Discrete Components Research Articles

Створення надійних ноутбуків на основі простих змінних компонентів

The subject of study in this article and research is principles of creating of reliable and repairable notebooks. The goal is to determine the structural and circuitral peculiarities of the construction of portable computers and laptops, which improve fault tolerance, repairability, allow possibility of power supply using wider voltage range, and also reduce the cost of repairing, which makes it possible to create more reliable solutions with fault tolerance. The task is to analyze the existing architectures of computers built on modern chipsets; to analyze cases of failure of the computer equipment regarding the causes and consequences of faults; to analyze the possible reasonability of repairing and the computer repair options; to propose recommendations of the structural organization of notebook components and the recommendations for the support of a wide range of notebook voltages of power supply. According to the tasks, the following results were obtained. The analysis of the constructional design features of modern laptops and portable computers is performed. The main components of notebook motherboard, including the processor, multicontroller, and host bridge, are analyzed. The possible causes of faults of system board components are analyzed. The interaction of the multicontroller with BIOS and UEFI of notebooks is analyzed. The causes and solutions of possible issues of battery replacement are identified. The disadvantages of direct wired connection of peripheral devices to the processors implemented as a system on chip are discussed. The recommendations of the creation of repairable circuits of notebooks are proposed. The proposed circuits have a higher cost, weight and size characteristics with higher power consumption, but the obtained fault-tolerance allows the use in critical industries. Conclusions. The scientific novelty of the obtained results is in the fact that the performed analysis of solutions from leading manufacturers and the practical experience of laptop failures diagnostics allowed to propose a set of recommendations of the reliable laptops creation and modification of the existing components including the suppor of a wide range of power supply voltages, that will make it possible the charging from power sources without the use of an additional converters. The proposed use of discrete components and controllers for each interface port for connection of peripheral devices increases the system durability to the influence of external factors with maintaining of workability of the notebook and the rest ports of motherboard in case of the fault of one of them.

On differentiability and mass distributions of typical bivariate copulas

Despite the fact that copulas are commonly considered as analytically smooth/regular objects, derivatives of copulas have to be handled with care. Triggered by a recently published result characterizing multivariate copulas via (d−1)-increasingness of their partial derivative we study the bivariate setting in detail and show that the set of non-differentiability points of a copula may be quite large. We first construct examples of copulas C whose first partial derivative ∂1C(x,y) is pathological in the sense that for almost every x∈(0,1) it does not exist on a dense subset of y∈(0,1), and then show that the family of these copulas is dense. Since in commonly considered subfamilies more regularity might be typical, we then focus on bivariate Extreme Value copulas (EVCs) and show that a topologically typical EVC is not absolutely continuous but has degenerated discrete component, implying that in this class typically ∂1C(x,y) exists in full (0,1)2.Considering that regularity of copulas is closely related to their mass distributions we then study mass distributions of topologically typical copulas and prove the surprising fact that topologically typical bivariate copulas are mutually completely dependent with full support. Furthermore, we use the characterization of EVCs in terms of their associated Pickands dependence measures ϑ on [0,1], show that regularity of ϑ carries over to the corresponding EVC and prove that the subfamily of all EVCs whose absolutely continuous, discrete and singular component has full support is dense in the class of all EVCs.

Introducing a specified on-line multimodal prehabilitation approach for total knee replacement surgery candidates using data from the COVID-19 pandemic: An exploratory field-based, pre-post, mixed methods implementation pilot study.

