High Priority Class Research Articles

Recognizing high-priority disinfection byproducts based on experimental and predicted endocrine disrupting data: Virtual screening and in vitro study

So far, about 130 disinfection by-products (DBPs) and several DBPs-groups have had their potential endocrine-disrupting effects tested on some endocrine endpoints. However, it is still not clear which specific DBPs, DBPs-groups/subgroups may be the most toxic substances or groups/subgroups for any given endocrine endpoint. In this study, we attempt to address this issue. First, a list of relevant DBPs was updated, and 1187 DBPs belonging to 4 main-groups (aliphatic, aromatic, alicyclic, heterocyclic) and 84 subgroups were described. Then, the high-priority endocrine endpoints, DBPs-groups/subgroups, and specific DBPs were determined from 18 endpoints, 4 main-groups, 84 subgroups, and 1187 specific DBPs by a virtual-screening method. The results demonstrate that most of DBPs could not disturb the endocrine endpoints in question because the proportion of active compounds associated with the endocrine endpoints ranged from 0 (human thyroid receptor beta) to 32% (human transthyretin (hTTR)). All the endpoints with a proportion of active compounds greater than 10% belonged to the thyroid system, highlighting that the potential disrupting effects of DBPs on the thyroid system should be given more attention. The aromatic and alicyclic DBPs may have higher priority than that of aliphatic and heterocyclic DBPs by considering the activity rate and potential for disrupting effects. There were 2 (halophenols and estrogen DBPs), 12, and 24 subgroups that belonged to high, moderate, and low priority classes, respectively. For individual DBPs, there were 23 (2%), 193 (16%), and 971 (82%) DBPs belonging to the high, moderate, and low priority groups, respectively. Lastly, the hTTR binding affinity of 4 DBPs was determined by an in vitro assay and all the tested DBPs exhibited dose-dependent binding potency with hTTR, which was consistent with the predicted result. Thus, more efforts should be performed to reveal the potential endocrine disruption of those high research-priority main-groups, subgroups, and individual DBPs.

Utilizing statistical and MCDM techniques in indexing morphometric parameters towards improved watershed management in the Nandhour-Kalish drainage system

ABSTRACT Morphometric analysis plays a crucial role in the effective management of the surface as well as subsurface water resources. In the present study, ASTER DEM and Survey of India toposheets were utilized to characterize various morphological aspects of the Nandhour-Kalish watershed in Uttarakhand, India. In total, 12 sub-watersheds were determined using the SWAT 2012 in ArcGIS v10.4.1 and were coded as SW1–SW12. For each sub-watershed, 17 morphometric indices were estimated using Principal Component Analysis to determine the most influential indices or criteria of morphometric parameters in the context of the hydro-sedimentological response. The relative influence of identified criteria parameters was assessed using the Criteria Importance for Intercriteria Correlation (CRITIC) method. The developed sub-watersheds were then prioritized towards the prompt implementation of soil and water conservation measures. The results indicate that three sub-watersheds (SW2, SW3, and SW4) were categorized under a very high class of priority, while three (SW1, SW5, and SW6) were indexed under a high priority class. The study is an attempt to ease out the morphometry-based prioritization, which otherwise is relatively complex due to the availability of a large number of input parameters and ambiguity concerning parameter selection for the process of prioritization.

Spatial Conservation Prioritization of Persian Squirrel Based on Habitat Suitability and Climate-Induced Forest Mortality Risk

The Zagros forests in Iran are currently experiencing an exacerbation of climate-induced mortality, placing the Persian squirrel, a keystone species reliant on these ecosystems, in jeopardy. Addressing this imminent threat, our research employed a spatial prioritization methodology, integrating assessments of habitat suitability and mortality risk. Utilizing a weighted ensemble approach, incorporating the strengths of diverse models and expert rules, we discerned that approximately 62% of surveyed forests are at risk, with 7% classified as high risk and 17% as very high risk. Notably, 83% of the forests exhibited varying degrees of habitat suitability, with 11% and 12% demonstrating high and very high suitability, respectively. Employing a conservation prioritization framework, we systematically categorized habitats into priority classes, with 8%, 17%, 29%, and 46% assigned to very high, high, moderate, and low conservation priority classes, respectively. Significantly, areas classified as very high priority demand immediate restoration efforts due to ongoing mortality, while other priority classes underscore the importance of protection and prevention in unaffected habitats. Acknowledging the irreversible nature of current climatic conditions in the Zagros forests, our strategic emphasis aligns with conservation triage principles, prioritizing the preservation of intact habitats yet to succumb to irreversible mortality.

