MPNTEXT: An Interactive Platform for Automatically Extracting Metal-Polyphenol Networks and Their Applications from Scientific Literature.

In recent years, metal-polyphenol networks (MPNs) have gained significant attention due to their unique properties and broad applications across various fields. However, the burgeoning volume of MPN literature necessitates the automation of chemical information extraction from the extensive corpus of unstructured data, including scientific publications. To address this challenge, we proposed a platform named MPNTEXT, which utilized natural language processing techniques and machine learning algorithms to efficiently identify and extract pertinent information, thereby assisting users in comprehending complex MPNs and their textual descriptions of applications. Users can enter keywords, such as "Fe", "drug delivery", or "tannic acid", to retrieve relevant information, which is then presented in a structured format. This study aims to provide a user-friendly tool for collecting and retrieving MPN data and promotes data-driven material design. The platform offers researchers a more convenient and efficient way to design versatile MPNs and explore their applications.

A polymer-like ultrahigh-strength metal alloy.

Futuristic technologies such as morphing aircrafts and super-strong artificial muscles depend on metal alloys being as strong as ultrahigh-strength steel yet as flexible as a polymer1-3. However, achieving such 'strong yet flexible' alloys has proven challenging4-9 because of the inevitable trade-off between strength and flexibility5,8,10. Here we report a Ti-50.8 at.% Ni strain glass alloy showing a combination of ultrahigh yield strength of σy ≈ 1.8 GPa and polymer-like ultralow elastic modulus of E ≈ 10.5 GPa, together with super-large rubber-like elastic strain of approximately 8%. As a result, it possesses a high flexibility figure of merit of σy/E ≈ 0.17 compared with existing structural materials. In addition, it can maintain such properties over a wide temperature range of -80 °C to +80 °C and demonstrates excellent fatigue resistance at high strain. The alloy was fabricated by a simple three-step thermomechanical treatment that is scalable to industrial lines, which leads not only to ultrahigh strength because of deformation strengthening, but also to ultralow modulus by the formation of a unique 'dual-seed strain glass' microstructure, composed of a strain glass matrix embedded with a small number of aligned R and B19' martensite 'seeds'. In situ X-ray diffractometry shows that the polymer-like deformation behaviour of the alloy originates from a nucleation-free reversible transition between strain glass and R and B19' martensite during loading and unloading. This exotic alloy with the potential for mass producibility may open a new horizon for many futuristic technologies, such as morphing aerospace vehicles, superman-type artificial muscles and artificial organs.

High emission of black carbon in heavy-duty diesel vehicles: Insights from microscopic operating conditions.

The in-depth investigation of the high black carbon (BC) emission scenarios of heavy-duty diesel vehicles (HDDVs) is a crucial step toward developing effective control strategies. Chassis dynamometer tests were conducted for three in-use HDDVs, namely, vehicle #1, #2, and #3, focusing on the instantaneous BC characterizations during multiple driving conditions, i.e., speed phases and acceleration intervals. BC emission was found to increase with positive acceleration, and high acceleration could result in instantaneous BC spikes. The total BC emissions during velocity-acceleration interval 15-60 km h-1 and 0.1-0.9 m s-2 contributed to 43.4 ± 10.2 % of the whole-cycle emissions, while the proportions of time spent in the velocity-acceleration interval to the whole cycle were 23.1 ± 7.6 %. The cold-start microscopic operating condition was assessed by the cold-start extra emissions (CSEEs). Under various pre-defined cold-start durations, the proportions of CSEEs in the total cycle emissions were 9.4-21.0 %, 0-9.1 %, and 6.8-39.4 % for vehicles #1, #2, and #3, respectively. The CSEEs exhibited an initial rise, followed by a plateau as the assumed cold-start durations extended. A uniform cold-start duration of 600 s was established based on the criterion that the relative standard deviation (RSD) of CSEEs during the plateau period was <10 %. We proposed that the updated cold-start duration can enhance the accuracy and consistency of cold-start corrections in emission inventory models.

Application of machine reading comprehension techniques for named entity recognition in materials science.

