An updated inventory of marine opisthobranch(Mollusca,Gastropoda)from the territorial waters of the Republic of Mauritius

Island ecosystems support diverse aquatic invertebrate communities comprising endemic taxa.Documentation of existing species is important for conservation.In this study,a checklist of marine opisthobranch from the Republic of Mauritius is presented.A combination of benthic surveys(50 m×5 m in triplicates),rover diving techniques and photo documentation were used over two years(2018–2020)within 35 sheltered and unsheltered lagoons.Morphological and molecular analysis were used for identification.Species composition within sheltered and unsheltered areas in Mauritius was estimated using the Bray-Curtis similarity.The checklist featured 117 species belonging to 61 genera and 28families,of which 13 are new records.The findings increased the knowledge of opisthobranch diversity from the Mauritius by 15.4%.Among the listed species,the distribution range of Cyerce nigra,Actinocyclus papillatus,and Phyllidia picta extended from the Western Pacific to the South Western Indian Ocean.Molecular analysis of the undescribed Gymnodoris sp.showed it resembled Gymnodoris sp.from Hawaii and were different by a genetic distance value of 10.6%.The species richness and evenness were higher within the sheltered regions of Mauritius which harboured the food resource of opisthobranch.These areas as compared to unsheltered regions were heavily populated,suggesting the probable influence of wave actions on opisthobranch diversity and abundance.The order Nudibranchia was reported as most speciose,with 86 species.The Sacoglossa and Nudibranchia were observed only on macroalgae and sponges respectively.High abundance was also recorded on shipwrecks which are the most common form of artificial reefs.With the inclusion of observations from previous studies,201species belonging to 94 genera and 36 families are now known from the Mauritius.

Intelligent Decision-Making in Warehouse Management: How AI Automation Improves Inventory Tracking, Order Fulfillment, and Logistics Efficiency Compared to Drone Technology

This paper analyzes how artificial intelligence (AI) automation can improve warehouse management compared to emerging technologies like drone usage. Specifically, we evaluate AI’s impact on crucial warehouse functions—inventory tracking, order fulfillment, and logistics efficiency. Our findings indicate AI automation enables real-time inventory visibility, optimized picking routes, and dynamic delivery scheduling, which drones cannot match. AI better leverages data insights for intelligent decision-making across warehouse operations, supporting improved productivity and lower operating costs.

A Note on an Order Level Inventory Model with Varying Two-Phased Demand and Time-Proportional Deterioration

The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. The two-phased demand function states the constant function for a certain period and the quadratic function of time for the rest part of the cycle time. No shortages as well as partial backlogging are allowed to occur. The mathematical expressions are derived for determining the optimal cycle time, order quantity and total cost function. An easy-to-use working procedure is provided to calculate the above quantities. A couple of numerical examples are cited to explain the theoretical results and sensitivity analysis of some selected examples is carried out.

An open-accessed inventory of landslides triggered by the M_(S)6.8 Luding earthquake,China on September 5,2022

This study constructs a preliminary inventory of landslides triggered by the M_(S) 6.8 Luding earthquake based on field investigation and human-computer interaction visual interpretation on optical satellite images.The results show that this earthquake triggered at least 5007 landslides,with a total landslide area of 17.36 km^(2),of which the smallest landslide area is 65 m^(2)and the largest landslide area reaches 120747 m^(2),with an average landslide area of about 3500 m^(2).The obtained landslides are concentrated in the IX intensity zone and the northeast side of the seismogenic fault,and the area density and point density of landslides are 13.8%,and 35.73 km^(-2) peaks with 2 km as the search radius.It should be noted that the number of landslides obtained in this paper will be lower than the actual situation because some areas are covered by clouds and there are no available post-earthquake remote sensing images.Based on the available post-earthquake remote sensing images,the number of landslides triggered by this earthquake is roughly estimated to be up to 10000.This study can be used to support further research on the distribution pattern and risk evaluation of the coseismic landslides in the region,and the prevention and control of landslide hazards in the seismic area.

