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Abstract Optical materials capable of dynamically manipulating electromagnetic waves are an emerging field in memories, optical modulators, and thermal management. Recently, their multispectral design preliminarily attracts much attention, aiming to enhance their efficiency and integration of functionalities. However, the multispectral manipulation based on these materials is challenging due to their ubiquitous wavelength dependence restricting their capacity to narrow wavelengths. In this article, we cascade multiple tunable optical cavities with selective-transparent layers, enabling a universal approach to overcoming wavelength dependence and establishing a multispectral platform with highly integrated functions. Based on it, we demonstrate the multispectral (ranging from 400 nm to 3 cm), fast response speed (0.9 s), and reversible manipulation based on a typical phase change material, vanadium dioxide. Our platform involves tandem VO2-based Fabry–Pérot (F-P) cavities enabling the customization of optical responses at target bands independently. It can achieve broadband color-changing capacity in the visible region (a shift of ~60 nm in resonant wavelength) and is capable of freely switching between three typical optical models (transmittance, reflectance, and absorptance) in the infrared to microwave regions with drastic amplitude tunability exceeding 0.7. This work represents a state-of-art advance in multispectral optics and material science, providing a critical approach for expanding the multispectral manipulation ability of optical systems.

Accurately forecasting the infrared radiation properties of multilayer systems exhibiting phase transition behavior presents a formidable challenge. In this study, we propose a physically-inspired Phase Transition Adaptation Model (PTAM) that leverages a deep neural network with a branching architecture, coupled with an analytical optical solver. Given the inherent difficulty in accurately measuring film thickness and the inability to test optical constants in situ, we employ a semi-self-supervised learning strategy and train the model exclusively using experimental twin spectral data generated by VO2-based smart radiation devices (SRDs) during the thermal phase transition process. Our proposed model exhibits remarkable proficiency in capturing spatial distribution information pertaining to material characteristics in multilayer systems possessing thermochromic phenomena. Additionally, it demonstrates exceptional accuracy in predicting the radiation regulation performance of such systems. These advances have significant implications for the cost-effective and efficient development of SRDs. In line with the pressing need to combat climate change and promote sustainable energy practices, this research makes a vital contribution to the quest for a more sustainable future.

The heating and cooling of enclosure space consume a large part of the global energy and contribute to the rise of extreme weather and the greenhouse effect. The radiative cooling and heating function by emitting infrared waves is a passive thermal management strategy, yet most of the research ignored the effect of inner radiance on the object temperature in enclosed spaces. Herein, a tunable Janus emitter with two types of multilayer configuration consisting of VO2/SiO2/ITO was designed and achieved controllable unidirectional emission for thermal management of enclosed spaces. The Fabry-Perot cavity helps create asymmetrical infrared emission on the separate sides, as well as tunable emissions are produced on both sides when the metal-insulating transition of VO2 occurs. This design results in not only remarkable thermal management within enclosed spaces, but also controllable heat insulation and release ability for outdoor spaces. This work may provide new strategies for energy saving, personal thermal management, and other facilities.

Abstract Background Fatty acids composition in poultry muscle is directly related to its tenderness, flavour, and juiciness, whereas its genetic mechanisms have not been elucidated. In this study, the genetic structure and key regulatory genes of the breast muscle fatty acid composition of local Chinese chicken, Gushi-Anka F2 resource population by integrating genome-wide association study (GWAS) and weighted gene co-expression network analysis (WGCNA) strategies. GWAS was performed based on 323,306 single nucleotide polymorphisms (SNPs) obtained by genotyping by sequencing (GBS) method and 721 chickens from the Gushi-Anka F2 resource population with highly variable fatty acid composition traits in the breast muscle. And then, according to the transcriptome data of the candidate genes that were obtained and phenotypic data of fatty acid composition traits in breast muscle of Gushi chickens at 14, 22, and 30 weeks of age, we conducted a WGCNA. Results A total of 128 suggestive significantly associated SNPs for 11 fatty acid composition traits were identified and mapped on chromosomes (Chr) 2, 3, 4, 5, 13, 17, 21, and 27. Of these, the two most significant SNPs were Chr13:5,100,140 (P = 4.56423e-10) and Chr13:5,100,173 (P = 4.56423e-10), which explained 5.6% of the phenotypic variation in polyunsaturated fatty acids (PUFA). In addition, six fatty acid composition traits, including C20:1, C22:6, saturated fatty acid (SFA), unsaturated fatty acids (UFA), PUFA, and average chain length (ACL), were located in the same QTL intervals on Chr13. We obtained 505 genes by scanning the linkage disequilibrium (LD) regions of all significant SNPs and performed a WGCNA based on the transcriptome data of the above 505 genes. Combining two strategies, 9 hub genes (ENO1, ADH1, ASAH1, ADH1C, PIK3CD, WISP1, AKT1, PANK3, and C1QTNF2) were finally identified, which could be the potential candidate genes regulating fatty acid composition traits in chicken breast muscle. Conclusion The results of this study deepen our understanding of the genetic mechanisms underlying the regulation of fatty acid composition traits, which is helpful in the design of breeding strategies for the subsequent improvement of fatty acid composition in poultry muscle.

