bluuebunny/crossref_metadata_2025 huggingface dataset:
The Potential of Endophytic Fungi for Enhancing the Growth and Accumulation of Phenolic Compounds and Anthocyanin in Maled Phai Rice (Oryza sativa L.)
Authors: Gateta Thanawan , Nacoon Sabaiporn , Seemakram Wasan , Ekprasert Jindarat , Theerakulpisut Piyada , Sanitchon Jirawat , Suwannarach Nakarin , Boonlue Sophon
Published: September 2023

Rice (Oryza sativa L.) is one of the most popular cereal crops, being consumed by almost half of the world’s population. Among several cultivars widely distributed in Thailand, Maled Phai is a Thai pigmented-upland rice with exceptionally high nutritional value and high demand in the local Thai market. This study aimed to investigate the feasibility of producing plant growth-promoting properties (PGP) and enhancing the accumulation of phytochemicals in Maled Phai rice seeds of endophytic fungi isolated from upland black rice. Among a total of 56 isolates, the 4 most effective PGP isolates were identified as Trichoderma zelobreve PBMP16, Talaromyces pinophilus PBMP28, Aspergillus flavus KKMP34, and Trichoderma sp. PBMP4 based on their morphological characteristics and multigene (ITS, rpb2, tef-1, CaM, and BenA) phylogenetic analyses. These four endophytic fungi could promote plant growth parameters under greenhouse conditions. Outstandingly, upland rice inoculated with Tr. zelobreve PBMP16 had a significant increase in total seed weight, root length, phenolic compounds, anthocyanin, antioxidants, and N uptake, which were higher than those of the noninoculated control, and even better than the chemical fertilizer. Overall, this report shows that endophytic fungi efficiently promoted growth and increased the phenolic compounds, anthocyanin, and antioxidants of Maled Phai rice.
Indicators of HSV1 Infection, ECM–Receptor Interaction, and Chromatin Modulation in a Nuclear Family with Schizophrenia
Authors: Huang Yen-Chen , Ping Lieh-Yung , Hsu Shih-Hsin , Tsai Hsin-Yao , Cheng Min-Chih
Published: September 2023

Schizophrenia (SCZ) is a complex psychiatric disorder with high heritability; identifying risk genes is essential for deciphering the disorder’s pathogenesis and developing novel treatments. Using whole-exome sequencing, we screened for mutations within protein-coding sequences in a single family of patients with SCZ. In a pathway enrichment analysis, we found multiple transmitted variant genes associated with two KEGG pathways: herpes simplex virus 1 (HSV1) infection and the extracellular matrix (ECM)–receptor interaction. When searching for rare variants, six variants, SLC6A19p.L541R, CYP2E1p.T376S, NAT10p.E811D, N4BP1p.L7V, CBX2p.S520C, and ZNF460p.K190E, segregated with SCZ. A bioinformatic analysis showed that three of these mutated genes were associated with chromatin modulation. We found that HSV1 infection, ECM–receptor interaction pathways, and epigenetic mechanisms may contribute to the pathogenesis of SCZ in certain families. The identified polygenetic risk factors from the sample family provide distinctive underlying biological mechanisms of the pathophysiology of SCZ and may be useful in clinical practice and patient care.
Does Financial Technology Adoption Influence Bank’s Financial Performance: The Case of Jordan
Authors: Kaddumi Thair A. , Baker Hafez , Nassar Mahmoud Daoud , A-Kilani Qais
Published: September 2023

This research will examine the impact of the adoption of financial technology on conventional banks’ financial performances. The research will place emphasis on the listed commercial banks at Amman Stock Exchange—ASE, using financial data for the period 2012–2020. The main study tool was a questionnaire that focuses on three main dimensions: financial inclusion—(FI), alternative payment methods—(APMs) and automation—(Auto). A total of 115 questionnaires were distributed to all commercial banks listed at Amman Stock Exchange—ASE. Multivariate regression analysis was employed to test the impact of the FinTech dimension as a proxy for independent variables on Jordanian commercial bank’s financial performance as a proxy for dependent variables. Based on the analysis results, the study concludes that all three FinTech dimensions: FI, APMs and Auto. reflected a positive significant impact on Jordanian commercial bank’s financial performance indicators (total deposit, total loans and net profit margin). Therefore, banks in general should invest more and more into financial technology tools and applications, in order to recruit potential clients and retain their current clients, to be able to sustain under fierce competition within the banking sector.
A Preliminary Study Exploring the Relationship between Occupational Health Hazards and Gut Microbiota among Firefighters
Authors: Yoo Ji Youn , McSkimming Daniel , Rajan Kalavathy , Sarkar Anujit , Labbé Nicole , Groer Maureen , Menon Usha
Published: September 2023