Individuals waiting for total-knee-replacement surgery are at risk of developing morbidities and frailty which may affect their postoperative recovery. Multi-modal prehabilitation could mitigate these unintentional effects. To implement and evaluate a specified online multi-modal prehabilitation intervention in patients waiting for total-knee-replacement surgery in a large urban acute hospital trust. A non-randomised, pre/post analysis implementation pilot with a nested qualitative study was conducted and is reported following the standards for implementation studies (StaRI) guidance. Of 35 listed cases, 12 (34%) were eligible, recruited, and completed an 8-week multi-modal online intervention incorporating 5 modalities (i) cardiovascular exercise, (ii) strength/balance function, (iii) smoking cessation, (iv) opioid use, (v) nutritional intake. Interventions were specified using the Rehabilitation Treatment Specification System, where rehabilitation treatment theory accounts for discrete treatment components. Two participated in an online qualitative interview post-intervention. Process evaluation included intervention fidelity, eligibility/recruitment/retention rates, and clinical outcomes included knee function, frailty, gait velocity, anxiety/depression, and quality of life. Five participants (42%) completed the intervention and were retained at follow-up. The intervention was delivered online at specified doses, frequency/durations indicative of high respective adherence, quantity, and exposure fidelity. There was significant improvement in median oxford knee score (p = 0.015), gait velocity (p = 0.040) and anxiety (p = 0.023). The interview revealed 5 themes; surgery preconceptions, motivation, acceptability, postoperative experiences, and future recommendations confirming acceptance of the intervention by virtue of adhering to the treatment exposure delivered as planned. The specified multi-modal prehabilitation was acceptable, implementable, and demonstrated evidence of preliminary efficacy. Further experimental pilot work that represents the spectrum of frailty, obesity, quality of life, and comorbidities associated with total-knee-replacement surgery is indicated.

Self-Adaptive Intelligent Metasurface Cloak System with Integrated Sensing Units.

Metasurfaces, which are ultrathin planar metamaterials arranged in certain global sequences, interact uniquely with the surrounding light field and exhibit unusual effects of light modulation. Many interesting applications have been discovered based on metasurfaces, particularly in invisibility cloaks. However, most invisibility cloaks are limited to working in specific directions. Achieving effectiveness in multiple directions requires the metasurface to be designed with both perception and modulation capabilities. Current multi-directional metasurface cloak systems are implemented with discrete components rather than an integrated sensing component. Here, we propose an intelligent metasurface cloak system that integrates sensing units, resulting in the cloaking effect with the help of a real-time direction sensor and an adaptive feedback control system. A reconfigurable reflective meta-atom based on phase modulation is presented. Sensing units replace parts of the meta-atoms in the designed tunable metasurface, integrating with an FPGA responsible for measuring the direction and frequency of the incident wave, constituting a closed-loop system together with the feedback parts. Experimental results demonstrate that the metasurface cloak system can recognize the different directions of the incoming wave, and can adaptively manipulate the reflected phase of EM waves to conceal objects without any human participation.

Modelling and Analysis of Adaptive ON-Time Controlled Boost Converter Using Verilog-A

ABSTRACT This paper presents a mixed modelling of adaptive ON-time controlled boost converter using Verilog-A. It is a mixture of Mathematical modelling, Behavioural modelling, and discrete components. While mathematical modelling has been used to model individual components, for circuits such as comparator and pulse generator behavioural modelling is used. Power MOSFETs in the power stage are the only discrete components used from the library. Each model was coded using Verilog-A in Cadence Virtuoso and its symbolic notation obtained. The symbols were then connected to obtain the complete schematic of the boost converter. The behavioural modelling of the boost converter is targeted for an output voltage of 1.2 V for an input voltage ranging from 0.5 to 0.7 V and switching frequency of 800 KHz. The modelling also captures the results for 40% variation in input and load, for which the output voltage is found to vary by about 5–6%. This work is an attempt at completely modelling a complex analog circuit. It also shows the successful integration of modelled components with discrete components. To validate the results obtained, the performance of the modelled converter is compared with that of circuit simulation, with both simulations being conducted at identical operating conditions. The results obtained with modelling simulation match that obtained with the circuit simulation.