Neurodegeneration is a pathological condition in which nervous system or neuron losses its structure, function, or both leading to progressive neural degeneration. Growing evidence strongly suggests that reduction of plasmalogens (Pls), one of the key brain lipids, might be associated with multiple neurodegenerative diseases, including Alzheimer’s disease (AD). Plasmalogens are abundant members of ether-phospholipids. Approximately 1 in 5 phospholipids are plasmalogens in human tissue where they are particularly enriched in brain, heart and immune cells. In this study, we employed a scheme of 2-months Pls intragastric administration to aged female C57BL/6J mice, starting at the age of 16 months old. Noticeably, the aged Pls-fed mice exhibited a better cognitive performance, thicker and glossier body hair in appearance than that of aged control mice. The transmission electron microscopic (TEM) data showed that 2-months Pls supplementations surprisingly alleviate age-associated hippocampal synaptic loss and also promote synaptogenesis and synaptic vesicles formation in aged murine brain. Further RNA-sequencing, immunoblotting and immunofluorescence analyses confirmed that plasmalogens remarkably enhanced both the synaptic plasticity and neurogenesis in aged murine hippocampus. In addition, we have demonstrated that Pls treatment inhibited the age-related microglia activation and attenuated the neuroinflammation in the murine brain. These findings suggest for the first time that Pls administration might be a potential intervention strategy for halting neurodegeneration and promoting neuroregeneration.

The buckling, de-lamination, and cracking of the thin film/substrate system caused by thermal stress is the main obstacle for functional failure. Moreover, the thermal stress of vanadium dioxide (VO2) thin film may be more complicated due to the stress re-distribution caused by phase transition. Therefore, the thermal stress of VO2 thin films deposited on four substrates with different materials (fused silica, silicon slice, sapphire, and glass) has been studied by finite element method in the present work. The influences of external temperature, substrate, and interlayer on thermal stress were analyzed. It was found that the substrates can greatly affect the thermal stresses, which were mainly caused by the mismatch of coefficient of thermal expansion (CTE). The thermal stress had a linear relationship with the external temperature, but this tendency would be redistributed or even change direction when phase transition occurred. The simulated results were in tandem with the analytical method. Meanwhile, the radial stress and shear stress distribution under the influence of phase transition were calculated. In addition, the reduction of thermal stress and shear stress showed that the appropriate interlayer can enhance the adhesive strength effectively.

Metamaterial absorber/emitter is an important aspect of infrared radiation manipulation. In this paper, we proposed four simple switchable infrared metamaterial absorbers/emitters with Ag/VO2 disks on the Ag plane employing triangle, square, hexagon, and circle unit cells. The spectral absorption peaks whose intensities are above 0.99 occur at ~4 μm after structure optimization when VO2 is in insulating state and disappear when VO2 becomes metallic state. The simulated electromagnetic field reveals that the spectral absorption peaks are attributed to the excitation of magnetic polariton within the insulating VO2 spacer layer, whose values exceed 1.59 orders of magnitude higher than the incident magnetic field. Longer resonant wavelength would be excited in square arrays because its configuration is a better carrier of charges at the same spans. For absorption stability, the absorbers/emitters with square and circular structures do not have any change with the polarization angles changing from 0° to 90°, due to the high rotational symmetric structure. And four absorbers/emitters reveal similar shifts and attenuations under different incident angles. We believed that the switchable absorber/emitter demonstrates promising applications in the sensing technology and adaptive infrared system.

