Common Constraints Research Articles

Modeling building energy self-sufficiency of using rooftop photovoltaics on an urban scale

The significant contribution of buildings to global energy-related CO2 emissions and climate change has led to projections of a carbon–neutral building stock by 2050. This study evaluates the potential contribution of rooftop photovoltaics to urban energy self-sufficiency by developing an enhanced CityBEM framework, our in-house urban building energy model (UBEM). This methodology enables city-scale, simultaneous simulations of building energy use and rooftop photovoltaic retrofitting with low computational time. CityBEM’s robustness and high spatiotemporal resolution facilitate transient simulations of individual buildings with diverse usage types across large urban areas, addressing common computational constraints and input data limitations in UBEM applications. The rooftop photovoltaic model in CityBEM utilizes a comprehensive approach with physics-based modeling of crystalline PVs, model validation, and a proper design of array networks to manage self-shading effects. More than 57,000 buildings with a combined footprint of 32.37 million square meters are located in the simulation test case covering downtown Montreal (Quebec, Canada) and the surrounding areas. Results indicate that rooftop PV adoption in these buildings could potentially generate 5.9 TWh of electricity annually, reduce energy demand by 27.3%, and achieve an average annual energy saving of 40%. This local generation could also reduce operational CO2 equivalent emissions by over 0.2 megatons. Overall, this study highlights the significant potential of rooftop photovoltaics for a cleaner, more energy self-sufficient urban future.

Heat Stress in Beef Cattle: Climate Change and the Global Scenario – A Review

Abstract With the increasing human population and urbanization, the demand for animal origin products is going to grow, especially in the developing nations till the 2050s and the production needs to be escalated and optimized with the changing climate. Heat stress is known to reduce the animal performance, production, shelf life and meat quality in all animals. The beef cattle are globally reared, following different managemental practices, so the usage of natural resources like land and water, manpower, fodders, production systems and the environmental impact also varies profoundly. Recent changes in the climate, global warming and depletion of resources have severely affected the production and heat stress is now a common constraint all over the world. Due to evolutionary diversification the tropical and temperate breeds are comparatively more thermotolerant, but the beef cattle in the colder regions are vulnerable to high environmental temperatures. Also, the production of beef increases the carbon footprint and is much less eco-friendly than growing plant-based protein. So, we comprehended the environmental temperature variation over the continents and impact of heat stress on beef cattle. Also, other factors like cattle population, land and pasture usage, livestock units in trade, methane emissions and gross beef production value were examined to evaluate the collective impact of all these on the beef sector. Our findings and predictions reveal that, in the advent of climate change, depleting natural resources and rise in the greenhouse gases, beef production will be a constant challenge, which can be only achieved by maintaining a healthy cattle population and optimum usage of natural resources. Only then can the beef sector be efficient, sustainable, and a profitable enterprise in future.

Learning Constrained Dynamic Correlations in Spatiotemporal Graphs for Motion Prediction.

Human motion prediction is challenging due to the complex spatiotemporal feature modeling. Among all methods, graph convolution networks (GCNs) are extensively utilized because of their superiority in explicit connection modeling. Within a GCN, the graph correlation adjacency matrix drives feature aggregation, and thus, is the key to extracting predictive motion features. State-of-the-art methods decompose the spatiotemporal correlation into spatial correlations for each frame and temporal correlations for each joint. Directly parameterizing these correlations introduces redundant parameters to represent common relations shared by all frames and all joints. Besides, the spatiotemporal graph adjacency matrix is the same for different motion samples, and thus, cannot reflect samplewise correspondence variances. To overcome these two bottlenecks, we propose dynamic spatiotemporal decompose GC (DSTD-GC), which only takes 28.6% parameters of the state-of-the-art GC. The key of DSTD-GC is constrained dynamic correlation modeling, which explicitly parameterizes the common static constraints as a spatial/temporal vanilla adjacency matrix shared by all frames/joints and dynamically extracts correspondence variances for each frame/joint with an adjustment modeling function. For each sample, the common constrained adjacency matrices are fixed to represent generic motion patterns, while the extracted variances complete the matrices with specific pattern adjustments. Meanwhile, we mathematically reformulate GCs on spatiotemporal graphs into a unified form and find that DSTD-GC relaxes certain constraints of other GC, which contributes to a better representation capability. Moreover, by combining DSTD-GC with prior knowledge like body connection and temporal context, we propose a powerful spatiotemporal GCN called DSTD-GCN. On the Human3.6M, Carnegie Mellon University (CMU) Mocap, and 3D Poses in the Wild (3DPW) datasets, DSTD-GCN outperforms state-of-the-art methods by 3.9%-8.7% in prediction accuracy with 55.0%-96.9% fewer parameters. Codes are available at https://github.com/Jaakk0F/DSTD-GCN.

