Design of Lidar Receiving Optical System with Large FoV and High Concentration of Light to Resist Background Light Interference.

Lidar has the advantages of high accuracy, high resolution, and is not affected by sunlight. It has been widely used in many fields, such as autonomous driving, remote sensing detection, and intelligent robots. However, the current lidar detection system belongs to weak signal detection and generally uses avalanche photoelectric detector units as detectors. Limited by the current technology, the photosensitive surface is small, the receiving field of view is limited, and it is easy to cause false alarms due to background light. This paper proposes a method based on a combination of image-side telecentric lenses, microlens arrays, and interference filters. The small-area element detector achieves the high-concentration reception of echo beams in a large field of view while overcoming the interference of ambient background light. The image-side telecentric lens realizes that the center lines of the echo beams at different angles are parallel to the central axis, and the focus points converge on the same focal plane. The microlens array collimates the converged light beams one by one into parallel light beams. Finally, a high-quality aspherical focusing lens is used to focus the light on the small-area element detector to achieve high-concentration light reception over a large field of view. The system achieves a receiving field of view greater than 40° for a photosensitive surface detector with a diameter of 75 µm and is resistant to background light interference.

Sealing solid agar in serum bottles for rapid isolation and long-term preservation of chemoautotrophic ammonia-oxidizing bacteria.

Ammonia-oxidizing bacteria (AOB) are ubiquitous on the earth and have broad applications in bioremediation. However, the number of their species with standing in nomenclature and deposited in Microbial Culture Collections still remains low. Moreover, only a few novel species have been reported over the last decades. In this study, we sealed agar in serum bottles to develop a kind of solid agar plate with the oxygen concentration in the headspace maintained at low levels. By using these plates, eight AOB isolates including two novel species were obtained. When AOB cells were grown on the sealed solid agar plates, the time to form visible colonies was largely reduced and the maximum diameter of colonies reached 2 mm, which makes the process of AOB isolation rapid and efficient. Based on five AOB isolates, the headspace oxygen concentration had a significant influence on AOB growth either on solid plate or in liquid culture. Especially, when grown under 21 % O2, the number of colonies formed on solid agar plates was very low and sometimes no visible colony formed. Besides the application on AOB isolation, the sealed solid agar plate was also effective for the enumeration and preservation of AOB cells. When preserved under room temperature for more than ten months, the AOB colonies on the plate could still be recovered. This method provides a feasible way to isolate more novel AOB species from the environment and deposit more species in Microbial Culture Collections.

Development of a novel membrane-based quorum-quenching microbial isolator for biofouling control: Process performance and microbial mechanism.

Quorum quenching (QQ) can mitigate biofouling in membrane bioreactors (MBRs) by inhibiting cell-to-cell communication. However, it is difficult to maintain long-term QQ activity. Here, a novel microbial isolator composed of tubular microfiltration membranes was developed to separate QQ bacteria (Rhodococcus sp. BH4) from sludge. The time to reach a transmembrane pressure of 50 kPa was delayed by 69.55 % (p = 0.002, Student's t test) in MBR with QQ microbial isolator (MBR-Q), compared to that in the control MBR (MBR-C) during stable operation. The concentration of proteins in the extracellular polymeric substances of sludge was reduced by 20.61 % in MBR-Q relative to MBR-C. The results of the bacterial community analyses indicated less enrichment of fouling-associated bacteria (e.g., Acinetobacter) but a higher abundance of QQ enzymes in MBR-Q than in MBR-C. This environmentally friendly technique can decrease the cleaning frequency and increase the membrane lifespan, thus improving the sustainability of MBR technology.

Flow interactions lead to self-organized flight formations disrupted by self-amplifying waves.

