Parkland trees on smallholder farms ameliorate soil physical-chemical properties in the semi-arid area of Tigray,Ethiopia

Proposed agroforestry options should begin with the species that farmers are most familiar with,which would be the native multipurpose trees that have evolved under smallholder farms and socioeconomic conditions.The African birch(Anogeissus leiocarpa(DC.)Guill.&Perr.)and pink jacaranda(Stereospermum kunthianum Cham.)trees are the dominant species in the agroforestry parkland system in the drylands of Tigray,Ethiopia.Smallholder farmers highly value these trees for their multifunctional uses including timber,firewood,charcoal,medicine,etc.These trees also could improve soil fertility.However,the amount of soil physical and chemical properties enhanced by the two species must be determined to maintain the sustainable conservation of the species in the parklands and to scale up to similar agroecological systems.Hence,we selected twelve isolated trees,six from each species that had similar dendrometric characteristics and were growing in similar environmental conditions.We divided the canopy cover of each tree into three radial distances:mid-canopy,canopy edge,and canopy gap(control).At each distance,we took soil samples from three different depths.We collected 216 soil samples(half disturbed and the other half undisturbed)from each canopy position and soil depth.Bulk density(BD),soil moisture content(SMC),soil organic carbon(SOC),total nitrogen(TN),available phosphorus(AP),available potassium(AK),p H,electrical conductivity(EC),and cation exchange capacity(CEC)were analysed.Results revealed that soil physical and chemical properties significantly improved except for soil texture and EC under both species,CEC under A.leiocarpus,and soil p H under S.kunthianum,all the studied soils were improved under both species canopy as compared with canopy gap.SMC,TN,AP,and AK under canopy of these trees were respectively 24.1%,11.1%,55.0%,and 9.3% higher than those soils under control.The two parkland agroforestry species significantly enhanced soil fertility near the canopy of topsoil through improving soil physical and chemical properties.These two species were recommended in the drylands with similar agro-ecological systems.

Exploring Trees Diversity and Ecological Value of Mountain Forests in the Blue Nile Region of Sudan

We carried out this research at Abu-Gaddaf Natural Forest Reserve (ANFR) which is located east of Blue Nile River, in Blue Nile State, Sudan. It aims at exploring tree composition assessing their diversity indices, and ecological importance values. For survey of types and estimation of density of tree species in the forest, we randomly distributed 97 circular sample plots (0.1 hectare (ha)). In each sample plot we identified all trees to the species level, recorded their frequencies and computed species diversity and importance value indices (IVI). A total of 13 tree species, which belong to 12 genera and nine families, were identified in the tree layer of the forest. Mean tree density in ANFR was 116 trees/ha, composed mainly of Boswellia papyrifera (Del.) Hochst. (48), followed by Combretum hartmannianu (19) and Lannea fruticosa (18). Fabaceae was the most common family followed by Combretaceae and Malvaceae. B. papyrifera Delile Hochst was the most abundant while Acacia seyal was the least abundant species. Species richness (R = 1.71), evenness (E = 0.69), dominance (0.24) indices and Simpson’s Index of Diversity (D' = 0.76) suggest a moderate diversity, moderate numbers of individuals in each species and a moderate community stability. The research provides empirical results on diversity and ecological importance value of species, signifies the urging need to safeguard threatened species and to prioritize them for conservation, as well as the need to promote management of abundant species to provide multiple forest ecosystem services.

