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The use of alternative fuels remains an important factor in solving the problem of reducing harmful substances caused by vehicles and decarbonising transport. It is also important to ensure the energy efficiency of vehicle power plants when using different fuels at a sufficient
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The use of alternative fuels remains an important factor in solving the problem of reducing harmful substances caused by vehicles and decarbonising transport. It is also important to ensure the energy efficiency of vehicle power plants when using different fuels at a sufficient level. The article presents the results of theoretical and experimental studies of the conversion of diesel engine to alternative fuels with hydrogen admixtures. Methanol is considered as an alternative fuel which is a cheaper alternative to commercial diesel fuel. The chemical essence of improving the calorific value of alternative methanol fuel was investigated. Studies showed that the energy effect of burning an alternative mixture with hydrogen additives exceeds the effect of burning the same amount of methanol fuel. The increase in combustion energy and engine power is achieved as a result of heat from efficient use of the engine exhaust gases and chemical conversion of methanol. An experimental installation was created to study the work of a converted diesel engine on hydrogen–methanol mixtures and thermochemical regeneration processes. Experimental studies of the energy and environmental parameters of diesel engine converted to work on an alternative fuel with hydrogen admixtures have shown that engine power increases by 10–14% and emissions of harmful substances decrease.
Full article
As a typical ecologically fragile area, the ecological security of the Loess Plateau has been seriously threatened. Ecological security patterns (ESP) have gradually become an effective method for protecting ecological security and supporting the management and sustainable development of ecosystems. Therefore, this study
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As a typical ecologically fragile area, the ecological security of the Loess Plateau has been seriously threatened. Ecological security patterns (ESP) have gradually become an effective method for protecting ecological security and supporting the management and sustainable development of ecosystems. Therefore, this study constructed a novel ESP based on ecological “function–structure”, utilizing minimum cumulative resistance (MCR) to identify ecological source areas and corridors. Additionally, time scales were introduced into the ESP, allowing for a comprehensive analysis of the spatiotemporal heterogeneity of ecological security in the Loess Plateau. The study revealed that the number of ecological sources decreased from southeast to northwest, with 27, 41, and 77 sources covering total areas of 4263.810 km2, 18,566.034 km2, and 113,209.595 km2 from 2000 to 2020, respectively. Similarly, the number and complexity of ecological corridors increased over the same time period, with 64, 85, and 105 corridors totaling lengths of 4579.326 km, 6526.996 km, and 7015.174 km, respectively. The expansion of ecological security zones was mainly observed in the southeast part of the Loess Plateau. Overall, the ESP of the Loess Plateau saw an improvement, with the southeastern part showing better ecological security than the northwestern part. These findings hold great significance for regional ecological security evaluations and are crucial for promoting ecological management and healthy development in the Loess Plateau.
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Boron toxicity significantly hinders the growth and development of cotton plants, therefore affecting the yield and quality of this important cash crop worldwide. Limited studies have explored the efficacy of ZnSO4 (zinc sulfate) and ZnO nanoparticles (NPs) in alleviating boron toxicity. Nanoparticles
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Boron toxicity significantly hinders the growth and development of cotton plants, therefore affecting the yield and quality of this important cash crop worldwide. Limited studies have explored the efficacy of ZnSO4 (zinc sulfate) and ZnO nanoparticles (NPs) in alleviating boron toxicity. Nanoparticles have emerged as a novel strategy to reduce abiotic stress directly. The precise mechanism underlying the alleviation of boron toxicity by ZnO NPs in cotton remains unclear. In this study, ZnO NPs demonstrated superior potential for alleviating boron toxicity compared to ZnSO4 in hydroponically cultivated cotton seedlings. Under boron stress, plants supplemented with ZnO NPs exhibited significant increases in total fresh weight (75.97%), root fresh weight (39.64%), and leaf fresh weight (69.91%). ZnO NPs positively affected photosynthetic parameters and SPAD values. ZnO NPs substantially reduced H2O2 (hydrogen peroxide) by 27.87% and 32.26%, MDA (malondialdehyde) by 27.01% and 34.26%, and O2− (superoxide anion) by 41.64% and 48.70% after 24 and 72 h, respectively. The application of ZnO NPs increased the antioxidant activities of SOD (superoxide dismutase) by 82.09% and 76.52%, CAT (catalase) by 16.79% and 16.33%, and POD (peroxidase) by 23.77% and 21.66% after 24 and 72 h, respectively. ZnO NP and ZnSO4 application demonstrated remarkable efficiency in improving plant biomass, mineral nutrient content, and reducing boron levels in cotton seedlings under boron toxicity. A transcriptome analysis and corresponding verification revealed a significant up-regulation of genes encoding antioxidant enzymes, photosynthesis pathway, and ABC transporter genes with the application of ZnO NPs. These findings provide valuable insights for the mechanism of boron stress tolerance in cotton and provide a theoretical basis for applying ZnO NPs and ZnSO4 to reduce boron toxicity in cotton production.
