Perfect Conditions Research Articles

BER Analysis of Underlay Cooperative Cognitive Radio-based NOMA System

Background: The integration of Cooperative Communications (CC), Cognitive Radio (CR) technology, and Non-Orthogonal Multiple Access (NOMA) techniques, termed Cooperative Cognitive Radio used NOMA (CCR-NOMA) systems, has emerged as a promising solution to address spectrum scarcity and connectivity challenges anticipated in sixth generation (6G) networks. Aim: This studyaims to investigate the Bit Error Rate (BER) performance of underlay CCRNOMA systems. Methods: We derive precise closed-form expressions for BER at distant users under perfect and imperfect Channel State Information (CSI) conditions. These mathematical formulations are validated through Monte Carlo simulations. Results: Our results indicate that the near user CU! exhibits superior performance compared to the far user CU!. Additionally, distant users utilizing the CCR-OMA protocol demonstrate better BER performance than those employing the CCR-NOMA protocol. Conclusion: The presence of imperfect CSI adversely affects BER performance. Moreover, the derived closed-form expressions for BER in the investigated system align well with Monte Carlo simulations. These findings provide valuable insights for optimizing the performance of CCR-NOMA systems in real-world scenarios.

Revision of Sabine's and Eyring's reverberation theories

Sabine's and Eyring's reverberation theories are still the most important theoretical frameworks for room acoustics. The important physical quantities derived from these theories are the average sound pressure level (sound energy density) and the reverberation time (sound energy decay). Eyring revised Sabine's theory to become the reverberation time zero in the perfect absorption condition. However, Eyring's theory has contradictions regarding the sound energy density in a steady state and the energy decay from the steady state. In this study, in order to resolve these contradictions, the theoretical framework for the consistent system is presented introducing the new concept of the average impulse response in a room, and the contradictions in the current room acoustic theory are clarified. Based on the theoretical framework, Sabine's reverberation theory is revised by a different way of Eyring's theory. The reverberation time of the revised theory is shorter than that of Sabine's theory and longer than that of Eyring's theory. Finally, ray-tracing computer simulations were performed to verify the revised theory. Results of sound ray tracing simulations were in better agreement with the values calculated using the revised theory rather than those calculated using Sabine's and Eyring's theories.

Photoelectrochemical sensor based on copper tetraamino phthalocyanine graphene oxide covalent compound for sensitive detection of cefazolin sodium

In the present research, a novel photoelectrochemical (PEC) sensor was built to detect cefazolin sodium. A copper tetraamino phthalocyanine (CuTAPc) covalently linked graphene oxide compound (CuTAPc-GO) was fabricated successfully by covalent bonding of CuTAPc with graphene oxide (GO). The novel PEC sensing platform was prepared using CuTAPc-GO as a photoelectric material. The prepared PEC sensor showed a higher PEC efficiency under red light. In the perfect conditions, the PEC sensor exhibited a linear correlation in detecting cefazolin sodium concentrations between 0.25 and 12.5μM, featuring a detection limit at 0.15μM. Furthermore, the manufacturing sensor was employed to detect cefazolin sodium in a real-world sample, demonstrating commendable sensitivity and stability. Thus, our study provides a new method for cefazolin sodium detection.

A bi-component model to assess the rheology of soft cellular aggregates probed using the micropipette aspiration technique