Collectively locomoting animals are often viewed as analogous to states of matter in that group-level phenomena emerge from individual-level interactions. Applying this framework to fish schools and bird flocks must account for visco-inertial flows as mediators of the physical interactions. Motivated by linear flight formations, here we show that pairwise flow interactions tend to promote crystalline or lattice-like arrangements, but such order is disrupted by unstably growing positional waves. Using robotic experiments on "mock flocks" of flapping wings in forward flight, we find that followers tend to lock into position behind a leader, but larger groups display flow-induced oscillatory modes - "flonons" - that grow in amplitude down the group and cause collisions. Force measurements and applied perturbations inform a wake interaction model that explains the self-ordering as mediated by spring-like forces and the self-amplification of disturbances as a resonance cascade. We further show that larger groups may be stabilized by introducing variability among individuals, which induces positional disorder while suppressing flonon amplification. These results derive from generic features including locomotor-flow phasing and nonreciprocal interactions with memory, and hence these phenomena may arise more generally in macroscale, flow-mediated collectives.

Recent advances on enhancing 3D printing quality of protein-based inks: A review.

3D printing is an additive manufacturing technology that locates constructed models with computer-controlled printing equipment. To achieve high-quality printing, the requirements on rheological properties of raw materials are extremely restrictive. Given the special structure and high modifiability under external physicochemical factors, the rheological properties of proteins can be easily adjusted to suitable properties for 3D printing. Although protein has great potential as a printing material, there are many challenges in the actual printing process. This review summarizes the technical considerations for protein-based ink 3D printing. The physicochemical factors used to enhance the printing adaptability of protein inks are discussed. The post-processing methods for improving the quality of 3D structures are described, and the application and problems of fourth dimension (4D) printing are illustrated. The prospects of 3D printing in protein manufacturing are presented to support its application in food and cultured meat. The native structure and physicochemical factors of proteins are closely related to their rheological properties, which directly link with their adaptability for 3D printing. Printing parameters include extrusion pressure, printing speed, printing temperature, nozzle diameter, filling mode, and density, which significantly affect the precision and stability of the 3D structure. Post-processing can improve the stability and quality of 3D structures. 4D design can enrich the sensory quality of the structure. 3D-printed protein products can meet consumer needs for nutritional or cultured meat alternatives.

Quantum random number generation based on phase reconstruction.

Quantum random number generator (QRNG) utilizes the intrinsic randomness of quantum systems to generate completely unpredictable and genuine random numbers, finding wide applications across many fields. QRNGs relying on the phase noise of a laser have attracted considerable attention due to their straightforward system architecture and high random number generation rates. However, traditional phase noise QRNGs suffer from a 50% loss of quantum entropy during the randomness extraction process. In this paper, we propose a phase-reconstruction quantum random number generation scheme, in which the phase noise of a laser is reconstructed by simultaneously measuring the orthogonal quadratures of the light field using balanced detectors. This enables direct discretization of uniform phase noise, and the min-entropy can achieve a value of 1. Furthermore, our approach exhibits inherent robustness against the classical phase fluctuations of the unbalanced interferometer, eliminating the need for active compensation. Finally, we conducted experimental validation using commercial optical hybrid and balanced detectors, achieving a random number generation rate of 1.96 Gbps at a sampling rate of 200 MSa/s.

Towards generalizable food source identification: An explainable deep learning approach to rice authentication employing stable isotope and elemental marker analysis.

In addressing the generalization issue faced by data-driven methods in food origin traceability, especially when encountering diverse input variable sets, such as elemental contents (C, N, S), stable isotopes (C, N, S, H and O) and 43 elements measured under varying laboratory conditions. We introduce an innovative, versatile deep learning-based framework incorporating explainable analysis, adept at determining feature importance through learned neuron weights. Our proposed framework, validated using three rice sample batches from four Asian countries, totaling 354 instances, exhibited exceptional identification accuracy of up to 97%, surpassing traditional reference methods like decision tree and support vector machine. The adaptable methodological system accommodates various combinations of traceability indicators, facilitating seamless replication and extensive applicability. This groundbreaking solution effectively tackles generalization challenges arising from disparate variable sets across distinct data batches, paving the way for enhanced food origin traceability in real-world applications.

Co-aggregation as A Simple Strategy for Preparing Fluorogenic Tetrazine Probes with On-Demand Fluorogen Selection.