Full article
Cell-free DNA (cfDNA) has recently emerged as a promising minimally invasive diagnostic biomarker for various cancers. In this study, our aim was to identify cfDNA biomarkers by investigating genes that displayed significant differences between glioma patients and their corresponding controls. To accomplish this,
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Cell-free DNA (cfDNA) has recently emerged as a promising minimally invasive diagnostic biomarker for various cancers. In this study, our aim was to identify cfDNA biomarkers by investigating genes that displayed significant differences between glioma patients and their corresponding controls. To accomplish this, we utilized publicly available data from the Gene Expression Omnibus, focusing on 5-hydroxymethylcytosine (5hmC) profiles in both cfDNA and genomic DNA (gDNA) from glioma patients and healthy individuals. The intersection of gene lists derived from these comparative analyses unveiled LRIG1 and ZNF703 as the two genes with elevated 5hmC levels in both the cfDNA of glioma patients and gDNA of glioma tissue compared to their respective controls. The gene expression data revealed both genes were upregulated in glioma tissue compared to normal brain tissue. Integration of 5hmC data revealed a strong positive correlation in the glioma tissue group between 5hmC and the gene expression of the LRIG1 gene. Furthermore, exploration using the AmiCa web tool indicated that LRIG1 gene expression was elevated compared to 17 other cancers included in the database, emphasizing its potential as a distinctive biomarker across multiple cancer types.
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In age determination, different methods aiming to obtain the closest result to chronological age have been investigated so far. The most commonly used one among these is the radiological method, which is usually used to evaluate the developmental stages of wrist bones or
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In age determination, different methods aiming to obtain the closest result to chronological age have been investigated so far. The most commonly used one among these is the radiological method, which is usually used to evaluate the developmental stages of wrist bones or teeth. In our study, we assessed bone age estimations using the Gilsanz–Ratib atlas (GRA), which has recently become commonly used for children aged 9 to 15 years; evaluated the dental age, determined with Cameriere’s European method; conducted morphometric measurements of the mandibular bone; and then examined their relationships with chronological age. The results of our study reveal that, in children during the puberty growth spurt, Cameriere’s EU formula might have higher accuracy in estimating chronological age in younger age groups, while the GRA might be more accurate for older ages. Additionally, we conclude that of the mandibular morphometric measurements, condylar height and tangential ramus height show strong positive correlations with age. As a result, we conclude that the morphometric measurements evaluated in the present study can be used as auxiliary methods in forensic anthropology and forensic dentistry.
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Gulf Cooperation Council (GCC) countries have faced environmental challenges in recent decades. This study aims to identify the contribution of digitalization, industrialization, and financial development to the ecological footprint (EF) in GCC countries between 2000 and 2021. The empirical investigation involves estimating the
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Gulf Cooperation Council (GCC) countries have faced environmental challenges in recent decades. This study aims to identify the contribution of digitalization, industrialization, and financial development to the ecological footprint (EF) in GCC countries between 2000 and 2021. The empirical investigation involves estimating the STochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model using the augmented mean group (AMG), common correlated effects mean group (CCEMG) and cross-sectionally augmented autoregressive distributed lag (CS-ARDL) estimators. The findings reveal the existence of long-term linkages between EF and the factors mentioned above. Furthermore, there is evidence that adopting digitalization and information and communication technologies (ICT) improves long-term environmental quality. In contrast, both industrialization and financial development exert detrimental effects on the environment. Finally, the JKS Granger non-causality test revealed that all variables, except financial development, predict environmental degradation in GCC countries. These findings can assist in formulating efficient strategies to reduce ecological degradation and achieve environmental sustainability in GCC countries.
