Modelling Land Use/Land Cover Change of River Rwizi Catchment, South-Western Uganda Using GIS and Markov Chain Model

Analysis of catchment Land use/Land cover (LULC) change is a vital tool in ensuring sustainable catchment management. The study analyzed land use/land cover changes in the Rwizi catchment, south western Uganda from 1989-2019 and projected the trend by 2040. Landsat images, field observations, key informant interviews and focus group discussions were used to collect data. Changes in cropland, forestland, built up area, grazing land, wetland and open water bodies were analyzed in ArcGIS version 10.2.2 and ERDAS IMAGINE 14 software and a Markov chain model. All the LULC classes increased in area except grazing land. Forest land and builtup area between 2009-2019 increased by 370.03% and 229.53% respectively. Projections revealed an increase in forest land and builtup area by 2030 and only built up area by 2040. LULCC in the catchment results from population pressure, reduced soil fertility and high value of agricultural products.

Emoti-Shing: Detecting Vishing Attacks by Learning Emotion Dynamics through Hidden Markov Models

This study examines vishing, a form of social engineering scam using voice communication to deceive individuals into revealing sensitive information or losing money. With the rise of smartphone usage, people are more susceptible to vishing attacks. The proposed Emoti-Shing model analyzes potential victims’ emotions using Hidden Markov Models to track vishing scams by examining the emotional content of phone call audio conversations. This approach aims to detect vishing scams using biological features of humans, specifically emotions, which cannot be easily masked or spoofed. Experimental results on 30 generated emotions indicate the potential for increased vishing scam detection through this approach.

D-S理论和Markov链组合的桥梁性能退化预测研究

为准确预测桥梁性能退化,考虑到数据随机性和微小扰动发生状态跳跃,提出了一种D-S(Dempster-Shafer)证据理论和Markov链组合的桥梁性能退化组合预测模型和性能退化率的概念.该模型基于指数平滑(exponential smoothing,ES)方法获得新的预测数据序列,并利用Markov链和D-S理论不断进行优化,从而实现桥梁性能退化的组合预测.实际工程的应用结果表明:性能退化率可以直观地表征在梁性能退化的速度.其次,该模型的平均相对误差为1.54%,较于回归、灰色和模糊加权Markov链模型,精度分别提高了1.11%,0.88%和2.8%,而后验差比值为0.242,小于0.35;模型的标准差为9.021,相比其他模型分别减小了3.978,3.405和7.500,而变异系数为0.109,均小于其他模型,验证了组合预测模型在精度和稳定性方面的优越性,可为在役桥梁结构性能退化预测与维护提供理论基础.

基于InVEST与CA-Markov模型的宝鸡市碳储量时空演变与预测

土地利用类型的变化是影响陆地生态系统碳储量变化的重要因素,分析区域未来土地利用格局对碳储量的影响、对维持碳平衡具有重要意义.基于宝鸡市2000—2020年土地利用数据,运用InVEST模型和CA-Markov模型,对2000—2020年宝鸡市不同土地利用类型碳储量的变化特征进行分析,并对2030年不同情景下宝鸡市土地利用变化及碳储量变化情况进行了预测.研究表明:①2000—2020年宝鸡市建设用地面积不断增加,耕地、林地和草地为主要土地利用类型.②2000—2020年,宝鸡市碳储量共损失0.42×10^(6)t,耕地和林地面积减少是其碳储量减少的主要原因.③2020—2030年自然发展情景下宝鸡市碳储量损失最多,耕地保护情景和生态保护情景下宝鸡市碳储量相差不大,控制城市扩张情景下宝鸡市碳储量损失最少、固碳能力最强.因此,未来进行国土空间规划时,可统筹考虑控制城市扩张情景、生态保护情景和耕地保护情景,以确保在粮食供给和生态安全的基础上,提高研究区的碳储量.