Metasurface-enabled broadband multidimensional photodetectors

Light encodes multidimensional information, such as intensity, polarization, and spectrum. Traditional extraction of this light information requires discrete optical components by subdividing the detection area into many “one-to-one” functional pixels. The broadband photodetection of high-dimensional optical information with a single integrated on-chip detector is highly sought after, yet it poses significant challenges. In this study, we employ a metasurface-assisted graphene photodetector, enabling to simultaneously detect and differentiate various polarization states and wavelengths of broadband light (1-8 μm) at the wavelength prediction accuracy of 0.5 μm. The bipolar polarizability empowered by this design allows to decouple multidimensional information (encompassing polarization and wavelength), which can be achieved by encoding vectorial photocurrents with varying polarities and amplitudes. Furthermore, cooperative multiport metasurfaces are adopted and boosted by machine learning techniques. It enables precise spin-wavelength differentiation over an extremely broad wavelength range (1-8 μm). Our innovation offers a recipe for highly compact and high-dimensional spectral-polarization co-detection.

Ghost age components in detrital thermochronology

Thermochronological dating of detrital samples is an important tool for understanding the thermal history of basins and their source regions. Detrital thermochronology data are often complex with apparent ages ranging over hundreds of million years due to variations in source-rock cooling age and rate, and the influence of post-depositional burial. A common strategy to interpret such data is to split a dataset into several age components by finite-mixture modeling. Herein, we describe for the first time a remarkable pattern of age components in some thermochronological datasets: two or more components showing ages that are approximately multiples of each other. We apply finite-mixture modeling to a log-normal age distribution (a random effects model) and show that these “ghost age components” are artifacts of inappropriately fitting discrete components to continuous age ranges. The striking pattern of the age components is a direct consequence of the underlying age distribution. For a continuous log-normal age distribution, the ghost components have approximately similar age ratios that depend on the overdispersion and the number of components. Due to their artifactual nature, ghost components appear in a range of dating methods, including fission-track, UPb and (UTh)/He dating, and in equivalent doses of luminescence dating. As they are not geologically meaningful, their occurrence hampers the geological interpretation of thermochronological data. We thus propose to carefully decide for the number of fitted components based on grain properties and additional geological information and to screen modeling results for the constant age ratios that are characteristic of ghost components.

A discrete CMUT self-biasing circuit towards implanted devices application

Wireless power transfer is an essential feature of biomedical engineering. It reduces the need for energy storage devices in medical implants. To recharge a body implanted battery, a convenient way is to transmit ultrasounds through the skin to a connected ultrasonic transducer. Lead-less, System-on-Chip compatible (SoC) and wideband, Capacitive Micromachined Ultrasonic Transducers (CMUT) are competitive with piezoelectric based technologies. However, their need for a high bias voltage is an obstacle to their use in implanted medical devices (IMDs). The voltage source required must meet precise specifications, such as reliability and volume, which the research community intends to respect. To meet this challenge, this work proposes an electronic circuit that allows a CMUT device to self-bias from a very low initial energy input. After presenting the electronic architecture and its main features, simulation and experimental results validate the solution’s working principle and operating points. With an electronic circuit made up of discrete components, a bias voltage of 60 V is built up from an implanted battery voltage of 2.2 V and an incident pressure of 120 kPa in water.

Bias correction and ensemble techniques in statistical downscaling model for rainfall prediction using Tweedie-LASSO in West Java, Indonesia

Rainfall is a climate element with high variations in space and time scales, so it is not easy to predict. One way to predict rainfall is statistical downscaling (SD). SD can predict local rainfall based on Global Circulation Model (GCM) data. The Decadal Climate Prediction Project (DCPP), one of the GCMs, originates from adjacent grids and experiences multicollinearity problems. Rainfall as a response variable is Tweedie Compound Poisson Gamma (TCPG) distribution data because it has a discrete component (rainfall events) and a continuous component (rainfall intensity), so SD modelling will be carried out using Tweedie-LASSO. This research aims to compare the performance of bias correction and ensemble methods in SD in predicting rainfall in West Java, Indonesia. Bias correction uses Empirical Quantile Mapping (EQM) with CHIRPS data, and the ensemble method uses a stacking technique with Random Forest (Stacking-RF) due to the varied characteristics of DCPP model sources. Evaluation results using Root Mean Square Error Prediction (RMSEP) and correlation coefficient show that bias correction improves single-model performance but not ensemble models. Besides that, ensemble models outperform single models both before and after bias correction. The combination of bias correction and ensemble modelling can be recommended when conducting SD to enhance the prediction capability of rainfall at stations and other areas.

