The study aimed to investigate the effects of colonization with two arbuscular mycorrhizal (AM) fungi, Funneliformis mosseae , Diversispora versiformis , alone and in combination on the growth and nutrient acquisition of NaCl-stressed Chrysanthemum morifolium (Hangbaiju) plants in the greenhouse experiment. Mycorrhizal and non-mycorrhizal Hangbaiju plants were grown under different salinity levels imposed by 0, 50 and 200 mM NaCl for five months, following 6 weeks of non-saline pre-treatment. The results showed that root length, shoot and root dry weight, total dry weight, shoot and root N concentration were higher in mycorrhizal than in non-mycorrhizal plants under moderate saline conditions especially with D. versiformis colonization. As salinity increased, the mycorrhizal colonization, the mycorrhizal dependence (MD) decreased. Enhancement of tissue N acquisition is probably the main mechanism underlying salt tolerance in AM plants. It is suggested that the symbiotic associations between D. versiformis fungus and C. morifolium plants may be taken as a biotechnological practice in culture.

One new cassane diterpene possessing an unusual N bridge between C-19 and C-20 named caesalsappanin R (1), as well as another new diterpene caesalsappanin S (2), were isolated from the seeds of Caesalpinia sappan with methanol extract. Their structures were determined by spectroscopic analysis and examined alongside existing data from prior studies. Their biological activities were profiled by their antiplasmodial activity.

Let R be a commutative ring with identity and S be a multiplicatively closed subset of R. The purpose of this paper is to introduce the concept of weakly S-primary ideals as a new generalization of weakly primary ideals. An ideal I of R disjoint with S is called a weakly S-primary ideal if there exists s∈S such that whenever 0≠ab∈I for a,b∈R, then sa∈√I or sb∈I. The relationships among S-prime, S-primary, weakly S-primary and S-n-ideals are investigated. For an element r in any general ZPI-ring, the (weakly) S_{r}-primary ideals are charctarized where S={1,r,r²,⋯}. Several properties, characterizations and examples concerning weakly S-primary ideals are presented. The stability of this new concept with respect to various ring-theoretic constructions such as the trivial ring extension and the amalgamation of rings along an ideal are studied. Furthermore, weakly S-decomposable ideals and S-weakly Laskerian rings which are generalizations of S-decomposable ideals and S-Laskerian rings are introduced.

Machinery degradation assessment can offer meaningful prognosis and health management in-formation. Although numerous machine prediction models based on artificial intelligence have emerged in recent years, they still face a series of challenges: (1) Many models continue to rely on manual feature extraction. (2) Deep learning models still struggle with long sequence prediction tasks. (3) Health indicators are inefficient for remaining useful life (RUL) prediction with cross-operational environments when dealing with high-dimensional datasets as inputs. This research proposes a health indicator construction methodology based on a transformer self-attention transfer network (TSTN). This methodology can directly deal with the high-dimensional raw dataset and keep all the information without missing when the signals are taken as the input of the diagnosis and prognosis model. First, we design an encoder with a long-term and short-term self-attention mechanism to capture crucial time-varying information from a high-dimensional dataset. Second, we propose an estimator that can map the embedding from the encoder output to the estimated degradation trends. Then, we present a domain dis-criminator to extract invariant features from different machine operating conditions. The case studies with the FEMTO-ST bearing dataset and the Monte Carlo method for RUL prediction during the degradation process are conducted. The experiment results fully exhibited the signif-icant advantages of the proposed method compared to other state-of-the-art techniques.

The three-dimensional morphology of frictional sub-surfaces holds significant importance for studying tribological issues. However, the uniformity of horizontal datum in 3D scanning is limited for curved surfaces, resulting in the inability to obtain accurate contour characterization parameters from the scanning results. This study aims to address this issue by constructing regular surface equations and normalizing the 3D profiler scanning results. By fitting the data, a "plane" surface representative of the surface features is obtained, and the paper demonstrates this approach on the surface morphology of different worn parts in the frictional area of spherical bearings located in the specific environment of the Three Gorges gate. The results indicate that the obtained "plane" effectively reconstructs the three-dimensional morphology map of the regular surface. Moreover, this reconstructed plane not only clearly illustrates the surface characteristics but also provides the foundation for analyzing the wear mechanism.

With advances in the development of autonomous vehicles (AVs), more attention has been paid to the effects caused by adverse weather conditions on them. It is well known that the performance of self-driving vehicles is reduced when they are exposed to stressors that impair visibility or generate water or snow accumulation on sensor surfaces. This paper proposes a model to quantify weather precipitation, such as rain and snow, perceived by moving vehicles based on outdoor data. The modelling covers a wide range of parameters, such as varying wind direction and realistic particle size distributions. The model allows the calculation of precipitation intensity on inclined surfaces of different orientations and on a circular driving path. The modelling results were partially validated against direct measurements carried out by a test vehicle. The model outputs showed strong correlation with the experimental data for both rain and snow. Mitigation strategies for heavy precipitation on vehicles can be developed and correlations between precipitation rate and accumulation level can be traced using the presented analytical model. Dimensional Analysis of the problem has highlighted the critical parameters that can help the design of future experiments. The obtained results highlight the importance of the angle of the sensing surface on the perceived precipitation level. The proposed model is used to analyze optimal orientations for minimization of the precipitation flux, which can help to determine the positioning of sensors on the surface of autonomous vehicles.

In recent years, with the popularity of smart mobile devices, the interaction between devices and users, especially in the form of voice interaction, has become increasingly important. If smart devices can understand more users' emotional states through voice data, more customized services can be provided for users. This paper proposes a novel machine learning model for speech emotion recognition, which combines convolutional neural networks (CNN), long short-term memory neural networks (LSTM), and deep neural networks (DNN), called CLDNN. To make the designed system can recognize the audio signal closer to the human auditory system does, this article uses the Mel frequency cepstral coefficients (MFCCs) of audio data as the input of the machine learning model. First, the MFCCs of the voice signal is extracted as the input of the model, and the feature values of the data are calculated using several local feature learning blocks (LFLB) composed of one-dimensional CNN. Because the audio signals are time-series data, the feature values obtained from LFLBs then input into LSTM layer to enhance the learning on time-series level. Finally, fully connected layers are used for classification and prediction. Three databases RAVDESS, EMO-DB and IEMOCAP are used for the experiments in this paper. The experimental results show that the proposed method can improve the accuracy compared to other related researches in speech emotion recognition.

The advent of graphene opens up the research into two-dimensional (2D) material, which is considered as a revolutionary material in the future. Due to its unique geometric structure, graphene exhibits a series of exotic physical and chemical properties. Besides, single-element-based 2D materials (Xenes) have garnered tremendous interest. At present, 16 kinds of Xenes (silicene, borophene, germanene, phosphorene, tellurene, etc.) have been explored, mainly distributed in the third, fourth, fifth and sixth main groups. The current methods to prepare monolayer or few-layer 2D materials include epitaxy growth, mechanical exfoliation, and liquid phase exfoliation. Although two Xenes (aluminene and indiene) have not been synthesized due to the limitations of synthetic methods or stability of Xenes, other Xenes have been successfully realized by elaborately artificial design and synthesis. Focusing on elemental 2D materials, this review mainly summarizes the recently reported work about tuning the electronic, optical, mechanical, or chemical properties of Xenes via surface modifications achieved by controllable approaches (doping, adsorption, strain, intercalation, phase transition, etc.) to broaden the applications in various fields, including spintronics, electronics, optoelectronics, superconducting, photovoltaics, sensors, catalysis, and biomedicines. These advances in surface modification of Xenes have laid a theoretical and experimental foundation for the development of 2D materials and their practical applications in diverse fields.

This paper introduces a multi-class hand gesture recognition model developed to identify a set of defined hand gesture sequences in two-dimensional RGB video recordings. The work presents an action detection classifier that looks at both appearance and spatiotemporal parameters of consecutive frames. The classifier utilizes a convolutional-based network combined with a long-short-term memory unit. To leverage the need for a large-scale dataset, the model uses an available dataset to then adopt a technique known as transfer learning to fine-tune the model on the hand gestures of relevance. Validation curves performed over a batch size of 64 indicate an accuracy of 93.95% (± 0.37) with a mean Jaccard index of 0.812 (± 0.105) for 22 participants. The presented model illustrates the possibility of training a model with a small set of data (113,410 fully labelled frames). The proposed pipeline embraces a small-sized architecture that could facilitate its adoption.

The paper proposes a novel methodology for the stabilization of shallow foundations, with a simplified model combined with 3D Electrical resistivity tomography (ERT-3D) and conso- lidation injections. To determine its usefulness, the method has been applied in a case located in Estepona (southern Spain). The chosen tomography model is the dipole-dipole configuration, with an optimized distance between electrodes of 0.80 m for a better visualization of the foundation subsoil; with this parameterization, a total of 72 electrodes were installed in the analyzed case. In this work, the depth of the anomaly in the building's supporting subsoil was detected ranging from 2.00 m to 3.90 m deep. The study also delineates areas of high resistivity variations (50-1,000 Ω m) in the middle and eastern end of the field. These data have been validated and corroborated with a field campaign. The results of the ERT-3D monitoring are presented, once the investment data has been processed with the RES3DINV software, from the beginning to the end of the stabilization intervention. The novelty occurs with the interaction between the tomography and the foundation consolidation injections, until the final stabilization; very useful methodology in case of emergency consolidation, where there is a need to minimize damage to the building. Thus, people using this combined system; will be able to practically solve the initial anomalies of the subsoil that caused the damages, in a non-invasive way, considerably lowering the value of the resistivities.

Black poplar (Populus nigra L.) was thermally modified in nitrogen atmosphere. Treatment in nitrogen atmosphere can improve the dimensional stability of black poplar. The effects of the modification process on poplar wood were evaluated for temperatures: 160 °C, 190 °C, and 220 °C applied for 2 h; and 160 °C and 190 °C for 6 h. The percentual impact of temperature and time of modification on the properties of modified wood was analysed. The study permitted to identify correlations between the chemical composition and selected physical properties of thermally modified poplar wood. The dimensional stability of poplar wood improves after thermal modification in nitrogen. The higher the temperature of modification, the lower the equilibrium moisture content (EMC) of black poplar. At the temperature of 220 °C, EMC was two times lower than the EMC of non-modified black poplar. It is also possible to reduce the dimensional changes of wood two-fold (at the modification temperature of 220 °C), both in radial and tangential directions, independently of the acclimatisation conditions (from 34% to 98% RH). Similar correlations have been found for wood that has been soaked in water. Higher modification temperatures and longer processing times contributed to a lower swelling anisotropy (SA).

This Letter revisits the instability of jet produced by shaped charge. Scaling laws for shaped charge jet are derived by dimensional analysis. It shows that the scaling laws are universal when cross-sectional shrinkage rate is not included in the formulation.

There exist numerous high-dimensional problems in the real world which cannot be solved through the common traditional methods. The metaheuristic algorithms have been developed as successful techniques for solving a variety of complex and difficult optimization problems. Notwithstanding their advantages, these algorithms may turn out to have weak points such as lower population diversity and lower convergence rate when facing complex high-dimensional problems. An appropriate approach to solve such problems is to apply multi-agent systems along with the metaheuristic algorithms. The present paper proposes a new approach based on the multi-agent systems and the concept of agent, which is named Multi-Agent Metaheuristic (MAMH) method. In the proposed approach, several basic and powerful metaheuristic algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Firefly Algorithm (FA), Bat Algorithm (BA), Flower Pollination Algorithm (FPA), Gray Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), Crow Search Algorithm (CSA), Farmland Fertility Algorithm (FFA), are considered as separate agents each of which sought to achieve its own goals while competing and cooperating with others to achieve the common goals. In overall, the proposed method was tested on 32 complex benchmark functions, the results of which indicated effectiveness and powerfulness of the proposed method for solving the high-dimensional optimization problems. In addition, in this paper, the binary version of the proposed approach, called Binary MAMH (BMAMH), was executed on the spam email dataset. According to the results, the proposed method exhibited a higher precision in detection of the spam emails compared to other metaheuristic algorithms and methods.

ARBTools is a Python library containing a Lekien-Marsden type tricubic spline method for interpolating three-dimensional scalar or vector fields presented as a set of discrete data points on a regular cuboid grid. ARBTools was developed for simulations of magnetic molecular traps, in which the magnitude, gradient and vector components of a magnetic field are required. Numerical integrators for solving particle trajectories are included, but the core interpolator can be used for any scalar or vector field. The only additional system requirements are NumPy.

