Key Constraints Research Articles

Political freedom and financial inclusion: Unraveling social trust and political rent-seeking

This paper delves into the role of political rights in shaping financial inclusion. Despite the acknowledged significance of political institutions in influencing financial systems, there remains limited understanding of the economic origins of the impact of political institutions on financial inclusion. Utilizing data from the 2021 Global Findex database, the study finds that weak political rights significantly reduce the likelihood of individuals possessing financial accounts and using digital financial services. Robustness tests employing an instrumental variable and the difference-in-differences framework confirm that inadequate political rights have a detrimental effect on financial inclusion. By exploring the reasons for financial exclusion and moderating factors, this study provides supportive evidence for the mechanisms of eroded social trust and political rent-seeking as the key constraints that hinder inclusiveness in providing mainstream financial products and services.

Cool Gaseous Exoplanets: surveying the new frontier with Twinkle

ABSTRACT Cool gaseous exoplanets (1.75 R⊕ < Rp < 3 RJ, 200 K <Teq < 1000 K) are an as-yet understudied population, with great potential to expand our understanding of planetary atmospheres and formation mechanisms. In this paper, we outline the basis for a homogeneous survey of cool gaseous planets with Twinkle, a 0.45-m diameter space telescope with simultaneous spectral coverage from 0.5–4.5 μm, set to launch in 2025. We find that Twinkle has the potential to characterise the atmospheres of 36 known cool gaseous exoplanets (11 sub-Neptunian, 11 Neptunian, 14 Jovian) at an SNR ≥ 5 during its 3-yr primary mission, with the capability of detecting most major molecules predicted by equilibrium chemistry to >5σ significance. We find that an injected mass–metallicity trend is well recovered, demonstrating Twinkle’s ability to elucidate this fundamental relationship into the cool regime. We also find that Twinkle will be able to detect cloud layers at 3σ or greater in all cool gaseous planets for clouds at ≤10 Pa pressure level, but will be insensitive to clouds deeper than 104 Pa in all cases. With these results, we demonstrate the capability of the Twinkle mission to greatly expand the current knowledge of cool gaseous planets, enabling key insights and constraints to be obtained for this poorly charted region of exoplanet parameter space.

Uptake of Internet of Things by SMEs in digital era in emerging economies: A systematic literature review

This paper aims to establish the uptake of Internet of Things (IoT) by small and medium enterprises (SMEs) in the digital era in emerging economies. This study aims to 1) determine adoption of IoT by SMEs during digital era in emerging economies, 2) establish challenges faced by SMEs in implementing IoT in emerging economies, and 3) develop a framework for digital transformation for SMEs in digital era in emerging economies. Systematic literature review approach was used. Articles from Scopus database ranging from 2018 to 2023 was used. 57 articles were shortlisted out of 153 articles. PRISMA framework was therefore used to perform systematic review analysis. Results demonstrate that in emerging economies, SMEs do not or are slowly adopting IoT concepts, making them less competitive. The results also determine that although IoT has great promise in SMEs, the key constraint is a lack of strategic implementation frameworks for its deployment and widespread adoption. This study was therefore carried out to develop a framework that supports digital transformation for SMEs in the digital era for emerging economies. Results have significant managerial and practical implications as they offer some insights to SME managers on how they can improve on the uptake and adoption of internet of things in digital era.

Tumor-immune metaphenotypes orchestrate an evolutionary bottleneck that promotes metabolic transformation.

