Uncovering the Memories Sealed in Stones

Do stones havememories?Can theytalk?ForGewang,a conservatorwhohas dedicated tenyears toTibetan stone carvingart,theanswer is yes.Heis thrilled to witness the increasing efforts in the preservation and study of stone carvings and the growing number of peoplejoining this cause.

A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction

Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.

Uncovering the miRNA-mediated regulatory network involved in Ma bamboo(Dendrocalamus latiflorus)de novo shoot organogenesis

Bamboo is an important non-timber forest product and is well-known for its reluctance to regenerate.Recently we have established a de novo shoot organogenesis(DNSO)protocol in Ma bamboo(Dendrocalamus latiflorus)and revealed the transcriptomic dynamics during Ma bamboo regeneration,which suggested the potential roles of Ma bamboo microRNAs(DlamiRNAs)in this process.However,how DlamiRNAs regulate bamboo DNSO is poorly understood.Here we performed integrated analysis with sRNAome,degradome,and transcriptome sequencing by using samples covering the four stages of the bamboo DNSO process.A total of 727 DlamiRNAs showed differential expression during the bamboo DNSO process,and the core DlamiRNA-DlamRNA-mediated regulatory networks for bamboo DNSO were constructed.Based on the results,DlamiR156 was selected for further functional characterization of its potential roles in bamboo DNSO.Transgenic bamboos with increased DlamiR156 levels exhibited an enhancement in their regeneration efficiency.Conversely,when DlamiR156 levels were downregulated,the regeneration efficiencies of transgenic bamboos decreased.Our findings show that the DlamiRNA-mediated regulatory pathways are significant in the process of bamboo regeneration and will contribute to our understanding of the molecular mechanisms governing plant organogenesis in a more comprehensive manner.

The Research on the Psychological Tactic of Covering the Dagger With a Smile

Thirty-Six Stratagems is one of the most important military works of ancient China.As the name of the book,it totally includes 36 stratagems that can be used in many different fields such as military,business,and politics.Covering the dagger with a smile is one of the most common ones in these stratagems.At the same time,it is the most insidious one.As a kind of psychological tactic,it usually acts as the secret weapon of the weak.Though this stratagem should not be seen as a kind of predominant strategy,it is still worth being researched deeply,because knowing more about this psychological tactic will offer a good reference for the researchers of ancient art of war.

Adding Value to Crop Production Systems by Integrating Forage Cover Crop Grazing

In addition to their value as cereal grains, wheat (Triticum aestivum L.) and triticale (× Triticosecale Wittmack) are important cool-season annual forages and cover crops. Yearling steer (Bos taurus) performance was compared in the spring following autumn establishment as for age cover crops after soybean [Glycine max (L.) Merr.] grain harvest. Replicated pastures (0.4 ha) were no-till seeded in three consecutive years into soybean stubble in autumn, fertilized, and grazed the following spring near Ithaca, NE, USA. Each pasture (n = 3) was continuously stocked in spring with four yearling steers (380 ± 38 kg) for 17, 32, and 28 d in 2005, 2006, and 2007, respectively. In 2005, average daily gain (ADG) for steers grazing triticale exceeded the ADG for wheat by 0.31 kghd-1d-1. In 2006, wheat ADG exceeded that for triticale by 0.12 kghd-1d-1. In 2007, steers grazing wheat lost weight, while steers grazing triticale gained 0.20 kghd-1d-1. Based on the 3-year average animal gains valued at $1.32 kg-1, mean net return ($ ha-1 yr-1) was $62.15 for triticale and $22.55 for wheat. Since these grazed cover crops provide ecosystem services in addition to forage, grazing could be viewed as a mechanism for recovering costs and adds additional value to the system. Based on this 3-year grazing trial, triticale was superior to wheat and likely will provide the most stable beef yearling performance across years with variable weather for the western Cornbelt USA.

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.

