Feature extraction for machine learning-based intrusion detection in IoT networks

A large number of network security breaches in IoT networks have demonstrated the unreliability of current Network Intrusion Detection Systems(NIDSs).Consequently,network interruptions and loss of sensitive data have occurred,which led to an active research area for improving NIDS technologies.In an analysis of related works,it was observed that most researchers aim to obtain better classification results by using a set of untried combinations of Feature Reduction(FR)and Machine Learning(ML)techniques on NIDS datasets.However,these datasets are different in feature sets,attack types,and network design.Therefore,this paper aims to discover whether these techniques can be generalised across various datasets.Six ML models are utilised:a Deep Feed Forward(DFF),Convolutional Neural Network(CNN),Recurrent Neural Network(RNN),Decision Tree(DT),Logistic Regression(LR),and Naive Bayes(NB).The accuracy of three Feature Extraction(FE)algorithms is detected;Principal Component Analysis(PCA),Auto-encoder(AE),and Linear Discriminant Analysis(LDA),are evaluated using three benchmark datasets:UNSW-NB15,ToN-IoT and CSE-CIC-IDS2018.Although PCA and AE algorithms have been widely used,the determination of their optimal number of extracted dimensions has been overlooked.The results indicate that no clear FE method or ML model can achieve the best scores for all datasets.The optimal number of extracted dimensions has been identified for each dataset,and LDA degrades the performance of the ML models on two datasets.The variance is used to analyse the extracted dimensions of LDA and PCA.Finally,this paper concludes that the choice of datasets significantly alters the performance of the applied techniques.We believe that a universal(benchmark)feature set is needed to facilitate further advancement and progress of research in this field.

A three-dimensional feature extraction-based method for coal cleat characterization using X-ray μCT and its application to a Bowen Basin coal specimen

Cleats are the dominant micro-fracture network controlling the macro-mechanical behavior of coal.Improved understanding of the spatial characteristics of cleat networks is therefore important to the coal mining industry.Discrete fracture networks(DFNs)are increasingly used in engineering analyses to spatially model fractures at various scales.The reliability of coal DFNs largely depends on the confidence in the input cleat statistics.Estimates of these parameters can be made from image-based three-dimensional(3D)characterization of coal cleats using X-ray micro-computed tomography(m CT).One key step in this process,after cleat extraction,is the separation of individual cleats,without which the cleats are a connected network and statistics for different cleat sets cannot be measured.In this paper,a feature extraction-based image processing method is introduced to identify and separate distinct cleat groups from 3D X-ray m CT images.Kernels(filters)representing explicit cleat features of coal are built and cleat separation is successfully achieved by convolutional operations on 3D coal images.The new method is applied to a coal specimen with 80 mm in diameter and 100 mm in length acquired from an Anglo American Steelmaking Coal mine in the Bowen Basin,Queensland,Australia.It is demonstrated that the new method produces reliable cleat separation capable of defining individual cleats and preserving 3D topology after separation.Bedding-parallel fractures are also identified and separated,which has his-torically been challenging to delineate and rarely reported.A variety of cleat/fracture statistics is measured which not only can quantitatively characterize the cleat/fracture system but also can be used for DFN modeling.Finally,variability and heterogeneity with respect to the core axis are investigated.Significant heterogeneity is observed and suggests that the representative elementary volume(REV)of the cleat groups for engineering purposes may be a complex problem requiring careful consideration.

Quasi-static and dynamic compressive behaviour of additively manufactured Menger fractal cube structures

This paper presents the first-ever investigation of Menger fractal cubes'quasi-static compression and impact behaviour.Menger cubes with different void ratios were 3D printed using polylactic acid(PLA)with dimensions of 40 mm×40 mm×40 mm.Three different orders of Menger cubes with different void ratios were considered,namely M1 with a void ratio of 0.26,M2 with a void ratio of 0.45,and M3with a void ratio of 0.60.Quasi-static Compression tests were conducted using a universal testing machine,while the drop hammer was used to observe the behaviour under impact loading.The fracture mechanism,energy efficiency and force-time histories were studied.With the structured nature of the void formation and predictability of the failure modes,the Menger geometry showed some promise compared to other alternatives,such as foams and honeycombs.With the increasing void ratio,the Menger geometries show force-displacement behaviour similar to hyper-elastic materials such as rubber and polymers.The third-order Menger cubes showed the highest energy absorption efficiency compared to the other two geometries in this study.The findings of the present work reveal the possibility of using additively manufactured Menger geometries as an energy-efficient system capable of reducing the transmitting force in applications such as crash barriers.