The micro-pipette aspiration technique is a classical experiment used to characterize the physical properties of inert fluids and biological soft materials such as cellular aggregates. The physical parameters of the fluid, as viscosity and interfacial tension, are obtained by studying how the fluid enters the pipette when the suction pressure is increased and how it relaxes when the suction pressure is put to zero. A mathematical model representative of the experiment is needed to extrapolate the physical parameters of the fluid-like matter; however, for biological materials as cells or cell aggregates these models are always based on strong starting hypotheses that impact the significance of the identified parameters. In this article, starting from the bi-constituent nature of the cell aggregate, we derive a general mathematical model based of a Cahn-Hilliard-Navier-Stokes set of equations. The model is applied to describe quantitatively the aspiration-retraction dynamics of a cell-aggregate into and out of a pipette. We demonstrate the predictive capability of the model and highlight the impact of the assumptions made on the identified parameters by studying two cases: one with a non-wetting condition between the cells and the wall of the pipette (classical assumption in the literature) and the second one, which is more realistic, with a partial wetting condition (contact angle θs = 150°). Furthermore, our results provide a purely physical explanation to the asymmetry between the aspiration and retraction responses which is alternative to the proposed hypothesis of an mechano-responsive alteration of the surface tension of the cell aggregate. Statement of SignificanceOur study introduces a general mathematical model, based on the Cahn-Hilliard-Navier-Stokes equations, tailored to model micro-pipette aspiration of cell aggregates. The model accounts for the multi-component structure of the cell aggregate and its intrinsic viscoelastic rheology. By challenging prevailing assumptions, particularly regarding perfect non-wetting conditions and the mechano-responsive alteration of cell surface tension, we demonstrate the reliability of the mathematical model and elucidate the mechanisms at play, offering a purely physical explanation for observed asymmetries between the aspiration and retraction stages of the experiment.

An Interference Cancelation and Signal Decoding Method for Non-orthogonal Multiple Access Based on Deep Learning

In wireless communication, spectral efficiency is one of the key performance parameters. The available limited resources must be effectively shared among different applications. Due to the tremendous demand for wireless applications, an effective technique could be used for sharing the resources (time/frequency). Non-orthogonal Multiple Access (NOMA), is a wireless network technique aimed at boosting spectral efficiency. In NOMA, Users in the downlink have received a super-imposed signal from a Base Station (BS) with varying power allocations. Depending on the power allocation, the receiver employs interference cancelation techniques to decode its own data. The effectiveness of interference cancelation hinges on achieving a perfect channel condition, which is challenging to achieve in practical scenarios. This study introduces an unsupervised Deep Learning (DL) approach known as autoencoder, aimed at interference cancelation to ensure signal decoding from super-imposed signal. In contrast to the traditional approach, simulation results of the proposed structure show that the DL-based receiver achieves superior performance in correctly decoding the signal.

Silver Oxide Nanoparticle Decorated Carbon Nanotube as Efficient Electron Gun

AbstractAlthough there have been numerous great field emission reports of pure and hybrid carbon nanotubes (CNTs) with ultra‐low turn‐on field and ultra‐high emission stability, practically all of the reports indicate concern about CNT manufacture on a large scale. This is due to the fact that CNT experiments require high pressure, temperature, metal catalysis, and an inert environment, and even after meeting all of these perfect conditions, the yield is quite low. Furthermore, as CNT is relatively inert in nature, it is nearly hard to make it reactive with any other metal without adequate functionalization. Keeping this in mind, this work reports the synthesis of CNT in amorphous form by a simple low‐temperature solid‐state reaction between ammonium chloride and ferrocene. The as‐synthesized CNT is further functionalized by silver oxide nanoparticle without additional functionalization. X‐ray diffraction (XRD) confirms the proper phase formation as well as the successful functionalization of the pure and hybrid sample, electron microscopic images confirm the successful functionalization of the as‐prepared CNT whereas Fourier transformed infrared (FTIR) spectroscopic analysis gives the ideas about different bonding present in all the samples. It has been found that the hybrid sample gives much better field emission performance compare to the pure CNT with betterment in both turn‐on field and enhancement factor more than 100%. The betterment is believed to be due to the favorable band bending, larger number of emission sites, and sharp curvature of the silver particles.

Casimir energy with perfect electromagnetic boundary conditions and duality: A field-theoretic approach

Using functional integral methods, we study the Casimir effect for the case of two infinite parallel plates in the QED vacuum, with (different) perfect electromagnetic boundary conditions applied to both plates. To enforce these boundary conditions, we add two Lagrange multiplier fields to the action. We subsequently recover the known Casimir energy in two ways: once directly from the path integral and once as the vacuum expectation value of the 00 component of the energy-momentum tensor. Comparing both methods, we show that the energy-momentum tensor must be modified and that it picks up boundary contributions as a consequence. We also discuss electromagnetic duality invariance of the theory and its interplay with the boundaries by generalizing the Deser-Teitelboim implementation of the duality transformation. Published by the American Physical Society 2024