Leaching and vertical distribution of Fe and Zn citrate nanoparticles in Indian red soil

This research aims to address common constraints in the effective utilization of plant nutrients in soil, such as fixation, mobility, leaching, and reactions with soil colloids. To mitigate these issues, Fe and Zn citrate nanoparticles were synthesized and applied as nanochelators in a reconstructed soil profile column. We evaluated the mobility, release, and leaching behaviors of these nanoparticles. Results revealed that, no leaching of Fe and Zn citrate nanoparticles occurred even after a 90-day incubation. The release profiles exhibited a peak at 60 and 90 days for Fe and Zn respectively. In the mobility studies, Fe and Zn availability was highest in the 0–15 cm soil depth. Fe citrate and Zn citrate nanoparticles demonstrated the highest availability at 264.7 mg/kg and 86.26 mg/kg of soil, respectively as compared with commercial samples. The superior performance of Fe and Zn citrate nanoparticles was observed in terms of reduced leaching and improved accessibility, indicating their potential as efficient and environmentally-friendly plant nutrient sources. The study concludes that Fe and Zn citrate nanoparticles are stable nutrient sources that can enhance plant use efficiency with minimal environmental impact.

Measurement and optimization method for aero-engine rotors based on binocular multi-line laser sensing and virtual assembly

During the assembly of aero-engine rotors, eccentricity and tilt errors along the radial and axial direction result in uneven loading along the mating surface, which significantly impacts the operational lifespan of the rotor. This paper proposes a three-dimensional contour measurement system based on binocular multi-line laser sensing and conducts an aircraft engine rotor stacking virtual assembly technology system, to response the practical requirements of aircraft engine rotor unit production assembly engineering. We combine multi-line structured light active projection device with the binocular stereo vision model to construct the contour measurement system, which enhances the surface features of the projected object by adhering to the common constraint of structured line and stereo vision. Furthermore, the error propagation model for multi-stage rotor assembly to investigate the mechanism of error impact is established aiming to facilitate quantitative research on virtual assembly mechanisms. By manipulating the rotor phases and evaluating the coaxiality under various conditions, effective prediction of phase variation can be achieved, the multi-objective benchmark virtual assembly method based on the error propagation model of multi-stage rotor coaxiality is presented. The experimental results indicate that the proposed measurement system achieves the maximum disparity between the spatial data points procured by the proposed measurement system and the predetermined value of 2.1 μm, and the maximum disparity between the target plane’s average movement distance and the preset value of 3.7 μm. The precision provided by this system effectively meets the objective of assembly phase optimization for multi-stage rotors. In the empirical experiment conducted on the three-stage rotors, both systems yielded identical optimized phases: 0° for the first-stage rotor, 270° for the second-stage rotor, and 120° for the third-stage rotor, thereby validating the efficacy of the proposed measurement and optimization method for aero-engine multi-stage rotors with virtual assembly.

