bluuebunny/crossref_metadata_2025 huggingface dataset:
Genome-Wide Association Study of Starch Properties in Local Thai Rice
Authors: Praphasanobol Parama , Purnama Putut Rakhmad , Junbuathong Supaporn , Chotechuen Somsong , Moung-Ngam Peerapon , Kasettranan Waraluk , Paliyavuth Chanita , Comai Luca , Pongpanich Monnat , Buaboocha Teerapong , Chadchawan Supachitra
Published: September 2023

Rice (Oryza sativa L.) is the main source of energy for humans and a staple food of high cultural significance for much of the world’s population. Rice with highly resistant starch (RS) is beneficial for health and can reduce the risk of disease, especially type II diabetes. The identification of loci affecting starch properties will facilitate breeding of high-quality and health-supportive rice. A genome-wide association study (GWAS) of 230 rice cultivars was used to identify candidate loci affecting starch properties. The apparent amylose content (AAC) among rice cultivars ranged from 7.04 to 33.06%, and the AAC was positively correlated with RS (R2 = 0.94) and negatively correlated with rapidly available glucose (RAG) (R2 = −0.73). Three loci responsible for starch properties were detected on chromosomes 1, 6, and 11. On chromosome 6, the most significant SNP corresponded to LOC_Os06g04200 which encodes granule-bound starch synthase I (GBSSI) or starch synthase. Two novel loci associated with starch traits were LOC_Os01g65810 and LOC_Os11g01580, which encode an unknown protein and a sodium/calcium exchanger, respectively. The markers associated with GBSSI and LOC_Os11g01580 were tested in two independent sets of rice populations to confirm their effect on starch properties. The identification of genes associated with starch traits will further the understanding of the molecular mechanisms affecting starch in rice and may be useful in the selection of rice varieties with improved starch.
First Report and Complete Genome Characterization of Cherry Virus A and Little Cherry Virus 1 from Russia
Authors: Chirkov Sergei , Sheveleva Anna , Tsygankova Svetlana , Slobodova Natalia , Sharko Fedor , Petrova Kristina , Mitrofanova Irina
Published: September 2023

Virus diseases affect the yield and fruit quality and shorten the productive life of stone fruits (Prunus spp. in the family Rosaceae). Of over fifty known viruses infecting these crops, cherry virus A (CVA) is among the most common, and little cherry virus 1 (LChV1) is one of the most economically important. Using high-throughput sequencing, full-length genomes of CVA and LChV1 isolates, found on interspecies hybrids in the Prunus collection of the Nikita Botanical Gardens, Russia, were sequenced, assembled, and characterized. CVA was found in the P. cerasifera × P. armeniaca hybrid and in phylogenetic analysis clustered with non-cherry virus isolates. The LChV1 isolate Stepnoe was detected in ((P. cerasifera Ehrh. × P. armeniaca L.) × P. brigantiaca Vill.) trihybrid suggesting that both P. cerasifera and P. brigantiaca potentially can be the LChV1 hosts. The isolate Stepnoe was most closely related to the Greece isolate G15_3 from sweet cherry, sharing 77.3% identity at the nucleotide level. Possibly, the highly divergent Russian isolate represents one more phylogroup of this virus. This is the first report of CVA and LChV1 from Russia, expanding the information on their geographical distribution and genetic diversity.
Comparative In Vitro and In Silico Enzyme Inhibitory Screening of Rosa x damascena and Pelargonium graveolens Essential Oils and Geraniol
Authors: Karadağ Ayşe Esra , Biltekin Sevde Nur , Demirci Betül , Demirci Fatih , Ghani Usman
Published: September 2023

The present work aims to evaluate Rosa x damascena Herrm. and Pelargonium graveolens L’Hér. essential oils, and the major constituent geraniol for their in vitro and in silico inhibitory activities against 5-lipoxygenase (5-LOX), cyclooxygenase (COX), acetyl cholinesterase (AChE), butyryl cholinesterase (BuChE), and angiotensin converting enzyme (ACE2) enzymes. Geraniol most potently inhibited the ACE2 relative to other enzymes. R. damascena essential oil moderately inhibited the cancer cell lines with no toxic effects on healthy HEK 293 cells. P. graveolens essential oil inhibited a number of cancer cell lines including A549, MCF7, PC3, and HEK 293 that are reported here for the first time. The molecular docking of geraniol with the target enzymes revealed that it binds to the active sites similar to that of known drugs. Geraniol carries the potential for further drug development due to its drug-like binding mode for the target enzymes. Our work confirms that these essential oils possess similar biological activities due to their similar phytochemistry in terms of the major constituents of the plants. The promising biological activities reported in this work further warrant the inclusion of in vivo studies to establish safe use of the target essential oils and their constituents.
Talking Different Languages: The Role of Plant–Plant Communication When an Invader Beats up a Strange Neighborhood
Authors: Hall Rea Maria , Markovic Dimitrije , Kaul Hans-Peter , Wagentristl Helmut , Urban Bernhard , Durec Nora , Renner-Martin Katharina , Ninkovic Velemir
Published: September 2023

