bluuebunny/crossref_metadata_2025 huggingface dataset:
Antimicrobial Activity and Mechanisms of Punicalagin against Vibrio parahaemolyticus
Authors: Liu Hongli , Zhu Wenxiu , Zou Yue , Xia Xiaodong
Published: April 2024

This study sought to explore the antimicrobial activity of punicalagin against V. parahaemolyticus and its potential modes of action. V. parahaemolyticus ATCC 17802 and RIMD 2210633Sm were exposed to punicalagin, and the energy production, membrane potential, and envelope permeability, as well as the interaction with cell biomolecules, were measured using a variety of fluorescent probes combined with electrophoresis and Raman spectroscopy. Punicalagin treatment disrupted the envelope integrity and induced a decrease in intracellular ATP and pH. The uptake of 1-N-phenyl-naphtylamine (NPN) demonstrated that punicalagin weakened the outer membrane. Punicalagin damaged the cytoplasmic membrane, as indicated by the membrane depolarization and the leakage of intracellular potassium ions, proteins, and nucleic acids. Electronic microscopy observation visualized the cell damage caused by punicalagin. Further, gel electrophoresis coupled with the Raman spectrum assay revealed that punicalagin affected the protein expression of V. parahaemolyticus, and there was no effect on the integrity of genomic DNA. Therefore, the cell envelope and proteins of V. parahaemolyticus were the assailable targets of punicalagin treatment. These findings suggested that punicalagin may be promising as a natural bacteriostatic agent to control the growth of V. parahaemolyticus.
Efficient Anthocyanin Recovery from Black Bean Hulls Using Eutectic Mixtures: A Sustainable Approach for Natural Dye Development
Authors: Kuasnei Mayara , Benvenutti Laís , Fernando dos Santos David , Ferreira Sandra Regina Salvador , Pinto Vânia Zanella , Ferreira Zielinski Acácio Antonio
Published: April 2024

There is a growing interest in exploring new natural sources of colorants. This study aimed to extract anthocyanins from broken black bean hulls (Phaseolus vulgaris L.) by modifying water with a eutectic mixture (choline chloride:citric acid (ChCl:Ca)). Ultrasound-assisted extraction (UAE) was employed and optimized in terms of temperature (30–70 °C), ultrasound power (150–450 W), and eutectic mixture concentration in water (1–9% (w/v)), resulting in an optimal condition of 66 °C, 420 W, and 8.2% (w/v), respectively. The main quantified anthocyanins were delphinidin-3-O-glycoside, petunidin-3-O-glycoside, and malvidin-3-O-glycoside. The half-life of the anthocyanins at 60 °C increased twelvefold in the eutectic mixture extract compared to the control, and when exposed to light, the half-life was 10 times longer, indicating greater resistance of anthocyanins in the extracted eutectic mixture. Additionally, the extracts were concentrated through centrifuge-assisted cryoconcentration, with the initial cycle almost double the extract value, making this result more favorable regarding green metrics. The first concentration cycle, which showed vibrant colors of anthocyanins, was selected to analyze the color change at different pH levels. In general, the technology that uses eutectic mixtures as water modifiers followed by cryoconcentration proved to be efficient for use as indicators in packaging, both in quantity and quality of anthocyanins.
Detecting DC Electrical Resistivity Changes in Seismic Active Areas: State-of-the-Art and Future Directions
Authors: Lapenna Vincenzo
Published: April 2024

In this paper, a critical review of the geoelectrical monitoring activities carried out in seismically active areas is presented and discussed. The electrical resistivity of rocks is one of the geophysical parameters of greatest interest in the study of possible seismic precursors, and it is strongly influenced by the presence of highly fractured zones with high permeability and fluid levels. The analysis in the present study was carried out on results obtained over the last 50 years in seismic zones in China, Japan, the USA and Russia. These past works made it possible to classify the different monitoring strategies, analyze the theoretical models for interpreting possible correlations between anomalies in resistivity signals and local seismicity, and identify the main scientific and technological gaps in the literature. In addition, great attention has been paid to some recent works on the study of the correlations between focal mechanisms and the shapes of anomalous patterns in resistivity time series. Finally, some future scenarios for the development of new activities in this field have been identified.
Treatment-Free Remission in Chronic Myeloid Leukemia
Authors: Bourne Garrett , Bhatia Ravi , Jamy Omer
Published: April 2024

With the discovery of tyrosine kinase inhibitors (TKIs), overall survival in patients with chronic myeloid leukemia (CML) now approaches that of the general population. While these TKIs have proven to be lifesaving, remaining on them lifelong creates both physical and financial burdens for patients. Recently, multiple trials have begun looking into the efficacy of trialing patients off these TKIs to see if they can sustain treatment-free remission (TFR). TFR eligibility is currently limited to a small population of patients with both robust and sustained responses to TKIs. Currently, for those who attempt a trial of TFR, the average success rates are promising, with anywhere from 38 to 54% of patients experiencing sustained TFR. For those who fail to maintain sustained TFR, safety results to date are reassuring, with almost all patients successfully responding to the re-initiation of TKIs, with death and disease progression being very rare complications. Moving forward, research is being conducted to more accurately risk stratify patients at diagnosis and pair them with optimized upfront treatment regimens aimed at increasing candidacy for the trial of TFR.
Artificial Intelligence, Intrapartum Ultrasound and Dystocic Delivery: AIDA (Artificial Intelligence Dystocia Algorithm), a Promising Helping Decision Support System
Authors: Malvasi Antonio , Malgieri Lorenzo E. , Cicinelli Ettore , Vimercati Antonella , D’Amato Antonio , Dellino Miriam , Trojano Giuseppe , Difonzo Tommaso , Beck Renata , Tinelli Andrea
Published: April 2024