Effects of mesenchymal stem cell on dopaminergic neurons,motor and memory functions in animal models of Parkinson's disease:a systematic review and meta-analysis

Parkinson’s disease is chara cterized by the loss of dopaminergic neurons in the substantia nigra pars com pacta,and although restoring striatal dopamine levels may improve symptoms,no treatment can cure or reve rse the disease itself.Stem cell therapy has a regenerative effect and is being actively studied as a candidate for the treatment of Parkinson’s disease.Mesenchymal stem cells are considered a promising option due to fewer ethical concerns,a lower risk of immune rejection,and a lower risk of teratogenicity.We performed a meta-analysis to evaluate the therapeutic effects of mesenchymal stem cells and their derivatives on motor function,memory,and preservation of dopamine rgic neurons in a Parkinson’s disease animal model.We searched bibliographic databases(PubMed/MEDLINE,Embase,CENTRAL,Scopus,and Web of Science)to identify articles and included only pee r-reviewed in vivo interve ntional animal studies published in any language through J une 28,2023.The study utilized the random-effect model to estimate the 95%confidence intervals(CI)of the standard mean differences(SMD)between the treatment and control groups.We use the systematic review center for laboratory animal expe rimentation’s risk of bias tool and the collaborative approach to meta-analysis and review of animal studies checklist for study quality assessment.A total of 33studies with data from 840 Parkinson’s disease model animals were included in the meta-analysis.Treatment with mesenchymal stem cells significantly improved motor function as assessed by the amphetamine-induced rotational test.Among the stem cell types,the bone marrow MSCs with neurotrophic factor group showed la rgest effect size(SMD[95%CI]=-6.21[-9.50 to-2.93],P=0.0001,I^(2)=0.0%).The stem cell treatment group had significantly more tyrosine hydroxylase positive dopamine rgic neurons in the striatum([95%CI]=1.04[0.59 to 1.49],P=0.0001,I^(2)=65.1%)and substantia nigra(SMD[95%CI]=1.38[0.89 to 1.87],P=0.0001,I^(2)=75.3%),indicating a protective effect on dopaminergic neurons.Subgroup analysis of the amphetamine-induced rotation test showed a significant reduction only in the intracranial-striatum route(SMD[95%CI]=-2.59[-3.25 to-1.94],P=0.0001,I^(2)=74.4%).The memory test showed significant improvement only in the intravenous route(SMD[95%CI]=4.80[1.84 to 7.76],P=0.027,I^(2)=79.6%).Mesenchymal stem cells have been shown to positively impact motor function and memory function and protect dopaminergic neurons in preclinical models of Parkinson’s disease.Further research is required to determine the optimal stem cell types,modifications,transplanted cell numbe rs,and delivery methods for these protocols.

东北地区土地覆被格局变化模拟:基于CLUE-S和Markov-CA模型的对比分析

研究以遥感解译的东北地区2000年、2010年、2015年的土地覆被变化为基础,充分考虑自然和社会因素对土地覆被变化的影响,分别通过CLUE-S模型和Markov-CA模型对东北地区2015年和2030年土地覆被格局进行模拟,研究结果表明:通过与遥感解译的2015年实际土地覆被类型数据对比验证,CLUE-S模型和Markov-CA模型模拟结果的总体Kappa指数分别为0.9700和0.9649,结果表明2种模型的模拟结果较为理想,CLUE-S模型的模拟精度较Markov-CA模型更高。2015—2030年东北地区草地、耕地、湿地、其他用地和水体面积呈现下降趋势,林地、人工表面面积呈现增加趋势,人地关系越发紧张。东北地区作为生态环境相对脆弱的区域需警惕不可持续的土地覆被变化,需权衡生态保护、粮食增加与基础设施建设的用地需求和协调发展。

