High Performance Research Articles

Bioinspired single-shot polarization photodetector based on four-directional grating arrays capped perovskite single-crystal thin film.

Polarization photodetectors (pol-PDs) have widespread applications in geological remote sensing, machine vision, biological medicine, and so on. However, commercial pol-PDs use bulky and complicated optical systems with lenses, polarizers, and mechanical spools, which are complex and cumbersome, and respond slowly. Inspired by the desert ants' compound eyes, we developed a single-shot pol-PD based on four-directional grating arrays capped perovskite single-crystal thin film without other standard polarization optics. Our pol-PD has a high detectivity, two orders of magnitude greater than that of commercial photodetectors, and exhibits high polarization sensitivity. The high performance of our pol-PD is due to the highly crystalline perovskite single-crystal thin film and regular nanograting structure, made by a nanoimprinting crystallization method. Our single-shot pol-PD is a compact on-chip optoelectronic device that demonstrates excellent performance in a wide range of applications including accurate bionic navigation, sharp image restoration in hazy scenes, stress visualization of polymers, and detection of cancerous areas in tissues without histological staining.

Location-Based Hybrid Video Streaming Protocol for VANETs

The services and applications provided by video streaming over Vehicular Ad-hoc Networks (VANETs) have recently become very attractive to technology users. In VANETs, the moving vehicles on the roads take great advantage of this radio link by exchanging information with each other related to the safety, traffic jams, accidents, and condition of the roads via video streaming. On the other hand, this transmission domain poses many challenging issues like frequent disconnections due to fast-speed vehicles, longer transmission delays, and inefficient link consumption etc. numbers of routing strategies have been proposed in the literature that aimed to address these challenges of an Intelligent Transportation System (ITS). This article is based on a Location-Based Hybrid Video Streaming Protocol (LBHVSP) that has been proposed with the intent to minimize the challenges related to video transmission as well as the attainment of high network performance. The idea presented is a motivation from the dynamic nature of transceiver and receiver transmission power, accompanied by the range-based localization techniques for inter-space computation of vehicular nodes. LBHVSP is a 2-way protocol that works as a combination of infrastructure-based and infrastructure-less wireless networks that tends to minimize the average packet delay for efficient utilization of bandwidth. It is a two-phase solution, firstly frames are transmitted to the second hop node available in the direct range that minimizes the traveling path in terms of hop count and ultimately yields minimal delay. Secondly, this technique utilizes the Road Side Units (RSUs) having wired connectivity for a faraway destination. Experimental results using different transmission scenarios reveal its efficacy by attaining maximum average packet throughput, minimum average packet drop rate, and minimum average per-packet delay in Signal Transmission Power and Packet Reception Power Threshold values. The proposed scheme has outperformed the state-of-the-art transmission scenarios in terms of static parameters. Varying transmission and reception powers subject to the inter-distance have shown remarkable outcomes. In comparison to pre-existing VANET protocols like DyTE and DSR, proposed scheme has shown an average improvement of 30% in packet drop rate, and 80% rise in throughput, approximately. Besides, our scheme has shown a remarkable decline in transmission delay as well. On comparing the LBHVSP performance against recent VANET communication protocol, it comes out that it attains the maximum throughput and delay improvement. Furthermore, to cater the packet drop, a smart re-transmission strategy should be designed particularly for multimedia streaming and video message exchange.

Superior conductive 1D and 2D network structured carbon-coated Ni-rich Li1.05Ni0.88Co0.08Mn0.04O2 as high-ion-diffusion cathodes for lithium-ion batteries.

