Multi-criteria Scoring Research Articles

Strategic Site Selection for Bio-LNG Plant in Indonesia: A Multi-Criteria Scoring Method Approach

In Indonesia, the energy sector is still predominantly reliant on fossil fuels, with renewable energy, including liquefied biomethane (Bio-LNG), playing a limited role. Nonetheless, Indonesia has significant potential for Bio-LNG development due to its abundant organic waste resources such as Palm Oil Mill Effluent (POME) from palm oil mills. Having approximately 891 Palm Oil Mills in Indonesia and being spread mostly in Sumatra, this study aims to select a strategic location for a Bio-LNG plant that can enhance logistical efficiency and economic viability for the plant. This study uses Multi-Criteria Decision Making (MCDM) methodologies to assess potential sites based on key criteria: Land Availability, Distance to Source of Feedstock, Distance to Customer Locations, Jetty Availability, and Future Business Developments. This study has narrowed down into focusing on provinces with substantial raw material potential, Riau Province, particularly Dumai City and its surroundings, which emerges as a pivotal hub. Secondary data are gathered to conduct a systematic scoring process evaluates and integrates each criterion to generate a comprehensive ranking of potential sites. The selected site for the Bio-LNG plant is Location 1, at the coordinates of 1.662056, 101.707092, Pelintung, Medang Kampai Subdistrict, Dumai City, Riau. Its strategic positioning, proximity to key transportation routes, availability of abundant feedstock, and access to necessary infrastructure make it an ideal choice. This study aims to advance Bio-LNG infrastructure in Indonesia, promoting cleaner energy solutions, and enhanced supply chain efficiency.

Assessing subsidy integration in the 40 years of agricultural planning in the Maldives

87% of agricultural subsidies are harmful to the environment and human health while contributing little to food security. The first step to addressing harmful subsidies is to identify and trace them in policies. Small Island Developing States (SIDS), such as the Maldives, are the most vulnerable to environmental degradation caused by activities they contribute minimally. In the case of subsidies, the relative contribution to the environmental degradation by islands and the relative impacts of subsidies on islands are not studied, leaving a void in the global knowledge pool. This paper addresses the first step of this gap by identifying and assessing the historical trends of subsidy integration in Maldivian agricultural policy by analyzing their temporal distribution patterns and the quality of subsidy inclusion in national plans in the past four decades. The framework adopted for this study is a multi-criteria scoring protocol and a classification of 15 subsidy types to deliver a quantitative overview of the status and trends in subsidy in the agriculture sector of the Maldives. The results showed that although the scale of agriculture in the country is limited, subsidies have consistently been an integral part of agricultural planning since 1985, with agricultural inputs being one of the most frequently and highly subsidized over the years. Twelve different subsidy types were traced in the ten assessed national plans, and eleven subsidy types were identified in the plan from 2019 to 2023. These results serve as a baseline for the understanding of subsidies in the Maldives by providing a narrative of an island state for the global overview of subsidies and for comparative studies thereof.

Abstract Mo009: Systems genetics approach identifies the genetic basis underlying anthracycline-induced cardiotoxicity