基于CA-Markov和InVEST模型的昆明市土地利用与生境质量时空变化及预测

基于2000年、2010年和2020年3期GlobeLand30土地利用数据,采用CA-Markov和InVEST模型,通过预测2030年土地利用以及生境变化特征,揭示昆明市土地利用变化趋势及对其生境质量时空演变的影响,为生态环境可持续性发展提供参考。结果表明:①研究区以耕地、林地和草地为主,2000—2020年由于退耕还林还草政策的实施和社会经济快速发展,耕地面积比例持续降低,人造地表面积比例增加,其他类型变化不大。②预计2030年人造地表扩张速度加快,主要是来自耕地、林地和草地的转换,除人造地表和草地外,其他用地类型面积均为下降趋势。③研究区于2010年景观破碎化程度达到最高,2020—2030年破碎化程度持续降低,各类型景观趋于简单化和规则化。④研究区平均生境质量逐渐降低,低生境质量区域与高生境质量区域面积逐渐增加,两极分化态势逐渐明显。

基于Markov-PLUS模型的福州市土地利用变化及情景模拟

为探究福州市土地利用变化规律,基于2000、2010和2020年GlobeLand30数据集,运用土地利用动态度和转移矩阵对2000—2020年土地利用演变进行剖析,采用Markov-PLUS模型对2030年土地利用的多情景变化趋势进行模拟。结果表明:2000—2020年,建设用地和水域面积增加,建设用地主要由耕地转入,其他用地面积减少。Markov-PLUS模型模拟总体精度为0.89,Kappa值为0.80,模拟效果较好。自然发展情景延续历史发展趋势,建设用地持续增长,以市辖区和闽侯县扩张最为突出,其他区(县、市)建设用地侵占周边耕地且集聚特征明显;城镇发展情景下,耕地、林地和草地均大面积减少,建设用地大幅增加,耕地和建设用地重心分别向东南和东北方向偏移,空间集聚特性进一步增强;耕地保护情景下,耕地主要向林地和建设用地转化,面积缩减的态势得到有效控制,重心迁移幅度较小;生态保护情景下,林地、草地和水域面积显著增加,建设用地增速得到有效控制,此情景更符合研究区区域发展和生态保护的双重诉求。研究可为福州市未来土地利用规划编制和土地可持续利用情景预测提供科学参考。

基于FLUS-Markov模型的玉溪市生态系统服务价值时空演变与预测

基于玉溪市2010年、2020年2期生态景观类型数据和粮食产量经济价值修正生态系统服务价值系数,分析玉溪市生态景观类型及生态系统服务价值分布特征,采用FLUS-Markov模型预测玉溪市2030年生态系统服务价值及其分布。结果表明,该模型预测结果的Kappa系数提高至0.8969,整体精度为0.9393,精度较高;2010—2020年玉溪市林地、草地的面积呈减少趋势,以林地、草地、水域为主的生态系统仍然面临威胁;2030年玉溪市生态系统服务价值为535.0471亿元,变化率为-0.1297%,玉溪市应加强对林地、草地的保护,加强退耕还林、退耕还草政策的实施,合理控制草地、林地向耕地的转化;2030年玉溪市生态系统服务价值依然表现为西部>中部>东部;2030年玉溪市各县市区生态系统服务价值贡献率由高到低依次为新平县、元江县、峨山县、易门县、华宁县、红塔区、江川区、澄江市、通海县。

Evaluating the role of large language models in inflammatory bowel disease patient information

This letter evaluates the article by Gravina et al on ChatGPT’s potential in providing medical information for inflammatory bowel disease patients.While promising,it highlights the need for advanced techniques like reasoning+action and retrieval-augmented generation to improve accuracy and reliability.Emphasizing that simple question and answer testing is insufficient,it calls for more nuanced evaluation methods to truly gauge large language models’capabilities in clinical applications.