Integration of new zircon U–Pb ages with biostratigraphy to establish a high-precision age model of the Miocene Nakayama Formation on Sado Island in Central Japan

The most common age constraint for the diatomaceous sediments is biostratigraphy of siliceous microfossils. Although biostratigraphy is a powerful tool to establish stratigraphy and correlate with sedimentary sequences in other sites, biostratigraphy generally includes uncertainties difficult to evaluate. In this study, we measured zircon U–Pb ages of eight tuff beds intercalated with diatomaceous mudstone of the Nakayama Formation on Sado Island in Central Japan and integrated the U–Pb ages with diatom and radiolarian biostratigraphy, whose ages and errors were re-evaluated by this study, to establish an age model precisely representing the sedimentary age. Two tuff beds in the upper and middle part of the formation offered zircon U–Pb ages of 6.7 ± 0.2 Ma and 10.87 ± 0.07 Ma, which are consistent with biostratigraphy, and provided a good example of effective integration of zircon U–Pb ages with the biostratigraphy. On the other hand, zircon U–Pb ages of the other six tuff beds in the lower part are around 12 Ma and not distinguishable from each other. In addition, older zircon grains in the 6 tuff beds are assembled in the interval from 30 to 20 Ma, which is consistent with the age of the volcanic basement rocks forming most part of Sado Island. Similarities in chemical compositions of glass shards and age distributions of zircon grains indicate that the volcaniclastic components in the tuff beds should originate from single or associated magmatic activities.

Cell Formation Problem with Alternative Routes and Machine Reliability: Review, Analysis, and Future Developments

The Cell Formation Problem (CFP) is a widely studied issue that aims to group machines effectively based on criteria such as productivity, lower costs, and greater efficiency. In recent years, more characteristics were summarized relating to this problem. This paper provides a bibliographic examination of methodologies addressing the CFP in cellular manufacturing, focusing on novel approaches such as alternative routes and machine reliability. The articles were obtained from Scopus and Web of Science and filtered using the PRISMA methodology. Classification based on objective functions, constraints, and methodologies facilitated informative visualizations for analysis. Findings indicate a focus on capital utilization optimization, with cost reduction via intercellular moves minimization as the primary objective. Common constraints include limits on the number of machines per cell, restricting machines to a single cell and singular production routes per part. The genetic algorithm predominates as a non-exact solution approach, while the “ε-constraint” method is commonly used. This study offers insights into contemporary trends in solving the CFP with alternative routings and machine reliability, aiding researchers and professionals in the field to improve the quality of their investigations.

Numerical simulations of the acoustic and electrical properties of digital rocks based on tetrahedral unstructured mesh

Abstract Unconventional reservoirs typically exhibit strong heterogeneity leading to a significant scale effect in digital rock physics simulations. To ensure the reliability of the simulation results, improving computational efficiency and increasing sample sizes are crucial. In this study, we present a numerical finite element simulation method for the acoustic and electrical properties of digital rock cores based on tetrahedral unstructured meshes. We calculated the elastic moduli and electrical resistivity of the Fontainebleau sandstone digital rock samples. A comparison was made between the tetrahedral mesh and the traditional voxel-based hexahedral mesh in terms of the accuracy and efficiency of finite element numerical simulations. The results indicate that this numerical simulation method based on the tetrahedral mesh exhibits high accuracy comparable to experimental results, and its computational efficiency is significantly improved compared to the traditional hexahedral mesh method. These findings highlight the advantages of this finite element simulation method in improving the computational scale and efficiency of digital rock simulations. It effectively addresses common computational resource constraints in dealing with large-scale core systems and facilitates better integration with engineering construction, well-logging instrument simulations, and production applications.

PELMI: Realize robust DNA image storage under general errors via parity encoding and local mean iteration.

