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Long-tailed ground squirrels (LTGRs, Spermophilus undulatus) are known as reservoirs of multiple arthropod-borne pathogens, such as Yersinia pestis and Bartonella rochalimae. However, data on the prevalence of spotted fever group rickettsiae (SFGR) and Coxiella burnetii in LTGRs and its ectoparasites are limited. In two alpine regions of Xinjiang Uygur Autonomous Region (XUAR, northwestern China), a total of 346 samples were collected from 142 LTGRs, including 142 livers and 204 pooled ectoparasites (Citellophilus tesquorum dzetysuensis: 120 pools of 484 fleas; Frontopsylla elatoides elatoides: 19 pools of 71 fleas; Neopsylla mana: 1 pool of 4 fleas; and Linognathoides urocitelli: 64 pools of 865 lice). From these samples, the DNA was extracted, followed by PCR amplification of different genetic markers. Particularly, genes encoding the outer membrane protein A and B (ompA, ompB), citrate synthase (gltA), and surface cell antigen 1 (sca1) were used to identify the SFGR. Additionly, the capsular outer membrane protein (Com1) gene and insertion sequence (IS1111) genes were used to detect Coxiella. Rickettsia sibirica subsp. sibirica, Rickettsia felis, and C. burnetii were detected in LTGRs, as well as in flea and louse pools. Rickettsia raoultii was found in LTGRs and flea pools. Furthermore, Rickettsia slovaca was also identified in the flea pools. This study provides molecular evidence for the occurrence of SFGR and C. burnetii in LTGRs and their ectoparasites. These findings suggest that R. sibirica, R. slovaca, R. raoultii, R. felis and C. burnetii are transmitted between LTGRs (as potential reservoirs) and their fleas and lice (as potential vectors).

Understanding the resilience of areas with different land-use types can enhance a city's ability to respond to and recover from disasters. Based on Docomo mobile GPS data and the 2018 Fukui Prefecture snow disaster, this study explores the resilience of areas with different land-use types from the grid level. First, the resilience triangle method was employed to assess the robustness, vulnerability, and survivability of different land-use types at the 500-m grid level. Second, Pearson correlation analysis and causal inference determined that snow depth is a causal factor leading to changes in grid resilience, thereby identifying the optimal time points for each grid to distinguish between disaster end and recovery start. Finally, a resilience map of Fukui Prefecture was created, integrating road data to identify cities with poor resilience and road sections prone to congestion during snow disasters. The results indicate that land-use types such as factories, agricultural land, building land, and mid-high-rise buildings have better resilience, especially mid-high-rise buildings, which exhibit strong resistance and recovery ability when facing disturbances, allowing them to return to normal states quickly. In urban planning, prioritizing such resilient building types could be beneficial. In contrast, sparse low-rise buildings, parks, facility land, and dense low-rise buildings exhibit poorer resilience and take longer to recover. Additionally, areas with poor traffic resilience in Fukui Prefecture are mainly concentrated in the northern part, particularly the vertical sections in Fukui City, Awara City, and Sakai City, as well as the vertical section from Sabae City to Echizen City and the horizontal section from Eiheiji-cho to Katsuyama City.