Communication through airborne volatile organic compounds (VOCs) and root exudates plays a vital role in the multifarious interactions of plants. Common ragweed (Ambrosia artemesiifolia L.) is one of the most troublesome invasive alien species in agriculture. Below- and aboveground chemical interactions of ragweed with crops might be an important factor in the invasive species’ success in agriculture. In laboratory experiments, we investigated the contribution of intra- and interspecific airborne VOCs and root exudates of ragweed to its competitiveness. Wheat, soybean, and maize were exposed to VOCs emitted from ragweed and vice versa, and the adaptation response was measured through plant morphological and physiological traits. We observed significant changes in plant traits of crops in response to ragweed VOCs, characterized by lower biomass production, lower specific leaf area, or higher chlorophyll contents. After exposure to ragweed VOCs, soybean and wheat produced significantly less aboveground dry mass, whereas maize did not. Ragweed remained unaffected when exposed to VOCs from the crops or a conspecific. All crops and ragweed significantly avoided root growth toward the root exudates of ragweed. The study shows that the plant response to either above- or belowground chemical cues is highly dependent on the identity of the neighbor, pointing out the complexity of plant–plant communication in plant communities.
Maize Production under Drought Stress: Nutrient Supply, Yield Prediction
Authors: Széles Adrienn , Horváth Éva , Simon Károly , Zagyi Péter , Huzsvai László
Published: September 2023

Maize yield forecasting is important for the organisation of harvesting and storage, for the estimation of the commodity base and for the provision of the country’s feed and food demand (export–import). To this end, a field experiment was conducted in dry (2021) and extreme dry (2022) years to track the development of the crop to determine the evolution of the relative chlorophyll content (SPAD) and leaf area index (LAI) for better yield estimation. The obtained results showed that SPAD and LAI decreased significantly under drought stress, and leaf senescence had already started in the early vegetative stage. The amount of top dressing applied at V6 and V12 phenophases did not increase yield due to the low amount of rainfall. The 120 kg N ha−1 base fertiliser proved to be optimal. The suitability of SPAD and LAI for maize yield estimation was modelled by regression analysis. Results showed that the combined SPAD-LAI was suitable for yield prediction, and the correlation was strongest at the VT stage (R2 = 0.762).
Optimization of LDO-Pectin Synthesis Conditions for the Removal of Metals from Wastewater: A Comparison of Response Surface Methods and Taguchi Approaches
Authors: Mohrazi Ava , Ghasemi-Fasaei Reza , Mojiri Amin , Safarzadeh Shirazi Sedigheh
Published: September 2023

With the continuous growth of industrialization, the presence of heavy metals (HMs) in the environment has become a critical issue, necessitating cost-effective and efficient techniques for their removal. The present study aimed to determine the optimal preparation conditions for synthesizing pectin (PC) as a polymer sorbent, combined with Magnesium (Mg) Aluminum (Al) layered double oxides (LDOs), using a fast and facile co-precipitation method. Both the response surface method (RSM) and the Taguchi method were employed to optimize the influence of key independent variables, including the molar ratio of cations Mg:Al, the ratio of pectin to LDO, and the temperature for removing multiple elements from wastewater. The results indicated that RSM is more accurate and examines more interactions, while Taguchi reduces the number of tests and is more economical than RSM. However, both statistical methods showed good potential for predicting the adsorption capacity (Qe) of HMs. The optimal preparation conditions were identified as a molar ratio of 3:1, a ratio of pectin to LDO of 7% w/w, and a temperature of approximately 600 °C. In conclusion, the application of RSM and Taguchi approaches was found to be feasible and effective in optimizing the preparation conditions of modified LDO, which can be utilized as a potential adsorbent for removing multiple elements from wastewater.
Innovative Strategies for Technical-Economical Optimization of FDM Production
Authors: Zisopol Dragoș Gabriel , Tănase Maria , Portoacă Alexandra Ileana
Published: September 2023

This article introduces a multi-objective optimization approach for determining the best 3D printing parameters (layer thickness and infill percentage) to efficiently produce PLA and ABS parts, extensively analyzing mechanical behavior under tests for different traits such as tensile strength, compression, flexural, impact, and hardness. The value analysis method is used to optimize settings that balance use value (Vi- represented by mechanical characteristics) and production cost (Cp). Findings reveal that the infill percentage significantly influences the Vi/Cp ratio for tensile, compression, and hardness tests, while flexural tests are influenced by layer thickness. Impact strength is influenced nearly equally by both factors, with material-specific variations. The desirability function proved useful for optimizing processes with multiple responses, identifying the optimal parameters for the FDM process: a layer thickness of 0.15 mm with 100% infill percentage for PLA, a layer thickness of 0.20 mm with 100% infill percentage for annealed PLA, and a layer thickness of 0.15 mm with 100% infill percentage for ABS. Overall, this study guides efficient 3D printing parameter selection through a technical-economic optimization based on value analysis.
The Optimization of Pressure-Assisted Microsyringe (PAM) 3D Printing Parameters for the Development of Sustainable Starch-Based Patches
Authors: Pérez Gutiérrez Carmen Laura , Cottone Francesco , Pagano Cinzia , Di Michele Alessandro , Puglia Debora , Luzi Francesca , Dominici Franco , Sinisi Rossella , Ricci Maurizio , Viseras Iborra César Antonio , Perioli Luana
Published: September 2023