The association of diet quality and physical activity with cardiovascular disease and mortality in 85,545 older Australians:A longitudinal study

Background:A quality diet and an active lifestyle are both important cornerstones of cardiovascular disease(CVD)prevention.However,despite their interlinked effects on metabolic health,the 2 behaviors are rarely considered jointly,particularly within the context of CVD prevention.We examined the independent,interactive,and joint associations of diet and physical activity with CVD hospitalization,CVD mortality,and all-cause mortality.Methods:CVD-free Australian participants aged 4574 years(n=85,545)reported physical activity,diet,sociodemographic,and lifestyle characteristics at baseline(20062009)and follow-up(20122015),and data were linked to hospitalization and death registries(03/31/2019 for CVD hospitalization and all-cause mortality and 12/08/2017 for CVD mortality).Diet quality was categorized as low,medium,and high based on meeting dietary recommendations.Physical activity was operationalized as(a)total moderate-to-vigorous physical activity(MVPA)as per guidelines,and(b)the composition of MVPA as the ratio of vigorous-intensity physical activity(VPA)to total MVPA.We used a left-truncated cause-specific Cox proportional hazards model using time-varying covariates.Results:During a median of 10.7 years of follow-up,6576 participants were admitted to the hospital for CVD and 6581 died from all causes(876 from CVD during 9.3 years).A high-quality diet was associated with a 17%lower risk of all-cause mortality than a low-quality diet,and the highest MVPA category(compared with the lowest)was associated with a 44%and 48%lower risk of CVD and all-cause mortality,respectively.Multiplicative interactions between diet and physical activity were non-significant.For all outcomes,the lowest risk combinations involved a high-quality diet and the highest MVPA categories.Accounting for total MVPA,some VPA was associated with further risk reduction of CVD hospitalization and all-cause mortality.Conclusion:For CVD prevention and longevity,one should adhere to both a healthy diet and an active lifestyle and incorporate some VPA when possible.

A systematic scoping review of study methodology for randomized controlled trials investigating probiotics in athletic and physically active populations

Background:The purported ergogenic and health effects of probiotics have been a topic of great intrigue among researchers,practitioners,and the lay public alike.There has also been an increased research focus within the realm of sports science and exercise medicine on the athletic gut microbiota.However,compared to other ergogenic aids and dietary supplements,probiotics present unique study challenges.The objectives of this systematic scoping review were to identify and characterize study methodologies of randomized controlled trials investigating supplementation with probiotics in athletes and physically active individuals.Methods:Four databases(MEDLINE,CINAHL,Cochrane CENTRAL,and Cochrane Database of Systematic Reviews)were searched for randomized controlled studies involving healthy athletes or physically active individuals.An intervention with probiotics and inclusion of a control and/or placebo group were essential.Only peer-reviewed articles in English were considered,and there were no date restrictions.Results were extracted and presented in tabular form to detail study protocols,characteristics,and outcomes.Bias in randomized controlled trials was determined with the RoB 2.0 tool.Results:A total of 45 studies were included in the review,with 35 using a parallel group design and 10 using a cross-over design.Approximately half the studies used a single probiotic and the other half a multi-strain preparation.The probiotic dose ranged from 2×10^(8)to 1×10^(11)colony forming units daily,and the length of intervention was between 7 and 150 days.Fewer than half the studies directly assessed gastrointestinal symptoms,gut permeability,or the gut microbiota.The sex ratio of participants was heavily weighted toward males,and only 3 studies exclusively investigated females.Low-level adverse events were reported in only 2 studies,although the methodology of reporting varied widely.The risk of bias was generally low,although details on randomization were lacking in some studies.Conclusion:There is a substantial body of research on the effects of prob iotic supplementation in healthy athletes and physically active individuals.Considerable heterogeneity in probiotic selection and dosage as well as outcome measures has made clinical and mechanistic interpretation challenging for both health care practitioners and researchers.Attention to issues of randomization of participants,treatments and interventions,selection of outcomes,demographics,and reporting of adverse events will facilitate more trustworthy interpretation of probiotic study results and inform evidence-based guidelines.