Alzheimer's disease (AD) is still an incurable neurodegenerative disease that causes dementia. AD changes the brain function that, over time, impairs memory and diminishes judgment and reasoning ability. Pathophysiology of AD is complex. Till now the cause of AD remains unknown, but risk factors include family history and genetic predisposition. The drugs previously approved for AD treatment do not modify the disease process and only provide symptomatic improvement. Over the past few decades, research has led to significant progress in the understanding of the disease, leading to several novel strategies that may modify the disease process. One of the major developments in this direction is the amyloid β (Aβ) aggregation. Small molecules could block the initial stages of Aβ aggregation, which could be the starting point for the design and development of new AD drugs in the near future. In this review we summarize the most promising small-molecule Aβ-aggregation inhibitors including natural compounds, novel small molecules, and also those are in clinical trials. Moreover, we briefly summarized some reported docking studies of small-molecule Aβ aggregation inhibitors. These will give us an idea about the chemical features required to design novel small molecules with anti-Aβ aggregation properties.

We reported a sandwich structured Pb(Zr0.4Ti0.6)O3/BaZr0.2Ti0.8O3/Pb(Zr0.4Ti0.6)O3 (PZT/BZT/PZT) film fabricated by using the sol−gel method, which was dense and uniform with a unique perovskite structure. The PZT/BZT/PZT films displayed high dielectric constants up to 1722.45 at the frequency of 10 kHz. Additionally, the enhanced energy storage density of 39.27 J·cm−3 was achieved at room temperature and 2.00 MV/cm, which was higher than that of the individual BaZr0.2Ti0.8O3 film (21.28 J·cm−3). Furthermore, the energy storage density and efficiency of PZT/BZT/PZT film increased slightly with the increasing temperature from −140 °C to 200 °C. This work proves the feasibility and effectiveness of a sandwich structure in improving dielectric, leakage, and energy storage performances, providing a new paradigm for high-energy−density dielectrics applications.

An optical limiter (OL) is a nonlinear device that protects sensitive photodetectors or human eyes from high-intensity illumination. However, current OLs have low open-state transmittance and a limited turndown ratio in some cases. In this study, first it is demonstrated that combining the insulator-to-metal transition (IMT) of vanadium dioxide (VO2) with anti-reflection layers can enable both high and broadband open-state transmittance (>-0.9 dB at the peak wavelength) while preserving a large turndown ratio (>21.8 dB). Furthermore, optothermal simulation is conducted to analyze the performance of the VO2 OL under ultrafast laser irradiation. The result reveals that IMT of the VO2 OL occurs at 0.23 µs when the incident laser intensity is 90 kW cm-2. These benefits offer a promising alternative to OLs in technologies ranging from sensor protection to human eye defense. [ABSTRACT FROM AUTHOR]

Abstract Public institutions, emblematic of public infrastructure, exhibit extensive reach and operational scope, positioning them as vanguards in China’s dual carbon initiatives and serving as exemplars. Electricity and natural gas predominantly fuel the operations of public institutions. Notably, the fixed commute routes and consistent procurement patterns of office personnel yield a standardized energy consumption profile within these entities. Researching carbon emissions related to commuting and evaluating procurement strategies for reducing carbon footprints in public institutions demonstrate a precision-tailored approach. This paper, through an analysis of the energy consumption characteristics, utilization structure of public institutions, and the commuting behaviors and procurement practices of office personnel, establishes a bespoke carbon accounting model specifically designed for public institutions, seamlessly embedded within a comprehensive platform. By providing fundamental methodological frameworks and advanced technological foundations for carbon accounting in public institutions across China, this work propels the nation’s efforts towards carbon peak and ultimately carbon neutrality.

