Background Paediatricians are often the first point of contact for children in Primary Care (PC), but still perceive gaps in their allergy knowledge. We investigated self-perceived knowledge gaps and educational needs in paediatricians across healthcare systems in Europe so that future educational initiatives may better support the delivery of allergy services in PC. Methods A multinational survey was circulated to paediatricians who care for children and adolescents with allergy problems in PC by the EAACI Allergy Educational Needs in Primary Care Paediatricians Task Force during February to March 2023. A 5-point Likert scale was used to assess level of agreement with questionnaire statements. 30 surveys per country was the cut-off for inclusion and statistical analysis. Results 1,991 respondents were obtained from 56 countries across Europe and 210 responses were from countries with a cut-off below 30 participants per country. Primary care paediatricians (PCPs) comprised 74.4% of the respondents. The majority (65.3%) were contracted to state or district health services. 61.7% had awareness of guidelines for onward allergy referral in their countries but only 22.3% were aware of the EAACI competencies document for allied health professionals for allergy. Total sample respondents versus PCP’s showed 52% and 47% of them have access to allergy investigations in their PC facility (mainly specific IgE and skin prick tests); 67.6% and 58.9% have access to immunotherapy, respectively. The main barrier for referral to a specialist was consideration that the patient’s condition could be diagnosed and treated in this PC facility, (57.8% and 63.6% respectively). The main reasons for referral was the need for hospital assessment, and partial response to first line treatment (55.4% and 59.2%, 47% and 50.7%, respectively). Learning and assessment methods preference was fairly equally divided between: Traditional methods (45.7% and 50.1% respectively) and e-Learning 45.5% and 44.9%, respectively. Generalist Physicians (GP’s) have the poorest access to allergy investigations (32.7%, p=0.000). The majority of the total sample (91.9%) assess patients with allergic pathology. 868 (43.6%) and 1,117 (46.1%), received allergy training as undergraduates and postgraduates respectively [these proportions in PCPs were higher (45% and 59%), respectively]. PCPs with special interest in allergology experienced greater exposure to allergy teaching as postgraduates. GP’s received the largest amount of allergy teaching as undergraduate. Identifying allergic disease based on clinical presentation, respondents felt most confident in the management of eczema/atopic dermatitis (87.4%) and rhinitis/asthma (86.2%), and least confident in allergen immunotherapy (36.9%) and latex allergy (30.8%). Conclusion This study exploring the confidence of PCP’s to diagnose, manage and refer patients with allergy, demonstrated knowledge gaps and educational needs for allergy clinical practice. It detects areas in need of urgent improvement especially in latex and allergen immunotherapy. It is important to ensure dissemination of allergy guidelines and supporting EAACI documents since the majority of PCPs lack awareness of them. This survey has enabled us to identify what the educational priorities of PCPs are and how they would like to have them met.

Editorial: Natural Sciences is Three Years YoungWe are pleased to note that, at the age of three, Wiley’s flagship journal, Natural Sciences, has reached a degree of maturity that is reflected in an average citation rate of 4.4 and inclusion in the Web of Scienceand the Emerging Sources Citation Index as well as in other indexing services. The three volumes of the journal published since 2021 are comprised of outstanding research articles and reviews as well as highlights, commentaries, perspectives, and critiques by leading members of the global community.Natural Sciences is an Open Science journal. Open Science encompasses not only open-access publishing but also open peer review and sharing of primary scientific data. The ongoing transformation of past publishing practices to Open Science is being fostered by a broad coalition of stakeholders comprised of research institutions, publishing houses, and governments. Open Science has recently received a strong endorsement from UNESCO. Natural Sciences is an inter- and multidisciplinary journal that publishes outstanding research from the global community spanning biology ,chemistry , and physics and their interfaces, as well as seminal works from related fields such as engineering andbiomedical research .In contrast to other high-ranking journals, Natural Sciences is run by practicing academic scientists who treat submitted papers just like they wish their own papers would be treated – fairly, quickly, and without bias. That’s why the tagline reads A Journal of, by, and for Scientists . In developing the concept of Natural Sciences , we work closely with Wiley to ensure efficient editorial practices. Wiley’s international network of experienced professionals steeped in scientific publishing is there for us 24/7. Together, we are committed to Open-Science publishing that is timely and rigorous – and to embracing Open-Science innovations in the process. The main ideas that led us to envision Natural Sciences are summarized in our Manifesto.As examples of what Natural Sciences has achieved so far, we invite you to check out our highly cited and downloaded articles:Top Cited Articles: Natural SciencesTop Downloaded Articles: Natural SciencesWe hope that the appeal of Open Science in general and of Natural Sciences in particular will make both the publishing model and the journal continue to prosper in the years to come. This is the submission link. Please note that any article publication charges are waived throughout 2024 .We look forward to your submissions,Elaine Bearer – Chief Editor for BiologyGerard Meijer – Chief Editor for PhysicsBretislav Friedrich – Academic Executive Editor

