bluuebunny/crossref_metadata_2025 huggingface dataset:
Surface Characterization of AZ31 Alloy after Long-Term Immersion in Simulated Body Fluid
Authors: Pakhomova Ekaterina , Varone Alessandra , Mezzi Alessio , Fava Alessandra , Manis Cristina , Loy Francesco , Palombi Alessandra , Cao Giacomo
Published: December 2023

The aim of the research campaign was to simulate in vitro the typical conditions for the corrosion in biofluid of a femoral bone implant manufactured with AZ31 alloy. The samples were immersed in biofluid (alpha-MEM) for time intervals of up to 56 days. For each immersion time, the chemical compositions and morphologies of the samples were studied with SEM, EDX, XRD, Raman spectroscopy, and XPS. The weight losses of the samples caused by corrosion were also measured. The results highlighted the formation of calcium phosphate crystals on the surface of the samples. This type of coating is well-known for its excellent corrosion resistance and for its ability to accelerate tissue regeneration. The deceleration of the corrosion process, observed after 28 days of immersion in biofluid, confirms the anti-corrosive effect of the coating that was spontaneously formed during the immersion tests.
X-ray Crystal Structure, Hirshfeld Surface Analysis, DFT, and Anticancer Effect of 3-Hydroxy-4-phenyl-1,5-benzodiazepin-2-one Derivatives
Authors: Lahmidi Sanae , Bakheit Ahmad , Essassi El , Mague Joel , Alanazi Mohammed
Published: December 2023

This study investigated the crystallographic and electronic properties of 1,5-benzodiazepine compounds, namely: cis-(3S,4S)-3-hydroxy-7,8-dimethyl-4-phenyl-1,3,4,5-tetrahydro-1,5-benzodiazepin-2-one 3b, trans-(3R,4R)-1-ethyl-3-hydroxy-7,8-dimethyl-4-phenyl-1,3,4,5-tetrahydro-2H-1,5-benzodiazepin-2-one 4, and trans-(3S,4S) 1-ethyl-3-ethoxy-7,8-dimethyl-4-phenyl-1,3,4,5-tetrahydro-1,5-benzodiazepin-2-one 5. Hirshfeld surface analysis was also applied to discern the intermolecular interactions, highlighting the significance of hydrogen bonding, van der Waals forces, and the influence of specific substituents. Furthermore, the MESP maps created using the density functional theory revealed the electrostatic nature of these molecules. The absence of dark blue regions on the MESP maps and variations due to different functional groups and substitutions were noteworthy findings. Collectively, this research offers crucial insights into the behaviour, interactions, and potential applications of new compounds. Finally, the anticancer effects of compounds 3b, 4, and 5 were evaluated against three cancer cell lines and one normal cell line, and the results showed that 3b and 4 had potent antiproliferative effects against all three cancer cell lines.
Identification of Floral Resources Used by the Stingless Bee Melipona beecheii for Honey Production in Different Regions of the State of Campeche, Mexico
Authors: León-Canul Román Alberto , Chalé-Dzul Juan Bautista , Vargas-Díaz Arely Anayansi , Ortiz-Díaz Juan Javier , Durán-Escalante Kelly Cristina , Carrillo-Ávila Eugenio , Santillán-Fernández Alberto
Published: December 2023

The stingless bee Melipona beecheii is experiencing colony decline due to floral resource scarcity caused by deforestation. A study was conducted to identify the floral resources used by M. beecheii using honey samples collected in four regions of the state of Campeche, Mexico. A melissopalynological analysis of sixteen collected honey samples identified 69 plant species from 24 families, and established that Fabaceae was the main plant family visited. Based on botanical origin, seven samples were classified as monofloral and nine as multifloral. The predominant species were Bursera simaruba, Lonchocarpus longistylus, Piscidia piscipula, Senna pallida and Senna racemosa. Shannon diversity index values (2.06–2.55) indicated moderate diversity in floral resources and Simpson diversity index values (0.82–0.89) indicated a moderate dominance of plant species in the studied regions. The results suggest M. beecheii is polylectic with some degree of specialization. The plant species identified as predominant in the studied honey samples are candidates for use in strategies intended to conserve the food resources used by M. beecheii on the Yucatan Peninsula.
The Diversity of Larvae with Multi-Toothed Stylets from About 100 Million Years Ago Illuminates the Early Diversification of Antlion-like Lacewings
Authors: Braig Florian , Popp Timo , Zippel Ana , Haug Gideon T. , Linhart Simon , Müller Patrick , Weiterschan Thomas , Haug Joachim T. , Haug Carolin
Published: December 2023