Materials science is an interdisciplinary field that studies the properties, structures, and behaviors of different materials. A large amount of scientific literature contains rich knowledge in the field of materials science, but manually analyzing these papers to find material-related data is a daunting task. In information processing, named entity recognition (NER) plays a crucial role as it can automatically extract entities in the field of materials science, which have significant value in tasks such as building knowledge graphs. The typically used sequence labeling methods for traditional named entity recognition in material science (MatNER) tasks often fail to fully utilize the semantic information in the dataset and cannot effectively extract nested entities. Herein, we proposed to convert the sequence labeling task into a machine reading comprehension (MRC) task. MRC method effectively can solve the challenge of extracting multiple overlapping entities by transforming it into the form of answering multiple independent questions. Moreover, the MRC framework allows for a more comprehensive understanding of the contextual information and semantic relationships within materials science literature, by integrating prior knowledge from queries. State-of-the-art (SOTA) performance was achieved on the Matscholar, BC4CHEMD, NLMChem, SOFC, and SOFC-Slot datasets, with F1-scores of 89.64%, 94.30%, 85.89%, 85.95%, and 71.73%, respectively in MRC approach. By effectively utilizing semantic information and extracting nested entities, this approach holds great significance for knowledge extraction and data analysis in the field of materials science, and thus accelerating the development of material science.Scientific contributionWe have developed an innovative NER method that enhances the efficiency and accuracy of automatic entity extraction in the field of materials science by transforming the sequence labeling task into a MRC task, this approach provides robust support for constructing knowledge graphs and other data analysis tasks.

New Insights into the Genetic Basis of Lysine Accumulation in Rice Revealed by Multi-Model GWAS.

Lysine is an essential amino acid that cannot be synthesized in humans. Rice is a global staple food for humans but has a rather low lysine content. Identification of the quantitative trait nucleotides (QTNs) and genes underlying lysine content is crucial to increase lysine accumulation. In this study, five grain and three leaf lysine content datasets and 4,630,367 single nucleotide polymorphisms (SNPs) of 387 rice accessions were used to perform a genome-wide association study (GWAS) by ten statistical models. A total of 248 and 71 common QTNs associated with grain/leaf lysine content were identified. The accuracy of genomic selection/prediction RR-BLUP models was up to 0.85, and the significant correlation between the number of favorable alleles per accession and lysine content was up to 0.71, which validated the reliability and additive effects of these QTNs. Several key genes were uncovered for fine-tuning lysine accumulation. Additionally, 20 and 30 QTN-by-environment interactions (QEIs) were detected in grains/leaves. The QEI-sf0111954416 candidate gene LOC_Os01g21380 putatively accounted for gene-by-environment interaction was identified in grains. These findings suggested the application of multi-model GWAS facilitates a better understanding of lysine accumulation in rice. The identified QTNs and genes hold the potential for lysine-rich rice with a normal phenotype.

Biological and physiological effects in Bemisia tabaci feeding on tomatoes endophytically colonized by Beauveria bassiana.

BACKGROUND: Entomopathogenic fungi (EPF) treatment of plants may affect the survival and feeding preferences of herbivorous pests. However, comprehensive studies on the fitness across their entire life cycle, feeding behavior, and physiological changes in herbivores consuming EPF-treated plants within the tripartite interactions of EPF, plants, and pests are still limited. In this study, we utilized life tables, electrical penetration graph (EPG), and metabolomics to uncover the biological and physiological characteristics of Bemisia tabaci on tomato plants inoculated with Beauveria bassiana through root irrigation. RESULTS: Our study indicated that Beauveria bassiana Bb252 can penetrate the entire tissue from the point of inoculation, primarily colonizing the intercellular spaces and vascular tissue. However, this colonization is temporary, lasting no more than 35 days. Moreover, the population fitness and feeding behavior of Bemisia tabaci on tomato plants treated with Beauveria bassiana via root irrigation were significantly affected, showing a substantial 41.4% decrease in net reproductive rate (R0), a notable reduction in watery salivation, and shortened phloem ingestion. Lastly, we observed a significant decrease in hormones and amino acids of whiteflies that fed on Beauveria bassiana-treated tomato plants by root irrigation. CONCLUSIONS: Our results indicated that the endophyte, Beauveria bassiana Bb252, reduced demographic fitness of Bemisia tabaci by altering its hormones and amino acids levels. These findings enhance our understanding of multitrophic interactions in integrated pest management. © 2024 Society of Chemical Industry.