In the process of sustainable development in the future, human society faces problems such as severe population load, economic transition, and lack of educational measures. One of the root causes of these problems is the shortage of innovative talents. Therefore, how to cultivate learners with multi-disciplinary integration and innovation ability is the key point that should be paid attention to in promoting the concept of quality education and coping with the future sustainable development process. This paper uses questionnaire survey method and literature analysis method to analyze the development of many educational institutions with STEAM concept as the core in China since 2017. It is found that the existing STEAM educational institutions generally have the following problems: the lack of team composition、difficulty in independent research and development、single course content and insufficient validation of course effectiveness. In order to more effectively promote the sustainable development of China's future course, STEAM education institutions should focus on strengthening the following development strategy: gradient team building, continuous independent research and development, cutting-edge projects curriculum transformation mechanism and multi-angle course effectiveness verification.

Three-dimensional (3D) imaging has attracted more and more interests because of its widespread applications, especially in information and life science. These techniques can be broadly divided into two types: ray-based and wavefront-based 3D imaging. Issues such as imaging quality and system complexity of these techniques limit the applications significantly, and therefore many investigations have focused on 3D imaging from depth measurements. This paper presents an overview of 3D imaging from depth measurements, and provides a summary of the connection between these the ray-based and wavefront-based 3D imaging techniques.

In this work, we report the fabrication of the new heterojunction of two 2D hybrid layered semiconductors, ZnO(stearic acid)/V₂O₅(hexadecylamine), and its behavior in the degradation of aqueous methylene blue under visible light irradiation. The optimal photocatalyst efficiency, reached at a ZnO(stearic acid)/ V₂O₅(hexadecylamine) ratio of 1:0.25, results to be about six times higher than that of pristine zinc oxide. Reusability test shows that after three photocatalysis cycles no significant changes in neither the dye degradation efficiency loss nor photocatalyst structure occur. Visible light photocatalytic performance observed indicates there is synergetic effect between both 2D nanocomposites used in the heterojunction. The visible light absorption enhancement promoted by the narrower bandgap V₂O₅ based components; an increased photo generated charge separation favored by extensive interface area; and abundance of hydrophobic sites for dye adsorption appear as probable causes of the improved photocatalytic efficiency in this hybrid semiconductors heterojunction. Estimated band-edge positions for both conduction and valence band of semiconductors together with experiments using specific radical scavengers allow a plausible photodegradation mechanism.

The plant Allium hookeri, belonging to the Allium genus, has a history of being used both as a common food ingredient and in herbal medicine. It has recently been reported to have anti-oxidant and anti-inflammatory effects. A. hookeri has been also shown to exhibit neuroprotective and anti-neuroinflammatory activities, but the active compounds responsible for these effects have not been identified in previous studies. This study aimed to perform a metabolite profiling using an HRESI-qTOF MS/MS-based molecular networking approach and identify the active compounds from A. hookeri that target senescent cell-associated secretory phenotype (SASP) inhibitory effects, which contribute to neuroprotective activities. As a result, ten compounds, including one new flavonoid (2) and nine known compounds (1 and 3–10), were identified, and their biological activity was tested. The most potent compound was N-trans-feruloyltyramine (7), which inhibited SASP markers and contributed to the senomorphic activities of A. hookeri. These findings suggest that the phenolamides from A. hookeri could be a promising source of bioactive compounds for preventing senescence-associated diseases.

Fifty-two kinds of N’-phenylhydrazides were successfully designed and synthesized. Their anti-fungal activity in vitro against five strains of C. alb. was evaluated. All prepared compounds owned varying degrees of activity and their MIC80, TAI, and TSI values were calculated. The in-hibitory activities of 27/52 compounds against fluconazole-resistant fungi C. alb. 4395 and C. alb. 5272 were much higher than those of fluconazole. The MIC80 values of 14/52 compounds against fluconazole-resistant fungus C. alb. 5122 were less than 4 μg/mL, so it was the most sensitive fungus (TSIB = 12.0). A11 showed the highest inhibitory activity against C. alb. SC5314, 4395, and 5272. The antifungal activities of B14 and D5 against four strains of fluconazole-resistant fungi were higher than those of fluconazole. The TAI values of A11 (2.71), B14 (2.13), and D5 (2.25) are the highest. Further exploring the antifungal mechanism revealed that the fungus treated with compound A11 produced free radicals and reactive oxygen species, and their mycelium mor-phology was damaged. In conclusion, the hydrazide scaffold showed potential in the develop-ment of antifungal lead compounds. Among them, A11, B14, and D5 demonstrated particularly promising antifungal activity and hold potential as novel antifungal agents.

Aberrant glycosylation affects cancer progression and immune evasion. Approximately 15% of colorectal cancers (CRCs) demonstrate microsatellite instability (MSI) and display major differences in outcomes and therapeutic responses as compared to corresponding microsatellite stable (MSS) tumors. We compared the N-glycan profiles of stage II and IV MSI CRC tumors, further subdivided into BRAFV600E wild-type and mutated subgroups (n=10 in each subgroup), with each other and with those of paired non-neoplastic mucosal samples using mass spectrometry. Further, the N-glycans of BRAFV600E wild-type stage II MSI tumors were compared to corresponding MSS tumors (n=9). Multiple differences in N-glycan profiles were identified between MSI CRCs and control tissues, as well as between stage II MSI and MSS samples. MSI CRC tumors showed a lower relative abundance of high-mannose N-glycans than the control tissues or the MSS CRCs. Among MSI CRC subgroups, acidic N-glycans showed tumor stage and BRAF mutation status dependent variation. Especially large, sulfated/phosphorylated, and putative terminal N-acetylhexosamine containing acidic N-glycans differed between the MSI CRC subgroups, showing opposite changes in stage II and IV, when comparing BRAF mutated and wild-type tumors. Our results show that molecular subgroups of CRC have characteristic glycan profiles that may explain certain carcinogenic properties of MSI tumors.

The use of nitrogen (N) fertilizers can have detrimental effects on the environment due to nitrate leaching. This study aims to examine the impact of N fertilizer source and application timing on wheat yield and nitrate leaching in various soil textures. A randomized complete block design (RCBD) was employed to conduct the experiment. The treatments consisted of two N fertilizer sources: ammonium nitrate (AN) and urea (NN), applied at three different times throughout the year, with a control treatment. The three application timings were total application before sowing (T₁), total application in spring (T₂), and half the amount before sowing and the other half in spring (T₃). The experiment was conducted in three different soil textures (sandy loam, silty clay loam, and silty clay), with three replications over three growing seasons: 2018-19 (Y₁), 2019-20 (Y₂), and 2020-21 (Y₃). The results indicated significant effects of different soil textures on grain yield. Specifically, the silty clay loam soil differed significantly from the sandy loam and silty clay soils in terms of grain yield. The interaction effects between the N fertilizer source and application timing were also found to be significant for all soil textures (p<0.01). In sandy loam and silty clay soils, the grain yield increased when using the T₃ application timing compared to the silty clay loam soil. Notably, the silty clay loam soil with the T₂ application timing exhibited the highest grain yield, with a yield of 6863.6 kg ha^-1. Furthermore, the study revealed that N fertilizers and their application timing significantly influenced the protein content in the silty clay and sandy loam soils. The protein percentages were 10.76 and 10.93 for the silty clay and sandy loam soils, respectively, following the T₂ treatment. Additionally, ammonium nitrate (AN) demonstrated a noticeable effect on the percentage of grain protein compared to urea (NN). In conclusion, the application timing of N fertilizers had an impact on grain yield and protein content in different soil textures. Moreover, nitrate concentration increased throughout the experiment, with the highest soil nitrate concentration observed in both fertilizer treatments, particularly in the sandy loam soil.

High-quality rice (Oryza sativa L.) is increasingly widely planted in China with the improvement of people's living standards and the achievement of rice breeding efforts in recent years. However, the agronomic and physiological performances of high-quality indica rice (HQIR) under different nitrogen(N) application conditions in southern China are little known. Two-year consecutive field experiments were conducted with two HQIR and two ordinary-quality indica rice (OQIR) varieties under moderate and high N application rates, with yield and yield components, biomass, N up-take, and their related traits investigated. We found that grain yields of HQIR were slightly de-creased, but grain yields of OQIR were significantly increased by 6.60%-8.88% under high N rate compared with moderate N rate in both years. Thereby, OQIR produced 8.34%-11.87% and 22.00%-22.50% higher grain yield than HQIR under moderate and high N rates, respectively. The different responses of grain yield to N application rates were mainly due to decreased grain set-ting rate in HQIR and increased spikelets m-2 in OQIR under high N rate. Furthermore, high N rate significantly reduced pre-anthesis AE and improved grain-leaf area ratio, while did not in-crease post-anthesis DM compared with moderate N rate in HQIR, which might result in carbon metabolic deterioration and imbalance of source-sink relationship and subsequently lower supply of carbohydrate to panicle. Our results suggest that a moderate N rate (165 kg N ha-1) is beneficial for HQIR varieties to balance the maximum grain yield and high quality in southern China

Graphene-based nanomaterials have emerged as promising materials for a wide range of applications.. Therefore, in the last years carbon nanoparticles have attracted great attention due to their low toxicity, high biocompatibility and easy preparation. Recently, N-doped carbon nanoparticles have been shown to have improved antibacterial activity over the undoped nanomaterial, but it is difficult to find correlations between the structure of the nanoparticle and its antibacterial activity. With this purpose, here, we analyze the effect of both, the nanoparticle size and the surface chemical composition of four N-doped carbon nanoparticles on the growth of Escherichia coli bacteria. Our results were analyzed using a Ligand-Substrate model based on the Monod´s equation, which allows us to interpret the dependence of the nanoparticle-bacteria affinity with the nanomaterial structure.

Ketamine is a dissociative anesthetic and antidepressant with several biological targets. Among the many targets, ketamine, notably, has an antagonistic effect on molecular N-methyl-D-aspartate (NMDA) receptors and has been identified as a non-competitive inhibitor of these receptors. Although ketamine has a wide range of therapeutic uses in the clinical setting, it is often used recreationally due to its psychoactive and analgesic effects. Regardless of the indication, prenatal exposure to ketamine has been widely investigated. The misuse of this drug, particularly in pregnant women, has been a point of concern. The neurotoxic potential of ketamine positions it as a danger to a developing fetus. Furthermore, the ability of ketamine to cross the blood-placental barrier poses a threat to the health and maturation processes of the neonate. This paper reviewed published work that explores the mechanisms through which prenatal ketamine exposure can cause altered neurodevelopment, neurobehavior, and the physiological consequences that follow. By exploring investigations using multiple different subjects such as: rodents, non-human primates, and human subjects, this paper develops a full picture of the existing data to generate a strong foundation for improved and informed public health policies.

In recent years, the role of non-coding RNAs (ncRNAs) in regulating cell physiology has begun to be better understood. Recent discoveries in viral molecular biology have revealed that such cellular functions are disturbed during viral infections mainly due to host cell ncRNAs, cellular factors, and virus-derived ncRNAs. Apart from the interplay between those molecules, other interactions derive from the specific folding of RNA virus genomes. These fulfill canonical regulation functions such as replication, translation, and viral packaging. In some cases, folds serve as precursors of small viral RNAs whose biogenesis is not yet clearly understood. Since ncRNAs and RNA viral genomes modulate complex molecular and cellular processes in viral infections, a new taxonomy is being proposed here overarching three main categories, considering the current information about ncRNA interactions in some well-known viral infections. The first category shows examples of host ncRNAs associated with the trigger of the immune response under viral infections. The second category describes interactions between the virus and host ncRNAs. The last category shows how the shape of the RNA viral genome is essential in processing RNAs derived from viruses. Finally, we introduce evidence of how these three categories can also work as a framework in order to organize known interactions of ncRNAs and cellular factors under DENV infection. This new taxonomy of interactions provides a comprehensive framework for organizing the ncRNA regulatory roles in the context of viral interactions and an RNA world.

The photocatalysis process over N-doped TiO2 under visible light is examined for Pb(II) oxidation to form the less toxic and handleable PbO2 suggesting a new method for Pb(II) remediation. The doping TiO2 with N element was conducted by simple hydrothermal technique and using urea as the N source with various concentrations. The doped photocatalysts were characterized by DRUVS, XRD, FTIR and SEM-EDX instruments. Photocatalysis of Pb(II) through batch experiment was performed for evaluation of the doped TiO2 activity under visible light, with applying various fractions of N doped, photocatalyst weigh, irradiation time, and solution pH. The research results attributed that N doping has been successfully performed, that shifted TiO2 absorption into visible region, allowing it to be active under visible irradiation. The photocatalytic removal of Pb(II) under visible ligth over N-TiO2 showed more effective than that of over the un-doped photocatalyst. The removal of Pb(II) has notably taken place through oxidation, that may form PbO2. The highest photocatalytic oxidation of Pb(II) 15 mg/L in 25 mL of the solution could be reached by using TiO2 doped with 10%w of N, 15 mg of N-TiO2 weight, 30 minutes of time, and at pH 8, suggesting a feseable method for Pb(II) remediation.