Morphometric parameters based prioritization of watersheds for soil erosion risk in Upper Jhelum Sub-catchment, India.

Soil erosion is the inherent and destructive threat affecting agricultural production and livelihood of million mouths. The increased frequency of floods and land use/land cover changes has made Upper Jhelum Sub-catchment susceptible to soil erosion risk. Morphometric based watershed prioritization for soil erosion risk may help in sustainable management of natural resources. Thus, this paper endeavors to prioritize watersheds of Upper Jhelum Sub-catchment in India based on morphometric parameters for soil erosion risk using geospatial techniques. Weights to the morphometric parameters were assigned through a multi-criteria decision method. The watersheds in the Sub-catchment have been categorized into low, medium, high and very high priority classes based on prioritization ranks that were determined by computing the compound value for the soil erosion risk, based on prioritization ranks obtained through compound value for the soil erosion risk. The results revealed 1E1D3 and 1E1D8 watersheds accorded very high priority. The watersheds namely IE1D2 and IEID4 were found under high priority. Medium priority for soil erosion risk was determined in IEID5 and IED7 watersheds while 1E1D1 and IE1D6 watersheds were identified for low priority. The study calls for implementing soil conservation practices in the Sub-catchment. The Sub-catchment can be made less hazardous for the soil erosion risk by implementing contour farming, building check dams, terrace farming, afforestation and limiting large scale overgrazing. The findings of this study may offer valuable insights for stakeholders for conservation of soil resource. The approach utilized in the study may be linked with soil loss estimation for effective conservation of natural resources in further future studies.

Cognitive-Radio-Based Resource Management for Smart Transportation: A Sliding Mode Control Approach

Smart transportation is one of the key components of the smart city. A significant amount of data is produced by the numerous vehicles connected via wireless networks. This demands smart spectrum management for efficient data communication. The optimal bandwidth usage can be obtained by opportunistically sharing the spectrum among high-priority class primary and low-priority class secondary users’ vehicles. In this study, we develop a mathematical model to ensure effective resource allocation in Cognitive Radio based Smart Transportation Networks (CR-STN) considering the mobility, bandwidth constraint and interference models. Robust sliding mode control is synthesized using an exponential reaching law to avoid data packet congestion in CR-STN to ensure smart spectrum management. In addition, a dynamic event-triggered mechanism is incorporated with the sliding mode controller to reduce computational complexity and energy expenses. The effectiveness of the suggested controller has been validated by simulation results.

Recent Developments in Photocatalytic Reduction of Nitro Compounds to Valuable Scaffolds

AbstractThe reduction of nitro compounds is one of the fundamental organic transformations and ascertain wide applicability in industrial chemistry, synthesis of valuable scaffolds, fine chemical synthesis, as well as environmental applicability for decontamination process. The transformation involves the conversion of nitro compounds into valuable scaffolds including amino, nitroso, hydroxyl amines, azo, and hydrazo compounds. Conventional approaches for the reduction of nitro compounds involves the environmentally harmful stoichiometric reagents, high-boiling reaction media, tedious processes, and harsh reaction conditions with high temperature and pressure. Additionally, the selectivity always remains a serious concern associated with the process due to the possibilities of several stable intermediate formation in the reaction pathway of reduction of nitro compounds. Nitro compounds are also of serious environmental concerns being a part of most harmful and high-priority classes of pollutants mainly released from industrial effluents, agricultural waste, and human sewage. A simple degradation of these pollutants bearing nitro group just removes the pollutants, however, the selective reduction of nitro group to valuable functionalities as mentioned above provides the industrially important scaffolds. With the advent of photocatalytic organic transformation, most of the scientific fraternity working in the area of organic synthesis, catalysis, and environmental decontaminations are utilizing the clean, green, low-temperature, energy and cost-effective, sustainable processes for the reduction of nitro compounds to access valuable scaffolds. Nowadays a lot of mechanistic developments in the field ease the processes for the developments of such highly valuable organic transformations. Herein, the present Account is focused on the recent developments in the photocatalytic reduction of nitro compounds to valuable scaffolds.1 Introduction2 Reduction of Nitro Compounds2.1 Conventional Approaches for Reduction of Nitro Compounds2.2 General Photocatalytic Mechanism3 Mechanistic Pathways: Electrochemical, Conventional and Photocatalytic Approaches3.1 Mechanism of Electrochemical Reduction of Nitroarene3.2 Conventional Reduction Mechanism of Nitroarenes3.3 General Photocatalytic Reduction Mechanism of Nitroarenes4 Photocatalytic Reduction of Nitro Compounds to Valuable Scaffolds4.1 Reduction of Nitro Compounds to Corresponding Amines4.2 Reduction of Nitro Compounds to Azo Compounds4.3 Reduction of Nitro Compounds to Azoxy Compounds4.4 Reduction of Nitro Compounds to Nitroso Compounds4.5 Reduction of Nitro Compounds to Hydroxyl Amines5 Future Perspective6 Conclusion