The aim of this work was to develop sustainable patches for wound application, using the biopolymer starch, created using a low-cost 3D printing PAM device. The composition of a starch gel was optimized for PAM extrusion: corn starch 10% w/w, β-glucan water suspension (filler, 1% w/w), glycerol (plasticizer, 29% w/w), and water 60% w/w. The most suitable 3D printing parameters were optimized as well (nozzle size 0.8 mm, layer height 0.2 mm, infill 100%, volumetric flow rate 3.02 mm3/s, and print speed 15 mm/s). The suitable conditions for post-printing drying were set at 37 °C for 24 h. The obtained patch was homogenous but with low mechanical resistance. To solve this problem, the starch gel was extruded over an alginate support, which, after drying, becomes an integral part of the product, constituting the backing layer of the final formulation. This approach significantly improved the physicochemical and post-printing properties of the final bilayer patch, showing suitable mechanical properties such as elastic modulus (3.80 ± 0.82 MPa), strength (0.92 ± 0.08 MPa), and deformation at break (50 ± 1%). The obtained results suggest the possibility of low-cost production of patches for wound treatment by additive manufacturing technology.
Thermoplastic Starch Biocomposite Films Reinforced with Nanocellulose from Agave tequilana Weber var. Azul Bagasse
Authors: Lomelí-Ramírez María Guadalupe , Reyes-Alfaro Benjamín , Martínez-Salcedo Silvia Lizeth , González-Pérez María Magdalena , Gallardo-Sánchez Manuel Alberto , Landázuri-Gómez Gabriel , Vargas-Radillo J. Jesús , Diaz-Vidal Tania , Torres-Rendón José Guillermo , Macias-Balleza Emma Rebeca , García-Enriquez Salvador
Published: September 2023

In this work, cellulose nanocrystals (CNCs), bleached cellulose nanofibers (bCNFs), and unbleached cellulose nanofibers (ubCNFs) isolated by acid hydrolysis from Agave tequilana Weber var. Azul bagasse, an agro-waste from the tequila industry, were used as reinforcements in a thermoplastic starch matrix to obtain environmentally friendly materials that can substitute contaminant polymers. A robust characterization of starting materials and biocomposites was carried out. Biocomposite mechanical, thermal, and antibacterial properties were evaluated, as well as color, crystallinity, morphology, rugosity, lateral texture, electrical conductivity, chemical identity, solubility, and water vapor permeability. Pulp fibers and nanocelluloses were analyzed via SEM, TEM, and AFM. The water vapor permeability (WVP) decreased by up to 20.69% with the presence of CNCs. The solubility decreases with the presence of CNFs and CNCs. The addition of CNCs and CNFs increased the tensile strength and Young’s modulus and decreased the elongation at break. Biocomposites prepared with ubCNF showed the best tensile mechanical properties due to a better adhesion with the matrix. Images of bCNF-based biocomposites demonstrated that bCNFs are good reinforcing agents as the fibers were dispersed within the starch film and embedded within the matrix. Roughness increased with CNF content and decreased with CNC content. Films with CNCs did not show bacterial growth for Staphylococcus aureus and Escherichia coli. This study offers a new theoretical basis since it demonstrates that different proportions of bleached or unbleached nanofibers and nanocrystals can improve the properties of starch films.
Facile Preparation of Polysiloxane-Modified Asphalt Binder Exhibiting Enhanced Performance
Authors: Qian Jinhua , Dong Fuying , Chen Xiaohui , Xu Xianying , Zhang Dongkang , Li Fulong , Gao Yuxia , Sun Huadong , Pang Laixue , Tang Xinde , Wang Dengxu
Published: September 2023

The development of polymer-modified asphalt (asphalt = asphalt binder) is significant because the polymer modifier can improve the performance of asphalt mixture and meet the requirements of the modern asphalt pavement. Herein, we present a novel polysiloxane-modified asphalt with enhanced performance, formed by simply mixing hydroxy-terminated polysiloxane (HO-PDMS) into base asphalt at 140 °C. The interaction mechanism of HO-PDMS in base asphalt was characterized by FT-IR, GPC, and DSC. It reveals that HO-PDMS polymers have been chemically bonded into the asphalt, and, thus, the resultant asphalt exhibits optimal compatibility and storage stability. The results based on fluorescence microscopy and a segregation test prove that HO-PDMS has good compatibility with base asphalt. Moreover, by virtue of the intriguing properties of polysiloxane, the present asphalt possesses improved low- and high-temperature properties, higher thermal stability, and enhanced hydrophobicity compared to conventional asphalt when using an appropriate dosage of HO-PDMS. DSC indicated that the Tg of modified asphalt (−12.8 °C) was obviously lower than that of base asphalt (−7.1 °C). DSR shows that the rutting parameter of modified asphalt was obviously higher than that of base asphalt. BBR shows that modified asphalt exhibited the lowest stiffness modulus and the highest creep rate with an HO-PDMS dosage of 6% and 4%, respectively. These results demonstrate that polysiloxane-modified asphalt can be promisingly utilized in realistic asphalt pavement with specific requirements, particularly high-/low-temperature resistance.
Cellulose Fibers-Based Porous Lightweight Foams for Noise Insulation
Authors: Seciureanu Mihai , Nastac Silviu-Marian , Guiman Maria-Violeta , Nechita Petronela
Published: September 2023