Background: Anthracycline-induced cardiotoxicity (ACT) occurs in 57% of treated cancer patients. Effects of genetic variations to individual susceptibility to ACT is emerging. However, diverse lifestyle and environmental factors combined with small sample sizes in human cohorts remain as limitations to effectively clarify the genetic susceptibility to ACT. This study employed a murine genetic reference population (GRP) of BXD mice derived from crosses between DBA/2J and C57BL/6J strains for mapping of quantitative trait loci (QTLs) associated with doxorubicin (DOX)-induced traits using systems genetics methods. Methods: To model the variability in ACT to DOX, 56 BXD strains (N≥3 mice/sex, 3-4 month-old) were injected intraperitonially once with DOX (20 mg/kg). Survival and body weight (BW) were monitored daily for 10 Days (D). Echocardiography was performed before and on D5 after DOX. Genetic mapping was performed using WebQTL (www.genenetwork.org) and multi-criteria scoring was used for filtering candidate genes associated with DOX-induced traits. Results: Varied body weight loss, proportions and median survival rates were found among DOX-treated BXDs. Parental C57BL/6J strain had 100% survival, while 75% of DBA/2J mice survived on D10. Among BXDs tested, 47 strains had median survival of 6±1 D, with the lowest seen in BXD77 (4 D). Echocardiography revealed abnormal small heart and restrictive dysfunction in BXDs, resembling Grinch syndrome seen in ACT patients. A significant QTL (LRS = 17.11) at 86~94 Mb of Chromosome (Chr) 10 was identified (genome wide P < 0.05). Further filtering identified Gnptab , Slc25a3 , Uhrf1bp1l, and Chpt1 as top candidate genes associated with the survival of DOX-treated BXDs. Mapping of QTLs associated with echocardiography values and weight loss are in a progress. Conclusions: Survival, BW loss, and echocardiography parameters significantly varied among DOX-treated BXDs suggesting an influence of genetic background on expression of those traits. Gnptab , Slc25a3, Uhrf1bp1l, and Chpt1 (Chr 10) are associated with DOX-induced survival traits in BXDs of GRP, suggesting that these genes are involved in modulating ACT severity in humans and require further functional and biological validation.

Mapping tidal restrictions to support blue carbon restoration

Blue carbon ecosystems (BCEs), encompassing mangroves, saltmarshes, and seagrasses, are vital ecosystems that deliver valuable services such as carbon sequestration, biodiversity support, and coastal protection. However, these ecosystems are threatened by various anthropogenic factors, including tidal restrictions like levees, barriers, and embankments. These structures alter the natural seawater flow, often converting coastal ecosystems into freshwater environments. Identifying tidal restrictions and assessing their suitability for tidal restoration in areas amenable for coastal management is a crucial first step to successfully restore BCEs and the associated ecosystem services they provide, i.e., managed realignment. This study presents a novel approach for detecting tidal restrictions in the state of Victoria, Australia, using high-resolution LiDAR data, geospatial analysis techniques, and a multi-criteria scoring system. Our model successfully identified 90 % of known tidal restrictions from an existing dataset, while also detecting an additional 118 potential tidal restrictions, representing a 35 % increase. The model performance analysis revealed trade-offs between precision, recall, and noise ratio when using different noise reduction thresholds, highlighting the importance of selecting an appropriate threshold based on project objectives. The multi-criteria scoring system, which considered factors such as proximity to BCEs and current land use, enabled the selection of tidal restrictions based on their hydrological suitability for restoration. The results of this study have significant implications for BCE restoration efforts not only in Victoria, but more broadly across Australia and globally, providing a systematic approach to identifying and targeting areas with the greatest potential for successful restoration projects. While the approach is low-cost and user-friendly, it is dependent on the availability of LiDAR data for the study area. This can make it accessible to researchers and practitioners worldwide, allowing for its adaptation and application in diverse regions to support global efforts in restoring BCEs through tidal restoration.

First Evidence of the Bioaccumulation and Trophic Transfer of Tire Additives and Their Transformation Products in an Estuarine Food Web.

The discovery of the significant lethal impacts of the tire additive transformation product N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine quinone (6PPD-Q) on coho salmon has garnered global attention. However, the bioaccumulation and trophic transfer of tire additives and their transformation products (TATPs) within food webs remain obscure. This study first characterized the levels and compositions of 15 TATPs in the Pearl River Estuary, estimated their bioaccumulation and trophic transfer potential in 21 estuarine species, and identified priority contaminants. Our observations indicated that TATPs were prevalent in the estuarine environment. Eight, six, seven, and 10 TATPs were first quantified in the shrimp, sea cucumber, snail, and fish samples, with total mean levels of 45, 56, 64, and 67 ng/g (wet weight), respectively. N,N'-Diphenyl-p-phenylenediamine (DPPD) and N,N'-bis(2-methylphenyl)-1,4-benzenediamine (DTPD) exhibited high bioaccumulation. Significant biodilution was only identified for benzothiazole, while DPPD and DTPD displayed biomagnification trends based on Monte Carlo simulations. The mechanisms of bioaccumulation and trophodynamics of TATPs could be explained by their chemical hydrophobicity, molecular mass, and metabolic rates. Based on a multicriteria scoring technique, DPPD, DTPD, and 6PPD-Q were characterized as priority contaminants. This work emphasizes the importance of biomonitoring, particularly for specific hydrophobic tire additives.