Full article
Nanoporous (NP) gold, the most extensively studied and efficient NP metal, possesses exceptional properties that make it highly attractive for advanced technological applications. Notably, its remarkable catalytic properties in various significant reactions hold enormous potential. However, the exploration of its catalytic activity in
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Nanoporous (NP) gold, the most extensively studied and efficient NP metal, possesses exceptional properties that make it highly attractive for advanced technological applications. Notably, its remarkable catalytic properties in various significant reactions hold enormous potential. However, the exploration of its catalytic activity in the degradation of water pollutants remains limited. Nevertheless, previous research has reported the catalytic activity of NP Au in the degradation of methyl orange (MO), a toxic azo dye commonly found in water. This study aims to investigate the behavior of nanoporous gold in MO solutions using UV-Vis absorption spectroscopy and high-performance liquid chromatography. The NP Au was prepared by chemical removal of silver atoms of an AuAg precursor alloy prepared by ball milling. Immersion tests were conducted on both pellets and powders of NP Au, followed by examination of the residual solutions. Additionally, X-ray photoelectron spectroscopy and electrochemical impedance measurements were employed to analyze NP Au after the tests. The findings reveal that the predominant and faster process involves the partially reversible adsorption of MO onto NP Au, while the catalytic degradation of the dye plays a secondary and slower role in this system.
Full article
Spermatogenesis involves a complex process of cellular differentiation maintained by spermatogonial stem cells (SSCs). Being critical to male reproduction, it is generally assumed that spermatogenesis starts and ends in equivalent transcriptional states in related species. Based on single-cell gene expression profiling, it has
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Spermatogenesis involves a complex process of cellular differentiation maintained by spermatogonial stem cells (SSCs). Being critical to male reproduction, it is generally assumed that spermatogenesis starts and ends in equivalent transcriptional states in related species. Based on single-cell gene expression profiling, it has been proposed that undifferentiated human spermatogonia can be subclassified into four heterogenous subtypes, termed states 0, 0A, 0B, and 1. To increase the resolution of the undifferentiated compartment and trace the origin of the spermatogenic trajectory, we re-analysed the single-cell (sc) RNA-sequencing libraries of 34 post-pubescent human testes to generate an integrated atlas of germ cell differentiation. We then used this atlas to perform comparative analyses of the putative SSC transcriptome both across human development (using 28 foetal and pre-pubertal scRNA-seq libraries) and across species (including data from sheep, pig, buffalo, rhesus and cynomolgus macaque, rat, and mouse). Alongside its detailed characterisation, we show that the transcriptional heterogeneity of the undifferentiated spermatogonial cell compartment varies not only between species but across development. Our findings associate ‘state 0B’ with a suppressive transcriptomic programme that, in adult humans, acts to functionally oppose proliferation and maintain cells in a ready-to-react state. Consistent with this conclusion, we show that human foetal germ cells—which are mitotically arrested—can be characterised solely as state 0B. While germ cells with a state 0B signature are also present in foetal mice (and are likely conserved at this stage throughout mammals), they are not maintained into adulthood. We conjecture that in rodents, the foetal-like state 0B differentiates at birth into the renewing SSC population, whereas in humans it is maintained as a reserve population, supporting testicular homeostasis over a longer reproductive lifespan while reducing mutagenic load. Together, these results suggest that SSCs adopt differing evolutionary strategies across species to ensure fertility and genome integrity over vastly differing life histories and reproductive timeframes.