The drug loading capacity prediction and cytotoxicity analysis of metal-organic frameworks using stacking algorithms of machine learning.

Metal-organic frameworks (MOFs) have shown excellent performance in the field of drug delivery. Despite the synthesis of a vast array of MOFs exceeding 100,000 varieties, certain formulations have exhibited suboptimal performance characteristics. Therefore, there is a pressing need to enhance their efficacy by identifying MOFs with superior drug loading capacities and minimal cytotoxicity, which can be achieved through machine learning (ML). In this study, a stacking regression model was developed to predict drug loading capacity and cytotoxicity of MOFs using datasets compiled from various literature sources. The model exhibited exceptional predictive capabilities, achieving R2 values of 0.907 for drug loading capacity and 0.856 for cytotoxicity. Furthermore, various model interpretation methods including partial dependence plots, individual conditional expectation, Shapley additive explanation, decision tree, random forest, CatBoost Regressor, and light gradient-boosting machine were employed for feature importance analysis. The results revealed that specific metal atoms such as Zn, Cr, Fe, Zr, and Cu significantly influenced the drug loading capacity and cytotoxicity of MOFs. Through model validation encompassing experimental validation and computational verification, the reliability of the model was thoroughly established. In general, it is a good practice to use ML methods for predicting drug loading capacity and cytotoxicity analysis of MOFs, guiding the development of future property prediction methods for MOFs.

Regulatory Insights for On-Board Monitoring of Vehicular NOx Emission Compliance.

Nitrogen oxide (NOx) emissions from heavy-duty diesel vehicles (HDDVs) have adverse effects on human health and the environment. On-board monitoring (OBM), which can continuously collect vehicle performance and NOx emissions throughout the operation lifespan, is recognized as the core technology for future vehicle in-use compliance, but its large-scale application has not been reported. Here, we utilized OBM data from 22,520 HDDVs in China to evaluate their real-world NOx emissions. Our findings showed that China VI HDDVs had a 73% NOx emission reduction compared with China V vehicles, but a considerable proportion still faced a significant risk of higher NOx emissions than the corresponding limits. The unsatisfactory efficiency of the emission treatment system under disadvantageous driving conditions (e.g., low speed or ambient temperature) resulted in the incompliance of NOx emissions, especially for utility vehicles (sanitation/garbage trucks). Furthermore, the observed intertrip and seasonal variability of NOx emissions demonstrated the need for a long-term continuous monitoring protocol instead of instantaneous evaluation for the OBM. With both functions of emission monitoring and malfunction diagnostics, OBM has the potential to accurately verify the in-use compliance status of large-scale HDDVs and discern the responsibility of high-emitting activities from manufacturers, vehicle operators, and driving conditions.

Particulate matter emissions from light-duty gasoline vehicles under different ambient temperatures: Physical properties and chemical compositions.

Fine particulate matter (PM2.5) from vehicle exhaust is typically emitted at breathing height and thus imposes severe adverse effects on human health and air quality. However, there is currently limited knowledge on the characteristics of PM2.5 in exhaust, specifically its chemical components, at different ambient temperatures. Particulate emissions from typical light-duty gasoline vehicles (LDGVs) were investigated on a chassis dynamometer according to the Worldwide Harmonized Light-Duty Test Cycle at ambient temperatures of 38 °C, 28 °C, 15 °C, 5 °C and - 7 °C. The results showed a significant increase in particulate mass (PM) and particle number (PN) emissions with decreasing ambient temperature, particularly during cold starts below 5 °C. The particle size distributions exhibited distinct bimodal patterns, with accumulation-mode (AM) particles (60-125 nm) dominating the gasoline direct injection (GDI) distribution and nucleation-mode (NM) particles (8-12 nm) dominating the port fuel injection (PFI) distribution. AM particles were more temperature-sensitive than NM particles. Lower temperatures produced higher emissions of elements, carbonaceous components, and large-ring polycyclic aromatic hydrocarbons, while water-soluble ions showed an opposite trend. The total toxic equivalent, primarily influenced by benzo[a]pyrene, was significantly higher at -7 °C. The penalty distribution of LDGV PM and PN, defined by comparing the emissions at the various temperatures to those at regulated temperatures (23-30 °C), exhibited notable temporal heterogeneity (winter > autumn > spring > summer) and spatial heterogeneity (northern China > southern China). These findings are essential for establishing more stringent vehicle emission standards and improving emission models in cold environments.

