-1, 2n, and 2n+1 adders and multipliers were designed using reversible gates. Besides, reversible forward and reverse converters for the 3-moduli set {2n-1, 2n+k, 2n+1} have been designed. The proposed RNS-based reversible computing approach has been applied for consecutive multiplications with an improvement of above 15% in quantum cost after the twelfth iteration, and above 27% in quantum depth after the ninth iteration. The findings show that the use of the proposed RNS-based reversible computing in convolution results in a significant improvement in quantum depth in comparison to conventional methods based on weighted binary adders and multipliers.
NBLex: emotion prediction in Kannada-English code-switch text using naïve bayes lexicon approach
Authors: Chundi Ramesh , Hulipalled Vishwanath R. , Simha Jay Bharthish
Published: December 2022

Emotion analysis is a process of identifying the human emotions derived from the various data sources. Emotions can be expressed either in monolingual text or code-switch text. Emotion prediction can be performed through machine learning (ML), or deep learning (DL), or lexicon-based approach. ML and DL approaches are computationally expensive and require training data. Whereas, the lexicon-based approach does not require any training data and it takes very less time to predict the emotions in comparison with ML and DL. In this paper, we proposed a lexicon-based method called non-binding lower extremity exoskeleton (NBLex) to predict the emotions associated with Kannada-English code-switch text that no one has addressed till now. We applied the One-vs-Rest approach to generate the scores for lexicon and also to predict the emotions from the code-switch text. The accuracy of the proposed model NBLex (87.9%) is better than naïve bayes (NB) (85.8%) and bidirectional long short-term memory neural network (BiLSTM) (84.7%) and for true positive rate (TPR), the NBLex (50.6%) is better than NB (37.0%) and BiLSTM (42.2%). From our approach, it is observed that a simple additive model (lexicon approach) can also be an alternative model to predict the emotions in code-switch text.
A review of the automated timber defect identification approach
Authors: Hong Chun Teo , Hashim Ummi Raba’ah , Ahmad Sabrina , Salahuddin Lizawati , Choon Ngo Hea , Kanchymalay Kasturi
Published: December 2022

Timber quality control is undoubtedly a very laborious process in the secondary wood industry. Manual inspections by operators are prone to human error, thereby resulting in poor timber quality inspections and low production volumes. The automation of this process using an automated vision inspection (AVI) system integrated with artificial intelligence appears to be the most plausible approach due to its ease of use and minimal operating costs. This paper provides an overview of previous works on the automated inspection of timber surface defects as well as various machine learning and deep learning approaches that have been implemented for the identification of timber defects. Contemporary algorithms and techniques used in both machine learning and deep learning are discussed and outlined in this review paper. Furthermore, the paper also highlighted the possible limitation of employing both approaches in the identification of the timber defect along with several future directions that may be further explored.
Rough set method-cloud internet of things: a two-degree verification scheme for security in cloud-internet of things
Authors: MaryJohn Rukmony Sheeba , Gnanamony Suganthi
Published: December 2022

The quick development of innovations and increasing use of the internet of things (IoT) in human life brings numerous challenges. It is because of the absence of adequate capacity resources and tremendous volumes of IoT information. This can be resolved by a cloud-based architecture. Consequently, a progression of challenging security and privacy concerns has emerged in the cloud based IoT context. In this paper, a novel approach to providing security in cloud based IoT environments is proposed. This approach mainly depends on the working of rough set rules for guaranteeing security during data sharing (rough set method-cloud IoT (RSM-CIoTD)). The proposed RSM-CIoTD conspire guarantees secure communication between the user and cloud service provider (CSP) in a cloud based IoT. To manage unauthorized users, an RSM-CIoTD scheme utilizes a registered authority which plays out a two-degree confirmation between the network substances. The security and privacy appraisal techniques utilize minimum and maximum trust benefits of past communication. The experiments show that our proposed system can productively and safely store the cloud service while outperforming other security methods.
Three level intrusion detection system based on conditional generative adversarial network
Authors: Abdulameer Hasan , Musa Inam , Salim Al-Sultani Noora
Published: December 2022