Optimizing Fuel Treatments Allocation to Protect the Wildland–Urban Interface from Large-Scale Wildfires in Greece

A crucial risk governance priority of the Greek forest managers is to reduce damages in the wildland–urban interface (WUI) by controlling wildfire behavior through fuel management practices. To support decisions for where management should be applied and how, this study experimented with new methods for fuel treatments allocation over a typical Mediterranean fire-prone landscape in the peninsula of Kassandra (an area of 350 km2), northern Greece. The Minimum Travel Time (MTT) fire simulation algorithm and the Treatment Optimization Model were used to produce eight spatial exclusionary and non-exclusionary datasets that were used as criteria for the spatial optimization of fuel management interventions. We used the Multicriteria Decisions Analysis method with Geographical Information Systems to cartographically intersect the criteria to produce two priority maps for two forest management scenarios (i.e., a control and a realistic one). The results revealed that 48 km2 of the study area was characterized as high-priority locations in the control scenario (i.e., with equally weighted management priorities), while 60 km2 was assigned to the high-priority class in the realistic scenario (i.e., with different weighted management priorities). Further analysis showed a substantial variation in treatment priority among the four major forest land cover types (broadleaves, sparse Mediterranean shrublands, conifers, and dense Mediterranean shrublands), revealing that the latter two had the highest selection values. Our methodological framework has already been operationally used by the Greek Forest Service branch of Kassandra to decide the most effective landscape fuel treatment allocation.

Soil loss and erosion potential estimation of Jhimruk watershed, Nepal

Soil erosion will have impact in the land productivity, water resource and watershed as a whole. The loss of top soil leads to land degradation and for an agrarian area like Jhimruk which also known as “The rice bowl of Nepal”, it would be a huge consequence on the land productivity. Therefore, it is essential to know the spatial distribution of the areas susceptible to the degradation and assess the erosion potential to plan effective mitigation measures. The Revised Universal Soil Loss Equation (RUSLE) model was used in a Geographic Information System (GIS) to estimate the soil loss of the Jhimruk watershed, Lumbini Province, Nepal. This research aimed to calculate the erosional soil loss status of the local governments lying inside the watershed. For this, remote sensing data obtained from various sources were used to generate the factor maps to calculate the soil loss through RUSLE. A 13-year mean annual precipitation data from the 8 meteorological stations in and around the watershed were used. The mean annual soil loss of the watershed was found to be 13.4 tons per hectare per year (t/ha/yr). However, the soil loss was calculated to be as high as 182 t/ha/yr. 68.82% of the total area of the watershed lie under very low erosion class and thus, have low conservation priority. On the other hand 7.73% of the total area of the watershed lie under extremely high erosion class and, thus, have a high conservation priority class. The mean erosion rate from the barren land was found to be highest (23.179 t/ha/yr) followed by agricultural (21.40 t/ha/yr) and forest area had the lowest erosion rate, i.e., 7.90 t/ha/yr.