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Adjuvants enhance immune responses stimulated by vaccines. To date, many seasonal influenza vaccines are not formulated with an adjuvant. In the present study, the adjuvant Advax-SM™ was combined with next generation, broadly reactive influenza hemagglutinin (HA) vaccines that were designed using a computationally
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Adjuvants enhance immune responses stimulated by vaccines. To date, many seasonal influenza vaccines are not formulated with an adjuvant. In the present study, the adjuvant Advax-SM™ was combined with next generation, broadly reactive influenza hemagglutinin (HA) vaccines that were designed using a computationally optimized broadly reactive antigen (COBRA) methodology. Advax-SM™ is a novel adjuvant comprising inulin polysaccharide and CpG55.2, a TLR9 agonist. COBRA HA vaccines were combined with Advax-SM™ or a comparator squalene emulsion (SE) adjuvant and administered to mice intramuscularly. Mice vaccinated with Advax-SM™ adjuvanted COBRA HA vaccines had increased serum levels of anti-influenza IgG and IgA, high hemagglutination inhibition activity against a panel of H1N1 and H3N2 influenza viruses, and increased anti-influenza antibody secreting cells isolated from spleens. COBRA HA plus Advax-SM™ immunized mice were protected against both morbidity and mortality following viral challenge and, at postmortem, had no detectable lung viral titers or lung inflammation. Overall, the Advax-SM™-adjuvanted COBRA HA formulation provided effective protection against drifted H1N1 and H3N2 influenza viruses.
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Increasingly stringent pollutant emission regulations and a customer demand for a high-fuel economy drive the modern automotive industry to hurriedly solve the problem of decarbonization and powertrain efficiency, leading R&D towards alternative powertrain solutions and fuels. Electrification, today, plays the biggest role in
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Increasingly stringent pollutant emission regulations and a customer demand for a high-fuel economy drive the modern automotive industry to hurriedly solve the problem of decarbonization and powertrain efficiency, leading R&D towards alternative powertrain solutions and fuels. Electrification, today, plays the biggest role in the topic, with Mild Hybrid Electrified Vehicles (MHEVs) being the most cost-effective architectures, displaying dominance in smaller markets such as Brazil. One of the biggest challenges for HEVs’ development is the complexity of the hybrid control system, knowing when to actuate the electric machine, and the optimum power delivery, plus the gearshift schedule becomes a hard optimization problem that plays a key role in powertrain efficiency and cost savings for the customer. This paper proposes the implementation of a genetic algorithm (GA) as a machine learning-based control strategy to determine the torque split and the gear engaged for each driving condition of an MHEV operation, aiming to optimize fuel consumption. A quasi-static model of the vehicle was developed in Matlab/Simulink version 2022b, the virtual vehicle was then tested following the FTP75 and HWFET driving cycles. Simulation results indicate that the control decisions taken by the GA are qualitatively coherent for all operation conditions, and even quantitatively coherent in some cases, and that the software has the potential to be used as a control strategy outside the simulation environment, in future steps of development.
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Dust storms are significant atmospheric events that impact air quality, public health, and visibility, especially in arid Saudi Arabia. This study aimed to develop dust storm frequency predictions for Riyadh, Jeddah, and Dammam by integrating meteorological and environmental variables. Our models include multiple
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Dust storms are significant atmospheric events that impact air quality, public health, and visibility, especially in arid Saudi Arabia. This study aimed to develop dust storm frequency predictions for Riyadh, Jeddah, and Dammam by integrating meteorological and environmental variables. Our models include multiple linear regression, support vector machine, gradient boosting regression tree, long short-term memory (LSTM), and temporal convolutional network (TCN). This study highlights the effectiveness of LSTM and TCN models in capturing the complex temporal dynamics of dust storms and demonstrates that they outperform traditional methods, as evidenced by their lower mean absolute error (MAE) and root mean square error (RMSE) values and higher R2 score. In Riyadh, the TCN model demonstrates its remarkable performance, with an R2 score of 0.51, an MAE of 2.80, and an RMSE of 3.48, highlighting its precision, adaptability, and responsiveness to changes in dust storm frequency. Conversely, in Dammam, the LSTM model proved to be the most accurate, achieving an MAE of 3.02, RMSE of 3.64, and R2 score of 0.64. In Jeddah, the LSTM model also exhibited an MAE of 2.48 and an RMSE of 2.96. This research shows the potential of using deep learning models to improve the accuracy and reliability of dust storm frequency forecasts.