Metabolism plays a complex role in the evolution of cancerous tumors, including inducing a multifaceted effect on the immune system to aid immune escape. Immune escape is, by definition, a collective phenomenon by requiring the presence of two cell types interacting in close proximity: tumor and immune. The microenvironmental context of these interactions is influenced by the dynamic process of blood vessel growth and remodelling, creating heterogeneous patches of well-vascularized tumor or acidic niches. Here, we present a multiscale mathematical model that captures the phenotypic, vascular, microenvironmental, and spatial heterogeneity which shapes acid-mediated invasion and immune escape over a biologically-realistic time scale. The model explores several immune escape mechanisms such as i) acid inactivation of immune cells, ii) competition for glucose, and iii) inhibitory immune checkpoint receptor expression (PD-L1). We also explore the efficacy of anti-PD-L1 and sodium bicarbonate buffer agents for treatment. To aid in understanding immune escape as a collective cellular phenomenon, we define immune escape in the context of six collective phenotypes (termed "meta-phenotypes"): Self-Acidify, Mooch Acid, PD-L1 Attack, Mooch PD-L1, Proliferate Fast, and Starve Glucose. Fomenting a stronger immune response leads to initial benefits (additional cytotoxicity), but this advantage is offset by increased cell turnover that leads to accelerated evolution and the emergence of aggressive phenotypes. This creates a bimodal therapy landscape: either the immune system should be maximized for complete cure, or kept in check to avoid rapid evolution of invasive cells. These constraints are dependent on heterogeneity in vascular context, microenvironmental acidification, and the strength of immune response. This model helps to untangle the key constraints on evolutionary costs and benefits of three key phenotypic axes on tumor invasion and treatment: acid-resistance, glycolysis, and PD-L1 expression. The benefits of concomitant anti-PD-L1 and buffer treatments is a promising treatment strategy to limit the adverse effects of immune escape.

Compound drought and hot stresses projected to be key constraints on maize production in Northeast China under future climate

Climate change and the increasing frequency of climate extremes associated with warming have been the most important climatic stressors for maize production. However, crop-model based assessments of the major determinants of yield variability at regional scale under future climate conditions are still underrepresented. In this study, we simulated maize yield in Northeast China at a reference period (1986–2005), and two future periods (2030 s: 2020–2039, 2050 s: 2040–2059) of Shared Socioeconomic Pathways (SSPs) of SSP1-2.6, SSP2-4.5 and SSP5-8.5 using Agricultural Production sIMulator (APSIM). We first characterized the variations of maize yield under climate change based on the simulations, and further investigated the key determinants of yield variability using machine learning techniques. The results suggest that maize yield would decrease by 14.8 % to 19.6 % (depending on the climate scenarios) compared to the reference period without adaption. Random forest performed best in explaining yield variability in a suite of machine learning models (extreme gradient boosting, gradient boosting, classification and regression tree, ridge and lasso regression and random forest), with a mean R2 of 0.77, a mean RMSE of 1239.2 kg/ha, a mean MAE of 885.1 kg/ha. Extreme climate indicators show a greater ability to explain yield variability in over half agro-ecological regions under higher warming levels such as SSP5-8.5. Cumulative precipitation (CPR) and compound drought and hot days (CDH) during growing seasons are the most important mean and extreme climate indicators affecting yield variability, respectively. Moreover, the effect sizes of CPR and CDH on yield variability are 1898 kg/ha and 5596 kg/ha, respectively. Therefore, CDH will be a key constraint on maize production. Future adaptive measures such as irrigation, breeding hot- or drought-tolerant cultivars should be implemented to enhance the resilience of maize crops in the face of climate change.

Integrating Artificial Intelligence for Academic Advanced Therapy Medicinal Products: Challenges and Opportunities

Cell and gene therapies represent promising new treatment options for many diseases, but also face challenges for clinical translation and delivery. Hospital-based GMP facilities enable rapid bench-to-bedside development and patient access but require significant adaptation to implement pharmaceutical manufacturing in healthcare infrastructures constrained by space, regulations, and resources. This article reviews key considerations, constraints, and solutions for establishing hospital facilities for advanced therapy medicinal products (ATMPs). Technologies like process analytical technology (PAT), continuous manufacturing, and artificial intelligence (AI) can aid these facilities through enhanced process monitoring, control, and automation. However, quality systems tailored for product quality rather than just compliance, and substantial investment in infrastructure, equipment, personnel, and multi-departmental coordination, remain crucial for successful hospital ATMP facilities and to drive new therapies from research to clinical impact.

