Era Of Devices Research Articles

Image Processing Based Pattern Recognition and Computerized Embroidery Machine

In the last decades, embroidery getting much attention in industries and academics. Although the technique is very old, it is still very much adopted. The current era of machine learning and smart devices makes this method even more attractive, easy to adopt and high accuracy. The proposed research work aims to highlight the implementation of new smart devices in this field, and the work is based on microcontrollers. Adopting the proposed work will be very easy and feasible to transform from the old sewing machine to a new smart method. Using smart devices, it is very easy and precise to get the embroidery fulfilling the user's demands. It gives simple raster images, which are used to convert into digital images to portray any new product. The current work is a novel idea of generating simple images rather than complicated ones, which are difficult to draw. In our method, we introduce the digitization process to input any image file used for vectorizing raster images, where vector images can easily convert into a DST embroidery file, a commonly used embroidery format originally from Tajima. It also has a Gcode file. The machine runs on a Gcode file which can be easily generated and runs on a product.

Hemostasis during thyroidectomy in the era of energy-based devices: an update

Hemostasis during thyroidectomy in the era of energy-based devices: an update

Quantum Error Mitigation via Matrix Product Operators

In the era of noisy intermediate-scale quantum (NISQ) devices, the number of controllable hardware qubits is insufficient to implement quantum error correction (QEC). As an alternative, quantum error mitigation (QEM) can suppress errors in measurement results via repeated experiments and postprocessing of data. Typical techniques for error mitigation, e.g., the quasi-probability decomposition method, ignore correlated errors between different gates. Here, we introduce a QEM method based on the matrix product operator (MPO) representation of a quantum circuit that can characterize the noise channel with polynomial complexity. Our technique is demonstrated on a $\rm{depth}=20$ fully parallel quantum circuit of up to $N_q=20$ qubits undergoing local and global noise. The circuit error is reduced by several times with only a small bond dimension $D^{\prime} = 1$ for the noise channel. The MPO representation increases the accuracy of modeling noise without consuming more experimental resources, which improves the QEM performance and broadens its scope of application. Our method is hopeful of being applied to circuits in higher dimensions with more qubits and deeper depth.

Biocompatibility and Connectivity of Semiconductor Nanostructures for Cardiac Tissue Engineering Applications.

Nano- or microdevices, enabling simultaneous, long-term, multisite, cellular recording and stimulation from many excitable cells, are expected to make a strategic turn in basic and applied cardiology (particularly tissue engineering) and neuroscience. We propose an innovative approach aiming to elicit bioelectrical information from the cell membrane using an integrated circuit (IC) bearing a coating of nanowires on the chip surface. Nanowires grow directly on the backend of the ICs, thus allowing on-site amplification of bioelectric signals with uniform and controlled morphology and growth of the NWs on templates. To implement this technology, we evaluated the biocompatibility of silicon and zinc oxide nanowires (NWs), used as a seeding substrate for cells in culture, on two different primary cell lines. Human cardiac stromal cells were used to evaluate the effects of ZnO NWs of different lengths on cell behavior, morphology and growth, while BV-2 microglial-like cells and GH4-C1 neuroendocrine-like cell lines were used to evaluate cell membrane-NW interaction and contact when cultured on Si NWs. As the optimization of the contact between integrated microelectronics circuits and cellular membranes represents a long-standing issue, our technological approach may lay the basis for a new era of devices exploiting the microelectronics' sensitivity and "smartness" to both improve investigation of biological systems and to develop suitable NW-based systems available for tissue engineering and regenerative medicine.

Avoiding barren plateaus with classical deep neural networks

Variational quantum algorithms (VQAs) are among the most promising algorithms in the era of Noisy Intermediate Scale Quantum Devices. Such algorithms are constructed using a parameterization U($\pmb{\theta}$) with a classical optimizer that updates the parameters $\pmb{\theta}$ in order to minimize a cost function $C$. For this task, in general the gradient descent method, or one of its variants, is used. This is a method where the circuit parameters are updated iteratively using the cost function gradient. However, several works in the literature have shown that this method suffers from a phenomenon known as the Barren Plateaus (BP). In this work, we propose a new method to mitigate BPs. In general, the parameters $\pmb{\theta}$ used in the parameterization $U$ are randomly generated. In our method they are obtained from a classical neural network (CNN). We show that this method, besides to being able to mitigate BPs during startup, is also able to mitigate the effect of BPs during the VQA training. In addition, we also show how this method behaves for different CNN architectures.