Short-Term Household Load Forecasting Based on Attention Mechanism and CNN-ICPSO-LSTM

Accurate load forecasting forms a crucial foundation for implementing household demand response plans andoptimizing load scheduling. When dealing with short-term load data characterized by substantial fluctuations,a single prediction model is hard to capture temporal features effectively, resulting in diminished predictionaccuracy. In this study, a hybrid deep learning framework that integrates attention mechanism, convolution neuralnetwork (CNN), improved chaotic particle swarm optimization (ICPSO), and long short-term memory (LSTM), isproposed for short-term household load forecasting. Firstly, the CNN model is employed to extract features fromthe original data, enhancing the quality of data features. Subsequently, the moving average method is used for datapreprocessing, followed by the application of the LSTM network to predict the processed data. Moreover, the ICPSOalgorithm is introduced to optimize the parameters of LSTM, aimed at boosting the model’s running speed andaccuracy. Finally, the attention mechanism is employed to optimize the output value of LSTM, effectively addressinginformation loss in LSTM induced by lengthy sequences and further elevating prediction accuracy. According tothe numerical analysis, the accuracy and effectiveness of the proposed hybrid model have been verified. It canexplore data features adeptly, achieving superior prediction accuracy compared to other forecasting methods forthe household load exhibiting significant fluctuations across different seasons.

Modeling injection-induced fault slip using long short-term memory networks

Stress changes due to changes in fluid pressure and temperature in a faulted formation may lead to the opening/shearing of the fault.This can be due to subsurface(geo)engineering activities such as fluid injections and geologic disposal of nuclear waste.Such activities are expected to rise in the future making it necessary to assess their short-and long-term safety.Here,a new machine learning(ML)approach to model pore pressure and fault displacements in response to high-pressure fluid injection cycles is developed.The focus is on fault behavior near the injection borehole.To capture the temporal dependencies in the data,long short-term memory(LSTM)networks are utilized.To prevent error accumulation within the forecast window,four critical measures to train a robust LSTM model for predicting fault response are highlighted:(i)setting an appropriate value of LSTM lag,(ii)calibrating the LSTM cell dimension,(iii)learning rate reduction during weight optimization,and(iv)not adopting an independent injection cycle as a validation set.Several numerical experiments were conducted,which demonstrated that the ML model can capture peaks in pressure and associated fault displacement that accompany an increase in fluid injection.The model also captured the decay in pressure and displacement during the injection shut-in period.Further,the ability of an ML model to highlight key changes in fault hydromechanical activation processes was investigated,which shows that ML can be used to monitor risk of fault activation and leakage during high pressure fluid injections.

Changes in Spring Snow Cover over the Eastern and Western Tibetan Plateau and Their Associated Mechanism

The spring snow cover(SC)over the western Tibetan Plateau(TP)(TPSC)(W_TPSC)and eastern TPSC(E_TPSC)have displayed remarkable decreasing and increasing trends,respectively,during 1985–2020.The current work investigates the possible mechanisms accounting for these distinct TPSC changes.Our results indicate that the decrease in W_TPSC is primarily attributed to rising temperatures,while the increase in E_TPSC is closely linked to enhanced precipitation.Local circulation analysis shows that the essential system responsible for the TPSC changes is a significant anticyclonic system centered over the northwestern TP.The anomalous descending motion and adiabatic heating linked to this anticyclone leads to warmer temperatures and consequent snowmelt over the western TP.Conversely,anomalous easterly winds along the southern flank of this anticyclone serve to transport additional moisture from the North Pacific,leading to an increase in snowfall over the eastern TP.Further analysis reveals that the anomalous anticyclone is associated with an atmospheric wave pattern that originates from upstream regions.Springtime warming of the subtropical North Atlantic(NA)sea surface temperature(SST)induces an atmospheric pattern resembling a wave train that travels eastward across the Eurasian continent before reaching the TP.Furthermore,the decline in winter sea ice(SIC)over the Barents Sea exerts a persistent warming influence on the atmosphere,inducing an anomalous atmospheric circulation that propagates southeastward and strengthens the northwest TP anticyclone in spring.Additionally,an enhancement of subtropical stationary waves has resulted in significant increases in easterly moisture fluxes over the coastal areas of East Asia,which further promotes more snowfall over eastern TP.

A Time Series Short-Term Prediction Method Based on Multi-Granularity Event Matching and Alignment