Firefighters are exposed to occupational hazards and have a higher prevalence of health issues. The gut microbiota plays a crucial role in the immune, endocrine, and neural systems, and disruptions in its composition can impact health outcomes. This pilot study aimed to investigate the potential association between occupational factors, changes in gut microbiota, and the development of adverse health outcomes in firefighters. To test this hypothesis, we recruited 15 firefighters and age/sex-matched controls to investigate the relationship between occupational environment and gut microbiota. Firefighters exhibit lower intestinal bacterial alpha diversity and a higher presence of pathogenic bacteria than the control. Moreover, unique gut bacterial taxa were observed in firefighters with high post-traumatic stress disorder (PTSD) scores, which could contribute to immune dysregulation and higher susceptibility to pathogen colonization. These preliminary findings suggest that occupational factors, including exposure to traumatic stressors and chemicals, may influence firefighters’ health by modulating their gut microbiota. The observed changes in gut microbiota composition and the potential link to occupational hazards highlight the need for further research in larger sample-size studies. Understanding the role of gut microbiota in firefighter health may have implications for preventive measures and interventions to mitigate occupational health risks and improve overall well-being.
A Hydraulic Axial Piston Pump Fault Diagnosis Based on Instantaneous Angular Speed under Non-Stationary Conditions
Authors: Liu Jiamin , Meng Shuai , Zhou Xintao , Gu Lichen
Published: September 2023

Due to the intense noise interference in hydraulic systems, it is extremely difficult to detect component faults through vibration signals. Diagnostic performance is also constrained by highly time-varying and non-stationary operating conditions. This study proposes to use instantaneous angular speed (IAS) signals that are both operational and state parameters as sources of information. Firstly, the instantaneous angular speed fluctuation (IASF) of a piston pump is analyzed theoretically, and it is concluded that its fluctuating components contain the health status information of the components. The IASF can then be obtained by subtracting the speed trend term from IAS signals obtained via a magneto-electric speed sensor. A synchro-extraction of the normal S transform (SNST) is proposed to process it via line-pass filtering. Finally, the filtered and reconstructed IASF signal is utilized to draw a two-dimensional polar coordinate map online. A non-stationary-condition test is carried out on the test platform to monitor the morphological characteristics of the valve plate under normal, slight, and severe wear conditions. The polar plot shows significant increases in speed fluctuations and oscillation times within a range from 180° to 270°. The relevant research results reflect that the IAS signal can provide a new method for monitoring the operating status of and conducting fault diagnoses for hydraulic equipment.
Significance of Temperature-Dependent Density on Dissipative and Reactive Flows of Nanofluid along Magnetically Driven Sheet and Applications in Machining and Lubrications
Authors: Ullah Zia , Hussain Ahmad , Aldhabani Musaad S. , Altaweel Nifeen H. , Shahab Sana
Published: September 2023

Nanofluid lubrication and machining are challenging and significant tasks in manufacturing industries that are used to control the removal of a material from a surface by using a cutting tool. The introduction of a nanofluid to the cutting zone provides cooling, lubricating, and chip-cleaning benefits that improve machining productivity. A nanofluid is a cutting fluid that is able to remove excessive friction and heat generation. Chemical reactions and temperature-dependent density are essential in the thermal behavior of a nanofluid. The present study presents a careful inspection of the chemical reactions, temperature-dependent density, viscous dissipation, and thermophoresis during the heat and mass transfer of a nanofluid along a magnetically driven sheet. The physical attitude of viscous dissipation and the chemical reaction improvement rate in magneto-nanofluid flow is the primary focus of the present research. By applying the proper transformation, nonlinear partial differential expressions are introduced to the structure of the ordinary differential framework. The flow equations are simplified into nonlinear differential equations, and these equations are then computationally resolved via an efficient computational technique known as the Keller box technique. Flow factors like the Eckert number, reaction rate, density parameter, magnetic force parameter, thermophoretic number, buoyancy number, and Prandtl parameter governing the velocity, temperature distribution, and concentration distribution are evaluated prominently via tables and graphs. The novelty of the current study is in computing a heat transfer assessment of the magneto-nanofluid flow with chemical reactions and temperature-dependent density to remove excessive friction and heating in cutting zones. Nanofluids play significant roles in minimum quantity lubrication (MQL), enhanced oil recovery (EOR), drilling, brake oil, engine oil, water-miscible cutting fluids, cryogenic cutting fluids, controlled friction between tools and chips and tools and work, and conventional flood cooling during machining processes.
A Multi-Stage Model for Perceived Quality Evaluation of Clothing Brands
Authors: Ren Minhui , Fan Yu , Chen Jindong , Zhang Jian
Published: September 2023

Perceived quality is crucial for the functioning of clothing brands. However, accurate evaluation of the perceived quality of clothing brands remains a common challenge. To achieve a multidimensional evaluation of the perceived quality of clothing brands, an index system is derived based on perceived quality theory. Then, by combining a fine-grained sentiment analysis approach with stochastic dominance criteria, a multi-stage model ECRM is proposed for the perceived quality evaluation of clothing brands based on online user reviews. ECRM comprises three stages: Extraction, Classification, and Ranking. To begin with, Contrastive Attention and dependency parsing are used to extract attribute–viewpoint phrases from online reviews. Subsequently, the pre-trained models are employed to classify the indexes and sentiment levels of these phrases. Furthermore, the perceived quality indexes are ranked using stochastic dominance criteria and the PROMETHEE-II method. Empirical analysis is conducted for the clothing brands of ALDB, AND, BNL, and QPL; the results show that, based on online user reviews, ECRM enables accurate evaluation of the perceived quality of clothing brands. Based on the evaluation results, it is found that Comfort, External, Protection, and Fineness are highly valued by consumers; moreover, the four brands focus on different indexes. Specific strategies for perceived quality improvements are proposed depending on the current status of the brands.
Holonomic and Non-Holonomic Geometric Models Associated to the Gibbs–Helmholtz Equation
Authors: Pripoae Cristina-Liliana , Hirica Iulia-Elena , Pripoae Gabriel-Teodor , Preda Vasile
Published: September 2023