Abstract Single-frame infrared small target detection is affected by the low image resolution and small target size, and is prone to the problems of small target feature loss and positional offset during continuous downsampling; at the same time, the sparse features of the small targets do not correlate well with the global-local linkage of the background features. To solve the above problems, this paper proposes an efficient infrared small target detection method. First, this paper incorporates BlurPool in the feature extraction part, which reduces the loss and positional offset of small target features in the process of convolution and pooling. Second, this paper designs an interactive attention deep feature fusion module, which acquires the correlation information between the target and the background from a global perspective, and designs a compression mechanism based on deep a priori knowledge, which reduces the computational difficulty of the self-attention mechanism. Then, this paper designs the context local feature enhancement and fusion module, which uses deep semantic features to dynamically guide shallow local features to realize enhancement and fusion. Finally, this paper proposes an edge feature extraction module for shallow features, which utilizes the complete texture and location information in the shallow features to assist the network to initially locate the target position and edge shape. Numerous experiments show that the method in this paper significantly improves nIoU, F1-Measure and AUC on IRSTD-1k Datasets and NUAA-SIRST Datasets.

Perovskite semiconductors have achieved great success during the last decades in the application of solar cells, light-emitting diodes, and photodiodes. Developing strategies to pattern perovskites with high-resolution is crucial to broaden the application scenarios of perovskite displays and on-chip lighting. However, the widely used lithography procedure has the problem of high-cost and complexity. In this study, we demonstrate a method to pattern a luminescent perovskite-acrylic polymer composite that is prepared by direct injection at room temperature. This strategy uses standard photoresists and UV lithography at room temperature, and then the pattern in the photoresists can be easily transferred to the perovskite-acrylic polymer composite. Finally, we can obtain high-quality micron-scale features. Furthermore, we demonstrate the universality of this strategy by adapting perovskite with different color emissions into the composite and patterning it using the same procedure. Another advantage of this patternable perovskite-acrylic polymer composite is its superb water-repellent properties, which are believed to be of great potential in underwater applications.

In the marine field, infrared detection technology is of great significance for timely localization and detection of ships in security missions. However, since infrared ship targets are often in the environmental conditions of small pixel occupancy, low contrast and complex background, it poses a great challenge for multiship detection, classification, and localization tasks. Therefore, to address these problems we propose an edge information-guided infrared ship target detection (EGISD-YOLO) network, in which a dense-csp structure is designed to improve the csp module of YOLO to increase the reusability of the backbone feature information, and in addition, to address the noise and interference generated by the image in the complex background, a deconvolutional channel attention module (DCA) is designed to link the contextual language to the image, which relates the contextual semantics to obtain the local information of the target. Crucially, we propose an edge-guided structure that takes the edge information of low-level features as a cue to fuse with deep-level features to enrich the target contour and thus improve the target localization ability, so that the network still possesses robustness under low-contrast conditions, and finally, we add a small-size prediction head at the end of the network to further increase the detection ability of weak targets. The proposed EGISD-YOLO is experimentally demonstrated to have better detection performance for infrared ship targets.

Phase control of random lasing processes has been a challenge both in physics and in the device/materials design. Although conventional saturable absorbers can be integrated with random lasers to conceive mode-locking scheme, low intensity and random directions of the lasing radiation reduce largely the possibility. In such considerations, we put forth a new mode-locking mechanism, which is defined as cascaded absorption and stimulated emission (CASE), and have it achieved in multicrystalline microdisk structures of a hybrid perovskite. This scheme applies only to lasing materials with strong overlap between the absorption and emission spectra. In this work, we employed 2-photon pumping at 800 nm with a pulse duration of about 150 fs to realize phase-locked random lasing in MAPbBr3 microdisks in donut shapes, which are produced by micro-imprinting using a flexibly transferred template of tricyclo[5.2.1.02,6] decanedimethanol diacrylate. The phase-locking performance is identified by the narrow-band lasing lines with equal separations. The constant phase shift for initializing phase locking is determined by the internal conversion lifetime in the MAPbBr3 molecules. Two-photon pumping enables large penetration depth into the microdisks and consequently large numbers of phase-locked lasing modes, producing much narrowed and high-contrasted spectral lines. Lasing lines with a bandwidth as narrow as 0.26 to 0.3 nm and an equal separation ranging from 1.7 to 4.8 nm have been achieved for different microdisk schemes. These results imply marked progress in new random lasing physics and potential applications in ultrafast laser technology.