Life science has progressed with applications of fluorescent probes-fluorophores linked to functional units responding to biological events. To meet the varied demands across experiments, simple organic reactions to connect fluorophores and functional units have been developed, enabling the on-demand selection of fluorophore-functional unit combinations. However, organic synthesis requires professional equipment and skills, standing as a daunting task for life scientists. In this study, we present a simple, fast, and convenient strategy for probe preparation: co-aggregation of hydrophobic molecules. We focused on tetrazine-a difficult-to-prepare yet useful functional unit that provides effective bioorthogonal reactivity and strong fluorogenicity. Simply mixing the tetrazine molecules and aggregation-induced emission (AIE) luminogens in water, co-aggregation is induced, and the emission of AIE luminogens is quenched. Subsequent click reaction bioorthogonally turns on the emission, identifying these coaggregates as fluorogenic probes. Thanks to this bioorthogonal fluorogenicity, we established a new time-gated fluorescence bioimaging technique to distinguish overlapping emission signals, enabling multi-organelle imaging with two same-color fluorophores. Our study showcases the potential of this co-aggregation method for the on-demand preparation of fluorescent probes as well as protocols and molecular design principles in this approach, offering an effective solution to evolving needs in life science research.

Seawater Accelerated the Aging of Polystyrene and Enhanced Its Toxic Effects on Caenorhabditis elegans.

Microplastics (MPs) are emerging pollutants and pose a significant threat to marine ecosystems. Although previous studies have documented the mechanisms and toxic effects of aging MPs in various environments, the impact of the marine environment on MPs remains unclear. In the present study, the aging process of polystyrene (PS) in seawater was simulated and the changes in its physicochemical properties were investigated. Our results showed that the surface of the PS eroded in the seawater, which was accompanied by the release of aged MPs with a smaller size. In situ optical photothermal infrared microspectroscopy revealed that the mechanism of PS aging was related to the opening of the carbonyl group and breaking of the bond between carbon and benzene removal. To verify the toxic effects of aged PS, Caenorhabditis elegans was exposed to PS. Aged PS resulted in a greater reduction in locomotion, vitality, and reproduction than virgin PS. Mechanistically, aged PS led to oxidative stress, high glutathione s-transferase activity, and high total glutathione in worms. Together, our findings provided novel information regarding the accelerated aging of PS in seawater and the increased toxicity of aged PS, which could improve our understanding of MPs' ecotoxicity in the marine environment.

Microplastics released from disposable medical devices and their toxic responses in Caenorhabditis elegans.

Owing to accelerated urbanization and industrialization, many plastic products have been manufactured and discharged into the environment, causing environmental and public health problems. Plastics in environmental media are further degraded by prolonged exposure to light, heat, mechanical friction, and other factors to form new pollutants called microplastics (MPs). Medical plastics have become a crucial source of plastics in environmental media. However, the release profiles of MPs from medical plastics and their potential ecological and health risks remain unclear. We used optical photothermal infrared spectroscopy to explore the release profiles of eight typical disposable medical devices under high-temperature steam disinfection (HSD). We also evaluated the toxicity of disposable medical devices-derived MPs in Caenorhabditis elegans (C. elegans). Our results showed that the changes in the surface morphology and modification of the disposable medical devices were mainly associated with the material. Polypropylene (PP) and polystyrene (PS) materials exhibited high aging phenomena (e.g., bumps, depressions, bulges and cracks), and HSD broke their oxygen-containing functional groups and carbon chains. By contrast, minor changes in the chemical and physical properties were observed in the polyvinyl chloride (PVC)-prepared disposable medical devices under the same conditions. Further physicochemical characterization indicated that the amount of MPs released from PP-prepared disposable medical devices (P4: 1.27 ± 0.34 × 106) was greater than that from PVC-prepared disposable medical devices (P7: 1.08 ± 0.14 × 105). The particle size of the released MPs was the opposite, PVC-prepared disposable medical devices (P7: 11.45 ± 1.79 µm) > PP-prepared disposable medical devices (P4: 7.18 ± 0.52 µm). Toxicity assessment revealed that disposable medical devices-released MPs significantly increased germ cell apoptosisin C. elegans. Moreover, MPs from PP-prepared disposable medical devices disrupted the intestinal barrier of worms, decreasing their lifespan. Our findings provided novel information regarding the profiles and mechanisms of MP release from disposable medical devices and revealed their potential risks to ecological environment.

