ON THE EIGENVALUE PROBLEM FOR ELLIPTIC SYSTEMS WITH STRONGLY EIGEN-EXPONENT UNDER NATURAL GROWTH CONDITIONS

Let Ω be a bounded domain with smooth boundary Ω in R~n. We consider the following eigenvalue problem for systems of elliptic equations under the natural growth conditions

EMERGENT PERMITTING STRATEGIES FOR NATURAL BUILDING SYSTEMS IN ONTARIO

INTRODUCTION Lowering the carbon intensity of the built environment is one of many tasks that must be undertaken in order to address climate change and to encourage sustainability.The siting,design,construction,occupancy,renovation,and disposal of single-family homes are all factors that contribute to the large carbon emissions generated by the sector.There are numerous strategies that seek to minimize the amount of emissions generated by a house during its lifecycle.This paper explores the use of so-called natural building systems in building envelope construction.

The research priorities of Resources and Environmental Sciences

The great challenges of sustainable development highlight an urgent need to systematically understand the mech-anisms linking humans and nature.Resources and Environmental Sciences are a broad and practical discipline focused on coupled human and natural systems.They aim to study the formation and evolution of resources in the earth system,the drivers of various environmental problems,processes and relationships between resources and the environment,particularly under the combined impacts of natural conditions and human activities.The major resources and environmental problems drive the discipline development;international science programmes guide the direction of the discipline;interdisciplinary and transdisciplinary integration promotes new branches of the discipline;and technological progress results in a research paradigm shift.Facing the critical research re-quirements of strengthening trans-and interdisciplinarity,breaking through the key technology,targeting major environmental and disaster issues,and supporting sustainable development,nine critical scientific issues should be focused on climate change impact and adaptation,petroleum and mineral resources,water cycle and water re-sources,soil and land resources,ecosystems,remote sensing and geographic information science,environmental science and technology,disaster risk,and global and regional sustainable development.Suggestions to enhancing funding systems,improve talent cultivation,develop scientific platforms,and strength international cooperation are provided in this study to support scientific policymaking.The promotion of Resources and Environmental Sci-ences enables a more comprehensive and in-depth understanding of economic development and environmental changes relevant to assure a more sustainable global development.

Two-stage approach to full Chinese parsing

Natural language parsing is a task of great importance and extreme difficulty. In this paper, we present a full Chinese parsing system based on a two-stage approach. Rather than identifying all phrases by a uniform model, we utilize a divide and conquer strategy. We propose an effective and fast method based on Markov model to identify the base phrases. Then we make the first attempt to extend one of the best English parsing models i.e. the head-driven model to recognize Chinese complex phrases. Our two-stage approach is superior to the uniform approach in two aspects. First, it creates synergy between the Markov model and the head-driven model. Second, it reduces the complexity of full Chinese parsing and makes the parsing system space and time efficient. We evaluate our approach in PARSEVAL measures on the open test set, the parsing system performances at 87.53% precision, 87.95% recall.

Development of the Marine Protected Areas Network for Restoration of the Degraded Underwater Landscapes of the Black Sea and Azov Sea

The paper is concerned with the development of a comprehensive methodology to establish a MPAs （marine protected areas） network in the Black Sea and Azov Sea region. Scientific basis to rationale establish that the MPAs network is a complex system of landscape zoning and mapping, defining their variability, sustainability, and geo-ecological condition, and taking into account evaluation of degradation of the underwater landscape over the past 100 years.

The in vitro proliferation and cytokine production of Vα24＋Vβ11＋ natural killer T cells in patients with systemic lupus erythematosus

Background Activation in vitro of natural killer T （NKT） cells in systemic lupus erythematosus （SLE） with a-galactosylceramide （a-GalCer） and dendritic cells （DC） may affect the immunoregulatory role of NKT cells. This study was designed to compare the number of NKT cells in patients with SLE to the number in healthy volunteers and measure the cytokines secreted from these NKT cells in vitro. Methods Three sets of culture conditions using （i） a-GalCer, （ii） DC, or （iii） both a-GalCer and DC （a-GalCer＋DC） were adopted to expand NKT cells from peripheral blood mononuclear cells （PBMC） of patients with SLE and healthy volunteers. Flow cytometry was used to assess the levels of interleukin （IL）-4, IL-10, interferon （IFN）-y and tumor necrosis factor （TNF）-a produced by the Vα24＋Vβ11＋ NKT cells. Results After 14 days in culture, the total cell count and percentage of Vα24＋Vβ11＋ NKT cells were increased under all conditions but were highest in the a-GalCer＋DC group. The level of IL-4 and IL-10 secreted by Vα24＋Vβ11＋ NKT cells from patients with active SLE was found to be higher than that of inactive patients and the control group （P 〈0.05）, while the levels of IFN-y and TNF-a were lower than those found in the inactive and control groups （P 〈0.05）. Conclusions Va24＋V^11＋ NKT cells showed the greatest expansion in vitro with a-GalCer and DC. Th2-type cytokines from Vα24＋Vβ11＋ NKT cells are the predominant type in patients with SLE, while Th 1 cytokines predominate in the control group. This evolution of NKT cell function during the progression of the disease may have important implications in understanding the mechanism of SLE and for the development of possible therapies using NKT cell agonists.