The position of the fetal head during engagement and progression in the birth canal is the primary cause of dystocic labor and arrest of progression, often due to malposition and malrotation. The authors performed an investigation on pregnant women in labor, who all underwent vaginal digital examination by obstetricians and midwives as well as intrapartum ultrasonography to collect four “geometric parameters”, measured in all the women. All parameters were measured using artificial intelligence and machine learning algorithms, called AIDA (artificial intelligence dystocia algorithm), which incorporates a human-in-the-loop approach, that is, to use AI (artificial intelligence) algorithms that prioritize the physician’s decision and explainable artificial intelligence (XAI). The AIDA was structured into five classes. After a number of “geometric parameters” were collected, the data obtained from the AIDA analysis were entered into a red, yellow, or green zone, linked to the analysis of the progress of labor. Using the AIDA analysis, we were able to identify five reference classes for patients in labor, each of which had a certain sort of birth outcome. A 100% cesarean birth prediction was made in two of these five classes. The use of artificial intelligence, through the evaluation of certain obstetric parameters in specific decision-making algorithms, allows physicians to systematically understand how the results of the algorithms can be explained. This approach can be useful in evaluating the progress of labor and predicting the labor outcome, including spontaneous, whether operative VD (vaginal delivery) should be attempted, or if ICD (intrapartum cesarean delivery) is preferable or necessary.
Phytophthora sojae Effector PsAvh113 Targets Transcription Factors in Nicotiana benthamiana
Authors: Wu Shuai , Shi Jinxia , Zheng Qi , Ma Yuqin , Zhou Wenjun , Mao Chengjie , Chen Chengjie , Fang Zhengwu , Xia Rui , Qiao Yongli
Published: April 2024

Phytophthora sojae is a type of pathogenic oomycete that causes Phytophthora root stem rot (PRSR), which can seriously affect the soybean yield and quality. To subvert immunity, P. sojae secretes a large quantity of effectors. However, the molecular mechanisms regulated by most P. sojae effectors, and their host targets remain unexplored. Previous studies have shown that the expression of PsAvh113, an effector secreted by Phytophthora sojae, enhances viral RNA accumulations and symptoms in Nicotiana benthamiana via VIVE assay. In this study, we analyzed RNA-sequencing data based on disease symptoms in N. benthamiana leaves that were either mocked or infiltrated with PVX carrying the empty vector (EV) and PsAvh113. We identified 1769 differentially expressed genes (DEGs) dependent on PsAvh113. Using stricter criteria screening and Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) analysis of DEGs, we found that 38 genes were closely enriched in response to PsAvh113 expression. We selected three genes of N. benthamiana (NbNAC86, NbMyb4, and NbERF114) and found their transcriptional levels significantly upregulated in N. benthamiana infected with PVX carrying PsAvh113. Furthermore, individual silencing of these three genes promoted P. capsici infection, while their overexpression increased resistance to P. capsici in N. benthamiana. Our results show that PsAvh113 interacts with transcription factors NbMyb4 and NbERF114 in vivo. Collectively, these data may help us understand the pathogenic mechanism of effectors and manage PRSR in soybeans.
Integrated Transcriptomics and Metabolomics Analysis Reveal the Regulatory Mechanisms Underlying Sodium Butyrate-Induced Carotenoid Biosynthesis in Rhodotorula glutinis
Authors: Huang Xingyu , Fan Jingdie , Guo Caina , Chen Yuan , Qiu Jingwen , Zhang Qi
Published: April 2024

Sodium butyrate (SB) is a histone deacetylase inhibitor that can induce changes in gene expression and secondary metabolite titers by inhibiting histone deacetylation. Our preliminary analysis also indicated that SB significantly enhanced the biosynthesis of carotenoids in the Rhodotorula glutinis strain YM25079, although the underlying regulatory mechanisms remained unclear. Based on an integrated analysis of transcriptomics and metabolomics, this study revealed changes in cell membrane stability, DNA and protein methylation levels, amino acid metabolism, and oxidative stress in the strain YM25079 under SB exposure. Among them, the upregulation of oxidative stress may be a contributing factor for the increase in carotenoid biosynthesis, subsequently enhancing the strain resistance to oxidative stress and maintaining the membrane fluidity and function for normal cell growth. To summarize, our results showed that SB promoted carotenoid synthesis in the Rhodotorula glutinis strain YM25079 and increased the levels of the key metabolites and regulators involved in the stress response of yeast cells. Additionally, epigenetic modifiers were applied to produce fungal carotenoid, providing a novel and promising strategy for the biosynthesis of yeast-based carotenoids.
Systems Reliability and Data Driven Analysis for Marine Machinery Maintenance Planning and Decision Making
Authors: Daya Abdullahi Abdulkarim , Lazakis Iraklis
Published: April 2024