Security threat protection is important in the internet of things (IoT) applications since both the connected device and the captured data can be hacked or hijacked or both at the same time. To tackle the above-mentioned problem, we proposed three-level intrusion detection system conditional generative adversarial network (3LIDS-CGAN) model which includes four phases such as first-level intrusion detection system (IDS), second-level IDS, third-level IDS, and attack type classification. In first-level IDS, features of the incoming packets are extracted by the firewall. Based on the extracted features the packets are classified into three classes such as normal, malicious, and suspicious using support vector machine and golden eagle optimization. Suspicious packets are forwarded to the second-level IDS which classified the suspicious packets as normal or malicious. Here, signature-based intrusions are detected using attack history information, and anomaly-based intrusions are detected using event-based semantic mapping. In third-level IDS, adversary packets are detected using CGAN which automatically learns the adversarial environment and detects adversary packets accurately. Finally, proximal policy optimization is proposed to detect the attack type. Experiments are conducted using the NS-3.26 network simulator and performance is evaluated by various performance metrics which results that the proposed 3LIDS-CGAN model outperforming other existing works.
Intrusion detection method for internet of things based on the spiking neural network and decision tree method
Authors: R. Zarzoor Ahmed , Shiltagh Al-Jamali Nadia Adnan , A. Abdul Qader Dina
Published: December 2022

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices’ power usage. Also, a rand order code (ROC) technique is used with SNN to detect cyber-attacks. The proposed method is evaluated by comparing its performance with two other methods: IDS-DNN and IDS-SNNTLF by using three performance metrics: detection accuracy, latency, and energy usage. The simulation results have shown that IDS-SNNDT attained low power usage and less latency in comparison with IDS-DNN and IDS-SNNTLF methods. Also, IDS-SNNDT has achieved high detection accuracy for cyber-attacks in contrast with IDS-SNNTLF.
Internet of things-based indoor smart hydroponics farm monitoring system
Authors: Krishner Macayana Yves Lean , Fernandez Ian Christian , Ung Kenneth , Austria Isabel , De Leon Maria Theresa , Vincent Densing Chris , Jairus Eslit John , Magpantay Percival , Miras Carlo , Ong Darvy , Santos Christopher , Talampas Marc , Michael Tiglao Nestor , Rosales Marc
Published: December 2022

Internet of things (IoT)-enabled systems are being used to monitor, control, and optimize agricultural systems like hydroponics. Optimization of these systems requires monitoring of various growth factors for plants which will also require multiple sensors. With the number of wireless sensors needed to track the conditions of the hydroponics system, the wireless sensor network will also grow in size and complexity. In this paper, a hybrid IoT-based monitoring system, with both wired and wireless components, with a target indoor farm application is proposed. The system was implemented using controller area network for the wired component, IPv6 over low power wireless personal area network (6LoWPAN) for the wireless component, and Amazon Web Services for the cloud services. Network simulations were performed to compare the network performance of the proposed hybrid system and the purely wireless system. The simulations show that incorporating a wired system results in improvements such as the reduction of packet loss from 12.23% in the purely wireless system to 5.62% in the hybrid system with burst traffic and even down to 0.0% in the hybrid system with continuous traffic.
O som da negridade em Apeshit
Authors: Gadelha Kaciano
Published: December 2022