Aiming at solving the problem that the capability of direction of arrival (DOA) method for estimation of nested arrays decreases sharply under unknown mutual coupling, an iterative weighted low rank matrix reconstruction (IW-LRMR) algorithm is proposed in this paper. Firstly, the received data covariance matrix is extended, and a weighted low-rank matrix recovery problem is formulated for joint estimations of the Toeplitz matrix and mutual coupling coefficients. Next, the DOA from recovered Toeplitz matrix is retrieved by using the root multiple signal classification (Root-MUSIC) algorithm. Experimental results show that IW-LRMR algorithm can effectively avoid the influence of mutual coupling while solving the grid mismatch problem so that the accuracy and the resolution of estimation are improved.

Carbon emissions limit the output demand of traditional fuel-generating units, significantly affecting the electric power and energy balance scheduling mechanisms of modern power systems. To address this, we first analyzed the short-term electric power and energy balance from a dual perspective, along with the electro-carbon coupling mechanism of dynamic dispatching on the source-load side. Based on this analysis, we constructed a framework for low-carbon bilateral demand response (LCBDR). Subsequently, based on the carbon emission flow theory, the carbon emission index information of the demand response system was obtained. Therefore, the short-term electric power and energy balance optimal scheduling model for LCBDR is established to achieve a low-carbon economy. In this study, the enhanced decision tree classifier (EDTC) algorithm is used to predict the electricity consumption behavior of transfer load (TL) user load, and an improved ‘ ε-greedy’ strategy particle swarm optimization (PSO) algorithm is proposed to realize the coordinated optimization of daily operational cost and daily carbon emission of the regional power grid. Finally, by setting up three different perspectives of the simulation examples, the proposed method can effectively realize the regional power grid’s low-carbon, economical, and efficient operation. The feasibility of the model can be verified via the IEEE-30 bus system.

Dry Needling in the Management of Chronic Tension Type Headache Associated with

Water transport timescales (WTTs) quantify how long it takes for water to travel through or remain in a system and are often cast as indicators of ecosystem function and health. Such timescales are known to be affected by vegetation in various environments. We quantify the impact of floodplain vegetation on WTTs within the Wax Lake Delta (WLD), a river delta system in Louisiana, USA, using a high-resolution Delft3D Flexible Mesh (DFM) model incorporating vegetation-induced flow resistance. We show that increased vegetation density leads to extended WTTs within vegetated sections of WLD while fostering flow localization and accelerating transport within distributary channels. We find that the presence or absence of floodplain vegetation significantly influences the volumetric flow directed toward the floodplain, with spatial distribution exerting more control than vegetation density. Vegetation density and spatial arrangement have minimal impact on flow directed out of the deltaic floodplain, indicating that vegetation does not constrain flow across the bayward boundary. Floodplain vegetation strongly influences local-scale transport timescales within the deltaic floodplain but minimally affects water age distributions within distributary channels. Furthermore, network-scale water age distribution remains largely unaffected by vegetation density and spatial arrangement, except for slight modifications in the heavy right tail of the distribution. These findings contribute to a better understanding of how vegetation affects deltaic hydrology across scales, highlighting the importance of considering multi-scale vegetation influences for coastal restoration and management strategies.