Enhancing PDF Malware Detection through Logistic Model Trees

Malware is an ever-present and dynamic threat to networks and computer systems in cybersecurity,and because of its complexity and evasiveness,it is challenging to identify using traditional signature-based detection approaches.The study article discusses the growing danger to cybersecurity that malware hidden in PDF files poses,highlighting the shortcomings of conventional detection techniques and the difficulties presented by adversarial methodologies.The article presents a new method that improves PDF virus detection by using document analysis and a Logistic Model Tree.Using a dataset from the Canadian Institute for Cybersecurity,a comparative analysis is carried out with well-known machine learning models,such as Credal Decision Tree,Naïve Bayes,Average One Dependency Estimator,Locally Weighted Learning,and Stochastic Gradient Descent.Beyond traditional structural and JavaScript-centric PDF analysis,the research makes a substantial contribution to the area by boosting precision and resilience in malware detection.The use of Logistic Model Tree,a thorough feature selection approach,and increased focus on PDF file attributes all contribute to the efficiency of PDF virus detection.The paper emphasizes Logistic Model Tree’s critical role in tackling increasing cybersecurity threats and proposes a viable answer to practical issues in the sector.The results reveal that the Logistic Model Tree is superior,with improved accuracy of 97.46%when compared to benchmark models,demonstrating its usefulness in addressing the ever-changing threat landscape.

Seedling potential of trees species along the elevational gradient in temperate hill forest of central Nepal

Regeneration status of tree species along elevation gradient in temperate hill forest was not understood greatly.Present research examined the tree diversity and its regeneration patterns along an elevation gradient in temperate hill forest,central Nepal.Data were collected from 300 sample plots within vertical elevation bands of 10,ranging from 1365 to 2450 m asl.A random sampling method was used for data collection in three seasons,winter,pre-monsoon and post monsoon seasons.Diameter at breast height(DBH)was used to broadly categorize the plant individual into trees,saplings and seedlings.The tree species richness ranged from 12 to 25 with density of 350 to 1200 individuals per hectare.Species richness of tree and sapling showed statistically significant unimodal pattern,which peaked at mid-elevation.Elevation showed a strong and positive linear correlation with the seedling density(Deviance=0.99,p<0.001)and a significant hump-shaped relationship with sapling density(Deviance=0.95,p<0.001).Similarly,elevations showed a statistically significant negative hump-shaped relationship with all trees,saplings and seedling stages(Deviances=0.89,0.87 and 0.57).The highest values of the Shannon-Wiener index and the lowest value of the Simpson index were found at mid-elevation for all growth forms.Nearly 92%of tree species were found at regenerating stage;49%in a good renewal regeneration status,32%in fair renewal regeneration,and 11%at a poor regenerating condition.Nevertheless,4%of tree species were reported as non-regenerating stages and 4%were newly introduced species.Hence,the regeneration status of the study area was considered fairly well since sapling(78.5%)>seedling(10.6%)≤mature(10.9%).Among tested environmental variables,elevation and annual mean rainfall were the most influential factors in the regeneration of tree species.

Efficiency of Bio-Fertilizing as One of the Natural Alternatives to Improve the Growth of Khaya senegalensis and Swietenia mahagoni Trees and for Sustainability

A field experiment was carried out at Ismailia Research Station, Ismailia Governorate from 2020-2022 to improve the growth of Khaya senegalensis and Swietenia mahagoni by using a combination of mineral fertilizer (NPK) and biological fertilizer (Azotobacter chroococcum, Bacillus megatherium, and Bacillus circulant) as recommended dose under new sandy soils conditions. Split plot designed with four treatments (Control, (50% Mineral fertilizer (M.) + 50% Biological fertilizer (Bio.)), 100% M. and 100% Bio.) of each species. Vegetative growth, leaf area, tree biomass, stored carbon, basal area, tree volume, and in the soil both of microbial account and mineral content were determined. The experimental results showed no significant differences between studied species among the most studied parameters except for Khaya senegalensis which gave the highest significant difference in root biomass and below-stored carbon than Swietenia mahagoni. Evidently, the highest significant growth parameters were 100% mineral fertilizer followed by (50% M. + 50% Bio.) as compared with control. No significant difference between 100% M. and (50% M. + 50% Bio.) of shoot dry biomass (15.19 and 12.02 kg, respectively) and above-stored carbon (0.28 and 0.22 Mt, respectively). Microbial account and mineral content in soil were improved after cultivation of tree species compared to before planting and control, especially with 50% mineral fertilizer and 50% bio-fertilizer treatment. In conclusion, a treatment containing 50% mineral fertilizer and 50% bio-fertilizer has led to the ideal Khaya senegalensis and Swietenia mahagoni growth in sandy soil for cheaper and sustainable.

