Distribution Of Resources Research Articles

Energy–Efficient Distribution of Resources in Cyber-Physical Internet of Things with 5G/6G Communication Framework

Energy–Efficient Distribution of Resources in Cyber-Physical Internet of Things with 5G/6G Communication Framework

The impact of land use and cover changes on river flows in Wundanyi Catchment of Taita Hills, Kenya (1970–2030)

<p>Taita hills are one of the most important biodiversity hotspots of Kenya but experiencing a high rate of deforestation due conversion of its original forestland to agriculture and settlement during the last century. These landscape dynamics coupled with rainfall fluctuations in these critical ecosystems may significantly affect water resource distribution and food security in Taita Taveta County and its environs. This study aimed to establish the trends of land use/cover change (LUCC) in Wundanyi catchment from 1970 to 2030 and predict their specific and combined effects on surface runoff and stream flow in the same period. The analysis was based on statistical trend analysis and dynamic landscape modeling using both historical and primary data from Wundanyi catchment, and Landsat TM and ETM+ imagery of Taita Hills for 1990, 2000, and 2010. Results show highly variable mean seasonal and annual values of discharge in Wundanyi catchment probably attributed to environmental changes affecting Taita Hills in general and Wundanyi catchment in particular. Compared to 1990, major land use/cover changes in 2010 were featured by the expansion of built-up area (250%), plantation forest (23.7%), broadleaved forest (17.4%), and thicket (15.9%). Was also notable the decrease in woodland (−30.3%), cropland (−21.6%), and shrubland (−0.8%). Dynamic spatial trends by the year 2030 will be evidenced by increased thicket by 0.41% per annum (<em>R</em><sup>2</sup> = 81.6%), and by decreased plantation forests (−0.13%; <em>R</em><sup>2</sup> = 91.3%), woodland (−0.10%; <em>R</em><sup>2</sup> = 77.6%), shrubland (−0.11%; <em>R</em><sup>2</sup> = 85.2%), broadleaved forests (−0.03%; <em>R</em><sup>2</sup> = 56.6%) and cropland (−0.09%; <em>R</em><sup>2</sup> of 84.4). These changes will shape the catchment landscape and influence its hydrology, unless the existing forest and agricultural policy interventions are enforced. Hence, crop diversification, agroforestry, and soil and water conservation structures are recommended to maintain effective control of LUCC on hydrological processes going on in the Wundanyi catchment.<strong></strong></p>

Dynamic edge clustering and task scheduling for edge assisted metaverse system in the field of remote work and collaboration

SummaryThe metaverse, a future digital world for living, working, learning, and interacting, is rapidly gaining significance, particularly in the domain of remote work and collaboration. This emerging digital landscape demands high‐performance, low‐latency, and scalable services to provide an immersive user experience. The current technology used in metaverse systems has some limitations, which emphasize the importance of adopting emerging technologies like Edge Computing (EC). However, as the number of users and data volume increases, it can impact both system performance and scalability of the edge‐assisted metaverse system. Additionally, the uneven distribution of edge servers can cause inconsistencies and result in high latency. To overcome these challenges, this paper proposes a dynamic edge clustering and task scheduling approach for edge‐assisted metaverse systems (DTAM) in the field of remote work and collaboration. The proposed approach addresses the challenges of high user volume and uneven resource distribution by incorporating dynamic clustering and edge server assistance to improve clustering performance. Furthermore, a Prioritized Experience Replay‐based Deep Q‐learning algorithm with state augmentation (PERDQSA) for task scheduling is introduced to improve sample efficiency and performance. The performance of the proposed DTAM is evaluated against existing techniques, and experimental results demonstrate its significant superiority in terms of specific metrics such as bandwidth, task response time, energy efficiency, and latency. The experiments demonstrated that DTAM outperforms Transformation‐based Edge Computing Deep Q‐Learning (TransEC‐DQL) in several key metrics. Specifically, DTAM achieves 28.5% reduction in latency, 13.7% reduction in response time, and 6.4% improvement in bandwidth compared to TransEC‐DQL. These results signify that DTAM can deliver a significantly enhanced user experience in the metaverse, particularly in the context of remote work and collaboration.