Accurate forecasting of time series is crucial across various domains.Many prediction tasks rely on effectively segmenting,matching,and time series data alignment.For instance,regardless of time series with the same granularity,segmenting them into different granularity events can effectively mitigate the impact of varying time scales on prediction accuracy.However,these events of varying granularity frequently intersect with each other,which may possess unequal durations.Even minor differences can result in significant errors when matching time series with future trends.Besides,directly using matched events but unaligned events as state vectors in machine learning-based prediction models can lead to insufficient prediction accuracy.Therefore,this paper proposes a short-term forecasting method for time series based on a multi-granularity event,MGE-SP(multi-granularity event-based short-termprediction).First,amethodological framework for MGE-SP established guides the implementation steps.The framework consists of three key steps,including multi-granularity event matching based on the LTF(latest time first)strategy,multi-granularity event alignment using a piecewise aggregate approximation based on the compression ratio,and a short-term prediction model based on XGBoost.The data from a nationwide online car-hailing service in China ensures the method’s reliability.The average RMSE(root mean square error)and MAE(mean absolute error)of the proposed method are 3.204 and 2.360,lower than the respective values of 4.056 and 3.101 obtained using theARIMA(autoregressive integratedmoving average)method,as well as the values of 4.278 and 2.994 obtained using k-means-SVR(support vector regression)method.The other experiment is conducted on stock data froma public data set.The proposed method achieved an average RMSE and MAE of 0.836 and 0.696,lower than the respective values of 1.019 and 0.844 obtained using the ARIMA method,as well as the values of 1.350 and 1.172 obtained using the k-means-SVR method.

Assessing Spatio-Temporal Land Cover Changes in Dhund River Basin, Eastern Rajasthan (India), Using Multi-Temporal Landsat Data

Land cover is an impression of natural cover on surface of earth such as bare soil, river, grass etc. and utilization of these natural covers for various human needs and purposes by mankind is defined as land use. Land cover identification, delineation and mapping is important for planning activities, resource management and global monitoring studies while baseline mapping and subsequent monitoring is done by application of land use to get timely information about quantity of land that has been used. The present study has been carried out in Dhund river watershed of Jaipur, Rajasthan which covers an area of about 1828 sq∙km. The minimum and maximum elevation of the area is found to be 214 m and 603 m respectively. Land use and land cover changes of three decades from 1991 to 2021 have been interpreted by using remotes sensing and GIS techniques. ArcGIS software (Arc map 10.2), SOI topographic map, Cartosat-1 DEM and satellite data of Landsat 5 and Landsat 8 have been used for interpretation of eleven classes. The study shows an increase in cultivated land, settlement, waterbody, open forest, plantation and mining due to urbanization because of increasing demands of food, shelter and water while a decrease in dense forest, river, open scrub, wasteland and uncultivated land has also been marked due to destruction of aforementioned by anthropogenic activities such as industrialization resulting in environmental degradation that leads to air, soil and water pollution.

Glacier area change (1993-2019) and its relationship to debris cover, proglacial lakes, and morphological parameters in the Chandra-Bhaga Basin, Western Himalaya, India

Glacier inventories serve as critical baseline data for understanding the impacts of climate change on glaciers.The present study maps the outlines of glaciers in the Chandra-Bhaga Basin(western Himalaya)for the years 1993,2000,2010,and 2019 using Landsat Thematic Mapper(TM),Enhanced Thematic Mapper(ETM),and Operational Land Imager(OLI)datasets.A total of 251 glaciers,each having an area above 0.5 km^(2),were identified,which include 216 clean-ice and 35 debris-covered glaciers.Area changes are estimated for three periods:1993-2000,2000-2010,and 2010-2019.The total glacierized area was 996±62 km^(2) in 1993,which decreased to 973±70 km^(2) in 2019.The mean rate of glacier area loss was higher in the recent decade(2010-2019),at 0.036 km^(2),compared to previous decades(0.029 km^(2) in 2000-2010 and 0.025 km^(2) in 1993-2000).Supraglacial debris cover changes are also mapped over the period of 1993 and 2019.It is found that the supraglacial debris cover increased by 14.12±2.54 km^(2)(15.2%)during 1993-2019.Extensive field surveys on Chhota Shigri,Panchi II,Patsio,Hamtah,Mulkila,and Yoche Lungpa glaciers were carried out to validate the glacier outlines and supraglacial debris cover estimated using satellite datasets.Controls of various morphological parameters on retreat were also analyzed.It is observed that small,clean ice,south oriented glaciers,and glaciers with proglacial lakes are losing area at faster rates than other glaciers in the basin.