Fleas are known to be vectors for a variety of pathogens in veterinary medicine. However, no information is available on the presence of Bartonella and Trypanosomatidae in fleas of the long-tailed ground squirrel (LTGR, Spermophilus undulatus). The present study shows detection of these pathogens in LTGR fleas. During 2022–2023, a total of 396 fleas were collected from 91 LTGRs in 4 alpine regions of Xinjiang Uygur Autonomous Region (northwestern China) and grouped into 54 flea pools. Flea species were identified according to morphological characteristics and molecular data. In addition, all flea samples were analyzed for Bartonella with amplification and sequencing of a 380-bp part of the gltA gene and Trypanosomatidae with targeting the 18S rRNA (850-bp) and gGAPDH (820-bp) genes. The flea species included Frontopsylla elatoides elatoides (203), Neopsylla mana (49), and Citellophilus tesquorum dzetysuensis (144). Of 54 flea pools, seven (12.96%) tested positive for Bartonella, and three (5.56%) were positive for Trypanosomatidae. Based on BLASTn and phylogenetic analyses, i) Bartonella washoensis in F. elatoides elatoides and C. tesquorum dzetysuensis, and Bartonella rochalimae in F. elatoides elatoides were identified. Interestingly, a new haplotype within the species Ba. washoensis was discovered in C. tesquorum dzetysuensis; and ii) Blechomonas luni was confirmed in C. tesquorum dzetysuensis and Trypanosoma otospermophili in F. elatoides elatoides. Two Bartonella species and two Trypanosomatidae members were discovered for the first time in fleas from LTGRs. This study broadens our understanding of the geographic distribution and potential vectors for Bartonella and Trypanosomatidae.

Traditional medical image sensors face multiple challenges. First, these sensors typically rely on large amounts of labeled data, which are time-consuming and costly to obtain. Second, when the data volume and image size are large, traditional sensors have limited computational power, making it difficult to effectively train and infer models. Additionally, traditional sensors have poor generalization ability and struggle to adapt to datasets with different modalities. This paper devises a novel framework, named LSDSL, and deploys it in the sensor. LSDSL utilizes low-quality sensor data for semi-supervised learning in medical image segmentation. in supervised learning, we devise the hard region exploration (hre) module to enhance the model’s comprehension of low-quality pixels in hard regions. in unsupervised learning, we introduce a pseudo-label sharing (ps) module, which allows low-quality pixels in one network to learn from the high-quality pixels in the other networks. our model outperforms other semi-supervised methods on the datasets of two different modalities (CT and MRI) in medical image sensors, achieving superior inference speed and segmentation accuracy.

Goupi plaster, a representative preparation of black plaster, has demonstrated promising effects in treating knee osteoarthritis. However, high temperature used in traditional frying extraction may cause decomposition of its effective components, thus limiting the efficacy. This study aimed to explore the scientific nature of the traditional preparation technology of Goupi plaster, and to compare the effects of different extraction methods on the types of chemical components and the content of index components. The UPLC-Q-Exactive-MS and UPLC-MS/MS technologies which have high efficiency, sensitivity and accuracy, were used to qualitatively and quantitatively analyze the chemical components of Goupi plaster under different preparation processes. The results show that the extraction solvent approach is different from the traditional frying extraction method, and has a positive effect. However, the mechanism of action of Goupi plaster is complex and its pharmacological effects are diverse. Future studies should explore whether it necessary to change the frying extraction method. This experiment provides a theoretical basis that will guide further scientific discussion and research into the frying extraction of Goupi plaster.

Third-party logistics companies face a challenging task in minimizing inventory transportation costs due to the complexities of managing numerous suppliers. Effectively optimizing costs becomes a formidable problem for such companies. This empirical research has yielded strategies for minimizing the inventory transportation cost specifically for company D. Through a rigorous optimization process, the findings presented in this paper demonstrate an average reduction of 7.18% in company D's inventory transportation cost. By jointly optimizing inbound logistics inventory transportation under VMI-TPL mode, this study extends the theory of supplier managed inventory and improves the inbound logistics mode. The results of this study can provide quantitative support and decision-making references for the project operation management of company D and similar enterprises.