By replacing the internal energy with the free energy, as coordinates in a “space of observables”, we slightly modify (the known three) non-holonomic geometrizations from Udriste’s et al. work. The coefficients of the curvature tensor field, of the Ricci tensor field, and of the scalar curvature function still remain rational functions. In addition, we define and study a new holonomic Riemannian geometric model associated, in a canonical way, to the Gibbs–Helmholtz equation from Classical Thermodynamics. Using a specific coordinate system, we define a parameterized hypersurface in R4 as the “graph” of the entropy function. The main geometric invariants of this hypersurface are determined and some of their properties are derived. Using this geometrization, we characterize the equivalence between the Gibbs–Helmholtz entropy and the Boltzmann–Gibbs–Shannon, Tsallis, and Kaniadakis entropies, respectively, by means of three stochastic integral equations. We prove that some specific (infinite) families of normal probability distributions are solutions for these equations. This particular case offers a glimpse of the more general “equivalence problem” between classical entropy and statistical entropy.
Malicious Traffic Classification via Edge Intelligence in IIoT
Authors: Wang Maoli , Zhang Bowen , Zang Xiaodong , Wang Kang , Ma Xu
Published: September 2023

The proliferation of smart devices in the 5G era of industrial IoT (IIoT) produces significant traffic data, some of which is encrypted malicious traffic, creating a significant problem for malicious traffic detection. Malicious traffic classification is one of the most efficient techniques for detecting malicious traffic. Although it is a labor-intensive and time-consuming process to gather large labeled datasets, the majority of prior studies on the classification of malicious traffic use supervised learning approaches and provide decent classification results when a substantial quantity of labeled data is available. This paper proposes a semi-supervised learning approach for classifying malicious IIoT traffic. The approach utilizes the encoder–decoder model framework to classify the traffic, even with a limited amount of labeled data available. We sample and normalize the data during the data-processing stage. In the semi-supervised model-building stage, we first pre-train a model on a large unlabeled dataset. Subsequently, we transfer the learned weights to a new model, which is then retrained using a small labeled dataset. We also offer an edge intelligence model that considers aspects such as computation latency, transmission latency, and privacy protection to improve the model’s performance. To achieve the lowest total latency and to reduce the risk of privacy leakage, we first create latency and privacy-protection models for each local, edge, and cloud. Then, we optimize the total latency and overall privacy level. In the study of IIoT malicious traffic classification, experimental results demonstrate that our method reduces the model training and classification time with 97.55% accuracy; moreover, our approach boosts the privacy-protection factor.
ClueCatcher: Catching Domain-Wise Independent Clues for Deepfake Detection
Authors: Lee Eun-Gi , Lee Isack , Yoo Seok-Bong
Published: September 2023

Deepfake detection is a focus of extensive research to combat the proliferation of manipulated media. Existing approaches suffer from limited generalizability and struggle to detect deepfakes created using unseen techniques. This paper proposes a novel deepfake detection method to improve generalizability. We observe domain-wise independent clues in deepfake images, including inconsistencies in facial colors, detectable artifacts at synthesis boundaries, and disparities in quality between facial and nonfacial regions. This approach uses an interpatch dissimilarity estimator and a multistream convolutional neural network to capture deepfake clues unique to each feature. By exploiting these clues, we enhance the effectiveness and generalizability of deepfake detection. The experimental results demonstrate the improved performance and robustness of this method.
Shark IgNAR: The Next Broad Application Antibody in Clinical Diagnoses and Tumor Therapies?
Authors: Jiang Xiaofeng , Sun Ling , Hu Chengwu , Zheng Feijian , Lyu Zhengbing , Shao Jianzhong
Published: September 2023

Antibodies represent a relatively mature detection means and serve as therapeutic drug carriers in the clinical diagnosis and treatment of cancer—among which monoclonal antibodies (mAbs) currently occupy a dominant position. However, the emergence and development of small-molecule monodomain antibodies are inevitable due to the many limitations of mAbs, such as their large size, complex structure, and sensitivity to extreme temperature, and tumor microenvironments. Thus, since first discovered in Chondroid fish in 1995, IgNAR has become an alternative therapeutic strategy through which to replace monoclonal antibodies, thus entailing that this novel type of immunoglobulin has received wide attention with respect to clinical diagnoses and tumor therapies. The variable new antigen receptor (VNAR) of IgNAR provides an advantage for the development of new antitumor drugs due to its small size, high stability, high affinity, as well as other structural and functional characteristics. In that respect, a better understanding of the unique characteristics and therapeutic potential of IgNAR/VNAR in clinical and anti-tumor treatment is needed. This article reviews the advantages of its unique biochemical conditions and molecular structure for clinical diagnoses and novel anti-tumor drugs. At the same time, the main advantages of the existing conjugated drugs, which are based on single-domain antibodies, are introduced here, thereby providing new ideas and methods for the development of clinical diagnoses and anti-tumor therapies in the future.
Effect of Heat Input on Microstructure and Tensile Properties in Simulated CGHAZ of a V-Ti-N Microalloyed Weathering Steel
Authors: Hu Bing , Wang Qiuming , Wang Qingfeng
Published: September 2023