Land use and cover change and influencing factor analysis in the Shiyang River Basin,China

Land use and cover change(LUCC)is the most direct manifestation of the interaction between anthropological activities and the natural environment on Earth's surface,with significant impacts on the environment and social economy.Rapid economic development and climate change have resulted in significant changes in land use and cover.The Shiyang River Basin,located in the eastern part of the Hexi Corridor in China,has undergone significant climate change and LUCC over the past few decades.In this study,we used the random forest classification to obtain the land use and cover datasets of the Shiyang River Basin in 1991,1995,2000,2005,2010,2015,and 2020 based on Landsat images.We validated the land use and cover data in 2015 from the random forest classification results(this study),the high-resolution dataset of annual global land cover from 2000 to 2015(AGLC-2000-2015),the global 30 m land cover classification with a fine classification system(GLC_FCS30),and the first Landsat-derived annual China Land Cover Dataset(CLCD)against ground-truth classification results to evaluate the accuracy of the classification results in this study.Furthermore,we explored and compared the spatiotemporal patterns of LUCC in the upper,middle,and lower reaches of the Shiyang River Basin over the past 30 years,and employed the random forest importance ranking method to analyze the influencing factors of LUCC based on natural(evapotranspiration,precipitation,temperature,and surface soil moisture)and anthropogenic(nighttime light,gross domestic product(GDP),and population)factors.The results indicated that the random forest classification results for land use and cover in the Shiyang River Basin in 2015 outperformed the AGLC-2000-2015,GLC_FCS30,and CLCD datasets in both overall and partial validations.Moreover,the classification results in this study exhibited a high level of agreement with the ground truth features.From 1991 to 2020,the area of bare land exhibited a decreasing trend,with changes primarily occurring in the middle and lower reaches of the basin.The area of grassland initially decreased and then increased,with changes occurring mainly in the upper and middle reaches of the basin.In contrast,the area of cropland initially increased and then decreased,with changes occurring in the middle and lower reaches.The LUCC was influenced by both natural and anthropogenic factors.Climatic factors and population contributed significantly to LUCC,and the importance values of evapotranspiration,precipitation,temperature,and population were 22.12%,32.41%,21.89%,and 19.65%,respectively.Moreover,policy interventions also played an important role.Land use and cover in the Shiyang River Basin exhibited fluctuating changes over the past 30 years,with the ecological environment improving in the last 10 years.This suggests that governance efforts in the study area have had some effects,and the government can continue to move in this direction in the future.The findings can provide crucial insights for related research and regional sustainable development in the Shiyang River Basin and other similar arid and semi-arid areas.

Predictive value of red blood cell distribution width and hematocrit for short-term outcomes and prognosis in colorectal cancer patients undergoing radical surgery

BACKGROUND Previous studies have reported that low hematocrit levels indicate poor survival in patients with ovarian cancer and cervical cancer,the prognostic value of hematocrit for colorectal cancer(CRC)patients has not been determined.The prognostic value of red blood cell distribution width(RDW)for CRC patients was controversial.AIM To investigate the impact of RDW and hematocrit on the short-term outcomes and long-term prognosis of CRC patients who underwent radical surgery.METHODS Patients who were diagnosed with CRC and underwent radical CRC resection between January 2011 and January 2020 at a single clinical center were included.The short-term outcomes,overall survival(OS)and disease-free survival(DFS)were compared among the different groups.Cox analysis was also conducted to identify independent risk factors for OS and DFS.RESULTS There were 4258 CRC patients who underwent radical surgery included in our study.A total of 1573 patients were in the lower RDW group and 2685 patients were in the higher RDW group.There were 2166 and 2092 patients in the higher hematocrit group and lower hematocrit group,respectively.Patients in the higher RDW group had more intraoperative blood loss(P<0.01)and more overall complications(P<0.01)than did those in the lower RDW group.Similarly,patients in the lower hematocrit group had more intraoperative blood loss(P=0.012),longer hospital stay(P=0.016)and overall complications(P<0.01)than did those in the higher hematocrit group.The higher RDW group had a worse OS and DFS than did the lower RDW group for tumor node metastasis(TNM)stage I(OS,P<0.05;DFS,P=0.001)and stage II(OS,P=0.004;DFS,P=0.01)than the lower RDW group;the lower hematocrit group had worse OS and DFS for TNM stage II(OS,P<0.05;DFS,P=0.001)and stage III(OS,P=0.001;DFS,P=0.001)than did the higher hematocrit group.Preoperative hematocrit was an independent risk factor for OS[P=0.017,hazard ratio(HR)=1.256,95%confidence interval(CI):1.041-1.515]and DFS(P=0.035,HR=1.194,95%CI:1.013-1.408).CONCLUSION A higher preoperative RDW and lower hematocrit were associated with more postoperative complications.However,only hematocrit was an independent risk factor for OS and DFS in CRC patients who underwent radical surgery,while RDW was not.