Neuroptera, the group of lacewings, is well known to have been more diverse in the past, offering to study patterns of biodiversity loss over time. This loss of diversity has been quantitatively established by the morphological diversity of lacewing larvae. Here, we explore in more detail the diversity of lacewing larvae with tooth-bearing mouthparts. All these larvae are representatives of Myrmeleontiformia, the group of antlion-like lacewings. Today, larvae of several major ingroups bear teeth on their mouthparts: (1) owllions (formerly Ascalaphidae and Myrmeleontidae; taxonomic status is currently unclear); (2) Nymphidae; (3) Crocinae (mostly in younger larvae); and (4) Nemopterinae (only micro teeth). In addition, there are several now extinct larval types with teeth known from Cretaceous ambers (about 100 million years old). These larvae also possess several plesiomorphic characters, indicating that they were part of the early diversification of Myrmeleontiformia. We report numerous new specimens of these now extinct forms and provide a quantitative morphological comparison of head and mouthpart shapes, demonstrating that some of these Cretaceous larvae possessed morphologies not represented in the extant fauna. The resulting pattern is complex, indicating that at least some extinct morphologies have been later replaced by modern-day antlions due to convergent evolution.
Immunohistochemistry in an Adult Case of Bitot’s Spots Caused by Vitamin A Deficiency
Authors: Fukuoka Hideki , Yokoi Norihiko , Sotozono Chie
Published: December 2023

Bitot’s spots (BS) are the buildup of superficially located keratin in the conjunctiva and are early indicators of vitamin A deficiency (VAD), primarily due to malnutrition and malabsorption, thus leading to xerophthalmia. BS are particularly prevalent in developing countries, and their presence necessitates prompt vitamin A supplementation to avert blindness, with the immunohistochemical characteristics of BS aiding in understanding the extent of epithelial abnormalities and the efficacy of vitamin A supplementation. We describe the case of a 34-year-old male with persistent BS despite extensive vitamin A supplementation and topical treatments who underwent surgical excision of the BS followed by amniotic membrane transplantation, thus resulting in symptom relief and epithelialization, with no recurrence observed during follow-up. Histopathologic and immunohistochemical evaluations revealed expression of keratinization-related proteins, along with an absence of mucin-5AC-positive cells, suggesting impaired differentiation into goblet cells due to VAD. This case highlights the potential age-related disparity in the efficacy of vitamin A supplementation, emphasizing the need for early detection and a multidisciplinary approach in the management of VAD, especially in young adults. The favorable outcome of surgical intervention highlights its viability in the management of persistent BS and encourages further investigation to optimize therapeutic strategies for VAD-related ocular manifestations.
Artificial Intelligence and Its Clinical Applications in Orthodontics: A Systematic Review
Authors: Dipalma Gianna , Inchingolo Alessio Danilo , Inchingolo Angelo Michele , Piras Fabio , Carpentiere Vincenzo , Garofoli Grazia , Azzollini Daniela , Campanelli Merigrazia , Paduanelli Gregorio , Palermo Andrea , Inchingolo Francesco
Published: December 2023

This review aims to analyze different strategies that make use of artificial intelligence to enhance diagnosis, treatment planning, and monitoring in orthodontics. Orthodontics has seen significant technological advancements with the introduction of digital equipment, including cone beam computed tomography, intraoral scanners, and software coupled to these devices. The use of deep learning in software has sped up image processing processes. Deep learning is an artificial intelligence technology that trains computers to analyze data like the human brain does. Deep learning models are capable of recognizing complex patterns in photos, text, audio, and other data to generate accurate information and predictions. Materials and Methods: Pubmed, Scopus, and Web of Science were used to discover publications from 1 January 2013 to 18 October 2023 that matched our topic. A comparison of various artificial intelligence applications in orthodontics was generated. Results: A final number of 33 studies were included in the review for qualitative analysis. Conclusions: These studies demonstrate the effectiveness of AI in enhancing orthodontic diagnosis, treatment planning, and assessment. A lot of articles emphasize the integration of artificial intelligence into orthodontics and its potential to revolutionize treatment monitoring, evaluation, and patient outcomes.
Tunneling between Multiple Histories as a Solution to the Information Loss Paradox
Authors: Chen Pisin , Sasaki Misao , Yeom Dong-han , Yoon Junggi
Published: December 2023

The information loss paradox associated with black hole Hawking evaporation is an unresolved problem in modern theoretical physics. In a recent brief essay, we revisited the evolution of the black hole entanglement entropy via the Euclidean path integral (EPI) of the quantum state and allow for the branching of semi-classical histories along the Lorentzian evolution. We posited that there exist at least two histories that contribute to EPI, where one is an information-losing history, while the other is an information-preserving one. At early times, the former dominates EPI, while at the late times, the latter becomes dominant. By doing so, we recovered the essence of the Page curve, and thus, the unitarity, albeit with the turning point, i.e., the Page time, much shifted toward the late time. In this full-length paper, we fill in the details of our arguments and calculations to strengthen our notion. One implication of this modified Page curve is that the entropy bound may thus be violated. We comment on the similarity and difference between our approach and that of the replica wormholes and the islands’ conjectures.
Reading to Young Children: Higher Home Frequency Associated with Higher Educational Achievement in PIRLS and PISA
Authors: Araújo Luisa , Costa Patrícia
Published: December 2023