The mechanical properties of a coarse-grained heat-affected zone (CGHAZ) are affected by welding thermal cycling with varied heat input (Ej), but its effect on tensile properties is rarely studied. In the present work, Ej = 15, 35, 55, 75 kJ/cm CGHAZ samples were prepared via GleebleTM (St. Paul, MN, USA) for a novel V-Ti-N microalloyed weathering steel. The tensile properties of CGHAZ with varied Ej were evaluated. The results indicated that mixed microstructures dominated by lath bainitic ferrite (LBF) and granular bainitic ferrite (GBF) were obtained at Ej = 15 and 35 kJ/cm, respectively, while a mixed microstructure composed of GBF, intragranular acicular ferrite (IGAF), and polygon ferrite (PF) formed at Ej = 55 and 75 kJ/cm, apart from martensite/austenite (M/A) constituents in each Ej condition. The above variation tendency in the microstructure with the increase in Ej led to coarsening of low-angle grain boundaries (LAGBs) and a decrease in dislocation density, which in turn resulted in a yield strength (YS) decrease from 480 MPa to 416 MPa. The mean equivalent diameter (MED), defined by the misorientation tolerance angles (MTAs) ranging from 2–6°, had the strongest contribution to YS due to their higher fitting coefficient of the Hall–Petch relationship. In addition, the increase in the average size (dM/A) of M/A constituents from 0.98 μm to 1.81 μm and in their area fraction (fM/A) from 3.11% to 4.42% enhanced the strain-hardening stress. The yield strength ratio (YR) reduced as the Ej increased, and the lower density and more uniform dislocations inside the ferrite led to a uniform elongation (uE) increase from 9.5% to 18.6%.
An Experimental Investigation about the Dimensional Accuracy and the Porosity of Copper-Filled PLA Fused Filament Fabrication Parts
Authors: Buj-Corral Irene , Sivatte-Adroer Maurici
Published: September 2023

In recent years, metal-filled plastic filaments have begun to be used in fused filament fabrication (FFF) technology. However, the characterization of the parts obtained is still under development. In this work, the results on dimensional accuracy and porosity of copper-filled 3D-printed parts are presented. Cuboid parts were 3D-printed in the vertical position. The three dimensions of each part were measured, and the relative error was calculated for each one of them. Dimensional accuracy in terms of width and depth depends mainly on the layer height and printing temperature, while accuracy in height is mainly influenced by print speed and the interaction of layer height with print speed. Porosity is related to layer height, printing temperature and print speed. According to multiobjective optimization, to minimize dimensional error and obtain a porosity target value of 20%, it is recommended to select a low layer height of 0.1 mm, a high print speed of 40 mm/s, a low extrusion multiplier of 0.94 and a low temperature of 200 °C. The results of the present work will help to select appropriate 3D printing parameters when using metal-filled filaments in FFF processes.
The Mating Type (MAT) and Virulence of Sporothrix schenckii sensu stricto Isolates Maintained in Culture Collection
Authors: Barreira Thais , Corrêa-Moreira Danielly , de Moraes Borba Cintia , Menezes Rodrigo Caldas , de Moraes Aurea Maria Lage , Oliveira Manoel Marques Evangelista
Published: September 2023

In an attempt to determine the mating type of different Sporothrix schenckii sensu stricto isolates that remained viable after a long period of preservation in a culture collection and to correlate them with the degree of virulence/pathogenicity, a PCR technique using primers designed for the sequences of MAT1-1-1 and MAT1-2-1 genes and a murine experimental model were used. The results showed that there was no correlation between the mating type and virulence among the isolates. Furthermore, different degrees of virulence/pathogenicity, ranging from high to low, were found among them based on different virulence parameters. It was assumed that the long period of preservation favored the changes, yielding the isolation of variants. Thus, we believe that new technologies for studies on factors can improve our knowledge of the pathogenesis of sporotrichosis.
Effects of Dry-Hopping on Beer Chemistry and Sensory Properties—A Review
Authors: Klimczak Krystian , Cioch-Skoneczny Monika , Duda-Chodak Aleksandra
Published: September 2023

Dry-hopping is the addition of hops to the wort on the cold side of the brewing process. Unlike standard hop additions, its main purpose is not to produce a characteristic bitterness but to extract as much of the hop essential oils as possible, which are largely lost in the standard hopping process. When dry-hopped, it is possible to obtain a beer with an aroma that is difficult to achieve when hops are used on the hot side of the brewing process. As a result, this process has become very popular in recent years, particularly in beers that belong to the ‘craft beer revolution’ trend. In addition, the usefulness of this process is increasing with the development of new hop varieties with unique aromas. This article presents the main components of hops, focusing on those extracted during the process. Changes in the composition of beer bittering compounds and essential oils resulting from this process are discussed. This paper presents the current state of the knowledge on the factors affecting the degree of extraction, such as hop dosage, the time, and temperature of the process. Issues such as process-related physicochemical changes, hop creep, low flavor stability, haze formation, and green flavor are also discussed.
Investigation of the Impact of Point Defects in InGaN/GaN Quantum Wells with High Dislocation Densities
Authors: Lottigier Pierre , Di Paola Davide Maria , Alexander Duncan T. L. , Weatherley Thomas F. K. , Sáenz de Santa María Modroño Pablo , Chen Danxuan , Jacopin Gwénolé , Carlin Jean-François , Butté Raphaël , Grandjean Nicolas
Published: September 2023