Simulation Performance of Temperature and Precipitation in the Yangtze River by Different Cumulus and Land Surface Schemes in RegCM4

To improve the simulation performance of the RegCM4 model in climate simulations over the Yangtze River Basin (YRB), it is essential to determine the optimal cumulus convection and land surface process schemes from the numerous physical parameterization options within RegCM4. In this study, we selected five cumulus convection schemes (Kuo, Grell, Emanuel, Tiedtke, and Kain–Fritsch) and three land surface process schemes (BATS, CLM3.5, and CLM4.5) to configure 72 mixed schemes. Four years of short-term simulations (1990–1993) with a horizontal resolution of 50 km were conducted using ERA-Interim as the initial and boundary conditions for the 72 schemes. The climate simulation performance of all schemes in the YRB was comprehensively evaluated using a multi-criteria scoring approach. The results indicate that among the selected cumulus convection schemes, the Kain–Fritsch scheme, applied to both ocean and land, demonstrates optimal performance in simulating precipitation over the YRB, with spatial correlation coefficients between simulated and observed annual precipitation around 0.3. Compared to the Community Land Models (CLM3.5 and CLM4.5), BATS exhibits superior capabilities in reproducing the temperature features of the region, with spatial correlation coefficients between simulated and observed values typically exceeding 0.99 and standard deviations within 1.25 °C. Under the optimal KF scheme, the simulated soil moisture in the YRB using CLMs is notably drier, ranging from −7.79 to −8.39 kg/m2, compared to that achieved with BATS. The findings provide a localized reference for the parameterization schemes of RegCM4 in the YRB.

Site Selection for Future Mobility Hubs in Melbourne: A Multicriteria Location-Allocation Analysis

Mobility hubs (MHs) are places offering access to various modes of transport along with enhanced facilities to provide integrated and seamless travel. This study proposes a method to find optimum locations for the planning and development of MHs using Greater Melbourne as a case. Our analysis focuses on 222 existing train stations. We identified 18 stations that meet our operational definition of a mobility hub – i.e., providing interchange facilities for trains, bus/tram, and shared mobility services. The remaining 204 stations were considered as potential candidates for future mobility hubs. These candidates were assessed using location-allocation analysis that optimizes their access for general public, students and commuters travelling by four different modes (car, bike, e-scooter and walking). The shortlisted stations were ranked using a multicriteria scoring system. The analysis resulted in 62 sites with high potential to develop as future mobility hubs.

Co-designing a multi-criteria approach to ranking hazards to and from Australia’s emerging offshore blue economy

A multi-sectoral assessment of risks can support the management and investment decisions necessary for emerging blue economy industries to succeed. Traditional risk assessment methods will be challenged when applied to the complex socio-ecological systems that characterise offshore environments, and when data available to support management are lacking. Therefore, there is a need for assessments that account for multiple sectors. Here we describe the development of an efficient method for an integrated hazard analysis that is a precursor to full risk assessments. Our approach combines diverse disciplinary expertise, expert elicitation and multi-criteria analysis to rank hazards, so it encompasses all types of hazards including human-caused, natural and technological. We demonstrate our approach for two sectors that are predicted to grow rapidly in Australia: offshore aquaculture and marine renewable energy. Experts ranked Climate Change as the hazard with the highest overall concern, but hazards including Altered Ecosystem Function, Biosecurity, Cumulative Effects, Structural Failure and Social Licence were also highly ranked. We show here how outputs from this approach (multi-criteria scores and ranks) could be used to identify hazards that; i) could be safely retired, ii) should be progressed to more quantitative risk assessments or iii) require ongoing information collection. The approach can encompass all types of hazards, which enables it to holistically consider priorities. The expert-based multi-criteria approach outlined here represents a pragmatic way to solve some of the challenges of applying risk assessments to emerging industries by using a method that can be applied across multiple blue economy sectors.