Spatial distribution and inventory of natural gas hydrate in the Qiongdongnan Basin,northern South China Sea

Natural gas hydrate is a potential clean energy source and is related to submarine geohazard,climate change,and global carbon cycle.Multidisciplinary investigations have revealed the occurrence of hydrate in the Qiongdongnan Basin,northern South China Sea.However,the spatial distribution,controlling factors,and favorable areas are not well defined.Here we use the available high-resolution seismic lines,well logging,and heat flow data to explore the issues by calculating the thickness of gas hydrate stability zone(GHSZ)and estimating the inventory.Results show that the GHSZ thickness ranges between mostly~200 and 400 m at water depths>500 m.The gas hydrate inventory is~6.5×109-t carbon over an area of~6×104 km2.Three areas including the lower uplift to the south of the Lingshui sub-basin,the Songnan and Baodao sub-basins,and the Changchang sub-basin have a thick GHSZ of~250-310 m,250-330 m,and 350-400 m,respectively,where water depths are~1000-1600 m,1000-2000 m,and2400-3000 m,respectively.In these deep waters,bottom water temperatures vary slightly from~4 to 2℃.However,heat flow increases significantly with water depth and reaches the highest value of~80-100 mW/m2 in the deepest water area of Changchang sub-basin.High heat flow tends to reduce GHSZ thickness,but the thickest GHSZ still occurs in the Changchang sub-basin,highlighting the role of water depth in controlling GHSZ.The lower uplift to the south of the Lingshui sub-basin has high deposition rate(~270-830 m/Ma in 1.8-0 Ma);the thick Cenozoic sediment,rich biogenic and thermogenic gas supplies,and excellent transport systems(faults,diapirs,and gas chimneys)enables it a promising area of hydrate accumulation,from which hydrate-related bottom simulating reflectors,gas chimneys,and active cold seeps were widely revealed.

Inventory of Host Plants and Parasitoids of the Fall Armyworm (FAW), Spodoptera frugiperda (JE Smith), in the Southern Agricultural Zone of Niger

The fall armyworm, Spodoptera frugiperda (JE Smith), is a polyphagous pest reported in sub-Saharan Africa since 2016 and has expanded rapidly in almost Africa. In Niger, Spodoptera frugiperda (JE Smith) is considered like a major pest of maize, to which it causes significant damage, in a context where proven control methods against this moth remain almost non-existent. The objective of the present study was to determine the economic importance of FAW through the damage caused to the different host plants and to identify the parasitoids of this caterpillar. The study was conducted in the southern agricultural zone of Niger, specifically in the regions of Dosso, Maradi, Tahoua and Zinder. FAW eggs and caterpillars were collected from six villages in each region and then incubated and reared in the entomology laboratory of INRAN in Maradi. The rate of infestation of the different crops by FAW was determined as well as the observation of the beneficiaries. The results obtained indicate the presence of FAW on millet with an attack rate varying from 45.7% to 68%, sorghum with 47.2% to 62.25% and sesame with 9.7%. This work also revealed an oophagous parasitoid, Telenomus remus with 138 ± 23 and larval parasitoids, Cotesia sp with 16 ± 1 maximum number of individuals emerged from the collected material. Also, it was identified the parasitoid Cotesia icipe with a rate of parasitism from 4.6% to 5.75%;the Charops ater whose rate of parasitism varies from 4.5% and 12.25% but for Chelonus insularis with 17.25% and Tachnidae with 53%. These very interesting results will constitute a basis for the development of biological control and a component of an agroecological management strategy of caterpillar.

Screening Tree Species for Carbon Storage Potential through Urban Tree Inventory in Planted Vegetation

Urban tree inventory is a great tool for gathering data that can be used by different end users. This study attempted to chart the species diversity in planted areas and measure their tree diameter at breast height to screen them for the carbon storage potential. A total of 2860 trees belonging to 36 species were recorded in the planted vegetation in parks and avenue plantation. The dominant species were Azadirachta indicia (25.5%), Conocarpus erectus (19.2%), Ficus spp. (15.5%), Tabebuia rosea (9.2%), Peitophorum pterocarpum (9.0%) and the remaining represents (21.6%) of the tree identified in this study. It was found that the highest contribution of carbon sequestration (CO2 equivalent) is dominated by the Ficus spp. (30.3%) with a total of 3399.3 tCO2eq, followed by Azadirachta indicia (25.4%) with a total of 2845.2 tCO2eq and Conocarpus erectus (20.4%) with a total of 2286 tCO2eq. The entire area has the capability to sequester around 11,213.3 tCO2eq and on average of 3.9 ± 0.1 tCO2eq. In accordance with the findings, it is imperative for the preservation of a sustainable environment to have vegetation that has the capacity to store carbon. The study suggests, there is potential to increase carbon sequestration in urban cities through plantation programs on existing and new land uses and along roads.