Low-Field-Driven Superior Energy Storage Effect with Excellent Thermal Stability by Constructing Coexistent Glasses.

In this work, we found that the defreezing coexistent glassy ferroelectric states hold significant potential for achieving superior energy storage performance, especially under low fields, by using phase field simulations and experimental approaches. A remarkable room-temperature energy recoverable storage density Wr exceeding 2.7 J/cm3 with a high efficiency η surpassing 80% under a low electric field of 170 kV/cm was obtained in the x = 6-12% compositions of x[Bi(Mg2/3Nb1/3)O3]-(1-x)[0.94(Bi0.5Na0.5)TiO3-0.06BaTiO3-1%MnO2] (BNBT-BMN) ceramics due to the combination of low Pr and high Pm of the coexistent ferroelectric glasses. Intriguingly, the superior Wr and η of the coexistent state of glasses can also be maintained in a wide temperature range of 293-430 K, indicating the excellent thermal stability of the energy storage behavior. Importantly, the Wr and η of this glass coexistent composition increase upon heating from room temperature to 360 K due to the defreezing process, leading to maximum Wr ∼ 2.9 J/cm3 with high efficiency η ∼ 90% of x = 10% at 360 K. When considering both energy storage behavior and thermal stability under low fields (<250 kV/cm), the BNBT-BMN ceramics outperform nearly all lead-free counterparts available today. Consequently, our work not only expands the research scope of ferroic glasses but also establishes a new paradigm for developing superior lead-free dielectrics suitable for high-temperature energy storage devices.

Characterizing NOx emissions from diesel trucks with tampered aftertreatment systems and its implications for identifying high emitters.

Reducing the differences between real-world and certificated NOx emission levels is an important element of in-use emission surveillance programs. Therefore, investigating the characteristics of the vehicles which have much higher NOx emissions (i.e., high-emitters) and determining a reasonable cut-off point to identify high-emitters with a low false detection rate is important. In this study, six diesel trucks were tested under different aftertreatment conditions. The results showed that the discrepancies of fuel-specific NOx emissions between vehicles with functioning and tampered selective catalytic reduction (SCR) systems occur mainly from medium- to high-speed modes. This is because the SCR systems were at low conversion efficiencies when the exhaust temperature was low, including cold-start and urban creep conditions. By using binary classification, we selected fuel-specific NOx cut-off points for high-emitters from China V and China VI diesel trucks. The false detection rate of high-emitters can decrease by 33 % and 95 %, if only NOx emissions from medium- to high-speed modes were used for the chosen cut-off points, respectively. This work highlights the importance of in-use emission compliance programs. It also suggests that high-emitters can be more accurately identified at medium- to high-speed modes if using instantaneous emission data.

Ultrahigh Energy Storage in Tungsten Bronze Dielectric Ceramics Through a Weakly Coupled Relaxor Design.

Dielectric energy-storage capacitors, known for their ultrafast discharge time and high-power density, find widespread applications in high-power pulse devices. However, ceramics featuring a tetragonal tungsten bronze structure (TTBs) have received limited attention due to their lower energy-storage capacity compared to perovskite counterparts. Herein, a TTBs relaxor ferroelectric ceramic based on the Gd0.03 Ba0.47 Sr0.485-1.5 x Smx Nb2 O6 composition, exhibiting an ultrahigh recoverable energy density of 9 J cm-3 and an efficiency of 84% under an electric field of 660 kV cm-1 is reported. Notably, the energy storage performance of this ceramic shows remarkable stability against frequency, temperature, and cycling electric field. The introduction of Sm3+ doping is found to create weakly coupled polar nanoregions in the Gd0.03 Ba0.47 Sr0.485 Nb2 O6 ceramic. Structural characterizations reveal that the incommensurability parameter increases with higher Sm3+ content, indicative of a highly disordered A-site structure. Simultaneously, the breakdown strength is also enhanced by raising the conduction activation energy, widening the bandgap, and reducing the electric field-induced strain. This work presents a significant improvement on the energy storage capabilities of TTBs-based capacitors, expanding the material choice for high-power pulse device applications.