Numerous studies have addressed the low electrical conductivity of Li1.05Ni0.88Co0.08Mn0.04O2 (Ni-rich NCM). Among these approaches, surface treatment using multiwalled carbon nanotubes (MWCNTs) has emerged as a promising strategy for enhancing the depolarization of Ni-rich NCM and improving its electrochemical performance. However, MWCNT coatings applied by various methods often result in agglomeration and increase the ion-transfer resistance of the coating layer, leading to degraded electrochemical performance. In this study, 1D and 2D network structures are assembled on Ni-rich NCM surfaces using a MWCNT solution dispersed in ethanol solvent by an incipient method. The resulting highly conductive network structure facilitates electron movement without interfering with Li-ion transport, enhancing the depolarization of Ni-rich NCM and enabling high electrochemical performance. The 1D and 2D network structure coated Ni-rich NCM exhibits an excellent rate capability of 87.64% at 3C/0.2C and a cycle retention of 94.53% after 50 cycles at 1C/1C. Moreover, the incipient method used herein effectively maximizes the electrochemical performance with less coating weight than other methods. These findings highlight the potential of the 1D and 2D network structure coated Ni-rich NCM for advanced energy storage applications.

Microstructure, Recovery Stress and Mechanical Property of Direct Energy Deposition Welded Fe-Mn-Si Based Shape Memory Alloy

Direct Energy Deposition (DED) is one of the main methods of additive manufacturing in which a feedstock material in the form of powder or wire is delivered to a substrate while an energy source, such as laser beam or electron beam, is simultaneously applied to melt the feedstock. In addition to fabricating complex three-dimensional shapes using computer aided design, the DED laser welding process can be employed to fill complex shaped gaps between two objects. In this study, 3 mm thick Fe-based shape memory alloy plates with a 45° groove were welded by DED using high manganese steel powder filler. The process parameters including scan speed, hatch spacing, and layer thickness were fixed at values of 840 mm/min, 0.3 mm, 0.15 mm, respectively and laser power was varied during the welding process from 150 W to 300 W. Microstructures of the welds showed different shapes and quantities of defects such as cracks, pores and a lack of fusion depending on the laser power used. Laser power of 150 W showed crack-free weldment with the highest mechanical properties. The tensile strength and recovery stress of the welded sample were higher than the base metal, demonstrating the potential high performance of welding Fe-Mn-Si shape memory alloy components using the L-DED.

High-Performance human resource practices: implications for discretionary work behaviour in higher educational institutions

Purpose Higher education institutions discretionally participate in THE training of citizens for a sustainable world. Empirical evidence argues the synergetic effect of high-performance human resource practices (H-PHRPs) on its outcomes. Scholars have, however, questioned the appropriateness and applicability of H-PHRPs in developing economies, one of the eye-catching debates being the implicit universality of H-PHRPs. Literature has also banded the H-PHRPS and established the antecedent role of H-PHRPS on its outcomes. This study aims to examine the relative importance of H-PHRPs on discretionary work behavior (DWB) using a sample from public university employees to confirm the external validity of H-PHRPS constructs by replicating the findings in an Eastern setting and, more so, a developing nation like Uganda. Design/methodology/approach In the study, the authors used relative analysis to determine the role of H-PHRPs in enhancing DWB. The authors examined performance-based compensation, employee training and development, employee empowerment, competence-based performance appraisal and merit-based promotion as the H-PHRPs. The authors selected a sample of employees from Ugandan Universities used an explanatory study design to test the antecedent role of H-PHRPs on DWB. Findings The research results show that individual H-PHRPs significantly affect DWB. As regards the relative importance of H-PHRPs on DWB, the findings further reveal that H-PHRPs predicts DWB over and above its individual components. Research limitations/implications The authors gathered the data from public universities; therefore, when applied to a scenario of private universities, the conclusions might not hold up. Therefore, to confirm the results of the current study, future research can take private universities into account. Although, the study was cross-sectional, high performance human resource strategies in an organization may evolve over time. This work paves the way for future longitudinal studies in the same field of study. Practical implications This research presents an understanding justification for human resources management strategies. Organizations’ managers should improve the morale of their employees through various management practices by strategically devising human resource practices geared toward enhancing employee DWB. Organizational managers ought to prioritize the high-performance practices in order of relative importance in enhancing employee DWB. By prioritizing human resource practices, like training and pay for performance, universities are able to proportionately direct distinctive focus on human resource practices that enhance employee behaviors. Originality/value The findings of the research have both empirical and theoretical significance. This is an innovative study that aims to determine the relative relevance of H-PHRPs on DWB by using a sample taken from Ugandan public universities which is a developing nation. From a theoretical standpoint, the study enhances the practicability of the social exchange theory by establishing that employees exhibit DWB to reciprocate the organization for the H-PHRPs provided by the organization.