A randomized controlled trial of Promoting Physical Activity in Regional and Remote Cancer Survivors(PPARCS)

Background:Physical activity(PA)is important for cancer survivors.Trials of remotely delivered interventions are needed to assist in reaching under-served non-metropolitan cancer survivors.The objective of this study was to ascertain whether wearable technology,coupled with health coaching was effective in increasing PA in breast and colorectal cancer survivors living in regional and remote areas in Australia.Methods:Cancer survivors from 5 states were randomized to intervention and control arms.Intervention participants were given a Fitbit Charge 2TMand received up to 6 telephone health coaching sessions.Control participants received PA print materials.Accelerometer assessments at baseline and 12 weeks measured moderate-to-vigorous PA(MVPA),light PA,and sedentary behavior.Results:Eighty-seven participants were recruited(age=63±11 years;74(85%)female).There was a significant net improvement in MVPA of 49.8 min/week,favoring the intervention group(95%confidence interval(95%CI):13.6-86.1,p=0.007).There was also a net increase in MVPA bouts of 39.5 min/week(95%CI:11.9-67.1,p=0.005),favoring the intervention group.Both groups improved light PA and sedentary behavior,but there were no between-group differences.Conclusion:This’s the first study to demonstrate that,when compared to standard practice(i.e.,PA education),a wearable technology intervention coupled with distance-based health coaching,improves MVPA in non-metropolitan cancer survivors.The results display promise for the use of scalable interventions using smart wearable technology in conjunction with phone-based health coaching to foster increased PA in geographically disadvantaged cancer survivors.

Ballistic impact response of flexible and rigid UHMWPE textile composites:Experiments and simulations

This study elaborates on the effects of matrix rigidity on the high-velocity impact behaviour of UHMWPE textile composites using experimental and numerical methods.Textile composite samples were manufactured of a plain-weave fabric(comprising Spectra?1000 fibres)and four different matrix materials.High-velocity impact tests were conducted by launching a spherical steel projectile to strike on the prepared samples via a gas gun.The experimental results showed that the textile composites gradually changed from a membrane stretching mode to a plate bending mode as the matrix rigidity and thickness increased.The composites deformed in the membrane stretching mode had higher impact resistance and energy absorption capacity,and it was found that the average energy absorption per ply was much higher in this mode,although the number of broken yarns was smaller in the perforated samples.Moreover,the flexible matrix composites always had higher perforation resistance but larger deformation than the rigid matrix counterparts in the tested thickness and velocity range.A novel numerical modelling approach with enhanced computational efficiency was proposed to simulate textile composites in mesoscale resolution.The simulation results revealed that stress and strain development in the more rigid matrix composite was localised in the vicinity of the impact location,leading to larger local deformation and inferior perforation resistance.

Super-exchange effect induced by early 3d metal doping on NiFe_(2)O_(4)(001)surface for oxygen evolution reaction

Understanding the intrinsic activity of oxygen evolution reaction(OER) is crucial for catalyst design.To date,different metal-doping strategies have been developed to achieve this,but the involving mechanisms remain unclear.Here,the electronic structure of the transition metal-doped NiFe_(2)O_(4)(001) surface is scrutinized for OER intrinsic activity using density functional theory calculations.Five 3d-orbital filling metals(Ti,V,Cr,Mn,and Co) are introduced as dopants onto A-and B-layers of the NiFe_(2)O_(4)(001) surface,and variation of oxidation states over Fe sites is observed on B-layer.Analyzing the magnetic moment and charge transfer of surface cation sites reveals that the variation of Fe oxidation states originates from the super-exchange effect and is influenced by the t2g-electron configuration of 3d metal dopants.This trend governs the generation of highly-active Fe3+sites on the B-layer,the adsorption strength of OER intermediates,i.e.,*O and*OH,and therefore the intrinsic activity.The finding of super-exchange mechanism induced by 3d early metal doping offers insights into electronic structure tailoring strategies for improving the intrinsic activity of OER electrocatalysts.