Understanding component criticality in machinery performance degradation is important in ensuring the reliability and availability of ship systems, particularly considering the nature of ship operations requiring extended voyage periods, usually traversing regions with multiple climate and environmental conditions. Exposing the machinery system to varying degrees of load and operational conditions could lead to rapid degradation and reduced reliability. This research proposes a tailored solution by identifying critical components, the root causes of maintenance delays, understanding the factors influencing system reliability, and recognising failure-prone components. This paper proposes a hybrid approach using reliability analysis tools and machine learning. It uses dynamic fault tree analysis (DFTA) to determine how reliable and important a system is, as well as Bayesian belief network (BBN) availability analysis to assist with maintenance decisions. Furthermore, we developed an artificial neural network (ANN) fault detection model to identify the faults responsible for system unreliability. We conducted a case study on a ship power generation system, identifying the components critical to maintenance and defects contributing to such failures. Using reliability importance measures and minimal cut sets, we isolated all faults contributing over 40% of subsystem failures and related events. Among the 4 MDGs, the lubricating system had the highest average availability of 67%, while the cooling system had the lowest at 38% using the BBN availability outcome. Therefore, the BBN DSS recommended corrective action and ConMon as maintenance strategies due to the frequent failures of certain critical parts. ANN found overheating when MDG output was above 180 kVA, linking component failure to generator performance. The findings improve ship system reliability and availability by reducing failures and improving maintenance strategies.
Spring-Damped Underactuated Swashplateless Rotor on a Bicopter Unmanned Aerial Vehicle
Authors: Guan Haofei , Wong K. C.
Published: April 2024

The stabilisation capabilities of unmanned aerial vehicles (UAVs) with bicopter underactuated swashplateless rotors are highly sensitive to motor-induced vibration. Due to the requirement of the active control of underactuated swashplateless rotors, conventional designs are limited in reducing vibration through control optimisation. A solution with customized passive spring-damping structures on a unique underactuated swashplateless rotor of a tiltrotor bicopter platform is presented. The implementation of this structure effectively reduces the self-coherent vibration in flights. As a result, a higher level of control authority has been achieved without setting excessive low-pass filtering for vibration. Experimentally obtained inertial measurement unit (IMU) data, rotor speed, rotor tilt angle, and the cyclic stator response are presented for comparison with Simulink model predictions.
Unraveling the Complexity of Inverting the Sturm–Liouville Boundary Value Problem to Its Canonical Form
Authors: Karjanto Natanael , Sadhani Peter
Published: April 2024

The Sturm–Liouville boundary value problem (SLBVP) stands as a fundamental cornerstone in the realm of mathematical analysis and physical modeling. Also known as the Sturm–Liouville problem (SLP), this paper explores the intricacies of this classical problem, particularly the relationship between its canonical and Liouville normal (Schrödinger) forms. While the conversion from the canonical to Schrödinger form using Liouville’s transformation is well known in the literature, the inverse transformation seems to be neglected. Our study attempts to fill this gap by investigating the inverse of Liouville’s transformation, that is, given any SLP in the Schrödinger form with some invariant function, we seek the SLP in its canonical form. By closely examining the second Paine–de Hoog–Anderson (PdHA) problem, we argue that retrieving the SLP in its canonical form can be notoriously difficult and can even be impossible to achieve in its exact form. Finding the inverse relationship between the two independent variables seems to be the main obstacle. We confirm this claim by considering four different scenarios, depending on the potential and density functions that appear in the corresponding invariant function. In the second PdHA problem, this invariant function takes a reciprocal quadratic binomial form. In some cases, the inverse Liouville transformation produces an exact expression for the SLP in its canonical form. In other situations, however, while an exact canonical form is not possible to obtain, we successfully derived the SLP in its canonical form asymptotically.
On the Integrability of Persistent Quadratic Three-Dimensional Systems
Authors: Ferčec Brigita , Žulj Maja , Mencinger Matej
Published: April 2024

We consider a nine-parameter familiy of 3D quadratic systems, x˙=x+P2(x,y,z), y˙=−y+Q2(x,y,z), z˙=−z+R2(x,y,z), where P2,Q2,R2 are quadratic polynomials, in terms of integrability. We find necessary and sufficient conditions for the existence of two independent first integrals of corresponding semi-persistent, weakly persistent, and persistent systems. Unlike some of the earlier works, which primarily focus on planar systems, our research covers three-dimensional spaces, offering new insights into the complex dynamics that are not typically apparent in lower dimensions.
A New Robust Iterative Scheme Applied in Solving a Fractional Diffusion Model for Oxygen Delivery via a Capillary of Tissues
Authors: Okeke Godwin Amechi , Udo Akanimo Victor , Alharthi Nadiyah Hussain , Alqahtani Rubayyi T.
Published: April 2024

In this paper, we constructed a new and robust fixed point iterative scheme called the UO iterative scheme for the approximation of a contraction mapping. The scheme converges strongly to the fixed point of a contraction mapping. A rate of convergence result is shown with an example, and our scheme, when compared, converges faster than some existing iterative schemes in the literature. Furthermore, the stability and data dependence results are shown. Our new scheme is applied in the approximation of the solution to the oxygen diffusion model. Finally, our results are applied in the approximation of the solution to the boundary value problems using Green’s functions with an example.
Improving Oriented Object Detection by Scene Classification and Task-Aligned Focal Loss
Authors: Qian Xiaoliang , Gao Shaoguan , Deng Wei , Wang Wei
Published: April 2024