A series of chiral complexes of the form Ir(NHC)2(aa)(H)(X) (NHC = N-heterocyclic carbene, aa = chelated amino acid, X = halide) was synthesized by oxidative addition of -amino acids to iridium(I) bis-NHC compounds and screened for asymmetric transfer hydrogenation of ketones. Following optimization of the reaction conditions, NHC, and amino acid ligands, high enantioselectivity was achieved when employing the Ir(IMe)2(l-Pro)(H)(I) catalyst (IMe = 1,3-dimethylimidazol-2-ylidene), which asymmetrically reduces a range of acetophenone derivatives in up to 95% enantiomeric excess.

The infections caused by Chikungunya virus (CHIKV), genus Alphavirus, have become a health problem around the world, due to this virus’s widespread occurrence and high morbidity rate and the absence of vaccines or antiviral drugs. In this study, we analyzed a competitive inhibitor of ornithine decarboxylase—an enzyme that is key in the biosynthesis of polyamines (PAs), N-ω-chloroacetyl-L-ornithine (NCAO), which is a possible inhibitor of CHIKV replication because intracellular polyamines participate in the in vitro transcription and translation of CHIKV. NCAO does not have any cytotoxic effect on C6/36 cells even at 1000 μM at 72 h post-exposure. However, in Vero cells, a cytotoxic effect was present above 380 μM at 48 h post-exposure, which was considered when determining the inhibitory effect on viral replication. In this work, we demonstrate that NCAO inhibits the replication of CHIKV in Vero and C6/36 cells in a dose-dependent manner, causing a decrease in the PFU/mL of at least 4 logarithms (p <0.01) in both cell lines. Viral yields were restored by the addition of exogenous polyamines, mainly putrescine. The HPLC analyses showed that NCAO decreases the content of intracellular PAs, even though mainly spermidines and spermines are present in infected cells. NCAO inhibits CHIKV replication by depleting the intracellular polyamines in Vero and C6/36 cells, suggesting that this compound is a possible antiviral for CHIKV infections.

Severe acute respiratory syndrome novel coronavirus 2 (SARS-CoV-2) has caused the global pandemic as COVID-19, which is the most notorious global public health crisis in the last 100 years. SARS-CoV-2 is composed of four structural proteins and several non-structured proteins. The multi-facet nucleocapsid (N) protein is the major component of structural proteins of CoVs, However, there are no dedicated genomic, sequences and structural analyses focusing on potential roles of N protein. Hence, there is an urgent requirement of a detailed study on N protein of SARS-CoV-2. Herein, we are presenting a comprehensive study on N protein from SARS-CoV-2. We have identified seven motifs conserved in the three major domains namely N-terminal domain, linker regions and the C-terminal domains. Out of seven motifs, six motifs are conserved across different members of coronaviridae, while motif4 is specific for SARS CoVs with potential amyloidogenic properties. Additionally, we report this protein has large patches of disordered regions flanking with these seven motifs. These motifs are hubs of epitopes with 67 experimentally verified epitopes from related viruses. We report the presence of three nuclear localization signals (NLS1-NLS3 mapped to 36-41, 256-26, and 363-389 residues, respectively) and two nuclear export signals (NES1-NLS2 from 151-161 and 217-230 residues, respectively) in the N protein of SARS-CoV-2. These deciphered two Q-patches as Q-patch1 and Q-patch2, mapped in the regions of 266-306, and 361-418 residues, which potentially help in the aggregation of the viral proteins along with ²¹⁹LALLLLDR²²⁶ patch. Additionally, we have identified 14 antiviral drugs potentially binding to seven motifs of N-proteins using docking-based drug discovery methods.

A hydrothermal pretreatment of the microalga Nannochloropsis gaditana at mild temperatures has been studied in order to reduce N and O content in the biocrude obtained by hydrothermal liquefaction (HTL). The work is focused on the evaluation of temperature, reactor loading and time (factors) to maximize the yield of the pretreated biomass and the heteroatom contents transferred from the microalga biomass to the aqueous phase (responses). The study followed the factorial design and response surface methodology. An equation for every response has been obtained, which leads to the accurate calculation of the operating conditions required to obtain a given value of these responses. Temperature and time are critical factors with a negative effect on the pretreated biomass yield, but a positive one on the N and O recovery in the aqueous phase. The slurry concentration has to be low to increase heteroatom recovery and high to maximize the pretreated microalga yields

Digital Elevation Models (DEMs) are widely used in geographic and environmental studies. In the current work, the fusion of multi-source DEMs is investigated to improve the overall accuracy of public domain DEMs. Multi-scale decomposition is an important analytical method in data fusion. Three multi-scale decomposition methods – the wavelet transform (WT), bidimensional empirical mode decomposition (BEMD) and nonlinear adaptive multi-scale decomposition (N-AMD) - are applied to the 1-arc-second Shuttle Radar Topography Mission Global digital elevation model (SRTM-1 DEM) and the Advanced Land Observing Satellite World 3D – 30 m digital surface model (AW3D30 DSM) in China. Of these, the WT and BEMD are popular image fusion methods. A new approach for DEM fusion is developed using N-AMD (which is originally invented to remove the cycle from sunspots). Subsequently, a window-based rule is proposed for the fusion of corresponding frequency components obtained by these methods. Quantitative results show that N-AMD is more suitable for multi-scale fusion of multi-source DEMs, taking the ice cloud and land elevation satellite (ICESat) global land surface altimetry data as a reference. The vertical accuracy of the fused DEM shows significant improvements of 29.6% and 19.3% in a mountainous region and 27.4% and 15.5% in a low-relief region, compared to the SRTM-1 and AW3D30 respectively. Furthermore, a slope position-based linear regression method is developed to calibrate the fused DEM for different slope position classes, by investigating the distribution of the fused DEM error with topography. The results indicate that the accuracy of the DEM calibrated by this method is improved by 16% and 13.6%, compared to the fused DEM in the mountainous region and low-relief region respectively, proving that it is a practical and simple means of further increasing the accuracy of the fused DEM.

The traditional Chinese drug Bombyx Batryticatus mori.L (BBm) which is also named the white stiff silkworm has been widely used in Chinese clinics for thousands of years. It is famous for its antispasmodic and blood circulation promoting effects. Cardiomyocyte hypertrophy, interstitial cell hyperplasia and myocardial fibrosis are closely related to the N-glycosylation of key proteins. To examine the alterations of N-glycosylation that occur in diabetic myocardium during the early stage of the disease and clarify the therapeutic effect of 1-DNJ extracted from BBm, we used the db/db mouse model and an approach based on hydrophilic chromatography solid-phase extraction integrated with an LC-MS/MS identification strategy to perform a site-specific N-glycosylation analysis of left ventricular cardiomyocyte proteins. AGEs, hydroxyproline, CTGF and other serum biochemical indicators were measured with ELISA. In addition, the α1,6-fucosylation of N-glycans was profiled with LCA lectin blots and FITC-labelled lectin affinity histochemistry. The results indicated that 1-DNJ administration obviously downregulated myocardium protein N-glycosylation in db/db mice. The expression levels of serum indicators and fibrosis-related cytokines were reduced significantly by 1-DNJ in a dose-dependent manner. The glycan α1,6-fucosylation level of the db/db mouse myocardium was elevated, and the intervention effect of 1-DNJ administration on N-glycan α1,6-fucosylation was significant. To verify this result, the well-known TGF-β/smad2/3 pathway was selected, and core α1,6-fucosylated TGFR-βⅡ was analysed semi-quantitatively with western blotting. The result supported the conclusions obtained from LCA lectin affinity histochemistry and lectin blot analysis. The expression level of FUT8 mRNA was also detected, and the results showed that 1-DNJ administration did not cause obvious inhibitory effects on FUT8 expression. Therefore, the mechanism of 1-DNJ to relieve the DCM-associated fibrosis can be concluded as the inhibition of N-GlcNAc formation and the reduction of substrate concentration.

We explore the possibility of using the external regions of galaxy clusters to measure their mass accretion rate (MAR). The main goal is to provide a method to observationally investigate the growth of structures on the nonlinear scales of galaxy clusters. We derive the MAR by using the mass profile beyond the splashback radius, evaluating the mass of a spherical shell and the time it takes to fall in. The infall velocity of the shell is extracted from N-body simulations. The average MAR returned by our prescription in the redshift range z=[0, 2] is within 20-40% of the average MAR derived from the merger trees of dark matter haloes in the reference N-body simulations. Our result suggests that the external regions of galaxy clusters can be used to measure the mean MAR of a sample of clusters.

Materials based on platinum metals with very good catalytic activity were tested in the reduction of p–nitrophenol (pNP) to p–aminophenol (pAP). The majority of presented catalytic materials are based on the adsorption of p–nitrophenol on the surface of the catalyst simultaneously with molecular hydrogen, coming from sodium borohydride in an aqueous medium, which reduces it. In the present paper, a catalytic material based on osmium dispersed in n–decanol or n–dodecanol is presented, which also works as an emulsion membrane, for the absorption of p–nitrophenol and molecular hydrogen at the n–alcohol aqueous solution interface. The hydrogenation of p–nitrophenol is carried out in a reaction and separation column in which the acid receiving phase emulsion is dispersed in the osmium nanodispersion, in n–alcohols. This emulsion circulates from the base of the column to its upper part in co-current or counter-current with the source phase consisting of p–nitrophenol and sodium borohydride. Experiments show that the circulation of counter-current phases is superior to that in co-current, and the emulsion based on n–decanol is more efficient than the one based on n–dodecanol. The increase in the pH difference between the source and receiving phases leads to the increase in the conversion of p–nitrophenol to p–aminophenol. The efficiency of separation of the reaction product in the receiving phase is lower than the conversion at the same operating time. The apparent catalytic rate constant (kapp) of the new catalytic material based on the emulsion membrane with nanodispersion of osmium nanoparticles (0.1×10−3 for n–dodecanol and 0.9×10−3 for n-decanol) is lower by an order of magnitude compared to those based on adsorption on catalysts from platinum metal group. The advantage of the tested membrane catalytic material is that it extracts p–aminophenol in the acid receiving phase. The paper proposes a mechanism of the studied reduction system.

Pedestrian Dead Reckoning (PDR) is a promising algorithm for indoor positioning. However, the accuracy of PDR degrades due to the accumulated error, especially in multi-floor buildings. This paper introduces a three-dimensional (3D) positioning method based on terrain feature matching to reduce the influence of accumulated error in multi-floor scene. The proposed method involves two steps: motion pattern recognition and position matching calibration. The motion pattern recognition aims to detect different motion states, i.e., taking the stairs or horizontal walking, from the streaming data. Then, stair entrances and corridor corners are matched with transition points of motion states and pedestrian turning points, respectively. After matching, calibration is performed to eliminate the accumulated errors. By carrying out experiments on a two-floor closed-loop path with a walking distance about 145 m, it is shown that this method can effectively reduce the accumulated error of PDR , achieving accurate 3D positioning . The average error is reduced from 6.60 m to 1.83 m.

As Artificial Intelligence (AI) technology, particularly Machine Learning algorithms, becomes increasingly ubiquitous, our abilities to understand and interpret AI and machine learning algorithms are becoming increasingly desirable. Visualization has been used as a common tool to view and understand complex machine learning processes. In this paper, we will focus on developing a general framework for the visualization of machine learning models as a scalar valued multi-dimensional function to help users understand how the models behave over different viewing spaces. We first give a formal definition of the visualization problem. Interpolation-based morphing and subspace sampling techniques are applied to generate various renderings through projections and cross-sections of the model space as 3D surfaces or heatmap images. This method will be applied to two real-world datasets and applications: the diagnosis of Alzheimer's Disease (AD) using a human brain networks dataset and a real-world benchmark dataset for predicting home credit default risks. The visualizations show that different machine learning algorithms can behave quite differently under different conditions.