The implications for potential marginal land resources of cassava across worldwide under climate change challenges.

The demand for energy plants is foreseen to grow as worldwide energy and climate policies promote the use of bioenergy for climate change mitigation. To avoid competing with food production, it's critical to assess future changes in marginal land availability for energy plant development. Using a machine learning method, boosted regression tree, this study modeled potential marginal land resources suitable for cassava under current and different climate change scenarios, based on cassava occurrence records and environmental covariates. The findings revealed that, currently, over 80% of the 1357.24 Mha of available marginal land for cassava cultivation is distributed in Africa and South America. Under three climate change scenarios, by 2030, worldwide suitable marginal land resources were predicted to grow by 39.71Mha, 66.21 Mha, and 39.31Mha for the RCP4.5, RCP6.0, and RCP8.5 scenarios, respectively; by 2050, the potential marginal land suitable for cassava will increase by 38.98Mha, 83.02 Mha, and 55.43Mha, respectively; by 2080, the global marginal land resources were estimated to rise by 40.82 Mha, 99.74 Mha, and 21.87 Mha from now, respectively. Our results highlight the impacts of climate change on potential marginal land resources of cassava across worldwide, which provide the basis for assessing bioenergy potential in the future.

An integrated deep-learning and multi-level framework for understanding the behavior of terrorist groups.

Human security is threatened by terrorism in the 21st century. A rapidly growing field of study aims to understand terrorist attack patterns for counter-terrorism policies. Existing research aimed at predicting terrorism from a single perspective, typically employing only background contextual information or past attacks of terrorist groups, has reached its limits. Here, we propose an integrated deep-learning framework that incorporates the background context of past attacked locations, social networks, and past actions of individual terrorist groups to discover the behavior patterns of terrorist groups. The results show that our framework outperforms the conventional base model at different spatio-temporal resolutions. Further, our model can project future targets of active terrorist groups to identify high-risk areas and offer other attack-related information in sequence for a specific terrorist group. Our findings highlight that the combination of a deep-learning approach and multi-scalar data can provide groundbreaking insights into terrorism and other organized violent crimes.

Sequencing trait-associated mutations to clone wheat rust-resistance gene YrNAM.

Stripe (yellow) rust, caused by Puccinia striiformis f. sp. tritici (Pst), can significantly affect wheat production. Cloning resistance genes is critical for efficient and effective breeding of stripe rust resistant wheat cultivars. One resistance gene (Yr10CG) underlying the Pst resistance locus Yr10 has been cloned. However, following haplotype and linkage analyses indicate the presence of additional Pst resistance gene(s) underlying/near Yr10 locus. Here, we report the cloning of the Pst resistance gene YrNAM in this region using the method of sequencing trait-associated mutations (STAM). YrNAM encodes a non-canonical resistance protein with a NAM domain and a ZnF-BED domain. We show that both domains are required for resistance. Transgenic wheat harboring YrNAM gene driven by its endogenous promoter confers resistance to stripe rust races CYR32 and CYR33. YrNAM is an ancient gene and present in wild wheat species Aegilops longissima and Ae. sharonensis; however, it is absent in most wheat cultivars, which indicates its breeding value.

Exploring the worldwide impact of COVID-19 on conflict risk under climate change.

Objectives: Understand whether and how the COVID-19 pandemic affects the risk of different types of conflict worldwide in the context of climate change. Methodology: Based on the database of armed conflict, COVID-19, detailed climate, and non-climate data covering the period 2020-2021, we applied Structural Equation Modeling specifically to reorganize the links between climate, COVID-19, and conflict risk. Moreover, we used the Boosted Regression Tree method to simulate conflict risk under the influence of multiple factors. Findings: The transmission risk of COVID-19 seems to decrease as the temperature rises. Additionally, COVID-19 has a substantial worldwide impact on conflict risk, albeit regional and conflict risk variations exist. Moreover, when testing a one-month lagged effect, we find consistency across regions, indicating a positive influence of COVID-19 on demonstrations (protests and riots) and a negative relationship with non-state and violent conflict risk. Conclusion: COVID-19 has a complex effect on conflict risk worldwide under climate change. Implications: Laying the theoretical foundation of how COVID-19 affects conflict risk and providing some inspiration for the implementation of relevant policies.