Super-Flexibility and High-Temperature Adhesion of Epoxy Structural Adhesives Endowed by Homogeneous Rigid–Flexible Crosslinking Networks

Epoxy adhesives that combine flexibility, high-temperature adhesion property, and medium–low-temperature curing ability are an urgent need in the microelectronic device era. Unfortunately, it is still a challenge so far. In this context, two kinds of curing agents are combined to construct homogeneous rigid–flexible crosslinking networks via the stepwise curing method for preparing an epoxy adhesive with prominent deformation ability and high-temperature adhesive strength. Detailed analysis showed that the crosslinking network constructed by the stepwise curing method was higher and more homogenous than that of the one-step curing method. Benefitting from the homogeneous rigid–flexible crosslinking network, the elongation at break and high-temperature adhesion strength (200 °C) of the epoxy adhesive prepared by the stepwise method were up to about 100% and 1.60 MPa, respectively, which were about 1677.7 and 112.5% higher than those of the epoxy adhesive cured by the one-step curing method. The epoxy adhesive with medium–low-temperature curing ability, excellent flexibility, and high-temperature adhesion was first reported. It is expected that this work could provide some inspiration to design the special epoxy adhesives.

Usefulness of pro-gastrin-releasing peptide as a predictor of the incidence of brain metastasis and effect of prophylactic cranial irradiation in patients with limited-stage small-cell lung cancer

Prophylactic cranial irradiation (PCI) is recommended for patients with limited-stage small-cell lung cancer (LS-SCLC) who respond well to initial treatment. However, PCI is often omitted because of its potential neurotoxicity in the era of modern diagnostic imaging devices. In the present study, we aimed to investigate the risk factors for brain metastasis (BM) in patients eligible for PCI and who may benefit more from it. Patients with LS-SCLC who responded well to definitive thoracic chemoradiotherapy were included in the present study. Competing risk regression was used to identify factors associated with BM, and the Kaplan–Meier method was used to assess overall survival (OS). Between 2004 and 2017, 62 patients were eligible for PCI and were analyzed. Of these, 38 (61.3%) underwent PCI. Overall, 17 patients (27.4%) developed BM, with a 2-year cumulative incidence of 22.8%. Multivariate analysis (MVA) revealed that pretreatment elevated pro-gastrin-releasing peptide (ProGRP) levels were associated with an increased risk for BM (HR, 7.96, P = 0.0091). PCI tended to reduce the risk of BM (HR, 0.33; P = 0.051). The use of PCI was associated with improved OS in patients with ProGRP levels > 410 pg/mL (P = 0.008), but not in those with ProGRP ≤ 410 pg/mL (P = 0.9). Pretreatment ProGRP levels may be useful in predicting the development of BM in patients with LS-SCLC who achieved a good response to initial therapy and to determine which patients should undergo PCI.

The evolution of field guides to British spiders

We review the development of field guides (in a broad sense) to British spiders from 1678 to the present day, and note features which made, or make, them more or less suitable for use in the field. The review concludes by exploring the future of paper field guides to this group of organisms in the era of electronic devices.

Shaping the future of cardiovascular medicine in the new era of wearable devices.

Shaping the future of cardiovascular medicine in the new era of wearable devices.

A Machine Learning Solution for Securing the Internet of Things Infrastructures

Securing Internet of Things (IoT) infrastructures against ever-evolving cyber threats remains a critical challenge in the era of interconnected devices. In this paper, we present a novel machine learning solution for enhancing IoT security through the detection and classification of diverse attacks. Leveraging the NSL-KDD dataset, we applied rigorous data preprocessing procedures, including feature engineering based on the chi-squared test, to select the most informative attributes. Our solution utilizes stacked Long Short-Term Memory (LSTM) networks, capable of capturing temporal dependencies and complex patterns within selected features. By exploiting LSTM's sequential learning and hierarchical representations, our approach effectively classifies attacks, ensuring the integrity and resilience of IoT networks. Comprehensive experiments showcase the superiority of our solution compared to various baseline methods, highlighting its accuracy, precision, recall, and F1-score. The proposed machine learning solution demonstrates remarkable effectiveness in securing IoT infrastructures, paving the way for a safer and more interconnected future.