UHVDC transmission line diagnosis method for integrated community energy system based on wavelet analysis

With the large-scale development of renewable energy power, China has faced with the challenges of the reverse regional distribution of wind and solar resources and power load, as well as the intermittency and randomness of renewable energy power. Therefore, China is vigorously developing ultra-high voltage direct current (UHVDC) transmission technology to solve the problem of insufficient flexibility caused by the uncertainty of renewable energy and the fluctuation of multi-energy loads in integrated community energy systems. UHVDC plays an increasingly pivotal role in the west-east transmission system in China’s power system due to its high transmission capacity and long transmission distance. Once the fault occurs in the ultra-high voltage direct (UHVD) transmission line, quick and accurate fault location identification is of great significance. Hence, this paper proposes a UHVDC transmission line diagnosis method based on wavelet analysis for integrated community energy systems. Wavelet transform (WT) is used to decompose the transient signal on a multi-scale, and then power systems computer-aided design (PSCAD) software is utilized for simulation calculation to obtain the singular spectrum entropy of each layer and facilitate wavelet transformations for signal denoising with advanced tools such as MATLAB. The prediction results can distinguish outside the rectification side fault, within the rectification side fault, and outside the inverter fault with an accuracy of 100%. A large number of simulations demonstrate that combining singular spectrum entropy with support vector machines (SVM) has emerged as a robust technique for integrated community energy systems, suggesting its potential as a standard method in UHVDC transmission line diagnosis. This study is of significant reference for realizing the complementarity of multiple types of power supply and ensuring a reliable power supply.

Technical efficiency and its convergence among village clinics in rural China: evidence from Shanxi Province

IntroductionVillage clinics (VCs) are the foundation of the three-tiered health service system in China, delivering basic and routine outpatient services to citizens in rural China. VC technical efficiency and its convergence play a critical role in policy decisions regarding the distribution of health service resources in rural China.MethodsThis study measured VC technical efficiency (using the slacks-based measure model), its convergence (using the convergence model), and the factors that influence the convergence in Shanxi Province, China. Data were obtained from the Shanxi Rural Health Institute 2014–2018 Health Statistics Report, which involved 3,543 VCs.ResultsThe results showed that VC technical efficiency was low and differed by region. There was no α convergence in VC technical efficiency, but evidence of β convergence was found in Shanxi. The main factors that influence convergence were the building area of each VC (BA), proportion of government subsidies (PGS), and ratio of total expenditure to total income of each VC (RTETI).ConclusionThe government should increase investments in VCs and improve VC technical efficiency. Meanwhile, the government should be aware of and take measures to curb the inequity in VC technical efficiency among different regions and take suitable measures to curb this disparity.

Choosing legislative candidates via primaries: The pivotal role of executive incumbency

How much influence does incumbency have on the way parties nominate candidates? I address this question in the context of Argentina, examining how political parties decide on candidate nomination methods for National Deputies. I argue that holding the governorship creates an imbalanced distribution of resources within a party, leading party factions to lean toward consensus in candidate selection and reducing the likelihood of choosing a primary election. Conversely, when a party lacks the governorship, its provincial party leader may have a weaker influence in deterring primary elections. I also theorize the various situations and resources governors can employ to discourage primary elections, including potential coattail effects, the option of seeking reelection, control over the primaries’ selectorate, and control of the electoral calendar. To test my expectations, I employ a regression discontinuity design, focusing on governors and those who finished as runners-up in lower chamber elections from 1985 to 2023. My findings reveal that governor incumbency decreases the probability of holding a primary election. I conduct further analyses by examining subgroups, considering the governor’s circumstances and the resources I previously theorized as factors influencing primary deterrence. I find that incumbency only deters primaries when the governor and National Deputies elections are concurrent, when the governor is not term-limited, and when they have control over the electorate and the electoral calendar.