A Light and Simplified Branch Bending Method for Young Pear Trees

Aiming at high cost and low efficiency of conventional branch bending method in the modern intensive planting and labor-saving cultivation mode of young pear trees,this paper provides a new branch bending method with wide source of raw materials,cheap price and simple operation,which is also suitable for the management of low-age branches in the process of high grafting and upgrading of traditional big trees.

Enhanced asphalt dynamic modulus prediction: A detailed analysis of artificial hummingbird algorithm-optimised boosted trees

This study introduces and evaluates a novel artificial hummingbird algorithm-optimised boosted tree(AHAboosted)model for predicting the dynamic modulus(E*)of hot mix asphalt concrete.Using a substantial dataset from NCHRP Report-547,the model was trained and rigorously tested.Performance metrics,specifically RMSE,MAE,and R2,were employed to assess the model's predictive accuracy,robustness,and generalisability.When benchmarked against well-established models like support vector machines(SVM)and gaussian process regression(GPR),the AHA-boosted model demonstrated enhanced performance.It achieved R2 values of 0.997 in training and 0.974 in testing,using the traditional Witczak NCHRP 1-40D model inputs.Incorporating features such as test temperature,frequency,and asphalt content led to a 1.23%increase in the test R2,signifying an improvement in the model's accuracy.The study also explored feature importance and sensitivity through SHAP and permutation importance plots,highlighting binder complex modulus|G*|as a key predictor.Although the AHA-boosted model shows promise,a slight decrease in R2 from training to testing indicates a need for further validation.Overall,this study confirms the AHA-boosted model as a highly accurate and robust tool for predicting the dynamic modulus of hot mix asphalt concrete,making it a valuable asset for pavement engineering.

基于Decision Trees的配电网中性点不接地系统选线

针对配电网中性点不接地系统,使用录波数据解决单相接地选线不准的难题,提出了基于Decision Trees算法进行单相接地选线的方法.使用PSCAD仿真10kV配电网单相接地故障得到录波数据,转换成通用格式,提取稳态数据并进行预处理,通过对比多个机器学习分类算法,选择基于Decision Trees算法进行单相接地选线.选择的Decision Trees算法训练准确度高达99.99%,且模型小,训练速度快.将训练后的模型导出,使用实际的故障录波数据进行验证,选线准确度高达95%以上.结果表明该方法易于实现,准确度高,适合在实际中应用.

Novel Soft ComputingModel for Predicting Blast-Induced Ground Vibration in Open-Pit Mines Based on the Bagging and Sibling of Extra Trees Models

This study considered and predicted blast-induced ground vibration(PPV)in open-pit mines using bagging and sibling techniques under the rigorous combination of machine learning algorithms.Accordingly,four machine learning algorithms,including support vector regression(SVR),extra trees(ExTree),K-nearest neighbors(KNN),and decision tree regression(DTR),were used as the base models for the purposes of combination and PPV initial prediction.The bagging regressor(BA)was then applied to combine these base models with the efforts of variance reduction,overfitting elimination,and generating more robust predictive models,abbreviated as BA-ExTree,BAKNN,BA-SVR,and BA-DTR.It is emphasized that the ExTree model has not been considered for predicting blastinduced ground vibration before,and the bagging of ExTree is an innovation aiming to improve the accuracy of the inherently ExTree model,as well.In addition,two empirical models(i.e.,USBM and Ambraseys)were also treated and compared with the bagging models to gain a comprehensive assessment.With this aim,we collected 300 blasting events with different parameters at the Sin Quyen copper mine(Vietnam),and the produced PPV values were also measured.They were then compiled as the dataset to develop the PPV predictive models.The results revealed that the bagging models provided better performance than the empirical models,except for the BA-DTR model.Of those,the BA-ExTree is the best model with the highest accuracy(i.e.,88.8%).Whereas,the empirical models only provided the accuracy from 73.6%–76%.The details of comparisons and assessments were also presented in this study.