DNA molecules as storage media are characterized by high encoding density and low energy consumption, making DNA storage a highly promising storage method. However, DNA storage has shortcomings, especially when storing multimedia data, wherein image reconstruction fails when address errors occur, resulting in complete data loss. Therefore, we propose a parity encoding and local mean iteration (PELMI) scheme to achieve robust DNA storage of images. The proposed parity encoding scheme satisfies the common biochemical constraints of DNA sequences and the undesired motif content. It addresses varying pixel weights at different positions for binary data, thus optimizing the utilization of Reed-Solomon error correction. Then, through lost and erroneous sequences, data supplementation and local mean iteration are employed to enhance the robustness. The encoding results show that the undesired motif content is reduced by 23%-50% compared with the representative schemes, which improves the sequence stability. PELMI achieves image reconstruction under general errors (insertion, deletion, substitution) and enhances the DNA sequences quality. Especially under 1% error, compared with other advanced encoding schemes, the peak signal-to-noise ratio and the multiscale structure similarity address metric were increased by 10%-13% and 46.8%-122%, respectively, and the mean squared error decreased by 113%-127%. This demonstrates that the reconstructed images had better clarity, fidelity, and similarity in structure, texture, and detail. In summary, PELMI ensures robustness and stability of image storage in DNA and achieves relatively high-quality image reconstruction under general errors.

Temperature Compensation using Constraint based Dynamic Time Warping in Guided Waves

Introduction: Guided waves being highly sensitive to temperature variations, temperature compensation algorithms, such as Optimal Baseline Selection, Baseline Signal Stretch and Scale Transform demonstrate effective performance under limited conditions. Dynamic Time Warping (DTW) has shown excellent compensation performance, however it comes with a substantial computational burden of O(N*N), where N represents the number of samples in each signal. Methodology: DTW works by construction of cost matrix that maps every point in one time series to all the points in the other time series, that results in complexity O(N*N).This problem can be solved by narrowing the search window using global constraints. The two most common constraints in the literature are the Sakoe-Chiba band and the Itakura Parallelogram. This paper uses Sakoe-Chiba band as a global constraint, the Sakoe-Chiba band is defined through a window size parameter which determines the largest temporal shift allowed from the diagonal. Temperature compensation performance of DTW Sakoe-Chiba is tested using the available OGW dataset #2 provided by Jochen Moll et al. The OGW dataset has been generated using 12 number of piezoelectric transducers bounded to CFRP (Carbon Fiber Reinforced Plastic) plate and varying the temperature from 20-60 degree with an increment of 0.5 degree. The signal is recorded for 1300 microseconds, that results in 13000 samples/time stamps(N). Initial results show that the Sakoe-Chiba constraint based DTW performs well and at a significantly lower cost, as indicated below. Result: The largest temporal shift (r) is estimated using Local Peak Coherence (LPC),for signal at 20 and 60 degree r is 135 samples. This results in complexity O(N*2r) which is very less than conventional DTW compensation technique O(N*N). In the final paper, the analysis will be replicated across a range of temperatures, and the performance of damage detection will be thoroughly discussed.

Class Symbolic Regression: Gotta Fit ’Em All

We introduce “Class Symbolic Regression” (Class SR), the first framework for automatically finding a single analytical functional form that accurately fits multiple data sets—each realization being governed by its own (possibly) unique set of fitting parameters. This hierarchical framework leverages the common constraint that all the members of a single class of physical phenomena follow a common governing law. Our approach extends the capabilities of our earlier Physical Symbolic Optimization (Φ-SO) framework for symbolic regression, which integrates dimensional analysis constraints and deep reinforcement learning for unsupervised symbolic analytical function discovery from data. Additionally, we introduce the first Class SR benchmark, comprising a series of synthetic physical challenges specifically designed to evaluate such algorithms. We demonstrate the efficacy of our novel approach by applying it to these benchmark challenges and showcase its practical utility for astrophysics by successfully extracting an analytic galaxy potential from a set of simulated orbits approximating stellar streams.