Effects of tag mass on the physiology and behaviour of common noctule bats

BackgroundExternal tags, such as transmitters and loggers, are often used to study bat movements. However, physiological and behavioural effects on bats carrying tags have rarely been investigated, and recommendations on the maximum acceptable tag mass are rather based on rules of thumb than on rigorous scientific assessment.MethodsWe conducted a comprehensive three-step assessment of the potential physiological and behavioural effects of tagging bats, using common noctules Nyctalus noctula as a model. First, we examined seasonal changes in body mass. Second, we predicted and then measured potential changes in flight metabolic rate in a wind tunnel. Third, we conducted a meta-analysis of published data to assess effects of different tag masses on the weight and behaviour of bats.ResultsIndividual body mass of common noctules varied seasonally by 7.0 ± 2.6 g (range: 0.5–11.5 g). Aerodynamic theory predicted a 26% increase in flight metabolic rate for a common noctule equipped with a 3.8 g tag, equating to 14% of body mass. In a wind tunnel experiment, we could not confirm the predicted increase for tagged bats. Our meta-analysis revealed a weak correlation between tag mass and emergence time and flight duration in wild bats. Interestingly, relative tag mass (3–19% of bat body mass) was not related to body mass loss, but bats lost more body mass the longer tags were attached. Notably, relatively heavy bats lost more mass than conspecifics with a more average body mass index.ConclusionBecause heavy tags (> 3 g) were generally used for shorter periods of time than lighter tags (~ 1 g), the long-term effects of heavy tags on bats cannot be assessed at this time. Furthermore, the effects of disturbance and resource distribution in the landscape cannot be separated from those of tagging. We recommend that tags weighing 5–10% of a bat’s mass should only be applied for a few days. For longer studies, tags weighing less than 5% of a bat's body mass should be used. To avoid adverse effects on bats, researchers should target individuals with average, rather than peak, body mass indices.

Co-creation of a novel approach for improving supply chain management for SARS-CoV-2 point of care diagnostic services in Mopani District, Limpopo Province: nominal group technique

IntroductionEffective supply chain management (SCM) of point-of-care (POC) tests for diseases like severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) requires active participation from diverse stakeholders, government entities, and regulatory bodies. The responsibility for overseeing various aspects of POC tests, including procurement, quality assurance, storage, inventory management, distribution, and human resource capacity, lies with national, provincial, and local levels of government. This study aimed to collaboratively develop an innovative approach to enhance SCM for SARS-CoV-2 POC diagnostic services in resource-limited settings, using the Mopani District in Limpopo province, South Africa, as a case study.MethodsKey stakeholders were invited to participate in an online workshop using purposive sampling. The study employed the nominal group technique (NGT) for data collection, which consisted of two phases. Phase 1 focused on identifying barriers in the supply chain of COVID-19 rapid tests, while phase 2 aimed to devise strategies to overcome the priority barriers identified in phase 1. Participants used a Likert scale of 1–5 to rank barriers and strategies, and an overall ranking score was calculated for each. The participants were provided with the results of the ranking exercise for their feedback.ResultsEleven key stakeholders from national (n = 1), provincial (n = 4), and local government (n = 2) levels, research entities (n = 3), and non-governmental organizations (n = 1) took part in the study. Participants identified significant barriers in the supply chain, such as the availability of testing kits, unknown demand, information on SCM during a pandemic, methods of controlling stock, and procurement processes. Strategies suggested by key stakeholders included monitoring stock levels and optimizing stock visibility systems to improve test availability, enhancing information visibility and consistent data updates to address unknown demand and improve SCM during a pandemic, employing data capturing and digitization for effective stock control, and implementing demand planning and standardized procurement processes at the national level to enhance stock procurement.DiscussionThe successful collaboration with key stakeholders, facilitated by the NGT, resulted in the co-creation of a novel approach to enhance SCM for COVID-19 diagnostic services in resource-limited settings. This study holds the potential to support the provision of COVID-19 diagnostic services in such settings. A recommended follow-up study would assess the feasibility of implementing this approach.