Oxygen Isotope Fractionation between Carbonate Minerals and Carbonic Acid Systems and Constraints for Environmental Science and Geological Processes

The equilibrium oxygen isotope fractionation factor is widely used in geological thermometry. However, under most natural conditions, the oxygen isotope exchange is rare to reach equilibrium. Especially for the complex water–rock interaction process, the contribution of the H2CO3 solution, CO32− solution, Ca(HCO3)2 solution, and CaCO3 solution to the equilibrium oxygen isotope fractionation factor of this process is poorly understood. In view of this predicament, these key parameters are obtained by ab initio calculations. The results showed that the contributions of different carbonate minerals and different aqueous solutions to the equilibrium oxygen isotope fractionation factor were different. Among all nine carbonate minerals (dolomite, calcite, aragonite, magnesite, siderite, otavite, smithsonite, ankerite, and strontianite), the minerals with the highest and lowest reduced partition function ratios (RPFR) were siderite and strontianite, respectively. At the same time, the RPFR of nitratine, which has the same structure as carbonate, was studied. The RPFRs of the three most widely distributed carbonates in nature (dolomite, calcite, and aragonite) were dolomite > calcite > aragonite. Among the H2CO3 solution, CO32− solution, Ca(HCO3)2 solution, and CaCO3 solution, the H2CO3 solution had the strongest ability to enrich 18O. In addition, the equilibrium oxygen isotope fractionation factors between aqueous solutions and gas phase species (CO2(g), H2O(g), and O2(g), etc.) were calculated systematically. The results showed that the oxygen isotope fractionation factors between solutions and gas phases were often inconsistent with the temperature change direction and that the kinetic effects played a key role. These theoretical parameters obtained in this study will provide key equilibrium oxygen isotope constraints for water-rock interaction processes.

An ecological approach for skill development and performance in soccer goalkeeper training: Empirical evidence and coaching applications

ABSTRACT Ecological approaches in sport consider that athletes adapt to properties of the task and the surrounding environment. Thus, task and environment are key constraints of performance. Yet, the influence of task and environmental constraints on athletes’ performance needs empirical examination, especially in sport-specific contexts such as soccer goalkeeping. This study aimed to examine if and how task and environmental constraints influenced goalkeepers (GKs’) performances. We monitored performance coefficients of two professional female GKs across 13 training tasks that varied based on 9 constraints, referring to both interactions among athletes and properties of the surrounding landscape. Results showed that constraints explain ~ 47% of the observed variability in GKs’ performances. Numerical complexity (i.e., the potential interactions between athletes) showed a major influence on performance, which indicates that number of interactions among athletes may constrain GKs’ perceived opportunities for action. Field dimensions and landscape representativity (including elements such as penalty area(s), target goal(s) and constraints for shooting) showed positive relationships with performance, supporting that training designs retaining closer proximity to the game may benefit GKs’ performances. Overall, results supported that athlete-environment couplings could be understood as a multifactorial model and hence, a combination of task constraints are necessary for designing effective learning environments.

EU constitutional dismantling through strategic informalisation: Soft readmission governance as concerted dis‐integration

AbstractThis contribution takes issue with what I have called the ‘constitutional dismantling’ of external migration policy through the tactical informalisation of readmission cooperation. It maps out the strategic use of soft law mediating the tacit approval or active involvement of the main EU actors. The strategy is supposed to enhance policy outcomes but is at the expense of foundational principles. The principles of conferral, institutional balance, and sincere/loyal cooperation impose key constraints on EU/Member State action that the choice for soft law ignores. My main contention is that this is not an unintended consequence, but a deliberate or, at least, tolerated result, amounting to a form of ‘concerted dis‐integration’ pursued by the very actors supposed to guard the EU integration project in line with Treaty provisions. The approach denotes the instrumentalisation of legal mechanisms for the advancement of policy objectives, embracing a regulation‐without‐legitimation paradigm that unravels the EU’s constitutional framework.