The benefits of reading aloud to young children for their reading development are well documented, and international large-scale assessments (ILSAs) offer an opportunity to explore its unique contribution to literacy achievement at both the primary and secondary levels. Using Portuguese data from ILSAs, this study shows the relationship between reading to young children in the home context and their later reading performance. Specifically, we use the Program for International Reading Literacy Study (PIRLS) 2011, which tests fourth-grade students, and the Program for International Student Assessment (PISA) 2018, which is used for the assessment of 15-year-olds. Data sources from these surveys include the mean reading performance of similar cohorts of students and home/parental questionnaires that include questions about the frequency of home book-reading, as well as other background variables. Linear regression analyses show a positive and significant relationship, both at the fourth-grade level and in secondary school, between students’ performance and having been read to at home during early childhood. These findings indicate that the advantages associated with book reading in the early years are maintained throughout students’ schooling. In addition, the analysis shows that, in both surveys, girls score higher than boys in reading, and that there is a positive association between parental education and reading achievement. Implications about how children’s early literacy development sets the foundation for future educational achievement are discussed, namely in the context of country-specific reading initiatives and reading practices.
A Compact MEMS Microphone Digital Readout System Using LDO and PPA-Less VCO-Based Delta-Sigma Modulation Technique
Authors: Li Fanyang , Yin Tao , Wu Shuwen , Deng Wenren
Published: December 2023

This paper presents a compact Micro-Electro-Mechanical System (MEMS) microphone digital readout system. The system is characterized by a low-dropout regulator (LDO) and a pre-amplifier and programmable-gain amplifier (PPA)-less voltage controlled oscillator (VCO)-based ΔΣ modulation technique, which improve compactness and design scalability. Specifically, to improve signal accuracy and maintain loop stability without a gain-tuning range trade-off, an active low pass filter (ALPF) and a current mode feed-forward path (CMFFP) are incorporated in a VCO-based delta-sigma modulation loop. By means of VCOs and SCG phase variation robustness and current source array feedback (CSAFB), the system achieves a high power supply rejection ratio (PSRR) and gain tuning without the need to design an extra regulator and PPA. The design was fabricated using a 180 nm Bipolar-CMOS-DMOS (BCD) process and measured at a 1.2 V supply voltage. According to the measurement results, the signal-to-noise and distortion ratio (SNDR) achieves 62 dB@1 kHz with 40 dB gain and a 10 kHz bandwidth. Furthermore, PSRR@1 kHz is below −55 dB, and power dissipation is within 57 µW.
NGDCNet: Noise Gating Dynamic Convolutional Network for Image Denoising
Authors: Zhu Minling , Li Zhihai
Published: December 2023

Deep convolution neural networks (CNNs) have become popular for image denoising due to their robust learning capabilities. However, many methods tend to increase the receptive field to improve performance, which leads to over-smoothed results and loss of critical high-frequency information such as edges and texture. In this research, we introduce an innovative end-to-end denoising network named the noise gating dynamic convolutional network (NGDCNet). By integrating dynamic convolution and noise gating mechanisms, our approach effectively reduces noise while retaining finer image details. Through a series of experiments, we conduct a comprehensive evaluation of NGDCNet by comparing it quantitatively and visually against state-of-the-art denoising methods. Additionally, we provide an ablation study to analyze the contributions of dynamic convolutional blocks and noise gating blocks. Our experimental findings demonstrate that NGDCNet excels in noise reduction while preserving essential texture information.
Novel Magnetic Field Modeling Method for a Low-Speed, High-Torque External-Rotor Permanent-Magnet Synchronous Motor
Authors: Kou Shaokai , Kou Ziming , Wu Juan , Wang Yandong
Published: December 2023

In view of the unstable electromagnetic performance of the air gap magnetic field caused by the torque ripple and harmonic interference of a multi-slot and multi-pole low-speed, high-torque permanent magnet synchronous motor, we propose a simplified model of double-layer permanent magnets. The model is divided into an upper and a lower subdomain, with the upper subdomain being an ideal circular ring and the lower subdomain being a segmented sector ring. Moreover, we develop an exact analytical model of the motor that predicts the magnetic field distribution based on Laplace’s and Poisson’s equations, which is solved using the method of separating variables. Taking a 40p168s low-speed, high-torque permanent magnet synchronous motor as an example, the accuracy of the model is verified by comparison with an ideal circular ring model, a segmented sector ring model, and the finite element method. Based on the proposed simplified model, three combined permanent magnets considering both edge-cutting and polar arc cutting structures are proposed, which are chamfered, rounded, and rectangular combinations. Under the premise of a consistent edge-cutting amount, the electromagnetic characteristics of the three combination types of permanent magnets are compared using the finite element method. The results show that the electromagnetic characteristics of the chamfered combination PM are superior to those of the other two combinations. Finally, a prototype is manufactured and tested to validate the theoretical analysis.
Research on Grid-Connected Control Strategy of Photovoltaic (PV) Energy Storage Based on Constant Power Operation
Authors: Wang Tao , Lin Cunhao , Zheng Kuo , Zhao Wei , Wang Xinglu
Published: December 2023

In order to effectively mitigate the issue of frequent fluctuations in the output power of a PV system, this paper proposes a working mode for PV and energy storage battery integration. To address maximum power point tracking of PV cells, a fuzzy control-based tracking strategy is adopted. The principles and corresponding mathematical models are analyzed for the three-phase voltage PWM converter and bidirectional DC/DC converter, while feedforward decoupling double closed loop, constant power (PQ), and constant voltage charge/discharge control strategies are proposed. Space vector pulse width modulation (SVPWM) technology is utilized to generate power switching tube driver signals. Finally, a simulation model is developed in MATLAB/Simulink for system analysis. The results demonstrate that the proposed method enables constant grid-connected power generation and constant voltage charging of the energy storage battery when the PV cell’s power generation exceeds that of the grid. When insufficient solar power generation occurs, both the PV system and energy storage battery work together to achieve constant grid-connected power.
Artificial Intelligence for Management of Variable Renewable Energy Systems: A Review of Current Status and Future Directions
Authors: Yousef Latifa A. , Yousef Hibba , Rocha-Meneses Lisandra
Published: December 2023