In this work, we report on the efficiency of single InGaN/GaN quantum wells (QWs) grown on thin (<1 µm) GaN buffer layers on silicon (111) substrates exhibiting very high threading dislocation (TD) densities. Despite this high defect density, we show that QW emission efficiency significantly increases upon the insertion of an In-containing underlayer, whose role is to prevent the introduction of point defects during the growth of InGaN QWs. Hence, we demonstrate that point defects play a key role in limiting InGaN QW efficiency, even in samples where their density (2–3 × 109 cm−2) is much lower than that of TD (2–3 × 1010 cm−2). Time-resolved photoluminescence and cathodoluminescence studies confirm the prevalence of point defects over TDs in QW efficiency. Interestingly, TD terminations lead to the formation of independent domains for carriers, thanks to V-pits and step bunching phenomena.
Eu3+ Complex-Based Superhydrophobic Fluorescence Sensor for Cr(VI) Detection in Water
Authors: Ding Wei , Vallabhuneni Sravanthi , Liu Jin , Wang Xinzhi , Zhao Yue , Wang Yao , Tang Qinglin , Wang Yanxin , Zhang Xiaolin , Kota Arun Kumar , Tang Jianguo
Published: September 2023

Cr(VI) compounds are bioaccumulative and highly toxic pollutants, and there is a need for simple and fast detection methods to monitor their trace levels. In this work, we developed a Eu3+ complex-based fluorescence sensor to easily detect Cr(VI) in water droplets. Our sensor consists of a nanofibrous membrane electrospun with a blend of polyvinylidene fluoride (PVDF), silica particles, and Eu3+ complex. Upon modifying the membrane surface with fluoroalkyl chemistry, the sensor displayed superhydrophobicity. When a water droplet with Cr(VI) was placed on such a superhydrophobic fluorescence sensor, the overlapping absorption of Cr(VI) and Eu3+ complex facilitated the inner filter effect, allowing the selective detection of Cr(VI) down to 0.44 µM (i.e., 45.76 µg L−1). We proposed and designed of new inexpensive and fast sensor for the detection of Cr(VI).
Novel Insights into Circular RNAs in Metastasis in Breast Cancer: An Update
Authors: Zepeda-Enríquez Paola , Silva-Cázares Macrina B. , López-Camarillo César
Published: September 2023

Circular RNAs (circRNAs) are single-stranded closed non-coding RNA molecules that are aberrantly expressed and produce tumor-specific gene signatures in human cancers. They exert biological functions by acting as transcriptional regulators, microRNA sponges, and protein scaffolds, regulating the formation of protein–RNA complexes and, ultimately, regulating gene expression. Triple-negative breast cancer (TNBC) is one of the most aggressive cancers of the mammary gland and has a poor prognosis. Studies of circRNAs in TNBC are limited but have demonstrated these molecules’ pivotal roles in cell proliferation, invasion, metastasis, and resistance to chemo/radiotherapy, suggesting that they could be potential prognostic biomarkers and novel therapeutic targets. Here, we reviewed the status of actual knowledge about circRNA biogenesis and functions and summarized novel findings regarding their roles in TNBC development and progression. In addition, we discussed recent data about the importance of exosomes in the transport and export of circRNAs in TNBC. Deep knowledge of circRNA functions in metastasis and therapy responses could be an invaluable guide in the identification of novel therapeutic targets for advancing the treatment of TNBC.
The European Educational Policy and Early School Leaving: A Conceptual Analysis from the Perspective of the Leaving Subject
Authors: Guerrero Puerta Laura
Published: September 2023

This article presents a conceptual analysis of the European educational policy concerning the phenomenon of early school leaving (ESL). It addresses the literature on ESL, emphasizing the importance of studying policies from the perspective of the constructions made of the leaving subject. The concept of lifelong learning is examined, along with its relevance in shaping the subject who leaves within European policies. Additionally, the presence of “double gestures” in educational policies is explored, where, while promoting inclusion, they simultaneously produce exclusion of certain individuals. The influence of the neoliberal approach on the conception of ESL is discussed, and the need to consider alternative approaches to avoid homogenizing the group of young individuals who leave school prematurely is proposed.
Watermelon Rind Mediated Biosynthesis of Bimetallic Selenium-Silver Nanoparticles: Characterization, Antimicrobial and Anticancer Activities
Authors: Hashem Amr , El-Sayyad Gharieb , Al-Askar Abdulaziz , Marey Samy , AbdElgawad Hamada , Abd-Elsalam Kamel , Saied Ebrahim
Published: September 2023

One of the most hazardous diseases that influences human health globally is microbial infection. Therefore, bimetallic nanoparticles have received much attention for controlling microbial infections in the current decade. In the present study, bimetallic selenium–silver nanoparticles (Se-Ag NPs) were effectively biosynthesized using watermelon rind WR extract through the green technique for the first time. UV-visible spectroscopy, transmission electron microscopy (TEM), and energy dispersive X-ray spectroscopy (EDX) methods were used to characterize the produced NPs. The results indicated that the bimetallic Se-Ag NPs had synergistic antimicrobial activity at low concentrations, which helped to reduce the toxicity of Ag NPs after the bimetallic Se-Ag NPs preparation and increase their great potential. Se-Ag NPs with sizes ranging from 18.3 nm to 49.6 nm were detected by TEM. Se-Ag NP surfaces were uniformly visible in the SEM picture. The cytotoxicity of bimetallic Se-Ag NPs was assessed against the Wi38 normal cell line to check their safety, where the IC50 was 168.42 µg/mL. The results showed that bimetallic Se-Ag NPs had antibacterial action against Candida albicans, Escherichia coli, Pseudomonas aeruginosa, Klebsiella oxytoca, Bacillus subtilis, and Staphylococcus aureus with a minimum inhibitory concentration (MIC) of 12.5 to 50 µg/mL. Additionally, bimetallic Se-Ag NPs had promising anticancer activity toward the MCF7 cancerous cell line, where the IC50 was 21.6 µg/mL. In conclusion, bimetallic Se-Ag NPs were biosynthesized for the first time using WR extract, which had strong antibacterial, antifungal and anticancer properties.
Phosphorus Acquisition Efficiency and Transcriptomic Changes in Maize Plants Treated with Two Lignohumates
Authors: Santoro Veronica , Della Lucia Maria Cristina , Francioso Ornella , Stevanato Piergiorgio , Bertoldo Giovanni , Borella Matteo , Ferrari Erika , Zaccone Claudio , Schiavon Michela , Pizzeghello Diego , Nardi Serenella
Published: September 2023