Aim of the study: Snoring is one of the main symptoms of obstructive sleep apnea syndrome (OSAS) patients. In this study, it was aimed to investigate whether snoring sound parameters can be used in pre- polysomnography (PSG) screening in patients with OSAS. Methods: All patients underwent full-night PSG test. Sound parameters were measured using the PRAAT acoustic analysis program. The relationship between these parameters and degree of OSAS, and also the relationship between snoring sound and types of OSAS were analyzed prospectively. Results: Seventy seven patients diagnosed OSAS were included the study. It was found that the shimmer scores decreased significantly from mild OSAS to severe OSAS (p=0.045). Although mean pitch scores increased from mild to severe OSAS, it was not found to be statistically significant (p=0.16). Mean pitch score was found to be significantly higher in the severe group (p=0.022). Shimmer scores were found significantly higher in REM-predominant OSAS patients than without REM-predominant OSAS patients (p=0.006). Shimmer scores were significantly higher in obese patients than in non-obese patients and in patients over 40 years of age years than under 40 years of age (p=0.032; p<0.01; respectively). The ROC analysis was performed to determine the cutoff value of mean Pitch (≥74.65) in predicting severe OSAS classification (AUC=0.69; p=0.017). Conclusion: Our results are important to show that, analysis of snoring sound with a noninvasive method of acoustic voice analysis, can be applied quickly and easily in the pre-PSG screening in especially clinically important advanced-stage OSAS cases that should be diagnosed urgently.

Ru nanoparticles supported mesoporous silica based [COK-12]-NH2 3 and [COK-12]-NH2-imid 4 were prepared by a condensation method using the [COK-12]-NH2 1 or [COK-12]-NH2-imid 2, respectively. The catalysts 3 and 4 were characterized by various methods, including 3 and 4 by 29Si solid state NMR, XPS, TEM spectroscopy. They were assessed as catalysts in the hydrolytic production of H2 from NaBH4. Their efficiency was measured and the influence of several parameters of NaOH concentration, temperature, catalyst loading and NaBH4 on the reaction were studied to identify the best reaction conditions. Catalyst 4 was found to be more efficacious than 3. The study of kinetics indicated that the catalytic hydrolysis is first order with Ea of 29.0 and 32.1 kJ mol−1 for catalysts 4 and 3, respectively. Finally, the stability of catalyst 4 was also examined: the activity of RuNP catalyst 4 which was 84% in the first run remained at 80% after the fourth run.

The purpose of feature selection in protein sequence recognition problems is to select the optimal feature set and use it as training input for classifiers and discover key sequence features of specific proteins. In the feature selection process, relevant features associated with the target task will be retained, and irrelevant and redundant features will be removed. Therefore, in an ideal state, a feature combination with smaller feature dimensions and higher performance indicators is desired. This paper proposes an algorithm called IIFS2.0 based on the cache elimination strategy, which takes the local optimal combination of cached feature subsets as a breakthrough point. It searches for a new feature combination method through the cache elimination strategy to avoid the drawbacks of human factors and excessive reliance on feature sorting results. We validated and analyzed its effectiveness on the protein dataset, demonstrating that IIFS2.0 significantly reduces the dimensionality of feature combinations while also improving various evaluation indicators. In addition, we provide IIFS2.0 on http://112.124.26.17:8006/ for researchers to use.