This paper examines effective and environmentally friendly materials intended for noise insulation and soundproofing applications, starting with materials that have gained significant attention within last years. Foam-formed materials based on cellulose fibers have emerged as a promising solution. The aim of this study was to obtain a set of foam-formed, porous, lightweight materials based on cellulose fibers from a resinous slurry pulp source, and to investigate the impact of surfactant percentage of the foam mixtures on their noise insulation characterisitcs. The basic foam-forming technique was used for sample assembly, with three percentages of sodium dodecyl sulphate (as anionic surfactant) related to fiber weight, and a standardised sound transmission loss tube procedure was used to evaluate noise insulation performance. Results were obtained as observations of internal structural configurations and material characteristics, and as measurements of sound absorption/reflection, sound transmission loss, and surface acoustic impedance. Based on the findings within this study, the conclusions highlight the strong potential of these cellulosic foams to replace widely used synthetic materials, at least into the area of practical noise insulation applications.
Preparation and Application of a Multifunctional Interfacial Modifier for Ramie Fiber/Epoxy Resin Composites
Authors: Zhang Liyue , Liu Jingkai , Dai Jinyue , Zhang Xufeng , Liu Xiaoling , Liu Xiaoqing , Yi Xiaosu
Published: September 2023

A multi-functional modifier, which could improve the mechanical and thermal performance simultaneously, is significant in composites production. Herein, inspired by the chemistry of mussel, an interfacial modifier named FPD was designed and synthesized through one simple step, which was attached by three functional groups (including catechol, N-H bond, and DOPO). Due to the innate properties of each functional group, FPD played multiple roles: adhere to the ramie fibers from catechol and cure with the epoxy resin from -NH-, an antiflaming property from DOPO, and the compatibilizer between ramie fibers and epoxy resin was also improved by changing the polarity of ramie fiber. All of the above functions can be proved by means of water contact angle (WCA), atomic force microscope (AFM), and scanning electron microscopy (SEM), etc. After solidification, the ramie fiber/epoxy composites demonstrated superior performances in terms of good mechanical properties and excellent flame retardant property. With the addition of 30 wt.% FPD, the tensile strength and modulus of the ramie/epoxy composite showed an improvement of 37.1% and 60.9%, and flexural strength and modulus of the composite were improved by 8.9% and 19.3% comparing with no addition composite. Moreover, the composite could achieve the goal for V-0 rating in the UL-94 test and LOI value was 34.6% when the addition of FPD reached 30 wt.%. This work provided us with an efficient method for fabricating nature fiber/epoxy composites with good properties.
Rational Design of Novel Conjugated Terpolymers Based on Diketopyrrolopyrrole and Their Applications to Organic Thin-Film Transistors
Authors: Ren Shiwei , Ding Yubing , Zhang Wenqing , Wang Zhuoer , Wang Sichun , Yi Zhengran
Published: September 2023

Organic polymer semiconductor materials, due to their good chemical modifiability, can be easily tuned by rational molecular structure design to modulate their material properties, which, in turn, affects the device performance. Here, we designed and synthesized a series of materials based on terpolymer structures and applied them to organic thin-film transistor (OTFT) device applications. The four polymers, obtained by polymerization of three monomers relying on the Stille coupling reaction, shared comparable molecular weights, with the main structural difference being the ratio of the thiazole component to the fluorinated thiophene (Tz/FS). The conjugated polymers exhibited similar energy levels and thermal stability; however, their photochemical and crystalline properties were distinctly different, leading to significantly varied mobility behavior. Materials with a Tz/FS ratio of 50:50 showed the highest electron mobility, up to 0.69 cm2 V−1 s−1. Our investigation reveals the fundamental relationship between the structure and properties of materials and provides a basis for the design of semiconductor materials with higher carrier mobility.
Fluidized Bed Co-Melt Granulation: New Insights in the Influence of Process Variables and Validation of Regime Map Theory
Authors: Lobos de Ponga Jacquelina C. , Piña Juliana , Cotabarren Ivana M.
Published: September 2023

The understanding of granule growth mechanisms and the effects of formulation and operating conditions over product quality and process performance in fluidized bed co-melt granulation is nowadays of great interest. In this sense, this work systematically studies the combined effects of binder content (WPEG) and fluidization air flowrate (FA) and temperature (TA) on granules’ quality and process-related variables (product mass (MP), elutriated fines (Mf), mass stuck on walls (MW)) by using a Box–Behnken-type design of experiments (DoE), as it is a statistical tool suggested by the Quality by Design (QbD) initiative. It was found that the granules’ size and powder flowability are significantly affected by WPEG (higher WPEG, higher granule size and better flowability). Interestingly, TA is the process variable that significantly affects MP, enhancing process performance at high temperature values. Regarding FA, it significantly affects d10, promoting the formation of small particles due to breakage at high flowrates and the presence of non-elutriated powder at low flowrates. As a consequence, intermediate FA is the optimum for obtaining higher MP. Regarding regime map studies, most runs experienced a rapid growth regime, which is in accordance with the granules’ high pore saturation. This result agrees with the observed high increment in particle size and the morphology of the final granules, allowing researchers to validate and extend existing previous maps.
Fouling Mitigation in Membrane Distillation Using Pulsation Flow Technique
Authors: Abulkhair Hani , Moujdin Iqbal Ahmed , Kaddoura Bashar , Khan Muhammad Saad
Published: September 2023