Lignohumates are increasing in popularity in agriculture, but their chemistry and effects on plants vary based on the source and processing. The present study evaluated the ability of two humates (H1 and H2) to boost maize plant performance under different phosphorus (P) availability (25 and 250 μM) conditions in hydroponics, while understanding the underlying mechanisms. Humates differed in chemical composition, as revealed via elemental analysis, phenol and phytohormone content, and thermal and spectroscopic analyses. H1 outperformed H2 in triggering plant responses to low phosphorus by enhancing phosphatase and phytase enzymes, P acquisition efficiency, and biomass production. It contained higher levels of endogenous auxins, cytokinins, and abscisic acid, likely acting together to stimulate plant growth. H1 also improved the plant antioxidant capacity, thus potentially increasing plant resilience to external stresses. Both humates increased the nitrogen (N) content and acted as biostimulants for P and N acquisition. Consistent with the physiological and biochemical data, H1 upregulated genes involved in growth, hormone signaling and defense in all plants, and in P recycling particularly under low-P conditions. In conclusion, H1 showed promising potential for effective plant growth and nutrient utilization, especially in low-P plants, involving hormonal modulation, antioxidant enhancement, the stimulation of P uptake and P-recycling mechanisms.
Prediction of Lost Circulation in Southwest Chinese Oil Fields Applying Improved WOA-BiLSTM
Authors: Liu Xianming , Jia Wen , Li Zhilin , Wang Chao , Guan Feng , Chen Kexu , Jia Lichun
Published: September 2023

Drilling hazards can be significantly decreased by anticipating potential mud loss and then putting the right well control measures in place. Therefore, it is critical to provide early estimates of mud loss. To solve this problem, an enhanced WOA (Whale Optimization Algorithm) and a BiLSTM (Bidirectional Long Short Term Memory) optimization based prediction model of lost circulation prior to drilling has been created. In order to minimize the noise in the historical comprehensive logging data, a wavelet filtering technique was first used. Then, according to the nonlinear Spearman rank correlation coefficient between mud loss and logging parameter values from large to small, seven characteristic parameters were preferred, and the sliding window was used to extract the relevant data. Secondly, the number of neurons in the first and second hidden layers, the maximum training time, and the initial learning rate of the BiLSTM model were optimized using the enhanced WOA method. The BiLSTM network was given the acquired superparameters in order to improve the model’s ability to predict occurrences. Finally, the model was trained and tested using the processed data. In comparison to the LSTM model, BiLSTM model, and WOA-BiLSTM model, respectively, the improved WOA-BiLSTM early mud loss prediction in southwest Chinese oil fields suggested in this study beat the others, receiving 22.3%, 18.7%, and 4.9% higher prediction accuracy, respectively.
A Review of Macroscopic Modeling for Shale Gas Production: Gas Flow Mechanisms, Multiscale Transport, and Solution Techniques
Authors: Liu Yuyang , Zhang Xiaowei , Zhang Wei , Guo Wei , Kang Lixia , Liu Dan , Gao Jinliang , Yu Rongze , Sun Yuping
Published: September 2023

The boost of shale gas production in the last decade has reformed worldwide energy structure. The macroscale modeling of shale gas production becomes particularly important as the economic development of such resources relies on the deployment of expensive hydraulic fracturing and the reasonable planning of well schedules. A flood of literature was therefore published focused on accurately and efficiently simulating the production performance of shale gas and better accounting for the various geological features or flow mechanisms that control shale gas transport. In this regard, this paper presents a holistic review of the macroscopic modeling of gas transport in shale. The review is carried out from three important points of view, which are the modeling of the gas flow mechanisms, the representation of multiscale transport, and solution techniques for the mathematical models. Firstly, the importance of gas storage and flow mechanisms in shale is discussed, and the various theoretical models used to characterize these effects in the continuum scale are introduced. Then, based on the intricate pore structure and various pore types of shale gas reservoirs, this review summarizes the multiple-porosity models in the literature to represent multiscale gas transport, and discusses the applicability of each model. Finally, the numerical and analytical/semi-analytical approaches used to solve the macroscopic mathematical model governing shale gas production are reviewed, with a focus on the treatment of the complex fracture network formed after multistage hydraulic fracturing.
A Review of Nano and Microscale Heat Transfer: An Experimental and Molecular Dynamics Perspective
Authors: Chatterjee Samyabrata , Paras  , Hu Han , Chakraborty Monojit
Published: September 2023