Oriented object detection (OOD) can precisely detect objects with arbitrary direction in remote sensing images (RSIs). Up to now, the two-stage OOD methods have attracted more attention because of their high detection accuracy. However, the two-stage methods only rely on the features of each proposal for object recognition, which leads to the misclassification problem because of the intra-class diversity, inter-class similarity and clutter backgrounds in RSIs. To address the above problem, an OOD model combining scene classification is proposed. Considering the fact that each foreground object has a strong contextual relationship with the scene of the RSI, a scene classification branch is added to the baseline OOD model, and the scene classification result of input RSI is used to exclude the impossible categories. To focus on the hard instances and enhance the consistency between classification and regression, a task-aligned focal loss (TFL) which combines the classification difficulty with the regression loss is proposed, and TFL assigns lager weights to the hard instances and optimizes the classification and regression branches simultaneously. The ablation study proves the effectiveness of scene classification branch, TFL and their combination. The comparisons with 15 and 14 OOD methods on the DOTA and DIOR-R datasets validate the superiority of our method.
On Intersections of B-Spline Curves
Authors: Yu Ying-Ying , Li Xin , Ji Ye
Published: April 2024

Bézier and B-spline curves are foundational tools for curve representation in computer graphics and computer-aided geometric design, with their intersection computation presenting a fundamental challenge in geometric modeling. This study introduces an innovative algorithm that quickly and effectively resolves intersections between Bézier and B-spline curves. The number of intersections between the two input curves within a specified region is initially determined by applying the resultant of a polynomial system and Sturm’s theorem. Subsequently, the potential region of the intersection is established through the utilization of the pseudo-curvature-based subdivision scheme and the bounding box detection technique. The projected Gauss-Newton method is ultimately employed to efficiently converge to the intersection. The robustness and efficiency of the proposed algorithm are demonstrated through numerical experiments, demonstrating a speedup of 3 to 150 times over traditional methods.
Abnormal Monitoring Data Detection Based on Matrix Manipulation and the Cuckoo Search Algorithm
Authors: Meng Zhenzhu , Wang Yiren , Zheng Sen , Wang Xiao , Liu Dan , Zhang Jinxin , Shao Yiting
Published: April 2024

Structural health monitoring is an effective method to evaluate the safety status of dams. Measurement error is an important factor which affects the accuracy of monitoring data modeling. Processing the abnormal monitoring data before data analysis is a necessary step to ensure the reliability of the analysis. In this paper, we proposed a method to process the abnormal dam displacement monitoring data on the basis of matrix manipulation and Cuckoo Search algorithm. We first generate a scatter plot of the monitoring data and exported the matrix of the image. The scatter plot of monitoring data includes isolate outliers, clusters of outliers, and clusters of normal points. The gray scales of isolated outliers are reduced using Gaussian blur. Then, the isolated outliers are eliminated using Ostu binarization. We then use the Cuckoo Search algorithm to distinguish the clusters of outliers and clusters of normal points to identify the process line. To evaluate the performance of the proposed data processing method, we also fitted the data processed by the proposed method and by the commonly used 3-σ method using a regression model, respectively. Results indicate that the proposed method has a better performance in abnormal detection compared with the 3-σ method.
Exploring Dynamic Spalling Behavior in Rock–Shotcrete Combinations: A Theoretical and Numerical Investigation
Authors: Luo Lin , Rui Yichao , Qiu Jiadong , Li Chongjin , Liu Xiong , Chen Cong
Published: April 2024

Spalling is a widespread dynamic disaster during blasting excavation in underground engineering. To clarify the coupled dynamic response and spalling behavior of an underground tunnel with a spray anchor, an investigation based on the rock–shotcrete combination was conducted using theoretical and numerical methods. The mathematical representation of stress wave propagation between rock and shotcrete was deduced based on the elastic stress wave theory. A novel method for predicting the location and time of initial spalling in a rock–shotcrete combination was proposed. A numerical simulation was conducted to verify the validity of the proposed theoretical method. In addition, the effect of the material’s tensile strength, the loading amplitude, and the thickness of shotcrete on the stress evolution and spalling characteristics was studied. The results demonstrate that the initial spalling locations are sensitive to the relationship between the normalized tensile strength of the rock, shotcrete, and interface. A high incident amplitude can cause the initial spalling in rock, and the shotcrete or rock–shotcrete interface can cause initial spalling due to a low incident amplitude. The stress evolution and spalling characteristics are sensitive to the thickness of shotcrete. The location of the initial spalling failure changes with the thickness of the shotcrete. An appropriate increment in thickness and normalized strength of the shotcrete is beneficial to the dynamic stability of underground engineering.
Group Doubly Coupled Designs
Authors: Zhou Weiping , Huang Shigui , Li Min
Published: April 2024