Full article
The maturation of B cells is a complex, multi-step process. During B cell differentiation, errors can occur, leading to the emergence of aberrant versions of B cells that, finally, constitute a malignant tumor. These B cell malignancies are classified into three main groups:
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The maturation of B cells is a complex, multi-step process. During B cell differentiation, errors can occur, leading to the emergence of aberrant versions of B cells that, finally, constitute a malignant tumor. These B cell malignancies are classified into three main groups: leukemias, myelomas, and lymphomas, the latter being the most heterogeneous type. Since their discovery, multiple biological studies have been performed to characterize these diseases, aiming to define their specific features and determine potential biomarkers for diagnosis, stratification, and prognosis. The rise of advanced -omics approaches has significantly contributed to this end. Notably, proteomics strategies appear as promising tools to comprehensively profile the final molecular effector of these cells. In this narrative review, we first introduce the main B cell malignancies together with the most relevant proteomics approaches. Then, we describe the core studies conducted in the field and their main findings and, finally, we evaluate the advantages and drawbacks of flow cytometry, mass cytometry, and mass spectrometry for the profiling of human B cell disorders.
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Seven novel porcine parvoviruses (nPPVs) (PPV2 through PPV8) have been described, although their pathogenicity and possible effects on porcine reproductive failure (PRF) are undefined. In this study, these nPPVs were assessed in gilts from Colombia; their coinfections with PPV1, PCV2, PCV3, PCV4, and
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Seven novel porcine parvoviruses (nPPVs) (PPV2 through PPV8) have been described, although their pathogenicity and possible effects on porcine reproductive failure (PRF) are undefined. In this study, these nPPVs were assessed in gilts from Colombia; their coinfections with PPV1, PCV2, PCV3, PCV4, and PRRSV and an association between the nPPVs and the reproductive performance parameters (RPPs) in sows were determined. For this, 234 serum samples were collected from healthy gilts from 40 herds in five Colombian regions, and the viruses were detected via real-time PCR. The results confirmed the circulation of PPV2 through PPV7 in Colombia, with PPV3 (40%), PPV5 (20%), and PPV6 (17%) being the most frequent. Additionally, no PCV4 or PPV8 was detected. PPV2 to PPV7 were detected in concurrence with each other and with the primary PRF viruses, and these coinfections varied from double to sextuple coinfections. Additionally, the association between nPPVs and PRF primary viruses was statistically significant for the presence of PPV6 in PCV3-positive (p < 0.01) and PPV5 in PPRSV-positive (p < 0.05) gilts; conversely, there was a significant presence of PPV3 in both PCV2-negative (p < 0.01) and PRRSV-negative (p < 0.05) gilts. Regarding the RPPs, the crude association between virus detection (positive or negative) and a high or low RPP was only statistically significant for PCV3 and the farrowing rate (FR), indicating that the crude odds of a low FR were 94% lower in herds with PCV3-positive gilts. This finding means that the detection of PCV3 in gilts (PCV3-positive by PCR) is associated with a higher FR in the farm or that these farms (with positive gilts) have lower odds (OR 0.06, p-value 0.0043) of a low FR. Additionally, a low FR tended to be associated with the detection of PPV4 and PPV5 (p-value < 0.20). This study is important for establishing the possible participation of nPPVs in PRF.
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As air pollution escalates, the need for air filters increases. It is better that the filters used be based on natural fibers, such as non-wood fibers, which cause low damage to the environment. However, the short fiber lengths, low apparent densities, and high
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As air pollution escalates, the need for air filters increases. It is better that the filters used be based on natural fibers, such as non-wood fibers, which cause low damage to the environment. However, the short fiber lengths, low apparent densities, and high volumes of non-wood materials can make it challenging to prepare filter paper with the required mechanical and physical properties. In that context, this study focused on utilizing bamboo fibers to fabricate filter paper by employing the anthraquinone soda pulping method. The pulp underwent bleaching and oxidation processes, with the incorporation of cationic starch (CS) and polyvinyl alcohol (PVA) to enhance resistance properties, resulting in the creation of handmade filter papers. The findings revealed that the tear, burst, and tensile strength of filter paper increased with the oxidation and addition of CS and PVA. Air permeability increased with addition of PVA and combination of CS and PVA. FTIR demonstrated the conversion of hydroxyl groups in cellulose chains to carboxyl groups due to oxidation. SEM images illustrated alterations in the fiber structure post-oxidation treatment, with CS reducing pores while PVA and the CS-PVA combination enlarged pore size and enhanced porosity. The BET surface area surface area expanded with oxidation and the addition of the CS-PVA blend, indicating heightened filter paper porosity. Notably, the combined inclusion of CS and PVA not only augmented mechanical strength but also increased porosity while maintaining pore size.