Bonding Optimization Strategies for Flexibly Preparing Multi-Component Piezoelectric Crystals.

Flexible films with optimal piezoelectric performance and water-triggered dissolution behavior are fabricated using the co-dissolution-evaporation method by mixing trimethylchloromethyl ammonium chloride (TMCM-Cl), CdCl2, and polyethylene oxide (PEO, a water-soluble polymer). The resultant TMCM trichlorocadmium (TMCM-CdCl3) crystal/PEO film exhibited the highest piezoelectric coefficient (d33) compared to the films employing other polymers because PEO lacks electrophilic or nucleophilic side-chain groups and therefore exhibits relatively weaker and fewer bonding interactions with the crystal components. Furthermore, upon slightly increasing the amount of one precursor of TMCM-CdCl3 during co-dissolution, this component gained an advantage in the competition against PEO for bonding with the other precursor. This in turn improved the co-crystallization yield of TMCM-CdCl3 and further enhanced d33 to ≈71 pC/N, exceeding that of polyvinylidene fluoride (a commercial flexible piezoelectric) and most other molecular ferroelectric crystal-based flexible films. This study presents an important innovation and progress in the methodology and theory for maintaining a high piezoelectric performance during the preparation of flexible multi-component piezoelectric crystal films.

The glue that binds: how organizational identification drives innovation performance in foreign-owned subsidiaries

PurposeAlthough organizational identification has been recognized as crucial for multinational enterprises, its configurations regarding innovation performance at the subsidiary level have hitherto received scant attention. Accordingly, the purpose of this research is to identify the types of configurations in which organizational identification in foreign-owned subsidiaries leads to high innovation performance.Design/methodology/approachWe base our research on social identity theory and the neo-configurational perspective to test our framework using survey data collected from subsidiaries located in Thailand and Vietnam.FindingsOur results provide evidence that organizational identification serves as a glue that binds strong inter- and intra-organizational network relationships to drive innovation performance. While we find some variation in that pattern between the two host countries, it appears overall that the conditions of expatriates in top management and the geographic distance between home and host country only play a peripheral role. We identify the “integrated innovation driver” and “distant local hub” as two subsidiary archetypes that show how organizational identity can drive high innovation performance in subsidiaries.Originality/valueThis study is one of the first to empirically investigate the main complementing factors in the context of organizational identification and innovation in foreign-owned subsidiaries, which have previously predominantly been investigated in isolation of each other.

The potential of insulin resistance indices to predict non-alcoholic fatty liver disease in patients with type 2 diabetes

