Balanced Mode Research Articles

The Potential of Chat-Based Artificial Intelligence Models in Differentiating Between Keloid and Hypertrophic Scars: A Pilot Study.

Lasting scars such as keloids and hypertrophic scars adversely affect a patient's quality of life. However, these scars are frequently underdiagnosed because of the complexity of the current diagnostic criteria and classification systems. This study aimed to explore the application of Large Language Models (LLMs) such as ChatGPT in diagnosing scar conditions and to propose a more accessible and straightforward diagnostic approach. In this study, five artificial intelligence (AI) chatbots, including ChatGPT-4 (GPT-4), Bing Chat (Precise, Balanced, and Creative modes), and Bard, were evaluated for their ability to interpret clinical scar images using a standardized set of prompts. Thirty mock images of various scar types were analyzed, and each chatbot was queried five times to assess the diagnostic accuracy. GPT-4 had a significantly higher accuracy rate in diagnosing scars than Bing Chat. The overall accuracy rates of GPT-4 and Bing Chat were 36.0% and 22.0%, respectively (P = 0.027), with GPT-4 showing better performance in terms of specificity for keloids (0.6 vs. 0.006) and hypertrophic scars (0.72 vs. 0.0) than Bing Chat. Although currently available LLMs show potential for use in scar diagnostics, the current technology is still under development and is not yet sufficient for clinical application standards, highlighting the need for further advancements in AI for more accurate medical diagnostics. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online instructions to authors www.springer.com/00266 .

Features of Bioluminescence Dynamics of Photobacterium phosphoreum IMV B-7071

The problem of the prolonged and stable intensity of bioluminescent signals is relevant in the development of any test systems that use biological objects. The aim of this work was to study the features of bioluminescence dynamics of Photobacterium phosphoreum IMV B-7071 in a liquid and on different stationary media. Methods. Bioluminescence studies were performed in liquid, agarose, and cellulose-cotton media. Bacterial suspensions were cultivated at 21°C in the mediums with standard composition. We studied both the background glow and its dynamics under conditions of mixing a liquid medium. Bioluminescence was recorded using digital photography with subsequent image processing of the samples. The measurements of luminescence were made by digital photo or video recording using Olympus digital camera SP560UZ, CANON 700D, and mobile device camera Samsung Galaxy 9 Note with specialized applications for mobile devices "Colorimeter (Lab Tools Apps)" and Camera Color Counter (Keuwsoft) at maximum light sensitivity in the automatic white balance mode at a fixed distance from the sample. Image processing was carried out using ImageJ and Origin Pro. Spectra of bacterial luminescence and its dynamics over time were measured using an LOMO MDR-23 spectrometer in the range of 200–750 nm. Results. The results of the study prove that in aqueous or solid agar and also on cellulose cotton medium, the intensity of bioluminescence of P. phosphoreum gradually increases, reaching a maximum within approximately 2 days, after which it slowly fades. It was established that the bioluminescence of photobacterium P. phosphoreum is a non-stationary process and has characteristic features of temporal dynamics associated with both the dynamics of the oxygen concentration in the environment of bacterial suspensions and the dynamics of the bacterial population density. Analysis of the luminescence spectra of bacteria shows that luminescence occurs mainly in the blue and green regions of the spectrum with luminescence maxima in the range of 460–520 nm, but the ultra-weak glow is also registered in the UV and red spectral ranges. The variability of photobacterial luminescence spectra over time in the spectral ranges of the main luminophores causes color fluctuations between the blue and green ranges. Conclusions. The key parameters of multi-day background and short-term induced bioluminescence dynamics of photobacteria in different environments were clarified, and the certain variability of the spectral characteristics of luminescent radiation over time was shown. The revealed features of the dynamics of the bioluminescence of P. phosphoreum must be taken into account in practical application to assess the toxicity of substances of various nature, as well as in environmental monitoring.