Mechanical properties of three-dimensional (3D) printed resin can be improved by decreasing oxygen concentrations during post-curing, and nitrogen saturated post-curing has been applied for the purpose. This study aimed to evaluate and compare the color stability of 3D printed resin crowns post-cured in normal air and nitrogen saturated conditions. Crowns were fabricated with 3D printer and post-cured in normal air (control group; air) or nitrogen saturated condition (experimental group; nitrogen). The specimens in each group were subdivided into four subgroups, each exposed to different discoloration agents: distilled water, coffee, wine, and curry. Post-immersion color changes were measured using a digital spectrophotometer and analyzed through repeated measures ANOVA. Fourier Transform Infrared (FT-IR) spectroscopy evaluated the degree of conversion of resin over immersion times for both post-curing conditions. Comparing the effects of post-curing conditions, significant difference was found between control and experimental groups over immersion time in wine and curry subgroups. In FT-IR analysis, there was significant difference in degree of conversion between the air and nitrogen groups from 10 to 300 seconds. The findings suggest that nitrogen saturated post-curing can potentially enhances the conversion rate of 3D printed resin crowns, thereby improving their color stability.

Liquid argon technology is widely used by many previous and current neutrino experiments, and it is also promising for future large-scale neutrino experiments. When detecting neutrinos using liquid argon, many hadrons are involved, which can also interact with argon nuclei. In order to gain a better understanding of detection processes, and to simulate neutrino events, knowledge of hadron-argon cross sections is needed. This paper describes a new procedure, which improves upon the previous work with a multi-dimensional unfolding, to measure hadron-argon cross sections in a liquid argon time projection chamber. Through a simplified version of simulation, we demonstrate the validity of this procedure.

Prenatal diagnosis of clubfoot traditionally relied on two-dimensional ultrasonography. To enhance diagnosis and predict postnatal outcomes, we examined the parameters that differentiate pathological clubfoot using three-dimensional ultrasonography. In our retrospective study, we examined the findings of prenatal ultrasound and the postnatal outcomes of pregnancies with suspected congenital clubfoot between 2018 and 2021. Based on the three-dimensional perspective, we measured the angles of varus, equinus, calcaneopedal block and forefoot adduction and compared the sonographic variables between the postnatal treated and non-treated groups. We evaluated 31 pregnancies (47 feet) with suspected clubfoot using three-dimensional ultrasonography. After delivery, a total of 37 feet (78.7%) underwent treatment involving serial casting only or additional Achilles tenotomy. The treated group showed significantly greater hindfoot varus deviation (60.5° vs. 46.6°, p=0.026) and calcaneopedal block deviation (65.6° vs. 26.6°, p &lt;0.05) compared to the non-treated group. The calcaneopedal block had an area under the curve of 0.98 with a diagnostic threshold of 46.2 degrees (sensitivity of 97%, specificity of 90%, positive predictive value of 97%, and negative predictive value of 90%). During prenatal evaluation of clubfoot using three-dimensional ultrasonography, the calcaneopedal block deviation has the potential to predict postnatal treatment.

In this paper, we investigate a financial market in which asset prices evolve based on a multi-dimensional Brownian motion process and a multi-dimensional Poisson process with different credit and deposit rates We proceed to evaluate European options by establishing upper and lower hedging prices through a transition to a suitable auxiliary market. Additionally, we address the minimization of shortfall risk and no-arbitrage price bounds in incomplete markets within this framework.

In recent years, vision-centric perception has played a crucial role in autonomous driving tasks, encompassing functions such as 3D detection, map construction, and motion forecasting. However, the deployment of vision-centric approaches in practical scenarios is hindered by substantial latency, often deviating significantly from the outcomes achieved through offline training. This disparity arises from the fact that conventional benchmarks for autonomous driving perception predominantly conduct offline evaluations, thereby largely overlooking the latency concerns prevalent in real-world deployment. While a few benchmarks have been proposed to address this limitation by introducing effective evaluation methods for online perception, they do not adequately consider the intricacies introduced by the complexity of input information streams. To address this gap, we propose the Autonomous-driving Streaming I/O (ASIO) benchmark, aiming to assess the streaming inputs characteristics and online performance of vision-centric perception in autonomous driving. To facilitate this evaluation across diverse streaming inputs, we initially establish a dataset based on the CARLA Leaderboard. In alignment with real-world deployment considerations, we further develop evaluation metrics based on information complexity specifically tailored for streaming inputs and streaming performance. Experimental results indicate significant variations in model performance and ranking under different major camera deployments, underscoring the necessity of thoroughly accounting for the influences of model latency and streaming inputs characteristics during real-world deployment. To enhance streaming performance consistently across distinct streaming inputs features, we introduce a backbone switcher based on the identified streaming inputs characteristics. Experimental validation demonstrates its efficacy in perpetually improving streaming performance across varying streaming inputs features.

On the basis of the findings of this paper, the theories of quantum mechanics and general relativity can be expressed in a comprehensive theory. The events were surveyed length of the time, in the Euclidean six-dimensional space-time (R6=x1+x2+x3+t1+t2+t3). Previous studies have not studied the relationship between the origin of matter's inherent properties, fundamental constants, and quantum mechanics phenomenon with space-time geometry. This theory prediction the with certainty obtained probabilistic results of quantum mechanics. This prediction is on the basis of metric resulting from the Eccentricity of the Ellipse due to the object density, in the length of time. The cause and nature of dark matter and dark energy are the findings of this article.

Quantile regression model is widely used in variable relationship research of general size data, due to strong robustness and more comprehensive description of the response variables' characteristics. With the increase of data size and data dimension, there have been some studies on high-dimensional quantile regression under the classical statistical framework, including higher-efficient frequency perspective, which is however at cost of randomness quantification, or lower-efficient Bayesian method based on MCMC sampling. To overcome these problems, we propose the high-dimensional quantile regression with Spike-and-Slab Lasso penalty based on variational Bayesian (VBSSLQR), which can not only improve the computational efficiency but also measure the randomness via variational distributions. The simulation studies and real data analysis illustrate that the proposed VBSSLQR method is superior to or equivalent to other quantile and non-quantile regression methods (including Bayesian and non-Bayesian methods), and its efficiency is higher than any other method.

The poor success rate of preclinical drugs which target the nervous system is related to the highly complex nature of brain physiology and pathophysiology. For in vitro drug screening in this field, the two-dimensional (2D) approach - where cells are incubated in a monolayer - is not physiologically relevant. In contrast, in vivo rodent models are very low throughput and expensive. As such, improved, well-characterised three dimensional (3D) in vitro models should be employed to bridge the gap between 2D in vitro primary screening and rodent models by incorporating aspects of the in vivo brain environment. These key features include the extracellular matrix (ECM) and a multidimensional relationship of supporting cells. In this study, a neural progenitor cell line was differentiated into the main types of cells found in brain, including neurons and astrocytes. This model was designed in a 3D extracellular matrix replacement in a minimalised manner. Different culture formats using multi-well plates were explored and a high-throughput cellular imaging platform was applied. Next, we applied this model to assess neural toxicity of a newly synthesised dual-specificity tyrosine-regulated kinase 1 (DYRK1) inhibitor derived from natural compounds, which is structurally related to a natural DYRK1A inhibitor harmine, K04179. Chemical studies have already shown that K04179 has higher specificity to DYRK1A compared with previously reported DYRK1 inhibitors, such as INDY. We have produced the first report of the biological effects of this new compound on the new 3D minimalised mid-brain model with quantification of both neuronal and astrocyte populations in tandem, revealing differential toxic effects of DYRK1 inhibitor compounds K04179 and INDY on neurons and glia.

In this paper we provide a highly selected review and synthesis on some of the recent and notable contribution to research in portfolio analysis. A unique perspective on this development in the literature is offered in this paper by judiciously identifying a few sample eigenvalues adjustment patterns in a portfolio that leads to an improvement in the out-of-sample portfolio Sharpe ratio when the population covariance matrix admits a high-dimensional factor model. These patterns unveil a key insight into a portfolio performance improvement and shed an important light on the effectiveness of a few recently introduced ”robust to estimation errors” covariance matrix estimation approaches, which were not originally designed with the goal to improve the out-of-sample portfolio performance.

Nisin, an antibacterial compound produced by Lactococcus lactis strains, has been approved by the US Food and Drug Administration to be used as a safe food additive to control the growth of undesirable pathogenic bacteria. Nisin is commonly described as a pH-dependent primary metabolite, since its production depends on growth and culture pH evolution. However, the relationship between bacteriocin synthesis and the consumption of the limiting nutrient has not been described until now. Therefore, this study aimed to develop a competitive four-dimensional Lotka Volterra-like equation to describe the relationships between culture pH, limiting nutrient (total nitrogen: TN) consumption and production of biomass (X) and nisin (BT) in four series of batch fermentation with L. lactis CECT 539 in diluted whey (DW)-based media. The developed four-dimensional LV-like equation (with a unique set of parameters) could not be used to describe all cultures belonging to each fermentation series. However, the four-dimensional LV-like equation described accurately each individual culture, providing a good description of the relationships between pH, TN, X and BT, higher values for R2 and F-ratios, lower values (&lt; 10%) for the mean relative percentage deviation modulus, with bias and accuracy factor values approximately equal to one.

This paper proposes a contact force controller for a constrained flexible manipulator in three-dimensional motion. This controller used the conversion formula obtained empirically and experimental results showed the effectiveness of the proposed contact force controller. First, the manipulator was operated with the tip of the second link restrained, then, time response of the root strain, joint angles and contact force were used to derive the relational between the three quantities. The effectiveness of the relational expression was verified by conducting a target contact force tracking experiment by inputting the angle from the relational expression. The contact force control using the strain feedback method was proposed with the strain amount estimated from the target contact force as the target value, and its effectiveness was verified by experiments. From the results obtained, controller using the strain feedback method was designed for the purpose of controlling the contact force at the tip of a flexible manipulator with two links and three degrees of freedom that performs three-dimensional spatial motion, and its effectiveness was shown by comparison with the contact force feedback method.

In recent years, intelligent fault diagnosis algorithms using deep learning method have achieved much success. However, the signals collected by sensors contain a lot of noise, which will have a great impact on the accuracy of the diagnostic model. To address this problem, we propose a one-dimensional convolutional neural network with multi-scale kernels (MSK-1DCNN) and apply this method to bearing fault diagnosis. We use a multi-scale convolution structure to extract different fault features in the original signal, and use the ELU activation function instead of the ReLU function in the multi-scale convolution structure to improve the anti-noise ability of MSK-1DCNN; then we use the training set with pepper noise to train the network to suppress overfitting. We use the Western Reserve University bearing data to verify the effectiveness of the algorithm and compare it with other fault diagnosis algorithms. Experimental results show that the improvements we proposed have effectively improved the diagnosis performers of MSK-1DCNN under strong noise and the diagnosis accuracy is higher than other comparison algorithms.

Big Data classification has recently received a great deal of attention due to the main properties of Big Data, which are volume, variety, and velocity. The furthest-pair-based binary search tree (FPBST) shows a great potential for Big Data classification. This work attempts to improve the performance the FPBST in terms of computation time, space consumed and accuracy. The major enhancement of the FPBST includes converting the resultant BST to a decision tree, in order to remove the need for the slow K-nearest neighbors (KNN), and to obtain a smaller tree, which is useful for memory usage, speeding both training and testing phases and increasing the classification accuracy. The proposed decision trees are based on calculating the probabilities of each class at each node using various methods; these probabilities are then used by the testing phase to classify an unseen example. The experimental results on some (small, intermediate and big) machine learning datasets show the efficiency of the proposed methods, in terms of space, speed and accuracy compared to the FPBST, which shows great potential for further enhancements of the proposed methods to be used in practice.

Cold gas-dynamic spray (cold spray) is an evolving coating deposition and restoration technology in which particles are deposited above the sonic speed. This paper presents the non-destructive three-dimensional characterization of cold sprayed stainless steel coating. The visualization of coating morphology and volumetric porosity, and the analyses of porosity size and spatial distributions confirmed that dense stainless steel coating with non-connected, micron-sized gradient porosity is successfully produced by cold spray. The suitability of X-ray tomography for characterizing cold sprayed coatings is assessed.

Object. Utilization of pedicle screws (PS) for spine stabilization is common in spinal surgery. With reliance on visual inspection of anatomical landmarks prior to screw placement, the free-hand technique requires a high level of surgeon skill and precision. Three-dimensional (3D) computer-assisted virtual neuronavigation improves the precision of PS placement and minimize steps. Methods. Twenty-three patients with degenerative, traumatic, or neoplastic pathologies received treatment via a novel three-step PS technique that utilizes a navigated power driver in combination with virtual screw technology. 1) Following visualization of neuroanatomy using intraoperative CT, a navigated 3-mm match stick drill bit was inserted at anatomical entry point with screen projection showing virtual screw. 2) Navigated Stryker Cordless Driver with appropriate tap was used to access vertebral body through pedicle with screen projection again showing virtual screw. 3) Navigated Stryker Cordless Driver with actual screw was used with screen projection showing the same virtual screw. One hundred and forty-four consecutive screws were inserted using this three-step, navigated driver, virtual screw technique. Results. Only 1 screw needed intraoperative revision after insertion using the three-step, navigated driver, virtual PS technique. This amounts to a 0.69% revision rate. One hundred percent of patients had intraoperative CT reconstructed images to confirm hardware placement. Conclusions. Pedicle screw placement utilizing the Stryker-Ziehm neuronavigation virtual screw technology with a three step, navigated power drill technique is safe and effective.