焦化污染区春季VOCs的污染特征及其控制策略

在对介休焦化区和方山对照区春季大气挥发性有机化合物(VOCs)污染特征进行分析的基础上,利用等效丙烯浓度(PEC)法和最大增量反应活性(MIR)法量化了VOCs的臭氧生成潜势(OFP),利用分数气溶胶生成系数(FAC)法和二次有机气溶胶(SOAP)法计算了VOCs的二次有机气溶胶生成潜势(SOAFP),采用健康风险评价法对可能会威胁人体健康的VOCs组分进行了风险评估.在此基础上,结合熵值法和正定矩阵因子(PMF)源解析模型对VOCs的优先控制物种和优先控制污染源进行了判别.结果表明,介休焦化区VOCs污染严重,总VOCs(TVOCs)浓度是方山的2.7倍.介休焦化区VOCs组成具有明显的烷烃占比低而芳香烃和烯烃占比高的特点.介休的OFP、SOAFP与健康风险都远高于方山,分别是方山的3.0、8.9和8.8倍,对介休OFP、SOAFP和健康风险影响最大的物种分别为乙烯、甲苯和苯,削减烯烃和芳香烃的排放是控制介休二次生成与健康风险的有效途径.焦化源(32.4%)是介休VOCs的主要来源,其次为汽油型尾气源(29.0%)和溶剂使用源(16.9%),其中焦化源是介休一级控制污染物苯和乙烯的主要来源,贡献高达74.1%和98.9%,汽油型尾气源(52.0%)和溶剂使用源(31.3%)是一级控制污染物甲苯的主要来源.

Strong coupling and catenary field enhancement in the hybrid plasmonic metamaterial cavity and TMDC monolayers

Strong coupling between resonantly matched surface plasmons of metals and excitons of quantum emitters results in the formation of new plasmon-exciton hybridized energy states.In plasmon-exciton strong coupling,plasmonic nanocavities play a significant role due to their ability to confine light in an ultrasmall volume.Additionally,two-dimensional transition metal dichalcogenides(TMDCs) have a significant exciton binding energy and remain stable at ambient conditions,making them an excellent alternative for investigating light-matter interactions.As a result,strong plasmon-exciton coupling has been reported by introducing a single metallic cavity.However,single nanoparticles have lower spatial confinement of electromagnetic fields and limited tunability to match the excitonic resonance.Here,we introduce the concept of catenary-shaped optical fields induced by plasmonic metamaterial cavities to scale the strength of plasmon-exciton coupling.The demonstrated plasmon modes of metallic metamaterial cavities offer high confinement and tunability and can match with the excitons of TMDCs to exhibit a strong coupling regime by tuning either the size of the cavity gap or thickness.The calculated Rabi splitting of Au-MoSe_2 and Au-WSe_2 heterostructures strongly depends on the catenary-like field enhancement induced by the Au cavity,resulting in room-temperature Rabi splitting ranging between 77.86 and 320 me V.These plasmonic metamaterial cavities can pave the way for manipulating excitons in TMDCs and operating active nanophotonic devices at ambient temperature.