Machine Learning and Image Processing-Based System for Identifying Mushrooms Species in Malaysia

Malaysia, a country with a tropical climate characterized by consistent warmth and year-long high humidity, houses the perfect conditions for mushroom growth. Recently, there has been a surge in back-to-nature activities in Malaysia. However, many participants lack prior knowledge about the local flora and fungi, leading to a rise in mushroom poisoning cases, some of which have been fatal. Despite thorough research, there is a notable lack of identification studies specifically focused on mushroom species in Malaysia. Identifying these species is crucial for medical providers to effectively counteract the toxins from ingested mushrooms and also serves as an important educational tool. This study aims to determine the most suitable architecture for mushroom identification, focusing specifically on mushroom species found in Malaysia. A dataset of these mushrooms was curated, augmented, and processed through multiple variants of Vision Transformers (ViTs) and ResNet models, with uniform hyperparameters to ensure fairness. The results indicate that the ViT-L/16 model achieved the highest accuracy at 90.47%.

Newtonian flow with slip and pressure-drop predictions in hyperbolic confined geometries

We study theoretically the steady Newtonian flow in confined and hyperbolic long tubes (symmetric channels and axisymmetric pipes) considering slip along the walls. Using a stream function formulation, and the extended (or high-order) lubrication method in terms of the square of the aspect ratio of the tube, ε, the solution for the stream function is found analytically up to twentieth order in ε. At the classic lubrication limit, i.e. i.e. for a vanishing small aspect ratio, and for perfect slip conditions, the analysis predicts a plug-like velocity profile and a constant strain-rate on the midplane/axis of symmetry of the tube. A constant strain-rate is also predicted for the non-slip case. Furthermore, the high order asymptotic results for the stream function and fluid velocity are post-processed with an acceleration technique to investigate the convergence and accuracy of the solution. The results reveal the existence of a boundary layer at the inlet of the tube, the influence of which diminishes in a very short distance from the entrance. We discuss the effect of the contraction ratio of the tube and the dimensionless slip coefficient on the midplane/centerline and wall (slip) velocities, as well as on the average pressure-drop, required to maintain a constant flow-rate. The acceleration of converge technique on the solution for the pressure-drop revealed a remarkable convergence at a value slightly larger (∼1 %) than the value predicted by the classic lubrication theory. Finally, we comment on the common practice in the literature for approaching the velocity profile with the velocity profile at the classic lubrication limit, and we compare the high-order results for the strain rate at the midplane/centerline with the effective strain rate previously derived in the literature by Housiadas & Beris, J. Rheology, 68(3), 327–339, 2024.

Deep separation of Bi and Pb from leaching solution of molybdenite-bismuthinite mixed ore by solvent extraction method

A novel lead and bismuth deep-separation extraction-stripping system is proposed for the leaching solution of molybdenite-bismuthinite mixed ore, which creates perfect conditions for the preparation of high-purity bismuth-based materials. Based on the activity and ionic strength theories, the forms of bismuth and lead present in the solution were predicted according to the thermodynamic models of different systems. The results showed that N235 + 2-octyl alcohol + kerosene formed a synergistic extraction system, which realized the synergistic extraction of bismuth, iron and lead with solvent extraction ratios of 98.74 %, 9.34 % and 46.24 %, respectively. In addition, the FTIR spectra of bismuth and lead before and after extraction were recorded to better understand the extraction and vaporization mechanisms. When stripping with water, the stripping ratios of iron and lead were 99.87 % and 99.74 %, respectively, while the loss ratio of bismuth was only 0.01 %. In conclusion, this study will be a key link in the comprehensive recycling process of bismuth resources.