The main obstacles to scaling up membrane distillation (MD) on a commercial level are membrane fouling and temperature polarization. Therefore, in this study, the significance of the pulsation feed flow phenomenon was used for membrane distillation (DCMD) polarization, and comparisons were made using steady-state feed flow. Two different Hertz and amplitudes of pulsation feed flow trends were used in DCMD using different sources of water, including distilled water, seawater, and wastewater. Compared to steady-state feed flow, the results revealed that flux was enhanced for seawater once the operating flow became turbulent, and it enhanced even more once the flow rate was increased and the turbulence flow was moved. For wastewater, pulsation in the feed flow had an impact on delaying the beginning of the flux decline point and enhancing the overall freshwater recovery. In both pulsation feed flows (1 and 2 Hertz), the results also revealed a deficiency in fouling and an improvement in the temperature distribution in the feed channel for seawater desalination and wastewater running under typical operational conditions. Taking this value into consideration, an enhancement in mass flux (~5–10%) was observed compared to steady-state feed flow. Moreover, the pulsation feed channels were found to reduce CPC by about 10–15%, proving the role of turbulence in mixing the flow and mitigating the reduction in concentration polarization.
Mechanisms of Stress Sensitivity on Artificial Fracture Conductivity in the Flowback Stage of Shale Gas Wells
Authors: Yang Xuefeng , Wu Tianpeng , Ren Liming , Huang Shan , Wang Songxia , Li Jiajun , Liu Jiawei , Zhang Jian , Chen Feng , Chen Hao
Published: September 2023

The presence of a reasonable flowback system after fracturing is a necessary condition for the high production of shale gas wells. At present, the optimization of the flowback system lacks a relevant theoretical basis. Due to this lack, this study established a new method for evaluating the conductivity of artificial fractures in shale, which can quantitatively characterize the backflow, embedment, and fragmentation of proppant during the flowback process. Then, the mechanism of the stress sensitivity of artificial fractures on fracture conductivity during the flowback stage of the shale gas well was revealed by performing the artificial fracture conductivity evaluation experiment. The results show that a large amount of proppant migrates, and the fracture conductivity decreases rapidly in the early stage of flowback, and then the decline gradually slows down. When the effective stress is low, the proppant is mainly plastically deformed, and the degree of fragmentation and embedment is low. When the effective stress exceeds 15.0 MPa, the fragmentation and embedment of the proppant will increase, and the fracture conductivity will be greatly reduced. The broken proppant ratio and embedded proppant ratio are the same under the two choke-management strategies. In the mode of increasing choke size step by step, the backflow proppant ratio is lower, and the broken proppant is mainly retained in fractures, so the damage ratio of fracture conductivity is lower. In the mode of decreasing choke size step by step, most of the proppant flows back from fractures, so the damage to fracture conductivity is greater. The research results have important theoretical guiding significance for optimizing the flowback system of shale gas wells.
Study on Variable Stress Corrosion Susceptibility of Four Typical High-Strength Sucker Rods in High-Salinity Well Fluids
Authors: Zhang Fenna , Li Jia , Zhu Hongying , Jing Chuankai , Wang Bin , Qi Yaoguang
Published: September 2023

To study the corrosion characteristics of high-strength sucker rods in high-salinity well fluids under alternating stresses, a single-factor stress corrosion test was designed. The slow strain rate tensile test (SSRT) was carried out for four kinds of high-strength sucker rods under different Cl− and HCO3− concentrations and with different service strengths, and the variable stress corrosion cracking susceptibility was analyzed. The results show that the elongation loss and absorbed work loss of the H-grade ultra-high-strength 4330 sucker rod after stress corrosion are greater than those of both the high-strength 4142 sucker rod and the high-strength 20CrMoA sucker rod. The elongation and absorbed work loss of the 30CrMoA and 20CrMoA sucker rods are less affected by the changes in Cl− and HCO3−. With the increase in use strength, the elongation and absorbed work loss of the high-strength sucker rod increase. The change in the surface of the sucker rod during the corrosion process is inconsistent with the actual elongation of the sucker rod and the absorbed work loss. It can be concluded that the stress corrosion cracking susceptibility of the sucker rod is not necessarily related to the tensile strength of the sucker rod. The 4330 sucker rod is not suitable for applications in wells with a high concentration of Cl−, but it is suitable for operation in alkaline conditions where corrosive media such as HCO3− and Cl− coexist. Under highly corrosive and highly mineralized conditions, the 30CrMoA sucker rod is less susceptible to stress corrosion. The stress corrosion cracking susceptibility of the 20CrMoA sucker rod is lower than that of the 4142 sucker rod. In high-salinity well fluids, the higher the use strength, the higher the stress corrosion cracking susceptibility of the high-strength sucker rod is. The test results for the weight-loss-based corrosion rate and plastic loss may contradict the determination of the corrosion susceptibility of the material under working conditions.
Advancing Fault Prediction: A Comparative Study between LSTM and Spiking Neural Networks
Authors: Souza de Abreu Rute , Silva Ivanovitch , Nunes Yuri Thomas , Moioli Renan C. , Guedes Luiz Affonso
Published: September 2023