Characteristics of NOX and NH3 emissions from in-use heavy-duty diesel vehicles with various aftertreatment technologies in China.

Some in-use China IV and China V heavy-duty diesel vehicles (HDDVs) with selective catalytic reduction (SCR) systems probably fail to mitigate nitrogen oxide (NOX) emissions as expected. Meanwhile, these SCR-equipped HDDVs might emit excessive ammonia (NH3). To better understand the NOX and NH3 emissions from typical HDDVs in China, seventeen in-use vehicles with various emission-control technologies were tested by using laboratory chassis dynamometers. The results indicated that individual NOX and NH3 emissions from HDDV fleets widely varied owing to differences in aftertreatment performance. China V and VI HDDVs with effectively functioning SCRs could substantially control their NOX emissions to be below the corresponding emission limits (i.e., 4.0 and 0.69 g/kWh for China V and China VI vehicles, respectively) but with a potential risk of high NH3 emissions caused by diesel exhaust fluid (DEF) overdosing. Furthermore, higher vehicle speed and payload resulted in lower NOX emissions and possibly higher NH3 emissions from HDDVs with effectively functioning SCRs, while higher NOX emissions from tampered- and non-SCR HDDVs. NOX emissions from China VI HDDVs were more sensitive to cold starts compared to China V and earlier vehicles, but there was no significant discrepancy in NH3 emissions between cold- and hot-start tests.

Genome-wide association studies using multi-models and multi-SNP datasets provide new insights into pasmo resistance in flax.

Introduction: Flax (Linum usitatissimum L.) is an economically important crop due to its oil and fiber. However, it is prone to various diseases, including pasmo caused by the fungus Septoria linicola. Methods: In this study, we conducted field evaluations of 445 flax accessions over a five-year period (2012-2016) to assess their resistance to pasmo A total of 246,035 single nucleotide polymorphisms (SNPs) were used for genetic analysis. Four statistical models, including the single-locus model GEMMA and the multi-locus models FarmCPU, mrMLM, and 3VmrMLM, were assessed to identify quantitative trait nucleotides (QTNs) associated with pasmo resistance. Results: We identified 372 significant QTNs or 132 tag QTNs associated with pasmo resistance from five pasmo resistance datasets (PAS2012-PAS2016 and the 5-year average, namely PASmean) and three genotypic datasets (the all SNPs/ALL, the gene-based SNPs/GB and the RGA-based SNPs/RGAB). The tag QTNs had R2 values of 0.66-16.98% from the ALL SNP dataset, 0.68-20.54%from the GB SNP dataset, and 0.52-22.42% from the RGAB SNP dataset. Of these tag QTNs, 93 were novel. Additionally, 37 resistance gene analogs (RGAs)co-localizing with 39 tag QTNs were considered as potential candidates for controlling pasmo resistance in flax and 50 QTN-by-environment interactions(QEIs) were identified to account for genes by environmental interactions. Nine RGAs were predicted as candidate genes for ten QEIs. Discussion: Our results suggest that pasmo resistance in flax is polygenic and potentially influenced by environmental factors. The identified QTNs provide potential targets for improving pasmo resistance in flax breeding programs. This study sheds light on the genetic basis of pasmo resistance and highlights the importance of considering both genetic and environmental factors in breeding programs for flax.

Genome-Wide Association Studies Using 3VmrMLM Model Provide New Insights into Branched-Chain Amino Acid Contents in Rice Grains.