基于CLUE-S和Markov模型的土地利用变化模拟预测

土地利用变化过程是极其复杂的,主要是因为其在变化的过程中不仅仅是单一因素作用的结果,而是多种因素掺杂在一起形成的复杂过程。在经济快速发展的今天,一旦区域土地利用存在不合理的情况,极容易影响区域资源可持续利用以及和谐稳定的状态,土地利用变化模拟预测可以改善土地利用结构、提高土地利用效率,帮助相关部门规划国土空间布局,缓解人地矛盾,实现自然资源可持续发展。本文是基于高分辨率遥感影像解译得到靖远县2期土地利用数据,并利用CLUE-S与Markov模型相结合的方法对靖远县未来土地利用变化从自然发展、耕地保护和生态安全三种情景进行预测。结果表明,(1)CLUE-S模型相对于小尺度的土地利用变化模拟预测的效果较好,精度较高。(2)建设用地在自然发展情景下的增加是最为显著的,在其他两种情景下受到限制因素后在减少,草地和耕地只有在自然发展情景下是减少,林地只在耕地保护情景下是减少,水域用地和未利用地都在自然发展情景下是增加的。(3)生态安全情景与耕地保护情景对未来土地利用变化的调控效果较好,林地、草地和耕地受到了更好的保护。研究表明,区域土地利用模拟预测可以更好地为土地利用规划编制提供参考。

基于InVEST和CA-Markov模型的“十四五”碳储量时空演变与预测——以张家界市为例

基于多情景模拟不同土地利用类型的碳储量,为张家界市实现旅游与生态发展提供建议。以张家界市2000年、2010年、2020年土地利用变化作为切入点,基于InVEST模型与CA-Markov模型,对不同时空的土地利用类型下的碳储量进行空间情景模拟和量化,探讨不同情景下的土地利用及其碳储量变化模式。结果表明:张家界市主要以林地、耕地为主,建设用地的增加主要来自耕地与草地;碳储量在空间分布上呈明显聚集性;碳储量呈逐年减少的趋势,共减少了0.35×10^(6)t。在不同的情景模拟下,相对于2020年,碳储量流失总量分别为3.44×10^(6)、3.04×10^(6)、3.99×10^(6)、4.93×10^(6) t。综合发展情景下的土地利用现状最为合理,能够为区域碳平衡和土地利用结构优化提供依据,助力张界市实现“双碳”目标与旅游高质量发展。

基于CA-Markov和InVEST模型的莆田市生态系统服务功能研究

在城市化影响下,建设用地的扩张对未来生态系统服务水平产生负面影响。评估并预测未来土地利用变化以及生态系统服务,可为城市可持续发展的规划和决策提供有效支持。为研究莆田市绿色空间变化及生态系统服务价值的动态趋势,基于CA-Markov模型分析莆田市2030年土地利用空间分布情况,运用InVEST模型对未来生态系统服务功能进行评估,进而分析其绿色空间格局。结果表明:(1)2020-2030年,莆田市建设用地持续扩张,增长至732.10km^(2),水体、林地、耕地、草地等绿色空间在未来10年整体面积将缩减97.92km;(2)经标准化后的莆田市总生态系统服务指数由2020年的0.5963缩减至2030年的0.5820,这主要由于绿色空间被建设用地侵占,导致总体生态系统服务水平发生下降;空间上,莆田市总生态系统服务评估指数呈现出"北部高,南部低"的分布特点;(3)将莆田市生态系统服务绿色空间分为高、中、低三级,其中高、中生态系统服务绿色空间面积将在2030年分别缩减至1556.60km^(2)、178.53km^(2),低生态系统服务绿色空间面积在2030年增加至1382.80km^(2)。未来城市绿色空间规划中,应当限制建设用地的进一步扩张,加强对现有绿色空间的保护,通过增加植被,优化土地利用结构的方式,完善莆田市生态系统服务水平。

Solving the Olbers’s Paradox, Explaining the “Red-Shift”, and Challenging the Relativities by “Sun Matters Theory” and “Sun Model of Universe”, an Evolution of the Einstein’s Static Universe Model