Este artigo pretende abordar as questões interseccionais no campo das artes e das ciências sociais em torno das categorias raça e gênero, articuladas pelo significante da negridade. Tendo como caso de análise o vídeo da música Apeshit, lançado em 2018, este artigo foca nos regimes de dizibilidade e visibilidade que se manifestam nas estéticas musicais. Nesta discussão, a performance preta opera uma quebra com regimes de (in)visibilidade na sequencialidade instaurada por uma certa narrativa da história da arte. Sonoridade, visualidade e corporalidade traçam um emaranhado sensível em uma performance, na qual se vislumbra problematicamente a reintegração de corpos subalternizados aos espaços que lhe foram negados como espaços da sua excelência. A dimensão performativa do clipe Apeshit permite trabalhar com estratégias de imaginação/criação de mundos que jogam com as ambivalências e os códigos da cultura hegemônica no sentido de traçar rotas e quebras performativas desde uma apropriação e decodificação da dimensão normativa e paródica desses códigos.
Left Ventricular Assist Devices: A Primer For the General Cardiologist
Authors: Chaudhry Sunit‐Preet , DeVore Adam D. , Vidula Himabindu , Nassif Michael , Mudy Karol , Birati Edo Y. , Gong Timothy , Atluri Pavan , Pham Duc , Sun Benjamin , Bansal Aditya , Najjar Samer S. ,   for the Future Leaders In Growing Heart Failure Therapies (FLIGHT) Investigators
Published: December 2022

Durable implantable left ventricular assist devices (LVADs) have been shown to improve survival and quality of life for patients with stage D heart failure. Even though LVADs remain underused overall, the number of patients with heart failure supported with LVADs is steadily increasing. Therefore, general cardiologists will increasingly encounter these patients. In this review, we provide an overview of the field of durable LVADs. We discuss which patients should be referred for consideration of advanced heart failure therapies. We summarize the basic principles of LVAD care, including medical and surgical considerations. We also discuss the common complications associated with LVAD therapy, including bleeding, infections, thrombotic issues, and neurologic events. Our goal is to provide a primer for the general cardiologist in the recognition of patients who could benefit from LVADs and in the principles of managing patients with LVAD. Our hope is to “demystify” LVADs for the general cardiologist.
In‐Hospital Outcomes of Acute Myocardial Infarction With Essential Thrombocythemia and Polycythemia Vera: Insights From the National Inpatient Sample
Authors: Wu Jing , Fan YongZhen , Zhao Wei , Li Bing , Pan Naifan , Lou Zhiyang , Zhang Mingyou
Published: December 2022

Background

Acute myocardial infarction (AMI) with essential thrombocythemia (ET) or polycythemia vera is rare, and there are scarce real‐world data on its management and impact on in‐hospital outcomes.

Methods and Results

Dates of current retrospective cohort study were obtained from the US National Inpatient Sample from October 2015 to 2019 for hospitalizations with AMI. The primary outcome was in‐hospital mortality, and the secondary outcome was major adverse cardiac or cerebrovascular events, stroke, and bleeding; major adverse cardiac or cerebrovascular event was defined by a composite of all‐cause mortality, stroke, and cardiac complications. Of the 2 871 934 weighted AMI hospitalizations, 0.27% were with ET and 0.1% were with polycythemia vera. Before propensity matching, AMI hospitalization with ET was associated with increased risk of in‐hospital mortality (7.1% versus 5.7%; odds ratio [OR], 1.14 [95% CI, 1.04–1.24]), major adverse cardiac or cerebrovascular events (12.6% versus 9%; OR, 1.36 [95% CI, 1.26–1.45]), bleeding (12.7% versus 5.8%; OR, 2.28 [95% CI, 2.13–2.44]), and stroke (3.1% versus 1.8%; OR, 1.66 [95% CI, 1.46–1.89]). Polycythemia vera was associated with an increased risk of in‐hospital mortality (7.8% versus 5.7%; OR, 1.21 [95% CI, 1.04–1.39]) and major adverse cardiac or cerebrovascular events (12.0% versus 9%; OR, 1.18 [95% CI, 1.05–1.33]). After propensity matching, ET was associated with increased risk of bleeding (12.6% versus 6.1%; OR, 2.22 [95% CI, 1.70–2.90]), and AMI with polycythemia vera was not associated with worse in‐hospital outcomes.