This article deals with special curves similar to those known in mathematics as Lamé curves. Their equations have a certain similarity with the equations of Lamé curves. But these curves are more like ellipses in appearance. Like ellipses, they have major and minor axes. These are such curves that their major and minor semi-axis coincide with an ellipse but are different than an ellipse. The main feature of these curves is that for any triangle whose base coincides with the axis of a given curve and the vertex is on a given curve, the condition aⁿ+bⁿ=cⁿ is obtained. The number “n” is called the degree or rank of this curve. To distinguish this group of curves, we called them Elbe curves. The equations of these lines are also provided in the paper.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the novel coronavirus responsible for the coronavirus disease 2019 (COVID-19) pandemic, represents a serious threat to public health. The spike (S) glycoprotein of SARS-CoV-2 mediates viral entry into host cells and is heavily glycosylated. In this study, we systemically analyzed the roles of 22 putative N-linked glycans in SARS-CoV-2 S protein expression, membrane fusion, viral entry, and stability. Using α-glycosidase inhibitors, castanospermine and NB-DNJ, we confirmed that disrupting the N-linked glycosylation process blocked the maturation of the S protein, leading to impairment of S protein-mediated membrane fusion. Single substitution of each of the 22 N-linked glycosylation sites with glutamine revealed that 9 out of the 22 N-linked glycosylation sites were critical for S protein folding and maturation, resulting in reduced S protein-mediated cell-cell fusion and viral entry. Of note, N1074Q mutation markedly affected S protein stability and induced significant receptor-independent syncytium (RIS) formation in HEK293T/hACE2-KO cells, and removal of the furin-cleavage site partially compensated instability of N1074Q mutation. Although the corresponding mutation in the SARS-CoV S protein (N1056Q) did not induce RIS in HEK293T cells, the mutants N669Q and N1080Q exhibited increased fusogenic activity and induced syncytia formation in HEK293T cells. Therefore, N-glycans on the SARS-CoV and SARS-CoV-2 S2 subunits are of great importance in maintaining the prefusion state of the S protein. The study revealed the critical roles of N-glycans in S protein maturation and stability, which have implications for the design of vaccines and anti-viral strategies.

Two new compounds, named aspergilins A (1) and B (2), were isolated from the mangrove endophytic fungus Aspergillus sp. A1E3 associated with the fruit of Rhizophora mucronata, together with averufanin (3). The planar structures and absolute configurations of these compounds were unambiguously established by extensive NMR investigations, quantum-chemical electronic circular dichroism (ECD) calculations, and single-crystal X-ray diffraction analysis. Most notably, the absolute configuration of aspergillin A (1) was determined by single-crystal X-ray diffraction analysis of its tri-pivaloyl derivative 4, conducted with Cu Kα radiation, whereas that of averufanin (3) was first clarified by quantum-chemical ECD calculations. Aspergilin A is the first orsellinic acid–ribose–​pyridazinone-Noxide hybrid containing a unique β-oxo-2,3-dihydropyridazine 1-oxide moiety, whereas aspergilin B and averufanin are the sterigmatocystin and anthraquinone derivative, respectively. From the perspective of biosynthesis, aspergilin A could be originated from the combined assembly of three building blocks, viz., orsellinic acid, β-D-ribofuranose, and L-glutamine. It is an unprecedented alkaloid-Noxide involving biosynthetic pathways of polyketide, pentose, and amino acid. Aspergilin B (2) exhibited potent antiproliferative activity against four cancer cell lines. In addition, Aspergilin B (2) dose-dependently induced G2/M phase arrest in HepG2 cells.

Cardiovascular diseases (CVD) are chronic diseases associated with a high risk of mortality and morbidity. Early detection of CVD is crucial to initiating timely interventions, such as appro- priate counseling and medication, which can effectively manage the condition and improve patient outcomes. Preventive measures should be implemented at the general public level, promoting a healthy lifestyle, and at the individual level, that is, in people with moderate to high risk of CVD or patients already diagnosed with CVD by addressing an unhealthy lifestyle. Personalized early diagnostic systems based on artificial intelligence (AI), ontologies, and other medical information processing systems may prove to be a great preventive measure. In this paper, we focus on the use of ontology-inspired database models in the diagnosis of cardiovascular disease, as well as their potential for use in web application development.

This article explores the relationship between convex functions defined on integers ($\mathbb{Z}$) and their extension to real numbers ($\mathbb{R}$). We introduce key definitions and investigate the hypothesis that there exists a unique convex curve within this family of functions, leading to a proof by contradiction. Our findings highlight the preservation of convexity as functions transition from integers to real numbers.

Glioblastoma (GBM) is an aggressive and lethal primary brain tumor with restricted treatment options and a dismal prognosis. Oncolytic virotherapy (OV) has developed as a promising approach for GBM treatment. However, reaching invasive GBM cells may be hindered by tumor-surrounding, non-neoplastic cells when the OV is applied intratumorally. In this study, using a rodent GBM model and immunofluorescence analyses, we investigated the intranasal delivery of the oncolytic adenovirus (OAV) XVir-N-31 via virus-loaded, optimized shuttle cells. Intranasal administration (INA) was selected due to its non-invasive nature and the potential to bypass the blood-brain barrier (BBB). Our findings demonstrate that INA of XVir-N-31 loaded shuttle cells successfully delivers OAVs to the core tumor and invasive GBM cells, significantly prolongs the survival of GBM bearing mice, induces immunogenic cell death and finally reduces tumor burden, all this highlighting the therapeutic potential of this innovative approach. Overall, this study provides compelling evidence for the effectiveness of INA of XVir-N-31 via shuttle cells as a promising therapeutic strategy for GBM. The non-invasive nature of INA of OV-loaded shuttle cells holds great promise for future clinical translation. However, further research is required to assess the efficacy of this approach to ultimately progress in human clinical trials.

Much evidence reveals an important link between gut microbiota and the heart. In particular, the gut microbiota plays a key role in the onset of cardiovascular (CV) disease, including heart failure (HF). In HF, splanchnic hypoperfusion causes intestinal ischemia resulting in the translocation of bacteria and their metabolites into the blood circulation. Among these, the most important is the Trimethylamine N-Oxide (TMAO), which is responsible through various mechanisms for pathological processes in different organs and tissues. In this review, we summarise the complex interaction between gut microbiota and CV disease, particularly with HF, and the possible strategies to influence its composition and function. Finally, we highlight the potential role of TMAO as a novel prognostic marker and new therapeutic target of HF.

This study employed a TSMC 0.18-µm 50 V process to establish a high-voltage n-LDMOS structure. In the reference device, the number of floating-poly (poly-2) turns was 7, and the width and spacing of each turn was 1 µm. Although increasing the number of turns reduces the peak field, directly reducing or increasing the number of poly-2 turns is a common practice. The present experiment was realized in three steps, namely fixing the number of occupied area adjustment turns, adjusting the width of each turn, and adjusting the distance between turns. The first step was fixing the number of occupied area adjustment turns. The number of turns was increased from 7 to 9, and the number of turns was reduced to 5 and 3 in the reference group. A reduction in the number of turns led to a greater decrease in the peak field and increase in the breakdown voltage despite the area remaining unchanged. A comparison of the use of three turns with that of seven turns revealed that the maximum electric field decreased by 42%, from 4.17e+3 to 2.46e+3 V/cm, and that the breakdown voltage (VBK) increased from 30.2 to 35.84 V. The second step was adjusting the width of each turn from 1 to 1.4, 1.2, 0.8, and 0.6 µm in the reference group. This increase in width reduced the maximum electric field and led to a greater increase in VBK. When the width was increased to 1.4 µm, the maximum electric field decreased by 29% from 1.95e+3 to 1.4e+3 V/cm, and the VBK increased by 183% from 30.2 to 85.6 V. The third step was adjusting the spacing of each turn from 1 to 1.4, 1.2, 0.8, and 0.6 µm in the reference group. The results revealed that a reduction in the spacing led to a greater reduction in the maximum electric field and an in-crease in the VBK. When the pitch was reduced to 0.6 µm, the maximum electric field decreased by 33%, from 1.95e+3 to 1.32e+3 V/cm, and the VBK increased by 345%, from 30.2 to 134.4 V.

The aim of the present study was to assess the efficacy of All Cosmos Industries (ACI) bio-organic and bio-chemical fertilizers and ACI N-Fixer (N-Bio Booster) on the paddy yields based on the field trial plots at Langkat, Medan, Indonesia. This application of ACI bio-organic fertilizer (NPK 5/5/5) and ACI bio-chemical (NPK 15/15/15) fertilizer and ACI N-Fixer tests were conducted at the paddy farm at Langkat from May-October 2018. This study employed a factorial randomized complete block design which consisted of two factors, namely: Factor I with four types of fertilizers while Factor II consisted of two paddy varieties (Inpari 30 and Inpari 32). Overall, the filled grains in the ACI treatments are significantly (P< 0.05) higher than those in the control treatments that used Normal Chemical Compound NPK. Overall, total weight per meter² (368-617g) in ACI treatments are also significantly (P< 0.05) higher than those (319-371g) in the control treatments. At harvesting time at 105 days after transplanting, significantly higher (P< 0.05) colony counts (13-15 x 10⁶ CFU/mL) (for ACI treatments), than those (8 x 10⁶ CFU/mL) in the controls positively indicated higher total yields of paddy grains per hectare. It was found that the application of ACI bio-organic and bio-chemical fertilizers and ACI N-Fixer can improve paddy yields of the two rice varieties, between 16.4-38.2% (up to 5.75 MT/ha), in the field trial plots at Langkat. These commercial fertilizers play an imperative role in refining the soil fertility and thereby can increase the yield of rice production. Therefore, it is highly recommended that ACI bio-organic and ACI bio-chemical fertilizers and ACI N-Fixer (N-Bio Booster) can be employed to increase the paddy yield in this region.

As the coronavirus disease 2019 (COVID-19), which is caused by the novel SARS-CoV-2, continues to spread rapidly around the world, there is a need for well validated serological assays that allow the detection of viral specific antibody responses in COVID-19 patients or recovered individuals. In this study, we established and used multiple indirect Enzyme Linked Immunosorbent Assay (ELISA)-based serological assays to study the antibody response in COVID-19 patients. In order to validate the assays we determined the cut off values, sensitivity and specificity of the assays using sera collected from pre-pandemic healthy controls, COVID-19 patients at different time points after disease-onset, and seropositive sera to other human coronaviruses. The developed SARS-CoV-2 S1 subunit of the spike glycoprotein and nucleocapsid (N)-based ELISAs not only showed high specificity and sensitivity but also did not show any cross-reactivity with other CoVs. We also show that all RT-PCR confirmed COVID-19 patients tested in our study developed both virus specific IgM and IgG antibodies as early as week one after disease onset. Our data also suggest that the inclusion of both S1 and N in serological testing would capture as many potential SARS-CoV-2 positive cases as possible than using any of them alone. This is specifically important for tracing contacts and cases and conducting large-scale epidemiological studies to understand the true extent of virus spread in populations.

In this paper, we have used magnetron sputtering to grow the high-quality GeSn layer on Ge (100) with Sn compositin up to 7%. The crystallinity of the GeSn layer is pretty good, and the strain relaxation degree of the GeSn layer is evaluated to be approximately 50%. The root mean square (RMS) value is 0.8 nm, and the averaged TDDs in the GeSn layer is 8.7×109 cm-2, which is obtained from the rocking curve of GeSn layer along (004) plane. PL measurement result shows the significant optical emission from the deposited high-quality GeSn layer, which also means that magnetron sputtering is an optional way to achieve the higher Sn composition GeSn luminescent material. To verify whether our deposited GeSn can used for optoelectronic devices, we fabricate the simple vertical p-i-n diode, and the room temperature current-voltage (I-V) characteristic was obtained. This result paves the way for future sputtered-GeSn optimization, which is critical for the optoelectronic application.