太古宙花岗质岩石Si-O同位素对岩石成因和板块构造的约束

板块构造的起源是地球科学核心问题之一,而表壳物质循环是现代板块构造的重要表现之一,因此检验地球表壳物质循环起始时间是约束板块构造启动时间的重要切入点。近年来,岩浆岩的Si-O同位素联合示踪开始被用来约束太古宙构造环境,但由于大多太古宙样品经历了强烈的变质作用,Si同位素数据是否代表原岩信息需要进一步的评估;此外,Si同位素在高温岩浆分异过程中变化非常小,在分析精度不够高的情况下,其分析结果则很可能无法揭示其潜在的变化规律。本文结合当前地球早期构造环境研究进展以及Si-O同位素的应用情况:(1)重点总结介绍了太古宙花岗质岩石(主要包括英云闪长岩-奥长花岗岩-花岗闪长岩;简称TTG)的Si同位素应用原理,及应用Si-O同位素约束地球早期构造环境的优势;(2)分析了目前研究中存在的问题,并给出了具体的改进建议和方法;(3)进一步总结了太古宙TTG Si同位素和全球规模的O同位素,Ge/Si比值,及其他地质学和地球化学指标,确认了在大约3.8Ga开始有表壳物质再循环特征的出现;(4)最后依据当前的研究进展,提出了未来具体研究方向。

Resonantly enhanced second-and third-harmonic generation in dielectric nonlinear metasurfaces

Nonlinear dielectric metasurfaces provide a promising approach to control and manipulate frequency conversion optical processes at the nanoscale,thus facilitating both advances in fundamental research and the development of new practical applications in photonics,lasing,and sensing.Here,we employ symmetry-broken metasurfaces made of centrosymmetric amorphous silicon for resonantly enhanced second-and third-order nonlinear optical response.Exploiting the rich physics of optical quasi-bound states in the continuum and guided mode resonances,we comprehensively study through rigorous numerical calculations the relative contribution of surface and bulk effects to second-harmonic generation(SHG)and the bulk contribution to third-harmonic generation(THG) from the meta-atoms.Next,we experimentally achieve optical resonances with high quality factors,which greatly boosts light-matter interaction,resulting in about 550 times SHG enhancement and nearly 5000-fold increase of THG.A good agreement between theoretical predictions and experimental measurements is observed.To gain deeper insights into the physics of the investigated nonlinear optical processes,we further numerically study the relation between nonlinear emission and the structural asymmetry of the metasurface and reveal that the generated harmonic signals arising from linear sharp resonances are highly dependent on the asymmetry of the meta-atoms.Our work suggests a fruitful strategy to enhance the harmonic generation and effectively control different orders of harmonics in all-dielectric metasurfaces,enabling the development of efficient active photonic nanodevices.

芭蕾核风格在女鞋款式设计中的应用研究

随着西方文化在中国的本土化发展,一种名为芭蕾核的服装风格在年轻女性中盛行。该风格旨在表达芭蕾舞蹈中的运动与灵巧,形成一种以女性特征为代表的视觉效果。然而,当今芭蕾核风格在女鞋类市场中的设计表现缺乏系统性的梳理与方法的总结。为了阐明芭蕾核风格在鞋类设计中的特征及应用规律,举例并归纳了芭蕾核的设计风格表征,提炼出芭蕾核中的特征设计元素,并以鞋类款式设计为例,探讨了芭蕾核风格在女鞋款式设计中的设计思路、设计方法、元素变现与发展趋势,为芭蕾核风格在女鞋类款式上的设计运用提供了方法指导。

High-Q resonant terahertz metasurfaces

In photonics, the quest for high-quality (high Q) resonances driven by the physics of bound states in the continuum (BIC)1,2has motivated researchers to explore innovative avenues for realizing groundbreaking applications in lasing3, sensing4and nonlinear photonics5. A conventional strategy to harness the properties of BICs involves breaking the symmetry of resonators in a uniform lattice, allowing uncoupled modes to interact with free space that opens a leaky channel in the form of socalled (quasi) q BIC6modes.