Recombinant adeno-associated virus, serotype 9 (rAAV9) has shown promise as a gene therapy vector for muscle and central nervous diseases. High-dose requirements of these therapies present critical safety considerations and biomanufacturing challenges. Notably, reduction of empty capsids (ECs), which lack therapeutic transgene, from rAAV9 products is critical to maximize efficacy. Removal of rAAV ECs from full capsids is a major downstream challenge because of their highly similar biophysical characteristics. Ultracentrifugation (UC) reduces ECs but is laborious and difficult to scale. In this paper, to replace a poorly scalable UC process, we developed an anion exchange (AEX) chromatography for rAAV9 EC reduction from full capsids. AEX load preparation by dilution incurred major product loss. Addition of an osmolyte amino acid and surfactants to dilution buffers increased yield and reduced aggregation. Elution salts were screened to maximize yield and EC reduction. The most promising load dilution buffer and elution salt were used in combination to form an optimized AEX method. The process reduced ECs three-fold, demonstrated robustness to a broad range of EC load challenges, and was scaled for large scale manufacture. Compared to UC, the AEX method simplified scale-up, reduced ECs to comparable levels (20%), afforded similar purity and product quality, and increased yield by 14%.

A robust interacting multiple model approach is proposed to address the problem of accuracy and non-Gaussian measurement noise in maneuvering target tracking. Firstly, the interacting multiple model effectively improves the accuracy of maneuvering target tracking. Secondly, the multiple fading factors are introduced into the prediction covariance matrix for adjusting the gain matrix in real-time to enhance the accuracy caused by model mismatch and improve the ability of state transitions. Finally, the maximum correntropy criterion effectively promotes the robustness to outliers. The effectiveness of the proposed approach has been verified through simulation.

Optimizing the extraction efficiency of rapeseed oil and protein, which is crucial for achieving sustainability, necessitates overcoming challenges such as low protein extraction rates and high solvent usage in aqueous extraction processes. Therefore, innovative approaches are required to simultaneously achieve high-yield extraction with minimal solvent consumption to advance industrial utilization. This study explores an economically viable approach for extracting oil and protein from rapeseed using multi-stage countercurrent extraction with low-temperature-and-alkali-assisted aqueous extraction processing (LA-AEP). Optimal LA-AEP conditions were identified at a material-to-solvent ratio of 1:4 (w/v), pH 11.0, and 40 oC, yielding a residual oil content of just 5.00%. Subsequently, four-stage countercurrent FC-LA-AEP was conducted, resulting in a reduced residual oil content of less than 3.42% and an increased protein concentration in the water phase to 5.90% (w/w). Notably, only 2.00 L/kg of rapeseed was required as the extracting agent. Rapeseed oil obtained through FC-LA-AEP exhibited tocopherol and sterol contents of 42.78 mg/100 g and 378.25 mg/100 g, respectively. FC-LA-AEP emerges as a promising method for rapeseed oil extraction, offering mild operating conditions, simultaneous high-quality oil and protein extraction, and minimal aqueous usage.

A power distribution system occasionally requires uninterrupted load transfer to avoid affecting the quality of power consumption, but the differences in voltage amplitudes and phases of both feeders may cause short-duration high currents. The critical issue of possible solutions is the different phase angles. This paper proposes the joint application of an energy storage system (ESS) and a proportional–integral controller to compensate for the active and reactive power in one feeder while using the voltage of the other feeder as the target value. The compensated power is injected into the transfer feeder buses to regulate the voltage amplitude and phase angles, thereby alleviating short-duration high currents during the load transfer of feeders. In this study, MATLAB/Simulink was used for circuit simulation analysis, and an 11.4 kV feeder model for three-phase power distribution systems, as well as an energy storage device, was constructed. Finally, the simulation results are analyzed to examine the improvement of transfer current under different feeder load scenarios.