Null models confirm nest site fidelity by male smallmouth bass, Micropterus dolomieu

BackgroundMany animals appear to preferentially renest in proximity to a site they previously occupied. Evidence of nest fidelity is often inferred from a right skewed distribution of distances between the nests of individuals that breed in two consecutive reproduction episodes, where many individuals nest some arbitrarily close distance to their prior nest and others, in the extended right tail of the distribution, nest far from the nest they previously occupied. Because right skewed distributions of inter-nest distances can arise even when individuals choose nest locations randomly, however, such inferences are prone to error. The importance of null models—used to generate patterns of individual inter-nest distances by processes that do not involve site attachment—for inferences about site fidelity has been known for decades but is still often unappreciated or ignored.MethodsThe right skewed distributions of inter-nest distances observed in two earlier studies of male smallmouth bass (Micropterus dolomieu) suggest prima facie that males exhibit nest site fidelity between annual reproduction episodes, but patterns of inter-nest distances have yet to be compared to an adequate null model. Here, we evaluate the nest site fidelity of marked male M. dolomieu in a decade-long dataset, where we apply a randomization procedure based on the rencontre probability problem to generate null models. Eight observed distributions of individual, annual inter-nest distances are compared to a year-specific null model to determine whether random processes are sufficient to explain the observed distributions of inter-nest distances.ResultsThrough contrasts between observed annual inter-nest distances and results derived from null models that imposed realistic constraints on behavior, we show that some males were undoubtedly nest-site faithful. To reinforce the utility of null models and to make these kinds of models more accessible, we also provide a supplemental tutorial. The tutorial illustrates how random site choices, subject to common ecological and behavioral constraints, and even how distance is measured, can produce patterns of inter-nest distances that falsely imply nest site fidelity, or a lack of fidelity. The R code needed to reproduce these null models is included. The inference errors evident in our examples generalize to other forms of site fidelity, such as the apparent patch fidelity of certain sea bird foragers.ConclusionsThe comparisons of observed distributions of inter-nest distances with those generated by null models imply that, as suggested in prior studies, male M. dolomieu indeed exhibit annual nest site fidelity. Procedures like those we apply are necessary first steps in analyses when distributions of distances between the nests of individuals in consecutive reproduction episodes are used to infer nest-site fidelity. Why male M. dolomieu are site faithful is a question yet to be answered.

Parameter Estimation of Birnbaum-Saunders Distribution under Competing Risks Using the Quantile Variant of the Expectation-Maximization Algorithm

Competing risks models, also known as weakest-link models, are utilized to analyze diverse strength distributions exhibiting multi-modality, often attributed to various types of defects within the material. The weakest-link theory posits that a material’s fracture is dictated by its most severe defect. However, multimodal problems can become intricate due to potential censoring, a common constraint stemming from time and cost limitations during experiments. Additionally, determining the mode of failure can be challenging due to factors like the absence of suitable diagnostic tools, costly autopsy procedures, and other obstacles, collectively referred to as the masking problem. In this paper, we investigate the distribution of strength for multimodal failures with censored data. We consider both full and partial maskings and present an EM-type parameter estimate for the Birnbaum-Saunders distribution under competing risks. We compare the results with those obtained from other distributions, such as lognormal, Weibull, and Wald (inverse-Gaussian) distributions. The effectiveness of the proposed method is demonstrated through two illustrative examples, as well as an analysis of the sensitivity of parameter estimates to variations in starting values.

Modified effective butterfly optimizer for solving optimal power flow problem

The optimal power flow (OPF) problem remains a popular and challenging work in optimizing power systems. Although researchers have suggested many optimization algorithms to solve this problem in the literature, their comparison studies lack fairness and transparency. As these studies increase in number, they deviate from a standard test system, considering a common security and technical constraints., there is a growing trend away from a standard test system. Different studies used different search ranges for the same decision and constraint parameters, different than the standard ranges suggested by IEEE systems. This caused many unfair comparisons in literature. Furthermore, these studies are generally not transparent enough so that their results cannot be verified. This has resulted in numerous infeasible solutions in the literature, violating the limits of constraint parameters. The recent incorporating of renewable energy sources in OPF studies has made this situation more complicated. Sorting through the literature and identifying those OPF applications having exactly the same test conditions is a challenging process. The main contribution is this paper adapts the modified effective butterfly algorithm (MEBO) to solve OPF problem under the common parameter constraints and sufficient transparency. The focus is on a transparent comparison with works in the literature with the same constraint values. This paper compares the performance of the proposed algorithm with other state-of-the-art algorithms in the literature, focusing on the wind energy and without wind energy IEEE 30-bus and IEEE 57-bus systems and the most commonly used constraints. The results demonstrate the efficiency and superiority of the proposed algorithm. For instance, in the 30-bus test system, compared to the initial case, fuel cost has been reduced by 11.42 %, emission by 14.33 %, L-index by 45.10 %, active power losses by 51.60 %, and voltage deviation by 92.70 %.