BackgroundThe triglyceride-glucose (TyG) index and related parameters, as well as the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), have been developed as insulin resistance markers to identify individuals at risk for non-alcoholic fatty liver disease (NAFLD). However, its use for predicting NAFLD in patients with type 2 diabetes mellitus (T2DM) remains unclear. In this study, we aimed to observe the performance of insulin resistance indices in diagnosing NAFLD combined with T2DM and to compare their diagnostic values in clinical practice.Patients and methodsOverall, 268 patients with T2DM from the Endocrinology Department of Jiangsu Provincial Hospital of Traditional Chinese Medicine were enrolled in this study and divided into two groups: an NAFLD group (T2DM with NAFLD) and a T2DM group (T2DM without NAFLD). General information and blood indicators of the participants were collected, and insulin resistance indices were calculated based on these data. Receiver operating characteristic (ROC) analysis was conducted to calculate the area under the curve (AUC) for insulin resistance-related indices, aiming to assess their ability to discriminate between T2DM patients with and without NAFLD.ResultsROC analysis revealed that among the five insulin resistance-related indices, four parameters (TyG, TyG-body mass index [BMI], TyG-waist circumference [WC], and TyG- (waist–hip ratio [WHR]) exhibited high predictive performance for identifying NAFLD, except for HOMA-IR (AUCs:0.710,0.738,0.737 and 0.730, respectivly). TyG-BMI demonstrated superior predictive value, especially in males. For males, the AUC for TyG-BMI was 0.764 (95% confidence interval [CI] 0.691–0.827). The sensitivity and specificity for male NAFLD were 90.32% and 47.89%, respectively. Moreover, in the Generalized linear regression models, there were positive associations of TyG, TyG-BMI, TyG-WC, TyG-WHR, and HOMA-IR with controlled attenuation parameter (CAP), with β values of 21.30, 0.745, 0.247, and 2.549 (all P < 0.001), respectively.ConclusionTyG-BMI is a promising predictor of NAFLD combined with T2DM, particularly in lean male patients.

Comprehensive and Sensitive Analysis of Total PAEs Using a Label-Free Zero-Voltage Photoelectrochemical Biosensor.

The sensing of phthalate esters (PAEs) is vital for people's health and environmental protection. This study aimed to develop a highly sensitive and selective photoelectrochemical (PEC) biosensor for PAEs analysis in complex samples. The biosensor is based on a CdS nanoparticle/TiO2 nanotube (CdS NP/TiO2 NT) electrode substrate and a truncated PAEs aptamer (PAEs-apt). By exploiting spatial variations in the potential resistance of the sensing interface, the biosensor achieved superior sensitivity in determining the concentration of PAEs compared to the SELEX aptamer. It exhibited a linear correlation in the range of 0.005 to 1 ng/mL with a detection limit of 1.67 ng/L. Furthermore, the biosensor displayed excellent selectivity for PAEs, with an analysis error factor below 0.277 when the concentration of interfering species was 100 times that of the target. The high performance of the biosensor was attributed to the excellent photoelectronic properties of CdS NPs/TiO2 NTs, high density of PAEs-apt for PAEs, high affinity of PAEs-apt for PAEs, and specific recognition of PAEs. Notably, this PEC biosensor could be used for the PAEs assay in urine and water samples, providing a sensitive and simple analytical method for detecting the same class of compounds with similar chemical structures in complex samples.

High performance and eco-friendly tannins glyoxal wood adhesives: Based on UV light-induced photocatalytic degradation of larch tannins

The development of tannins adhesives with high performance and eco-friendly properties is crucial for addressing the dependence of traditional formaldehyde-based wood adhesives on petrochemical resources and the harm of formaldehyde emission. However, conventional methods for preparing tannins adhesives generally involve the use of tannins with high mean degree of polymerization (mDP) and formaldehyde, resulting in poor bonding properties and formaldehyde emission, hindering their industrial application. Herein, the larch tannins (LT) were degraded by photocatalytic degradation to obtain tannins with different mDP, and the tannins glyoxal (G) adhesives were synthesized with different mass ratios of G to LT, then used to prepare plywood with poplar veneer. The effect of different mDP and different mass ratios of G to LT on the properties of adhesives such as viscosity, curing time, shear strength, formaldehyde emission, water insoluble rate, humidity absorption rate and thermal properties were explored. The findings indicated that photocatalysis could lead to regular degradation of LT, and the different mDP of the LT could be obtained by adjusting the photocatalytic degradation time in a certain time range (1–6 h). When the mass ratio of G to LT6 (the LT with the maximum formaldehyde reactivity and mDP 3.71after 6 h of photocatalytic degradation) was 10 %, the LT6–10 %G adhesives imparted to the plywood with excellent bonding strength and water resistance under the hot-pressing temperature 140 °C. The dry shear strength, 3 h hot water shear strength (63 °C) and 3 h boiling water shear strength were as high as 1.83, 1.12, and 0.83 MPa. Its superior bonding performance exceeded the requirements of the Chinese national standard (GB/T9846-2015, ≥0.70 MPa). The formaldehyde emission was 0.12 mg/L, lower than poplar veneer (0.23 mg/L). LT6–10 %G adhesives sufficiently to be considered as a substitute for the formaldehyde-based wood adhesives currently in use.