Error Performance Analysis of Wireless Video Communication Systems Employing Multi-level MPSK Modulation and MIMO Technologies

Real-time communications of high definition video with the available limited channel bandwidth is a fundamental requirement for modern mobile and wireless networks such as Wi-Fi, WiMax, 3G, LTE and the emerging 5G. To fulfill this requirement, H.264/AVC and High Efficiency Video Coding (HEVC) or H.265 standards have been implemented to achieve high error performance over wireless channels and large compression efficiency thereby optimizing channel bandwidth. The problem of establishing and maintaining reliable communication paths among mobile users employing multiclass bitstreams to achieve high spatial diversity and coding gains is a big challenge for researchers. In practice, multimedia standards employ data partitioning where different levels of importance are assigned to the multimedia content. The problem of transmission of coded HEVC data over wireless channels employing MIMO technologies to maximize high spatial diversity and coding gains has not been explicitly explored in existing research works. Moreover, to meet the demand of 5G networks in providing ultra-reliable low latency communications it is required to study fully the performance of multimedia data over wireless channels. To this end we propose, in this paper, to study and analyze the performance of coded MIMO systems employing a triple-class bitstreams source namely a high priority, medium priority and low priority class. The objective of our study is to promote Unequal Error Protection (UEP) as well as spatial diversity of the coded bitstreams without sacrificing the channel bandwidth and increasing the computational complexity. Space-Time Block Codes with Orthogonal properties and Hierarchical or Multi-level 8PSK modulation are considered in our analysis and the adopted approach will be shown, through numerical evaluation and simulations, that excellent UEP capabilities as well as high spatial diversity gains can be achieved. New Bit Error Rate (BER) expressions in closed form are derived for independent and identically distributed Rayleigh channel in the presence of Additive White Gaussian Noise (AWGN). Single and multiple fading channel reception systems with Maximum Ratio Combining (MRC) are considered. The simulations of our proposed UEP transmission model are designed and implemented in Matlab Simulink® R2017. It is shown that the most important priority data gives a coding gain of around 11 dB over the less important one at a BER of 10--6 for an 8-diversity order Orthogonal Space-Time Block Code (OSTBC) employing Hierarchical 8PSK modulation. This work can be extended to evaluate the error probability of multiuser coded systems for 4G and 5G networks.

Priority Modeling for Public Urban Park Development in Feasible Locations using GIS, Intuitionistic Fuzzy AHP, and Fuzzy TOPSIS

As feasible locations of public urban park in Bogor Municipality have been acquired in a previous study, decision makers are urgently needed to be informed on which locations should be prioritized for public urban park (PUP) development. Therefore, this study aggregates four multi-spatial criteria for PUP development priority modeling, namely distance to slum neighborhood, accessibility, slope, and land value. These four criteria in form of vector datasets were weighted using intuitionistic fuzzy analytical hierarchy process (IF-AHP) to consider the hesitancy, vagueness, and fuzziness might arise from experts’ judgement as well as from multi-spatial data processing. Resulted criteria weights from IF-AHP show that accessibility weight 0.261, land value weight 0.259, distance to slum weight 0.255, and slope weight 0.225, respectively. Criteria weights were inputted into fuzzy technique for order preference by similarity to the ideal solution (TOPSIS) and geographic information system (GIS) to rank location priority. Results from fuzzy TOPSIS show that very high priority class which has the biggest CCi values range (0.654-0.76) provides 0.14 km2 area of feasible PUP development scattered in 10 locations. The biggest area for feasible PUP development is generated by medium priority class (CCi values 0.439-0.546) in 26 locations and approximately area of 0.38 km2.

Erosion risk assessment through prioritization of sub-watersheds in Nyabarongo river catchment, Rwanda