Efficient rebar bundling: vision robotics innovations

ABSTRACT The application of vision robots in rebar bundling operations has aroused great interest in the industry. The performance cost and complex application environment have become the key constraints to its development. Based on this, in this paper, we firstly design a rebar bundling intersection image acquisition system for rebar intersections in complex environments; secondly, we use GhostNet to lighten the backbone network and combine the Convolutional Block Attention Module (CBAM) and Bidirectional Feature Pyramid Network (BiFPN) with the neck to improve the adaptive ability to the complex environments; and finally, in order to make our network has better robustness, we try to introduce Distance Intersection Union (DIoU) in the network and verify the performance of the improved model through comparison and ablation experiments. The experimental results show that the mAP, accuracy and recall of the improved YOLOv5 model are 97.8%, 95.6% and 95.4%, which are 1.1%, 0.9% and 0.1% higher than that of YOLOv5s, respectively. Meanwhile, computational quantization and parameter quantization are reduced by 36% and 34%, respectively. This indicates that our proposed improved network has better intersection detection performance and also provides favorable conditions for deployment in robotic systems.

A test of balanced fitness limitations theory: Pollen limitation in plants.

When reproductive success is determined by the relative availabilities of a series of essential, non-substitutable resources, the theory of balanced fitness limitations predicts that the cost of harvesting a particular resource shapes the likelihood that a shortfall of that resource will constrain realized fitness. Plant reproduction through female function offers a special opportunity to test this theory; essential resources in this context include, first, the pollen received from pollinators or abiotic vectors that is used to fertilize ovules, and, second, the resources needed to provision the developing seeds and fruit. For many plants realized reproductive success through female function can be readily quantified in the field, and one key potential constraint on fitness, pollen limitation, can be assessed experimentally by manually supplementing pollen receipt. We assembled a comparative dataset of pollen limitation using only studies that supplement pollen to all flowers produced over the plant's reproductive lifespan. Pre- and post-pollination costs were estimated using the weight of flowers and fruits and estimates of fruit set. Consistent with expectations, we find self-incompatible plants make greater pre-pollination investments and experience greater pollen limitation. However, contrary to theoretical expectations, when variation due to self-compatibility is accounted for by including self-compatibility in the statistical model as a covariate, we find no support for the prediction that plants that invest more heavily in pre-pollination costs are subject to greater pollen limitation. Strong within-species, between-population variation in the expression of pollen limitation makes the quantification of mean pollen limitation difficult. We urge plant ecologists to conduct more studies of pollen limitation using whole-plant pollen supplementation to produce a richer comparative dataset that would support a more robust test of the balanced limitations hypothesis.

Study on the mechanical properties and microstructure of recycled brick aggregate concrete with waste fiber

Abstract Recycled concrete technology can promote the sustainable development of the construction industry, but the insufficient mechanical properties of recycled concrete have become a key constraint on its development. By adding waste fibers, the mechanical properties of recycled concrete can be improved, and the problem of disposing of waste polypropylene fibers can be solved. In this article, the effects of recycled brick aggregate content and waste fiber content on the mechanical properties and microstructures of recycled brick aggregate concrete through macroscopic mechanical experiments and microstructure experiments are investigated. The results show that the addition of recycled brick aggregate reduces the mechanical properties of concrete; when the content of recycled brick aggregate is 100%, the compressive strength and splitting tensile strength decrease by 22.04 and 20.00%, respectively. The addition of waste fibers can improve the mechanical properties of recycled brick aggregate concrete, but it is necessary to control the contents of waste fibers in a certain range. When the content of waste fibers is 0.08%, the best improvement effect on the mechanical properties of concrete is achieved; the compressive strength of concrete with a 50% (100%) recycled aggregate replacement rate increases by 6.06% (8.90%), while the splitting tensile strength of concrete with a 50% (100%) recycled aggregate replacement rate increases by 2.30% (6.16%). Through microstructural analysis, the mechanism by which waste fiber improves the mechanical properties of recycled brick aggregate concrete is revealed. The addition of waste fibers has the effect of strengthening the framework inside the recycled brick aggregate concrete, forming a good structural stress system and allowing the recycled brick aggregate concrete to continue to bear loads after cracking. In this study, waste brick aggregate and waste fiber are effectively utilized, which can not only reduce pollution to the environment but also realize the sustainable utilization of resources.