PO-649-07 SAFETY OF SAME-DAY DISCHARGE AFTER PULMONARY VEIN ISOLATION: CONTEMPORARY SINGLE CENTER EXPERIENCE

Pulmonary vein isolation (PVI) has become an increasingly effective and safe strategy to treat AF. Same-day discharge is a potential way to minimize health care resource utilization, and improve patient experience. However, prior studies have not examined the feasibility of same-day discharge after PVI in the contemporary era of high DOAC utilization and vascular closure devices.

Virtual Voice Assistant for Smart Devices

Digital assistants have been a budding technology lately. In modern society, chatbots have found their way in many sectors of e-commerce. With widespread advancements in the field of artificial intelligence, developing machines to ease real life tasks is the norm of the day. Voice Assistants have gained a lot of popularity in this era of home automation and smart devices. These personal assistants, voice or text, can be easily programmed to perform many tasks by simply commanding them to. High tech industries like, Google have publicized voice-based search that is, especially, a bonanza for many like senior citizens who are not comfortable using the keypad/keyboard or English language as these assistants offer support in other languages like Hindi too. Any voice-based assistant works on two pivotal functions namely - listening to(detecting) commands and responding to the given commands given by user. Along with these two base functions, we need customized directive that will define the functionality of the voice assistant.

Securing IoT-Empowered Fog Computing Systems: Machine Learning Perspective

The Internet of Things (IoT) is an interconnected network of computing nodes that can send and receive data without human participation. Software and communication technology have advanced tremendously in the last couple of decades, resulting in a considerable increase in IoT devices. IoT gadgets have practically infiltrated every aspect of human well-being, ushering in a new era of intelligent devices. However, the rapid expansion has raised security concerns. Another challenge with the basic approach of processing IoT data on the cloud is scalability. A cloud-centric strategy results from network congestion, data bottlenecks, and longer response times to security threats. Fog computing addresses these difficulties by bringing computation to the network edge. The current research provides a comprehensive review of the IoT evolution, Fog computation, and artificial-intelligence-inspired machine learning (ML) strategies. It examines ML techniques for identifying anomalies and attacks, showcases IoT data growth solutions, and delves into Fog computing security concerns. Additionally, it covers future research objectives in the crucial field of IoT security.

Unplanned Hospital Readmissions After Transcatheter Aortic Valve Replacement in the Era of New-Generation Devices.

Unplanned hospital readmissions after transcatheter aortic valve replacement (TAVR) are frequent and have been associated with a poor prognosis. We sought to determine the trends in the incidence and causes of unplanned hospital readmission after TAVR in patients receiving new-generation devices (NGDs) vs early-generation devices (EGDs). The study population consisted of 1802 consecutive TAVR recipients (863 EGDs and 939 NGDs). Early and late readmissions were defined as those occurring ≤30 days and >30 days to 1-year post TAVR, respectively. A total of 986 unplanned hospital readmissions (cardiac cause, 38.4%; non-cardiac cause, 61.6%) were recorded at a median time of 110 days (interquartile range [IQR], 37-217) post TAVR. The rates of early (12.3% vs 9.4%; P=.046) and late (39.1% vs 31.6%; P<.01) readmission were lower in the NGD population. In the NGD group, major/life-threatening periprocedural bleeding (hazard ratio [HR], 2.40, 95% confidence interval [CI], 1.06-5.42; P=.04) and estimated glomerular filtration rate (eGFR) <60 mL/min at hospital discharge (HR, 1.80; 95% CI, 1.15-2.83; P=.01) were associated with an increased risk of early readmission post TAVR. Chronic obstructive pulmonary disease (HR, 1.42; 95% CI, 1.07-1.88; P=.02), eGFR <60 mL/min (HR, 1.43; 95% CI, 1.11-1.84; P<.01), and combining antiplatelet and anticoagulation therapy (HR, 1.37; 95% CI, 1.01-1.85; P=.04) determined an increased risk of late readmission. TAVR recipients receiving NGDs exhibited a significant but modest reduction in unplanned hospital readmissions, with about one-third of patients still requiring rehospitalization at 1-year follow-up in the contemporary TAVR era. Non-cardiac comorbidities, periprocedural bleeding events, and intensive antithrombotic therapy determined an increased risk.