Rice (Oryza sativa L.) is a globally important food source providing carbohydrates, amino acids, and dietary fiber for humans and livestock. The branched-chain amino acid (BCAA) level is a complex trait related to the nutrient quality of rice. However, the genetic mechanism underlying the BCAA (valine, leucine, and isoleucine) accumulation in rice grains remains largely unclear. In this study, the grain BCAA contents and 239,055 SNPs of a diverse panel containing 422 rice accessions were adopted to perform a genome-wide association study (GWAS) using a recently proposed 3VmrMLM model. A total of 357 BCAA-content-associated main-effect quantitative trait nucleotides (QTNs) were identified from 15 datasets (12 BCAA content datasets and 3 BLUP datasets of BCAA). Furthermore, the allelic variation of two novel candidate genes, LOC_Os01g52530 and LOC_Os06g15420, responsible for the isoleucine (Ile) content alteration were identified. To reveal the genetic basis of the potential interactions between the gene and environmental factor, 53 QTN-by-environment interactions (QEIs) were detected using the 3VmrMLM model. The LOC_Os03g24460, LOC_Os01g55590, and LOC_Os12g31820 were considered as the candidate genes potentially contributing to the valine (Val), leucine (Leu), and isoleucine (Ile) accumulations, respectively. Additionally, 10 QTN-by-QTN interactions (QQIs) were detected using the 3VmrMLM model, which were putative gene-by-gene interactions related to the Leu and Ile contents. Taken together, these findings suggest that the implementation of the 3VmrMLM model in a GWAS may provide new insights into the deeper understanding of BCAA accumulation in rice grains. The identified QTNs/QEIs/QQIs serve as potential targets for the genetic improvement of rice with high BCAA levels.

Comprehensive Analysis of Metabolome and Transcriptome Reveals the Regulatory Network of Coconut Nutrients.

Coconut flesh is widely consumed in the market for its good flavor. However, a comprehensive and dynamic assessment of the nutrients in coconut flesh and their molecular regulatory mechanisms is lacking. In this study, the metabolite accumulation and gene expression of three representative coconut cultivars belonging to two subspecies were investigated using ultra performance liquid chromatography/tandem mass spectrometry. A total of 6101 features were detected, of which 52, 8, and 158 were identified as amino acids and derivatives, polyamines, and lipids, respectively. The analysis of the metabolite pathway showed that glutathione and α-linolenate were the main differential metabolites. Transcriptome data revealed significant differences in the expression of five glutathione structural genes and thirteen polyamine-regulated genes, consistent with trends in metabolite accumulation. Weighted correlation network and co-expression analyses showed that a novel gene WRKY28 was implicated in the regulation of lipid synthesis. These results broaden our understanding of coconut nutrition metabolism and provide new insights into the molecular basis of coconut nutrition metabolism.

Impacts on real-world extra cold start emissions: Fuel injection, powertrain, aftertreatment and ambient temperature.

Vehicles emit substantial amounts of pollutants during start periods. Engine starts mainly occur in urban areas, causing serious harm to humans. To investigate the impacts on extra cold start emissions (ECSEs), eleven China 6 vehicles with various control technologies (fuel injection, powertrain, and aftertreatment) were monitored with a portable emission measurement system (PEMS) at different temperatures. For conventional internal combustion engine vehicles (ICEVs), the average ECSEs of CO2 increased by 24%, while the average ECSEs of NOx and particle number (PN) decreased by 38% and 39%, respectively, with air conditioning (AC) on. Gasoline direct injection (GDI) vehicles had 5% lower CO2 ECSEs, but 261% higher NOx ECSEs and 318% higher PN ECSEs than port fuel injection (PFI) vehicles at 23 °C. The average PN ECSEs were significantly reduced by gasoline particle filters (GPFs). The GPF filtration efficiency was higher in GDI than PFI vehicles due to particle size distribution. Hybrid electric vehicles (HEVs) generated excessive PN extra start emissions (ESEs), resulting in a 518% increase compared to ICEVs. The start times of the GDI-engine HEV accounted for 11% of the whole test time, but the proportion of PN ESEs relative to total emissions were 23%. Linear simulation based on the decrease in ECSEs with increasing temperature underestimated the PN ECSEs from PFI and GDI vehicles by 39% and 21%, respectively. For ICEVs, CO ECSEs varied with temperature in a U shape with a minimum at 27 °C; NOx ECSEs decreased as ambient temperature increased; PFI vehicles generated more PN ECSEs at 32 °C than GDI vehicles, stressing the significance of ECSEs at high temperature. These results are useful for improving emission models and assessing air pollution exposure in urban aeras.

