Agricultural Investment Project Decisions Based on an Interactive Preference Disaggregation Model Considering Inconsistency

Agricultural investment project selection is a complex multi-criteria decision-making problem,as agricultural projects are easily influenced by various risk factors,and the evaluation information provided by decisionmakers usually involves uncertainty and inconsistency.Existing literature primarily employed direct preference elicitation methods to address such issues,necessitating a great cognitive effort on the part of decision-makers during evaluation,specifically,determining the weights of criteria.In this study,we propose an indirect preference elicitation method,known as a preference disaggregation method,to learn decision-maker preference models fromdecision examples.To enhance evaluation ease,decision-makers merely need to compare pairs of alternatives with which they are familiar,also known as reference alternatives.Probabilistic linguistic preference relations are employed to account for the presence of incomplete and uncertain information in such pairwise comparisons.To address the inconsistency among a group of decision-makers,we develop a pair of 0-1mixed integer programming models that consider both the semantics of linguistic terms and the belief degrees of decision-makers.Finally,we conduct a case study and comparative analysis.Results reveal the effectiveness of the proposed model in solving agricultural investment project selection problems with uncertain and inconsistent decision information.

Do BRICS Have Similar Disaggregated Trade Patterns with Different Regions?

This is the first study attempting to investigate the patterns of BRICS' imports and exports with five United Nations regional groups: the African, Asia-Pacific, Eastern European, Latin American and Caribbean, and Western European and Others. A panel data gravity trade model with series from 2001 to 2016 was used to estimate the gravity variables in the models. The main results provide evidence that reinforced the dissimilarities in the foreign trade patterns of BRICS with these five regional groups. The econometric results substantiated that BRICS' foreign trade patterns are sensitive to changes in the economies of trading partners from the more developed regions. This is evidence for stronger economic ties between BRICS and the more developed regions such as Western Europe and Asia-Pacific. It also reveals the trade convergence of BRICS in these developed regions.

Reporting Children’s Development below the Test Floor: Looking Back and Forth to Describe Individual Strengths and Needs

The test floor effects seen in standardised tests lead to a standardised score of 1 or less with a flat profile that hides a child’s individual strengths and needs. The Griffiths III community of practitioners requested advice on the reporting of children’s development below the floor of the test, so that individual strengths and needs can be described. This paper reports the third phase of research following an earlier Scoping Review and a wider literature review. To confirm quality control, Phase 3 was conducted in a retrospective manner using the same methodology as the earlier phases but in a reverse direction. Peer reviewer comments and key elements from the Scoping Review and keywords from the publications were tabulated. Data analysis included a change of perspective to that of the child and their individual rights with respect to the literature themes already described in Phase 2. These confirmed that there is little specific guidance in the literature, but that computational advances for homogeneous populations and especially disaggregated data offer some solutions. A greater balance between broad biopsychosocial models and standardised models of assessment should be sought by practitioners together with the use of disaggregated data to highlight issues that pertain to individual subsets of results. This will ensure that the child’s right for their individual strengths and needs to be described together with a plan for management, may be met.

Proanthocyanidins prevent tau protein aggregation and disintegrate tau filaments

Occurrence of neurofibrillary tangles of the tau protein is a hallmark of tau-related neurodegenerative diseases, i.e. Alzheimer's disease(AD) and frontotemporal dementia. The pathological mechanism underlying AD remains poorly understood, and effective treatments are still unavailable to mitigate the disease.Inhibiting of tau aggregation and disrupting the existing fibrils are key targets in drug discovery towards preventing or curing AD. In this study, grape seed proanthocyanidins(GSPs) was found to effectively inhibit the repeat domain of tau(tau-RD) aggregation and disaggregate tau-RD fibrils in a concentrationdependent manner by inhibiting β-sheet formation of tau-RD. In cells, GSPs relieved cytotoxicity induced by tau-RD aggregates. Molecular dynamics simulations indicated that strong hydrogen bonding,hydrophobic interaction and π-π stacking between GSPs and tau-RD protein were major reasons why GSPs had high inhibitory activity on tau-RD fibrillogenesis. These results provide preliminary data to develop GSPs into medicines, foodstuffs or nutritional supplements for AD patients, suggesting that GSPs could be a candidate molecule in the drug design for AD therapeutics.

Can a multistage approach improve individual tree mortality predictions across the complex mixed-species and managed forests of eastern North America?