Conceptual Design of a Combined Brake-Accelerator Pedal for Limbs Disabled Driver Using a Hybrid Approach

This paper presents the conceptual design of a combined brake-accelerator pedal for limbs disabled drivers using a hybrid approach. A hybrid in which it consists of a combination of TRIZ for design generation, a Morphological Chart for design composition, and a Pugh Matrix for design selection. The aim is to generate and select the best concept design for a combined brake-accelerator pedal with special attention based on the needs of the disabled’s ergonomics. In this paper, the function analysis, cause, and effects analysis, TRIZ contradiction matrix, and 40 Inventive principles were applied in the solution generation stage. The outcomes of solutions proposed in TRIZ were then refined using a Morphological chart to deliberate the design composition of the combined brake-accelerator pedal. As a result, three innovative design concepts of combined brake-accelerator pedals were produced. Pugh Matrix was finally utilized to perform multi-criteria scoring based on the baseline to select the best ergonomics concept for combined brake-accelerator pedals for disabled drivers.

A robust multicriteria clustering methodology for portfolio decision analysis

We consider a portfolio decision problem in which a subset of projects is selected to form a portfolio by dealing with uncertain multiple criteria evaluations, decision makers’ preferences and real-world constraints. Over the last years, many methods have been developed with the aim of maximizing the sum of multicriteria scores of projects selected for the final portfolio. In this paper, unlike the existing literature, we propose a new robust multicriteria clustering methodology that enables to group the best ranked projects into a new kind of cluster (so-called optimal portfolio) that complies with the given constraints. With this aim, a new Integer Programming (IP) model as an extension of the K-medoids clustering technique is combined with the PROMETHEE method. Specifically, we first apply PROMETHEE for multicriteria evaluation of the individual projects and then the two main outputs of PROMETHEE, preference matrix and net flows, are used in the IP model to generate clusters of projects with the given resource constraints. Herein, to alleviate the problem without the influence of all K clusters on the final results, we focus on generating two clusters, with the selected projects in the best one forming the portfolio. In developing this model, we also introduce portfolio quality constraints to ensure the proper distribution of “good” evaluations among all considered criteria. We then enhance this combined model by embedding it into SMAA framework to consider the inherent uncertainties. As a large number of potentially optimal portfolios are obtained through the SMAA simulation, both project and portfolio-level robustness indices are computed in order to help decision makers to identify the most robust and stable portfolio. Our methodology is validated using the data from a bridge maintenance program.

Towards selecting the optimized external wall solution in Iran: Comparison between life cycle assessment (LCA), cost benefits, and thermal performance

External walls, as the main components of a building's envelope, directly affect the building's thermal and environmental performance due to their high carbon emissions, life cycle costs, and user comfort. As the buildings are responsible for one-third of global GHG emissions, choosing the most effective solutions for external walls is crucial to combat the environmental crisis. This paper aims to identify and assess conventional external walls in Iran. A multi-criteria scoring system is established to evaluate them regarding carbon emissions, cost benefits, and thermal performance (R-value). A selection criteria is defined, and a total of 45 external walls are identified and categorized into three wall types: solid, filled cavity, and partial cavity walls. Assessing environmental impact involves conducting a cradle-to-handover simplified life cycle assessment. Cost assessment is performed using construction costs, and thermal performance assessment is conducted based on thermal conductivity coefficient and thickness. Based on the results, the highest scores belong to partial cavity walls. Partial cavity walls perform better than simple and filled cavity walls, although the simple wall is Iran's most widely used wall solution. The manufacturing stage represents the more significant contribution to environmental impact in all cases, followed by transportation and construction. The environmental analysis indicates that the structural layer (53.7%), followed by external finishing (14%), and transportation (12.1%) are the three highest contributors, respectively. The results also stress the importance of transport protocols in the carbon emissions reduction of external walls by indicating the structural layer as a carbon hotspot.