Ultrasensitive Indium Phosphide Nanomembrane Wearable Gas Sensors

Air quality is deteriorating due to continuing urbanization and industrialization.In particular,nitrogen dioxide(NO_(2))is a biologically and environmentally hazardous byproduct from fuel combustion that is ubiquitous in urban life.To address this issue,we report a high-performance flexible indium phosphide nanomembrane NO_(2)sensor for real-time air quality monitoring.An ultralow limit of detection of~200 ppt and a fast response have been achieved with this device by optimizing the film thickness and doping concentration during indium phosphide epitaxy.By varying the film thickness,a dynamic range of values for NO_(2)detection from parts per trillion(ppt)to parts per million(ppm)level have also been demonstrated under low bias voltage and at room temperature without additional light activation.Flexibility measurements show an adequately stable response after repeated bending.On-site testing of the sensor in a residential kitchen shows that NO_(2)concentration from the gas stove emission could exceed the NO_(2)Time Weighted Average limit,i.e.,200 ppb,highlighting the significance of real-time monitoring.Critically,the indium phosphide nanomembrane sensor element cost is estimated at<0.1 US$due to the miniatured size,nanoscale thickness,and ease of fabrication.With these superior performance characteristics,low cost,and real-world applicability,our indium phosphide nanomembrane sensors offer a promising solution for a variety of air quality monitoring applications.

Tracking the Confiscated Green Sea Turtles in the South China Sea:Where Did They Come From?Where Will They Go?

The population of the green sea turtle(Chelonia mydas)is under decline,threatened by bycatch and illegal acquisition despite worldwide protection efforts.However,the confiscation of illegally acquired sea turtles could aid in tracking their origin and movement patterns,crucial for effective conservation strategies.Combining satellite tracking and genetic analysis offers an opportunity to investigate the relationship between the origins and migration directions of green sea turtles in the western Pacific.Here,we applied two methods to investigate the spatial ecology of 18 green turtles caught as bycatch in the South China Sea.Our results revealed the genetic origins and diverse movements of the turtles.Bayesian Mixed Stock Analysis(MSA)suggested that these turtles originated from the rookery of the Xisha Islands(49.6%),central Ryukyu(24.6%),NE Borneo(8%),and the Sulu Sea(5.2%),with other rookeries in meagre proportions(<2%each).Satellite tracking showed the ranges of their travel were smaller than the whole contributed rookery range,but diverse.The haplotype diversity of these turtles is high,and CmP19 stands out as both the most frequent and the most diverse haplotype in terms of swimming destinations.These results indicate that the South China Sea is likely an important transportation hub and mating spot for green turtles.Our findings provided evidence for the rehabilitation of these green turtles in the wild and illustrated the complexity of movement during the green turtle’s life history,and the“mixed backgrounds”of the green turtles also highlight the need for joint conservation efforts of neighbouring countries in the South China Sea.

Privacy-preserved learning from non-i.i.d data in fog-assisted IoT:A federated learning approach

With the prevalence of the Internet of Things(IoT)systems,smart cities comprise complex networks,including sensors,actuators,appliances,and cyber services.The complexity and heterogeneity of smart cities have become vulnerable to sophisticated cyber-attacks,especially privacy-related attacks such as inference and data poisoning ones.Federated Learning(FL)has been regarded as a hopeful method to enable distributed learning with privacypreserved intelligence in IoT applications.Even though the significance of developing privacy-preserving FL has drawn as a great research interest,the current research only concentrates on FL with independent identically distributed(i.i.d)data and few studies have addressed the non-i.i.d setting.FL is known to be vulnerable to Generative Adversarial Network(GAN)attacks,where an adversary can presume to act as a contributor participating in the training process to acquire the private data of other contributors.This paper proposes an innovative Privacy Protection-based Federated Deep Learning(PP-FDL)framework,which accomplishes data protection against privacy-related GAN attacks,along with high classification rates from non-i.i.d data.PP-FDL is designed to enable fog nodes to cooperate to train the FDL model in a way that ensures contributors have no access to the data of each other,where class probabilities are protected utilizing a private identifier generated for each class.The PP-FDL framework is evaluated for image classification using simple convolutional networks which are trained using MNIST and CIFAR-10 datasets.The empirical results have revealed that PF-DFL can achieve data protection and the framework outperforms the other three state-of-the-art models with 3%–8%as accuracy improvements.