Abstract Background Conversion or editing of adenosine (A) into inosine (I) catalyzed by specialized cellular enzymes represents one of the most common post-transcriptional RNA modifications with emerging connection to disease. A-to-I conversions can happen at specific sites and lead to increase in proteome diversity and changes in RNA stability, splicing, and regulation. Such sites can be detected as adenine-to-guanine sequence changes by next-generation RNA sequencing which resulted in millions reported sites from multiple genome-wide surveys. Nonetheless, the lack of extensive independent validation in such endeavors, which is critical considering the relatively high error rate of next-generation sequencing, leads to lingering questions about the validity of the current compendiums of the editing sites and conclusions based on them. Results Strikingly, we found that the current analytical methods suffer from very high false positive rates and that a significant fraction of sites in the public databases cannot be validated. In this work, we present potential solutions to these problems and provide a comprehensive and extensively validated list of A-to-I editing sites in a human cancer cell line. Our findings demonstrate that most of true A-to-I editing sites in a human cancer cell line are located in the non-coding transcripts, the so-called RNA 'dark matter'. On the other hand, many ADAR editing events occurring in exons of human protein-coding mRNAs, including those that can recode the transcriptome, represent false positives and need to be interpreted with caution. Nonetheless, yet undiscovered authentic ADAR sites that increase the diversity of human proteome exist and warrant further identification. Conclusions Accurate identification of human ADAR sites remains a challenging problem, particularly for the sites in exons of protein-coding mRNAs. As a result, genome-wide surveys of ADAR editome must still be accompanied by extensive Sanger validation efforts. However, given the vast number of unknown human ADAR sites, there is a need for further developments of the analytical techniques, potentially those that are based on deep learning solutions, in order to provide a quick and reliable identification of the editome in any sample.

Semantic segmentation is primarily employed to generate accurate prediction labels for each pixel of the input image, and then classify the images according to the generated labels. Semantic segmentation of building and water in remote sensing images helps us to conduct reasonable land planning for a city. However, many current mature networks face challenges in simultaneously attending to both contextual and spatial information when performing semantic segmentation on remote sensing imagery. This often leads to misclassifications and omissions. Therefore, this paper proposes a Dual-Branch Network with Spatial Supplementary Information (SPNet) to address the aforementioned issues. We introduce a Context-aware Spatial Feature-Extractor Unit (CSF) to extract contextual and spatial information, followed by the Feature-Interaction Module (FIM) to supplement contextual semantic information with spatial details. Additionally, incorporating the Goal-Oriented Attention Mechanism helps in handling noise. Finally, to obtain more detailed branches, a Multichannel Deep Feature-Extraction Module (MFM) is introduced to extract features from shallow-level network layers. This branch guides the fusion of low-level semantic information with high-level semantic information. Experiments were conducted on building and water datasets, respectively. The results indicate that the segmentation accuracy of the model proposed in this paper surpasses that of other existing mature models. On the building dataset, the mIoU reaches 87.57, while on the water dataset, the mIoU achieves 96.8, which means that the model introduced in this paper demonstrates strong generalization capabilities.

The mass loss mechanisms of an aqueous film-forming foam (AF foam), an AR/AFFF water-soluble film-forming foam extinguishing agent (AR foam), and a Class A foam extinguishing agent (A foam) at different levels of thermal radiation, thermal convection, and heat conduction intensity were studied. At a relatively low thermal radiation intensity, the liquid separation rate of the AF, AR, and A foams is related to the properties of the foam itself, such as viscosity and surface/interface tension, which are relatively independent of the external radiation heat flux of the foam. At low radiation intensity (15 kW/m2 and 25 kW/m2), the liquid separation rate of the AF and A foams is relatively stable. When the heat flux intensity is 35 kW/m2, the liquid separation rate of the AF and A foams increases notably, which may be mainly due to the rapid decrease in foam viscosity. And the mass loss behavior is dominated by liquid separation in the AF, AR, and A foams under the influence of thermal radiation and thermal convection. Under the same experimental conditions, the liquid separation rate of AF is the fastest. There is no significant difference in the evaporation rates of the three kinds of foam in the same heat conduction condition. In addition, the AR and A foams usually have a 25% longer liquid separation time (t) under thermal radiation and thermal convection, and the thermal stability is better than AF foam. The temperature reached by the AF foam layer under thermal convection was lower than that of the AR and A foams, and the time for the foam layer to reach the highest temperature under heat conduction was longer than that of the AR and A foams.