Using the inner membrane of Escherichia coli as a scaffold to anchor enzymes for metabolic flux enhancement.

Clustering enzymes in the same metabolic pathway is a natural strategy to enhance productivity. Synthetic protein, RNA and DNA scaffolds have been designed to artificially cluster multiple enzymes in the cell, which require complex construction processes and possess limited slots for target enzymes. We utilized the Escherichia coli inner cell membrane as a native scaffold to cluster four fatty acid synthases (FAS) and achieved to improve the efficiency of fatty acid synthesis in vivo. The construction strategy is as simple as fusing target enzymes to the N-terminus or C-terminus of the membrane anchor protein (Lgt), and the number of anchored enzymes is not restricted. This novel device not only presents a similar efficiency in clustering multiple enzymes to that of other artificial scaffolds but also promotes the product secretion, driving the entire metabolic flux forward and further increasing the gross yield compared with that in a cytoplasmic scaffold system.

Pollen viability-based heat susceptibility index (HSIpv): A useful selection criterion for heat-tolerant genotypes in wheat.

Terminal heat stress during reproductive stage in wheat (Triticum aestivum L.) causes pollen grain sterility and has a drastic impact on wheat crop production. Finding genotypes with high pollen viability under heat stress is crucial to cope with the impact of climate change through developing heat-tolerant cultivars. To assess the effect of terminal heat stress on pollen viability in a panel of spring wheat genotypes (N = 200), RCBD (randomized complete block design) field trials were conducted under normal and heat stress conditions for two consecutive years (2020-2021 and 2021-2022). Analysis of variance showed significant variation in genotypes, treatments, and genotype × treatment interaction. Fifty and 46 genotypes were categorized as heat tolerant (HSI pv < 0.5) in the first and second year, respectively. Twelve genotypes, namely, Chenab-70, Pari-73, Pak-81, MH-21, Punjab-76, NIFA-Aman, NUWYT-63, Swabi-1, Nisnan-21, Frontana, Amin-2000, and Pirsabak-2004, were found to be heat tolerant across the years. The violin plot displayed a trend of improvement in heat tolerance (HSI pv < 0.5) over the period of time in many modern wheat varieties. However, some modern wheat varieties released after 2001 such as Janbaz-09 (57%), Ghazi-2019 (57%), and Sindhu-16 (43%) had very low pollen viability under heat stress conditions. The results of phenotypic coefficient of variance (PCV%), genotypic coefficient of variance (GCV%), broad sense heritability (h2 bs), and genetic advance (GA) suggested the major contribution of genetic factors in controlling pollen viability trait. Higher values of h2 bs and GA under heat stress conditions suggested pollen viability as a heat tolerance trait controlled by additive genetic effects. Taken together, these results suggested pollen viability as a useful trait for selection in early generations under elevated temperatures. The genotypes identified as heat tolerant in both years can be used as genetic resources for breeding cultivars with higher pollen viability under elevated temperature conditions.

Secrecy performance analysis in the FSO communication system considering different eavesdropping scenarios.

In this paper, we numerically study the secrecy performance of the free-space optical (FSO) system by considering different eavesdropping scenarios. More precisely, we considered three possible eavesdropping scenarios for Eve: 1) Eve is between Alice and Bob; 2) Eve and Bob are in the same receiving plane; 3) Eve is behind Bob. We adopt the Málaga (M)-distribution channel to model atmospheric turbulence due to the presence of link blockage while considering the non-zero boresight pointing error and path loss. To do so, we obtain a novel probability density function (PDF) and cumulative distribution function (CDF) under different eavesdropping scenarios, based on which we derived the secrecy outage probability (SOP) analytical expressions as well as their asymptotic expressions at a high SNR regime. We verified the results using Monte Carlo simulations, which showed that the parameters related to atmospheric turbulence and pointing errors, as well as the location of the eavesdropper, have different effects on different eavesdropping scenarios.