Significant progress in the development of micro and nanoscale devices has been observed for the past three decades. The thermal transportation in these small-length scales varies significantly, and it is difficult to explain the underlying physics using the pre-existing theoretical formulations. When the bulk dimension of a system is comparable to or smaller than the mean free path (MFP) of the thermal carriers, classical theories, such as Fourier’s Law of heat conduction, are unable to accurately explain the system energy dynamics. The phenomena of energy transit and conversion at the micro to nanoscale is an interesting topic of research due to the substantial changes in behavior that are documented when compared to those at the macro size. This review article is broadly divided into two parts. Initially, the recent development in the field of molecular dynamic (MD) simulations is emphasized. Classical MD simulation is such a powerful tool that provides insight into the length scales where the conventional continuum approaches cease to be valid. Several examples of recent developments in the applicability of MD simulations for micro and nanoscale thermal transportation are reviewed. However, there are certain limitations of the MD simulations where the results deviate from experimental validation due to the lack of knowledge of the appropriate force fields. Hence the experimental development of micro and nanoscale thermal transportation processes is briefly reviewed and discussed in the other section of this review article.
Adsorption of Multi-Collector on Long-Flame Coal Surface via Density Functional Theory Calculation and Molecular Dynamics Simulation
Authors: Cheng Gan , Peng Yujie , Lu Yang , Zhang Mengni
Published: September 2023

The quantum chemical properties of long-flame coal (LFC) and collectors (kerosene, diesel, diethyl phthalate (DEP), biodiesel collector (BDC), and emulsified biodiesel collector (EBDC)) were analyzed via the density functional theory (DFT). The molecular dynamics (MD) of the coal–collector–water system and the adsorption of collectors on LFC were conducted based on the first principles. The results showed that the frontier molecular orbitals of kerosene, diesel, DEP, and BDC were 0.38 eV, 0.28 eV, 0.27 eV, and 0.20 eV, respectively. The chemical reactivity order of the above mentioned collectors was BDC > DEP > diesel > kerosene. Kerosene, diesel, and DEP adsorbed with carbonyl, hydroxyl, and carboxyl groups in LFC, respectively. Carboxyl groups in BDC and carboxyl groups in LFC bilaterally adsorbed, while BDC repelled water molecules via hydrogen bonds on the LFC surface. In the systems of BDC and EBDC, the diffusion coefficients of a water molecule were 2.83 × 10−4 cm2/s and 3.73 × 10−4 cm2/s. The emulsifier that adsorbed onto the oil–water interface of the coal–BDC–water system improved the dispersion of BDC during flotation, while at the same time increasing the number of hydrogen bonds between BDC and LFC, which accelerated the migration of water molecules from the LFC surface.
Study on Process Parameters in Hydrothermal Liquefaction of Rice Straw and Cow Dung: Product Distribution and Application of Biochar in Wastewater Treatment
Authors: Seikh Asiful H. , Alharbi Hamad F. , Alnaser Ibrahim A. , Karim Mohammad R. , Mohammed Jabair A. , Aijaz Muhammad Omer , Hassan Ahmed , Abdo Hany S.
Published: September 2023

In this study, rice straw (RS) and cow dung (CD) waste were hydrothermally processed for the recovery of bio-oil and biochar. The hydrothermal experiments were performed in a 5 L capacity reactor under the following process conditions: temperature (240–340 °C), solvent to biomass ratios of 1:1, 1:2, 2:1, 1:3 and 3:1, a time of 1 h and a pressure of 15 bar. The HTL products were characterized via FTIR, SEM and GC–MS (gas chromatography mass spectrometry). It was seen that the maximum bio-oil yield was 32.5 wt% and the biochar yield was 18.5 wt% for the 2:1 RS:CD mixture at a temperature of 320 °C. The bio-oil contained hexadecane, heptadecane, octadecane and other hydrocarbons, and their presence was confirmed by GC–MS. The biochar was analyzed, and it was used in wastewater treatment to remove the colorants. The biochar also showed some promising results in the colorants removal study, with an efficiency of more than 76%.
A Lightweight Identification Method for Complex Power Industry Tasks Based on Knowledge Distillation and Network Pruning
Authors: Wang Wendi , Zhou Xiangling , Jiang Chengling , Zhu Hong , Yu Hao , Wang Shufan
Published: September 2023

Lightweight service identification models are very important for resource-constrained distribution grid systems. To address the increasingly larger deep learning models, we provide a method for the lightweight identification of complex power services based on knowledge distillation and network pruning. Specifically, a pruning method based on Taylor expansion is first used to rank the importance of the parameters of the small-scale network and delete some of the parameters, compressing the model parameters and reducing the amount of operation and complexity. Then, knowledge distillation is used to migrate the knowledge from the large-scale network ResNet50 to the small-scale network so that the small-scale network can fit the soft-label information output from the large-scale neural network through the loss function to complete the knowledge migration of the large-scale neural network. Experimental results show that this method can compress the model size of the small network and improve the recognition accuracy. Compared with the original small network, the model accuracy is improved by 2.24 percentage points to 97.24%. The number of model parameters is compressed by 81.9% and the number of floating-point operations is compressed by 92.1%, making it more suitable for deployment in resource-constrained devices.
Response of Nitrogen Removal Performance and Microbial Distribution to Seasonal Shock Nutrients Load in a Lakeshore Multicell Constructed Wetland
Authors: Yuan Jing , Wang Bin , Hou Zeying , Peng Jiayu , Li Dan , Chu Zhaosheng
Published: September 2023