Arabic Dialect Identification in Social Media:A Comparative Study of Deep Learning and Transformer Approaches

Arabic dialect identification is essential in Natural Language Processing(NLP)and forms a critical component of applications such as machine translation,sentiment analysis,and cross-language text generation.The difficulties in differentiating between Arabic dialects have garnered more attention in the last 10 years,particularly in social media.These difficulties result from the overlapping vocabulary of the dialects,the fluidity of online language use,and the difficulties in telling apart dialects that are closely related.Managing dialects with limited resources and adjusting to the ever-changing linguistic trends on social media platforms present additional challenges.A strong dialect recognition technique is essential to improving communication technology and cross-cultural understanding in light of the increase in social media usage.To distinguish Arabic dialects on social media,this research suggests a hybrid Deep Learning(DL)approach.The Long Short-Term Memory(LSTM)and Bidirectional Long Short-Term Memory(BiLSTM)architectures make up the model.A new textual dataset that focuses on three main dialects,i.e.,Levantine,Saudi,and Egyptian,is also available.Approximately 11,000 user-generated comments from Twitter are included in this dataset,which has been painstakingly annotated to guarantee accuracy in dialect classification.Transformers,DL models,and basic machine learning classifiers are used to conduct several tests to evaluate the performance of the suggested model.Various methodologies,including TF-IDF,word embedding,and self-attention mechanisms,are used.The suggested model fares better than other models in terms of accuracy,obtaining a remarkable 96.54%,according to the trial results.This study advances the discipline by presenting a new dataset and putting forth a practical model for Arabic dialect identification.This model may prove crucial for future work in sociolinguistic studies and NLP.

Water quality monitoring and evaluation using remote sensing techniques in China:a systematic review

Introduction:The application of remote-sensing techniques for water quality assessment has become increasingly popular in China.However,existing reviews are often limited to qualitative description and are quite fragmented.Outcomes:We conducted a quantitative systematic review to display current research status and identify the existing challenges and future directions.Our review revealed that the application of remote-sensing techniques in water quality research has expanded dramatically in China,but the spatial distribution is quite uneven.Second,the ground object spectrometer is the most widely applied data source.Water color indicators such as chlorophyll a and suspended solid are the most widely investigated in China.Third,semiempirical method is the most commonly used inversion method.Existing studies rarely considered the anthropogenic factors,which limited the model robustness and its application in humandominated aquatic ecosystems.Discussion and Conclusion:We concluded that,in the past several decades,China has made notable progresses in monitoring and evaluation of water quality using the remote-sensing techniques(especially in inland lakes).We proposed that further improvements would be needed in terms of temporal and spatial coverage,indicator list,the incorporation of human–nature interactions,inversion accuracy,and model generalization.

Socioecological drivers facilitating biodiversity conservation in traditional farming landscapes

Traditional farming landscapes have evolved as tightly coupled socioecological systems that support high biodiversity.However,land-use change severely threatens the high biodiversity of these landscapes.Navigating nature conservation in such landscapes requires a thorough understanding of the key drivers underpinning biodiversity.Through empirical research on mammals,birds,butterflies,and plants in a traditional cultural landscape in Romania,we revealed seven hypothesized drivers facilitating biodiversity conservation.Similar proportions of three main land-use types support the landscape species pool,most likely through habitat connectivity and frequent spillover between land-use types.Landscape complementation and supplementation provide additional habitat for species outside their core habitats.Gradients of woody vegetation cover and gradients in land-cover heterogeneity provide mosaic landscapes with wide ranges of resources.Traditional land-use practices underpin landscape heterogeneity,traditional land-use elements such as wood pastures,and human-carnivore coexistence.Top-down predator control may limit herbivore populations.Lastly,cultural ties between humans and nature have a central influence on people’s values and sustainable use of natural resources.Conservation approaches should aim to maintain or restore these socioecological drivers by targeting the heterogeneous character of the forest-farmland mosaic at large scales through"broad and shallow"conservation measures.These large-scale measures should be complemented with"deep and narrow"conservation measures addressing specific land-use types,threats,or species.In both cases,conservation measures should integrate the entire socioecological system,by recognizing and strengthening important links between people and the environment.

Enhancing Tax Administration Capacity

The COVID-19 pandemic has shown us the societal importance of tax administration service delivery capacities and agility.Tax administration capacity is a key factor for nurturing both societal resilience and domestic resource mobilisation.Tax administrations around the globe are implementing new digital technologies to enhance taxpayer service quality,reduce operational and compliance burdens and increase revenues.In addition to the ongoing incremental improvement of the core tax administration functions,there are also increasing signs of transformation towards a more fundamental change in the nature of tax administration.This concerns a more system-wide compliance management approach in which tax administrations try to closely engage with the natural systems that taxpayers use to manage their business,engage in transactions and communicate in order to reduce errors,minimise burdens and increasingly build tax compliance.This paper explores the way in which tax administrations are enhancing the capacity of core functions and are preparing for a more holistic compliance management approach,including using an increasing amount of digital data sources facilitated by the introduction of new digital innovations.

Application of Grammatical Parsing Technique in Chinese Input

In Peking University Computer Research Institute (PUCRI) a method of inputting Chinese sentences based on words has been developed. To reduce the troubles in choosing one word out of the others characterized by the same feature, grammatical parsing technique is applied to the method and good results have been achieved. This article describes the outline of the method, the principle of applying grammatical formulas and the branch-cutting algorithm used to speed up the grammatical parsing.