Tree mortality plays a fundamental role in the dynamics of forest ecosystems,yet it is one of the most difficult phenomena to accurately predict.Various modeling strategies have been developed to improve individual tree mortality predictions.One less explored strategy is the use of a multistage modeling approach.Potential improvements from this approach have remained largely unknown.In this study,we developed a novel multistage approach and compared its performance in individual tree mortality predictions with a more conventional approach using an identical individual tree mortality model formulation.Extensive permanent plot data(n=9442)covering the Acadian Region of North America and over multiple decades(1965–2014)were used in this study.Our results indicated that the model behavior with the multistage approach better depicted the observed mortality and showed a notable improvement over the conventional approach.The difference between the observed and predicted numbers of dead trees using the multistage approach was much smaller when compared with the conventional approach.In addition,tree survival probabilities predicted by the multistage approach generally were not significantly different from the observations,whereas the conventional approach consistently underestimated mortality across species and overestimated tree survival probabilities over the large range of DBH in the data.The new multistage approach also predictions of zero mortality in individual plots,a result not possible in conventional models.Finally,the new approach was more tolerant of modeling errors because it based estimates on ranked tree mortality rather than error-prone predicted values.Overall,this new multistage approach deserves to be considered and tested in future studies.

Assessment of Future Drought in Southwest China Based on CMIP5 Multimodel Projections

In the last decade, a series of severe and extensive droughts have swept across Southwest China, resulting in tremendous economic losses, deaths, and disruption to society. Consequently, this study is motivated by the paramount importance of as- sessing future changes in drought in Southwest China. Precipitation is likely to decrease over most parts of Southwest China around the beginning of the century, followed by widespread precipitation increases; the increase in potential evapotran- spiration （PET）, due to the joint effects of increased temperature and surface net radiation and decreased relative humidity, will overwhelm the whole region throughout the entire 21st century. In comparative terms, the enhancement of PET will outweigh that of precipitation, particularly under Representative Concentration Pathway （RCP） 8.5, resulting in intensified drought. Generally, the drying tendency will be in the southeast portion, whereas the mountainous region in the northwest will become increasingly wetter owing to abundant precipitation increases. Droughts classified as moderate/severe according to historical standards will become the norm in the 2080s under RCP4.5/RCP8.5. Future drought changes will manifest different characteristics depending on the time scale： the magnitude of change at a time scale of 48 months is nearly twice as great as that at 3 months. Furthermore, we will see that not only will incidences of severe and extreme drought increase dramatically in the future, but extremely wet events will also become more probable.

Development of fragility curves by incorporating new spectral shape indicators and a weighted damage index:case study of steel braced frames in the city of Mashhad,Iran

In this study, strong ground motion record （SGMR） selection based on Eta （~/） as a spectral shape indicator has been investigated as applied to steel braced flame structures. A probabilistic seismic hazard disaggregation analysis for the definition of the target Epsilon （ε） and the target Eta （η） values at different hazard levels is presented, taking into account appropriately selected SGMR＇s. Fragility curves are developed for different limit states corresponding to three representative models of typical steel braced frames having significant irregularities in plan, by means of a weighted damage index. The results show that spectral shape indicators have an important effect on the predicted median structural capacities, and also that the parameter r/is a more robust predictor of damage than searching for records with appropriate c values.

Linking individual-tree and whole-stand models for forest growth and yield prediction

Background： Different types of growth and yield models provide essential information for making informed decisions on how to manage forests. Whole-stand models often provide well-behaved outputs at the stand level, but lack information on stand structures. Detailed information from individual-tree models and size-class models typically suffers from accumulation of errors. The disaggregation method, in assuming that predictions from a whole-stand model are reliable, partitions these outputs to individual trees. On the other hand, the combination method seeks to improve stand-level predictions from both whole-stand and individual-tree models by combining them. Methods： Data from 100 plots randomly selected from the Southwicte Seed Source Study of Ioblolly pine （Pinus taedo L） were used to evaluate the unadjusted individual-tree model against the disaggregation and combination methods. Results： Compared to the whole-stand model, the combination method did not show improvements in predicting stand attributes in this study. The combination method also did not perform as well as the disaggregation method in tree-level predictions. The disaggregation method provided the best predictions of tree- and stand-level survival and growth. Conclusions： The disaggregation approach provides a link between individual-tree models and whole-stand models, and should be considered as a better alternative to the unadjusted tree model.