Model predictive control of 3L‐NPC inverter to enhance fault ride through capability under unbalanced grid conditions

AbstractUnbalanced voltages are becoming increasingly common in distribution networks due to the growing integrations of distributed renewable energy resources as well as large loads such as electric vehicle chargers. Such unbalanced voltages introduce significant control challenges as they produce ripples in the controlling signals, impacting the operation of inverters during the unbalanced conditions. Therefore, this paper proposes a controlling algorithm for three‐level inverters aimed at suppressing these ripples on controlling signals; improving the overall performance of inverters, and consequently enhancing the fault ride‐through capability under unbalanced conditions and faults. The proposed controlling algorithm enables inverters to operate in either a balanced current output mode or a suppressed‐ripple active power output mode, depending on the specific event scenario and demands from the grid operators. Current harmonics are suppressed even under severe faults. For improving the voltage balance on the DC capacitors in three‐level inverters, an enhanced method of neutral point current prediction is presented. The proposed method ensures higher balancing accuracy through the use of weighted switching costs, avoiding the requirement of a balancing controller or current extrapolation. Simulation and experimental results demonstrate the effectiveness of the proposed controller for reliable grid operation.

Integrated energy hub dispatch with a multi-mode CAES–BESS hybrid system: An option-based hierarchical reinforcement learning approach

The high penetration of renewable energy sources (RES) in power generation has driven demand for advanced integrated energy management systems (IEMS). In this study, to address the challenges of insufficient adaptability to dynamic supply–demand, a multi-type energy IEMS combining compressed air energy storage (CAES) and a battery energy storage system (BESS) is proposed, which operates under a multi-mode energy storage (MES) mechanism with rapid response, long-term balance, and synergic adjustment modes. To address the complexity of sequential decisions, an option-critic based twin delayed deep deterministic policy gradient (OCTD3) algorithm is firstly proposed within the hierarchical reinforcement learning (HRL) framework, enhancing efficiency through encapsulation of subtasks within ”options”. Additionally, model precision is refined by fitting the electricity–gas–heat conversion dynamics of CAES under off-design conditions. Dispatch tasks are modeled as an option-based Semi-Markov Decision Process (SMDP) and optimized by the OCTD3 to improve the power fluctuations index (PFI), comprehensive costs index (CCI), and system response synergy index (SRSI). Comparative simulations reveal that the MES mechanism boosts SRSI by 91.8%, showcasing high adaptability to varied supply–demand scenarios. The OCTD3 algorithm develops five hybrid strategies for CAES–BESS across three modes, effectively cutting costs by reducing electricity purchases and fluctuations expenses, and lowering PFI by 42.2% through balancing peak–valley loads and swiftly responding to transient shifts.

Semantic segmentation algorithm for video from UAV based on adaptive keyframe scheduling via similarity measurement

Abstract Unmanned aerial vehicle (UAV) videos exhibit complex object motion features and significant differences between frame features. To solve the problems of feature information loss and drastic accuracy decline in applying the video semantic segmentation method based on the fixed-period update strategy of keyframes, a keyframe recognition method based on similarity measurement is proposed, forming a video semantic segmentation algorithm based on adaptive keyframe scheduling. one keyframe recognition method based on pixel similarity measurement is established by modeling the similarity relationship between low-level pixels in adjacent frames. Meanwhile, the other keyframe recognition method based on feature similarity measurement is established by constructing a shallow Siamese network to measure the similarity relationship between features of frames. Then a discriminative network is constructed based on the obtained similarity of inter frames, and the segmentation process is accelerated by reusing features of keyframes through the optical flow network. Thereby a video semantic segmentation method for UAV based on adaptive keyframe strategy is established. The effectiveness of the proposed video semantic segmentation algorithm is verified on UAVid dataset. The results demonstrated that the speed of the proposed algorithm reaches 53.2 FPS and 54.5 FPS on the premise that the mean intersection over union is higher than 40% (this value is compared with the segmentation accuracy in the balanced mode when the similarity threshold is 0.76 and 0.88, respectively), which is 18.5 FPS and 19.8 FPS higher than the PSPNet image semantic segmentation algorithm. In addition, analysis of experiment results shows that the pixel-similarity-based keyframe recognition is suitable for high-precision video semantic segmentation scenes that need to improve segmentation efficiency, and the feature-similarity-based keyframe recognition is more suitable for high real-time video semantic segmentation tasks that require a small decrease in overall algorithm accuracy. 
In a word, the proposed video semantic segmentation algorithm based on adaptive keyframe scheduling via similarity measurement can improve segmentation speed while ensuring segmentation accuracy and stability.