The nitrogen isotopic compositions of lunar soil have important implications for the sources of lunar volatiles and even the evolution of the moon. At present, the research on the lunar nitrogen isotopic compositions is mainly based on the lunar meteorites and the samples brought back by the Apollo and Luna missions. However, volatiles adsorbed on the surface of the lunar soil may be lost due to changes in temperature and pressure, as well as vibration and shock effects when the sample is returned. At the same time, in the case of low N content in the sample, since N is the main component of the earth’s atmosphere, it is easily affected by the atmosphere during the analysis process. Therefore, in situ nitrogen isotopic analysis of lunar soil on orbit is necessary to avoid the problems mentioned above and is one of the primary science goals for the Lunar Soil Volatile Measuring instrument on Chang’e-7 spacecraft. After the nitrogen purification procedure, the volatiles in lunar soil that are released through single-step or stepped heating techniques diffuse to the quadrupole mass spectrometer to obtain the N contents and isotopic compositions of the lunar soil. This paper introduces the ground test for N isotopic analysis of lunar soil in orbit according to the Lunar Soil Volatile Measuring Instrument. After long-term repeated measurements, the background and CO-corrected Air-STD 14N/15N ratio is 268.986 ± 4.310 (1SD, n = 35), and the overall reproducibility of measurements is 1.6%. The accuracy of N isotopic compositions is calculated to be better than 5%, which can distinguish different sources of N components in lunar soil.

Aiming at the current problems of the ultra wide band (UWB) indoor positioning system based on the double sided two-way ranging (DS-TWR) algorithm, there are more communication times and a higher conflict rate in a multi-tag environment, an improved algorithm was proposed.The Hash algorithm to hash and distribute the communication content between the tag and the anchor was used, so that the anchor could reply to multiple tags in a regular and unified manner during each ranging process, which greatly reduced the number of times the anchor sends RES (responds) data.Experimental results show that the improved algorithms’ communication times between a tag and the anchor were reduced by 15% compared with the traditional DS-TWR algorithm, which increases the time proportion of the anchor receiving state in ranging, thereby reducing the anchor receiving RNG (range) data.The collision rate of packets, the success rate of ranging has increased by 43.6%.Due to the reduction in the number of communications required in each positioning cycle and the reduction in the collision rate between data packets, a smaller channel capacity would be required, thereby increasing the label capacity of the positioning system, which has strong engineering significance.

According to the big impact hypothesis, the moon should be very dry. However, more and more evidence from the remote sensing of the moon in recent years indicates that there is a lot of water in the moon’s polar regions. Researching the source and distribution of volatiles such as water can provide a key constraint on the formation and evolution of the moon. If there is a large amount of a volatile such as water ice in the polar area of the moon, it can be used as a further resource. Regrettably, there are no detectors in place to detect the amount and presence of water to date. In the new wave of lunar exploration, polar water has become one of the main tasks of NASA, ESA and RKA. The Chang’e-7 spacecraft of China’s fourth lunar exploration phase has also used the Water Molecular Analyzer and the Lunar Soil Volatile Measuring Instrument to detect water content in the lunar polar region. This paper introduces a set of methods and principles for analyzing water content via the heat flux method according to the characteristics of the Lunar Soil Volatile Measuring Instrument that was deployed on the lunar surface. According to the current design, the water content of 0.008~0.17% can be analyzed.

The evolutionarily conserved complex, the Par proteins, regulates cell polarity. Here, the authors show that in Drosophila neuroblasts, the Par complex exhibits liquid–liquid phase separation dependent on the cell cycle.

HECT type E3 ligases are key regulators of cell growth and proliferation. Here the authors present the crystal structures of the Nedd4 family E3 ligase WWP1 in a closed and semi-open state and in combination with mutagenesis experiments identify a multi-lock regulatory mechanism that allows the fine-tuning of activities of Nedd4 family E3 ligases.

Polarized localization of Numb and Pon in Drosophila neuroblasts (NBs) enables their unequal segregation during asymmetric cell divisions. Here, the authors demonstrate liquid-liquid phase separation of Pon and Numb in NBs mediated by multivalent intermolecular interactions is required for their basal condensation.