Full article
Weeds represent a serious drawback affecting the productivity of field crops worldwide. While the most common approach to control weeds in no-till practices is the use of glyphosate-based herbicides (GBHs), reducing their use represents a major challenge. This two-year field study aims to
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Weeds represent a serious drawback affecting the productivity of field crops worldwide. While the most common approach to control weeds in no-till practices is the use of glyphosate-based herbicides (GBHs), reducing their use represents a major challenge. This two-year field study aims to evaluate whether the use of cover crops (CC) in transgenic soybean and corn productions can (1) help control weeds and (2) reduce the amount of GBH needed for managing weeds. Sampling was carried out in 32 experimental field plots (four crop managements with four replicates on both crops). Crop managements consisted of GBH applications at rates of 0.84, 1.67, and 3.3 L ha−1 in plots in direct seeding with CC (DSCC) and at rates of 3.3 L ha−1 in plots without CC (DS). Weed cover rates, plant parameters (fresh and dry weights and heights), grain yields, water, and cation contents in soil were considered as indicators of interspecific competition. Results obtained in both years show that it is possible to reduce GBH use by 50% in plots with CC compared to plots without CC using a rate of GBH application of 3.33 L ha−1 (DS 3.3). However, weeds had a large impact on water content in soil, which was reflected by smaller plants and lower yields in plots with only 0.84 L ha−1 of GBH applied. In the context of the study, the use of CCs seems to facilitate the development of more sustainable agriculture while reducing the quantities of GBH generally used.
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Pulsed laser deposition (PLD) is a simple and extremely versatile technique to grow thin films and nanomaterials from a wide variety of materials. Compared to traditional fabrication methods, PLD is a clean physical vapour deposition approach that avoids complicated chemical reactions and by-products,
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Pulsed laser deposition (PLD) is a simple and extremely versatile technique to grow thin films and nanomaterials from a wide variety of materials. Compared to traditional fabrication methods, PLD is a clean physical vapour deposition approach that avoids complicated chemical reactions and by-products, achieving a precise stochiometric transfer of the target material onto the substrate and providing control over the film thickness. Halide perovskite materials have attracted extensive attention due to their excellent photoelectric and photovoltaic properties. In this paper, we present an overview of the fundamental and practical aspects of PLD. The properties and preparation methods of the halide perovskite materials are briefly discussed. Finally, we will elaborate on recent research on the preparation of perovskite solar cells by PLD, summarize the advantages and disadvantages of the PLD preparation, and prospect the all-vacuum PLD-grown solar cells in a full solar cell structure.
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This paper investigates the optimal remediation process in an aquifer using Modflow 6 software and genetic algorithms. A theoretical confined aquifer has been polluted over a long period of time by unnoticed leakage in a pipeline conveying leachate from an adjacent landfill to
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This paper investigates the optimal remediation process in an aquifer using Modflow 6 software and genetic algorithms. A theoretical confined aquifer has been polluted over a long period of time by unnoticed leakage in a pipeline conveying leachate from an adjacent landfill to a wastewater treatment plant. When the extended leakage and groundwater pollution are discovered, the optimal planning of the remediation strategy is investigated using the pump-and-treat method or/and hydrodynamic control of the pollution. The practical goal is to find the optimal locations and flow rates of two additional pumping wells, which will pump the polluted water or/and control pollution, protecting an existing drinking water pumping well, securing its fully operational mode even during the remediation process with the minimum possible cost, simply represented by the pumped water volume of the additional wells. The remediation process is considered complete when the maximum concentration in the aquifer drops below a certain limit. The Modflow software (handled by the Flopy Python package) simulates the flow field and advective–dispersive mass transport, and a genetic algorithm is used as the optimization tool. The coupled simulation–optimization model, Modflow-GA, complemented by a sophisticated post-processing results analysis, provides optimal and alternate sub-optimal remediation strategies for the decision makers to select from.