At deep-sea hydrothermal vents, deprived of light, most living communities are fuelled by chemosynthetic microorganisms. These can form symbiotic associations with metazoan hosts, which are then called holobionts. Among these, two endemic shrimp of the Mid-Atlantic Ridge (MAR), Rimicaris exoculata and Rimicaris chacei are colonized by dense and diversified chemosynthetic symbiotic communities in their cephalothoracic cavity and their digestive system. Although both shrimp harbor similar communities, they exhibit widely different population densities, distribution patterns at small scale and diet, as well as differences in post-settlement morphological modifications leading to the adult stage. These contrasting biological traits may be linked to their symbiotic development success. Consequently, key questions related to the acquisition of the symbionts and the development of the holobiont are still open. Here we examined symbiotic development in juveniles of R. exoculata and R. chacei from TAG and Snake Pit using 16S metabarcoding to identify which symbiotic lineages are present at each juvenile stage. In addition, we highlighted the abundance and distribution of microorganisms at each stage using Fluorescence in situ Hybridization (FISH) and Scanning Electron Microscopy (SEM). For the first time, Candidatus Microvillispirillaceae (midgut tube), Candidatus Foregutplasma rimicarensis and Candidatus BG2-rimicarensis (foregut) were identified in late juveniles stages. However, these lineages were absent in early juveniles stages, which coincides for the midgut tube with our observations of an immature tissue, devoid of microvilli. Conversely, symbiotic lineages from the cephalothoracic cavity were present from the earliest juvenile stages of both species and their overall diversities were similar to those of adults. These results suggest different symbiont acquisition dynamics between the cephalothoracic cavity and the digestive system, which may also involve distinct transmission mechanisms.

Ubiquitylation, a critical post-translational modification, regulates various biological pathways. Despite its implications in diseases like cancer, the ubiquitinome of the human hypothalamus remains inadequately explored. We conducted label-free ubiquitinome analysis on hypothalamus samples from healthy elderly individuals, identifying 21,815 ubiquitylated sites across 5,314 proteins. Motif analysis revealed specific residue preferences. Functional enrichment analysis revealed significant roles in cellular processes, particularly in transport and catabolism pathways. Analysis of E3 ligase and deubiquitinating enzyme substrates emphasized dynamic protein turnover regulation. Integration with pathway analysis unveiled the significance of ubiquitinated proteins in neurological pathways, underscoring their relevance to neurological function and dysfunction. This study provides crucial insights into hypothalamic ubiquitination, highlighting the pressing need for further investigation into ubiquitin-mediated pathways in neurological disorders.

This paper may be the first meta-analysis that presents a comprehensive synthesis of scientific works spanning the last five years, focusing on methodologies and results related to the analysis of nanocomposite using nanoparticules. The primary objective is to identify the optimal algorithm using software information and leading to better classification methodology. Specifically, this study come up with the advantages and the drawbacks of the most used algorithms and proposes an enhancement and performance of Recurrent Neural Networks based Long Short Term Memory (LSTM) neurons. Besides, a comparaison of Deep Learning methods for the classification of polymeric nanoparticles, with polypropylene serving as a case study will be implemented. Experiment comparison were conducted to assess with one physical property, later expanded to four properties and finally to eight properties. Neural networks, including Artificial Neural Networks (ANN), Recurrent Neural Networks (RNN), and Recurrent Neural Networks-Monte Carlo, were employed for simulations. The evaluation criteria encompassed accuracy, calculation time, mean square error (MSE) and other metrics. The findings contribute to the selection of an optimal algorithm for the analysis of polymeric nanoparticles, emphasizing the potential of Deep Learning methodologies, particularly Recurrent Neural Networks Monte Carlo, in advancing classification accuracy and efficiency.