Soil polygon disaggregation through similarity-based prediction with legacy pedons

Conventional soil maps generally contain one or more soil types within a single soil polygon.But their geographic locations within the polygon are not specified.This restricts current applications of the maps in site-specific agricultural management and environmental modelling.We examined the utility of legacy pedon data for disaggregating soil polygons and the effectiveness of similarity-based prediction for making use of the under-or over-sampled legacy pedon data for the disaggregation.The method consisted of three steps.First,environmental similarities between the pedon sites and each location were computed based on soil formative environmental factors.Second,according to soil types of the pedon sites,the similarities were aggregated to derive similarity distribution for each soil type.Third,a hardening process was performed on the maps to allocate candidate soil types within the polygons.The study was conducted at the soil subgroup level in a semi-arid area situated in Manitoba,Canada.Based on 186 independent pedon sites,the evaluation of the disaggregated map of soil subgroups showed an overall accuracy of 67% and a Kappa statistic of 0.62.The map represented a better spatial pattern of soil subgroups in both detail and accuracy compared to a dominant soil subgroup map,which was commonly used in practice.Incorrect predictions mainly occurred in the agricultural plain area and the soil subgroups that are very similar in taxonomy,indicating that new environmental covariates need to be developed.We concluded that the combination of legacy pedon data with similarity-based prediction is an effective solution for soil polygon disaggregation.

Residential PV capacity estimation and power disaggregation using net metering measurements

As the intermittency and uncertainty of photovoltaic(PV)power generation poses considerable challenges to the power system operation,accurate PV generation estimates are critical for the distribution operation,maintenance,and demand response program implementation because of the increasing usage of distributed PVs.Currently,most residential PVs are installed behind the meter,with only the net load available to the utilities.Therefore,a method for disaggregating the residential PV generation from the net load data is needed to enhance the grid-edge observability.In this study,an unsupervised PV capacity estimation method based on net metering data is proposed,for estimating the PV capacity in the customer’s premise based on the distribution characteristics of nocturnal and diurnal net load extremes.Then,the PV generation disaggregation method is presented.Based on the analysis of the correlation between the nocturnal and diurnal actual loads and the correlation between the PV capacity and their actual PV generation,the PV generation of customers is estimated by applying linear fitting of multiple typical solar exemplars and then disaggregating them into hourly-resolution power profiles.Finally,the anomalies of disaggregated PV power are calibrated and corrected using the estimated capacity.Experiment results on a real-world hourly dataset involving 260 customers show that the proposed PV capacity estimation method achieves good accuracy because of the advantages of robustness and low complexity.Compared with the state-of-the-art PV disaggregation algorithm,the proposed method exhibits a reduction of over 15%for the mean absolute percentage error and over 20%for the root mean square error.

Projection of hydrothermal condition in Central Asia under four SSP-RCP scenarios

Hydrothermal condition is mismatched in arid and semi-arid regions,particularly in Central Asia(including Kazakhstan,Kyrgyzstan,Tajikistan,Uzbekistan,and Turkmenistan),resulting many environmental limitations.In this study,we projected hydrothermal condition in Central Asia based on bias-corrected multi-model ensembles(MMEs)from the Coupled Model Intercomparison Project Phase 6(CMIP6)under four Shared Socioeconomic Pathway and Representative Concentration Pathway(SSP-RCP)scenarios(SSP126(SSP1-RCP2.6),SSP245(SSP2-RCP4.5),SSP460(SSP4-RCP6.0),and SSP585(SSP5-RCP8.5))during 2015-2100.The bias correction and spatial disaggregation,water-thermal product index,and sensitivity analysis were used in this study.The results showed that the hydrothermal condition is mismatched in the central and southern deserts,whereas the region of Pamir Mountains and Tianshan Mountains as well as the northern plains of Kazakhstan showed a matched hydrothermal condition.Compared with the historical period,the matched degree of hydrothermal condition improves during 2046-2075,but degenerates during 2015-2044 and 2076-2100.The change of hydrothermal condition is sensitive to precipitation in the northern regions and the maximum temperatures in the southern regions.The result suggests that the optimal scenario in Central Asia is SSP126 scenario,while SSP585 scenario brings further hydrothermal contradictions.This study provides scientific information for the development and sustainable utilization of hydrothermal resources in arid and semi-arid regions under climate change.