基于FP-tree的新能源汽车产业国际竞争力影响因素关联挖掘算法

为充分挖掘新能源汽车产业国际竞争力影响因素、探究价值增长点,提出了基于FP-tree的影响因素关联挖掘算法。通过构建国际竞争力各指标影响因素的关联规则,分析任意事务数据集中的关联数据,利用最小支持度参数minsup按照从上到下的方式搜索,确定最长的频繁项目集,采用FP-tree关联频繁项目集,设定分支关联性挖掘标准,实现了新能源汽车产业国际竞争力影响因素的挖掘。测试结果表明,设计算法的最小支持度和数据关联挖掘时间较短,置信度分析具有较高的稳定性。

Interannual dynamics of stemwood nonstructural carbohydrates in temperate forest trees surrounding drought

Interactions between water and carbon dynamics underlie drought-related tree mortality.While whole-tree water relations have been shown to play a key role in the response to and recovery from drought,the role of nonstructural carbohydrates(NSC) and how their storage and allocation changes surrounding drought events deserves further attention and is critical for understanding tree survival.Here,we quantified in situ NSC responses of temperate forest trees to the 2016 drought in the northeastern United States.Sugar and starch concentrations were measured in the stemwood of five tree species from 2014 to 2019,which allowed us to monitor NSCs in relation to climatic conditions before,during,and after the natural drought.We found that immediately following the drought,measured stemwood NSC concentrations decreased.However,NSC concentrations rebounded quickly within three years.Notably,trees allocated proportionally more to starch than to sugars following the 2016 drought.In winter 2017,starch comprised 45% of total stemwood stores,whereas starch made up only 1-2% in other years.Further,we modeled and assessed the climatic drivers of total NSC concentrations in the stem.Variation in total NSC concentrations was significantly predicted by the previous year’s temperature,precipitation,and standardized precipitation-evapotranspiration index(SPEI),with stemwood concentrations decreasing following hotter,drier periods and increasing following cooler,wetter periods.Overall,our work provides insight into the climatic drivers of NSC storage and highlights the important role that a tree’s carbon economy may play in its response and recovery to environmental stress.

基于CatBoost用信预测模型的TreeSHAP解释性研究

银行客户申请信用贷款在授信通过后,精准预测客户是否用信及分析影响客户用信的关键因素,对提高银行客户服务能力及盈利能力具有重要意义.目前,机器学习算法鲜有在用信预测方面的应用,且金融用信领域缺乏模型可解释性的研究,为此提出一种基于CatBoost的TreeSHAP解释性用信预测模型.通过CatBoost构建用信预测模型,利用3种超参数优化算法对该模型进行对比优化,与基线模型在4项主要性能指标上进行实验对比,结果表明经TPE算法优化后的模型性能均优于其他模型,然后结合TreeSHAP方法从全局和局部的层面增强模型的可解释性,解释性分析客户用信的影响因素,为银行对客户进行精准化营销提供决策依据.

Risk Assessment of Deep-Water Horizontal X-Tree Installation

Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.