​​Research Prioritization in Indian Livestock Sector: A Policy Appraisal

Background: Livestock makes multi-faceted contribution to socio-economic development of rural people. However, challenges exist in exploiting the opportunities offered by this sector. Focused research efforts will be a key factor in addressing these challenges. There is a need for a critical and objective evaluation of livestock research priorities at the regional, species and commodity-specific levels so as to ensure optimum use of scarce resources. This study was aimed to identify regional, species and commodity wise priorities for allocation of livestock research resources. Methods: The study used multi-criteria scoring model incorporating the multiple objectives for making choices. The objectives included were growth, equity, sustainability and participation in trade. Such scoring models are used to rank a long list of commodities, research alternatives and target domains. Result: The study identified regional, species and commodity priorities for allocation of livestock research resources. Significant tradeoffs in the priority rankings of states were revealed when equity and sustainability indicators were considered. Species-wise prioritization including all the criteria revealed that cattle and buffalo stake the highest claims on research resources. The study also revealed inter-regional variations in allocation of research resources based upon species.

Joint assessment of temporal segmentation, time unit and detection algorithms in syndromic surveillance

The choice of the aggregation that defines the temporal unit of epidemiological surveillance is part of the more theoretical framework of the modifiable temporal unit problem (MTUP). It has been demonstrated that this choice influences temporal cluster detection and may lead to false-positive results and poor estimation of regression model parameters. In syndromic surveillance (SyS), despite the choice of which temporal aggregation to use being crucial, it has not yet been addressed in the literature. In most SyS systems, this choice is driven by the frequency of the data collection and/or human resources available, although neither the temporal unit’s influence on the performance of anomaly detection algorithms nor on the efficiency of the SyS are known.The main objective of our study was to analyze the influence of the temporal aggregation unit on the performances of SyS detection algorithms used routinely, according to the characteristics of specific syndromes and outbreaks. Simulating daily time series of various syndromes, we tested three different time series aggregation methods. For each of four anomaly detection algorithms and their variants, we calculated seven performance indicators and multi-criteria scores to guide epidemiologists in their choice of which temporal aggregation of surveillance to use. From 19,200 analyzed time series, we observed an effect of temporal aggregation on the performance of the detection algorithms tested. Results also showed that the time aggregation unit was linked to the detection algorithm used, and that strong aggregation-algorithm interactions need to be taken into account when deciding on which aggregation-algorithm pair to use. Using theoretical data, our study also showed that no one ideal aggregation-algorithm pair exists for all contexts when deciding on which temporal unit of surveillance to use, and that the choice depends on several parameters.Our results can help public health practitioners choose the most appropriate time series aggregation and algorithm according to their specific needs. Finally, the present work enabled us to develop recommendations for a One Health project where the same time aggregation type and detection method could be used for both human and animal syndromic surveillance data.

Noisy Optimization of Dispatching Policy for the Cranes at the Storage Yard in an Automated Container Terminal

In this paper, we claim that the operation schedule of automated stacking cranes (ASC) in the storage yard of automated container terminals can be built effectively and efficiently by using a crane dispatching policy, and propose a noisy optimization algorithm named N-RTS that can derive such a policy efficiently. To select a job for an ASC, our dispatching policy uses a multi-criteria scoring function to calculate the score of each candidate job using a weighted summation of the evaluations in those criteria. As the calculated score depends on the respective weights of these criteria, and thus a different weight vector gives rise to a different best candidate, a weight vector can be deemed as a policy. A good weight vector, or policy, can be found by a simulation-based search where a candidate policy is evaluated through a computationally expensive simulation of applying the policy to some operation scenarios. We may simplify the simulation to save time but at the cost of sacrificing the evaluation accuracy. N-RTS copes with this dilemma by maintaining a good balance between exploration and exploitation. Experimental results show that the policy derived by N-RTS outperforms other ASC scheduling methods. We also conducted additional experiments using some benchmark functions to validate the performance of N-RTS.