This review paper provides a summary of methods in which artificial intelligence (AI) techniques have been applied in the management of variable renewable energy (VRE) systems, and an outlook to future directions of research in the field. The VRE types included are namely solar, wind and marine varieties. AI techniques, and particularly machine learning (ML), have gained traction as a result of data explosion, and offer a method for integration of multimodal data for more accurate forecasting in energy applications. The VRE management aspects in which AI techniques have been applied include optimized power generation forecasting and integration of VRE into power grids, including the aspects of demand forecasting, energy storage, system optimization, performance monitoring, and cost management. Future directions of research in the applications of AI for VRE management are proposed and discussed, including the issue of data availability, types and quality, in addition to explainable artificial intelligence (XAI), quantum artificial intelligence (QAI), coupling AI with the emerging digital twins technology, and natural language processing.
Molecular Simulation of Nitrogen Adsorption in Multidimensional Nanopores and New Insights into the Inversion of Pore Size Distribution for Gas Shale
Authors: Chen Zhuo , Lin Mian , Jiang Wenbin , Cao Gaohui
Published: December 2023

Low-temperature nitrogen adsorption is a widely used method for the research and evaluation of gas shale’s pore structure. The existing interpretation method, utilizing gas adsorption isotherms to obtain pore size distribution (PSD), is always based on the one-dimensional geometry model, while the void space of gas shale has strong multi-dimensional characteristics. It is necessary to investigate the nitrogen condensation and evaporation behavior in multidimensional structures. In this study, a series of two-dimensional and three-dimensional models based on ink-bottle pores were constructed. A hybrid molecular simulation approach combining grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) is proposed to simulate the low-temperature nitrogen adsorption isotherms. Three aspects have been analyzed in detail. Compared with the conventional understanding that the threshold of cavitation in the ink-bottle pore only relates to throat diameter, this study discloses a wider and more comprehensive range of conditions of cavitation that considers both the throat length and diameter. As pore spaces of shale samples consist of many complex interconnected pores, the multi-stage ink-bottle pore model is more suitable than the single ink-bottle pore model to similarly reproduce the wider cavitation pressure range. A more universal parameter is proposed that quantitatively unifies the influence of cavity diameter and length on condensation pressure and has good applicability in cavities with different shapes. This work quantitatively studies the nitrogen adsorption isotherms of three-dimensional complex nanopore structures using molecular simulation and provides a reasonable explanation for the low-temperature nitrogen adsorption isotherms of gas shale.
Investigation of Emulsified Oil Adsorption onto Functionalized Magnetic Nanoparticles—Kinetic and Isotherm Models
Authors: Hamedi Hamideh , Rezaei Nima , Zendehboudi Sohrab
Published: December 2023

Recently, considerable attention has been given to using magnetic nanoparticles (MNPs) for capturing oil from oil-in-water (O/W) emulsions, despite MNPs’ inherent instability and agglomeration. Their stabilization through changing surface chemistry is required to increase dispersivity. In this research, we use cetyltrimethylammonium bromide (CTAB) as a cationic surfactant to increase the positive surface charge of the particles, resulting in a better stability in the aqueous solution because of increased repulsive forces. The functionalized MNPs are characterized using transmission electron microscopy (TEM), zeta potential, and contact angle (CA) measurements. The aim of this study is to investigate the oil separation efficiency (SE) and equilibrium oil adsorption capacity of the synthesized particles, which are determined using gas chromatography analysis. We also study the adsorption behavior using isotherm and kinetic models. The SE values indicate the superior performance of MNP@CTAB for oil adsorption from dodecane-in-water nanoemulsion (SE = 99.80%) compared to the bare MNPs with SE of approximately 57.46%. These findings are attributed to the stronger electrostatic attraction between the MNP@CTAB having high positive charge and negatively charged oil droplets. The adsorption isotherm results using both linear and non-linear regression methods show that the Freundlich isotherm is the best fit to the experimental equilibrium data (with calculated R2 > 0.97), verifying a multilayer heterogeneous adsorption. Moreover, the pseudo-first-order kinetic model describes the experimental equilibrium data in a greater congruence (R2 = 0.99), suggesting physical adsorption of oil onto MNPs through van der Waals and physical bonding, which is also confirmed through zeta potential measurements.
Classification and Design of Backfill Coal Mining Systems Based on Typical Engineering Cases
Authors: Cui Pengfei , Zhang Qiang , Yang Kang , Lv Haonan , Cao Jinming , Wang Wei
Published: December 2023