Combining field data and modeling to better understand maize growth response to phosphorus(P) fertilizer application and soil P dynamics in calcareous soils

We used field experimental data to evaluate the ability of the agricultural production system model (APSIM) to simulate soil P availability,maize biomass and grain yield in response to P fertilizer applications on a fluvo-aquic soil in the North China Plain.Crop and soil data from a 2-year experiment with three P fertilizer application rates(0,75 and 300 kg P_(2)O_(5) ha^(–1)) were used to calibrate the model.Sensitivity analysis was carried out to investigate the influence of APSIM SoilP parameters on the simulated P availability in soil and maize growth.Crop and soil P parameters were then derived by matching or relating the simulation results to observed crop biomass,yield,P uptake and Olsen-P in soil.The re-parameterized model was further validated against 2 years of independent data at the same sites.The re-parameterized model enabled good simulation of the maize leaf area index (LAI),biomass,grain yield,P uptake,and grain P content in response to different levels of P additions against both the calibration and validation datasets.Our results showed that APSIM needs to be re-parameterized for simulation of maize LAI dynamics through modification of leaf size curve and a reduction in the rate of leaf senescence for modern staygreen maize cultivars in China.The P concentration limits (maximum and minimum P concentrations in organs)at different stages also need to be adjusted.Our results further showed a curvilinear relationship between the measured Olsen-P concentration and simulated labile P content,which could facilitate the initialization of APSIM P pools in the NCP with Olsen-P measurements in future studies.It remains difficult to parameterize the APSIM SoilP module due to the conceptual nature of the pools and simplified conceptualization of key P transformation processes.A fundamental understanding still needs to be developed for modelling and predicting the fate of applied P fertilizers in soils with contrasting physical and chemical characteristics.

Biological perspectives in geotechnics:Application and monitoring

This paper builds on exploring the applications of biomediated pathways to solve geotechnical challenges.First,the state of the art of biological remediation strategies including microbial remediation and phytoremediation have been introduced and critically reviewed in the context of decontaminating the soils.Next,biopolymerisation,biomineralisation and bioneutralisation processes have been depicted with a special emphasis on the applications including but not limited to soil stabilisation,soil erosion prevention,anti-desertification and pH neutralisation.Each of these methods have their own limitations and bottlenecks while scaling up,and these challenges have been summarised and some possible paths to overcome the challenges have also been discussed.The state of the art of electromagnetic(EM)monitoring methods to capture the effects of biomediation on spatio-temporal soil properties are then highlighted as a non-invasive and rapid pathway to track the progress of biomediated soil processes.Finally,each of the technologies discussed have been evaluated for their maturity level using the principles of technology readiness level(TRL).A majority of the technologies amounting to around 77%are still in the TRL 4e7,i.e.in the valley of death.It is thus evident that development of these technologies needs to be supported with appropriate funding for improving their maturity to a level of industrial deployment.

Competitive effect, but not competitive response, varies along a climatic gradient depending on tree species identity

Background: Understanding the role of species identity in interactions among individuals is crucial for assessing the productivity and stability of mixed forests over time. However, there is limited knowledge concerning the variation in competitive effect and response of different species along climatic gradients. In this study, we investigated the importance of climate, tree size, and competition on the growth of three tree species: spruce(Picea abies), fir(Abies alba), and beech(Fagus sylvatica), and examined their competitive response and effect along a climatic gradient.Methods: We selected 39 plots distributed across the European mountains with records of the position and growth of 5,759 individuals. For each target species, models relating tree growth to tree size, climate and competition were proposed. Competition was modelled using a neighbourhood competition index that considered the effects of inter-and intraspecific competition on target trees. Competitive responses and effects were related to climate.Likelihood methods and information theory were used to select the best model.Results: Our findings revealed that competition had a greater impact on target species growth than tree size or climate. Climate did influence the competitive effects of neighbouring species, but it did not affect the target species? response to competition. The strength of competitive effects varied along the gradient, contingent on the identity of the interacting species. When the target species exhibited an intermediate competitive effect relative to neighbouring species, both higher inter-than intraspecific competitive effects and competition reduction occurred along the gradient. Notably, species competitive effects were most pronounced when the target species' growth was at its peak and weakest when growing conditions were far from their maximum.Conclusions: Climate modulates the effects of competition from neighbouring trees on the target tree and not the susceptibility of the target tree to competition. The modelling approach should be useful in future research to expand our knowledge of how competition modulates forest communities across environmental gradients.