Evaluating the integration of traditional gong methods in smart home environment for the recovery of health functions of stroke patients

Since the 21st century, network and mobile communication technology are gradually entering the medical and health services field. Combining body area networks, broad-generation mobile communications, and cloud platforms has made various medical applications for large-scale populations possible. The development of digital medical technology, especially digital telemedicine, is increasingly proving to be an important means of significantly reducing the cost of medical care and access, changing the distribution of medical resources, and improving the overall level of care. To observe the effects of traditional Chinese medicine gongfu combined with rehabilitation therapy on mild depression, anxiety, and functional recovery of activities of daily living (ADL) in patients recovering from stroke, and to provide new treatment methods to improve the function and daily living ability of the group who develop mild depression and anxiety after stroke. In this paper, the digital medical engineering application combining information technology and medical treatment integrates various high-end information technologies such as body domain network and cloud computing to solve the difficulties in the current application one by one, to provide the national people with the system provides “timely”, “local” and “bottomless” remote digital health services to the Chinese people.

Assessment of the potential of salt mines for renewable energy peaking in China

Renewable energy sources, such as wind and solar, can reduce environmental pollution and promote the transformation of the energy structure. However, the intermittency and uncertainty of new energy sources such as wind and photovoltaics pose challenges to large-scale grid integration. Effective utilization of intermittent energy sources requires large-scale energy storage facilities. Salt rock is recognized as an excellent medium for underground large-scale energy storage with a wide range of applications. This paper identifies the potential of salt caverns to be used for large-scale energy storage by analyzing the distribution of wind and solar energy resources in China, taking into account the grid-connected infrastructure of the Chinese power grid and the geographic location of salt mines. The overlapping areas are identified for utilization in compressed air energy storage and hydrogen storage. Through meticulous categorization and analysis of the factors influencing salt cavern underground storage site selection, the AHP-EWM method is introduced to establish an objective hierarchy model for a comprehensive evaluation system of salt cavern underground storage site selection. The comprehensive planning of China's 20 major salt mines is conducted, and the research findings hold significant reference value for facilitating the low-carbon energy transition in China.

Кількісне оцінювання функціональної ефективності мережевих структур за аналізом чутливості оптимізаційної моделі до зовнішніх впливів

The real network organizational structure is constantly under the influence of external influences, which can cause unexpected consequences due to the cascading spread of relevant disturbances directed at critically important parameters. Parametric sensitivity analysis is the latest computational procedure, the results of which provide the researcher with an idea and quantitative assessment of the appropriate response of the structure in the form of an analytical platform as a composition and interaction of scenario analysis, cascade process development and optimization modeling technology. The main task is timely adaptation to expected changes in business analytics, oriented to optimal resources distribution. The generalized minimum cost problem is a typical example of widespread problems of optimal distribution and use of limited, in particular, energy resources, of any nature and purpose, using the scientific management and analysis of decisions, in its network model attention is paid to the potentials of nodes. The maximum flow problem is an example of the active and effective application of methods and models of flows optimization, where the processes and objects used a network organization, the energy systems and complexes investigated, where arc parameters are critical in its model. In the article, for these classic optimization problems, mathematical and spreadsheet models were built on concrete examples. Direct and dual mathematical programming problems were solved, the following stages were carried out - the organization of a computer experiment and the construction of an analytical platform for evaluating the behavior of the network structure under the influence of external influences and disturbances as their consequences. To take into account the specific conditions of real objects with a network structure at the stage of modification, the model supplemented with appropriate restrictions and correction of input data sets. The obtained results should be useful for planning and management personnel and top-management for discussion and decision-making regarding, for example, the optimal placement of energy equipment, the weighted distribution of energy flows in the "source-sink" system or the appointment of executors for work, automated project management using project networks, etc. Keywords: optimization modeling, maximum network flow, minimum cost flows, network organizational structures, decision making, spreadsheet modeling and analytics.

Load and go: Assessing safety outcomes of patients discharged from the emergency department after receiving phenobarbital for alcohol withdrawal.