A non-intrusive technique for estimating the efficiency of low voltage three-phase induction motors

This paper introduces a non-intrusive technique based on the air–gap torque (AGT) method to estimate the efficiency of induction motors (IMs). The technique uses a 3rd-degree equation to calculate the sum of windage and friction losses (FWL) and rotor stray load losses (SLLr), considering the number of IM poles. IM speed is estimated using motor current signature analysis, and a new procedure to estimate stator resistance is presented. Efficiency is then determined by applying the estimated rotor speed, stator resistance, and the sum of FWL and SLLr in the AGT equations. This method requires only nameplate information, IM line voltages, and currents. Simulations and experimental tests for balanced, unbalanced, and harmonic feeding modes show the proposed technique’s estimated efficiency values are very close to measured values, unlike the AGT method. This demonstrates the proposed technique’s high accuracy, making it suitable for non-intrusive efficiency estimation of in-service IMs in industrial programs.

State-of-Charge Estimation of Reconfigurable Supercapacitor

Abstract A large body of research has been done on state-of-charge (SOC) estimate of supercapacitors in the literature; most of the works have been on SOC estimation of individual supercapacitor units. Nonetheless, supercapacitors are usually linked to balancing circuits in real-world applications in order to remove inter-cell imbalances. The cells’ system dynamics shift to a new mode when the balancing circuit is turned on, making the SOC calculation techniques that are currently in use inappropriate. Our proposal in this research is a Kalman filtering-based reconfigurable supercapacitor balancing system SOC estimate method. By fusing a reconfigurable balancing circuit with the equivalent circuit model of supercapacitors, we create a linear switching systems model. The switching system’s discrete-time form is shown, and its observability is examined. With filter gains dynamically modified according to the system mode, a switching Kalman filter is intended to estimate the SOC of the switched system. The accuracy of SOC estimation is greatly improved by the suggested method when supercapacitors are in the balancing mode, as confirmed by the simulation results.

Validation of LC-MS/MS method for opioid monitoring in Valencia City wastewater: Assessment of synthetic wastewater as potential aid

In this study, a comprehensive and sensitive method for the simultaneous detection of 17 opioids (OPs) and their human metabolites in wastewater using high-performance liquid chromatography coupled to tandem mass spectrometry was validated. The chromatographic separations of opioids were carried out on a Kinetex® Biphenyl column (1.7 μm, 100 Å, 50 × 2.1 mm). A synthetic wastewater approach was used for recovery studies to mimic a contaminant-free matrix. Two solid-phase extraction (SPE) sorbents (hydrophilic-lipophilic balance and mixed mode with the previous phase and a weak cationic exchange) were studied to optimize sample treatment and obtain higher recoveries. The mixed mode was chosen because the recoveries of 17 target analytes at three spiked concentrations (25, 50, and 100 ng mL−1) were > 80 % for 75 % of the analytes in a simulated wastewater. The intra- and inter-day relative standard deviations (RSDs) were between ±1 % and ±20 %. The method limits of quantification ranged from 5 to 25 ng L−1, the only exceptions being heroin (275 ng L−1) and morphine-3β-glucuronide (250 ng L−1). Suppression/enhancement is comparable between the synthetic and the influent wastewater. The analytical method was applied to the OPs analysis in twenty-one influent samples collected from the treatment plants treating the wastewater of Valencia City (Spain). Twelve OPs were detected with total daily concentrations ranging from 1 ng L−1 to 2135 ng L−1. The widespread presence of these compounds in water suggests potential widespread exposure, highlighting the need for increased environmental awareness. Furthermore, the estimated daily intake results raise concerns about opioid use as a potential future health and social issue.