Conclusions

AMI hospitalization with ET is associated with high bleeding risk before and after propensity score matching, particularly for hospitalizations treated with percutaneous coronary intervention. The management of AMI requires a multidisciplinary and patient‐centered approach to ensure safety and improve outcomes.
Change in Depressive Symptoms During the First Month of Discharge and 1‐Year Clinical Outcomes in Patients Hospitalized for Heart Failure
Authors: Wang Bin , Lei Lubi , Zhang Haibo , Miao Fengyu , Zhang Lihua , Tian Aoxi , Li Jing
Published: December 2022

Background

The patterns of depressive symptom change during the first month after discharge, as well as their prognostic implications, and predictors of persistent or new‐onset depressive symptoms are not well characterized.

Methods and Results

We included patients hospitalized for heart failure undergoing Patient Health Questionnaire‐2 before discharge and at 1 month after discharge in a multicenter prospective cohort. We characterized 4 patterns of change in depressive symptoms—persistent, new‐onset, remitted depressive symptoms, and no depressive symptom—and examined the associations between the 4 patterns and 1‐year clinical outcomes. We analyzed the factors associated with persistent or new‐onset depressive symptoms. A total of 4130 patients were included. Among 1175 (28.5%) symptomatic patients and 2955 (71.5%) symptom‐free patients before discharge, 817 (69.5%) had remission, and 366 (12.2%) had new‐onset depressive symptoms, respectively. Compared with no depressive symptom, persistent depressive symptoms were associated with an increased risk of cardiovascular death (hazard ratio [HR], 2.10 [95% CI, 1.59–2.79]) and heart failure rehospitalization (HR, 1.56 [95% CI, 1.30–1.87]); new‐onset depressive symptoms were associated with an increased risk of cardiovascular death (HR, 1.78 [95%CI, 1.32–2.40]) and heart failure rehospitalization (HR, 1.54 [95% CI, 1.29–1.83]). Remitted depressive symptoms were associated with a slightly increased risk of cardiovascular death but had no significant association with heart failure rehospitalization. Patients who were female or had poor socioeconomic status, stroke history, renal dysfunction, or poor health status had a higher risk of persistent or new‐onset depressive symptoms.

Conclusions

Sex, socioeconomic status, clinical characteristics, and health status help identify patients with high risks of depressive symptoms at 1 month after discharge. Dynamic capture of depressive symptom change during this period informs long‐term risk stratifications and targets patients who require psychological interventions and social support to improve clinical outcomes.

Registration

URL:
https://www.clinicaltrials.gov
; Unique identifier (NCT02878811).
Fin Field-Effect Transistor (FinFET) Based Low Noise Low Power Chopper Stabilized Capacitively Coupled Amplifier for Biosignal Acquisition System
Authors: Farshori Mohammad Aleem , Nizamuddin M. , Zulqarnain Mohammad , Sharma Vipin
Published: December 2022

Design of low power and low noise amplifier for biomedical signal acquisition is quite challenging. In this paper, an inverter based chopper stabilized capacitively coupled amplifier is designed for biomedical applications using 14 nm FinFET technology. Single-stage inverter based amplifier
which is used as a core amplifier in the proposed chopper stabilized circuit is designed and compared using different configurations of FinFET and CMOS. Gain and power dissipation is better with fully FinFET based single-stage amplifier when compared with fully CMOS based counterpart. When
the FinFET based amplifier is used with capacitive feedback and chopper stabilization circuit, it provides a significant reduction of noise as shown by Noise Efficiency Factor (NEF) of 3.66. The gain in chopper stabilized amplifier is 36.7 dB and bandwidth is in the range of 9.16 Hz–7.6
kHz. The CMRR and PSRR of the designed amplifier are 96.1 dB and 98.5 dB respectively. The power dissipation of the amplifier is 1.24 μW which is relatively better. In the end, spike reduction circuitry is also used successfully to minimize the spikes in the output signal.
A Novel Hybrid Reconfigurable Architecture for Prediction of Side Channel Attacks with Its Countermeasure Mechanism
Authors: Karthikeyan M. , Ponniyin Selvan V.
Published: December 2022