Abstract Characterizing the long-term kinetics of maternally derived and vaccine-induced measles immunity is critical for informing measles immunization strategies moving forward. Based on two prospective cohorts of children in China, we estimate that maternally derived immunity against measles persists for 2.4 months. Following two-dose series of measles-containing vaccine (MCV) at 8 and 18 months of age, the immune protection against measles is not lifelong, and antibody concentrations are extrapolated to fall below the protective threshold of 200 mIU/ml at 14.3 years. A catch-up MCV dose in addition to the routine doses between 8 months and 5 years reduce the cumulative incidence of seroreversion by 79.3–88.7% by the age of 6 years. Our findings also support a good immune response after the first MCV vaccination at 8 months. These findings, coupled with the effectiveness of a catch-up dose in addition to the routine doses, could be instrumental to relevant stakeholders when planning routine immunization schedules and supplemental immunization activities.

The germination of seeds is a prerequisite for crop production. Protrusion is important for seed germination, and visible radicle protrusion through seed covering layers is the second phase of the process of seed germination. Analyzing the mechanism of protrusion is important for the cultivation of rice varieties. In this study, 302 microcore germplasm populations were used for the GWAS of the protrusion percentage (PP). The frequency distribution of the PP at 48 h and 72 h is continuous, and six PP-associated QTLs were identified, but only qPP2 was detected repeatedly two times. The candidate gene analysis showed that LOC_Os02g57530 (ETR3), LOC_Os01g57610 (GH3.1) and LOC_Os04g0425 (CTB2) were the candidate genes for qPP2, qPP1 and qPP4, respectively. The haplotype (Hap) analysis revealed that Hap1 of ETR3, Hap1 and 3 of GH3.1 and Hap2 and 5 of CTB2 are elite alleles for the PP. Further validation of the germination phenotype of these candidate genes showed that Hap1 of ETR3 is a favorable allele for the germination percentage; Hap3 of GH3.1 is an elite allele for seed germination; and Hap5 of CTB2 is an elite allele for the PP, the germination percentage and the vigor index. The results of this study identified three putative candidate genes that provide valuable information for understanding the genetic control of seed protrusion in rice.

Computer-based assessments provide the opportunity to collect a new source of behavioral data related to the problem-solving process, known as log file data. To understand the behavioral patterns that can be uncovered from these process data, many studies have employed clustering methods. In contrast to one-mode clustering algorithms, this study utilized biclustering methods, enabling simultaneous classification of test takers and features extracted from log files. By applying the biclustering algorithms to the “Ticket” task in the PISA 2012 CPS assessment, we evaluated the potential of biclustering algorithms in identifying and interpreting homogeneous biclusters from the process data. Compared with one-mode clustering algorithms, the biclustering methods could uncover clusters of individuals who are homogeneous on a subset of feature variables, holding promise for gaining fine-grained insights into students’ problem-solving behavior patterns. Empirical results revealed that specific subsets of features played a crucial role in identifying biclusters. Additionally, the study explored the utilization of biclustering on both the action sequence data and timing data, and the inclusion of time-based features enhanced the understanding of students’ action sequences and scores in the context of the analysis.

Abstract Background The outbreak of SARS-CoV-2 at the end of 2019 sounded the alarm for early inspection on acute respiratory infection (ARI). However, diagnosis pathway of ARI has still not reached a consensus and its impact on prognosis needs to be further explored. Methods ESAR is a multicenter, open-label, randomized controlled, non-inferiority clinical trial on evaluating the diagnosis performance and its impact on prognosis of ARI between mNGS and multiplex PCR. Enrolled patients will be divided into two groups with a ratio of 1:1. Group I will be directly tested by mNGS. Group II will firstly receive multiplex PCR, then mNGS in patients with severe infection if multiplex PCR is negative or inconsistent with clinical manifestations. All patients will be followed up every 7 days for 28 days. The primary endpoint is time to initiate targeted treatment. Secondary endpoints include incidence of significant events (oxygen inhalation, mechanical ventilation, etc.), clinical remission rate, and hospitalization length. A total of 440 participants will be enrolled in both groups. Discussion ESAR compares the efficacy of different diagnostic strategies and their impact on treatment outcomes in ARI, which is of great significance to make precise diagnosis, balance clinical resources and demands, and ultimately optimize clinical diagnosis pathways and treatment strategies. Trial registration Clinicaltrial.gov, NCT04955756, Registered on July 9th 2021.