Multicell constructed wetlands (MCWs) on lakeshores are a prospective treatment technique. However, the factors affecting the nutrient removal performance of lakeshore MCWs at the field scale are unclear. This study chose a field-scale lakeshore MCW with the highest mass removal efficiency (approximately 49,175.12 mg m−2 day−1) for total nitrogen removal in the wet season to investigate the response of nitrogen removal and microbial distribution to seasonal shock nutrients load. The mass loading rates in the wet season were as high as 43~72 times over those in the dry season. Hence, a storage pond (SP), as a forebay retention cell, was necessary to mitigate the shock loads of the influent, which is beneficial to nitrogen removal of the MCW system. The two major genera in the sediments are heterotrophic nitrification–aerobic denitrification bacteria, and the abundance and species of the nitrogen-related functional genera were higher in the wet season than the dry season. According to the results of redundancy analysis, the hydraulic residence time (29.4%, F = 2.2, p < 0.1) and hydraulic loading rate (85.9, F = 36.5, p < 0.05) were the major factors explaining microbial community variation, instead of environmental factors (temperature, pH, and dissolved oxygen). The shock loads of influent and the periodic saturation in sediments contributed to a complicated oxygen and nitrogen nutrient exchange environment resulting in higher abundance and species of nitrogen-related microbes, which is beneficial to nitrogen removal in lakeshore MCWs. The results provided a scientific basis for the optimal design of constructed wetlands on lakeshores.
Stick–Slip Characteristics of Drill Strings and the Related Drilling Parameters Optimization
Authors: Wang Chao , Chen Wenbo , Wu Zhe , Li Jun , Liu Gonghui
Published: September 2023

To eliminate or reduce stick–slip vibration in torsional vibration of the drilling string and improve the rate of penetration (ROP), a stick–slip vibration model of the drilling string considering the ROP was established based on the multidimensional torsional vibration model of the drilling string. The model was verified by simulation analysis. The characteristics of the drilling string stick–slip vibration in the three stages of stationary, slip, and stick were analyzed. This paper investigated the influence of rotary torque, rotary speed, and weight on bit (WOB) on stick–slip vibrations in the drill string. Based on this, the relationship between the drilling parameters and ROP was established. Drilling parameter optimization was completed for soft, medium-hard, and hard formations. Results showed that appropriately increasing torque and decreasing WOB can reduce or even eliminate stick–slip vibrations in the drill string and increase the ROP. The parameter optimization increased the ROP by 11.5% for the soft formation, 13.7% for the medium-hard formation, and 14.3% for the hard formation. The established drill string stick–slip vibration model provides theoretical guidance for optimizing drilling parameters in different formations.
Perceptual Soft End-Effectors for Future Unmanned Agriculture
Authors: Ye Weikang , Zhao Lin , Luo Xuan , Guo Junxian , Liu Xiangjiang
Published: September 2023

As consumers demand ever-higher quality standards for agricultural products, the inspection of such goods has become an integral component of the agricultural production process. Unfortunately, traditional testing methods necessitate the deployment of numerous bulky machines and cannot accurately determine the quality of produce prior to harvest. In recent years, with the advancement of soft robot technology, stretchable electronic technology, and material science, integrating flexible plant wearable sensors on soft end-effectors has been considered an attractive solution to these problems. This paper critically reviews soft end-effectors, selecting the appropriate drive mode according to the challenges and application scenarios in agriculture: electrically driven, fluid power, and smart material actuators. In addition, a presentation of various sensors installed on soft end-effectors specifically designed for agricultural applications is provided. These sensors include strain, temperature, humidity, and chemical sensors. Lastly, an in-depth analysis is conducted on the significance of implementing soft end-effectors in agriculture as well as the potential opportunities and challenges that will arise in the future.
Quantitative Comparison of Hand Kinematics Measured with a Markerless Commercial Head-Mounted Display and a Marker-Based Motion Capture System in Stroke Survivors
Authors: Casile Antonino , Fregna Giulia , Boarini Vittorio , Paoluzzi Chiara , Manfredini Fabio , Lamberti Nicola , Baroni Andrea , Straudi Sofia
Published: September 2023

Upper-limb paresis is common after stroke. An important tool to assess motor recovery is to use marker-based motion capture systems to measure the kinematic characteristics of patients’ movements in ecological scenarios. These systems are, however, very expensive and not readily available for many rehabilitation units. Here, we explored whether the markerless hand motion capabilities of the cost-effective Oculus Quest head-mounted display could be used to provide clinically meaningful measures. A total of 14 stroke patients executed ecologically relevant upper-limb tasks in an immersive virtual environment. During task execution, we recorded their hand movements simultaneously by means of the Oculus Quest’s and a marker-based motion capture system. Our results showed that the markerless estimates of the hand position and peak velocity provided by the Oculus Quest were in very close agreement with those provided by a marker-based commercial system with their regression line having a slope close to 1 (maximum distance: mean slope = 0.94 ± 0.1; peak velocity: mean slope = 1.06 ± 0.12). Furthermore, the Oculus Quest had virtually the same sensitivity as that of a commercial system in distinguishing healthy from pathological kinematic measures. The Oculus Quest was as accurate as a commercial marker-based system in measuring clinically meaningful upper-limb kinematic parameters in stroke patients.