The Internet of Things (IoT) has pushed everyone‘s normal life zone to their comfort zone by making them use embedded IoT devices for controlling and monitoring their daily gadgets. IoT devices find their applications in health care, agriculture, industrial automation, and even
vehicles. Since IoT involves numerous devices’ data sharing, which causes network traffic and makes them vulnerable to security breaches, especially Side-Channel Attacks (SCA), it creates demand for an intelligent framework. As of now, many secured cryptoengines are integrated into embedded
chips, but still, SCAs play a very vital role in IoT networks. As a result, the paper proposes a novel reconfigurable architecture as Field Programmable Gate Arrays (FPGA) that integrates deep learning models for effective SCA prediction as well as a countermeasure mechanism based on chaotic
maps. Finally, the experimentation results prove the excellence of the proposed framework in terms of prediction accuracy (99%), sensitivity (98.9%), and specificity (98.9%) in comparison with LSTM, ELM SVM, RF, NB, and ANN. The results also demonstrated that the proposed framework requires
only 50% of the total energy for network operation.
Carrier Density Dependence of the Mobility in Disordered Organic Semiconductors with Gaussian Disorder
Authors: Liang Y. L. , Wang L. G. , Wang C. G. , Wang G. C. , Zhang L.
Published: December 2022

In this paper, the charge transport properties and energetic disorder are studied for pristine Si-PCPDTBT, mono-PCBM, bis-PCBM, and their blends of Si-PCPDTBT:mono-PCBM, Si-PCPDTBT:bis-PCBM. We show that the current density versus voltage curves of electron-only devices for mono-PCBM,
bis-PCBM, Si-PCPDTBT:mono-PCBM, Si-PCPDTBT:bis-PCBM, and hole-only devices for Si-PCPDTBT, Si-PCPDTBT:mono-PCBM, Si-PCPDTBT:bis-PCBM cannot be accurately described using a conventional mobility model within which the mobility depends only on the electric field, but that a fully consistent
description of all curves can be obtained using the improved extended Gaussian disorder model (IEGDM). Within the IEGDM, the presence of energetic disorder is described by a Gaussian density of states, and the mobility depends on the electric field and carrier density. Furthermore, we found
that the mobility increases as the width of the Gaussian density of states decreases for both electron-only and hole-only devices, and the mobility is closely related to the energetic disorder. We view this as an indication that the energetic disorder appears to govern the charge transport
in disordered organic semiconductors.
Non-Slicing Very Large Scale Integration Floorplan Optimization Technique Using an Improved Modified Memetic Algorithm with O-Tree Representation
Authors: Gupta Rohin , Gill Sandeep Singh
Published: December 2022

Interconnects in the VLSI floorplan play an essential role in determining a particular chip’s speed and parametric losses. For researchers, balancing between optimization of area and wirelength has been the central focus. This paper has proposed an improved memetic algorithm according
to the floorplan problem in which the Genetic Algorithm is used for global exploration and an inherent efficient local search method for improving the result in the search region. The representation used for the floorplan is O-Tree (Ordered Tree) implemented through the Code-Based Location
Search and Position (CBLSP) methodology. For wirelength calculation, the Half Perimeter Wire Length (HPWL) methodology is utilized. The mentioned techniques are checked on MCNC benchmark circuits with different preferences for wirelength and area. It has been found that the proposed methodology
has generated the best and near to best results for area. In terms of wirelength, the proposed methodology has shown improvement with a range of 3.97%–65.47%. For multi-objective optimization with the area and wirelength (α = 0.5, β = 0.5), significant improvement
in wirelength with a 25.1% decrease for the APTE benchmark, 47.4% decrease for HP Benchmark, and 10.7% decrease for the AMI33 benchmark circuit has been recorded.
Properties of Luminescent Materials and Photoelectronic Devices
Authors: Shi Hong
Published: December 2022