Backfill coal mining technology has drawn widespread attention due to its benefits of “controlling surface deformation and subsidence, reducing mining-induced disturbance in the stope, and recycling solid mine wastes”. However, the backfill coal mining technology is still progressing slowly in China. The geological environment of China’s mining areas is complex and highly diversified, and backfill coal mining is expected to fulfill different goals in a wide range of engineering scenarios. These facts explain the poor reproducibility of backfill coal mining projects. This study reviews the existing backfill coal mining systems in China. Based on findings from a survey of engineering cases, we summarize five types of new backfill coal mining methods classified by deployment style; namely, borehole grouting backfill, roadway backfill, borehole–roadway backfill, in situ backfill, and roadway-in-situ backfill. A total of 15 backfill coal mining methods falling into the above five categories are described. An engineering design workflow for backfill coal mining consisting of five steps is proposed; namely, identifying the targets of backfill, analyzing the feasibility of deploying the backfill system, comparing the engineering quantities of different engineering schemes, estimating the economic efficiency of backfill, and backfill performance tracking and monitoring. Real cases of backfill engineering design are analyzed to inform the fast and reasonable design of backfill strategy for specific working faces in certain coal mines.
Driving Urban Energy Sustainability: A Techno-Economic Perspective on Nanogrid Solutions
Authors: Turan Onur , Durusu Ali , Yumurtaci Recep
Published: December 2023

In response to technological advances, environmental concerns, and the depletion of conventional energy sources, the world is increasingly focusing on renewable energy sources (RES) as a means of generating electricity in a more sustainable and environmentally friendly manner. Türkiye, with its advantageous geographical location, long hours of sunshine, and favourable climatic conditions, has a high potential for the use of solar energy. The objective of this study was to identify an energy system that minimizes investment costs while optimizing the levelized cost of energy (LCOE) and minimizing greenhouse-gas (GHG) and carbon dioxide emissions. To achieve this, the study used the concept of nanogrids (NGs) and carried out different evaluations for electric vehicle charging stations (EVCS) at different energy levels connected to the grid. The research focused on classic apartment buildings and multistory condominium-style buildings in Istanbul, Türkiye. Using HOMER Grid 1.11.1 version software, the study identified two optimal configurations: a PV–GRID system with 7 kW photovoltaic capacity and a PV–WT–GRID system with 90 kW PV capacity and 6 kW wind-turbine capacity. These configurations had a significantly lower LCOE compared to the cost of electricity from the conventional grid. When examining the sensitivity to economic factors, it was observed that the net present cost (NPC) and LCOE values fluctuated with electricity prices, inflation rates, and equipment costs. In particular, the two optimal configurations did not include a battery energy-storage system (BESS) due to the low energy demand in the PV–GRID system and the efficiency of the wind turbines in the PV–WT–GRID system. This highlights the need to tailor energy solutions to specific consumption patterns and resource types. In conclusion, the adoption of PV–GRID and PV–WT–GRID systems in Istanbul’s urban buildings demonstrates economic viability and environmental benefits, highlighting the importance of renewable energy sources, particularly solar PV, in mitigating energy-related environmental challenges, such as reducing CO2 emissions and reducing dependence on conventional grid electricity.
Quantitative Assessment of the Impacts of Climate Change and Human Activity on the Net Primary Productivity of Subtropical Vegetation: The Case of Shaoguan, Guangdong, China
Authors: Zhao Chenyao , Chen Shuisen , Jia Kai , Li Dan , Qin Boxiong , Sun Yishan , Zhang Hao
Published: December 2023

Vegetation net primary productivity (NPP) is critical to maintaining and enhancing the carbon sink of vegetation. Shaoguan is a characteristic forest city in the subtropical region of South China and an ecological barrier in the Guangdong–Hong Kong–Macau Greater Bay Area (GBA), playing an instrumental role in protecting water resources, purifying air, and maintaining ecological balance. However, studies that quantify subtropical vegetation NPP dynamics in Shaoguan under the influence of climate and human drivers are still incomplete. In this research, vegetation NPP at 30 m resolution was estimated from 2001 to 2020 using the enhanced CASA model based on the GF-SG algorithm in Shaoguan. The RESTREND method was then utilized to quantify climatic and human effects on NPP. The results indicated that the vegetation NPP in Shaoguan increased rapidly (4.09 g C/m2/yr, p < 0.001) over the past 20 years. Climate and human drivers contributed 0.948 g C/m2/yr and 3.137 g C/m2/yr to vegetation NPP, respectively. Human activity plays a major role in vegetation restoration through ecological projects, whereas vegetation deterioration is primarily attributable to the combined action of climate change and human activity, such as urban expansion, deforestation, and meteorological disasters. The results emphasize the importance of ecological projects for the restoration of vegetated ecosystems and ecological construction in Shaoguan.
Arbuscular Mycorrhizal Fungi Adjusts Root Architecture to Promote Leaf Nitrogen Accumulation and Reduce Leaf Carbon–Nitrogen Ratio of Mulberry Seedlings
Authors: Zhang Huirong , Cheng Hongguang , Twagirayezu Gratien , Zhang Fang , Shi Yanjin , Luo Chaobin , Yan Fan , Wang Zhenhong , Xing Dan
Published: December 2023