Field cricket (Gryllus bimaculatus) is newly emerged as an edible insect in several countries. Anti-inflammatory effect of glycosaminoglycan derived this cricket was not fully investigated on chronic disease animal model such as diabetic mouse. For potential therapeutic agents, anti-diabetic activities of field cricket glycosaminoglycan (GbG) was evaluated in diabetic mice based on their abilities to reduce glucose, ALT, AST, LDL-cholesterol, and BUN levels, compared with dung beetle (Catharsius molossus) glycosaminoglycan (CaG) as a positive control glycosaminoglycan. Db mice were orally administered for one month according to their groups: Db Hetero (normal), Db Homo (type-2 diabetic), CaG (5 mg/kg), GbG (5 mg/kg), and metformin (10 mg/kg). Blood glucose level was decreased after 1^st week treatment with GbG. It also inhibited LDL-cholesterol and alkaline phosphatase levels. Regarding oxidative damage of diabetic state, levels of hepatocellular biomarkers levels and protein carbonyl content were reduced in db mice treated with GbG. Especially anti-oxidative activities of catalase, superoxide dismutase, and glutathione peroxidase were significantly increased in GbG treated group compared to those in the control. GbG was composed of heparin disaccharides and main N-glycan was identified as Hex₉GlcNAc₂ (m/z 1905.7) of with neutral mono-sugar mainly comprising of hexose, L (+) rhamnose by mass spectroscopy. These results from sero-biochemical, hepatocellular anti-oxidant assay in db mice data suggest cricket (G. bimaculatus) glycosaminoglycan might play a role in its anti-diabetic action.

In this work, nylon 6/ P(N-phenylmaleimide-alt-styrene) blends were prepared by melt blending, and the mechanical, heat-resistant, crystallographic and dynamical mechanical properties of nylon 6/ P(N-phenylmaleimide-alt-styrene) blends with different contents were investigated and analyzed. The results showed that the mechanical properties decreased with increasing PNS, while the heat deflection temperature (HDT), relative crystallinity (Xn), and storage modulus (G’) increased with increasing PNS. The results of differential Scanning Calorimetry (DSC) proved the PNS played the positive role of nucleating PA6. And the results of dynamic mechanical analysis (DMA) proved the PNS could improve the rigidity of PA6/PNS blends. From the SEM, these PNS domains were between 0.2 and 4 μm in diameter. The experimental results indicated that the addition of PNS improved the rigidity of PA6/PNS blends, and then improved the heat-resistant property.

Fabrication of a nanocrystal zinc oxide (ZnO)/nitrogen-doped (N-doped) graphene composite using a novel and facile in situ sol-gel technique is demonstrated. Two-dimensional nanostructure morphology with uniform ZnO nanoparticles (average diameter of 10.25 nm) anchored on N-doped graphene nanosheets was observed via electron microscopy. Because of the polar heteroatoms on the graphene sheets, an abundance sites for polysulfide absorption were provided. More importantly, the strong chemical interaction between ZnO and polysulfides efficiently hindered the transport of polysulfides. Consequently, the lithium/sulfur (Li/S) battery with the ZnO/N-doped graphene composite-coated separator delivered enhanced performance in terms of discharge capacity and cycling stability when compared to the cell with a normal separator. With the modified separator, the battery achieved a discharge capacity as high as 942 mAh g^-1 for the first cycle and remained at 90.02 mAh g^-1 after the 100th charge/discharge test at 0.1 C. Results indicate that impeding the shuttling of polysulfides contributes to efficiently improving the behavior of the Li/S battery.

Fabrication of a nanocrystal zinc oxide (ZnO)/nitrogen-doped (N-doped) graphene composite using a novel and facile in situ sol-gel technique is demonstrated. Two-dimensional nanostructure morphology with uniform ZnO nanoparticles (average diameter of 10.25 nm) anchored on N-doped graphene nanosheets was observed via electron microscopy. Because of the polar heteroatoms on the graphene sheets, an abundance sites for polysulfide absorption were provided. More importantly, the strong chemical interaction between ZnO and polysulfides efficiently hindered the transport of polysulfides. Consequently, the lithium/sulfur (Li/S) battery with the ZnO/N-doped graphene composite-coated separator delivered enhanced performance in terms of discharge capacity and cycling stability when compared to the cell with a normal separator. With the modified separator, the battery achieved a discharge capacity as high as 942 mAh g^-1 for the first cycle and remained at 90.02 mAh g^-1 after the 100th charge/discharge test at 0.1 C. Results indicate that impeding the shuttling of polysulfides contributes to efficiently improving the behavior of the Li/S battery.

The Chinese drug Bombyx Batryticatus mori.L which also named as the white stiff silkworm is widely used in clinics, due to the significant antispasmodic and promotional blood circulation effects. In addition, its hypoglycemic effect is also recognized in recent years. From a pathological point of view, the enzymatic glycosylation and non-enzymatic glycation both have important roles in regulating properties of proteins and are associated with Diabetes. With the db/db mouse model, we examined the alterations of N-glycosylation of diabetic myocardium at primary stage and clarify the differences in glycosylation of myocardium before and after with 1-DNJ treatment. Hydrophilic chromatography solid phase extraction enrichment and LC-MS/MS identification was applied to profile the alternations in protein glycosylation. Meanwhile, N-glycan α1, 6-fucosylation alterations were profiled with LCA lectin blot and FITC-labelled lectin affinity histochemistry. Our results showed that AGES, hydroxyproline, CTGF and other serum indicators and fibrosis related cytokines expressional levels were reduced significantly by 1-DNJ in a dose-dependent manner. In order to verify this result, the well-known pathway of TGF-β/smad2/3 was picked out and α1, 6-core fucosylated TGFR-βⅡwas semi-quantified with western blot method. The result sustained the conclusion from LCA lectin affinity histochemistry and lectin blot analysis. The expressional level of α1, 6-fucosyltransferase mRNA was increased in the myocardium of db/db mice, however, the 1-DNJ administration did not show obvious inhibitory effect on FU8 expression. This unexpected result can be interpreted as 1-DNJ plays the roles by reducing the concentration of substrate rather than inhibiting α1，6-fucose glycosyltransferase expression. Meanwhile, 1-DNJ crude extract from BBm with some flavonoids accompany can also play the roles of anti-oxidant, and all the chemicals protect the diabetic myocardium from hyperglycemia damage commonly.

Following our previous success in identifying new steroid-based anticancer agents, we herein disclosed the structural requirements for retaining high potency against cancer cells and associated modes of action. The structurally novel steroidal dimer by001 inhibited growth of different esophageal cancer cells and colony formation at low micromolar levels, elevated cellular ROS levels and caused mitochondrial dysfunction. Mechanistic studies showed that by001 induced cell death through the mitochondria and death receptor-mediated apoptotic pathways and autophagy induction, as well as inhibited migration.

We monitored the water quality and hydrological conditions of a horizontal subsurface constructed wetland (HSSF-CW) in Beijing, China, for 2 years. We simulated the area rate constant and the temperature coefficient with the first-order kinetic model. We examined the relationships between the nitrogen (N) removal rate, N load, seasonal variations in the N removal rate, and environmental factors, such as the area rate constant, temperature, and dissolved oxygen (DO). The effluent ammonia (NH₄⁺-N) and nitrate (NO₃⁻-N) concentrations were significantly lower than the influent concentrations (p<0.01, n=38). The NO₃⁻-N load was significantly correlated with the removal rate (R²=0.9566, p<0.01), but the NH^₄+-N load was not correlated with the removal rate (R²=0.0187, p>0.01). The area rate constants of NO₃⁻-N and NH₄⁺-N at 20 °C were 27.01±26.49 and 16.63±10.58 m∙yr⁻¹, respectively. The temperature coefficients for NO₃⁻-N and NH₄⁺-N were estimated at 1.0042 and 0.9604, respectively. The area rate constants for NO₃⁻-N and NH₄⁺-N were not correlated with temperature (p>0.01). The NO₃⁻-N area rate constant was correlated with the corresponding load (R²=0.9625, p<0.01). The NH₄⁺-N area rate was correlated with DO (R²=0.6922, p<0.01), suggesting that the factors that influenced the N removal rate in this wetland met Liebig's law of the minimum.

Several vaccines against COVID -19 have been developed and licenced to enhance the immune response against SARS-CoV-2. Similarly, infection with SARS-CoV-2 before vaccination has been shown to provide significant protection against severe infection and hospitalisation. The aim of this study was to investigate the effect of three doses of Sinopharm vaccine and SARS-CoV-2 infection on the specific immune response in 103 volunteers, measuring neutralizing antibodies, anti-S1 IgG, anti-RBD IgM, anti-N IgM, anti-N IgG antibodies and interferon γ. Our results showed that the presence of cardiovascular diseases increased the level of anti-N-IgG antibodies, while endocrinological diseases decreased the level of neutralizing antibodies and anti-N-IgG antibodies, suggesting that these diseases alter the effect of vaccine immunity. In addition, there was a significant decrease in anti-S1 IgG levels 6 months and in anti-N IgG levels 18 months post-infection, while neutralizing antibody and interferon γ levels were constant at 3, 6 and 18 months post-infection. Therefore, our results confirm the importance of hybrid immunity as the strongest and most durable compared to exclusively natural or vaccine-induced immunity. Significant positive correlations were found between humoral and cellular immunity markers: neutralizing antibodies, anti-S1 IgG, anti-N IgG and interferon γ, indicating a unique coordinated response specific to COVID-19.

As a new plant slope protection technology, living stumps can effectively improve slope stability. The current study attemptes to investigate the mechanical characteristics of the root system of living stumps and their reinforcement mechanism on slopes by carrying out a three-dimensional living stump slope modeling test. Using ABS materials, a 3D model of a living elm stump was created by 3D printing and a slope model test was carried out. The reinforcement mechanism of the living stump was studied through a combination of model testing and numerical simulation. The results indicate that, due to the presence of living stumps in the lower and middle parts of the slope, the maximum shear stress area of the soil moved to a deeper direction. The stress state of the soil around the living stump was effectively improved due to the existence of the lateral root system.Living stumps in the lower part of the slope cross the potential sliding surface and transferred the soil shear stress gradually to the root system through root-soil interaction. Moreover, the tap roots and lateral roots of living stumps form a robust spatial structure that bears the shear stress of soil together, thus increasing the stability of the slope.

Energy distance is used to eigenvalue distributions in this new Wishart distribution study, providing a new perspective on high-dimensional data. Multivariate statistics relies on Wishart distribution to explain covariance matrices. This analysis shows how degrees of freedom and covariance matrix configurations affect eigenvalue dispersion. We use energy distance based on eigenvalue distributions to assess Wishart distribution differences without the "curse of dimensionality" via extensive simulation simulations. This approach improves measurement accuracy and processing efficiency in distribution comparisons and enables new analytical pathways in scientific fields that need data covariance comprehension. Our results show that degrees of freedom and matrix structure considerably affect energy distances, expanding the theoretical framework and practical applications of statistical models.

To solve the problem of a uneven load for a dual-input counter-rotating transmission system, this research is based on Small Displacement Torsor Jacobian-Torsor theory.Considering the influence of the local parallel chain of a gearbox on the calculation accuracy of the backlash,the processing method of a meshing tooth pair parallel chain is proposed. The probability distribution of the tolerance band of gearbox manufacturing and assembly errors is modeled, the three-dimensional tolerance analysis model of a dual-input counter-rotating gearbox is established, and the Monte Carlo method is used to solve the backlash of the output end. The output backlash is solved with the Monte Carlo method, and the theoretical design backlash is combined with the output backlash to derive the gearbox side clearance range. The gearbox shaft system is analyzed statically, the range of the equal load coefficient is calculated, and the equal load performance optimization method based on the matching relationship between the gear backlash and the elastic shaft torsional stiffness is proposed. The correctness of the three-dimensional tolerance analysis combined with the elastic deflection angle used to optimize the equal load performance of the dual-input counter-rotating transmission system is verified by comparison with the relevant test data.

This work is devoted to the construction and study of commutative gates for a two-qubit quantum system. Using four-dimensional algebra developed by the Kazakh mathematician Abenov M.M. all groups of commutative gates have been constructed, and among all states of a two-qubit quantum system, unitary states with which a specific gate is connected have been identified. An explicit type of gate is described that transfers a quantum system from one unitary state to another unitary state. The proposed approach opens up new possibilities for the design of quantum algorithms not only for two-qubit quantum systems, but also for $n$-qubit quantum systems.

In this work, an entropy-stable and well-balanced numerical scheme for a one-dimensional blood flow model is presented. Such scheme is obtained from an explicit entropy conservative flux along with a second order discretization of the source term by using centered finite differences. We prove that the scheme is entropy-stable and preserves steady-states solutions. In addition, some numerical examples are included to test the performance of the proposed scheme.