Design of a “binaural” hydroacoustic transducer

Purpose This study aims to design a piezoelectric sensor with high performance transmitting and receiving functions, which is characterized by simple structure and multifunctionality. Design/methodology/approach In accordance with the binaural principle, a binaural-sensitive element is constructed with the middle module transmitting the signal and the left and right modules receiving the signal. The traditional 1-3-2 piezoelectric composite material is selected for the sensitive element of the transmitting module, while the improved 1-3-2 piezoelectric composite material is selected for the sensitive element of the receiving module. The impact of varying the thickness of the transmitting module on its resonance frequency and the influence of varying the thickness of the receiving module on its anti-resonance frequency were investigated through simulations conducted using ANSYS finite element software. This was done to ascertain the optimal thickness dimensions and operating frequencies for the binaural sensitive elements. Findings At last, binaural transducers were constructed and subjected to experimental evaluation within an anechoic chamber. The experimental results demonstrate that the operating frequency of both the transmitting and receiving modules is 150 kHz, the transmitting voltage response is 160 dB, and the receiving sensitivity of the “left ear” is −192 dB, and the receiving sensitivity of the “right ear” is −190 dB. The objective of achieving high-performance transmitting and receiving within the same frequency range has been met. Originality/value A binaural sensitive element is proposed to realize high-performance transmission and reception in the same frequency range.

Optimization of Delay and Area for Approximate Radix-8 Booth Multiplier

This paper investigates the optimization of Radix-8 Booth Multipliers, which are essential for efficient arithmetic operations in modern digital systems, particularly in applications such as digital signal processing, telecommunications, and image processing where rapid and accurate calculations are crucial. The study aims to enhance performance by focusing on reducing both delay and area while ensuring that acceptable accuracy levels are maintained for error-tolerant applications. To achieve these optimization goals, we compare three methodologies: the Carry Save Adder (CSA), the Kogge Stone Adder (KSA), and the Carry Look-Ahead Adder (CLA), each of which presents unique advantages and trade-offs in terms of speed, area utilization, and power consumption. The results of our analysis demonstrate that the Kogge Stone Adder provides the best overall performance in terms of speed and area efficiency, making it the most suitable choice for optimizing Radix-8 Booth Multipliers, particularly in scenarios where high performance and efficient resource use are critical. By emphasizing these findings, this study contributes valuable insights into the design of more efficient multipliers that can meet the increasing demands of contemporary digital applications. Key Words: Radix-8 Booth Multiplier, approximate computing, delay optimization, area optimization, Carry Save Adder (CSA), Kogge Stone Adder (KSA), Carry Look-Ahead Adder (CLA), digital systems, arithmetic operations, performance enhancement, error-tolerant applications, partial product generation, hardware description languages (HDLs), digital signal processing, machine learning, approximation techniques, simulation and testing, power consumption, ASIC design.

The Association of β2-Microglobulin with Physical Performance in Chinese Hemodialysis Patients with and without Diabetes.