Enhancement and Broadening of the Internal Electric Field of Hole-Transport-Layer-Free Perovskite Solar Cells by Quantum Dot Interface Modification.

Hole-transport-layer-free perovskite solar cells have attracted strong interest due to their simple structure and low cost, but charge recombination is serious. Built-in electric field engineering is an intrinsic driver to facilitate charge separation transport and improve the efficiency of photovoltaic devices. However, the enhancement of the built-in electric field strength is often accompanied by the narrowing of the space charge region, which becomes a key constraint to the performance improvement of the device. Here, we propose an effective regulation method, the component engineering of quantum dots, to enhance the strength of the built-in electric field and broaden the range of space charge. By using all inorganic CsPbBrxI3-x (x = 0, 1, 2, 3) quantum dot interface modification to passivate the defects of MAPbI3 perovskite films, the regulation law of quantum dot components on the work function of perovskite films was revealed, and the mechanism of their influence on the internal electric field intensity and space charge region distribution was further clarified, thereby fundamentally solving the serious problem of charge recombination. As directly observed by electron-beam-induced current (EBIC), the introduction of CsPbBr2I quantum dots can effectively enhance the interfacial electric field intensity, widening the space charge region from 160 to 430 nm. Moreover, the efficiency of the hole-free transport layer perovskite solar cells modified by CsPbBr2I quantum dots was also significantly enhanced by 1.5 times. This is an important guideline for electric field modulation and efficiency improvement within photovoltaic devices with other simplified structures.

Bright z ∼ 9 Galaxies in Parallel: The Bright End of the Rest-frame UV Luminosity Function from HST Parallel Programs

The abundance of bright galaxies at z > 8 can provide key constraints on models of galaxy formation and evolution, as the predicted abundance varies greatly when different physical prescriptions for gas cooling and star formation are implemented. We present the results of a search for bright z ∼ 9–10 galaxies selected from pure parallel Hubble Space Telescope (HST) imaging programs. We include 132 fields observed as part of the Brightest of Reionizing Galaxies survey, the Hubble Infrared Pure Parallel Imaging Extragalactic Survey, and the WFC3 Infrared Spectroscopic Parallel survey. These observations cover a total of 620 arcmin2, about 70% of which is also covered with Spitzer Space Telescope infrared imaging. We identify 13 candidate galaxies in the range 8.3 < z < 11 with 24.5 < m H < 26.5 (−22.9 < M UV < −21.2), 11 of which constitute new discoveries. This sample capitalizes on the uncorrelated nature of pure parallel observations to overcome cosmic variance and leverages a full multiwavelength selection process to minimize contamination without sacrificing completeness. We perform detailed completeness and contamination analyses, and present measurements of the bright end of the UV luminosity function using a pseudobinning technique. We find a number density consistent with results from Finkelstein et al. and other searches in HST parallel fields. These bright candidates likely reside in overdensities, potentially representing some of the earliest sites of cosmic reionization. These new candidates are excellent targets for follow up with JWST, and four of them will be observed with the NIRSpec prism in Cycle 1.

Weather Variables for Within-Vineyard Awareness of Botrytis Risk

Background and Aims. Botrytis bunch rot (BBR) in cool temperate climates is a key constraint to the consistent supply of grapes to winery specifications. BBR severities have been correlated with specific environmental conditions; however, data-driven applications intended to support crop protection decisions are restricted in access and/or of unknown commercial value. The aims of this study were to evaluate variables providing within-vineyard awareness of BBR risk in Riesling vines. Methods and Results. Descriptors of BBR epidemics from eight site years, 2009–2014, were developed for vine areas of ∼0.5 ha within two regions of Tasmania with different climates. Two variables using the daily Bacchus index, from crop stage E-L 19 to E-L 31 or 34, accounted for &gt;80% of the variance in the final mean BBR severity. A BBR risk index (BBR-I), incorporating the mean daily Bacchus index from E-L 19 to E-L 31 and the median daily vapour pressure deficit of air at 15 : 00 during the late-season interval, accounted for up to 99.5% of the variance in the final mean BBR severity. The late-season interval (days) or median daily RH (%) at 15:00 in the same period accounted for 86.4 or 83.3% of the variance. Spatial variability of BBR severity mapped in 4.8 ha of Sauvignon Blanc in 2018-19 confirmed the need to apply BBR risk indicators at an appropriate spatial scale. Conclusions. Environmental variables with biological relevance served as indicators of BBR risk at the study sites and have the potential to discriminate BBR risk among production regions in Tasmania. Significance of the Study. Study findings are expected to support the development of applications that raise awareness of BBR risk at an appropriate spatial scale for in-season adaption of crop protection, diagnosis of crop protection efficacy, and/or site selection decisions. Accompanying formulae with sample data in Microsoft® Excel will support transitions to automated data analyses.