Exploring the role of Mobility-as-a-Service in morning commuting trips

Promising the seamless integration of multiple transportation modes, Mobility-as-a-Service (MaaS) has gained popularity over the years, yet its effectiveness in enticing private car users and improving travel efficiency remains uncertain. This study explores the competitiveness of MaaS-enabled multi-modal travel options versus private car usage through equilibrium analysis. In addition to pricing that affects the fixed cost for travel, we examine the often overlooked inconvenience cost associated with multi-modal trips. We establish our analysis for the commuting problem of a one-origin-one-destination network, where a highway and a mass transit line connect the residential area and the central business district (CBD) area. Travelers choose their departure time and travel mode among auto, Park-and-Ride (PnR), ride-hailing and transit (RnT) to minimize their total travel cost. Inconvenience costs associated with searching for parking and waiting for ride-hailing are explicitly modeled. We analytically provide the mode share and departure time windows under all possible equilibria. Our findings reveal the complex nature of mode choice, distinctly affected by fixed and inconvenience costs, with demand playing an even more significant role. Notably, fixed costs set an entry fee to adopt different modes, and the feature of inconvenience costs affects the utilization of available transportation resources. More importantly, to benefit the overall system, we encourage maintaining a balanced mode share by implementing pricing and capacity strategies rather than aiming for a completer transition of private car users to MaaS.

Research on topology technology of integrated battery energy storage system with reconfigurable battery and converter

In traditional battery energy storage systems (BESS), batteries are usually connected in a simple series or parallel form, and separate converters and balancing modules are typically used for energy exchange between the battery and external sources, as well as for balancing energy between batteries. This paper proposes an integrated battery energy storage system (IBESS) with reconfigurable batteries and DC/DC converters, resulting in a more compact structure. The IBESS can reconfigure the connection of energy storage batteries based on the battery's status and external demand. The DC/DC converters can operate in different modes such as boost, buck, or buck-boost converters. The IBESS has five working modes: discharging mode, balancing mode, battery discharging and balancing mode, constant current and constant voltage (CCCV) charging mode and backup mode. To verify the feasibility of the proposed energy storage system, a model with four battery modules was built using MATLAB/SIMULINK, and the operation of all working modes was demonstrated. The simulation results verified the system's performance and reliability, demonstrating its flexibility and efficiency in different operating modes.

ChatGPT, Bard, Bing Chat, and Claude generate feedback for Chinese as foreign language writing: A comparative case study

AbstractThis comparative case study analyzes and evaluates the performance of four prevalent artificial intelligence (AI) models―ChatGPT, Google Bard, Microsoft Bing, and Claude―in generating feedback on Chinese as a Foreign Language writing. The study assessed the models' effectiveness, accuracy, alignment with pedagogical principles, and cultural appropriateness through a multi‐faceted data collection process involving student article writing, chatbot feedback, and teacher evaluation. The quantitative analysis of teacher ratings indicates that Claude demonstrated the highest average alignment with human instructor scores across the four articles, followed by Google Bard. Qualitative examination reveals differences in the types of feedback provided, with models excelling at surface‐level vocabulary, grammar, and mechanics critiques but limited in providing rhetorical, pragmatic, and structural feedback compared to teachers. While showing potential benefits, judicious integration of AI writing feedback tools upholding academic integrity is advised. This paper utilizes non‐Pro subscription plans for its research, ensuring accessibility by teachers or students without any cost. The date of access for these chatbots was September 20, 2023. The AI models used include ChatGPT based on OpenAI's GPT‐3.5 architecture with a knowledge cut‐off in January 2022, without Internet browsing capabilities; Google Bard from the Gemini family, version 1.0, which integrates internet‐based search; Microsoft Copilot (Balanced mode), which evolved from Bing Chat, providing information and content generation; and Claude version 2. This approach ensures the study's findings are applicable and replicable for educators and students utilizing freely available resources.