Doubly coupled designs (DCDs) have better space-filling properties between the qualitative and quantitative factors than marginally coupled designs (MCDs) which are suitable for computer experiments with both qualitative and quantitative factors. In this paper, we propose a new class of DCDs, called group doubly coupled designs (GDCDs), and provide methods for constructing two forms of GDCDs, within-group doubly coupled designs and between-group doubly coupled designs. The proposed GDCDs can accommodate more qualitative factors than DCDs, when the subdesigns for the qualitative factors are symmetric. The subdesigns of qualitative factors are not asymmetric in the existing results on DCDs, and in this paper, we construct GDCDs with symmetric and asymmetric designs for the qualitative factors, respectively. Moreover, detailed comparisons with existing MCDs show that GDCDs have better space-filling properties between qualitative and quantitative factors. Finally, the methods are particularly easy to implement.
Fluorescent α-Conotoxin [Q1G, ΔR14]LvIB Identifies the Distribution of α7 Nicotinic Acetylcholine Receptor in the Rat Brain
Authors: Shan Hongyu , Wang Nan , Gao Xinyu , Wang Zihan , Yu Jinpeng , Zhangsun Dongting , Zhu Xiaopeng , Luo Sulan
Published: April 2024

α7 nicotinic acetylcholine receptors (nAChRs) are mainly distributed in the central nervous system (CNS), including the hippocampus, striatum, and cortex of the brain. The α7 nAChR has high Ca2+ permeability and can be quickly activated and desensitized, and is closely related to Alzheimer’s disease (AD), epilepsy, schizophrenia, lung cancer, Parkinson’s disease (PD), inflammation, and other diseases. α-conotoxins from marine cone snail venom are typically short, disulfide-rich neuropeptides targeting nAChRs and can distinguish various subtypes, providing vital pharmacological tools for the functional research of nAChRs. [Q1G, ΔR14]LvΙB is a rat α7 nAChRs selective antagonist, modified from α-conotoxin LvΙB. In this study, we utilized three types of fluorescein after N-Hydroxy succinimide (NHS) activation treatment: 6-TAMRA-SE, Cy3 NHS, and BODIPY-FL NHS, labeling the N-Terminal of [Q1G, ΔR14]LvΙB under weak alkaline conditions, obtaining three fluorescent analogs: LvIB-R, LvIB-C, and LvIB-B, respectively. The potency of [Q1G, ΔR14]LvΙB fluorescent analogs was evaluated at rat α7 nAChRs expressed in Xenopus laevis oocytes. Using a two-electrode voltage clamp (TEVC), the half-maximal inhibitory concentration (IC50) values of LvIB-R, LvIB-C, and LvIB-B were 643.3 nM, 298.0 nM, and 186.9 nM, respectively. The stability of cerebrospinal fluid analysis showed that after incubation for 12 h, the retention rates of the three fluorescent analogs were 52.2%, 22.1%, and 0%, respectively. [Q1G, ΔR14]LvΙB fluorescent analogs were applied to explore the distribution of α7 nAChRs in the hippocampus and striatum of rat brain tissue and it was found that Cy3- and BODIPY FL-labeled [Q1G, ΔR14]LvΙB exhibited better imaging characteristics than 6-TAMARA-. It was also found that α7 nAChRs are widely distributed in the cerebral cortex and cerebellar lobules. Taking into account potency, imaging, and stability, [Q1G, ΔR14]LvΙB -BODIPY FL is an ideal pharmacological tool to investigate the tissue distribution and function of α7 nAChRs. Our findings not only provide a foundation for the development of conotoxins as visual pharmacological probes, but also demonstrate the distribution of α7 nAChRs in the rat brain.
Objective Quantification Technique and Widely Targeted Metabolomics-Based Analysis of the Effects of Different Saccharidation Processes on Preserved French Plums
Authors: Yan Shengkun , Dong Rong , Yang Jiapeng , Wang Guoqiang
Published: April 2024

Vacuum saccharification significantly affected the flavor and color of preserved French plums. However, the correlation between color, flavor, and metabolites remains unclear. Metabolites contribute significantly to enhancing the taste and overall quality of preserved French plums. This study aimed to investigate the distinctive metabolites in samples from various stages of the processing of preserved French plums. The PCF4 exhibited the highest appearance, overall taste, and chroma. Furthermore, utilizing UPLC and ESI-Q TRAP-MS/MS, a comprehensive examination of the metabolome in the processing of preserved French plums was conducted. A total of 1776 metabolites were analyzed. Using WGCNA, we explored metabolites associated with sensory features through 10 modules. Based on this, building the correlation of modules and objective quantification metrics yielded three key modules. After screening for 151 differentiated metabolites, amino acids, and their derivatives, phenolic acids, flavonoids, organic acids, and other groups were identified as key differentiators. The response of differential metabolites to stress influenced the taste and color properties of preserved prunes. Based on these analyses, six important metabolic pathways were identified. This study identified changes in the sensory properties of sugar-stained preserved prunes and their association with metabolite composition, providing a scientific basis for future work to improve the quality of prune processing.
Theoretical Study of p-Block Metal Single-Atom-Loaded Carbon Nitride Catalyst for Photocatalytic Water Splitting
Authors: Chen Mengning , Wu Yidi , Wan Qiang , Lin Sen
Published: April 2024