Potential of peptides and phytochemicals in attenuating different phases of islet amyloid polypeptide fi brillation for type 2 diabetes management

Islet amyloid polypeptide(IAPP),or amylin,has been identifi ed as a key factor in the development of type 2 diabetes(T2D).IAPP aggregates,which form amyloid fi brils,contribute to cytotoxicity of the pancreatic β-cells,resulting in loss of function and subsequent reduction in insulin production.As a result,surviving β-cells overcompensate for this reduction of insulin production,further contributing to the loss of function because of increased stress,thus leading to insulin resistance.Endogenously,IAPP monomers function in a variety of roles;however,aggregation renders them non-functional.The use of naturally occurring compounds,including peptides and phytochemicals,has been explored as a way to mitigate or inhibit IAPP fi bril formation.This review discusses the structure,endogenous roles and mechanism of IAPP fi bril formation,recent advances on inhibitors of IAPP fi bril formation,and new insights on the future development and application of foodderived inhibitors towards T2D management.

Reservoir quality of fluvial sandstone reservoirs in salt-walled mini- basins： an example from the Seagull field, Central Graben, North Sea, UK

The Triassic fluvial sandstones of the Skagerrak Formation were deposited in a series of salt-walled mini-basins and act as important hydrocarbon reservoirs for several high-pressure, high-temperature（HPHT） fields in the Central Graben, North Sea. The HPHT reservoirs exhibit excellent reservoir quality considering their depth of burial and hence have been of high interest for hydrocarbon exploration. This research uses a multidisciplinary approach to assess the Skagerrak Formation fluvial reservoir quality from the Seagull field incorporating core analysis, petrography, electron microscopy, XRD analysis, fluid inclusion appraisal and burial history modelling. Halokinesis and salt withdrawal at the margin of the saltwalled mini-basin induced early disaggregation bands and fractures at shallow burial and led to increased influx of meteoric water and clay mineral infiltration from overlying sedimentation. The density of disaggregation bands correlates with the occurrence and magnitude of pore-filling authigenic clay minerals, concentrated along the margin of the saltwalled mini-basin. The fluvial channel sandstones of the Skagerrak Formation are subject to strong intra-basinal spatial reservoir quality variations despite diagenesis and low vertical effective stress having played a favourable role in arresting porosity loss.

Temporal Disaggregation of Time Series Revisited

With the benefits of increased computing power and much improved software,temporal disaggregation is examined.Disaggregation,the process of obtaining high frequency data from low frequency data has been discussed for many years.This study examines three methods which utilize the autoregressive integrated moving average(ARIMA)model in a simulation study comparing parameter estimation,disaggregation mean square error,and forecast mean square error.Finally,the three methods are applied to a real-world time series.

The Determinants of China's Minimum Wage Rates

We use a highly disaggregated panel of macro data and minimum wages at the county level to investigate the processes behind minimum wage adjustments in China.Relying on random effects models,spatial econometrics techniques,and multilevel analyses,we document that a comparatively small number of economic variables-including the local price level and GDP per capita-are important determinants of minimum wage rates.Interactions between adjacent counties and counties of the same administrative type,and centralized mechanisms,particularly at the provincial level,also play an important role in explaining the variance in minimum wage rates across counties.Finally,we show that China's provinces are the key players for setting minimum wage rates and that,when they do so,they are not uniform in the way they weigh different economic variables.

Distributed Real-time Temperature and Energy Control of Energy Efficient Buildings via Geothermal Heat Pumps

Geothermal heat pumps(GHPs)are a type of heating ventilation and air conditioning(HVAC)systems that use low-temperature resources from soil and groundwater for heating/cooling.In recent years,there has been an increasing interest in GHP systems due to their high energy efficiency and abundant geothermal resources.Thus,the optimization and control design of the GHP system has become a hot topic.On the other hand,as the GHP system is an ideal respon-sive load,mechanism design for the GHP system to realize demand response(DR)in a virtual power plant(VPP)without affecting user comfort is particularly essential.In this paper,we propose a distributed real-time temperature and energy management method via GHP systems for multi-buildings,where both floor and radiator heating/cooling distribution subsystems in multiple thermal zones are considered.We design an energy demand response mechanism for a single GHP to track the given energy consumption command for participating in VPP aggregation/disaggregation.Besides,a coordination mechanism for multiple GHPs is designed for the community-level oper-ator in joining VPP aggregation/disaggregation.Both designed schemes are scalable and do not need to measure or predict any exogenous disturbances such as outdoor temperature and heating disturbances from external sources,e.g.,user activity and device operation.Finally,four numerical examples for the simulation of two different scenarios demonstrate the effectiveness of the proposed methods.