Active Equalization for Lithium-Iron Battery Pack Based on Reduced-Order Solving Strategy for the Hanoi Tower Problem

In order to address the energy imbalance issue of a series-connected lithium-iron battery pack, this paper proposes an active equalization method based on a reduced-order solving strategy for the Hanoi Tower problem. The proposed scheme utilizes a combined structure of a switching-network circuit and a bidirectional Cuk converter and leverages an ultracapacitor cell as the energy-transfer carrier. Simulation and comparison demonstrate that the exchange of unbalanced energy within the battery pack can be achieved. The proposed approach can effectively achieve various balancing modes such as cell-to-cell, cell-to-string, string-to-cell, and string-to-string with a relatively fast balancing speed.

Optimization method for capacity configuration and power allocation of electrolyzer array in off-grid integrated energy system

Hydrogen production using renewable energy is in line with China's the goal of carbon peak and carbon neutrality. The construction of off-grid hydrogen energy industrial park can effectively achieve local utilization of renewable energy and develop the green hydrogen industry. However, off-grid hydrogen energy industrial park has not the compensation and sustentation from large power grid, the stable operation and economic production of electrolyzer are affected by significant factors, such as power fluctuation and frequent start stop. Therefore, this paper proposed the optimization method for capacity configuration and power allocation of electrolyzer array in off-grid integrated energy system. Firstly, based on units of energy supply, energy conversion, and energy storage, a structural model of off-grid integrated energy system was established. Then, by analyzing the operational characteristics of single electrolyzer and electrolyzer array, flexible mode of multiple electrolyzers operating in combination was proposed. Furthermore, considering the hydrogen production cost, the mean of hydrogen production volatility and penalty cost, the capacity configuration and power allocation methods for electrolyzer array were proposed, and the optimization problem is solved with multi-objective particle swarm optimization algorithm. Finally, the hydrogen energy industrial park in Zhangye is taken as example to verify the effectiveness of above research content. Compared to a single type of alkaline electrolyzer, the mean of hydrogen production volatility of multiple electrolyzers operating in combination has decreased by 43.2 %, the hydrogen production quantity has increased by 9.74 %. Compared to a single type of proton exchange membrane electrolyzer, the hydrogen production cost has been reduced by 14.16 %. Compared with the balanced running mode, the flexible operation mode can improve the cost-effective and quantity of hydrogen production.

A comparison of high frequency force balance mode shape correction approaches for predicting wind effects on a high-rise building

A comparison of high frequency force balance mode shape correction approaches for predicting wind effects on a high-rise building

A CMOS BD-BCI: Neural Recorder with Two-Step Time-Domain Quantizer and Multi-Polar Stimulator with Dual-Mode Charge Balancing.

This work presents a bi-directional brain-computer interface (BD-BCI) including a high-dynamic-range (HDR) two-step time-domain neural acquisition (TTNA) system and a high-voltage (HV) multipolar neural stimulation system incorporating dual-mode time-based charge balancing (DTCB) technique. The proposed TTNA includes four independent recording modules that can sense microvolt neural signals while tolerating large stimulation artifacts. In addition, it exhibits an integrated input-referred noise of 2.3 μVrms from 0.1- to 250-Hz and can handle a linear input-signal swing of up to 340 mVPP. The multipolar stimulator is composed of four standalone stimulators each with a maximum current of up to 14 mA (±20-V of voltage compliance) and 8-bit resolution. An inter-channel interference cancellation circuitry is introduced to preserve the accuracy and effectiveness of the DTCB method in the multipolar-stimulation configuration. Fabricated in an HV 180-nm CMOS technology, the BD-BCI chipset undergoes extensive in-vitro and in-vivo evaluations. The recording system achieves a measured SNDR, SFDR, and CMRR of 84.8 dB, 89.6 dB, and >105 dB, respectively. The measurement results verify that the stimulation system is capable of performing high-precision charge balancing with ±2 mV and ±7.5 mV accuracy in the interpulse-bounded time-based charge balancing (TCB) and artifactless TCB modes, respectively.