Finding the most suitable existing irrigation dams for small hydropower development in Turkey: A GIS-Fuzzy logic tool

This paper enables a screening of existing irrigation dams in order to assess and rank potential sites for small hydropower development by using a Geographic Information System (GIS)-fuzzy logic multi-criteria scoring technique. The following criteria are evaluated: dam characteristics (reservoir normal level, reservoir capacity, dam purpose, dam ageing), and grid connection spatial characteristics. The proposed method estimates the suitability degree of each criterion separately and then aggregates them into a Site Suitability Index (SSI). Existing irrigation dams in Turkey are assessed in order to be utilized for hydropower development. The overall score of each candidate site is obtained and, their performance is compared for different strategies. One of the most suitable dams, Karadere, was chosen as a case study. By using the daily continuous monitored data, we showed that flow and head is highly variable during the irrigation season. Accordingly, we evaluated an innovative compact medium-head hydro turbine that can capture those fluctuations with its operational flexibility and minimal civil works. Moreover, an optimal path methodology was applied to find the best grid connection route from the dam to its nearest substation considering the site land use characteristics in order to minimize land expropriation.

SLA-Aware Multi-Criteria Data Placement in Cloud Storage Systems

This paper proposes a multi-criteria data placement mechanism for typical cloud storage systems. The primary goal of this study is to place the clients’ files in the storage cluster by taking into account the principles of service level agreements and the levels of user support services. For this purpose, a multi-criteria scoring model is defined based on a trade-off between three criteria that can be crucial from the clients’ viewpoint: data access latency, data privacy, and computational performance. The second goal of the proposed mechanism is to improve the fairness of the storage allocation mechanism for various kinds of files compared to the conventional mechanisms. In this case, the cloud service provider gives each data storage node a chance to become the host of an already received file using a probabilistic ranking model. The experimental results demonstrate that the proposed data placement mechanism increases the robustness of cloud storage architecture under different file, network, and storage configurations compared to the existing data placement mechanisms.

Analysis of Rock Raw Materials Transport and its Implications for Regional Development and Planning. Case Study of Lower Silesia (Poland)

The movement of rock raw materials from source to demand areas is carried out predominately with road and railway transport. The latter is less damaging to infrastructure, the environment and society and is cheaper for longer distances, but it is also less flexible and not widely used. The Lower Silesia region in southwestern Poland is an important producer of rock raw materials and the principal provider of igneous and metamorphic dimension stones and crushed rocks in the country. A multicriteria scoring scheme has been developed and applied to identify mines presently using road transport, that are predisposed to switch to or include a railway form of transport. Four criteria have been proposed, C1—distance to railway loading point, C2—annual production of rock raw material, C3—economic reserves, and C4—type of rock raw material. The scoring scheme (classification) was developed based on the results of descriptive statistics for mines presently using railway or combined road and railway forms of transport. Two scenarios were analyzed, one with equal weights (0.25) and the other with higher significance of C1 = 0.40 and C2 = 0.30, and lower significance of C3 = 0.20 and C4 = 0.10. In the result, 24 mines were identified and ranked in terms of their potential to introduce railway transport. The proposed methodology can be used universally for other regions and countries, and the results will be included in drawing up regional spatial development policies.

A fuzzy-based model for risk assessment of routes in oil transportation

The transportation of oil is the final step that the oil is taken before it is distributed to consumer. Road transport is a type of oil transportation methods, and transfers between facilities of primary and secondary bases are carried out by tanker trucks. A particular advantage of tanker trucks is that they provide direct travel from the source to the destination. However, road transport involves possible hazards for population and environment. At this point, this study presents a fuzzy-based risk assessment model for the routes in an oil transportation company. Fuzzy analytic hierarchy process, which is a commonly used multi-criteria decision-making method, is applied in weighting nine criteria related to the road characteristics. Then, risk scores for eleven different routes which the tanker trucks of the company followed are determined by using a basic multi-criteria scoring method. Results of the case study emerge that the most important criterion is narrow road. The riskiest route for the company has been determined. In order to reduce risks to an acceptable level, a number of control measures are suggested such as to assign experienced drivers for this route, provide regular training for drivers, make regular vehicle maintenance and transport large quantities at one time as possible. To demonstrate validity, a comparison is also provided between the proposed approach and Pythagorean fuzzy analytic hierarchy process-based risk scoring model. In conclusion, this study contributes to the applicability of fuzzy analytic hierarchy process to assess riskiness for routes in oil transportation.