Infrared pedestrian target detection is affected by factors such as the low resolution and contrast of infrared pedestrian images, as well as the complexity of the background and the presence of multiple targets occluding each other, resulting in indistinct target features. To address these issues, this paper proposes a method to enhance the accuracy of pedestrian target detection by employing contour information to guide multi-scale feature detection. This involves analyzing the shapes and edges of the targets in infrared images at different scales to more accurately identify and differentiate them from the background and other targets. First, we propose a preprocessing method to suppress background interference and extract color information from visible images. Second, we propose an information fusion residual block combining a U-shaped structure and residual connection to form a feature extraction network. Then, we propose an attention mechanism based on a contour information-guided approach to guide the network to extract the depth features of pedestrian targets. Finally, we use the clustering method of mIoU to generate anchor frame sizes applicable to the KAIST pedestrian dataset and propose a hybrid loss function to enhance the network’s adaptability to pedestrian targets. The extensive experimental results show that the method proposed in this paper outperforms other comparative algorithms in pedestrian detection, proving its superiority.

In this study, a transcriptomic analysis of the dehydration rate of mature rice seeds was conducted to explore candidate genes related to the dehydration rate and provide a theoretical basis for breeding and utilization. We selected two rice cultivars for testing (Baghlani Nangarhar, an extremely rapid dehydration genotype, and Saturn, a slow dehydration genotype) based on the results determined by previous studies conducted on the screening of 165 germplasm materials for dehydration rate phenotypes. A rapid dehydration experiment performed on these two types of seeds was conducted. Four comparative groups were set up under control and dehydration conditions. The differentially expressed genes (DEGs) were quantified via transcriptome sequencing and real-time quantitative PCR (RT-qPCR). GO (Gene ontology) and KEGG(Kyoto Encyclopedia of Genes and Genomes) analyses were also conducted. In Baghlani Nangarhar, 53 DEGs were screened, of which 33 were up-regulated and 20 were down-regulated. In Saturn, 25 DEGs were screened, of which 19 were up-regulated and 6 were down-regulated. The results of the GO analysis show that the sites of action of the differentially expressed genes enriched in the rapid dehydration modes are concentrated in the cytoplasm, internal components of the membrane, and nucleosomes. They play regulatory roles in the processes of catalysis, binding, translocation, transcription, protein folding, degradation, and replication. They are also involved in adaptive responses to adverse external environments, such as reactive oxygen species and high temperature. The KEGG analysis showed that protein processing in the endoplasmic reticulum, amino acid biosynthesis, and oxidative phosphorylation were the main metabolic pathways that were enriched. The key differentially expressed genes and the most important metabolic pathways identified in the rapidly and slowly dehydrated genotypes were protein processing in the endoplasmic reticulum and oxidative phosphorylation metabolism. They were presumed to have important regulatory roles in the mechanisms of stress/defense, energy metabolism, protein synthesis/folding, and signal transduction during the dehydration and drying of mature seeds. The results of this study can potentially provide valuable information for further research on the genes and metabolic pathways related to the dehydration rate of mature rice seeds, and provide theoretical guidance for the selection and breeding of new rice germplasm that can be rapidly dehydrated at the mature stage.

Abstract Background Obesity is an important underlying cause of central precocious puberty (CPP), but previous large studies are flawed by using just age and breast examination to diagnose CPP. We aimed to determine whether overweight and obesity in childhood increases hormonally diagnosed CPP. Methods Our retrospective, case-control study recruited 846 children diagnosed as having CPP and randomly sampled 1650 healthy control subjects in Xingtai Third Hospital in China between November 2018 and March 2021. Information was obtained from an electronic medical record and questionnaire investigated in the outpatient visit. Observations were made before the a priori hypothesis. Unconditional logistic regression for analysis was used to determine whether overweight and obesity status and duration of overweight/obesity were associated with CPP. Results Overweight and obesity were significantly associated with increased odds of CPP among girls, even after adjusting for birth weight, exclusive breastfeeding for 6 month, household income, maternal overweight, paternal overweight, and maternal menarche age (overweight: the adjusted odds ratio (aOR) (95%CI): 1.92 (1.16, 3.24), p = 0.02; obesity: aOR (95%CI): 1.78 (1.13, 3.48), p = 0.03). Furthermore, the effects of overweight and obesity were significant when ongoing for 1 to 2 years, 2 to 3 years, and greater than 3 years, but not at less than 1 year. For boys, association between obesity and increased odds of CPP was observed (aOR (95%CI): 1.68 (1.09, 3.75), p = 0.03). The effects of overweight and/or obesity were only significant when ongoing for greater than 2 years. Conclusions Prolonged overweight and obesity in early childhood may be risk factors for CPP, especially in girls. Weight loss might be an important approach for the prevention of precocious puberty in children.