Soil erosion is a multi-dimension problem that attracted the attention of researchers and planners worldwide. Literature reports, soil conservation strategies should be integrated with the priority assessment to deal with such a problem and taking up a focus according to the priority order. However, in spite of various forms of land and water degradation in Rwanda, a holistic investigation or multi-criteria based watersheds prioritization that integrate various aspects and methods has yet to be assessed. Thus, Nyabarongo River Catchment which is the major river catchment in Rwanda that drains about 33% of the total Rwanda coverage has been selected and sub-watersheds were grouped into three order clusters (C1, C2, and C3) using Hierarchical Cluster Analysis (HCA). The priority assessment was estimated using the combination of Compound parameter index (Ci) and Erosion Hazard Rate Index (EHRI) derived from the Analytical Hierarchy Process (AHP) in Geographic Information System (GIS) using remote sensing, soil and geology data. Based on the literature, the Ci technique, in general, considered four parameters viz. morphometric analysis dimensionally reduced using the Principal Component Analysis (PCA) together with land cover, soil, and geology. Whereas EHRI considered five Erosion Hazard Parameters (EHPs) viz. Soil Loss (SL), Sediment Production Rate (SPR), Sediment Transport Index (STI), Runoff Potential (RP), and Slope. The priority assessment was categorized into High, Moderate, and Low priority classes. The priority assessment based on Ci and EHRI provided the same outcome. They noticed high priority in sub-watersheds under cluster C2 account for (35.94%), those under cluster C3 comprise for (16.27%) were identified as a moderate priority, and sub-watersheds belonging to cluster C1 account for (47.8%) falling under low priority sub-watersheds for conservation measures. Therefore, effective soil conservation measures at a priority basis are needed for sustained productivity while minimizing undesirable effects on the environment.

Suggesting priority areas in the buffer zone of Serra do Brigadeiro State Park for forest restoration compensatory to bauxite mining in Southeast Brazil

Prioritizing is essential to optimize resource allocation and restoration benefits. Bauxite mining is an important economic activity in the Zona da Mata region of Minas Gerais state, Southeast Brazil. The exploitation process of this ore creates demands for compensatory forest restoration, which may be directed to key areas for conservation such as the Buffer Zone of the Serra do Brigadeiro State Park (BZ-SBSP).The objective of this study was to propose a new application of Multicriteria Evaluation based on Geographic Information Systems (MCE-GIS) to suggest priority areas for compensatory forest restoration in BZ-SBSP by using criteria important at the landscape level and in the field. The modeling of priority areas followed a suitability scale approach, which varied from 0 to 255, using five factors: permanent preservation areas, slope, land use and land cover, distance from conserved forest fragments and ecological corridors. The factors were aggregated under three different risk scenarios: Weighted Linear Combination (WLC), low risk Ordered Weighted Average (OWA) and high-risk OWA. Suitability increased with the risk assumed in the analysis. The area corresponding to the very high priority class increased from 0.31% in the most conservative scenario to 10.72% in the riskiest scenario. The high-risk OWA scenario can be considered the best alternative for presenting a greater number of viable options and high suitability in at least some factors. The maps generated in this study may support multiple stakeholders to identify and direct resources to high priority sites. It is important to highlight that a set of economic, social, and technical factors may still restrict the restoration of an area indicated as high priority. Thus, this study can be considered as general guidelines for restoration planning, suggesting areas that should result in greater benefits derived from forest restoration and in greater success of the projects, when considering the landscape of interest, its integrity and other relevant aspects that should be considered in a restoration project.

Feedback controlled resource management model for express service in electric vehicle charging stations

The number of electric vehicles on the roads is increasing globally. However, the charging duration of electric vehicles is long, and the number and capacity of fast charging public stations are limited. This may lead to congested electric vehicle charging stations and long waiting times in queues. Priority based express service can reduce the waiting times of the high priority class. This study develops a feedback controlled express station management model (FC-EXP) for priority service in electric vehicle charging stations. FC-EXP manages the charging station's resources dynamically in real time such that the ratio of high and normal priority vehicles' delay times follow a relative delay target. Stations can announce different relative delay targets depending on their pricing policies. FC-EXP provides a self-controlling resource management capability to express charging stations. Results show that FC-EXP successfully tracks the relative delay target under different conditions, both in steady state and in real time.