Graphitic carbon nitride (g-C3N4), recognized for its considerable potential as a heterogeneous photocatalyst in water splitting, has attracted extensive research interest. By using density functional theory (DFT) calculations, the regulatory role of p-block metal (PM) single atoms on the photocatalytic activity of g-C3N4 in overall water splitting was systematically explored. The incorporation of PM atoms (Ge, Sn and Pb) led to a reduction in the overpotentials required for both the oxygen evolution reaction (OER) and the hydrogen evolution reaction (HER). Combined with the electronic structures analysis via hybrid functional, it was found that the introduction of Ge, Sn or Pb optimizes the positions of the valence band maximum (VBM) and the conduction band minimum (CBM), providing a robust driving force for HER and ensuring substantial driving force for OER. Meanwhile, the presence of these three PMs induces the spatial separation of VBM and CBM, inhibiting the recombination of carriers. These findings have significant implications for the design and preparation of efficient photocatalysts.
Effects of Central Metal Ion on Binuclear Metal Phthalocyanine-Based Redox Mediator for Lithium Carbonate Decomposition
Authors: Yan Qinghui , Yan Linghui , Huang Haoshen , Chen Zhengfei , Liu Zixuan , Zhou Shaodong , He Haiyong
Published: April 2024

Li2CO3 is the most tenacious parasitic solid-state product in lithium–air batteries (LABs). Developing suitable redox mediators (RMs) is an efficient way to address the Li2CO3 issue, but only a few RMs have been investigated to date, and their mechanism of action also remains elusive. Herein, we investigate the effects of the central metal ion in binuclear metal phthalocyanines on the catalysis of Li2CO3 decomposition, namely binuclear cobalt phthalocyanine (bi-CoPc) and binuclear cobalt manganese phthalocyanine (bi-CoMnPc). Density functional theory (DFT) calculations indicate that the key intermediate peroxydicarbonate (*C2O62−) is stabilized by bi-CoPc2+ and bi-CoMnPc3+, which is accountable for their excellent catalytic effects. With one central metal ion substituted by manganese for cobalt, the bi-CoMnPc’s second active redox couple shifts from the second Co(II)/Co(III) couple in the central metal ion to the Pc(-2)/Pc(-1) couple in the phthalocyanine ring. In artificial dry air (N2-O2, 78:22, v/v), the LAB cell with bi-CoMnPc in electrolyte exhibited 261 cycles under a fixed capacity of 500 mAh g−1carbon and current density of 100 mA g−1carbon, significantly better than the RM-free cell (62 cycles) and the cell with bi-CoPc (193 cycles).
Antioxidant and Cytotoxic Properties of Berberis vulgaris (L.) Stem Bark Dry Extract
Authors: Ivan Ionuț Mădălin , Olaru Octavian Tudorel , Popovici Violeta , Chițescu Carmen Lidia , Popescu Liliana , Luță Emanuela Alice , Ilie Elena Iuliana , Brașoveanu Lorelei Irina , Hotnog Camelia Mia , Nițulescu George Mihai , Boscencu Rica , Gîrd Cerasela Elena
Published: April 2024

Berberis vulgaris (L.) has remarkable ethnopharmacological properties and is widely used in traditional medicine. The present study investigated B. vulgaris stem bark (Berberidis cortex) by extraction with 50% ethanol. The main secondary metabolites were quantified, resulting in a polyphenols content of 17.6780 ± 3.9320 mg Eq tannic acid/100 g extract, phenolic acids amount of 3.3886 ± 0.3481 mg Eq chlorogenic acid/100 g extract and 78.95 µg/g berberine. The dried hydro-ethanolic extract (BVE) was thoroughly analyzed using Ultra-High-Performance Liquid Chromatography coupled with High-Resolution Mass Spectrometry (UHPLC–HRMS/MS) and HPLC, and 40 bioactive phenolic constituents were identified. Then, the antioxidant potential of BVE was evaluated using three methods. Our results could explain the protective effects of Berberidis cortex EC50FRAP = 0.1398 mg/mL, IC50ABTS = 0.0442 mg/mL, IC50DPPH = 0.2610 mg/mL compared to ascorbic acid (IC50 = 0.0165 mg/mL). Next, the acute toxicity and teratogenicity of BVE and berberine—berberine sulfate hydrate (BS)—investigated on Daphnia sp. revealed significant BS toxicity after 24 h, while BVE revealed considerable toxicity after 48 h and induced embryonic developmental delays. Finally, the anticancer effects of BVE and BS were evaluated in different tumor cell lines after 24 and 48 h of treatments. The MTS assay evidenced dose- and time-dependent antiproliferative activity, which was higher for BS than BVE. The strongest diminution of tumor cell viability was recorded in the breast (MDA-MB-231), colon (LoVo) cancer, and OSCC (PE/CA-PJ49) cell lines after 48 h of exposure (IC50 < 100 µg/mL). However, no cytotoxicity was reported in the normal epithelial cells (HUVEC) and hepatocellular carcinoma (HT-29) cell lines. Extensive data analysis supports our results, showing a significant correlation between the BVE concentration, phenolic compounds content, antioxidant activity, exposure time, and the viability rate of various normal cells and cancer cell lines.
Valorisation of Agri-Food Waste for Bioactive Compounds: Recent Trends and Future Sustainable Challenges
Authors: Yadav Sujeeta , Malik Kamla , Moore Janie McClurkin , Kamboj Baldev Raj , Malik Shweta , Malik Vinod Kumar , Arya Sandeep , Singh Karmal , Mahanta Shikhadri , Bishnoi Dalip Kumar
Published: April 2024