Domestication of newly evolved hexaploid wheat-A journey of wild grass to cultivated wheat.

Domestication of wheat started with the dawn of human civilization. Since then, improvement in various traits including resistance to diseases, insect pests, saline and drought stresses, grain yield, and quality were improved through selections by early farmers and then planned hybridization after the discovery of Mendel's laws. In the 1950s, genetic variability was created using mutagens followed by the selection of superior mutants. Over the last 3 decades, research was focused on developing superior hybrids, initiating marker-assisted selection and targeted breeding, and developing genetically modified wheat to improve the grain yield, tolerance to drought, salinity, terminal heat and herbicide, and nutritive quality. Acceptability of genetically modified wheat by the end-user remained a major hurdle in releasing into the environment. Since the beginning of the 21st century, changing environmental conditions proved detrimental to achieving sustainability in wheat production particularly in developing countries. It is suggested that high-tech phenotyping assays and genomic procedures together with speed breeding procedures will be instrumental in achieving food security beyond 2050.

Mapping QTL for Adult-Plant Resistance to Stripe Rust in a Chinese Wheat Landrace.

Wheat stripe (yellow) rust is a worldwide disease that seriously reduces wheat grain yield and quality. Adult-plant resistance (APR) to stripe rust is generally more durable but usually controlled by multiple genes with partial resistance. In this study, a recombinant inbred line population was developed from a cross between a Chinese wheat landrace, Tutoumai, with APR to stripe rust, and a highly susceptible wheat cultivar, Siyang 936. The population was genotyped by genotyping-by-sequencing and phenotyped for APR to stripe rust in four consecutive field experiments. Three QTLs, QYr.sdau-1BL, QYr.sdau-5BL, and QYr.sdau-6BL, were identified for APR to stripe rust, and explained 8.0-21.2%, 10.1-22.7%, and 11.6-18.0% of the phenotypic variation, respectively. QYr.sdau-1BL was further mapped to a 21.6 Mb region using KASP markers derived from SNPs identified by RNA-seq of the two parents. In the QYr.sdau-1BL region, 13 disease-resistance-related genes were differently expressed between the two parents, and therefore were considered as the putative candidates of QYr.sdau-1BL. This study provides favorable gene/QTL and high-throughput markers to breeding programs for marker-assisted selection of the wheat stripe rust APR genes.

The CC-NB-LRR protein BSR1 from Brachypodium confers resistance to Barley stripe mosaic virus in gramineous plants by recognising TGB1 movement protein.

Although some nucleotide binding, leucine-rich repeat immune receptor (NLR) proteins conferring resistance to specific viruses have been identified in dicot plants, NLR proteins involved in viral resistance have not been described in monocots. We have used map-based cloning to isolate the CC-NB-LRR (CNL) Barley stripe mosaic virus (BSMV) resistance gene barley stripe resistance 1 (BSR1) from Brachypodium distachyon Bd3-1 inbred line. Stable BSR1 transgenic Brachypodium line Bd21-3, barley (Golden Promise) and wheat (Kenong 199) plants developed resistance against BSMV ND18 strain. Allelic variation analyses indicated that BSR1 is present in several Brachypodium accessions collected from countries in the Middle East. Protein domain swaps revealed that the intact LRR domain and the C-terminus of BSR1 are required for resistance. BSR1 interacts with the BSMV ND18 TGB1 protein in planta and shows temperature-sensitive antiviral resistance. The R390 and T392 residues of TGB1ND (ND18 strain) and the G196 and K197 residues within the BSR1 P-loop motif are key amino acids required for immune activation. BSR1 is the first cloned virus resistance gene encoding a typical CNL protein in monocots, highlighting the utility of the Brachypodium model for isolation and analysis of agronomically important genes for crop improvement.