In the initial stages of restoring rocky desertification, the proliferation of nutrients strongly influences plant survival. The carbon–nitrogen doctrine in plants argues that a lower leaf carbon–nitrogen (C:N) ratio enhances the growth of plant nutrients. However, the mechanisms by which inoculation with arbuscular mycorrhizal fungi (AMF) can influence plants during the restoration of rocky desertification are not thoroughly understood. This study used mulberry as a suitable example of a mycorrhizal plant in desertification areas to examine changes in growth, leaf carbon, nitrogen accumulation, and the carbon–nitrogen ratio post inoculation using AMF. The correlation between leaf carbon–nitrogen ratio and root morphology following AMF inoculation was also examined. The results demonstrated that inoculating mulberry with the dominant strains Funneliformis mosseae (Fm) and Rhizophagus intraradices (Ri) not only enhanced above-ground growth and improved carbon and nitrogen nutrient absorption but also had a more pronounced effect on leaf nitrogen accumulation than on carbon accumulation, resulting in a potential decrease in the leaf C:N ratio by 42.13%. It also significantly improved root morphology by exponentially increasing the number of connections and crossings by 120.5% and 109.8%, respectively. Further analysis revealed a negative correlation between leaf C:N ratio and root morphology, as well as between root length and the number of connections. Plants with more developed root systems exhibited greater competitiveness for nitrogen, resulting in a lower leaf C:N ratio. This study suggests that the inoculation of AMF could enhance leaf nitrogen accumulation and reduce the leaf C:N ratio by expanding the spatial absorption range of the root through positive changes in root morphology, thereby promoting plant nutrient growth. This study forms a fundamental scientific basis for the successful management of desertification.
Effects of Moisture Content and Silage Starter on the Fermentation Quality and In Vitro Digestibility of Waxy Corn Processing Byproduct Silage
Authors: Yi Qixuan , Yu Meng , Wang Peng , Du Jiarui , Zhao Tianyue , Jin Yitong , Tang Hongyu , Yuan Bao
Published: December 2023

We investigated the effects of the moisture content and silage starter preparation on the fermentation quality, nutritional value, and in vitro digestibility of waxy corn processing byproducts and rice bran (WRB) mixed silage and waxy corn processing byproducts and rice polished powder (WRPP) mixed silage. Two mixed silages with 55%, 60%, and 65% moisture content (MC) were set up without any additives (control) or with former Lactobacillus (L), and opened on the 60th day after storage the fermentation quality, nutritive value, and in vitro digestibility of the silages in each treatment. The optimal formulation of high-quality waxy corn processing byproduct (WCPP) silage was screened to provide a reference and theoretical basis for the further development and utilisation of WCPPs. The results showed that the proportions of ammonia nitrogen to total nitrogen (AN/TN) and acid detergent lignin (ADL) significantly decreased with a decreasing MC, whereas the levels of lactic acid (LA), crude protein (CP), dry matter (DM), and in vitro crude protein digestibility (IVCPD) significantly increased (p < 0.05) for both mixed silages with L. After treatment with 60% MC, the content of neutral detergent fibre (NDF) was significantly lower, and the CP content was significantly greater in the WRB mixed silage treated with L (p < 0.05). With 55% MC, the addition of L not only reduced the pH and AN/TN ratio of the two mixed silages but also significantly improved their in vitro digestibility (p < 0.05). Studies have shown that reducing the MC of silage raw materials and adding L allows for the preparation of high-quality silage.
Federated Learning for Intrusion Detection Systems in Internet of Vehicles: A General Taxonomy, Applications, and Future Directions
Authors: Alsamiri Jadil , Alsubhi Khalid
Published: December 2023

In recent years, the Internet of Vehicles (IoV) has garnered significant attention from researchers and automotive industry professionals due to its expanding range of applications and services aimed at enhancing road safety and driver/passenger comfort. However, the massive amount of data spread across this network makes securing it challenging. The IoV network generates, collects, and processes vast amounts of valuable and sensitive data that intruders can manipulate. An intrusion detection system (IDS) is the most typical method to protect such networks. An IDS monitors activity on the road to detect any sign of a security threat and generates an alert if a security anomaly is detected. Applying machine learning methods to large datasets helps detect anomalies, which can be utilized to discover potential intrusions. However, traditional centralized learning algorithms require gathering data from end devices and centralizing it for training on a single device. Vehicle makers and owners may not readily share the sensitive data necessary for training the models. Granting a single device access to enormous volumes of personal information raises significant privacy concerns, as any system-related problems could result in massive data leaks. To alleviate these problems, more secure options, such as Federated Learning (FL), must be explored. A decentralized machine learning technique, FL allows model training on client devices while maintaining user data privacy. Although FL for IDS has made significant progress, to our knowledge, there has been no comprehensive survey specifically dedicated to exploring the applications of FL for IDS in the IoV environment, similar to successful systems research in deep learning. To address this gap, we undertake a well-organized literature review on IDSs based on FL in an IoV environment. We introduce a general taxonomy to describe the FL systems to ensure a coherent structure and guide future research. Additionally, we identify the relevant state of the art in FL-based intrusion detection within the IoV domain, covering the years from FL’s inception in 2016 through 2023. Finally, we identify challenges and future research directions based on the existing literature.
Fu Brick Tea as a Staple Food Supplement Attenuates High Fat Diet Induced Obesity in Mice
Authors: Wu Daying , Zhao Haoan , Guo Lei , Liu Xiukun , Liang Yan , Liu Qian , Cao Wei , Chen Xueyan , Gao Xin
Published: December 2023