Reinvent Cloud Software Stacks for Resource Disagggiregation

Due to the unprecedented development of low-latency interconnect technology,building large-scale disaggre-gated architecture is drawing more and more attention from both industry and academia.Resource disaggregation is a new way to organize the hardware resources of datacenters,and has the potential to overcome the limitations,e.g.,low re-source utilization and low reliability,of conventional datacenters.However,the emerging disaggregated architecture brings severe performance and latency problems to the existing cloud systems.In this paper,we take memory disaggregation as an example to demonstrate the unique challenges that the disaggregated datacenter poses to the existing cloud software stacks,e.g.,programming interface,language runtime,and operating system,and further discuss the possible ways to rein-vent the cloud systems.

Contour detection with bicubic spline surfaces

Contour detection has a rich history in multiplefields such as geography,engineering,and earth science.The predominant approach is based on piecewise planar tessellation and now being challenged concerning the extraction of contour objects for non-linear elevation functions,particularly with respect to bicubic spline functions.A storage-efficient method was developed in previous research,but the detection of the complete set of contour objects is yet to be realized.Although intractable,theoretical underpinnings pertinent to curvature resulted in an approach to realize the complete detection of objects.Given a digital elevation model dataset,in this study,a bicubic spline surface function wasfirst determined.Thereafter,candidate initial points on the edges across the region of interest were identified,and the recursive disaggregation of rectangles was repeated if the non-existence of a solution could not be assured.A developed tracking method was then applied.During advancement,other initial points on the same contour curve were identified and eliminated to circumvent duplicate detection.The completeness of the outlets provides analytical tools for elevation and other geographical assessments.Demonstrative experiments included the development of a three-dimensional contour-based network and slope assessments.The latter application transforms the slope analysis type from raster-based to vector-based.Highlights.Detection of a complete set of contour objects amenable to bicubic spline surfaces..Small closure inside a single patch is detectable if size exceeds the standard..Curvature&tolerances central to step length adjustment and tangent angle determination..Redundant initial points are identified and eliminated during the tracking process..Various potential applications in addition to geographical elevations.

Potential Alzheimer’s disease therapeutic nano-platform: Discovery of amyloid-beta plaque disaggregating agent and brain-targeted delivery system using porous silicon nanoparticles

There has been a lot of basic and clinical research on Alzheimer’s disease(AD)over the last 100 years,but its mechanisms and treatments have not been fully clarified.Despite some controversies,the amyloid-beta hypothesis is one of the most widely accepted causes of AD.In this study,we disclose a new amyloid-beta plaque disaggregating agent and an AD brain-targeted delivery system using porous silicon nanoparticles(pSiNPs)as a therapeutic nano-platform to overcome AD.We hypothesized that the negatively charged sulfonic acid functional group could disaggregate plaques and construct a chemical library.As a result of the in vitro assay of amyloid plaques and library screening,we confirmed that 6-amino-2-naphthalenesulfonic acid(ANA)showed the highest efficacy for plaque disaggregation as a hit compound.To confirm the targeted delivery of ANA to the AD brain,a nano-platform was created using porous silicon nanoparticles(pSiNPs)with ANA loaded into the pore of pSiNPs and biotin-polyethylene glycol(PEG)surface functionalization.The resulting nano-formulation,named Biotin-CaCl2-ANA-pSiNPs(BCAP),delivered a large amount of ANA to the AD brain and ameliorated memory impairment of the AD mouse model through the disaggregation of amyloid plaques in the brain.This study presents a new bioactive small molecule for amyloid plaque disaggregation and its promising therapeutic nano-platform for AD brain-targeted delivery.

A systematic approach in load disaggregation utilizing a multi-stage classification algorithm for consumer electrical appliances classification

The potential to save energy in existing consumer electrical appliances is very high. One of the ways to achieve energy saving and improve energy use awareness is to recognize the energy consumption of individual electrical appliances. To recognize the energy consumption of consumer electrical appliances, the load disaggregation methodology is utilized. Non-intrusive appliance load monitoring (NIALM) is a load disaggrega-tion methodology that disaggregates the sum of power consumption in a single point into the power consumption of individual electrical appliances. In this study, load disaggregation is performed through voltage and current waveform, known as the V-I trajectory. The classification algorithm performs cropping and image pyramid reduction of the V-I trajectory plot template images before utilizing the principal component analysis (PCA) and the k-nearest neighbor (k-NN) algorithm. The novelty of this paper is to establish a systematic approach of load disaggregation through V-I trajectory-based load signature images by utilizing a multi-stage classification algorithm methodol-ogy. The contribution of this paper is in utilizing the “k- value,” the number of closest data points to the nearest neighbor, in the k-NN algorithm to be effective in classification of electrical appliances. The results of the multi-stage classification algorithm implementation have been discussed and the idea on future work has also been proposed.