Decoding and preserving Indonesia's iconic Keris via A CNN-based classification

The present study explores the domain of Keris classification by employing advanced Convolutional Neural Networks (CNNs) as a potent technique for identifying subtle patterns and cultural characteristics inherent in these renowned Indonesian daggers. The study has presented encouraging findings about the identification of Pamor, Dhapur, and Tangguh categories. However, it is crucial to recognise and confront the inherent constraints associated with this research. The key constraints of the study pertain to the diversity of data, accuracy of labeling, generalizability of the model, and ethical considerations. The acquisition of a comprehensive dataset that effectively encompasses the whole range of Keris patterns offers a significant obstacle. Furthermore, it is crucial to pay careful attention to the accuracy of labeling, since it can be influenced by the subjective character of Keris classification. The important worry lies in guaranteeing the model's capacity to generalise to Keris images that have not been previously encountered, as well as its ability to comprehend and explain its decision-making process. The careful establishment of ethical frameworks is necessary to address ethical problems related to cultural sensitivity and the potential misuse of AI outputs in the realm of cultural heritage. Nevertheless, these constraints offer significant perspectives on potential areas for future investigation and enhancement. Future endeavours may prioritise the augmentation and broadening of the dataset, fostering collaboration with specialists in cultural domains, improving the interpretability of the model, and effectively addressing ethical considerations. The present study not only exhibits potential for expanding artificial intelligence in the domain of cultural preservation, but also contributes to a more profound understanding and recognition of the complex artistry and historical significance encapsulated within the Keris.

The distribution of insect pests and the associated loss of stored sorghum in the Kena district of Konso Zone, South-Western Ethiopia.

Sorghum is a staple crop grown in the poorest and most food-insecure regions of Ethiopia. But storage insect pests are its key constraints that have been causing considerable loss. Accordingly, an assessment of the prevalence of insect pests and the associated loss of sorghum stored under farmers' traditional storages was done in randomly selected major sorghum-growing kebeles of Kena District using a nested design between November 1, 2019 and December 30, 2020. It was conducted through the sampling of one kg of grain from a total of 360 randomly selected farmers' storages. Pests' abundance was determined by dividing the total number of individual species by the total number of samples. A count and weight method was used to estimate percent grain damage and weight loss by pests. Sitophilus zeamais, Sitophilus oryzae, Sitotroga cereallella, Tribolium castaneum, Tribolium confusum, Cryptolestes ferrugineus, Cryptolestes pusillus, Rhyzopertha dominica, and Plodia interpunctella were the pests identified from grain samples. When compared to mid-latitude, where they were found in the range between 2.36± 0.21 and 17.50±0.98 mean number of species, all of these pests had a considerably (p < 0.05) larger distribution in low-land kebeles, where they predominated in the range between 5.44±2.00 and 23.61±1.75 amean number. During the nine-month storage period, the degree of pest infestation, percentage of grain damage, and weight loss were significantly (p < 0.05) higher in the bamboo bins when no management measures were implemented in the mid-land and low-land kebeles, respectively, than in the barn. Consequently, bamboo bin storage was considered ineffective for sufficient sorghum grain protection against pests and the associated loss over a longer storage period. But barn storage and the use of cultural pest management practices performed better in protecting stored sorghum from pests. Therefore, improving the bamboo bin storage method is needed to improve its grain protection efficacy.