Modal fracture of higher groups

In this paper, we examine the modal aspects of higher groups in Shulman's Cohesive Homotopy Type Theory. We show that every higher group sits within a modal fracture hexagon which renders it into its discrete, infinitesimal, and contractible components. This gives an unstable and synthetic construction of Schreiber's differential cohomology hexagon. As an example of this modal fracture hexagon, we recover the character diagram characterizing ordinary differential cohomology by its relation to its underlying integral cohomology and differential form data, although there is a subtle obstruction to generalizing the usual hexagon to higher types. Assuming the existence of a long exact sequence of differential form classifiers, we construct the classifiers for circle k-gerbes with connection and describe their modal fracture hexagon.

Past, present, and future of hybrid plasmonic waveguides for photonics integrated circuits

This article addresses the past, present, and future status of hybrid plasmonic waveguides (HPWs). It presents a comprehensive review of HPW-based photonic integrated circuits (PICs), covering both passive and active devices, as well as potential application of on-chip HPW-based devices. HPW-based integrated circuits (HPWICs) are compatible with complementary metal oxide semiconductor technology, and their matched refractive indices enables the adaptation of existing fabrication processes for silicon-on-insulator designs. HPWs combine plasmonic and photonic waveguide components to provide strong confinement with longer propagation length Lp of HP modes with nominal losses. These HPWs are able to make a trade-off between low loss and longer Lp, which is not possible with independent plasmonic and photonic waveguide components owing to their inability to simultaneously achieve low propagation loss with rapid and effective all-optical functionality. With HPWs, it is possible to overcome challenges such as high Ohmic losses and enhance the functional performance of PICs through the use of multiple discrete components. HPWs have been employed not only to guide transverse magnetic modes but also for optical beam manipulation, wireless optical communication, filtering, computation, sensing of bending, optical signal emission, and splitting. They also have the potential to play a pivotal role in optical communication systems for quantum computing and within data centers. At present, HPW-based PICs are poised to transform wireless chip-to-chip communication, a number of areas of biomedical science, machine learning, and artificial intelligence, as well as enabling the creation of densely integrated circuits and highly compact photonic devices.

The acute effect of time-restricted feeding (12 & 16 h) and varying exercise intensities on fat-oxidation rate in inactive young adults – a randomized control trial

Background and purposeTime-restricted feeding (TRF) is a dietary pattern that alternates between periods of fasting and feeding, which has gained significant attention in recent years. The 16/8 approach consists of fasting for 16 h and feeding for an 8-h window, while the 12/12 method consists of fasting for 12 h and a 12-h feeding window. Limited research exists comparing the effects of these methods coupled with physical activity (PA). The aim of this investigation was to examine the acute effects between conditions of varying TRF durations (12 and 16 h) and PA intensities on the fat oxidation rate (FOR). It was hypothesized that i) the TRF16 conditions would exhibit higher FORmax and that PA would enhance these effects, and ii) High Intensity Interval Training (HIIT) would result in greater effects on FORmax compared to Low-Moderate Intensity Steady State Continuous Training (MICT) PA.Methods and resultsEighteen young adults (age: 23 ± 2.0 yrs., body mass index: 23.5 ± 2.8 kg·m−2) were recruited and participated in the supervised intervention. The discrete component open circuit spirometry system was used to measure oxygen consumption (VO2), and Frayne’s equation was used to determine the FOR plus FORmax. ANOVA was used to determine pre/post-intervention differences in FORmax. The FORmax for the TRF16 + HIIT intervention was significantly higher than the TRF12 (mean difference = 0.099 g·min-1, p = 0.011, 95% CI 0.017 to 0.180) and TRF16 fast alone (mean difference = 0.093 g·min-1, p = 0.002, 95% CI 0.027 to 0.159). The FORmax for TRF12 + HIIT intervention was significantly higher than the TRF12 fast alone (mean difference = 0.070 g·min−1, p = 0.023, 95% CI 0.007 to 0.134). The TRF16 + HIIT intervention was also significantly higher than the TRF12 fast alone (mean difference = 0.099 g·min−1, p = 0.011, 95% CI 0.017 to 0.180).ConclusionThis study contributes to the ever-growing body of literature on the acute effects of TRF and PA on young adult males and females. The findings suggest that the TRF16 + HIIT PA intervention results in the highest FORmax. Trial registrationRetrospective Registration ISRCTN # 10076373 (October 6, 2023).