Remaining Useful Life Prediction Method for Multi-Component System Considering Maintenance:Subsea Christmas Tree System as A Case Study

Maintenance is an important technical measure to maintain and restore the performance status of equipment and ensure the safety of the production process in industrial production,and is an indispensable part of prediction and health management.However,most of the existing remaining useful life(RUL)prediction methods assume that there is no maintenance or only perfect maintenance during the whole life cycle;thus,the predicted RUL value of the system is obviously lower than its actual operating value.The complex environment of the system further increases the difficulty of maintenance,and its maintenance nodes and maintenance degree are limited by the construction period and working conditions,which increases the difficulty of RUL prediction.An RUL prediction method for a multi-omponent system based on the Wiener process considering maintenance is proposed.The performance degradation model of components is established by a dynamic Bayesian network as the initial model,which solves the uncertainty of insufficient data problems.Based on the experience of experts,the degree of degradation is divided according to Poisson process simulation random failure,and different maintenance strategies are used to estimate a variety of condition maintenance factors.An example of a subsea tree system is given to verify the effectiveness of the proposed method.

Patterns of Ips cembrae(Herr)infestation on trap and standing trees of European larch(Larix decidua Mill.)

The large larch beetle,Ips cembrae,is a significant pest causing the death of larch.In 2020,the attack density of I.cembrae on larch trap trees and standing trees was evaluated using sample sections placed along the trunk.As a defensive measure against I.cembrae,trap trees were highly effective in both spring and summer.The attack density increased with increasing trap tree surface area/volume.Galleries were established evenly throughout the entire trunk including the thin upper portion.When the number of trap trees was low and their capacity full,a continual aggregation of adults occurred due to pheromone communication,leading to attacks on healthy standing trees in the immediate vicinity.It was found that I.cembrae attacked standing trees from the trunk base,with a continual colonization of the stem up to 70%of the tree height in a time-differentiated progression of development stages.The attack density of I.cembrae on standing trees was up to 40%lower than on the trap trees.

The ecological scale mediates whether trees experience drought legacies in radial growth

The impact of lag effects produced by disturbances on primary production has been a major concern among ecologists during the last decade.Sudden and extreme climatic events are imposing drastic reductions in radial growth of trees as evidenced in tree-rings series Dendrochronological samples are obtained at tree level but analyzed at an aggregated scale(i.e.,mean chronologies),although aggregating tree-ring chronology on a regional scale may reduce the possibility of studying the variability of individual tree response to drought,by amplifying the average population response.Here,we conducted experimental research in which 370 trees of 5 species were analyzed to assess the potential statistical and scaling issues that may occur when using regressionbased methods to analyze ecosystem responses to disturbances.Drought legacy effects were quantified using individual and aggregated scales.Then,lag effects were validated using confidence and prediction intervals to identify values falling outside the certainty of the climate-growth model Individual scale legacy effects contrasted with confidence intervals were commonly distributed across species but were scarce when compared with prediction intervals.The analysis of aggregated scale legacies detected significant growth reductions when validated using prediction intervals;however,individual scale legacy lag effects were not detected.This finding directly contrasts the results obtained when using an aggregated scale.Our results provide empirical evidence on how aggregating ecological data to infer processes that emerge from an individual scale can lead to distorted conclusions.We therefore encourage the use of individual based statistical and ecological procedures to analyze tree rings as a means of further understanding the ecosystem responses to disturbances.

Mapping species assemblages of tropical forests at different hierarchical levels based on multivariate regression trees

Background: Vegetation distribution maps are of great significance for nature protection and management. In diverse tropical forests, accurate spatial mapping of vegetation types is challenging;the high species diversity and abundance of rare species challenge classification concepts, while remote sensing signals may not vary systematically with species composition, complicating the technical capability for delineating vegetation types in the landscape.Methods: We used a combination of field-based compositional data and their relations to environmental variables to predict the distribution of forest types in the Wuzhishan National Natural Reserve(WNNR), Hainan Island,China, using multivariate regression trees(MRT). The MRT was based on arboreal vegetation composition in 132plots of 20 m×20 m with a regular spacing of 1 km. Apart from the MRT, non-metric multidimensional scaling(NMDS) was used to evaluate vegetation-environment relationships.Results: The MRT model worked best when using 14 key environmental variables including topography, climate,latitude and soil, although the difference with the simpler model including only topographical variables was small. The full model classified the 132 plots into 3 vegetation types, 6 formation groups, 20 formations and 65associations at different hierarchical syntaxonomic levels. This model was the basis for forest vegetation maps for the WNNR. MRT and NMDS showed that elevation was the main driving force for the distribution of vegetation types and formation groups. Climate, latitude, and soil(especially available P), together with topographic variables, all influenced the distribution of formations and associations.Conclusions: While elevation determines forest-type distributions, lower-level syntaxonomic forest classes respond to the topographic diversity typical for mountains. Apart from providing the first detailed forest vegetation map for any part of WNNR, we show how, in spite of limitations, MRT with existing environmental data can be a useful method for mapping diverse and remote tropical forests.