Variability of fuel consumption and CO2 emissions of a gasoline passenger car under multiple in-laboratory and on-road testing conditions.

An increasing divergence regarding fuel consumption (and/or CO2 emissions) between real-world and type-approval values for light-duty gasoline vehicles (LDGVs) has posed severe challenges to mitigating greenhouse gases (GHGs) and achieving carbon emissions peak and neutrality. To address this divergence issue, laboratory test cycles with more real-featured and transient traffic patterns have been developed recently, for example, the China Light-duty Vehicle Test Cycle for Passenger cars (CLTC-P). We collected fuel consumption and CO2 emissions data of a LDGV under various conditions based on laboratory chassis dynamometer and on-road tests. Laboratory results showed that both standard test cycles and setting methods of road load affected fuel consumption slightly, with variations of less than 4%. Compared to the type-approval value, laboratory and on-road fuel consumption of the tested LDGV over the CLTC-P increased by 9% and 34% under the reference condition (i.e., air conditioning off, automatic stop and start (STT) on and two passengers). On-road measurement results indicated that fuel consumption under the low-speed phase of the CLTC-P increased by 12% due to the STT off, although only a 4% increase on average over the entire cycle. More fuel consumption increases (52%) were attributed to air conditioning usage and full passenger capacity. Strong correlations (R2 > 0.9) between relative fuel consumption and average speed were also identified. Under traffic congestion (average speed below 25 km/hr), fuel consumption was highly sensitive to changes in vehicle speed. Thus, we suggest that real-world driving conditions cannot be ignored when evaluating the fuel economy and GHGs reduction of LDGVs.

Pannier is a key regulator of embryogenesis, pupal development and female reproduction in the insect pest Bactrocera dorsalis.

BACKGROUND: Most arthropods are famous for their large reproductive capacity, with the ovary playing a vital role in the process. The study of the regulatory mechanisms of ovarian development may have the potential for a reproduction-based pest management strategy. GATA-binding transcription factors (GATAs) as important regulatory factors mediate many physiological processes, including development, immunity, insecticide resistance and reproduction. The Pannier (pnr), a member of GATA family, was confirmed to be involved in ovarian development of Bactrocera dorsalis in our previous study. However, the direct evidence of pnr regulating the fly ovarian development is still lacking. RESULTS: We used CRISPR/Cas9 to create Bdpnr loss-of-function mutations. Homozygous Bdpnr-/- mutants were nonviable, with most individuals dying during embryogenesis, some surviving to the larval stages, and the remaining few dying during pupation. In contrast, heterozygous individuals reached the adult stage, but ovarian development was disrupted, with concomitant decreases in egg laying and hatching rates. We also found that two genes encoding vitellogenin proteins (BdVg1 and BdVg2) and the vitellogenin receptor (BdVgR) were significantly down-regulated in heterozygous mutants compared to wild-type controls. CONCLUSION: These results indicate that Bdpnr is required for embryonic and post-embryonic development, including the formation of ovaries. Bdpnr could therefore be considered as a molecular target for tephritid fly pest control. © 2022 Society of Chemical Industry.

Advances in emission control of diesel vehicles in China.

Diesel vehicles have caused serious environmental problems in China. Hence, the Chinese government has launched serious actions against air pollution and imposed more stringent regulations on diesel vehicle emissions in the latest China VI standard. To fulfill this stringent legislation, two major technical routes, including the exhaust gas recirculation (EGR) and high-efficiency selective catalytic reduction (SCR) routes, have been developed for diesel engines. Moreover, complicated aftertreatment technologies have also been developed, including use of a diesel oxidation catalyst (DOC) for controlling carbon monoxide (CO) and hydrocarbon (HC) emissions, diesel particulate filter (DPF) for particle mass (PM) emission control, SCR for the control of NOx emission, and an ammonia slip catalyst (ASC) for the control of unreacted NH3. Due to the stringent requirements of the China VI standard, the aftertreatment system needs to be more deeply integrated with the engine system. In the future, aftertreatment technologies will need further upgrades to fulfill the requirements of the near-zero emission target for diesel vehicles.