Predicting system faults is critical to improving productivity, reducing costs, and enforcing safety in industrial processes. Yet, traditional methodologies frequently falter due to the intricate nature of the task. This research presents a novel use of spiking neural networks (SNNs) in anticipating faults in syntactical time series, utilizing the generalized stochastic Petri net (GSPN) model. The inherent ability of SNNs to process both time and space aspects of data positions them as a prime instrument for this endeavor. A comparative evaluation with long short-term memory (LSTM) networks suggests that SNNs offer comparable robustness and performance.
Atomic Orbital Search Algorithm for Efficient Maximum Power Point Tracking in Partially Shaded Solar PV Systems
Authors: Hussain Md Tahmid , Tariq Mohd , Sarwar Adil , Urooj Shabana , BaQais Amal , Hossain Md. Alamgir
Published: September 2023

The efficient extraction of solar PV power is crucial to maximize utilization, even in rapidly changing environmental conditions. The increasing energy demands highlight the importance of solar photovoltaic (PV) systems for cost-effective energy production. However, traditional PV systems with bypass diodes at their output terminals often produce multiple power peaks, leading to significant power losses if the optimal combination of voltage and current is not achieved. To address this issue, algorithms capable of finding the highest value of a function are employed. Since the PV power output is a complex function with multiple local maximum power points (LMPPs), conventional algorithms struggle to handle partial shading conditions (PSC). As a result, nature-inspired algorithms, also known as metaheuristic algorithms, are used to maximize the power output of solar PV arrays. In this study, we introduced a novel metaheuristic algorithm called atomic orbital search for maximum power point tracking (MPPT) under PSC. The primary motivation behind this research is to enhance the efficiency and effectiveness of MPPT techniques in challenging scenarios. The proposed algorithm offers several advantages, including higher efficiency, shorter tracking time, reduced output variations, and improved duty ratios, resulting in faster convergence to the maximum power point (MPP). To evaluate the algorithm’s performance, we conducted extensive experiments using Typhoon HIL and compared it with other existing algorithms commonly employed for MPPT. The results clearly demonstrated that the proposed atomic orbital search algorithm outperformed the alternatives in terms of rapid convergence and efficient MPP tracking, particularly for complex shading patterns. This makes it a suitable choice for developing an MPP tracker applicable in various settings, such as industrial, commercial, and residential applications. In conclusion, our research addresses the pressing need for effective MPPT methods in solar PV systems operating under challenging conditions. The atomic orbital search algorithm showcases its potential in significantly improving the efficiency and performance of MPPT, ultimately contributing to the optimization of solar energy extraction and utilization.
Non-Classical Circularly Polarized Luminescence Control of Peptide Luminophore Based on Precise Chiral Space Control
Authors: Imai Yoshitane , Kitamatsu Mizuki
Published: September 2023

Light that rotates in a circular spiral when viewed from the front is known as circularly polarized luminescence (CPL), and can be divided into two types, namely, left- and right-rotating light. To emit both left- and right-rotating CPLs, two types of optically active luminophores, namely, enantiomer D- and L-bodies, are generally required. This mini-review mainly discusses our latest study on CPL properties via the control of the pyrene ring as the luminescent unit incorporated into chiral peptides. In this study, optically active peptide–pyrene organoluminescent materials that emit CPL were synthesized by combining a peptide as a frame and two pyrene rings as a luminescent unit. By adjusting the interpyrene distance, external conditions, and absolute chiral configuration (D- or L-configuration), the chiral spatial configuration of the luminescent pyrene ring was precisely controlled. Consequently, the direction of CPL rotation from pyrenylalanine-containing peptides with the same configuration was successfully controlled.
Improved Time-Varying BLF-Based Tracking Control of a Position-Constrained Robot
Authors: Zhang Tan , Zhang Jinzhong
Published: September 2023

In this work, one improved symmetric time-variant logarithmic barrier, Lyapunov function (BLF), is developed for the first time to handle the state constraint problem of nonlinear systems. It is universal in the sense that the improved barrier function is a general one that can be used not only in systems with constrained requirements but also in systems without constrained requirements, without altering the designed controller. First of all, the n-link robotic system is transformed into a kind of multi-input and multi-output (MIMO) system. Then, a trajectory tracking control scheme is designed by combining the improved time-variant logarithmic BLF with the disturbance observer to solve the problems of model uncertainty and position constraint for the robotic system. We give that under the proposed controller, all the robotic system’s error vectors can trend to the equilibrium point asymptotically while the constraint conditions on the position are always met. Finally, the effectiveness of the presented scheme is indicated by completing two simulation experiment cases.
Long-Tailed Object Detection for Multimodal Remote Sensing Images
Authors: Yang Jiaxin , Yu Miaomiao , Li Shuohao , Zhang Jun , Hu Shengze
Published: September 2023

With the rapid development of remote sensing technology, the application of convolutional neural networks in remote sensing object detection has become very widespread, and some multimodal feature fusion networks have also been proposed in recent years. However, these methods generally do not consider the long-tailed problem that is widely present in remote sensing images, which limits the further improvement of model detection performance. To solve this problem, we propose a novel long-tailed object detection method for multimodal remote sensing images, which can effectively fuse the complementary information of visible light and infrared images and adapt to the imbalance between positive and negative samples of different categories. Firstly, the dynamic feature fusion module (DFF) based on image entropy can dynamically adjust the fusion coefficient according to the information content of different source images, retaining more key feature information for subsequent object detection. Secondly, the instance-balanced mosaic (IBM) data augmentation method balances instance sampling during data augmentation, providing more sample features for the model and alleviating the negative impact of data distribution imbalance. Finally, class-balanced BCE loss (CBB) can not only consider the learning difficulty of specific instances but also balances the learning difficulty between categories, thereby improving the model’s detection accuracy for tail instances. Experimental results on three public benchmark datasets show that our proposed method achieves state-of-the-art performance; in particular, the optimization of the long-tailed problem enables the model to meet various application scenarios of remote sensing image detection.
Double Inversion Layers Affect Fog–Haze Events over Eastern China—Based on Unmanned Aerial Vehicles Observation
Authors: Liu Ruolan , Liu Duanyang , Yuan Shujie , Wu Hong , Zu Fan , Liu Ruixiang
Published: September 2023