Inventory of the Thermo-Physiological Behavior of Fabrics—A Review

A comprehensive literature review was performed to create an inventory of thermal-physiological quantities for fabrics from different fiber materials, material blends, and fabric structures. The goal was to derive over-arching concepts that cannot be seen by the individual studies alone. Equations of best fits suggest non-linear changes for fabric thickness, thermal and water-vapor resistance with changes in material blend ratio. Air permeability decreases with increasing fabric density and fabric weight wherein the degree of decrease differs among fabric materials, blend ratio, and fabric structure. Water-vapor transmission rates strongly depend on fabric thickness, material, and blend, but marginally depend on fabric structure as long as the fabric and material thickness remain the same.

Methods of vendor managed inventory control in supply chain management

By inducing the typical inventory control problem - the bullwhip effect, this paper presents vendor managed inventory (VMI) control methods on the basis of traditional methods of inventory management methods, constructs a VMI mathematics model, and analyzes the influence of VMI on inventory cost and channel profit. Finally, a special case is studied to verify that VMI is an effective supply chain strategy that can not only increase channel profit of supplier and customer but also improve full channel coordination, thereby reducing the bullwhip effect.

Vendor managed inventory and bullwhip effect

This paper studies that the bullwhip effect of order releases and the amplifications of safety stock arise within the supply chain even when the demand model is ARIMA(0, 1, 1) and the forecast method used is a simple exponentially weighted moving average. It also examines a vendor managed inventory (VMI) program to determine how it can help alleviate such negative effects, and gives the theoretical proofs and numerical illustrations. The results show that the effects with VMI are better than the effect without VMI in demand forecasting and safety stock levels, etc.

Quantity-based shipment consolidation and stock replenishment policy with lead time in vendor-managed inventory system

In order to let the supplier make more reasonable supply decisions,an integrated continuous replenishment policy for the vendor-managed inventory system is presented,which considers the quantity-based shipment consolidation and stock replenishment with lead time.Then the system cost is analyzed and a mathematical model is built.Since the model is rather complex,the bounds of the optimal policy are first attained,then the problem is solved by a heuristic algorithm.Through experiments the relationship between the order lead time and the corresponding integrated policy is discussed,and the influence on the system cost is also analyzed.The results reveal that the lead time's influence on the system is more serious with the increase of the order lead time,the integrated policy with the order lead time is more reasonable and the optimal policy can minimize the total system cost.Finally,the parameter sensitivity of the model is analyzed.

Comparative research on three-echelon and two-echelon medicine inventory model with positive lead-time

According to the principle of minimizing total cost, the three-echelon optimized medical inventory model with stochastic lead-time and two-echelon optimized medicine inventory model with fixed lead-time are established. The relationship between lead-time and inventory cost is studied by Matlab software. It shows that the variety of lead-time has an important effect on medicine inventory systems. Numerical simulation and sensitivity analysis of two models are presented by Lingo software. Based on analysis, it is concluded that the two-echelon model with lead-time results in inventory cost savings, and keeps the quality of care as reflected in service levels when compared with the three-echelon network structure.

Educational Leader's Personality Style Inventory in K12 and Higher Education Levels

The research introduced the application of Personality Style Inventory on two levels of educational leaders: K12 level and higher education level, including both American and Chinese school leaders. Through comparing and contrasting of personality types at different levels, it is revealed that educational leaders in different levels have different personal characteristics and the researcher tries to find out how the Personality Style Inventory can improve the leadership practice.

Application of Inventory Theory in Service Stations

A service station plays an important role in the petroleum product distribution terminal. With the increase in petroleum consumption in China, the inventory theory should be applied in the stock control of service stations. In this paper the inventory theory including its background and characteristics is introduced. At the same time, the application of the theory in some trades today, especially in petroleum trade, is analyzed. Then (s, S) stochastic model is advanced, which is established according to the principle of operational research and, based on this model, a sample is given, which discusses the details of application in the stock control of service stations. The sample is simplified but implies the validity of the model in optimizing the storage of petroleum products in the market.