Worldwide, a massive amount of agriculture and food waste is a major threat to the environment, the economy and public health. However, these wastes are important sources of phytochemicals (bioactive), such as polyphenols, carotenoids, carnitine, coenzymes, essential oils and tocopherols, which have antioxidant, antimicrobial and anticarcinogenic properties. Hence, it represents a promising opportunity for the food, agriculture, cosmetics, textiles, energy and pharmaceutical industries to develop cost effective strategies. The value of agri-food wastes has been extracted from various valuable bioactive compounds such as polyphenols, dietary fibre, proteins, lipids, vitamins, carotenoids, organic acids, essential oils and minerals, some of which are found in greater quantities in the discarded parts than in the parts accepted by the market used for different industrial sectors. The value of agri-food wastes and by-products could assure food security, maintain sustainability, efficiently reduce environmental pollution and provide an opportunity to earn additional income for industries. Furthermore, sustainable extraction methodologies like ultrasound-assisted extraction, pressurized liquid extraction, supercritical fluid extraction, microwave-assisted extraction, pulse electric field-assisted extraction, ultrasound microwave-assisted extraction and high hydrostatic pressure extraction are extensively used for the isolation, purification and recovery of various bioactive compounds from agri-food waste, according to a circular economy and sustainable approach. This review also includes some of the critical and sustainable challenges in the valorisation of agri-food wastes and explores innovative eco-friendly methods for extracting bioactive compounds from agri-food wastes, particularly for food applications. The highlights of this review are providing information on the valorisation techniques used for the extraction and recovery of different bioactive compounds from agricultural food wastes, innovative and promising approaches. Additionally, the potential use of these products presents an affordable alternative towards a circular economy and, consequently, sustainability. In this context, the encapsulation process considers the integral and sustainable use of agricultural food waste for bioactive compounds that enhance the properties and quality of functional food.
A Performance Analysis of Security Protocols for Distributed Measurement Systems Based on Internet of Things with Constrained Hardware and Open Source Infrastructures
Authors: Gentile Antonio Francesco , Macrì Davide , Carnì Domenico Luca , Greco Emilio , Lamonaca Francesco
Published: April 2024

The widespread adoption of Internet of Things (IoT) devices in home, industrial, and business environments has made available the deployment of innovative distributed measurement systems (DMS). This paper takes into account constrained hardware and a security-oriented virtual local area network (VLAN) approach that utilizes local message queuing telemetry transport (MQTT) brokers, transport layer security (TLS) tunnels for local sensor data, and secure socket layer (SSL) tunnels to transmit TLS-encrypted data to a cloud-based central broker. On the other hand, the recent literature has shown a correlated exponential increase in cyber attacks, mainly devoted to destroying critical infrastructure and creating hazards or retrieving sensitive data about individuals, industrial or business companies, and many other entities. Much progress has been made to develop security protocols and guarantee quality of service (QoS), but they are prone to reducing the network throughput. From a measurement science perspective, lower throughput can lead to a reduced frequency with which the phenomena can be observed, generating, again, misevaluation. This paper does not give a new approach to protect measurement data but tests the network performance of the typically used ones that can run on constrained hardware. This is a more general scenario typical for IoT-based DMS. The proposal takes into account a security-oriented VLAN approach for hardware-constrained solutions. Since it is a worst-case scenario, this permits the generalization of the achieved results. In particular, in the paper, all OpenSSL cipher suites are considered for compatibility with the Mosquitto server. The most used key metrics are evaluated for each cipher suite and QoS level, such as the total ratio, total runtime, average runtime, message time, average bandwidth, and total bandwidth. Numerical and experimental results confirm the proposal’s effectiveness in foreseeing the minimum network throughput concerning the selected QoS and security. Operating systems yield diverse performance metric values based on various configurations. The primary objective is identifying algorithms to ensure suitable data transmission and encryption ratios. Another aim is to explore algorithms that ensure wider compatibility with existing infrastructures supporting MQTT technology, facilitating secure connections for geographically dispersed DMS IoT networks, particularly in challenging environments like suburban or rural areas. Additionally, leveraging open firmware on constrained devices compatible with various MQTT protocols enables the customization of the software components, a crucial necessity for DMS.
Performance Assessment for the Validation of Wireless Communication Engines in an Innovative Wearable Monitoring Platform
Authors: Serrani Alessio , Aliverti Andrea
Published: April 2024

In today’s health-monitoring applications, there is a growing demand for wireless and wearable acquisition platforms capable of simultaneously gathering multiple bio-signals from multiple body areas. These systems require well-structured software architectures, both to keep different wireless sensing nodes synchronized each other and to flush collected data towards an external gateway. This paper presents a quantitative analysis aimed at validating both the wireless synchronization task (implemented with a custom protocol) and the data transmission task (implemented with the BLE protocol) in a prototype wearable monitoring platform. We evaluated seven frequencies for exchanging synchronization packets (10 Hz, 20 Hz, 30 Hz, 40 Hz, 50 Hz, 60 Hz, 70 Hz) as well as two different BLE configurations (with and without the implementation of a dynamic adaptation of the BLE Connection Interval parameter). Additionally, we tested BLE data transmission performance in five different use case scenarios. As a result, we achieved the optimal performance in the synchronization task (1.18 ticks as median synchronization delay with a Min-Max range of 1.60 ticks and an Interquartile range (IQR) of 0.42 ticks) when exploiting a synchronization frequency of 40 Hz and the dynamic adaptation of the Connection Interval. Moreover, BLE data transmission proved to be significantly more efficient with shorter distances between the communicating nodes, growing worse by 30.5% beyond 8 m. In summary, this study suggests the best-performing network configurations to enhance the synchronization task of the prototype platform under analysis, as well as quantitative details on the best placement of data collectors.
Improved Finite Element Model Updating of a Highway Viaduct Using Acceleration and Strain Data
Authors: Hekič Doron , Ribeiro Diogo , Anžlin Andrej , Žnidarič Aleš , Češarek Peter
Published: April 2024