Olbers’s paradox, known as the dark night paradox, is an argument in astrophysics that the darkness of the night sky conflicts with the assumption of an infinite and eternal static universe. Big-Bang theory was used to partially explain this paradox, while introducing new problems. Hereby, we propose a better theory, named Sun Matters Theory, to explain this paradox. Moreover, this unique theory supports and extended the Einstein’s static universe model proposed by Albert Einstein in 1917. Further, we proposed our new universe model, “Sun Model of Universe”. Based on the new model and novel theory, we generated innovative field equation by upgrading Einstein’s Field Equation through adding back the cosmological constant, introducing a new variable and modifying the gravitationally-related concepts. According to the Sun Model of Universe, the dark matter and dark energy comprise the so-called “Sun Matters”. The observed phenomenon like the red shift is explained as due to the interaction of ordinary light with Sun Matters leading to its energy and frequency decrease. In Sun Model, our big universe consists of many universes with ordinary matter at the core mixed and surrounded with the Sun Matters. In those universes, the laws of physics may be completely or partially different from that of our ordinary universe with parallel civilizations. The darkness of night can be easily explained as resulting from the interaction of light with the Sun Matters leading to the sharp decrease in the light intensity. Sun Matters also scatter the light from a star, which makes it shining as observed by Hubble. Further, there is a kind of Sun Matters named “Sun Waters”, surrounding every starts. When lights pass by the sun, the Sun Waters deflect the lights to bend the light path. According to the Sun Model, it is the light bent not the space bent that was proposed in the theory of relativities.

Hubble Tension Explanation from This Cosmological Model AΛΩ (Slow Bang Model, SB)

In this article we present a model of Hubble-Lemaître law using the notions of a transmitter (galaxy) and a receiver (MW) coupled to a model of the universe (Slow Bang Model, SB), based on a quantum approach of the evolution of space-time as well as an equation of state that retains all the infinitesimal terms. We find an explanation of the Hubble tension H0. Indeed, we have seen that this constant depends on the transceiver pair which can vary from the lowest observable value, from photons of the CMB (theoretical [km/s/Mpc]) to increasingly higher values depending on the earlier origin of the formation of the observed galaxy or cluster (ETG ~0.3 [Gy], ~74 [km/s/Mpc]). We have produced a theoretical table of the values of the constant according to the possible pairs of transmitter/receiver in the case where these galaxies follow the Hubble flow without large disturbance. The calculated theoretical values of the constant are in the order of magnitude of all values mentioned in past studies. Subsequently, we applied the models to 9 galaxies and COMA cluster and found that the models predict acceptable values of their distances and Hubble constant since these galaxies mainly follow the Hubble flow rather than the effects of a galaxy cluster or a group of clusters. In conclusion, we affirm that this Hubble tension does not really exist and it is rather the understanding of the meaning of this constant that is questioned.

Development of diabetic complications and influencing factors among 32653 type 2 diabetes patients:retrospective cohort study using a multi-state Markov

Background:Patients with type 2 diabetes are at high risk for developing multiple chronic complications.However,there is a lack of studies of the cumulative number of diabetic complications in China.Methods:A retrospective cohort study was performed from 2009 to 2021.Type 2 diabetes patients who were first diagnosed after the age of 35 years between January 1,2009,and December 31,2017,were included.Five states were defined according to the number of chronic complications:no(S0),one(S1),two(S2),three(S3),and four or more complications(S4).A multi-state Markov model was constructed to estimate transition probability,transition intensity,mean sojourn time,and the possible factors for each state.Results:The study included 32653 type 2 diabetes patients(mean age,59.59 years;15929(48.8%)male),and mean follow-up time of 7.75 years.In all,4375 transitions were observed.The 12-year transition probability of from state S0 to S1 was the lowest at 16.4%,while that from S2 to S3 was the highest,at 45.6%.Higher fasting blood glucose,lower high-density lipoprotein cholesterol,higher total cholesterol,and an unhealthy diet were associated with higher risk of progression from S0 to S1.Being female,less than 60 years old,weekly physical activity,and vegetarian diet decreased this risk.Being female and less than 60 years old reduced the likelihood of transition from S1 to S2,whereas lower high-density lipoprotein cholesterol increased this likelihood.Conclusions:Following the occurrence of two complications in type 2 diabetes patients,the risk for accumulating a third complication within a short time is significantly increased.It is important to take advantage of the stable window period when patients have fewer than two complications,strengthen the monitoring of blood glucose and blood lipids,and encourage patients to maintain good living habits to prevent further deterioration.