The goal of this work is to analyze how double inversion layers affect fog–haze events and boundary layers over Eastern China based on unmanned aerial vehicle observations. During 10–12 December 2020, two successive fog–haze events occurred in Eastern China. Based on the unmanned aerial vehicle (UAV), wind, temperature, relative humidity (RH), and aerosol mass concentration were monitored simultaneously in Lianyungang, China. Several observations were found after analyzing the physical fields of these data. The results show that the concentrations of air pollutants during fog events were negatively correlated with horizontal visibilities. The mass concentrations of particulate matter increased rapidly (After 08:00 BJT 11) in the fog dissipation stages (PM2.5 and PM10 increased from 97 and 150 μg/m3 to 213 and 300 μg/m3, respectively). Double temperature inversion significantly affected fog events, where the enhancement of the lower-level temperature inversion (where the inversion layer top height was between 150 and 300 m) corresponded to the explosive growth of fog and the dissipation of the upper-level inversion layer. (The bottom height of the inversion layer was between 350 m and 600 m) This indicates the end of fog events. Fog layer thicknesses are negatively correlated with the concentrations of air pollutants in the near-surface layer. The thickening of the inversion layer near the surface corresponds to an increase (after 05:00 BJT 11 and 03:00 BJT 12) in fog layer height. The fog event is maintained when water vapor conditions are favorable enough or when there is a deep near-surface temperature inversion but the maintenance of the near-surface temperature inversion at an intensity of above 2 °C (100 m)−1 mainly contributes to the durations of these two fog events. Calculations through the trajectory model reveal that the air pollutant source varied during these two events, which was the main reason for the difference in air pollutant concentrations between the two events.
DSF-Net: A Dual Feature Shuffle Guided Multi-Field Fusion Network for SAR Small Ship Target Detection
Authors: Xu Zhijing , Zhai Jinle , Huang Kan , Liu Kun
Published: September 2023

SAR images play a crucial role in ship detection across diverse scenarios due to their all-day, all-weather characteristics. However, detecting SAR ship targets poses inherent challenges due to their small sizes, complex backgrounds, and dense ship scenes. Consequently, instances of missed detection and false detection are common issues. To address these challenges, we propose the DSF-Net, a novel framework specifically designed to enhance small SAR ship detection performance. Within this framework, we introduce the Pixel-wise Shuffle Attention module (PWSA) as a pivotal step to strengthen the feature extraction capability. To enhance long-range dependencies and facilitate information communication between channels, we propose a Non-Local Shuffle Attention (NLSA) module. Moreover, NLSA ensures the stability of the feature transfer structure and effectively addresses the issue of missed detection for small-sized targets. Secondly, we introduce a novel Triple Receptive Field-Spatial Pyramid Pooling (TRF-SPP) module designed to mitigate the issue of false detection in complex scenes stemming from inadequate contextual information. Lastly, we propose the R-tradeoff loss to augment the detection capability for small targets, expedite training convergence, and fortify resistance against false detection. Quantitative validation and qualitative visualization experiments are conducted to substantiate the proposed assumption of structural stability and evaluate the effectiveness of the proposed modules. On the LS-SSDDv1.0 dataset, the mAP50−95 demonstrates a remarkable improvement of 8.5% compared to the baseline model. The F1 score exhibits a notable enhancement of 6.9%, surpassing the performance of advanced target detection methods such as YOLO V8.
Methane Emissions in Boreal Forest Fire Regions: Assessment of Five Biomass-Burning Emission Inventories Based on Carbon Sensing Satellites
Authors: Zhao Siyan , Wang Li , Shi Yusheng , Zeng Zhaocheng , Nath Biswajit , Niu Zheng
Published: September 2023