In this paper, an organic light emitting device is designed, and its fabrication and performance are tested. During the stacking process, the relative thickness ratio of each luminescent layer is changed. It is found that the devices show different luminescent characteristics under
the condition that the total thickness is the same but the thickness ratio of each luminescent layer is different. Among them, x varies by 8, 6, 4 and 2 nm, while y varies by 2, 4, 6 and 8 nm. Four devices are made. It is found that the electroluminescence spectrum of the device
has obvious changes, the color of the device changes significantly from blue to near white, and the brightness and efficiency of the device also have different degrees of change. This paper mainly studies the role of luminescence layer thickness for the brightness in the device. The experimental
results show that when x = 6 nm, y = 4 nm, the maximum brightness of the device is 4238 cd/m2, color coordinate (0.31,0.38).
Increasing Compound Hazards of Tropical Cyclones and Heatwaves over Southeastern Coast of China under Climate Warming
Authors: Wang Pinya , Yang Yang , Xue Daokai , Qu Yi , Tang Jianping , Leung L. Ruby , Liao Hong
Published: December 2022

Compound hazards are more destructive than the individual ones. Using observational and reanalysis datasets during 1960–2019, this study shows a remarkable concurrent relationship between extreme heatwaves (HWs) over southeastern coast of China (SECC) and tropical cyclone (TC) activities over western North Pacific (WNP). Overall, 70% of HWs co-occurred with TC activities (TC–HWs) in the past 60 years. Although the total frequency of TCs over WNP exhibited a decreasing trend, the occurrences of TC–HWs over SECC have been increasing, primarily due to the increasing HWs in the warming climate. In addition, TC–HWs are stronger and longer lasting than HWs that occur alone (AHWs). And in the long-term perspective, both AHWs and TC–HWs exhibit increasing trends, especially since the mid-1980s. The enhancement on HWs caused by TC activities is sustained until TCs make their landfalls and then collapse. Based on composite analysis, TC activities enhance HWs by modulating atmospheric circulations and triggering anomalous descending motion over southern China mainland which intensifies the western Pacific subtropical high (WPSH) and favors increased temperatures therein. Given the severe adverse impacts of TC–HWs on coastal populations, more research is needed to assess the future projections of TC–HWs, as HWs are expected to be more frequent and stronger as the climate warms, whereas TCs over WNP may occur less often.
Adult Drug Treatment Courts and Community-Level Drug Possession Arrests
Authors: Hibbard Patrick Franklin
Published: December 2022

Though the literature largely recognizes adult drug treatment courts (ADCs) as beneficial to participants, with lower rates of recidivism and drug use, the question remains of how ADCs impact communities and how other institutions (e.g., law enforcement) react to their presence. This study extends previous work estimating higher arrests associated with ADCs, particularly for crimes involving higher degrees of law enforcement discretion. Results indicate lower drug possession arrest rates for White residents in rural communities, and higher in urban areas, generally, but especially for Black citizens. Though the exact source of these changes has yet to be determined, current analysis indicates larger effect sizes for arrests scaled per officer, as compared to per population, pointing toward changes in law enforcement behavior.
Government Expenditure for Economic Growth: The Ethiopian Experience
Authors: Dagne Girum
Published: December 2022

This article investigates the relationship between sectoral government expenditure with economic growth in Ethiopia. In this study, the time series data from the period 1979–2018 is used. Autoregressive Distributed Lag approach to co-integration and error correction model are applied to investigate the short- and long-run impacts of government expenditure on economic growth. Using bound test approach to cointegration, the study revealed that agriculture, health and road expenditure has positive and significant in the long run, while expenditure on health and road has also a positive and statistically significant in short run. Applying the Granger causality test, we found a unidirectional causality running from health, transportation and communication and road government expenditure to growth at the one lag length. Therefore, it is important that the government better to spend on agriculture, health and road sectors of government expenditure for better development on these sectors and also should increase the efficiency of financial resources.
Compact living or policy inaction? Effects of urban density and lockdown on the COVID-19 outbreak in the US
Authors: Hong Andy , Chakrabarti Sandip
Published: December 2022