Higher β2-Microglobulin (β2-MG) is associated with aging, stroke and cognitive impairment, which are all connected with poor physical fitness. Poor physical function is ascribed to increasing mortality. However, there has been an academic dispute over the association of serum β2-MG with survival rate. Furthermore, diabetes mellitus (DM) has been well linked to poor physical function and a high level of β2-MG. We hypothesized that higher β2-MG could be associated with worse physical performance in hemodialysis (HD) patients, and that association could vary with diabetes. We conducted a multicenter cross-sectional study at seven HD centers in Shanghai and Suzhou, respectively, in China, where a collection was made of the clinical characteristics, laboratory indicator, physical performance and DM assessment. The physical function was measured by the Short Physical Performance Battery (SPPB), and SPPB score ≤9 as the cutoff for low physical performance.The patients were divided into two groups of low and high physical performance, before categorized into four subgroups based on the absence of diabetes and SPPB scores. Logistic regression analyses were conducted to explore the association of β2-MG with physical performance. The final analysis involved a total of 780 patients, 251(32.2%) having diabetes. In the total population, β2-MG was lower in those with low SPPB than in those with high SPPB. Only in non-diabetic patients, β2-MG was lower in the low SPPB group, and positively associated with SPPB and its three compenents scores. Regardless of diabetes status, those who had low SPPB were prone to be older, accompanied by the poor nutritional status. Addtionally, the diabetes patients tended to have shorter HD duration and higher body mass index than the non-diabetic patients. Both before and after the covariates adjusted, β2-MG was significantly associated with physical performance in HD patients without diabetes. Low level of β2-MG was significantly associated with poor physical performance in Chinese HD patients without DM.

Machine Learning Models Decoding the Association Between Urinary Stone Diseases and Metabolic Urinary Profiles

Background: Employing advanced machine learning models, we aim to identify biomarkers for urolithiasis from 24-h metabolic urinary abnormalities and study their associations with urinary stone diseases. Methods: We retrospectively recruited 468 patients at Peking Union Medical College Hospital who were diagnosed with urinary stone disease, including renal, ureteral, and multiple location stones, and had undergone a 24-h urine metabolic evaluation. We applied machine learning methods to identify biomarkers of urolithiasis from the urinary metabolite profiles. In total, 148 (34.02%) patients were with kidney stones, 34 (7.82%) with ureter stones, and 163 (34.83%) with multiple location stones, all of whom had detailed urinary metabolite data. Our analyses revealed that the Random Forest algorithm exhibited the highest predictive accuracy, with AUC values of 0.809 for kidney stones, 0.99 for ureter stones, and 0.775 for multiple location stones. The Super Learner Ensemble Method also demonstrated high predictive performance with slightly lower AUC values compared to Random Forest. Further analysis using multivariate logistic regression identified significant features for each stone type based on the Random Forest method. Results: We found that 24-h urinary magnesium was positively associated with both kidney stones and multiple location stones (OR = 1.195 [1.06–1.3525] and 1.3258 [1.1814–1.4949]) due to its high correlation with urinary phosphorus, while 24-h urinary creatinine was a protective factor for kidney stones and ureter stones, with ORs of 0.9533 [0.9117–0.996] and 0.8572 [0.8182–0.8959]. eGFR was a risk factor for ureter stones and multiple location stones, with ORs of 1.0145 [1.0084–1.0209] and 1.0148 [1.0077–1.0223]. Conclusion: Machine learning techniques show promise in revealing the links between urological stone disease and 24-h urinary metabolic data. Enhancing the prediction accuracy of these models leads to improved dietary or pharmacological prevention strategies.

High temperature performance of recycled fine concrete

The objective of this study is to explore the physical and mechanical behaviour of concretes comprising four different ratios of recycled fine (RF), namely (5%, 10%, 15% and 20%) along with that of a reference concrete (Cref-0%), under three different heating–cooling cycles (200 °C, 400 °C and 600 °C). The thermal properties of concrete during heating and cooling (20 °C – 600 °C – 20 °C) were also investigated. It was determined that the physical properties (mass loss and ethanol porosity) of recycled concrete (RC) with 5% of recycled fine (RC-5%) were similar to those of Cref-0%. At ambient temperatures, the higher the ratio of recycled fines, the lower the residual compressive strength and residual elastic modulus of the recycled concrete. After thermal loading at 600 °C, the residual mechanical properties of all types of concrete were equivalent, regardless of the content recycled fine.