Fu brick tea (FBT), a product of microbial fermentation from primary dark tea, also known as raw material tea (RMT), has been extensively studied for its functional properties. However, its potential as a staple food supplement for weight loss remains poorly understood. This study compared the weight loss effects of orlistat, traditional plain noodles (NN), and noodles supplemented with varying amounts of RMT (RMTN) and FBT (FBTN), with the aim to elucidate their lipid-reducing effects and underlying mechanisms. Experimental trials on high fat diet fed mice revealed significant weight loss, lipid-lowering, and hypoglycemic effects upon supplementation with orlistat, RMTN, and FBTN. Moreover, supplementation with orlistat, RMTN, and FBTN effectively restored serum and liver-related index levels, mitigating high-fat diet-induced dyslipidemia. Additionally, these supplements ameliorated liver and kidney damage by inhibiting oxidative stress and inflammatory responses. Furthermore, orlistat, RMTN, and FBTN exert their anti-obesity effects primarily by modulating genes associated with lipid metabolism and inflammatory responses and through regulation of the composition and structure of the gut microbiota. Importantly, FBTN demonstrated a significantly stronger lipid-lowering effect compared to RMTN, particularly at higher tea addition ratios. In contrast, NN supplementation exhibited minimal to no weight loss effects. Based on these findings, it could be inferred that FBT holds promise as a staple food supplement to ameliorate high-fat diet-induced obesity and its associated health conditions.
The Euphrates Poplar Responses to Abiotic Stress and Its Unique Traits in Dry Regions of China (Xinjiang and Inner Mongolia): What Should We Know?
Authors: Ndayambaza Boniface , Si Jianhua , Deng Yanfang , Jia Bing , He Xiaohui , Zhou Dongmeng , Wang Chunlin , Zhu Xinglin , Liu Zijin , Qin Jie , Wang Boyang , Bai Xue
Published: December 2023

At the moment, drought, salinity, and low-temperature stress are ubiquitous environmental issues. In arid regions including Xinjiang and Inner Mongolia and other areas worldwide, the area of tree plantations appears to be rising, triggering tree growth. Water is a vital resource in the agricultural systems of countries impacted by aridity and salinity. Worldwide efforts to reduce quantitative yield losses on Populus euphratica by adapting tree plant production to unfavorable environmental conditions have been made in response to the responsiveness of the increasing control of water stress. Although there has been much advancement in identifying the genes that resist abiotic stresses, little is known about how plants such as P. euphratica deal with numerous abiotic stresses. P. euphratica is a varied riparian plant that can tolerate drought, salinity, low temperatures, and climate change, and has a variety of water stress adaptability abilities. To conduct this review, we gathered all available information throughout the Web of Science, the Chinese National Knowledge Infrastructure, and the National Center for Biotechnology Information on the impact of abiotic stress on the molecular mechanism and evolution of gene families at the transcription level. The data demonstrated that P. euphratica might gradually adapt its stomatal aperture, photosynthesis, antioxidant activities, xylem architecture, and hydraulic conductivity to endure extreme drought and salt stress. Our analyses will give readers an understanding of how to manage a gene family in desert trees and the influence of abiotic stresses on the productivity of tree plants. They will also give readers the knowledge necessary to improve biotechnology-based tree plant stress tolerance for sustaining yield and quality trees in China’s arid regions.
Long Non-Coding RNAs: Discoveries, Mechanisms, and Research Strategies in Seeds
Authors: Li Xiumei , Liu Qinjian , Liu Jun
Published: December 2023

Seeds provide nutrients for the embryo and allow for dormancy in stressed environments to better adapt the plant to its environment. In addition, seeds are an essential source of food for human survival and are the basis for the formation of food production and quality. Therefore, the research on the genetic mechanism of seed development and germination will provide a theoretical basis and technical support for the improvement of crop yield and quality. Recent studies have shown that long non-coding RNAs (lncRNAs) occupy a pivotal position in seed development and germination. In this review, we describe the key processes in seed biology and examine discoveries and insights made in seed lncRNA, with emphasis on lncRNAs that regulate seed biology through multiple mechanisms. Given that thousands of lncRNAs are present in the seed transcriptome, characterization has lagged far behind identification. We provide an overview of research strategies and approaches including some exciting new techniques that may uncover the function of lncRNAs in seed. Finally, we discuss the challenges facing the field and the opening questions. All in all, we hope to provide a clear perspective on discoveries of seed lncRNA by linking discoveries, mechanisms, and technologies.
Assessment of Candidate Reference Genes for Gene Expression Studies Using RT-qPCR in Colletotrichum fructicola from Litchi
Authors: Dong Dingming , Huang Rong , Hu Yuzhuan , Yang Xinyan , Xu Dagao , Jiang Zide
Published: December 2023