Research on energy-saving optimization method for central air conditioning system based on multi-strategy improved sparrow search algorithm

Aiming at the problem of high energy consumption caused by the nonlinear, strong coupling, and large hysteresis characteristics of central air conditioning (CAC) system, an energy-saving optimization method based on WTD–CNN–LSTM and multi-strategy improved sparrow search algorithm (MISSA) is proposed, which works to minimize the total energy consumption during the operation of the CAC system. Firstly, minimize the sum of energy consumption of chillers, freezing pumps, cooling pumps, and cooling towers as the objective function, and use the range of operating parameters of each equipment as the basic constraint conditions to establish an energy-saving optimization model for the CAC system. Then, WTD–CNN–-LSTM is used to predict the future cooling load, and the predicted results are used as key constraint condition to achieve on-demand cooling. Finally, MISSA is proposed to improve the initialization, update and convergence stages of the CAC system operation parameter optimization process, accurately obtaining the optimal operating parameters. Compared with manual experience, MISSA reduces energy consumption by 15.32 % and improves energy efficiency ratio by 20.76 %. Meanwhile, compared with other optimization algorithms, MISSA reduces energy consumption by 4.85–13.26 % and improves energy efficiency ratio by 6.53–16.33 % after optimizing the CAC system. The experiment verifies that MISSA is more energy efficient when applied to the CAC system and has the advantages of accuracy, fast convergence, strong global search capability, and the ability to jump out of local optimization.

RPRA: Reputation-based prioritization and resource allocation leveraging predictive analytics and vehicular fog computing

Predictive analytics and vehicle fog computing (VFC) have emerged as important methodologies for enabling seamless and instantaneous access to storage and information in real-time and facilitating the execution of resource-hungry smart applications. VFC-enabled IoT devices that use predictive analytics efficiently can process data in a timely manner. However, besides time sensitivity, better security and privacy solutions for several such smart systems, such as smart healthcare systems, are essential but have rarely been developed so far. With the nature of healthcare information being personal-specific and trust being of paramount significance, our research aims to fill a gap by proposing reputation-based prioritization and resource allocation (RPRA). It is a VFC-enabled framework for time-sensitive, computationally resource-deficient smart healthcare IoT devices that uses latency and energy as key constraints. RPRA is a subjective logic-based heuristic approach that uses context-dependent, indirect, and perceived reputation-based trust. Our method minimizes trust bias and trust-based assaults and uses static weight allocation and a specialized algorithm that guarantees utility maximization. We employed three distinct key metrics, i.e., individual perception, real-time perception, and marginal perception, to identify rogue nodes with hostile intent and remove them from active participation. In a dynamic VFC-enabled healthcare system, our approach outperforms in terms of utility-based reputation values with the highest range on the scale of [0,70] and the least algorithmic complexity.

Constraints and opportunities in harvesting woody biomass: perspectives of foresters and loggers in the Northeastern United States

ABSTRACT Extensive forest resources make the Northeastern United States a promising source of woody biomass. Managing overstocked stands, common to the region, has been a major challenge due to a significant proportion of the harvest being low-value products. There are also various socio-economic and ecological factors that constrain the harvest decision. The objectives of the study were to compare and identify the key components, circumstances, and constraints related to the harvesting of small-diameter trees (SDT), regionally; to test if the responses varied between different job and experience categories; and to understand the perspectives of foresters and loggers to improve the current constraints. An online survey with 270 inputs from foresters and loggers in the Northeastern United States showed that, on average, 24% of the total harvest residue comprised small-diameter trees. The strongest agreement was on utilizing woody biomass for bioenergy and institutional heat energy. The primary reason for harvesting woody biomass was to satisfy the landowner’s objectives and for maintaining aesthetic value. The major constraints in woody biomass harvesting were the lack of markets and higher trucking distance. Respondent recommendations strongly emphasized the need for new and improved markets, infrastructure, and increased support from government.