Learning to Resolve Conflicts for Multi-Agent Path Finding with Conflict-Based Search

Conflict-Based Search (CBS) is a state-of-the-art algorithm for multi-agent path finding. On the high level, CBS repeatedly detects conflicts and resolves one of them by splitting the current problem into two subproblems. Previous work chooses the conflict to resolve by categorizing conflicts into three classes and always picking one from the highest-priority class. In this work, we propose an oracle for conflict selection that results in smaller search tree sizes than the one used in previous work. However, the computation of the oracle is slow. Thus, we propose a machine-learning (ML) framework for conflict selection that observes the decisions made by the oracle and learns a conflict-selection strategy represented by a linear ranking function that imitates the oracle's decisions accurately and quickly. Experiments on benchmark maps indicate that our approach, ML-guided CBS, significantly improves the success rates, search tree sizes and runtimes of the current state-of-the-art CBS solver.

Service Differentiation in IEEE 802.11ah WLAN under Restricted Access Window based MAC protocol

The restricted access window (RAW) based channel access scheme proposed for IEEE 802.11ah wireless LAN (WLAN) divides the stations (STAs) in the network into groups and allocates RAW slots for each group of STAs. In this way, the STAs belonging to each group can attempt to access the medium during their designated RAW slot by invoking the enhanced distributed channel access (EDCA) protocol. This paper describes an analytical model to evaluate the saturation throughput of IEEE 802.11ah WLAN under the RAW based scheme, when STAs carry traffic of distinct access categories (ACs) and use the EDCA protocol for medium sharing. However, when groups are formed by randomly selecting the STAs, i.e., if random grouping (RG) scheme is employed, each group will contain STAs carrying traffic of distinct ACs. This will lead to starvation and degraded throughput performance for the low priority class STAs, since they have to contend with high priority class STAs within the same group during the RAW slot assigned. To resolve this issue, we propose an algorithm to realize priority class based grouping (PCG), in which the STAs belonging to the same ACs are grouped together. We also describe an analytical model to evaluate the saturation throughput of the network under the proposed PCG scheme. We establish that saturation throughput of the network and the relative service differentiation ratio of the lower priority class STAs can be significantly improved under the proposed PCG scheme compared to the conventional RG scheme.

IRCTGP: A Novel Intra-node Resource Control Protocol Based on Traffic Priority and Evolutionary Games Theory for Wireless Sensor Networks

A Wireless Sensor Network (WSN) is a network which is made up of resource-constrained wireless sensors with restricted capabilities. Quality of Service in Wireless Sensor Networks is still an open area of research, due to the fact that several problems need to be solved using resource constrained WSN nodes. The probability of congestion occurrence and packet loss in Wireless Sensor Networks is high, which makes it difficult to satisfy different qualities of service requirements. Congestion in WSN needs to be controlled to improve the quality of service such as throughput and packet loss ratio along with the packet delay. In particular, we proposed the use of evolutionary game theory in the design of a QoS-aware Intra-node congestion control protocol. Intra-node congestion control protocol is a non-cooperative asymmetric game that adjusts the queue accepting rate and queue service rate such that higher priority classes have lower loss rate and lower queuing delay. Simulation results show that the proposed protocol decreases packet dropping and improves network throughput and network quality of service performance.

RECENT LAND USE AND LAND COVER CHANGE DYNAMICS IN THE GRAN CHACO AMERICANO

Abstract. Land transformation is one of the most significant human changes on the Earth’s surface processes. Therefore, land use land cover time series are a key input for environmental monitoring, natural resources management, territorial planning enforcement at national scale. We here capitalize from the MapBiomas initiative to characterize land use land cover (LULC) change in the Gran Chaco between 2010 and 2017. Specifically we sought to a) quantify annual changes in the main LULC classes; b) identify the main LULC transitions and c) relate these transitions to current land use policies. Within the MapBiomas project, Landsat based annual maps depicting natural woody vegetation, natural herbaceous vegetation, dispersed natural vegetation, cropland, pastures, bare areas and water. We used Random Forest machine learning algorithms trained by samples produced by visual interpretation of high resolution images. Annual overall accuracy ranged from 0,73 to 0,74. Our results showed that, between 2010 and 2017, agriculture and pasture lands increased ca. 3.7 Mha while natural forestry decreased by 2.3 Mha. Transitions from forests to agriculture accounted for 1.14% of the overall deforestation while 86% was associated to pastures and natural herbaceous vegetation. In Argentina, forest loss occurred primarily (39%) on areas non considered by the territorial planning Law, followed by medium (33%), high (19%) and low (9%) conservation priority classes. These results illustrate the potential contribution of remote sensing to characterize complex human environmental interactions occurring over extended areas and timeframes.