Most finite element model updating (FEMU) studies on bridges are acceleration-based due to their lower cost and ease of use compared to strain- or displacement-based methods, which entail costly experiments and traffic disruptions. This leads to a scarcity of comprehensive studies incorporating strain measurements. This study employed the strain- and acceleration-based FEMU analyses performed on a more than 50-year-old multi-span concrete highway viaduct. Mid-span strains under heavy vehicles were considered for the strain-based FEMU, and frequencies and mode shapes for the acceleration-based FEMU. The analyses were performed separately for up to three variables, representing Young’s modulus adjustment factors for different groups of structural elements. FEMU studies considered residual minimisation and the error-domain model falsification (EDMF) methodology. The residual minimisation utilised four different single-objective optimisations focusing on strains, frequencies, and mode shapes. Strain- and frequency-based FEMU analyses resulted in an approximately 20% increase in the overall superstructure’s design stiffness. This study shows the benefits of the intuitive EDMF over residual minimisation for FEMU, where information gained from the strain data, in addition to the acceleration data, manifests more sensible updated variables. EDMF finally resulted in a 25–50% overestimated design stiffness of internal main girders.
Low-Complexity 2D-DOD and 2D-DOA Estimation in Bistatic MIMO Radar Systems: A Reduced-Dimension MUSIC Algorithm Approach
Authors: Ahmad Mushtaq , Zhang Xiaofei , Lai Xin , Ali Farman , Shi Xinlei
Published: April 2024

This paper presents a new technique for estimating the two-dimensional direction of departure (2D-DOD) and direction of arrival (2D-DOA) in bistatic uniform planar array Multiple-Input Multiple-Output (MIMO) radar systems. The method is based on the reduced-dimension (RD) MUSIC algorithm, aiming to achieve improved precision and computational efficiency. Primarily, this pioneering approach efficiently transforms the four-dimensional (4D) estimation problem into two-dimensional (2D) searches, thus reducing the computational complexity typically associated with conventional MUSIC algorithms. Then, exploits the spatial diversity of array response vectors to construct a 4D spatial spectrum function, which is crucial in resolving the complex angular parameters of multiple simultaneous targets. Finally, the objective is to simplify the spatial spectrum to a 2D search within a 4D measurement space to achieve an optimal balance between efficiency and accuracy. Simulation results validate the effectiveness of our proposed algorithm compared to several existing approaches, demonstrating its robustness in accurately estimating 2D-DOD and 2D-DOA across various scenarios. The proposed technique shows significant computational savings and high-resolution estimations and maintains high precision, setting a new benchmark for future explorations in the field.
Advanced Detection of Failed LEDs in a Short Circuit for Automotive Lighting Applications
Authors: Martínez-Pérez Jose R. , Carvajal Miguel A. , Santaella Juan J. , López-Ruiz Nuria , Escobedo Pablo , Martínez-Olmos Antonio
Published: April 2024

This paper addresses the issue of LED short-circuit fault detection in signaling and lighting systems in the automotive industry. The conventional diagnostic method commonly implemented in newer vehicles relies on measuring the voltage drop across different LED branches and comparing it with threshold values indicating faults caused by open circuits or LED short circuits. With this algorithm, detecting cases of a few LEDs short-circuited within a branch, particularly a single malfunctioning LED, is particularly challenging. In this work, two easily implementable algorithms are proposed to address this issue within the vehicle’s control unit. One is based on a mathematical prediction model, while the other utilizes a neural network. The results obtained offer a 100% LED short-circuit fault detection rate in the majority of analyzed cases, representing a significant improvement over the conventional method, even in scenarios involving a single malfunctioning LED within a branch. Additionally, the neural network-based model can accurately predict the number of failed LEDs.
3D Shape Measurement of Aeroengine Blade Based on Fringe Projection Profilometer Improved by Multi-Layer Concentric Ring Calibration
Authors: Chen Ze , Ju Yuhang , Sun Chuanzhi , Wang Yinchu , Liu Yongmeng , Tan Jiubin
Published: April 2024

The precision requirements for aeroengine blade machining are exceedingly stringent. This study aims to improve the accuracy of existing aeroengine blade measurement methods while achieving comprehensive measurement. Therefore, this study proposes a new concentric ring calibration method and designs a multi-layer concentric ring calibration plate. The effectiveness of this calibration method was verified through actual testing of standard ball gauges. Compared with the checkerboard-grid calibration method, the average deviation of the multilayer concentric ring calibration method for measuring the center distance of the standard sphere is 0.02352, which improves the measurement accuracy by 3–4 times. On the basis of multi-layer concentric ring calibration, this study builds a fringe projection profiler based on the three-frequency twelve-step phase shift method. Compared with the CMM, the average deviation of the blade chord length measured by this solution is 0.064, which meets the measurement index requirements of aeroengine fan blades.