Microalgae have been widely employed in water pollution treatment since they are eco-friendly and economical. However, the relatively slow treatment rate and low toxic tolerance have seriously limited their utilization in numerous conditions. In light of the problems above, a novel biosynthetic titanium dioxide (bio-TiO2 NPs)—microalgae synergetic system (Bio-TiO2/Algae complex) has been established and adopted for phenol degradation in the study. The great biocompatibility of bio-TiO2 NPs ensured the collaboration with microalgae, improving the phenol degradation rate by 2.27 times compared to that with single microalgae. Remarkably, this system increased the toxicity tolerance of microalgae, represented as promoted extracellular polymeric substances EPS secretion (5.79 times than single algae), and significantly reduced the levels of malondialdehyde and superoxide dismutase. The boosted phenol biodegradation with Bio-TiO2/Algae complex may be attributed to the synergetic interaction of bio-TiO2 NPs and microalgae, which led to the decreased bandgap, suppressed recombination rate, and accelerated electron transfer (showed as low electron transfer resistance, larger capacitance, and higher exchange current density), resulting in increased light energy utilization rate and photocatalytic rate. The results of the work provide a new understanding of the low-carbon treatment of toxic organic wastewater and lay a foundation for further remediation application.

Detailed knowledge of COVID-19 epidemiology is needed to inform public health responses. Here, the authors use large-scale contact tracing data to provide empirical estimates of key parameters, and show that susceptibility increases with age but transmissibility does not vary significantly.

Land surface temperature (LST) retrieval from thermal infrared (TIR) remote sensing image requires atmospheric and land surface emissivity (LSE) data that are sometimes unattainable. To overcome this problem, a hybrid algorithm is developed to retrieve LST without atmospheric correction and LSE data input, by combining the split-window (SW) and temperature–emissivity separation (TES) algorithms. The SW algorithm is used to estimate surface-emitting radiance in adjacent TIR bands, and such radiance is applied to the TES algorithm to retrieve LST and LSE. The hybrid algorithm is implemented on five TIR bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Analysis shows that the hybrid algorithm can estimate LST and LSE with an error of 0.5–1.5 K and 0.007–0.020, respectively. Moreover, the LST error of the hybrid algorithm is equivalent to that of the original ASTER TES algorithm, involving 1%–2% uncertainty in atmospheric correction. The hybrid algorithm is validated using ground-measured LST at six sites and ASTER LST products, indicating that the temperature difference between the ASTER TES algorithm and the hybrid algorithm is 1.4 K and about 2.5–3.5 K compared to the ground measurement. Finally, the hybrid algorithm is applied to at two places.

Abstract Behavioral lateralization, which is associated with the functional lateralization of the two brain hemispheres, commonly exists in animals and can provide an individual with benefits such as enhanced cognition and dual tasking. Lateral bias in limb use, as a type of behavioral lateralization, occur in many species, but the reasons for the coexistence of left‐ and right‐biased individuals in a population remain poorly understood. We examined the footedness of male yellow‐bellied tits (Pardaliparus venustulus) when they used feet to clamp mealworms against a perch, and tested its association with other fitness‐related behavioral traits (i.e., feeding efficiency, exploration tendency, and escape performance). We expected differently footed individuals to have respective advantages in these behaviors and thereby coexist (“respective advantage” hypothesis). We found their footedness repeatable, and there was no population‐level bias. While no associations of feeding efficiency and exploration tendency with footedness were detected, the right‐footed individuals were found to be harder to catch than the other individuals. Future studies need to investigate the reasons for the right‐footed individuals' superior escape performance. Moreover, the escape advantage for being right‐footed and the lack of population‐level bias in footedness in male yellow‐bellied tits suggest that the benefits related to left footedness also remain to be explored.