Post Debarking Response of Prunus africana (Hook. F) Kalkman (Rosaceae) Trees at Two Exploitation Sites in North Kivu (Eastern Democratic Republic of Congo)

Prunus africana is a species of great economic, medicinal and ecological importance. Due to its multiple uses, unsustainable exploitation methods and low regeneration capacity in tropical rainforests, this species is threatened with extinction. Present and exploited in the eastern part of DR Congo, knowledge of the dynamics of post-bark regeneration of Prunus africana remains fragmentary and poorly known. In North Kivu province, this species thrives in both afromontane forest and lowland tropical rainforest habitats. In order to contribute to the rational and sustainable exploitation of Prunus africana in this province, this paper was carried out with the objective of contributing to the knowledge of the dynamics of the regeneration of post-harvest bark of Prunus africana in two exploitation sites (low and high altitude). To achieve this objective, the inventory was conducted on 16 plots of 25 hectares each, with 8 plots per site. Dendrometric parameters (diameter at breast height (DBH), total tree height) and tree growth and regeneration parameters, i.e., stem bark thickness of the unharvested and harvested portions of the trees (bark reconstitution) were measured. A total of 716 barked stems of Prunus africana in 2016 in 25 hectares constituted the study sample. Results show that sites do not influence diameter at breast height of P. africana trees (p > 0.05) or total tree height. The bark diameter of harvested trees and the bark diameter of unharvested trees varied significantly by site (p 0.05). In contrast, the annual growth rate of bark differed with altitude;the highest rate was observed in trees growing at high altitude (2.97 ± 0.9 mm/yr) compared to 2.23 ± 0.74 mm/yr at low altitude. In view of these results, this study indicates that a half-rotation of 7 years could allow an effective reconstitution of the bark of Prunus africana at the second passage on the remaining side of the same stem.

Quantification of Above-Ground Biomass and Carbon Sequestration Potential of Roadside Trees in the Plateau Department of Benin Republic

Roadside trees are effective natural solutions for mitigating climate change. Despite the usefulness of trees to carbon sequestration, there is a dearth of information on the estimation of biomass and carbon stock for roadside trees in the study area. This study aimed to estimate the carbon stock and carbon dioxide equivalent of roadside trees. A complete enumeration of trees was carried out in Kétou, Pobè and Sakété within the communes of the Plateau Department, Bénin Republic. Total height and diameter at breast height were measured from trees along the roads while individual wood density value was obtained from wood density database. The allometric method of biomass estimation was adopted for the research. The results showed that the total estimations for above-ground biomass, carbon stock and carbon equivalent from all the enumerated roadside trees were 154.53 mt, 72.63 mt and 266.55 mt, respectively. The results imply that the roadside trees contain a substantial amount of carbon stock that can contribute to climate change mitigation through carbon sequestration.

Transplantation and Post-planting Tending and Management Techniques of Olive Trees(Olea europaea L.)

This paper introduced the preparation work before transplanting big olive trees(Olea europaea L.),including key technical measures such as plant excavation,transportation,planting,and post-planting tending.The aim was to provide scientific basis and feasible solutions for adjusting the density of olive trees in Shiyan City,and to assist in the high-quality development of the olive industry.