Land Use and Land Cover Dynamics in the Eseka Alluvial Gold Mining District, Centre Region, Cameroon

Local populations in Cameroon thrive on forest resources and the flow of ecosystem services they provide are pivotal in sustaining national economy, improving people’s lives, safeguarding biodiversity, and mitigating the impacts of environmental changes. The exploitation of these resources invariably leads to deforestation and forest degradation. This study was designed to evaluate land use land cover change (LULCC) in the Eseka alluvial gold mining district with the aid of Landsat images. In the investigation of forest cover change, four Landsat satellite images for (1990, 2002, 2015 and 2022) were used. Ground-truthing also helped to identify the activities carried out by the local population and to determine agents, drivers and pressures of land use and land cover change. Four main land cover classes namely: forest, agricultural land, settlement/mining camps and water bodies were selected. Between 1990 and 2022, the proportion of forest decreased from 98% to 34% while those of agricultural land and settlement/mining camps increased from 2% to 60% and 0.54% to 6% respectively. Analysis showed ongoing deforestation with forest cover loss of ~98,263 ha in 32 years giving a cover change percentage of 63.94%. Kappa coefficient for the study period ranged from 0.92 to 0.99. Forest cover loss could be attributed to farming activities, wood extraction and alluvial gold mining activities. Economic motives notably the need to increase household income from a frequent demand for farm and wood products in neighbouring towns and the quest for gold were the main drivers of these activities. Hence, this study assesses the impact of human activities from the mining sector on the forest ecosystem in a bid to inform mitigation policies.

Characteristics of the microbial communities regulate soil multi-functionality under different cover crop amendments in Ultisol

The use of cover crops is a promising strategy for influencing the soil microbial consortium,which is essential for the delivery of multiple soil functions(i.e.,soil multifunctionality).Nonetheless,relatively little is known about the role of the soil microbial consortium in mediating soil multifunctionality under different cover crop amendments in dryland Ultisols.Here,we assessed the multifunctionality of soils subjected to four cover crop amendments(control,non-amended treatment;RD,radish monoculture;HV,hairy vetch monoculture;and RDHV,radish-hairy vetch mixture),and we investigated the contributions of soil microbial richness,network complexity,and ecological clusters to soil multifunctionality.Our results demonstrated that cover crops whose chemical composition differed from that of the main plant crop promoted higher multifunctionality,and the radish-hairy vetch mixture rendered the highest enhancement.We obtained evidence that changes in soil microbial richness and network complexity triggered by the cover crops were associated with higher soil multifunctionality.Specifically,specialized microbes in a key ecological cluster(ecological cluster 2)of the soil microbial network were particularly important for maintaining soil multifunctionality.Our results highlight the importance of cover crop-induced variations in functionally important taxa for promoting the soil multifunctionality of dryland Ultisols.

Short-term efficacy of microwave ablation in the treatment of liver cancer and its effect on immune function

BACKGROUND Hepatectomy is the first choice for treating liver cancer.However,inflammatory factors,released in response to pain stimulation,may suppress perioperative immune function and affect the prognosis of patients undergoing hepatectomies.AIM To determine the short-term efficacy of microwave ablation in the treatment of liver cancer and its effect on immune function.METHODS Clinical data from patients with liver cancer admitted to Suzhou Ninth People’s Hospital from January 2020 to December 2023 were retrospectively analyzed.Thirty-five patients underwent laparoscopic hepatectomy for liver cancer(liver cancer resection group)and 35 patients underwent medical image-guided microwave ablation(liver cancer ablation group).The short-term efficacy,complications,liver function,and immune function indices before and after treatment were compared between the two groups.RESULTS One month after treatment,19 patients experienced complete remission(CR),8 patients experienced partial remission(PR),6 patients experienced stable disease(SD),and 2 patients experienced disease progression(PD)in the liver cancer resection group.In the liver cancer ablation group,21 patients experienced CR,9 patients experienced PR,3 patients experienced SD,and 2 patients experienced PD.No significant differences in efficacy and complications were detected between the liver cancer ablation and liver cancer resection groups(P>0.05).After treatment,total bilirubin(41.24±7.35 vs 49.18±8.64μmol/L,P<0.001),alanine aminotransferase(30.85±6.23 vs 42.32±7.56 U/L,P<0.001),CD4+(43.95±5.72 vs 35.27±5.56,P<0.001),CD8+(20.38±3.91 vs 22.75±4.62,P<0.001),and CD4+/CD8+(2.16±0.39 vs 1.55±0.32,P<0.001)were significantly different between the liver cancer ablation and liver cancer resection groups.CONCLUSION The short-term efficacy and safety of microwave ablation and laparoscopic surgery for the treatment of liver cancer are similar,but liver function recovers quickly after microwave ablation,and microwave ablation may enhance immune function.