Thermal infrared (TIR) remote sensing technology is capable of acquiring large-scale land surface temperature (LST), which is a key factor in the energy exchange between land surface and atmosphere. The visible and infrared multispectral sensor (VIMS) equipped in the Chinese Gaofen-5 (GF-5) satellite can obtain four channels of TIR images with a 40 m spatial resolution. However, due to the change of working environment, the TIR sensor suffers a low-accurate radiometric calibration that needs improvement. This paper puts forward a new cross-calibration for GF-5/VIMS TIR images by linking the top of the atmosphere (TOA) radiance of the vertical angle MODIS observation with the GF-5/VIMS image to estimate the radiometric calibration coefficients, Gain and Offset. To verify the recalibration performance, a new nonlinear two-channel split-window (SW) algorithm and a light gradient boosting machine (LightGBM) method which is used to refine LST from the SW algorithm by minimizing the residuals, were developed for the recalibrated GF-5/VIMS TIR 3 and TIR 4 channels. The radiometric cross-calibration algorithm and the optimized SW algorithm were applied to real GF-5/VIMS TIR images. The validation results showed that the brightness temperature and LST were improved significantly, and the LST retrieval error was reduced greatly to 1.79 K after recalibration, indicating a large improvement of the LST retrieval for GF-5/VIMS TIR image using the proposed cross-calibration and SW algorithms.

A threshold effect in the periodical patterning of the hybrid halide perovskites and a directional output coupling effect in the incoherent random lasing from the patterned materials are reported. Using 1D gratings, the random crystallization process is confined into the grating grooves, producing continuous microstrips of CH3NH3PbBr3 along the groove channels. However, the confinement is strongly dependent on the width of the grating grooves, which can be optimized by tuning the patterning periods. It is thus discovered that the most orderly arranged crystal strips are achieved for a grating period of 10 μm, corresponding to a channel width of about 5 μm, which is the lower limit for the formation of continuous crystal strips. Complicated interfaces inside such randomly organized multicrystals supplied scattering centers for optical gain mechanisms. Thus, incoherent random lasing actions are observed for all of these patterned structures, however, the best lasing performance is achieved for a grating period of 10 μm, which agrees with the highest quality of the crystal strips. The patterned substrate with a 1D grating supplies mechanisms for directional crystallization of hybrid halide perovskites and directional output coupling of random laser emission, enhancing significantly the practical application possibilities of such random lasers.

Abstract Background Under caged conditions, birds are affected more severely by environmental stressors such as dietary structure, activity space, human disturbances, and pathogens, which may be reflected in the gene expression in peripheral blood or other tissues. Elucidating the molecular mechanism of these stress responses will help improve animal welfare. Results In the present study, the blood transcriptomes of six male and five female caged magpies (Pica pica) were sequenced, and a total of ~ 100 Gb in clean reads were generated using the Illumina HiSeq 2000 sequencer. A total of 420,291 unigenes were identified after assembly, of which 179,316 were annotated in five databases, 7471 were assigned to 269 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and 566 were assigned to the Clusters of Orthologous Groups (COG) functional classification “defense mechanisms”. Analysis of differentially expressed genes (DEGs) showed that 2657 unigenes were differentially expressed between males and females (q

In this paper, the slice-within-Gibbs sampler has been introduced as a method for estimating cognitive diagnosis models (CDMs). Compared with other Bayesian methods, the slice-within-Gibbs sampler can employ a wide-range of prior specifications; moreover, it can also be applied to complex CDMs with the aid of auxiliary variables, especially when applying different identifiability constraints. To evaluate its performances, two simulation studies were conducted. The first study confirmed the viability of the slice-within-Gibbs sampler in estimating CDMs, mainly including G-DINA and DINA models. The second study compared the slice-within-Gibbs sampler with other commonly used Markov Chain Monte Carlo algorithms, and the results showed that the slice-within-Gibbs sampler converged much faster than the Metropolis-Hastings algorithm and more flexible than the Gibbs sampling in choosing the distributions of priors. Finally, a fraction subtraction dataset was analyzed to illustrate the use of the slice-within-Gibbs sampler in the context of CDMs.