Fluid inclusions in mineralized fracture infillings (i.e. veins) could preserve information about subsurface fluids like temperature and salinity. The isotopic composition of water in these fluid inclusions could provide direct evidence of the provenance of these mineral forming fluids. So far, the isotope compositions of fluid inclusions have been mainly derived from carbonate veins and other precipitates, like speleothems. The aim of this study is to analyse the δ18O and δ2H isotopic compositions of aqueous fluid inclusions of quartz veins using a Cavity Ring-Down Spectroscopy (CRDS) analyser in combination with a moisturized nitrogen background and mechanical crusher. For this study, we analysed δ18O and δ2H values of fluid inclusions in quartz veins from three north-western European locations formed during the Variscan orogeny. Prior to crushing, the fluid-rich quartz fraction was separated from the pure quartz fraction, from other mineral phases and host rock by using conventional heavy liquids and magnet separation. Raman spectrometry detected some rare occurrences of hydrocarbon, methane and nitrogen in the fluid inclusions. The samples were sequentially crushed to elucidate the potential impact of different fluid inclusion assemblages (FIA) on the δ18O and δ2H values. The results from single and sequential mechanical crushing, together with interlaboratory comparisons, exhibit reliable and consistent isotopic patterns across locations with high precision (for δ18O: 1σ SD < 0.8 ‰; for δ2H: 1σ SD < 1.5 ‰). The obtained data trends three different clusters for three study zones, providing evidence for the presence of meteoric-derived fluids in the fold-and-thrust belt of the Variscan orogeny. These findings demonstrate that the CRDS approach can be successfully applied to quartz minerals, investigating fluid pathways within the upper crust and the formation of these secondary minerals.

In this article, a two prey-one predator model in which prey and predator disperse simultaneously in a heterogeneous environment with n patches is proposed and analyzed. We prove that the solution of the system is positive and uniformly ultimately bounded. Meanwhile, we use the monotonic theory of spectral bounds to investigate the effect of the dispersal rate on population dynamics. To be precise, we discuss the stability behaviour for the trivial equilibrium and semitrivial equilibrium as well as the uniform persistence of the system. Furthermore, we prove the global asymptotic stability of the positive equilibrium by constructing a global Lyapunov function which applies the results from graph theory. Some numerical simulations are provided to show the effectiveness of the theoretical results.

One of the most important sources of gas emissions is municipal solid waste. In the context of renewable energy production and greenhouse gas emission reduction, we are interested in the biogas produced by the decomposition process of organic matter under anaerobic conditions in a controlled landfill. We present a mathematical model of anaerobic digestion with acidogenic and methanogenic biomasses. Then, we analyze the model and show that an infinite number of non-hyperbolic equilibria induce an attractor. We give numerical results that highlight the impact of the mortality of acidogenic and methanogenic biomasses on biogas production.

Thermal images, extensively utilized in various communication applications, are concurrently impacted by noise, contrast, and details. However, existing image restoration methods, designed for RGB domain, exhibit suboptimal effects when applied to thermal domain due to a lack of consideration for the interaction between noise and contrast, consequently resulting in detail losses. In this letter, we propose a two-stage deep network based on this interaction for thermal image enhancemnet. Our network decouples the image restoration task into a denoising stage and a contrast improvement stage for simultaneous denoising and contrast improvement. Detail information is extracted, preserved, and fused in the process of the entire network to avoid the detail losses. Extensive experiments show that our propsoed method outperforms other state-of-the-art approachs in terms of PSNR , SSIM, and visual effect.

A rare case of wheat-dependentexercise-induced anaphylaxis induced by exercise 5 hours after wheat ingestion.Tomoki Yaguchi1, Katsutoshi Nakano1, Tadayuki Kumagai1Department of Pediatrics, Yaizu City Hospital, Shizuoka, JapanCorresponding authorTomoki Yaguchi, 1000, Dobara, Yaizu-shi, Shizuoka 425-0055, Japan. Phone: +81-54-623-3111, Fax: +81-54-624-9103, E-mail: ravvvvish@gmai.l.comWord Count for Main Text; 916The number of Table; 1, Figure; 0Keywords：wheat-dependent exercise-induced anaphylaxis, food allergy, aspirin, sensitization, anaphylaxis