Modelling the water diversion of a sustainable cover system under humid climates

Extreme rainfall significantly threatens the safety of the landfill cover system,especially under humid climates.This study aims to provide design recommendations for a sustainable landfill cover system consisting of a low-permeability soil layer underlying a two-layer capillary barrier for humid climates.First,the numerical back-analysis was conducted for verification against a series of flume model tests.Then,a parametric study was performed to investigate the effects of inclination angle,particle size and layer thickness on the lateral diversion length(DL)of the three-layer cover system under the 100-year return period rainfall of humid climates.The results show that the water lateral DL of the cover system can be greatly enhanced by increasing the inclination angle from 3°to 18°.Moreover,the bottom layer of the cover system with a coarser d10 was more susceptible to the impact of the heavy rainfall,while this can be alleviated by increasing the thickness of the bottom layer.A dimensionless number,defined as the ratio of thickness and d_(10) of the bottom layer,is proposed for designing lateral diversion of the three-layer cover system under humid climates.To preserve the maximum DL,it is suggested that the proposed dimensionless number should be larger than 95 and 110 for the design of rainfall events with 50-year and 100-year return periods for humid climates,respectively.

Near-Surface Soil Chemical Properties as Affected by Cover Crops Over Time in the Lower Mississippi River Valley

Typical row-crop agricultural practices can potentially be harmful to soil health and future sustainability. The use of cover crops (CC) as a mechanism to improve soil health on a wide scale remains underutilized. Soil health remains a major concern for the sustainability of agricultural productivity, therefore, research into CC implementation as a mean to preserve or improve soil health is warranted. The objective of this study was to evaluate the effects of CC on the soils in the eastern Arkansas portion of the Lower Mississippi River Valley (LMRV) over time for various chemical soil parameters, including pH, soil organic matter (SOM), soil elemental contents (i.e., P, K, Ca, Mg, S, Na, Fe, Mn, Zn, Cu, and B), soil respiration, and a generalized soil health score index. Soil pH decreased over time under both CC and no-cover-crop (NCC) treatments, by −0.3 and −0.2, respectively. Soil OM decreased over time under NCC by −0.1%, but did not differ between CC treatments. Soil N availability decreased over time under NCC (−22.6 kg·ha−1), but did not change over time under CC. Soil respiration decreased over time under both CC and NCC, by −76.1 mg·L−1 and −77.3 mg·L−1, respectively, though there was no effect of CC treatment. The Haney soil health score index decreased under CC (−7.0) and NCC (−6.8) without an effect from CC treatment. Results of the study place emphasis on the temporal nature of soil health as influenced by cover crops and their potential to improve soil health.

Adaptive Successive POI Recommendation via Trajectory Sequences Processing and Long Short-Term Preference Learning

Point-of-interest(POI)recommendations in location-based social networks(LBSNs)have developed rapidly by incorporating feature information and deep learning methods.However,most studies have failed to accurately reflect different users’preferences,in particular,the short-term preferences of inactive users.To better learn user preferences,in this study,we propose a long-short-term-preference-based adaptive successive POI recommendation(LSTP-ASR)method by combining trajectory sequence processing,long short-term preference learning,and spatiotemporal context.First,the check-in trajectory sequences are adaptively divided into recent and historical sequences according to a dynamic time window.Subsequently,an adaptive filling strategy is used to expand the recent check-in sequences of users with inactive check-in behavior using those of similar active users.We further propose an adaptive learning model to accurately extract long short-term preferences of users to establish an efficient successive POI recommendation system.A spatiotemporal-context-based recurrent neural network and temporal-context-based long short-term memory network are used to model the users’recent and historical checkin trajectory sequences,respectively.Extensive experiments on the Foursquare and Gowalla datasets reveal that the proposed method outperforms several other baseline methods in terms of three evaluation metrics.More specifically,LSTP-ASR outperforms the previously best baseline method(RTPM)with a 17.15%and 20.62%average improvement on the Foursquare and Gowalla datasets in terms of the Fβmetric,respectively.