Analysis of Porter’s Five Forces Competitive Model in China’s Property Rights Trading Market

In recent years,China’s property rights trading market has been extremely competitive,but there are also new contradictions and challenges.This paper aims to analyze the external and internal competitive market of the property rights market through Porter’s five forces competition model,then find out the problems and defects in the development,thereby promoting the better development and progress of China’s property rights trading market.

Customer Segment Prediction on Retail Transactional Data Using K-Means and Markov Model

Retailing is a dynamic business domain where commodities and goods are sold in small quantities directly to the customers.It deals with the end user customers of a supply-chain network and therefore has to accommodate the needs and desires of a large group of customers over varied utilities.The volume and volatility of the business makes it one of the prospectivefields for analytical study and data modeling.This is also why customer segmentation drives a key role in multiple retail business decisions such as marketing budgeting,customer targeting,customized offers,value proposition etc.The segmentation could be on various aspects such as demographics,historic behavior or preferences based on the use cases.In this paper,historic retail transactional data is used to segment the custo-mers using K-Means clustering and the results are utilized to arrive at a transition matrix which is used to predict the cluster movements over the time period using Markov Model algorithm.This helps in calculating the futuristic value a segment or a customer brings to the business.Strategic marketing designs and budgeting can be implemented using these results.The study is specifically useful for large scale marketing in domains such as e-commerce,insurance or retailers to segment,profile and measure the customer lifecycle value over a short period of time.

Modeling urban land use dynamics using Markov-chain and cellular automata in Gondar City,Northwest Ethiopia

Modeling urban land-use dynamics is critical for urban experts’and infrastructure managers’planning.This study attempts to explore the land-use/land-cover(LULC)dynamics of Gondar using satellite images from 1984 to 2020.Markov-Chain and Cellular Automata(MC-CA)models have been recognized as performing well in predicting urban land-use change.However,only a few models work in Ethiopia in general,and no study in Gondar has applied this approach to study urban land-use patterns.Therefore,Gondar land-use/land cover changes of Gondar were predicted using the MC-CA model in IDRISI.The built-up area in Gondar city covered 1413 ha(3%of the total area)in 1984 and increased to 2380 ha(5%)in 1994;21153 ha(45.5%)in 2004;22622 ha(48.7%)in 2014;and 23427 ha(50.5%)in 2020.The area has been predicted to reach 57.5%in the 2050s,showing a faster increase that will cause a very vast loss of farmland.This will increase urban sprawl challenges as well as overall environmental disequilibrium in the preceding decade.Thus,innovative and careful structures and systems in urban planning are required to secure a sustainable urban future and to make our cities livable and competitive in the paradigm of sustainable cities.

基于Markov-PLUS和InVEST模型的锡林郭勒草原碳储量变化预测

【目的】研究锡林郭勒草原土地利用对碳储量的影响,了解草原生态系统固碳能力的变化趋势。【方法】基于1995-2015年土地利用变化规律,结合场景分析法和Markov⁃PLUS复合模型,模拟锡林郭勒草原历史趋势、经济发展和生态保护3个场景下2035年的土地利用空间分布,并利用InVEST模型预测相应的碳储量,分析土地利用变化对碳储量的影响。【结果】(1)1995-2015年,锡林郭勒草原林地和城乡工矿居民用地面积持续增加,草地面积减少,但草地仍是占比最大的土地利用类型,20年间区域碳储量增加了18228.93×10^(3) t;(2)预测到2035年,历史趋势和经济发展场景下,用地面积增加的主要为草地和城乡工矿居民用地,生态保护场景下为林地和草地,3种场景下碳储量增量分别为4419.74×10^(3)、11207.75×10^(3)和18498.45×10^(3) t。【结论】Markov⁃PLUS和InVEST模型预测锡林郭勒草原未来土地利用和碳储量变化获得的结果可靠;预测结果表明,1995-2035年锡林郭勒碳储量呈增加趋势,生态保护场景下碳储量增幅显著高于其他场景;林地、草地与其他地类之间的转变是导致碳储量变化的主要原因。本研究可以为该区域未来的土地利用结构的调整和管理提供参考。