Co-seismic Landslide Inventory and Susceptibility Mapping in the 2008 Wenchuan Earthquake Disaster Area,China

The Ms 8.0 May 12,2008 Wenchuan earthquake triggered tens of thousands of landslides.The widespread landslides have caused serious casualties and property losses,and posed a great threat to post-earthquake reconstruction.A spatial database,inventoried 43,842 landslides with a total area of 632 km 2,was developed by interpretation of multi-resolution remote sensing images.The landslides can be classified into three categories:swallow,disrupted slides and falls;deep-seated slides and falls,and rock avalanches.The correlation between landslides distribution and the influencing parameters including distance from co-seismic fault,lithology,slope gradient,elevation,peak ground acceleration(PGA) and distance from drainage were analyzed.The distance from co-seismic fault was the most significant parameter followed by slope gradient and PGA was the least significant one.A logistic regression model combined with bivariate statistical analysis(BSA) was adopted for landslide susceptibility mapping.The study area was classified into five categories of landslide susceptibility:very low,low,medium,high and very high.92.0% of the study area belongs to low and very low categories with corresponding 9.0% of the total inventoried landslides.Medium susceptible zones make up 4.2% of the area with 17.7% of the total landslides.The rest of the area was classified into high and very high categories,which makes up 3.9% of the area with corresponding 73.3% of the total landslides.Although the susceptibility map can reveal the likelihood of future landslides and debris flows,and it is helpful for the rebuilding process and future zoning issues.

The national forest inventory in China:history-results-international context

Background： National forest resource assessments Inventories （NFI＇s）, constitute an important nationa and monitoring, commonly known as National Forest information infrastructure in many countries. Methods： This study presents details about developments of the NFI in China, including sampling and plot design and the uses of alternative data sources, and specifically · reviews the evolution of the national forest inventory in China through the 20th and 21st centuries, with some reference to Europe and the US; · highlights the emergence of some common international themes： consistency of measurement; sampling designs; implementation of improved technology; expansion of the variables monitored more efficient scientific transparency;· presents an example of how China＇s expanding NFI exemplifies these global trends. Results： Main results and important changes in China＇s NFI are documented, both to support continued trend analysis and to provide data users with historical perspective. Conclusions： New technologies and data needs ensure that the Chinese NFI, like the national inventories in other countries, will continue to evolve. Within the context of historical change and current conditions, likely directions for this evolution are suggested.

Landslide inventory and susceptibility modelling using geospatial tools,in Hunza-Nagar valley,northern Pakistan

A comprehensive landslide inventory and susceptibility maps are prerequisite for developing and implementing landslide mitigation strategies. Landslide susceptibility maps for the landslides prone regions in northern Pakistan are rarely available. The Hunza-Nagar valley in northern Pakistan is known for its frequent and devastating landslides. In this paper, we have developed a landslide inventory map for Hunza-Nagar valley by using the visual interpretation of the SPOT-5 satellite imagery and mapped a total of 172 landslides. The landslide inventory was subsequently divided into modelling and validation data sets. For the development of landslide susceptibility map seven discrete landslide causative factors were correlated with the landslide inventory map using weight of evidence and frequency ratio statistical models. Four different models of conditional independence were used for the selection of landslide causative factors. The produced landslides susceptibility maps were validated by the success rate and area under curves criteria. The prediction power of the models was also validated with the prediction rate curve. The validation results shows that the success rate curves of the weight of evidence and the frequency models are 82% and 79%, respectively. The prediction accuracy results obtained from this study are 84% for weight of evidence model and 80% for the frequency ratio model. Finally, the landslide susceptibility index maps were classified into five different varying susceptibility zones. The validation and prediction result indicates that the weight of evidence and frequency ratio model are reliable to produce an accurate landslide susceptibility map, which may be helpful for landslides management strategies.