Opinion: Strengthening research in the Global South – atmospheric science opportunities in South America and Africa

Abstract. To tackle the current pressing atmospheric science issues, as well as those in the future, a robust scientific community is necessary in all regions across the globe. Unfortunately, this does not yet exist. There are many geographical areas that are still underrepresented in the atmospheric science community, many of which are in the Global South. There are also larger gaps in the understanding of atmospheric composition, processes, and impacts in these regions. In this opinion, we focus on two geographical areas in the Global South to discuss some common challenges and constraints, with a focus on our strengths in atmospheric science research. It is these strengths, we believe, that highlight the critical role of Global South researchers in the future of atmospheric science research.

Fish Biodiversity and Suggested Conservation Measures of Transboundary River Someshwari in Netrokona, Bangladesh

Considering the importance of fish biodiversity for sustainable management of river fisheries, this study aims to explore and evaluate the fish biodiversity of Someshwari River along with conservation measures from November 2020 to October 2021. Data collection was carried out in Jaria, Susang Durgapur, Shivganj Bazar and Bijoypur of Netrokona district. Questionnaire interview, Focus Group Discussion (FGD), Direct observations, Key Informant Interview (KII) was used to collect data. During the study period, 23 species under 12 families were determined. Among them 6 finfish species are endangered, 4 are critically endangered, 5 are vulnerable, 7 are data deficient, and 2 are not threatened, respectively which includes highest catch catfishes at about 26.62%. However, the lowest amount catch constituted the Miror carp of about 5.29%. After the catfish, the second highest catch was 15.9% of small prawn. Another dominant group major carps contained 11.26%, and barbs remained at 11% of the catch and the loaches constituted 1.3% of the total catch. In addition, other groups like Mola carplet 7%, gourami 2.20%, Spiny eels 9.86% etc. were found in the Someshwari river. There were about 81% fish for food and 17% ornamental fish. Fourteen distinct types of fishing equipment were used namely: nets, traps, hooks, and lines, and wounding equipment. Finally, indiscriminate use of harmful gear, extraction of sand and rock, inadequate supervision of Governments and Non Governemental orgazizations, pollution from the adjacent areas, high interest rate of bank loan were understood as common constraints in the study area. Therefore, recommendations were made to improve river fisheries management through habitat restoration, increasing public awareness, prohibition on exploiting brood fish and active participation for sustainable catch.

Gymnosperms demonstrate patterns of fine‐root trait coordination consistent with the global root economics space

Abstract Gymnosperms encompass a diverse group of mostly woody plants with high ecological and economic value, yet little is known about the scope and organization of fine‐root trait diversity among gymnosperms due to the undersampling of most gymnosperm families and the dominance of angiosperm groups in recent syntheses. New and existing data were compiled for morphological traits (root diameter, length, tissue density, specific root length [SRL] and specific root area [SRA]), the architectural trait branching ratio, root nitrogen content [N] and mycorrhizal colonization. We used phylogenetic least squares regression and principal component analysis to determine trait–trait relationships and coordination across 66 species, representing 11 of the 12 extant gymnosperm families from boreal, temperate, subtropical and tropical biomes. Finally, we compared the relationship between family divergence time and mean trait values to determine whether evolutionary history structured variation in fine‐root traits within the gymnosperm phylogeny. Wide variation in gymnosperm root traits could be largely captured by two primary axes of variation defined by SRL and diameter, and root tissue density and root nitrogen, respectively. However, individual root length and SRA each had significant correlations with traits defining both main axes of variation. Neither mycorrhizal colonization nor root branching ratio were closely related to other traits. We did not observe a directional evolution of mean trait values from older to more recently diverged gymnosperm families. Synthesis. Despite their unique evolutionary history, gymnosperms display a root economic space similar to that identified in angiosperms, likely reflecting common constraints on plants adapting to diverse environments in both groups. These findings provide greater confidence that patterns observed in broad syntheses justly capture patterns of trait diversity among multiple, distinct lineages. Additionally, independence between root architecture and other traits may support greater diversity in below‐ground resource acquisition strategies. Unlike angiosperms, there were no clear trends towards increasingly thin roots over evolutionary time, possibly because of lower diversification rates or unique biogeographic history among gymnosperms, though additional observations are needed to more richly test evolutionary trends among gymnosperms.