Heat-Resistant Shape Memory Fully Biobased Epoxy Resins with High Storage Modulus and Recycle Performance

Heat-Resistant Shape Memory Fully Biobased Epoxy Resins with High Storage Modulus and Recycle Performance

Real-Time On-Site Ground-Motion Prediction Using ResNet

Abstract On-site warnings can decrease the range of late alert zone during earthquakes. This study develops a deep learning model to predict whether the maximum peak ground acceleration at a station exceeds 25 Gal based on the waveform of the initial P-wave. A ResNet architecture model is developed to address the degradation problem in multilayered models, thereby enhancing performance. The model exhibits high performance for a test dataset, achieving F1-scores higher than 90% over various time windows, and outperforms the traditional progressive displacement value (Pdv) method and newer convolutional neural network (CNN) methods. Ground motion of two actual earthquakes are applied to test the model and validate its prediction capabilities, and the results indicate that the proposed model has higher accuracy and speed than Pdv and CNN methods. In addition, the model is integrated with the Earthworm earthquake early warning system for real-time waveform analysis and prediction, extending the model’s applicability beyond experimental stages to online systems. The proposed method is also tested using data from earthquakes that occurred in March 2023.

High Performance Bounded Finite Time Control for Linear Systems With Input Saturation

ABSTRACTReal‐world dynamical controlled systems are often subject to input saturation due to the physical constraints of actuators. This causes the response performance of the system to be degraded. To this end, we propose a high‐performance bounded finite time control (HP‐BFTC) method based on sliding mode control for finite time tracking of linear systems with input saturation. In this method, a novel concept of rate regulation finite‐time stability is proposed to achieve better steady‐state performance. A bounded controller based on sliding mode control is proposed to achieve finite‐time stability in rate regulation, wherein a finite time approach rate based on an inverse tangent function is presented to alleviate chattering caused by sign function, and two control parameters are introduced to improve response performance. The rate regulation finite‐time stability of the system is proved in the estimated domain of attraction. In addition, a parameter tuning principle is given to enhance the response performance of the closed‐loop system in transient and steady state. The superiority of the proposed method in performance is verified by a case study.

Predictive modeling of ash and moisture content in acid-treated walnut shells using artificial neural networks

ABSTRACT In this paper, the use of artificial neural networks (ANN) to predict changes in ash and moisture content (MC) of walnut shells after acidic pretreatment was investigated. The physicochemical and structural properties of walnut shells were analyzed, as well as the influential parameters on the changes of these studied variables. The study aimed to determine the changes in the walnut shells composition and evaluate the possibility of using the ANN model to predict the above-mentioned initial variables. The ANN model showed extremely high performance in modeling, with a coefficient of determination (R2) of 0.99 for ash and 0.90 for MC and low values of root mean square error (RMSE) and χ2, indicating the accuracy of the model in predicting the composition of walnut shells after acidic pretreatment. This study confirms the potential of ANN in accurately modeling changes in the composition of walnut shells and paves the way for further research on a wider range of crops and different pretreatments.

How does cloning change phenolics, minerals and antioxidant activity in Helichrysum arenarium (L.) Moench (Clone A, Clone B)?

Tissue culture and cloning are valuable techniques in plant biology research as they enable the production of genetically identical plants, which may be utilized for many purposes such as crop enhancement, plant breeding, and genetic manipulation. Helichrysum arenarium (L.) Moench (HA), also known as immortelle or strawflower (Asteraceae), is a species of flowering plant in the sunflower family. In this study, the aerial part of two Clones (Clone A, Clone B) of H. arenarium were used to consider the effect of Clones on the phenolics, minerals, and antioxidant activities. The methanol extracts were analyzed and compared for phenolic compounds and antioxidant activities. Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) is a widely used method for the determination of a wide range of elements in plant materials, including macro and micro elements. Calcium and potassium are the major mineral elements. The phenolics were identified and quantified using high performance liquid chromatography combined with tandem mass spectrometry (HPLC-MS/MS). The highest caffeic acid was determined in the methanolic extract, followed by protocatechuic aldehyde and protocatechuic acid.