In this study, cotton fabric reinforced phenolic resin (CPF) composites were modified by adding four two-dimensional fillers: graphitic carbon nitride (g-C3N4), graphite (Gr), molybdenum disulfide (MoS2), and hexagonal boron nitride (h-BN). The tribological properties of these modified materials were investigated under dry friction and water lubrication conditions. CPF/ Gr composite exhibits significantly better tribological performance than the other three fillers modified CPF composites under dry friction, with a 24% reduction in friction coefficient and a 78% reduction in wear rate compared to unmodified CPF composite. Under water lubrication conditions, all four fillers did not significantly alter the friction coefficient of the CPF composite. However, except for an excessive amount of Gr, the other three fillers can reduce the wear rate. Particularly, in the case of 10% MoS2 content, the wear rate decreased by 56%. Scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS) were employed for the analysis of the morphology and composition of the transfer films. Additionally, molecular dynamics (MD) simulations were conducted to investigate the adsorption effects of Gr, MoS2, and PF on the counterpart surface under both dry friction and water lubrication conditions. The difference in the adsorption capacity of Gr and MoS2 on the counterpart, as well as the resulting formation of transfer films, accounts for the variation in tribological behavior between CPF/Gr and CPF/MoS2 composites. By combining the lubrication properties of MoS2 and Gr under dry friction and water lubrication conditions, using them as co-fillers can achieve a synergistic lubrication effect.

The research community has shown significant interest in the aqueous synthesis of nanomaterials due to its ability to eliminate the need for complex organic solvents. This synthesis approach aligns with the principles of green chemistry, attracting considerable attention. Aqueous solution technology in fabricating nanostructures has gained recognition for its potential to create ultrasensitive, low-energy, and ultrafast optoelectronic devices. This report focuses on synthesizing lead iodide (PbI2) nanoplates using a water-based solution technique and fabricating a planar photodetector. The photodetectors with a planar type of device structure (ITO/PbI2 NPs/Au) demonstrated a remarkable photosensitivity of 3.9×103 and a photoresponsivity of 0.51 mA/W at a wavelength of 405 nm. Notably, the asymmetrical output properties of ITO/PbI2 NPs/Au detector deliver additional evidence of the effective creation of a Schottky contact. Thus, the photodetector exhibited a photoresponse even at 0 V bias, leading to the realization of self-powered photodetectors. Additionally, the device exhibited a rapid photoresponse of 0.21/0.38 s (−5 V) in the visible range. This study has expanded the horizons for the aqueous-phase synthesis of nanoplate nanostructures, enabling the large-area fabrication of high-performance photodetectors.

The natural units of measure lauded by Max Planck more than 100 years ago are rarely used today. But many physical constants, including Planck's constant, the gravitational constant, the speed of light, vacuum permittivity, and vacuum permeability, consist of natural units in their unit dimensions. The natural units are present in all formulas containing these constants. The defining characteristic of the natural units is an alignment of unit values at the Planck scale. This alignment gives a computational basis of proportionality from which the correlated properties and dynamics of elementary particles, including wavelength, period, mass, momentum, and energy, manifest in equal or inversely proportional ratios of the Planck scale. These correlations explain many of the defining equations of quantum mechanics, classical gravity, and electromagnetism.

Due to increasing concerns about global warming and energy crisis, intensive efforts have been made to explore renewable and clean energy sources. Single-atom metals and two-dimensional (2D) nanomaterials have attracted extensive attention in the fields of energy and environment because of their unique electronic structures and excellent properties. In this review, we sum-marize the state-of-art progress on the single-atom metal supported at 2D MoS2 (single-atom metal/2D MoS2) for electrochemical CO2 reduction and water splitting. First, we introduce the advantages of single-atom metal/2D MoS2 catalysts in the fields of electrocatalytic CO2 reduction and water splitting, followed by the strategies for improving electrocatalytic performances of single-atom metal/2D MoS2 hybrid nanomaterials and the typical preparation methods. Further, we discuss the important applications of the nanocomposites in electrocatalytic CO2 reduction and water splitting via some typical examples, particularly focusing on their synthesis routes, modification approaches, and physiochemical mechanisms for improving their electrocatalytic performances. Finally, our perspectives on the key challenges and future directions of exploring high-performance metal single-atom catalysts are presented based on recent achievements in the development of single-atom metal/2D MoS2 hybrid nanomaterials.

High-dimensional measurement error data are becoming more prevalent across various fields. Research on measurement error regression models has gained increasing attention due to the risk of drawing inaccurate conclusions if measurement errors are ignored. When the dimension p is larger than the sample size n, it is challenging to develop statistical inference methods for high-dimensional measurement error regression models due to the existence of bias, nonconvexity of objective function, high computational cost and many other difficulties. Over the past few years, some works have overcome the aforementioned difficulties and proposed several statistical inference methods. This paper mainly reviews the current development on estimation, hypothesis testing and variable screening methods for high-dimensional measurement error regression models and shows the theoretical results of these methods with some directions worthy of exploring for future research.

Manual measurement of rock discontinuities is time-consuming and subjective according to the experience of the surveyor. This work proposes a three-dimensional laser scanning-based method for the semi-automatic identification of rock discontinuities. Multisite cloud scanning is performed with real-time kinematic (RTK)-assisted orientation to estimate the rock fracturing degree; then, discontinuity orientations are extracted with the man–machine interactive method or automatic method. The proposed method was applied to actual examples to illustrate its accuracy at identifying rock discontinuities. The sensitivity of the identification accuracy to different parameters was investigated.

Additive manufacturing (AM) is an emerged layer-by-layer manufacturing process. However, its broad adoption is still hindered by limited material options, different fabrication defects, and inconsistent part quality. Material extrusion (ME) is one of the most widely used AM technologies, and, hence, is adopted in this research. Low-cost metal ME is a new and AM technology used to fabricate metal composite parts using sintered metal infused filament material. Since the involved materials and process are relatively new, there is a need to investigate the dimensional accuracy of ME fabricated metal parts for real-world applications. Each step of the manufacturing process, from the material extrusion to sintering, might significantly affect the dimensional accuracy. This research provides a comprehensive analysis of dimensional changes of metal samples fabricated by the ME and sintering process, using statistical and machine learning algorithms. Machine learning (ML) methods can be used to assist researchers in sophisticated pre-manufacturing planning and product quality assessment and control. This study compares linear regression to neural networks in assessing and predicting the dimensional changes of ME made components after 3D printing and sintering process. The prediction outcomes using a neural network performed the best with the highest accuracy as compared to regression. The findings of this study can help researchers and engineers to predict the dimensional variations and optimize the printing and sintering process parameters to obtain high quality metal parts fabricated by the low-cost ME process.

We review the latest developments in the field of the metal-insulator transition in strongly-correlated two-dimensional electron systems. Particular attention is given to recent discoveries of a sliding quantum electron solid and interaction-induced spectrum flattening at the Fermi level in high-quality silicon-based structures.

This paper addresses the problem of assessing and optimizing acoustic positioning system for underwater target localization with range measurements only. We present a new three-dimensional assessment model to assess the optimal geometric beacon formation whether meet user needs. For the sake of mathematical tractability, it is assumed that the measurements of the range between the target and beacons are corrupted with white Gaussian noise with variance is distance-dependent. Then by adopting dilution of precision (DOP) parameters in the assessment model, the relationship between DOP parameters and positioning accuracy is derived. In addition, the optimal geometric beacon formation that will yield the best performance is achieved by minimizing the values of geometric dilution of precision (GDOP) on condition that the position of target is known and fixed. Next, in order to make sure whether the estimate positioning accuracy over interesting region satisfy the precision needed by the users, geometric positioning accuracy (GPA), horizonal positioning accuracy (HPA) and vertical positioning accuracy (VPA) are utilized to assess the optimal geometric beacon formation. Simulation examples are designed to illustrate the exactness of the conclusion. Unlike other work which only use GDOP to optimize the formation and cannot assess the performance of the specified dimensions, this new three-dimensional assessment model can assess the optimal geometric beacon formation in each dimension for any point in three-dimensional space, which can provide users with guidance advices to optimize performance of every specified dimension.

Resistive patch array incorporating with metallic backplane provided an effective way to the achievement of broadband metamaterial absorbers(MAs). When loading metallic metamaterial to resistive MA, the outstanding construction helps realize more flexible and diversified forms of broadband absorption. In this paper, we attempted to load metallic resonators(MRs) to resistive MA in the three-dimensional construction, which benefits further enhancement of lower-frequency absorption. Simulation showed that the partial absorption band was separated to lower frequency, while the rest of broadband absorption was unaffected. Meanwhile, after combining multi-unit of the proposed MAs, the stair-stepping broadband absorption was also achieved. At last, three samples were fabricated. The agreements between simulations and experimental results demonstrated that resistive MA loaded with MRs provided an effective way for further enhancement of lower-frequency absorption with almost no change of the absorbing structure and areal density. Thus, it is worthy to expect a wide range of applications to emerge inspired from the proposed attempt.

A new series of 1,3,4-oxadiazoles derivatives was synthesized, characterized and evaluated for their in vitro and in vivo anti-thrombotic activity. Compounds (3a-3i) exhibited significant clot lysis with respect to negative control and reference drug streptokinase (30,000 IU) while enhanced clotting time (CT) values were observed (130-342 sec) for these tested compounds than the standard drug heparin (110 sec.). High affinity towards 1NFY with greater docking score was observed for the compounds (3a, 3i, 3e, 3d and 3h) than the control ligand RPR200095. In addition, very good inhibitory potential against factor Xa (F-Xa) was observed with higher docking scores (5612-6270) with ACE values (–189.68 to –352.28 kcal/mol) than the control ligand RPR200095 (Docking score 5192; ACE –197.81 kcal/mol. In vitro, in vivo and in silico results proposed that these newly synthesized compounds can be used as anti-coagulant agents.

Glycosylation, the most significant modification of proteins, plays an essential role in cellular processes. Congenital disorders of glycosylation (CDG) are multisystemic diseases resulting from mutations affecting glycosylation steps. Diagnosis of CDG relies on biochemical assays, such as isoelectric focusing. Despite its significance, CDG cases remain unreported in Cuba due to the lack of implemented diagnostic methods. This study aimed to evaluate transferrin glycoforms for diagnosing congenital N-glycosylation defects. We conducted a cross-sectional descriptive study using serum samples from 17 patients stored at the National Center for Medical Genetics of Cuba for suspected CDG. Results revealed abnormal glycosylation patterns in 7 patients, suggesting congenital N-glycosylation defects. We conclude that the implementation of transferrin glycoform analysis could pioneer a preliminary diagnosis of CDG in Cuba.

In the past few decades, N-heterocyclic carbenes (NHCs) open the new field of organocatalysis in synthetic organic chemistry. This review highlights the dramatic progress in the NHC-catalyzed C−O bond formation based on the activation of aldehyde C(sp2)−H bonds. The oxidative and redox transformations for the synthesis of various molecules with structural diversity and complexity are summarized. Furthermore, new methods and strategies for NHC catalysis are emerging continuously; thus, cooperative catalysis with Brønsted acid, hydrogen-bonding catalyst, transition-metal catalyst, and photocatalyst is also described.

Antibacterial bone cements (ABCs), such as antibiotic-loaded bone cements (ALBCs), have been widely utilized in clinical treatments. Currently, bone cements loaded with vancomycin, gentamicin, tobramycin, or clindamycin are approved by the US Food and Drug Administration. However, traditional ALBCs exhibit drawbacks like burst release and bacterial resistance. Therefore, there is a demand for the development of antibacterial bone cements containing novel agents. In this review, we summarize the latest advancements in ABCs. More importantly, we provide an overview and outlook on novel antibacterial agent-loaded bone cements, including metallic antibacterial agents, pH-switchable antibacterial agents, cationic polymers, N-halamines, non-leaching acrylic monomers, antimicrobial peptides, etc. Offering novel perspectives for designing ABCs and treating bone infections.

One of the most concerning global environmental issues is the pollution of agricultural soils by heavy metals (HMs), especially cadmium (Cd), which not only affects human health by taking Cd-containing foods but also impacts the quality of rice. The soil's nitrification and denitrification processes, coupled with the release of volatile organic compounds by plants, raise substantial concerns. The understanding of three aspects of paddy soil under conditions of heavy-metal pollution and water management is currently limited. In this review, we summarized recent literature related to the deleterious effects of Cd on both soil processes related to the N cycle and rice quality, particularly aroma, in different water management practices. Under both continuous flooding (CF) and alternate wetting and drying (AWD) conditions, cadmium (Cd) has been observed to reduce both nitrification and denitrification processes. The adverse effects are more pronounced in continuous flooding (CF) compared to alternate wetting and drying (AWD). Similarly, the alteration in rice aroma is more significant in AWD than in CF. The precise modulation of volatile organic compounds (VOCs) by Cd, remains unclear based on the available literature. Nevertheless, HM accumulation is higher in AWD conditions compared to CF, leading to a detrimental impact on volatile organic compounds (VOCs). The literature concluded that AWD practices should be avoided in Cd contaminated fields to decrease accumulation and maintain the quality of rice. In the future, rhizospheric engineering and plant biotechnology can be used to decrease the transport of HMs from the soil to the plant’s edible parts.