L-theanine, the unique constituent of tea, improves neuronal survivability by curtailing inflammatory responses in MPTP model of Parkinson's disease

Discrete components of tea possess multitude of health advantages. Escalating evidence advocate a consequential association between habitual tea consumption and a subsided risk of Parkinson's disease (PD). l-theanine is a non-protein amino acid inherent in tea plants, which exhibits structural resemblance with glutamate, the copious excitatory neurotransmitter in brain. Neuromodulatory effects of l-theanine are evident from its competency in traversing the blood brain barrier, promoting a sense of calmness beyond enervation, and enhancing cognition and attention. Despite the multifarious reports on antioxidant properties of l-theanine and its potential to regulate brain neurotransmitter levels, it is obligatory to understand its exact contribution in ameliorating the pathophysiology of PD. In this study, MPTP-induced mouse model was established and PD-like symptoms were developed in test animals where an increasing dosage of l-theanine (5, 25, 50, 100 and 250 mg/kg) was intraperitoneally administered for 23 days. 50 and 100 mg/kg dosage of l-theanine alleviated motor impairment and specific non-motor symptoms in Parkinsonian mice. The dosage of 100 mg/kg of l-theanine also improved striatal dopamine and serotonin level and tyrosine-hydroxylase positive cell count in the substantia nigra. Most crucial finding of the study is the proficiency of l-theanine to diminish astroglial injury as well as nitric oxide synthesis, which suggests its possible credential to prevent neurodegeneration by virtue of its anti-inflammatory attribute.

Designing 3D-printed concrete structures with scaled fabrication models

This article proposes using scaled fabrication models to assist the design research of 3D-printed discrete concrete structures where full-scale fabrication tests are costly and time-consuming. A scaled fabrication model (SFM) is a scaled model 3D-printed the same way as in actual construction to reflect its fabrication details and acquire alike layer line textures. The components of a 1:10 SFM can be easily produced by consumer-level desktop 3D printers with minimal modification. SFMs assist the design communication and make possible quick tests of distinct fabrication designs that are hard to assess in digital modeling during the conceptual design phase. A case study of a discrete compression-dominant funicular floor derived from graphic statics is presented to illustrate the contribution of SFM to the design research of force-informed toolpathing where the printing direction of a component is aligned to the principal stress line. The design iterations encompass a sequence of component, partial, and full model SFM printing tests to explore and optimize the fabrication schemes where parallel, non-parallel, and creased slicing methods to create toolpaths are compared and chosen to adapt different discrete components.

Interfacial characterization and bonding mechanism of W/ODS-316 L steel multi-material structure fabricated by laser powder bed fusion

Interfacial characterization and bonding mechanism of W/ODS-316 L steel multi-material structure fabricated by laser powder bed fusion

Miniaturized spectroscopy system based on a semiconductor nanofilm

Abstract Spectroscopy plays a pivotal role in various applications for industrial and commercial analysis. Conventional spectroscopy instruments include various discrete optical components like light sources, monochromators and detectors. These components are mechanically intricate and require space for the mechanisms that adjust and calibrate them, which increases the instrument’s footprint and make them less adjustable for portable applications. This drawback initiated the increase in the demand for miniatured spectral detection systems. Here, we present a low-cost ultra-compact miniaturized spectral detection system, which integrates both linear variable light sources, sample chambers and detectors within a centimetre-scale chip. The linear variable light generation across wavelengths ranging from 480 nm to 600 nm is achieved by stimulating different regions of the ZnCdSeS bandgap-graded semiconductor nanofilm with ultraviolet light. We demonstrate the capability of the system with precise identification of liquids. Our device overcomes the typical miniaturization limits imposed by discrete optical components, and long light paths in conventional spectroscopy instruments and opens up numerous potential applications across various fields due to its portability, ease of use, and lower cost.