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Background and Objectives: Peripheral arterial stiffness (PAS), assessed by brachial-ankle pulse wave velocity (baPWV), is an independent biomarker of cardiovascular diseases (CVD) in patients on maintenance hemodialysis (HD). Malondialdehyde-modified low-density lipoprotein (MDA-LDL), an oxidative stress marker, has been linked to atherosclerosis and
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Background and Objectives: Peripheral arterial stiffness (PAS), assessed by brachial-ankle pulse wave velocity (baPWV), is an independent biomarker of cardiovascular diseases (CVD) in patients on maintenance hemodialysis (HD). Malondialdehyde-modified low-density lipoprotein (MDA-LDL), an oxidative stress marker, has been linked to atherosclerosis and CVD. However, the association between serum MDA-LDL and PAS among HD patients has not been fully elucidated. This study aimed to examine the association of serum MDA-LDL with PAS in HD patients and to identify the optimal cutoff value of serum MDA-LDL for predicting PAS. Materials and Methods: A cross-sectional study was conducted in 100 HD patients. Serum MDA-LDL was quantified using an enzyme-linked immunosorbent assay (ELISA), and baPWV was measured using a volume plethysmographic device. Patients were divided into the PAS group (baPWV > 18.0 m/s) and the non-PAS group (baPWV ≤ 18.0 m/s). The associations of baPWV and other clinical and biochemical parameters with serum MDA-LDL were assessed by multivariable logistic regression analyses. A receiver operating characteristic (ROC) curve analysis was performed to determine the optimal cutoff value of serum MDA-LDL for predicting PAS. Results: In multivariable logistic regression analysis, higher serum MDA-LDL, older age, and higher serum C-reactive protein [odds ratios (ORs) and 95% confidence intervals: 1.014 (1.004–1.025), 1.044 (1.004–1.085) and 3.697 (1.149–11.893)] were significantly associated with PAS. In the ROC curve analysis, the optimal cutoff value of MDA-LDL for predicting PAS was 80.91 mg/dL, with a sensitivity of 79.25% and a specificity of 59.57%. Conclusions: Greater serum MDA-LDL levels, particularly ≥80.91 mg/dL, were independently associated with PAS in HD patients. The findings suggest that oxidative stress plays a crucial role in the pathogenesis of PAS, and targeting MDA-LDL may be a potential therapeutic strategy for reducing cardiovascular risk in HD patients.
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In response to the shortcomings of the consensus algorithm for intellectual property transactions, such as high communication overhead, random primary node selection, and prolonged consensus time, a Practical Byzantine Fault Tolerance (PBFT) improvement algorithm based on Divisive Analysis (DIANA) D-PBFT algorithm is proposed.
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In response to the shortcomings of the consensus algorithm for intellectual property transactions, such as high communication overhead, random primary node selection, and prolonged consensus time, a Practical Byzantine Fault Tolerance (PBFT) improvement algorithm based on Divisive Analysis (DIANA) D-PBFT algorithm is proposed. Firstly, the algorithm adopts the hierarchical clustering mechanism of DIANA to cluster nodes based on similarity, enhancing node partition accuracy and reducing the number of participating consensus nodes. Secondly, it designs a reward and punishment system based on node ranking, to achieve consistency between node status and permissions, timely evaluation, and feedback on node behaviours, thereby enhancing node enthusiasm. Then, the election method of the primary node is improved by constructing proxy and alternate nodes and adopting a majority voting strategy to achieve the selection and reliability of the primary node. Finally, the consistency protocol is optimised to perform consensus once within the cluster and once between all primary nodes, to ensure the accuracy of the consensus results. Experimental results demonstrate that the D-PBFT algorithm shows a better performance, in terms of communication complexity, throughput, and latency.