Bilema Community Conserved Area (BCCA) was degraded due to intensive human encroachment and many of the wild animals were eliminated. However, since the last 30 years the area has been well conserved and rehabilitated by the surrounding community’s initiatives, and carnivores could recover and reoccupy it. The current study aimed to assess the level of livestock predation in and around BCCA. Call-up method was applied to estimate carnivore densities and questionnaire surveys were conducted to estimate the magnitude of carnivore predation at three different distant villages from the periphery of the BCCA. The study revealed that spotted hyena (Crocuta Crocuta) and black-backed jackals (Lupulella mesomelas) were the major livestock predators in BCCA. A density 1.6 of spotted hyenas and 0.36 of black-backed jackals were recorded per one ha of the conserved area. Spotted hyenas attacked cattle, sheep, goats and donkeys, while black-backed jackals predated sheep, goats and poultries. About 5.4% of the total livestock owned by the respondents were predated by the two carnivores in three years period (2021 – 2023) and responsible for 36,796 USD economic loss. Spotted hyenas’ predation mainly from enclosure and their higher predation was recorded during the wet season, while black-backed jackals attacked livestock around the periphery mainly from the inside of BCCA, and their higher kills were recorded during the dry season. Spotted hyena predations exhibited significantly higher outside of the BCCA, and nearly consistent from boarders of the BCCA towards outside. In total, livestock predation strongly affects local communities’ livelihoods around BCCA. When predators attack continue, people may be triggered to retaliate against predators which in turn threatens the persistence of carnivore populations. Hence, for the sustainable coexistence of carnivores and local communities living around BCCA proper compensation of the economic loss and appropriate conflict mitigation practices should be promoted and implemented.

Abstract: Effective biodiversity conservation requires reasonable targeted regionalization, and insufficient data and unclear targets often lead to conservation biases and deficiencies. So, we explored quantitative and representative methods to delineate freshwater biodiversity regions. We established a river-lake network model as the mask of the Yangtze River Basin. Based on field samplings and the literatures, we filtered the environmental variables by principal component analysis, and identified key factors to distribution of fish functional group and macroinvertebrate taxonomic group by Mantel test, then conducted species distribution models using maximum entropy modeling. We delineated biodiversity regionalization using the binary data of high suitability in the hydrological units (HUs) by spatial cluster analysis, then calculated Jaccard dissimilarity index (βdissim) among all HUs. Proportion of vegetation and waterbody type are key to the distribution of annelids and mollusks, while distribution of arthropods depend more on bioclimatic and topographic variables. For fish, topographic and hydrological variables were more important. We have delineated seven freshwater biodiversity regions (HWR, HDR, WSR, DQR, QWR, LXR and FPR). The βdissim of fish is the highest in LXR and FPR, while for macroinvertebrates, it is the highest in HWR. Species distribution models could compensate for the scarce and uneven data. Single target, and region delineation based on provincial administration or subbasins are insufficient for biodiversity conservation. Transition zones and confluent regions exhibit higher species richness and beta diversity, while these regions are often overlooked. We hope the method could serve as a reference to realize comprehensive of systematic conservation planning for biodiversity conservation.

Large language models (LLMs), with their billions to trillions of parameters, excel in natural language processing, machine translation, dialogue systems, and text summarization. These capabilities are increasingly pivotal in the Metaverse, where they can enhance virtual interactions and environments. However, their extensive use, particularly in the Metaverse’s immersive platforms, raises significant privacy concerns. This paper analyzes existing privacy issues in LLMs, vital for both traditional and Metaverse applications, and examines protection techniques across the entire life cycle of these models, from training to user deployment. We delve into cryptography, embedding layer encoding, differential privacy and its variants, and adversarial networks, highlighting their relevance in the Metaverse context. Specifically, we explore technologies like homomorphic encryption and secure multi-party computation, which are essential for Metaverse security. Our discussion on Gaussian differential privacy, Renyi differential privacy, Edgeworth accounting, and the generation of adversarial samples and loss functions, emphasizes their importance in the Metaverse’s dynamic and interactive environments. Lastly, the paper discusses the current research status and future challenges in the security of LLMs within and beyond the Metaverse, emphasizing urgent problems and potential areas for exploration.