Design and construction of wireless water level control system with motor protector

This research work presents the design and construction of a micro-controller-based wireless water level control system. The need to bring a solution to the problem of water shortage in various places by eliminating one of the culprit; waste of water during pumping and dispensing into overhead thanks, calls for an automated control system which puts into consideration, means of avoiding mechanical tears and wears that arises with the use of robes as water level sensor, through the incorporation of wireless water level sensor in place of robes in sensing the water level in the modeled tank. To solve this problem, circuit analysis and design, of the five main sub-circuitry units, this includes: power supply unit, logic and switching circuitry unit, relay unit, LCD display unit was carried out using ultrasonic water level sensor, AT89S51 microcontroller, LCD module relay circuitry system and a few discrete components. The design of the controller in this scenario is not just cost effective but helps in avoiding mechanical tears and wears that arises with the use of robes as water level sensor, by providing an improvement on existing water level control system through the incorporation of wireless water level sensor in place of robes in sensing the water level in the modeled tank.

Towards scalable cryogenic quantum dot biasing using memristor-based DC sources

Cryogenic memristor-based DC sources offer a promising avenue for in situ biasing of quantum dot arrays. In this study, we present experimental results and discuss the scaling potential for such DC sources. We first demonstrate the operation of a commercial discrete operational amplifier down to ▪ which is used on the DC source prototype. Then, the tunability of the memristor-based DC source is validated by performing several ▪-DC sweeps with a resolution of ▪ at room temperature and at ▪. Additionally, the DC source prototype exhibits a limited output drift of ▪ at ▪. This showcases the potential of memristor-based DC sources for quantum dot biasing. Limitations in power consumption and voltage resolution using discrete components highlight the need for a fully integrated and scalable complementary metal–oxide–semiconductor-based (CMOS-based) approach. To address this, we propose to monolithically co-integrate emerging non-volatile memories (eNVMs) and ▪ CMOS circuitry. Simulations reveal a reduction in power consumption, down to ▪ per DC source and in footprint. This allows for the integration of up to one million eNVM-based DC sources at the ▪ stage of a dilution fridge, paving the way for near term large-scale quantum computing applications.

SemanticMesh: parameterized fusion of semantic components for photogrammetric meshes

ABSTRACT The façades of photogrammetric building mesh models frequently lack detailed semantics, such as windows, doors, and balconies. To address this, we introduce SemanticMesh, a methodology designed to enrich façades with detailed semantics by integrating discrete components seamlessly. The process begins by transforming a localized area of the building surface into a 2D planar mesh using geodesic vectors, based on the component poses. This is followed by the application of 2D constrained triangulation to map the component boundaries onto the parameterized plane, after which the mesh is reconverted into 3D space. To achieve a smooth and aesthetically pleasing integration, we employ a Laplacian mesh deformation technique along the 3D embedding boundary. Our experiments across three distinct datasets – featuring near-planar, non-planar, and noisy surfaces – demonstrate that SemanticMesh provides superior modeling outcomes compared to conventional approaches.

Chip-scale integrated holographic devices based on top-emitting vertical cavity surface emitting lasers.

Holography technology is considered the ultimate three-dimensional (3D) visualization technology in the future. However, conventional methods for achieving holography generally utilize discrete optical components and off-chip laser sources, resulting in a large size and high complexity, which are undesirable for practical applications. In this Letter, chip-scale integrated holographic devices are realized by integrating top-emitting vertical cavity surface emitting lasers (VCSELs) with micro holograms printed by 3D femtosecond laser nanoprinting technology. The VCSELs are designed to operate in a single fundamental mode with a Gaussian emission profile. Then the Gaussian beams are phase-modulated by the integrated micro holograms designed by the Gerchberg-Saxton (GS) algorithm and the target holographic images can be displayed behind the holograms. Such integrated holographic devices are of micron size and can be easily scaled into arrays with arbitrary channels on-demand, which are important for achieving miniaturized and portable holographic imaging systems.