Using Data from a State Travel Demand Model to Develop a Multi-Criteria Framework for Transload Facility Location Planning

The majority of freight is transported within the U.S. by road. However, the use of alternative modes, such as rail and barge, is associated with lower transportation and infrastructure maintenance costs, release of highway capacity, increased safety, and lower emissions. Thus, there is a latent opportunity for shippers and consumers to benefit from modal shift. In this context, strategically located freight-transfer facilities to improve rail and barge access is key. Moreover, for states with lower commodity tonnages and access to short-line rail and navigable waterways, transload facilities have significant potential to shift freight to underutilized modes. This paper develops a multi-criteria assessment framework to identify strategic locations for transload facilities at the state level. Using a statewide travel demand model (STDM) as the main data source, this framework provides a sketch-planning tool to support decision-making for state Departments of Transportation and economic development agencies. The multi-criteria quantify four measures of facility potential: (a) interaction with the transportation network, (b) amount of freight transported between major freight routes, (c) spatial aggregation, and (d) directionality aggregation. Each criterion is estimated and combined at the county level to produce a multi-criteria score, which defines a county’s potential to support transload movements. Using this score, counties are ranked, and facilities prioritized. The framework is applied to Arkansas and validated using the STDM for base (2010) and forecast (2040) years.

A review on the state of the biodiversity knowledge on Iran’s southern seas: introducing a methodology to evaluate the validity of the reported cases

High maritime activities in the Persian Gulf and the Gulf of Oman as the major waterways for oil and gas transport and the lack of a documented database on total taxa diversity require greater attention for the biodiversity of these environments. The available marine biodiversity data in Iran are sparse and abandoned on libraries’ shelves and, as such, accessing relevant and reliable current information about the status of Iranian southern seas biodiversity is challenging. Therefore, there is an urgent need to extract, standardize, and evaluate these biodiversity data. A comprehensive review of the available biodiversity data on the Iranian southern seas provided an estimate about the species diversity and highlighted the amount of reliable biodiversity data, research gaps, and required information for the lesser-known areas. In the present review, the available biodiversity data records of the Persian Gulf and the Gulf of Oman under Iranian ownership was extracted from non-database information sources (books, theses, research reports, and articles) and open-access database portals, such as the Ocean Biogeographic Information System (OBIS), Global Biodiversity Information Facility (GBIF, https://doi.org/10.15468/dl.jm7hat ), and those museum collections with online portal data collection search facilities. In total, 59,745 biodiversity records were extracted from all information sources. After data standardization based on the OBIS data scheme (Darwin core format), eight criteria with 29 sub-criteria were considered and scored to measure the validity of each record. Consequently, the presence of 3364 valid species (more than twice the number predicted earlier for the total species diversity) was reported for the study area. Describing new species shows an increasing trend, as most of the 80 new species until the beginning of 2018 were described recently. Mollusca phylum had the most amount of synonymy in non-database information sources. The results show that some marine taxa have been ignored in previous studies and the focus was on a certain group of organisms. Multi-criteria scoring analysis shows that 6% of the extracted biodiversity data for non-database information sources have 75–100% credit (valid), 70% have 50–75% credit (semi-valid), 23.4% have 25–50% credit (a little valid), and 0.9% have 0–25% credit (invalid). On the other hand, OBIS data extracted for Iran do not have invalid data due to its good data quality control, but 58 and 20% of its extracted data are semi-valid and valid, respectively. We believe that all of the eight mentioned criteria are required for reporting biodiversity data, and our proposed weighting system helps different users who need to know how reliable is the published data.