Vacuum-driven assembly of electrostatically levitated microspheres on perforated surfaces

At the onset of a miniaturized device era, several promising methods, primarily wet methods, have been developed to attain large-scale assemblies of microparticles. To improve the speed, versatility and robustness of the current methods for the structured assembly of microparticles, an automatable method capable of forming 2D arrays of microspheres on large silicon surfaces is devised. The method uses surfaces perforated with vacuum-suction holes, capable of aspiring and holding individual particles from a particle cloud generated by subjecting a lump of chargeable particles, e.g., silica, polystyrene, and polymethyl methacrylate (PMMA), to a strong electrical field under ambient air conditions. The microsphere levitation depends on the electrical conductivity and permittivity of the particles. A single or double brush stroke can remove excess particles covering the formed arrays. We find that silica or polystyrene microspheres with a diameter of 5 μm or 10 μm can be assembled on the order of a few seconds, independently of the array size. Owing to the reversible nature of the arresting vacuum force, the assembled layers can be transferred to another surface, such as polydimethylsiloxane (PDMS) sheets, thus providing a key step for future particle printing processes for the fabrication of hierarchical materials, e.g., photonic crystals.

Debunking the July Effect in Transcatheter Interventions in Structural Heart Disease: Truth or Myth?

BackgroundThe “July effect”, the perception of worse outcomes in the first month of training, has been previously demonstrated in critical care medicine and general surgery. However, the July effect in the context of structural heart interventions (i.e., transcatheter aortic valve replacement [TAVR] and MitraClip) remains unknown. MethodsAll adult patients undergoing TAVR or MitraClip in the 2012-2016 National Inpatient Sample were included. Outcomes were compared by procedure month and academic year quartiles (i.e., between the first academic year quartile [Q1] vs. the fourth quartile [Q4]). Outcomes between teaching and nonteaching hospitals were compared using risk-adjusted logistic difference-in-difference regression. ResultsDuring the study period, 94,170 TAVR (Q1: 25,250; Q4: 23,170) and 8750 MitraClip (Q1: 2220; Q4: 2150) procedures were performed. In-hospital mortality did not vary as per academic year quartiles for either procedure, even after risk adjustment. These findings persisted in sensitivity analysis by procedure month and newer device era (2015-2016; all p > 0.05). In the subgroup analysis, the unadjusted and adjusted Q1 vs. Q4 in-hospital mortality between teaching and nonteaching hospitals were similar for either procedure. In-hospital mortality also did not vary by procedure month when stratified by hospital teaching status for both procedures. However, postprocedural complication rates appeared to be improving among the TAVR teaching hospitals for stroke, major bleeding, and vascular complications (all p < 0.05). ConclusionsIn this large, nationwide study, the July effect was not evident for structural heart interventions. With increasing interest and growth in transcatheter procedures, early resident and fellow teaching can be achieved with appropriate supervision.

Disability Stigma and Discrimination in Nepal: A Study of Pokhara Metropolitan City

Stigma and discrimination attached to disability are not new phenomenon in Nepal. People, irrespective of disability status, have been aware of these phenomena since long history of human kind from socio-cultural perspectives prevalent in Nepalese society. In this context, people with disability have been facing stigma and discrimination in their family and society. There are tremendous disruptions in attaining quality of life of the people. However, there is a dearth of such studies attached to disability, especially in the present contexts of socio-cultural transformation and era of assistive devices. This study focuses on root causes of disability stigma and discrimination in people with disability in Pokhara Metropolitan City. It adopts qualitative research approach, following in-depth interview to people with disability using semi-structured questionnaires in the city. This study investigated that there are heavily loaded stigma and discrimination in people with disability, especially in women in-migrants in their place of origin. It concludes that gender, caste, class, and residence are intrinsically linked with the daily lives of the people. This study has important policy implications in reducing stigma and discrimination, and in attaining quality of lives of the people.