An in-depth assessment of the physical layer performance in the proposed B5G framework

The introduction of fifth-generation (5G) technology marks a significant milestone in next-generation networks, offering higher data rates and new services. Achieving optimal performance in 5G and beyond 5G (B5G) systems requires addressing key requirements like increased capacity, high efficiency, improved performance, low latency, support for many connections, and quality of service. It is well-known that suboptimal network configuration, hardware impairments, or malfunctioning components can degrade system performance. The physical layer of the radio access network, particularly channel estimation and synchronization, plays a crucial role. Hence, this paper offers an in-depth evaluation of the 5G Physical Downlink Shared Channel (PDSCH), along with its related channel models such as the Clustered Delay Line (CDL) and the Tapped Delay Line (TDL). This work assesses 5G network performance through practical and IA-based channel estimation and synchronization techniques, and anticipates numerologies for B5G networks. Extensive simulations leveraging the Matlab 5G New Radio (NR) toolbox assess standardized channel scenarios in both macro-urban and indoor environments, following configurations set by the 3rd Generation Partnership Project (3GPP). The numerical results offer valuable insights into achieving the maximum achievable throughput across various channel environments, including both line-of-sight (LoS) and non-line-of-sight (NLoS) conditions. The throughput comparisons are performed under assumptions of ideal, realistic, and convolutional neural networks (CNN)-based channel estimation with both perfect and realistic synchronization conditions. Importantly, the study pinpoints certain physical layer elements that have a pronounced impact on system performance, providing essential insights for devising effective strategies or refining CNN-based methods for forthcoming mobile B5G networks.

On the suitability of a convolutional neural network based RCM-emulator for fine spatio-temporal precipitation

High resolution regional climate models (RCM) are necessary to capture local precipitation but are too expensive to fully explore the uncertainties associated with future projections. To resolve the large cost of RCMs, Doury et al. (2023) proposed a neural network based RCM-emulator for the near-surface temperature, at a daily and 12 km-resolution. It uses existing RCM simulations to learn the relationship between low-resolution predictors and high resolution surface variables. When trained the emulator can be applied to any low resolution simulation to produce ensembles of high resolution emulated simulations. This study assesses the suitability of applying the RCM-emulator for precipitation thanks to a novel asymmetric loss function to reproduce the entire precipitation distribution over any grid point. Under a perfect conditions framework, the resulting emulator shows striking ability to reproduce the RCM original series with an excellent spatio-temporal correlation. In particular, a very good behaviour is obtained for the two tails of the distribution, measured by the number of dry days and the 99th quantile. Moreover, it creates consistent precipitation objects even if the highest frequency details are missed. The emulator quality holds for all simulations of the same RCM, with any driving GCM, ensuring transferability of the tool to GCMs never downscaled by the RCM. A first showcase of downscaling GCM simulations showed that the RCM-emulator brings significant added-value with respect to the GCM as it produces the correct high resolution spatial structure and heavy precipitation intensity. Nevertheless, further work is needed to establish a relevant evaluation framework for GCM applications.

The Monetary Trilemma Need Not Hold in the Short Run: The Case of Hong Kong

The monetary trilemma autonomy has been at the heart of a great deal of international monetary analysis. It implies that countries with fixed exchange rates and no capital controls will lose monetary autonomy. What is often not recognized, however, is that the trilemma need not hold in the short run. If capital mobility is less than perfect, then countries can sterilize reserve flows and maintain a degree of monetary autonomy in the short run. Hong Kong has perfect conditions for the trilemma to hold even in the short run. It is a small open economy with a fixed exchange rate and no major capital controls. If the trilemma does not hold for Hong Kong in the short run, then it is likely to not hold for many other countries either. We investigate this issue using two approaches. One is to estimate the effects of changes in US interest rates on those in Hong Kong. As with earlier literature, we find that the pass-through is substantially less than one, indicating imperfect capital mobility. The second is to estimate whether Hong Kong has been able to engage in some degree of sterilization. The Hong Kong Monetary Authority uses a measure of the monetary base that differs from the standard International Monetary Fund definition. We test both measures and find evidence of partial sterilization of international reserve flows. These tests indicate that Hong Kong does have a degree of short-term monetary autonomy.