Litchi (Litchi chinensis Sonn.) is a tropical fruit originating from southern China that is currently cultivated in subtropical and tropical regions worldwide. Litchi anthracnose, caused by Colletotrichum fructicola, a dominant species of Colletotrichum spp., is an important disease of litchi that damages the fruits in fields and in post-harvest storage. Real-time quantitative PCR (RT-qPCR) is a common technique with which to detect the expression of and function of target genes quickly and precisely, and stable reference genes are crucial. However, there is no comprehensive information on suitable reference genes of C. fructicola present. Here, we designed eight candidate genes (GAPDH, α-tubulin, 18S, β-tubulin, EF1a, TATA, RPS5, and EF3) using RefFinder software (programs: geNorm, ΔCt, BestKeeper, and NormFinder) to investigate their reliability in the detection of C. fructicola under five different treatments (fungal development stage, temperature, UV, culture medium, and fungicide). The results showed the optimal reference genes under different conditions: EF1a and α-tubulin for developmental stage; α-tubulin and β-tubulin for temperature; α-tubulin and RPS5 for UV treatment; RPS5 and α-tubulin for culture medium; α-tubulin, GAPDH, and TATA for fungicide treatments. The corresponding expression patterns of HSP70 (Heat shock protein 70) were significantly different when the most and the least stable reference genes were selected when treated under different conditions. Our study provides the first detailed list of optimal reference genes for the analysis of gene expression in C. fructicola via RT-qPCR, which should be useful for future functional studies of target genes in C. fructicola.
Microbiota-Induced Epigenetic Alterations in Depressive Disorders Are Targets for Nutritional and Probiotic Therapies
Authors: Nohesara Shabnam , Abdolmaleky Hamid Mostafavi , Zhou Jin-Rong , Thiagalingam Sam
Published: December 2023

Major depressive disorder (MDD) is a complex disorder and a leading cause of disability in 280 million people worldwide. Many environmental factors, such as microbes, drugs, and diet, are involved in the pathogenesis of depressive disorders. However, the underlying mechanisms of depression are complex and include the interaction of genetics with epigenetics and the host immune system. Modifications of the gut microbiome and its metabolites influence stress-related responses and social behavior in patients with depressive disorders by modulating the maturation of immune cells and neurogenesis in the brain mediated by epigenetic modifications. Here, we discuss the potential roles of a leaky gut in the development of depressive disorders via changes in gut microbiota-derived metabolites with epigenetic effects. Next, we will deliberate how altering the gut microbiome composition contributes to the development of depressive disorders via epigenetic alterations. In particular, we focus on how microbiota-derived metabolites such as butyrate as an epigenetic modifier, probiotics, maternal diet, polyphenols, drugs (e.g., antipsychotics, antidepressants, and antibiotics), and fecal microbiota transplantation could positively alleviate depressive-like behaviors by modulating the epigenetic landscape. Finally, we will discuss challenges associated with recent therapeutic approaches for depressive disorders via microbiome-related epigenetic shifts, as well as opportunities to tackle such problems.
Compilation of Genotype and Phenotype Data in GCDH-LOVD for Variant Classification and Further Application
Authors: Tibelius Alexandra , Evers Christina , Oeser Sabrina , Rinke Isabelle , Jauch Anna , Hinderhofer Katrin
Published: December 2023

Glutaric aciduria type 1 (GA-1) is a rare but treatable autosomal-recessive neurometabolic disorder of lysin metabolism caused by biallelic pathogenic variants in glutaryl-CoA dehydrogenase gene (GCDH) that lead to deficiency of GCDH protein. Without treatment, this enzyme defect causes a neurological phenotype characterized by movement disorder and cognitive impairment. Based on a comprehensive literature search, we established a large dataset of GCDH variants using the Leiden Open Variation Database (LOVD) to summarize the known genotypes and the clinical and biochemical phenotypes associated with GA-1. With these data, we developed a GCDH-specific variation classification framework based on American College of Medical Genetics and Genomics and the Association for Molecular Pathology guidelines. We used this framework to reclassify published variants and to describe their geographic distribution, both of which have practical implications for the molecular genetic diagnosis of GA-1. The freely available GCDH-specific LOVD dataset provides a basis for diagnostic laboratories and researchers to further optimize their knowledge and molecular diagnosis of this rare disease.
Evidence for a Negative Loss Spiral between Co-Worker Social Support and Burnout: Can Psychosocial Safety Climate Break the Cycle?
Authors: McLinton Sarven S. , Jamieson Stephanie D. , Tuckey Michelle R. , Dollard Maureen F. , Owen Mikaela S.
Published: December 2023

Previous research suggests that co-worker social support predicts burnout, but this relationship may be far more complex, with the potential for a reciprocal cycle of loss. Leading research on loss spirals has explicitly called for more research on interindividual factors such as social support and, by extension, how interventions that operate on these interpersonal resources could play a role in primary and secondary prevention (i.e., intervening in cycles of loss). In this study, we explore the reciprocal relationship between burnout and co-worker social support, with psychosocial safety climate (PSC) as an upstream predictor and moderator of this relationship. Using hierarchical linear modelling (N = 380 frontline healthcare workers, nested within N = 63 teams) on longitudinal data, we found a reciprocal relationship between burnout and co-worker support, which was both triggered and moderated by PSC. These findings provide initial evidence for a social support–burnout loss spiral, wherein individuals with poor co-worker support are more likely to become burnt-out, and in this depleted state they are subsequently less likely to reach out for those social supports when available, which would, in turn, lead to further burnout. This social support–burnout loss spiral is exacerbated when working in a low-PSC context, as the environment does not send positive safety signals about resource scarcity and replenishment. Therefore, PSC may be a potential target for intervention both in primary prevention (i.e., stopping the loss spiral in the first instance) and in secondary intervention, as high PSC signals to workers already in the burnout–support loss cycle when it is safe to reinvest resources or engage in recovery behavior.