Landslide inventory and susceptibility assessment using multiple statistical approaches along the Karakoram highway,northern Pakistan

China-Pakistan Economic Corridor(CPEC)is a framework of regional connectivity,which will not only benefit China and Pakistan but will have positive impact on Iran,Afghanistan,India,Central Asian Republic,and the region.The surrounding area in CPEC is prone to frequent disruption by geological hazards mainly landslides in northern Pakistan.Comprehensive landslide inventory and susceptibility assessment are rarely available to utilize for landslide mitigation strategies.This study aims to utilize the high-resolution satellite images to develop a comprehensive landslide inventory and subsequently develop landslide susceptibility maps using multiple techniques.The very high-resolution(VHR)satellite images are utilized to develop a landslide inventory using the visual image classification techniques,historic records and field observations.A total of 1632 landslides are mapped in the area.Four statistical models i.e.,frequency ratio,artificial neural network,weights of evidence and logistic regression were used for landslide susceptibility modeling by comparing the landslide inventory with the topographic parameters,geological features,drainage and road network.The developed landslides susceptibility maps were verified using the area under curve(AUC)method.The prediction power of the model was assessed by the prediction rate curve.The success rate curves show 93%,92.8%,92.7%and 87.4%accuracy of susceptibility maps for frequency ratio,artificial neural network,weights of evidence and logistic regression,respectively.The developed landslide inventory and susceptibility maps can be used for land use planning and landslide mitigation strategies.

Mapping forest age using National Forest Inventory,airborne laser scanning,and Sentinel-2 data

Background:The age of forest stands is critical information for forest management and conservation,for example for growth modelling,timing of management activities and harvesting,or decisions about protection areas.However,area-wide information about forest stand age often does not exist.In this study,we developed regression models for large-scale area-wide prediction of age in Norwegian forests.For model development we used more than 4800 plots of the Norwegian National Forest Inventory(NFI)distributed over Norway between latitudes 58°and 65°N in an 18.2 Mha study area.Predictor variables were based on airborne laser scanning(ALS),Sentinel-2,and existing public map data.We performed model validation on an independent data set consisting of 63 spruce stands with known age.Results:The best modelling strategy was to fit independent linear regression models to each observed site index(SI)level and using a SI prediction map in the application of the models.The most important predictor variable was an upper percentile of the ALS heights,and root mean squared errors(RMSEs)ranged between 3 and 31 years(6%to 26%)for SI-specific models,and 21 years(25%)on average.Mean deviance(MD)ranged between^(−1) and 3 years.The models improved with increasing SI and the RMSEs were largest for low SI stands older than 100 years.Using a mapped SI,which is required for practical applications,RMSE and MD on plot level ranged from 19 to 56 years(29%to 53%),and 5 to 37 years(5%to 31%),respectively.For the validation stands,the RMSE and MD were 12(22%)and 2 years(3%),respectively.Conclusions:Tree height estimated from airborne laser scanning and predicted site index were the most important variables in the models describing age.Overall,we obtained good results,especially for stands with high SI.The models could be considered for practical applications,although we see considerable potential for improvements if better SI maps were available.

Inventory of Atmospheric Pollutant Emissions from Burning of Crop Residues in China Based on Satellite-retrieved Farmland Data

The burning of crop residues emits large quantities of atmospheric aerosols.Published studies have developed inventories of emissions from crop residue burning based on statistical data.In contrast,this study used satellite-retrieved land-cover data(1 km×1 km)as activity data to compile an inventory of atmospheric pollutants emitted from the burning of crop residues in China in 2015.The emissions of PM10,PM2.5,VOCs,NOx,SO2,CO,and NH3 from burning crop straw on nonirrigated farmland in China in 2015 were 610.5,598.4,584.4,230.6,35.4,3329.3,and 36.1 Gg(1 Gg=109 g),respectively;the corresponding emissions from burning paddy rice residues were 234.1,229.7,342.3,57.5,57.5,1122.1,and 21.5 Gg,respectively.The emissions from crop residue burning showed large spatial and temporal variations.The emissions of particulate matter and gaseous pollutants from crop residue burning in nonirrigated farmland were highest in east China,particularly in Shandong,Henan,Anhui,and Sichuan provinces.Emissions from burning paddy rice residue were highest in east and central China,with particularly high levels in Shandong,Jiangsu,Zhejiang,and Hunan provinces.The monthly variations in atmospheric pollutant emissions were similar among different regions,with the highest levels observed in October in north,northeast,northwest,east,and southwest China and in June and July in central and south China.The developed inventory of emissions from crop residue burning is expected to help improve air quality models by providing high-resolution spatial and temporal data.