WATERSHED PRIORITIZATION ACROSS ERBIL PROVINCE FOR SOIL EROSION MANAGEMENT VIA MORPHOMETRIC ANALYSIS

Soil erosion is one of the foremost factors giving rise to watershed deterioration due to improper and unwise utilization of natural resources without proper vision, particularly in developing countries like Iraq. Since it is not possible to implement rehabilitation programs over all areas at a time, prioritization plays a major role in identification of the areas which are in need of immediate actions. Accordingly, the current study was conducted to perform morphometric analysis as the basis for prioritization. To achieve the above objective, 30 watersheds of different scales were delineated within Erbil governorate and standard procedures were followed to carry out morphometric analysis. Prioritization ranks were determined for the study watersheds based on computation of compound factors and on the technique for order preference by similarity to ideal solution (TOPSIS). The results indicated that nearly two approaches offered similar results. The regression analysis indicated that the priority rank from (TOPSIS) can be predicted from the priority rank from compound factor computation with a reasonable accuracy. Based on TOPSIS approach, watersheds: Kawlan-smelan, Nawandee, Warte, Prdi-qasre, Nawprdan, Darbandy-rayat, Dargalla and Mergasor fall within the very high priority class and as a consequence immediate actions should be taken to protect these watersheds. By contrast, the watersheds: Kasnazan, Smaquly, Bestana, Kawanyan, Rulka and Degala 1 are categorized under the low prioritization level. Further improvements in specifying the priority ranks can be expected upon coupling land use/land cover with morphometric analysis.

Performance Analysis of Priority-Based Access Class Barring Scheme for Massive MTC Random Access

In a massive machine-type communication (MTC) environment, a traffic control algorithm is essential to solving traffic congestion problems. Additionally, as MTC applications have diverse quality-of-service requirements, traffic control should be applied in a way that guarantees diverse requirements. Therefore, we propose a priority-based access class barring (PACB) scheme, in which MTC devices are divided into multiple classes according to their delay requirements, and a different access class barring (ACB) factor is used for each class. This article suggests an approach to choose multiple ACB factors that can maximize the number of successful access events and can also guarantee the low delay requirement of the high-priority class. Then, an analytical model is proposed for the ideal case, and throughput, drop probability, and access delay are derived to evaluate the performance. For a realistic environment, we also suggest an estimation algorithm for the PACB scheme, in which a base station estimates the number of active devices for each class. Numerical and simulation results showed that the analytical model is consistent with the simulation results. Additionally, the performance of the estimation algorithm was similar to that of the ideal case. Furthermore, the proposed PACB scheme can decrease the delay of a high-priority class and improve the throughput and drop probability compared to existing algorithms.

Endocrine surgery during COVID-19 pandemic: do we need an update of indications in Italy?

The ongoing spread of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) poses a significant threat to global health. As the coronavirus outbreak began spreading, hospitals were forced to relocate resources to treat the growing number of COVID-19 patients. As a consequence, doctors across the country canceled tens of thousands of nonurgent surgeries. However, recognizing that the COVID-19 situation may be highly variable and fluid in different communities across the country, elective surgery could be still allowed in some centers for patients included in the high-priority class. The majority of endocrine disorders requiring surgical treatment in patients identifiable as first-priority class, or needing hospitalization within 30 days, are generally represented by malignant thyroid tumors, hyperthyroidism, hyperparathyroidism, and some adrenal disorders. The need for urgent intervention is evaluated on a case-by-case basis according to the severity of the symptoms, the likelihood of progression, and global clinical judgment. On the basis of the above indications, during the last 4 weeks, we performed 18 planned surgical treatments in patients with thyroid cancer (total thyroidectomies, plus lymph node dissection if needed) or multinodular toxic goiter. In no case, postoperative ventilatory support was needed, and the average hospital stay was 3 days. The negative COVID-19 status for all the treated patients was appropriately evaluated beforehand. Nobody knows how long the current COVID-19 pandemic will be lasting. Certainly, we will be requested in the next future to incrementally offer surgical services for endocrine disorders that have been deferred for the COVID-19 pandemic.