The coronavirus pandemic has reignited the debate over urban density. Popular media has been quick to blame density as a key contributor to rapid disease transmission, questioning whether compact cities are still a desirable planning goal. Past research on the density–pandemic connection have produced mixed results. This article offers a critical perspective on this debate by unpacking the effects of alternative measures of urban density, and examining the impacts of mandatory lockdowns and the stringency of other government restrictions on cumulative Covid-19 infection and mortality rates during the early phase of the pandemic in the US. Our results show a consistent positive effect of density on Covid-19 outcomes across urban areas during the first six months of the outbreak. However, we find modest variations in the density–pandemic relationship depending on how densities are measured. We also find relatively longer duration mandatory lockdowns to be associated with lower infection and mortality rates, and lockdown duration’s effect to be relatively more pronounced in high-density urban areas. Moreover, we find that the timing of lockdown imposition and the stringency of the government’s response additionally influence Covid-19 outcomes, and that the effects vary by urban density. We argue that the adverse impact of density on pandemics could be mitigated by adopting strict lockdowns and other stringent human mobility and interaction restriction policies in a spatially targeted manner. Our study helps to inform current and future government policies to contain the virus, and to make our cities more resilient against future shocks and threats.
Separating the Men from the Boys: The John Worthy School (1891-1916)
Authors: Garneau Susan M.
Published: December 2022

The John Worthy School (JWS) was created at the turn of the twentieth century to house younger male misdemeanants within Chicago’s House of Correction separately from older offenders. The JWS reflected reformers’, experts’, and city leaders’ goals of reforming, educating, and punishing juveniles differently from more “hardened” criminals. Although scholars have previously focused on the creation of juvenile courts, few have examined the creation, implementation, and operation of correctional institutions for younger offenders. Doing so highlights the clear tensions in these facilities and the limits of juvenile incarceration. In addition, through the JWS and informal subsidiary institutions, the city of Chicago expanded the reach of the city’s power into the lives and families of those detained within the walls of the facility. However, shortly after the JWS closed, such responsibility transferred to county and state authorities.
Right middle lobe syndrome after upper lobectomy: Role of the bronchial angle
Authors: Strollo Diane C , Donnenberg Vera S , Madan Shobhit , Moran Pauline L , Luketich James D , Sanchez Manuel Villa
Published: December 2022

Background

Right middle lobe syndrome is part of a spectrum of relatively rare but serious conditions that may occur following right upper lobectomy. We aimed to assess whether the preoperative middle lobe bronchial angle on CT predicted patients at risk of developing middle lobe syndrome.

Method

All patients who had a complete upper lobectomy over 4 years were retrospectively reviewed for clinical and imaging findings of middle lobe syndrome. Patients with previous lung surgery, preoperative chemo- or radiation therapy, or more extensive surgical resection were excluded. Patient demographics and symptoms, the surgical, pathologic and bronchoscopy reports, and pre- and post-operative chest imaging, to include 3D CT reconstructions and measurements of the middle lobe angles in a subset of patients, were retrospectively reviewed.

Result

One hundred and twenty-eight patients met inclusion criteria. Ten (8%) had middle lobe syndrome based on symptoms and imaging features. Eight had severe middle lobe consolidation. Two had postoperative onset of wheezing, with middle lobe bronchial abnormality on CT. The pre- and postoperative middle lobe bronchial angles of 14 patients without middle lobe syndrome were compared to 10 patients with middle lobe syndrome. The middle lobe bronchus was completely obliterated postoperatively and could not be determined in 1 patient. There was no significant difference between the pre- and postoperative angles in patients with or without middle lobe syndrome.

Conclusion

Middle lobe syndrome occurred in 8% of patients with right upper lobectomy. The preoperative middle lobe bronchial angle did not predict patients at risk for developing middle lobe syndrome.