Full article
The integration of Internet-of-Things technology with traditional agricultural irrigation is a crucial factor in the advancement of traditional agricultural irrigation towards smart irrigation. Despite the widespread use of conventional irrigation methods in many areas, they lead to the significant wastage of both human
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The integration of Internet-of-Things technology with traditional agricultural irrigation is a crucial factor in the advancement of traditional agricultural irrigation towards smart irrigation. Despite the widespread use of conventional irrigation methods in many areas, they lead to the significant wastage of both human and water resources. Therefore, the development of energy-saving and efficient intelligent irrigation systems through the application of Internet-of-Things technology and wireless communication technology is the way forward. This paper summarizes the common wireless communication technologies in the agricultural Internet of Things: Fifth-generation, WiFi, ZigBee, LoRa, and NB-IoT. The research status of the above wireless communication technology in agricultural irrigation management is discussed, and the agricultural irrigation management example using the above wireless communication technology is also presented. The advantages and limitations of the application of the above wireless communication technology in agricultural irrigation management are sorted out. Finally, this paper analyzes the challenges of data security issues, data fusion problems, intelligent irrigation system costs, power and energy problems, and system equipment failures faced by the use of IoT wireless communication technology in agricultural irrigation management. This review aims to assist researchers and users in choosing the most suitable wireless communication technology for diverse applications.
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In this article, when , we establish the -regularity of weak solutions to the degenerate parabolic p-Laplacian equation
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In this article, when , we establish the -regularity of weak solutions to the degenerate parabolic p-Laplacian equation on the group SU(3) granted with horizontal vector fields . Compared to the Heisenberg group, , we obtained the optimal range of p; that is, .
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Wearing masks is an effective protective measure for residents to prevent respiratory infectious diseases when going out. Due to issues such as a small target size, target occlusion leading to information loss, false positives, and missed detections, the effectiveness of face mask-wearing detection
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Wearing masks is an effective protective measure for residents to prevent respiratory infectious diseases when going out. Due to issues such as a small target size, target occlusion leading to information loss, false positives, and missed detections, the effectiveness of face mask-wearing detection needs improvement. To address these issues, an improved YOLOv7 object detection model is proposed. Firstly, the C2f_SCConv module is introduced in the backbone network to replace some ELAN modules for feature extraction, enhancing the detection performance of small targets. Next, the SPPFCSPCA module is proposed to optimize the spatial pyramid pooling structure, accelerating the model convergence speed and improving detection accuracy. Finally, the HAM_Detect decoupled detection head structure is introduced to mitigate missed and false detections caused by target occlusion, further accelerating model convergence and improving detection performance in complex environments. The experimental results show that improved YOLOv7 achieved an mAP of 90.1% on the test set, a 1.4% improvement over the original YOLOv7 model. The detection accuracy of each category improved, effectively providing technical support for mask-wearing detection in complex environments.
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Index insurance for forage, pasture, and rangeland has gained ground in policy and academic circles. Stakeholders promote it as an innovative risk management tool for enhancing resilience to drought-induced perils and providing a way for consumption smoothing to livestock producers in drought vulnerable
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Index insurance for forage, pasture, and rangeland has gained ground in policy and academic circles. Stakeholders promote it as an innovative risk management tool for enhancing resilience to drought-induced perils and providing a way for consumption smoothing to livestock producers in drought vulnerable ecosystems. Index insurance, which avoids market failures such as moral hazard, adverse selection, and transactional cost, has been piloted and implemented all over the world. To support future development and research on index-based insurance in livestock systems, operational index insurance for forage, pasture, and rangeland systems in developed (USA and Canada) and developing (Kenya and Ethiopia) countries are reviewed and compared. This paper finds some similar characteristics (huge subsidy payments—ranging from 50 to 100 percent, significant government role, low adoption, insufficient payouts, data challenges, etc.), of this product between the two regions. A major difference between the PRF and NDVI is the number of choices available to users of rainfall index insurance who face close to 3000 choice options, while NDVI users have less than 5 choice options available for them. Based on these insights, we highlight opportunities where the two regions can benchmark and improve upon their respective index insurance schemes—index-based livestock insurance (IBLI) in developing and rainfall index insurance for forage in developed regions.
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