Parallel Gate Fidelity of Flip‐Flop Qubits in Small 1D‐ and 2D‐Arrays in a Noisy Environment

AbstractThe long coherence time of donor atom nuclear spin states and of its bounded electron in can be exploited to define a qubit. This work is focused on a type of donor‐ and quantum dot‐based qubit, the flip‐flop (FF) qubit, that leverages antiparallel electron‐nuclear spin states of a donor atom controlled by an electric field. It can provide long‐range inter‐qubit interactions in the order of some hundreds of nanometers, thus relaxing the common constraints and tolerances on inter‐qubit distances in donor‐based qubits. Simulation results of linear array (LA) and square array (SA) of four FF qubits are presented to study the effect of noise, idle qubits, and simultaneous gating (parallel gating) on gate fidelity. The impact of noise and qubit mutual coupling for both considered types of array are presented and the obtained fidelity results are compared.

A Structural Equation Model Study for Adoption of Internet of Things for the Growth of Manufacturing Industries in Australia

This research study delves into the integration of IoT within the Australian manufacturing sector, analyzing five key factors influencing adoption and drawing comparisons with Rogers' innovation theory. Its objectives encompass assessing how competitiveness, regulatory support, management support, manufacturing growth, and cost savings affect IoT adoption. Methodologically, the research journey includes defining the problem, conducting a thorough literature review, crafting a research proposal, executing pilot and main studies, validating findings, and ultimately composing the final thesis. Quantitative data obtained from a large pool of over 500 respondents shed light on the positive impacts of competitiveness, regulatory support, and cost savings on IoT adoption. Additionally, the study employs Importance-Performance Map Analysis (IPMA) to underscore the significance of management support in successful IoT implementation. Despite facing limitations such as common method bias and constraints on generalizability, the research underscores the transformative potential of IoT in enhancing operational efficiency and decision-making within Australian manufacturing. Overall, the study's findings confirm the significant influence of key factors on IoT adoption, affirming its potential to drive competitiveness, regulatory compliance, cost efficiency, and growth within the Australian manufacturing landscape.

Morphological diversity in true and false crabs reveals the plesiomorphy of the megalopa phase

Brachyura and Anomala (or Anomura), also referred to as true and false crabs, form the species-rich and globally abundant group of Meiura, an ingroup of Decapoda. The evolutionary success of both groups is sometimes attributed to the process of carcinization (evolving a crab-like body), but might also be connected to the megalopa, a specific transitional larval phase. We investigate these questions, using outline analysis of the shields (carapaces) of more than 1500 meiuran crabs. We compare the morphological diversity of different developmental phases of major ingroups of true and false crabs. We find that morphological diversity of adults is larger in false crabs than in true crabs, indicating that taxonomic diversity and morphological diversity are not necessarily linked. The increasing morphological disparity of adults of true and false crabs with increasing phylogenetic distance furthermore indicates diverging evolution of the shield morphology of adult representatives of Meiura. Larvae of true crabs also show larger diversity than their adult counterparts, highlighting the importance of larvae for biodiversity studies. The megalopa phase of Meiura appears to be plesiomorphic, as it overlaps between true and false crabs and shows little diversity. Causes may be common evolutionary constraints on a developmental phase specialized for transitioning.