Melittin, a natural antimicrobial peptide, displays a broad-spectrum antimicrobial activity, which has caused increasing attention as a potential antibiotic alternative. However, melittin has not been used widely at present due to its high hemolysis and low proteolytic stability. In this study, N-terminal fatty acid was conjugated to melittin to develop new melittin-derived lipopep-tides (MDLs) for improving the limitation of melittin. Our results showed that, the antimicrobial activity of MDLs was increased by 2 to 16 times compared with native melittin, and the stability of these MDLs against trypsin and pepsin degradation was increased by 50 to 80%. Besides, the hemolytic of the MDLs decreased when the length of the carbon chain of fatty acids exceeded 10. Among them, the newly designed analog Mel-C8 showed optimal antimicrobial activity and protease stability. The antimicrobial mechanism studied revealed that the MDLs showed a rapid bactericidal effect by interacting with LPS or LTA and penetrating the bacterial cell membrane. In conclusion, we designed and synthesized a new class of MDLs with potent antimicrobial activity, high proteolytic stability, and low hemolysis through N-terminal fatty acid conjugation.

Following on from work already carried out in our laboratory on a new biomass-derived green solvent, eucalyptol, we are now turning our attention to sabinene as a new green solvent. Sabinene is also derived from biomass. We have shown that it can be used as such or distilled to synthesize thiazolo[5,4-b]pyridine heterocycles by thermal or microwave activation. This new solvent was compared with various conventional and green solvents. The conditions were optimized to enable us to carry out the syntheses in good yields, and we were able to show that sabinene, a natural bicyclic monoterpene, could be used effectively as a solvent.

In the study of rough sets, there are many covering approximation spaces, how to classify covering approximation spaces has become a hot issue. In this paper, we propose concepts covering approximation $T_{1}$-space, $F-$symmtry, covering rough continuous mapping, covering rough homeomorphism mapping to solve this question. We also propose a new method for constructing topology in Theorem 5.1, and get the following properties: (1) For each $x\in U$, $\{X_{i}:i\in I\}\subseteq \mathcal{P}(U)$ is all the subsets of $U$ which contains $x$ and $*$ is a reflexive relation on $U$. If $V\in \tau$ is a subset of $U$ and $x\in V$, then $\underline{*}(\bigcap \limits_{i\in I}X_{i})$ is the smallest subset of $U$ and $x \in \underline{*}(\bigcap \limits_{i\in I}X_{i})\subseteq V$. Denoted by $C(x)=\bigcap \{\underline{*}(X_{i}):x\in \underline{*}(X_{i}),i\in I\}$. (2)If $V\in \tau$ is a subset of $U$, then $V =$ $\bigcup \limits_{x\in V} C(x)$. (3) Let $\{\underline{*}(X_{i}):x\notin \underline{*}(X_{i}), i\in I\}$, then $\overline{\{x\}}$ $=$ $U \setminus \bigcup \limits_{x\notin \underline{*}(X_{i}), i\in I}\underline{*}(X_{i})$; (4) Let $*$ be a reflexive relation on $U$. For every $X\subseteq U$, we have $int(\underline{*}(X))=\underline{*}(X)$. Where $int(\underline{*}(X))$ represents the interior of $\underline{*}(X)$. (5) Let $\{\underline{*}(X_{i}):x\in \underline{*}(X_{i}),i\in I\}$ be a family subsets of $U$, then $\{\underline{*}(X_{i}):x\in \underline{*}(X_{i}),i\in I\}$ is a base for $(U,\tau)$ at the point $x$. \\

The inability to efficiently metabolize homocysteine (Hcy), which occurs in nutritional and genetic deficiencies, leads to hyperhomocysteinemia (HHcy) thereby causing endothelial dysfunction, a hallmark of atherosclerosis which underpins cardiovascular disease (CVD). The dysregulation of mammalian target of rapamycin (mTOR) signaling, and impaired autophagy play important roles in CVD. Biochemically, HHcy is characterized by elevated levels of Hcy and its metabolites, Hcy-thiolactone (HTL) and N-Hcy-protein (N-Hcy). However, whether these metabolites can dysregulate mTOR signaling and autophagy in endothelial cells is not known. Here, we examined the influence of HTL, N-Hcy, and Hcy on the PHF8/H4K20me1/mTOR/autophagy pathway in human umbilical vein endothelial cells (HUVEC). We found that treatments with HTL, N-Hcy, or Hcy significantly reduced PHF8 protein and mRNA expression, increased H4K20me1, and upregulated mTOR signaling. Autophagy was also impaired (significantly downregulated BECN1, ATG5, ATG7, and LC3 protein and mRNA levels). We also found that these changes were mediated by PHF8-targeting microRNA (miR): miR-22-3p and miR-1229-3p. The effects of HTL, N-Hcy, or Hcy on the miR expression and on the PHF8/H4K20me1/mTOR/autophagy pathway were abrogated by treatments with an inhibitor of miR-22 or miR-1229. Taken together, these findings show that Hcy metabolites can upregulate miR-22-3p and miR-1229-3p expression, which then dysregulate the PHF8/H4K20me1/mTOR/autophagy pathway, important for vascular homeostasis.

Rechargeable aqueous Zn-ion batteries (ZIBs) have attracted considerable attention owing to their high theoretical capacity of 820 mA h g‒1, low cost and intrinsic safety. However, the electrolyte leakage and the instability issues of Zn negative electrodes originating from side reactions between the aqueous electrolyte and Zn negative electrode, not only restricts the battery stability but also results in short-circuit of aqueous ZIBs. Herein we report a flexible and stable N-isopropylacrylamide/sodium alginate (N-SA) gel electrolyte, which possesses high mechanical strength and high ionic conductivity of 2.96×10‒2 S cm‒1, and enables the Zn metal negative electrode and MnO2 positive electrode to reversibly and stably cycle. Compared to the liquid electrolyte, the N-SA hydrogel electrolyte can effectively form a uniform Zn deposition and suppress the generation of irreversible by-products. The assemble symmetric Zn/Zn cells at a current density of 1 mA cm‒2 shows a stable voltage profile, which maintains a low level of about 100 mV over 2600 h without an obvious short circuit or any overpotential increasing. Specially, the assembled Zn/N-SA/MnO2 batteries can deliver a high specific capacity of 182 mAh g‒1 and maintain 98% capacity retention after 650 cycles at 0.5 A g‒1. This work provides a facile method to fabricate high-performance SA-based hydrogel electrolytes that illustrates their potential for flexible batteries for wearable electronics.

In this paper, new N-way Wilkinson power dividers (WPDs) are represented by using slow-wave structures such as narrow slits loaded and meandered transmission lines. The slit loaded and meandered lines are used to represent the quarter wavelength transmission lines of a conventional WPD for size reduction. Based on the proposed approaches, 2-, 4- and 8-way power dividers are designed, simulated and fabricated. The fabricated -, 4- and 8-way circuits have been measured at the center frequencies of 2.03, 1.77, and 1.73 GHz in an excellent agreement with the predicted ones. The meandered transmission lines are also used to design new types of WPDs having novel input/output port arrangements. For this purpose, two 3-way WPDs are located at both sides of the same board so as to have different power splitting ratios at different inputs and outputs to provide alternative solutions for antenna arrays. Furthermore, a 5-way dual layer WPD is introduced by locating the meandered transmission lines to two layers. The proposed 3- and 5-way WPDs allow halving the input power at the next output port in the order of P/2, P/4, P/8, P/16, and P/16. All of the designed power halving WPDs have been simulated, fabricated and successfully tested.

To study the influence of electrothermal effect of ESD protection device on the reliability of inte-grated circuit,a theoretical model of ESD protection device thermal resistance is constructed in the paper based on the Conservation of Energy Principle. By analyzing the temperature relativity between electricity parameter and thermology parameter of ESD protection device characterized by self-heating thermal resistance, the quantitative relationship expression of physical parameter and geometric parameter is obtained, which can be used to improve ESD protection device elec-tro-thermal effect. The simulation testing and the real tape-out testing of ESD protection device self-heating thermal resistance based on ggNMOS are shown and compared. It is concluded that self-heating thermal resistance is an effective index for the protection device electrothermal char-acterization. Based on the established model, the self-heating thermal resistance could be decreased to improve the homogeneity of the heat transference. The uneven distribution of device temperature can be reduced, and the overall reliability of chips can be improved.

A new spirurid nematode Protospirura canariensis n. sp., parasite of the black rat Rattus rattus (Rodentia: Muridae) in El Hierro Island (Canary Archipelago, Spain) is described by means of light (LM) and scanning electron microscopy (SEM). The most discriminant characteristics between the new species and the existing species in the genus Protospirura are: (a) the number of tooth-like prominences in the submedian and lateral lobes of pseudolabia, both in males and females (2 and 4, respectively), (b) the size of right and left spicules in males (643–715 µm and 309–412 µm, respectively), and (c) the number and arrangement of cloacal papillae in males. The new species has a total of 17 cloacal papillae (four large and pedunculated pairs of precloacal papillae, an unpaired precloacal papilla and four pairs of postcloacal papillae). The arrangement of postcloacal papillae are as follows: the first pair are large, pedunculated and placed near the posterior edge of cloaca; the three remaining postcloacal pairs are grouped and located near the posterior tip. In the latter group, papillae in the first pair are large and pedunculated. Parasitized host and geographical distribution are also useful criteria to distinguish P. canariensis n. sp. from the remaining species of the genus Protospirura. In addition, the cytochrome c oxidase subunit 1 (cox1) sequence of the new species is provided and compared with available data of related species.

Background Nitrous Oxide (N₂O) is a dissociative anaesthetic that is sometimes used recreationally. The prevalence of N₂O use is difficult to quantify but appears to be increasing. Research on N₂O harms and application of harm reduction strategies are limited. The aim of this mixed method systematic review was to collate and synthesise the disparate body of research on recreational nitrous oxide use to inform harm reduction approaches tailored for young people. Methods To identify publications reporting recreational use of N₂O, a search of public health, psychology and social science databases was conducted. Databases included PubMed, CIHNAL, PsycINFO, Scopus and Web of Science. Gray literature and Google advanced search were also used. Due to limited published literature on the recreational use of N₂O, no limit was placed on publication date or study type. A thematic synthesis extracted descriptive and analytical themes from the selected studies. Quality appraisal was conducted using the CASP Tool for Qualitative studies and the Joanna Briggs Institute case report assessment tool Results The search retrieved 407 reports. Thirty-four were included in the final analysis including sixteen case reports. The included studies were primarily concerned with raising awareness of the apparently increasing use and subsequently increasing harms of recreational N₂O use. There was limited reference to policy or legislative responses in any published studies, no suggestions for harm reduction strategies or application of service level responses. In general, individuals lack awareness of N2O related harms. Conclusion The review found three key areas that deserve further consideration including: 1) policy, 2) service delivery, and 3) harm associated with N₂O use. We recommend a top-down (policy) and bottom-up (services delivery/services users) approach to harm reduction for N₂O use which also includes further consultation and research with both groups. Future research could explore young people’s experience of N₂O use including benefits and problems to inform contextually relevant harm reduction strategies.

Glycosylation is a complex post-translational modification that conveys functional diversity to glycoconjugates. Cell surface glycosylation mediates several biological activities such as induction of intracellular signaling pathway and pathogen recognition. Red blood cell (RBC) membrane N-glycans determine blood type and influence cell lifespan. Although several proteomic studies were carried out, glycosylation of RBC membrane proteins has not been systematically investigated. This work aims at exploring the human RBC N-glycome by high-sensitivity MALDI-MS techniques to outline a fingerprint of RBC N-glycans. To this purpose, MALDI-TOF spectra of healthy subjects harboring different blood groups were acquired. Results showed the predominant occurrence of neutral and sialylated complex N-glycans with bisected N-acetylglucosamine, core- and/or an-tennary fucosylation. In the higher mass region these species presented with multiple N-acetyllactosamine repeating units. Amongst the detected glycoforms, the presence of glycans bearing ABO(H) antigens allowed us to define a distinctive spectrum for each blood group. For the first time, advanced glycomic techniques have been applied to a comprehensive exploration of human RBC N-glycosylation, providing a new tool for the early detection of distinct glycome changes associated with disease conditions as well as to understand pathogens molecular recognition.