Enhanced Energy Transfer Efficiency for IoT-Enabled Cyber-Physical Systems in 6G Edge Networks with WPT-MIMO-NOMA

The integration of wireless power transfer (WPT) with massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks can provide operational capabilities to energy-constrained Internet of Things (IoT) devices in cyber-physical systems such as smart autonomous vehicles. However, during downlink WPT, co-channel interference (CCI) can limit the energy efficiency (EE) gains in such systems. This paper proposes a user equipment (UE)–base station (BS) connection model to assign each UE to a single BS for WPT to mitigate CCI. An energy-efficient resource allocation scheme is developed that integrates the UE–BS connection approach with joint optimization of power control, time allocation, antenna selection, and subcarrier assignment. The proposed scheme improves EE by 24.72% and 33.76% under perfect and imperfect CSI conditions, respectively, compared to a benchmark scheme without UE–BS connections. The scheme requires fewer BS antennas to maximize EE and the distributed algorithm exhibits fast convergence. Furthermore, UE–BS connections’ impact on EE provided significant gains. Dedicated links improve EE by 24.72% (perfect CSI) and 33.76% (imperfect CSI) over standard connections. Imperfect CSI reduces EE, with the proposed scheme outperforming by 6.97% to 12.75% across error rates. More antennas enhance EE, with improvements of up to 123.12% (conventional MIMO) and 38.14% (massive MIMO) over standard setups. Larger convergence parameters improve convergence, achieving EE gains of 7.09% to 11.31% over the baseline with different convergence rates. The findings validate the effectiveness of the proposed techniques in improving WPT efficiency and EE in wireless-powered MIMO–NOMA networks.

Design and theoretical analysis of broadband bend-resistant low-loss hollow-core anti-resonant fiber

With the development of modern fiber-optic communication technology, bend-resistant low-loss fiber within the S+C+L bands is essential to meeting the requirements of dense wavelength division multiplexing (DWDM) systems, and a small-tube-added multi-nested hollow-core anti-resonant fiber (SM-HC-ARF) is proposed. In conventional double-nested HC-ARF, a pair of circular tubes are tangent to both the inner and outer tubes to form a multi-nested structure. A small tube is put in the gap between the nested structure to enhance the anti-resonance effect further. The influence of fiber structural parameters on transmission characteristics is analyzed by the finite element method combined with the perfect matching layer condition. The numerical results show that, in the range of 1460–1625 nm, the bending loss and the confinement loss are less than 1.17 (at a bending radius of 8 cm) and 0.80 dB/km, respectively. Specifically, at 1550 nm, the bending loss is 0.43 dB/km, and the confinement loss is 0.33 dB/km. The broadband anti-bending low-loss SM-HC-ARF can be expected to apply in the DWDM system and other optical communication technologies.

An experimental parametric study assessing the effect of a certain initial geometric imperfection on cylinder buckling

Given the sensitivity of axially-loaded cylinder buckling to geometric imperfections, the advent of additive manufacturing provides a compelling platform to assess subtle changes in initial configuration from an experimental perspective. The cylindrical form is ubiquitous in many load-bearing contexts, from soda cans to submarines to rocket fuel tanks. Despite the relative simplicity of the shape, it is striking how the assessment of buckling loads continues to pose strong challenges to the designers of these load-bearing components, often in a situation where weight-saving is a key constraint. Furthermore, this type of buckling typically corresponds to a sudden, severe, catastrophic event, and in addition to posing serious consequences in practice, this also presents challenges for those conducting high-fidelity experiments, especially in terms of repeatability. Any conditions that deviate from a pristine cylindrical shape, and purely axial loading, are the root-cause of the buckling variability. Typically, the slight deviations from the pristine (perfect) conditions are somewhat random and unpredictable in nature. 3D-printing now provides the experimentalist with the ability to produce cylindrical specimens to a very high degree of geometric fidelity, thus allowing a degree of control of the form of subtle geometric imperfections. This paper focuses attention on a specific form of deviation from a pristine cylindrical shape, in which the longitudinal sides follow a mild cosine wave form. The amplitude of this shape is varied (in both directions, i.e., inwards and outwards), and its effect on both the buckling load and buckling mode shape assessed experimentally, using the outcome of finite element analysis as a guide.