Phenobarbital (PB) is a long-acting GABA A-agonist with favorable pharmacokinetics (long half-life and duration of effect) that allows effective treatment of alcohol withdrawal (AW) after administration of a single loading dose. Current evidence suggests that in the setting of AW, PB administration may be associated with decreased hospital admissions and hospital length of stay. The aim of this study was to evaluate the safety outcomes of AW patients who were treated and discharged from the emergency department (ED) after receiving PB for AW. This retrospective chart review included a convenience sample of 33 AW patients who presented to four EDs within an 18-month span. Descriptive statistics (frequencies and percentages) were used to describe demographics, distribution of resources and referrals, and the safety outcomes of PB administration for low-risk AW patients. Patients were selected for inclusion in consultation with a medical toxicologist, treated with PB, and discharged from the ED. Electronic medical records were utilized to gather information on the patient cohort. All patients were treated with at least a single loading dose of 5‒10mg/kg (ideal body weight) of intravenous or per os PB during their ED stay. Only one patient had an unanticipated event after discharge, which was related to driving against advice. Two additional patients had ED revisits for recurrent alcohol use within 72h, and 16 patients had recurrent alcohol use within 30 days. All 33 patients were provided with resources for linkage to treatment. None required hospital admission. ED PB "load and go" may be a safe, effective AW treatment that could help treat AW, facilitate linkage to specific rehabilitation treatments, and decrease hospital admissions.

Racist dogs and classist rats?

In cities across the world, animals reflect, reproduce and transform urban inequalities – yet their role in mediating social hierarchies remains undertheorized. Urban scholars have begun to highlight the importance of infrastructures and technologies in configuring access to essential goods and services. While this research provides key insights into how non-human entities mediate unequal relations, it has largely overlooked how certain animals – „political animals“ – also co-produce inequalities. This article focuses on two critical urban domains, security and public health, that are often characterized by stark inequalities, and takes the role of key animals within these domains – dogs and rats, respectively – as a new analytical entry-point. Security dogs are socialized to identify threatening individuals on the basis of classed and raced markers. Rats thrive in upscale neighborhoods with historical architecture and abundant green space – yet the public health risks and the stigma associated with these rodents may disproportionately affect low-income residents. Drawing on research on security dogs in Kingston, Jamaica and rats in Amsterdam, this talk discusses the role of animals in the formation of sociospatial boundaries, and the distribution of resources and risks across urban spaces and populations. Focusing on the interactions these two types of „political animals“ have with both humans and infrastructure, it sets out a research agenda for studying how animals’ everyday encounters with their cultural and material environments combine to result in (in-)equitable social outcomes.

Navigating occupational safety and health challenges in sustainable infrastructure projects: a comprehensive review

Ensuring occupational safety and health (OSH) is paramount in infrastructure projects due to their inherently high-risk nature and the increased likelihood of accidents. Despite its importance, numerous obstacles impede the successful adoption of OSH measures in these settings. Addressing these challenges is key to not only implementing OSH protocols effectively but also to improving working conditions and managing other operational facets like quality and environmental concerns, ultimately resulting in better infrastructure developments. Adopting proactive OSH strategies is crucial for preventing significant accidents and fostering a safety culture within infrastructure projects. This review focuses on identifying the primary obstacles and barriers to effective OSH in infrastructure projects, laying the groundwork for improving safety performance in the sector. It highlights organizational and legislative issues as the foremost challenges due to their direct impact on safety culture, resource distribution, compliance, and accountability. Although factors related to environmental and safety practices are deemed less critical, they are nonetheless vital for comprehensive risk management and the promotion of a safe working environment. Tackling these issues is imperative for cultivating a strong safety culture and safeguarding the health of workers on infrastructure projects. It is also essential to acknowledge the distinct OSH challenges presented by different construction scenarios to devise customized safety measures and effectively reduce risks. This review emphasizes the necessity of recognizing the unique aspects of each construction project, addressing specific dangers, and meeting regulatory demands to achieve thorough safety management.