Abstract SY22-01: A strategy to intervene mitotic kinases to induce mitotic catastrophe in cancer cells

Abstract Chromosomal instability (CIN) is an outstanding feature of cancer, which relates to intratumor heterogeneity, therapeutic resistance, and poor prognosis. While cancer cells can proliferate with CIN, experimentally induced aneuploidy is known to suppress cell growth, leading to the idea that extreme ploidy changes are detrimental to cancer cells. One of the major etiologies of CIN is abnormal kinetochore microtubule attachments, followed by chromosome missegregation. To avoid this, cells have evolved a robust system including two molecular networks for stabilizing and destabilizing microtubule attachments. Two mitotic kinases are involved in this system which have opposite but balanced mode of actions. We previously found that a wide range of cancer cells are defective for destabilization and results in an elevated rate of missegregation. In this study, we aimed to manipulate this kinase balance and found that weighing the balance to stabilizers can cause catastrophic chromosome segregation in mitosis, and such effect could be induced predominantly in cancer cells. These findings prompted us to undertake a screen for small molecules targeting the balanced activity of mitotic kinases. Citation Format: Motoko Takahashi, Minji Jo, Nana Kamakura, Chang Liu, Utako Kato, Toru Hirota. A strategy to intervene mitotic kinases to induce mitotic catastrophe in cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr SY22-01.

An Active Equalization Method for Cascade Utilization Lithium Battery Pack With Online Measurement of Electrochemical Impedance Spectroscopy

Abstract With the rapid development of new energy vehicles, a large number of lithium batteries have been produced, used and retired. The full utilization and safe use of the whole life cycle of the batteries have become a hot topic in the research field. Compared to brand new batteries, retired power batteries exhibit significant inconsistency and safety risks due to aging, thus necessitating effective battery equalization and safety monitoring methods. In this article, an active equalization method for cascade utilization lithium battery pack with online measurement of electrochemical impedance spectroscopy is proposed to actively equalize the retired battery pack and alleviate the inconsistency of the battery pack. Besides, the electrochemical impedance spectrum of the single battery is measured online without adding additional hardware circuit, so as to realize real-time safety monitoring and solve the safety problem of the battery. Finally, in order to verify the feasibility of the active equalization and electrochemical impedance spectrum monitoring scheme designed in this article, a simulation model is built based on MATLAB-Simulink platform. The simulation results show that the six batteries in the proposed scheme model complete the active equalization in about 710s, 850s and 740s respectively in the balance mode, charge mode and discharge mode, and the electrochemical impedance spectrum in the frequency range of 1-20KHz can be successfully measured.

Shallow geothermal potential and numerical modelling of the geo-exchange for a sustainable post-earthquake building reconstruction (Potenza River valley, Marche Region, Central Italy)