Numerical experiment of phase-matched ion-based high-order harmonic generation in the water-window x-ray spectral region via electromagnetic envelope equation

We present a phase-matching scheme for efficient high-order harmonic generation in the water-window x-ray spectral region using a 405-nm driving pulse. A high-intensity pulse (∼1016 W/cm2) is used to produce He1+ ions as the target medium, increasing the cutoff photon energy to the water-window x-ray spectral region. By adjusting the driving pulse divergence, the positive dipole phase variation balances the negative plasma dispersion and geometrical phase shift, achieving phase matching. Using the electromagnetic envelope equation coupled with the Keldysh ionization model, numerical experiments identify the optimal conditions. Results show that the relative conversion efficiencies of the 95th harmonic (4.26 nm) and the 169th harmonic (2.4 nm) reach 66% and 79% of the perfect phase-matching conditions, respectively.

Drone-based early detection of bark beetle infested spruce trees differs in endemic and epidemic populations

IntroductionEuropean forests face increasing threats due to climate change-induced stressors, which create the perfect conditions for bark beetle outbreaks. The most important spruce forest pest in Europe is the European Spruce Bark Beetle (Ips typographus L.). Effective management of I. typographus outbreaks necessitates the timely detection of recently attacked spruce trees, which is challenging given the difficulty in spotting symptoms on infested tree crowns. Bark beetle population density is one of many factors that can affect infestation rate and symptoms development. This study compares the appearance of early symptoms in endemic and epidemic bark beetle populations using highresolution Unmanned Aerial Vehicles (UAV) multispectral imagery.MethodsIn spring of 2022, host colonization by bark beetles was induced on groups of spruce trees growing in 10 sites in the Southern Alps, characterized by different population density (5 epidemic and 5 endemic). A multispectral sensor mounted on a drone captured images once every 2 weeks, from May to August 2022. The analyses of a set of vegetational indices allowed the actual infested trees’ reflectance features and symptoms appearance to be observed at each site, comparing them with those of unattacked trees.ResultsResults show that high bark beetles population density triggers a more rapid and intense response regarding the emergence of symptoms. Infested trees were detected at least 1 month before symptoms became evident to the human eye (red phase) in epidemic sites, while this was not possible in endemic sites. Key performing vegetation indices included NDVI (Normalized Difference Vegetation Index), SAVI (Soil Adjust Vegetation Index, with a correction factor of 0.44), and NDRE (Normalized Difference Red Edge index).DiscussionThis early-detection approach could allow automatic diagnosis of bark beetles’ infestations and provide useful guidance for the management of areas suffering pest outbreaks.

Empowering Aquarists a Comprehensive Study On IOT-Enabled Smart Aquarium Systems For Remote Monitoring And Control

owadays, a lot of people keep fish as pets at home and the aquarium keeper has been feeding the fish in the tanks, therefore appropriate setup and upkeep are required. Taking care of the aquarium appears to be somewhat tough for aquarists. The fish's quality of life depends on the aquarium being kept up properly. Changes in water quality, fish feeding, temperature management, light control, and the challenge of physically inspecting aquarium conditions are these problems are experienced.. As such, it is important to monitor the physical characteristics regularly and to improve the quality of the water. It has water quality management, which levels the aquarium to the perfect conditions by keeping an eye on the physical variations in the tank. Thus, the system that this model suggests is capable of real-time operation and is fitted with sensors. It carries out turbidity system, water renewal, temperature monitoring, and pH level detection in water and all these things are carried out in the ESP32 controller which contains an inbuit WiFi module. For large-scale aquaculture, an embedded system with a wireless network technology and a water quality testing unit was proposed. The aquarium's state is tracked and sent to the user's mobile application via Thingspeak IoT platfrom.

Automated Hydroponic Farm System

Current agriculture faces a multitude of issues – limited seasons, excessive pesticide use, sustainability concerns in organic farming, high carbon footprint, and inconsistent produce quality. Traditional methods, restricted by seasons and harming the environment with pesticides, are struggling to keep up with a changing world. This paper proposes a groundbreaking solution: an automated hydroponic farm system. Unlike traditional methods, this system allows year-round, pesticide-free production through advanced growing stations using a precise nutrient delivery technique (NFT). To create perfect growing conditions, a Greenhouse Climate Control System with various sensors regulates factors like temperature, humidity, and light. Additionally, a Central Console acts as the brain of the system, connecting everything and monitoring the entire farm. By automating these processes, this hydroponic system aims to revolutionize agriculture, offering a sustainable, efficient, and high-quality alternative.