Robotic-assisted free flap harvesting for diverse soft tissue reconstruction: a PRISMA scoping review of clinical outcomes over the last decade.

The aim of our study was to assess the advantages and limitations of robotic technology in diverse reconstructive procedures. A scoping review was conducted in Oct'23, on published studies from 2013 to 2023, focussing on robotic-assisted free flap harvesting. Three databases Ovid-MEDLINE, Scopus, and PubMed were searched. Original research studies reporting robotic-assisted free flap harvest were included. Studies on lesion excision, microvascular anastomosis, local flap harvest, roboticassisted flap inset, review articles, abstract-only studies, non-English documents, and animal studies were excluded from this review. Sixteen studies met the inclusion criteria out of a total of 318, searched initially. These studies included a total of 128 patients, who underwent robotic-assisted free flap harvest for the reconstruction of various defects, with 140 free flaps harvested. The most common flaps harvested by robotic technique were deep inferior epigastric artery perforator (DIEP) flap 120 (85.7%), radial forearm free (RFF) flap 11 (7.9%), latissimus dorsii flap 4 (2.9%), rectus abdominus flap 4 (2.9%), and omental flap 1 (0.7%). Breast reconstruction was the major procedure done i.e. 120 (85.7%) followed by head and neck 11 (7.9%) and limb defects 9 (6.4%) reconstruction procedures. The reported clinical outcomes were acceptable in all the studies with a 99% flap success rate and minimal complications. Variability in operating time was observed depending upon surgical steps undertaken with robotic systems. This scoping review highlights the role of robotic-assisted free flap harvesting in plastic surgery and its potential benefits on clinical outcomes, due to its high precision and minimal invasiveness. However, challenges like cost effectiveness, resource distribution and learning curve are there.

Financing education spending in the context of interbudgetary relations in the Republic of Kazakhstan

In the current conditions, education is endowed with strategic importance as a sphere of social activity that directly forms the level of intelligence of the population, ensuring competitiveness and innovation in the development of the country's economy. Therefore, the study’s relevance is because the educational capital obtained in the learning process is a combination of theoretical knowledge, practical skills, work experience, and personal characteristics that bring a person income during his career and stimulate further investment in education. Education impacts each citizen’s income and directly affects the economic development of the country, its financial capabilities, and national competitiveness. Thus, this article aims to reveal the critical aspects of republican and local financing of education in Kazakhstan and the prospects for its development. The methodological basis of the research is formed by a system of general scientific and unique research methods: synthesis, system-analytical analysis, and abstract-logical method. The critical result of the work is the systematization of acquisitions within the framework of the researched topic and the study of the features of optimizing the decentralization of education financing in Kazakhstan. Proposed: to increase the efficient distribution of financial resources at all levels of the budget system; increase the opportunities for educational institutions to raise additional funds through educational innovations, expand the list of paid services provided by such institutions; carry out decentralization of education, taking into account the characteristics of the regions, their production potential, the demographic situation and the interests of territorial communities. The results of this scientific study, as well as the conclusions formulated on their basis, are of significant importance both for the scientific community and for financial experts and practitioners from the educational field since they have a structured presentation of the material based on which logical and constructive conclusions are drawn, which may have an impact on the subsequent processes of reforming the financial provision of education in Kazakhstan.

Pengendalian Biaya Tenaga Kerja dalam Organisasi Sektor Publik: Studi tentang Pengelolaan Pegawai Tidak Tetap (PTT) dan Alternatif Outsourcing

This article discusses the management of labor costs in the public sector with a focus on the management of non-permanent employees (PTT) and outsourcing alternatives. This research highlights problems in personnel management, especially employee expenditure costs that must be borne by government agencies. This study reviews cost control systems, labor costs, and methods for managing honorary staff costs in government. The findings show that outsourcing is more efficient than recruiting PTT or temporary workers as a solution to control labor costs. Additionally, this paper recommends Activity Based Costing (ABC) method for public sector organizations to provide valuable information related to detailed cost data. This research shows that decentralizing recruitment in local governments can improve efficiency, effectiveness and fairness, but can also lead to corruption and disparities in the distribution of human resources. Cost control, outsourcing, and the use of Activity-Based Costing (ABC) can help public sector organizations manage costs and increase operational efficiency. To achieve better governance, operational efficiency and effective cost control, public sector organizations need to consider the various strategies and methods described in this research.