An Interference-Managed Hybrid Clustering Algorithm to Improve System Throughput.

In the current smart era of 5G, cellular devices and mobile data have increased exponentially. The conventional network deployment and protocols do not fulfill the ever-increasing demand for mobile data traffic. Therefore, ultra-dense networks have widely been suggested in the recent literature. However, deploying an ultra-dense network (UDN) under macro cells leads to severe interference management challenges. Although various centralized and distributed clustering methods have been used in most research work, the issue of increased interference persists. This paper proposes a joint small cell power control algorithm (SPC) and interference-managed hybrid clustering (IMHC) scheme, to resolve the issue of co-tier and cross-tier interference in the small cell base station cluster tiers. The small cell base stations (SBSs) are categorized based on their respective transmitting power, as high-power SBSs (HSBSs) and low-power SBSs (LSBSs). The simulation results show that by implementing the IMHC algorithm for SBSs in a three-tier heterogeneous network, the system throughput is improved with reduced interference.

Outcomes of Stroke Thrombectomy Performed by Interventional Radiologists versus Neurointerventional Physicians

PurposeTo test the hypothesis that interventional radiologists (IRs) and neurointerventional (NI) physicians have similar outcomes of endovascular stroke thrombectomy (EVT), which could be used to improve the availability of thrombectomy. Materials and MethodsEight hospitals providing EVT performed by IRs and NI physicians at the same institution submitted sequential retrospective data limited to the era of modern devices. Good clinical outcomes (a 90-day modified Rankin score [mRS] of 0–2) and technically successful revascularization (a modified thrombolysis in cerebral infarction score of ≥2b) were compared between the specialties after adjusting for treating hospital, patient age, stroke severity, Alberta stroke program early computed tomography score, time from symptom onset to door, and clot location. Propensity score matching was used to compare the outcomes. A total of 1,009 patients were evaluated (622 treated by IRs and 387 treated by NI physicians). ResultsThe median time from stroke onset to puncture was 245 versus 253 minutes (P = .49), the technically successful revascularization rate was 81.8% versus 82.4% (P = .81), and the good clinical outcome rate was 45.5% versus 50.1% (P = .16). After adjusting, the physician specialty was not a significant predictor of good clinical outcomes (odds ratio, 1.028; 95% confidence interval, 0.760–1.390; P = .86). After matching, an mRS of 0–2 was present in 47.7% of IR treated patients and 51.1% of NI treated patients (P = .366). ConclusionsThere were no significant differences in the successful revascularization rate and good clinical outcomes between IRs and NI physicians. The outcomes of EVT performed by IRs were similar to those of EVT performed by NI physicians, as determined using previously published trials and registries. This may be useful for addressing coverage and access to stroke interventions.

Quantum logic with spin qubits crossing the surface code threshold

High-fidelity control of quantum bits is paramount for the reliable execution of quantum algorithms and for achieving fault tolerance—the ability to correct errors faster than they occur1. The central requirement for fault tolerance is expressed in terms of an error threshold. Whereas the actual threshold depends on many details, a common target is the approximately 1% error threshold of the well-known surface code2,3. Reaching two-qubit gate fidelities above 99% has been a long-standing major goal for semiconductor spin qubits. These qubits are promising for scaling, as they can leverage advanced semiconductor technology4. Here we report a spin-based quantum processor in silicon with single-qubit and two-qubit gate fidelities, all of which are above 99.5%, extracted from gate-set tomography. The average single-qubit gate fidelities remain above 99% when including crosstalk and idling errors on the neighbouring qubit. Using this high-fidelity gate set, we execute the demanding task of calculating molecular ground-state energies using a variational quantum eigensolver algorithm5. Having surpassed the 99% barrier for the two-qubit gate fidelity, semiconductor qubits are well positioned on the path to fault tolerance and to possible applications in the era of noisy intermediate-scale quantum devices.