The southern part of the Marche Region (Italy) was hit in 2016 by dramatic seismic events that caused damages and fatalities. After these events, the national and local administrations started a development plan to improve the energy efficiency of the restored or reconstructed buildings. Shallow geothermal energy, consisting of closed-loop Borehole Heat Exchangers (BHEs) coupled with heat pumps, could represent a first-order renewable choice for indoor air conditioning (heating and cooling) systems. The feasibility and potential of the BHEs also match this technology's null visual outdoor impact which is paramount in preserving the landscape of the earthquake-affected areas. However, the exploitation, sustainability, and correct design of these systems require detailed knowledge of the ground's geological, hydrogeological, and thermophysical properties. In this framework, the present study was carried out to map and test, through the G.POT algorithm, the shallow geothermal potential and sustainability of the Potenza River valley through the publicly available data from the Italian Seismic Microzonation studies — an extensive database of geognostic drillings and other geological and geophysical surveys. This step allowed us to assign the main thermal parameters (thermal conductivity, volumetric heat capacity, specific heat extracted) to each geological layer and averaged them over the first 100 m (i.e., a typical depth for BHEs). All the data were then interpolated to produce geothermal thematic maps to visualize and compare the potential and adequacy of the territory for the installation of closed-loop BHEs. Finally, finite elements numerical models (FEFLOW® software) were developed in a balanced mode through the annual heating and cooling cycles to verify the sustainability of this renewable concerning the thermal impact induced to the ground by the BHEs during a long-term (20 years) operation.

Conspicuous chloroplast with light harvesting-photosystem I/II megacomplex in marine Prorocentrum cordatum.

Marine photosynthetic (micro)organisms drive multiple biogeochemical cycles and display a large diversity. Among them, the bloom-forming, free-living dinoflagellate Prorocentrum cordatum CCMP 1329 (formerly P. minimum) stands out with its distinct cell biological features. Here, we obtained insights into the structural properties of the chloroplast and the photosynthetic machinery of P. cordatum using microscopic and proteogenomic approaches. High-resolution FIB/SEM analysis revealed a single large chloroplast (∼40% of total cell volume) with a continuous barrel-like structure, completely lining the inner face of the cell envelope and enclosing a single reticular mitochondrium, the Golgi apparatus, as well as diverse storage inclusions. Enriched thylakoid membrane fractions of P. cordatum were comparatively analyzed with those of the well-studied model-species Arabidopsis (Arabidopsis thaliana) using 2D BN DIGE. Strikingly, P. cordatum possessed a large photosystem-light harvesting megacomplex (>1.5 MDa), which is dominated by photosystems I and II (PSI, PSII), chloroplast complex I, and chlorophyll a-b binding light harvesting complex proteins. This finding parallels the absence of grana in its chloroplast and distinguishes from the predominant separation of PSI and PSII complexes in A. thaliana, indicating a different mode of flux balancing. Except for the core elements of the ATP synthase and the cytb6f-complex, the composition of the other complexes (PSI, PSII, and pigment-binding proteins, PBPs) of P. cordatum differed markedly from those of A. thaliana. Furthermore, a high number of PBPs was detected, accounting for a large share of the total proteomic data (∼65%) and potentially providing P. cordatum with flexible adaptation to changing light regimes.

Dual-band independently tunable 8-element MIMO antenna for 5G smartphones

In this paper, a multi-input multi-output (MIMO) antenna for future mobile phone applications operating in sub-6 GHza using a novel combination of an E-shaped slot placed on the ground plane and an F-shaped probe is used to achieve a dual-band independently tunable antenna. The proposed antenna is not only self-isolated but it has also effectively achieved high isolation of greater than 17 dB in both 3.5 GHz (3.4 – 3.6 GHz) and 4.7 GHz (4.6 – 4.87 GHz) frequency bands for 8-element MIMO antenna configuration for 5G smartphones. The simple yet compact size of (0.035 λ0▪ 0.23 λ0), of the slot antenna produces a balanced slot mode which not only reduces the ground effects but also improves the isolation between two adjacent input ports. The novelty of the proposed dual-band MIMO antenna is its independent control of each band across a wide frequency band and results demonstrate higher efficiency (64% – 71%) and diversity gain performance in both frequency bands. Furthermore, the antenna is designed by the meticulous configurations of 8-antenna elements without employing any external decoupling structure to attain the desired polarization diversity. The prototype of this 8-element MIMO antenna is also fabricated and measured to validate its simulated performance. The simple structure of the proposed design and high efficiency makes it a promising candidate for 5G smartphones.