How to promote data sharing among enterprises based on dynamic evolutionary game analysis

ABSTRACT In traditional contexts, enterprises often hesitate to engage in data sharing due to the associated heightened risks and transaction costs. Blockchain technology, leveraging its encryption algorithms and smart contracts, effectively alleviates these challenges, thereby encouraging enterprises to actively participate in data sharing. The adoption of reasonable reward and penalty mechanisms can prevent opportunistic behaviours and stimulate data sharing among businesses. It is noteworthy that blockchain technology and data alliance have a mutually substitutive effect in terms of risk and communication costs, while they complement each other in regulatory and transaction costs. The integration of blockchain technology with data alliance can enhance collaborative revenue and reduce various costs. When distributing collaborative revenue, it is crucial to adhere to the guiding principle of ‘prioritizing efficiency while considering fairness’. Collaboration becomes a reality when all parties collectively achieve a substantial overall revenue threshold. Subsequently, in-depth exploration of fair resource allocation principles is crucial to ensure the equitable distribution of resources.

Macrofaunal diversity patterns in coastal marine sediments: re-examining common metrics and methods

Complex biodiversity patterns arise in marine systems due to overlapping ecological processes, including organism interactions, resource distribution, and environmental conditions. Despite the importance of documenting these patterns, describing diversity in natural ecosystems remains challenging. Here, we investigate 3 nearshore sub-Arctic sites to describe benthic macroinfaunal taxa and biological traits, with the ultimate aim of determining whether common diversity metrics and typical sampling efforts adequately capture community composition in these systems. First, we assess how diversity relates to sediment depth and examine relationships among commonly used taxonomic and functional diversity indices. Second, using a power analysis, we explore how sampling effort influences the interpretation of diversity patterns in coastal systems. We report significant variation in community composition among sites, even across small spatial scales of km, and find that taxonomically diverse communities do not necessarily correspond to high functional diversity. We further find that although environmental factors such as sediment depth consistently affect macroinfaunal diversity, the direction and magnitude of these relationships are site-dependent. Finally, we demonstrate that typical sampling effort for coastal benthic studies (for example, <5 push cores of ~7 cm diameter) may not capture macroinfaunal community composition adequately, potentially obscuring hotspots in common diversity metrics such as taxonomic or functional richness. However, indices such as Simpson’s diversity may be well-suited to resource-limited studies with restricted sampling capacity. Our results highlight the importance of adopting multi-pronged approaches to biodiversity assessment and determining optimal sample sizes for marine benthic systems, particularly in the context of biodiversity monitoring for conservation purposes.

Resource allocation modeling for autonomous prediction of plant cell phenotypes

Predicting the plant cell response in complex environmental conditions is a challenge in plant biology. Here we developed a resource allocation model of cellular and molecular scale for the leaf photosynthetic cell of Arabidopsis thaliana, based on the Resource Balance Analysis (RBA) constraint-based modeling framework. The RBA model contains the metabolic network and the major macromolecular processes involved in the plant cell growth and survival and localized in cellular compartments. We simulated the model for varying environmental conditions of temperature, irradiance, partial pressure of CO2 and O2, and compared RBA predictions to known resource distributions and quantitative phenotypic traits such as the relative growth rate, the C:N ratio, and finally to the empirical characteristics of CO2 fixation given by the well-established Farquhar model. In comparison to other standard constraint-based modeling methods like Flux Balance Analysis, the RBA model makes accurate quantitative predictions without the need for empirical constraints. Altogether, we show that RBA significantly improves the autonomous prediction of plant cell phenotypes in complex environmental conditions, and provides mechanistic links between the genotype and the phenotype of the plant cell.