Greenhouse gases such as CH4 generated by forest fires have a significant impact on atmospheric methane concentrations and terrestrial vegetation methane budgets. Verification in conjunction with “top-down” satellite remote sensing observation has become a vital way to verify biomass-burning emission inventories and accurately assess greenhouse gases while looking into the limitations in reliability and quantification of existing “bottom-up” biomass-burning emission inventories. Therefore, we considered boreal forest fire regions as an example while combining five biomass-burning emission inventories and CH4 indicators of atmospheric concentration satellite observation data. By introducing numerical comparison, correlation analysis and trend consistency analysis methods, we explained the lag effect between emissions and atmospheric concentration changes and evaluated a more reliable emission inventory using time series similarity measurement methods. The results indicated that total methane emissions from five biomass-burning emission inventories differed by a factor of 2.9 in our study area, ranging from 2.02 to 5.84 Tg for methane. The time trends of the five inventories showed good consistency, with the Quick Fire Emissions Dataset version 2.5 (QFED2.5) having a higher correlation coefficient (above 0.8) with the other four datasets. By comparing the consistency between the inventories and satellite data, a lagging effect was found to be present between the changes in atmospheric concentration and gas emissions caused by forest fires on a seasonal scale. After eliminating lagging effects and combining time series similarity measures, the QFED2.5 (Euclidean distance = 0.14) was found to have the highest similarity to satellite data. In contrast, Global Fire Emissions Database version 4.1 with small fires (GFED4.1s) and Global Fire Assimilation System version 1.2 (GFAS1.2) had larger Euclidean distances of 0.52 and 0.4, respectively, which meant that they had lower similarity to satellite data. Therefore, QFED2.5 was found to be more reliable while having higher application accuracy compared to the other four datasets in our study area. This study further provided a better understanding of the key role of forest fire emissions in atmospheric CH4 concentrations and offered reference for selecting appropriate biomass burning emission inventory datasets for bottom-up inventory estimation studies.
A Quick-Look Software for In Situ Magnetic Field Modeling from Onboard Unmanned Aircraft Vehicles (UAVs) Measurements
Authors: Thebault Erwan , Gailler Lydie-Sarah
Published: September 2023

UAVs represent a tremendous opportunity to perform geophysical and repeated experiments, particularly in volcanic contexts. Their ability to be deployed rapidly and fly at various altitudes and the fact that they are easy to operate despite complex field conditions make them attractive for magnetic surveys. Detailed maps of the magnetic field in turn bring key constraints on the rocks’ composition, thermal anomalies, intrusive systems, and crustal contrast evolution. Yet, raw magnetic field measurements require careful processing to minimize directional, positional, and crossover errors. Moreover, stitching together adjacent or overlapping surveys acquired at different times and altitudes is not a trivial task. Therefore, it is challenging in remote areas to directly evaluate the consistency of a survey and to ascertain the success of the field mission. In this paper, we present a fast algorithm allowing for a quick-look modeling of scalar magnetic intensity measurements. The approach relies on rectangular harmonic analysis (RHA). The field measurements are automatically corrected for a global main field. Then, they are projected along this main field and modeled in terms of RHA functions. The software can exploit the quality indices provided with data and a procedure is applied to mitigate the effect of outliers. Maps for the scalar and the vector anomaly fields are readily built on an interpolated regular grid leveled at a constant altitude. In order to assess the modeling and the inversion procedures, analyses are carried out with synthetic measurements derived from a high-resolution global lithospheric magnetic field model estimated on the French aeromagnetic grid and at UAV locations with some added nonrandom noise. These analyses indicate that RHA is efficient for first-order and direct mapping of the crustal magnetic field structures measured by UAVs but that it could be applied on airborne and marine magnetic intensity data covering dense and large geographical extensions.
Neural-Network-Based Target Classification and Range Detection by CW MMW Radar
Authors: Richter Yair , Balal Nezah , Pinhasi Yosef
Published: September 2023

This study presents a reliable classification of walking pedestrians and animals using a radar operating in the millimeter waves (mmW) regime. In addition to the defined targets, additional targets were added in an attempt to fool the radar and to present the robustness of the proposed technique. In addition to the classification capabilities, the presented scheme allowed for the ability to detect the range of targets. The classification was achieved using a deep neural network (DNN) architecture, which received the recordings from the radar as an input after the pre-processing procedure. Qualitative detection was made possible due to the radar’s operation at extremely high frequencies so that even the tiny movements of limbs influenced the detection, thus enabling the high-quality classification of various targets. The classification results presented a high achievable accuracy even in the case where the targets attempted to fool the radar and mimicked other targets. The combination of the use of high frequencies alongside neural-network-based classification demonstrated the superiority of the proposed scheme in this research over the state of the art. The neural network was analyzed with the help of interpretable tools such as explainable AI (XAI) to achieve a better understanding of the DNN’s decision-making process and the mechanisms via which it was able to perform multiple tasks at once.
TTNet: A Temporal-Transform Network for Semantic Change Detection Based on Bi-Temporal Remote Sensing Images
Authors: Jiang Liangcun , Li Feng , Huang Li , Peng Feifei , Hu Lei
Published: September 2023

Semantic change detection (SCD) holds a critical place in remote sensing image interpretation, as it aims to locate changing regions and identify their associated land cover classes. Presently, post-classification techniques stand as the predominant strategy for SCD due to their simplicity and efficacy. However, these methods often overlook the intricate relationships between alterations in land cover. In this paper, we argue that comprehending the interplay of changes within land cover maps holds the key to enhancing SCD’s performance. With this insight, a Temporal-Transform Module (TTM) is designed to capture change relationships across temporal dimensions. TTM selectively aggregates features across all temporal images, enhancing the unique features of each temporal image at distinct pixels. Moreover, we build a Temporal-Transform Network (TTNet) for SCD, comprising two semantic segmentation branches and a binary change detection branch. TTM is embedded into the decoder of each semantic segmentation branch, thus enabling TTNet to obtain better land cover classification results. Experimental results on the SECOND dataset show that TTNet achieves enhanced performance when compared to other benchmark methods in the SCD task. In particular, TTNet elevates mIoU accuracy by a minimum of 1.5% in the SCD task and 3.1% in the semantic segmentation task.