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Human capital efficiency, corporate sustainability, and performance: Evidence from emerging economies
Get PDFThis study examines how corporate sustainability (CS) influences the relationship between human capital (HC) effectiveness and corporate performance (CP) in the context of emerging economies. Drawing on HC theories and CS, we employ partial least squares structural equation modeling (PLS-SEM) to analyze data from 94 industrial and service firms listed on the Amman Stock Exchange (ASE) between June and October 2022. Our findings reveal the dual role of HC, which not only directly influences CP but also significantly reinforces CS efforts. This research contributes to strategic management literature by highlighting the mediating role of CS in the HC-performance nexus. The results underscore the strategic value of HC in enhancing sustainable practices, which positively affect CP. These insights are particularly relevant for emerging economies, where understanding the role of HC can guide corporate strategies toward sustainable growth. Theoretical and practical implications are discussed, with a focus on the importance of HC development to promote resilience and support sustainability goals in emerging markets. Future research could explore these dynamics across other industries and regions
Advancing precision agriculture: domain-specific augmentations and robustness testing for convolutional neural networks in precision spraying evaluation
Get PDFData availability: The data currently are unavailable. Reason for Unavailability: We would like to refine the dataset and then open source in future. The data were also collected on a proprietary system.Modern agriculture relies heavily on the precise application of chemicals such as fertilisers, herbicides, and pesticides, which directly affect both crop yield and environmental footprint. Therefore, it is crucial to assess the accuracy of precision sprayers regarding the spatial location of spray deposits. However, there is currently no fully automated evaluation method for this. In this study, we collected a novel dataset from a precision spot spraying system to enable us to classify and detect spray deposits on target weeds and non-target crops. We employed multiple deep convolutional backbones for this task; subsequently, we have proposed a robustness testing methodology for evaluation purposes. We experimented with two novel data augmentation techniques: subtraction and thresholding which enhanced the classification accuracy and robustness of the developed models. On average, across nine different tests and four distinct convolutional neural networks, subtraction improves robustness by 50.83%, and thresholding increases by 42.26% from a baseline. Additionally, we have presented the results from a novel weakly supervised object detection task using our dataset, establishing a baseline Intersection over Union score of 42.78%. Our proposed pipeline includes an explainable artificial intelligence stage and provides insights not only into the spatial location of the spray deposits but also into the specific filtering methods within that spatial location utilised for classification.Engineering and Physical Sciences Research Council [EP/S023917/1]. This work is also supported by Syngenta as the Industrial partner. The research presented in this paper was carried out on the High-Performance Computing Cluster supported by the Research and Specialist Computing Support service at the University of East Anglia
LIE scales: Composing with scales of linear intervallic expansion
Get PDFThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThis thesis includes a portfolio of scored compositions with written commentaries and a list of all completed pieces (2017–2024) composed using LIE scalic principle. All compositions use extended fixed pitch fields (FPFs) as source scales and are primarily scored for acoustic instruments. LIE scales (scales of Linear Intervallic Expansion) were initially derived from my discovery of a unique correspondence between consecutive counting numbers (+1, +2, +3...) and Messiaen's “mode 2” scale ,0, 1, 3, 4, 6, 7, 9, 10-. In brief, this compound-chromatic theory of scales combines Non-Octave-Repeating Scales (beyond interval cycles) with Axiomatic scale theory. I explain my development of LIE scales, addresses some of the perceptual aspects of these FPFs, catalogue numerous scales and draw a compositional conclusion. My structural methodology is informed by the work of Webern, Bartók, Schillinger and Slonimsky, for example, but transcends 12-tone theory per se and suggests an alternative approach to harmonic dualism, whilst providing a rich generative vein for compositional development.
I explore abstract harmonic polarity by using extended anti/complimentary scales, treating melody and timbre as emergent entities rather than structural prerequisites, and research how harmonic meaning and our awareness of octave equivalence can be enhanced or avoided through composing with compound LIE scalic structures. This thesis should be of interest to any composers working with synthetic mathematically derived patterns, and musicologists specialising in early 20th Century compositional approaches. LIE scales could also be used as a repository of alternative scalic ideas for improvisational purposes. Future research might explore LIE scalic principles microtonally and with regard to granulation, a spectral centroid, and a-spatial (or medial) theories of auditory perception
Protoporphyrin IX iron(II) revisited. An overview of the Mössbauer spectroscopic parameters of low-spin porphyrin iron(II) complexes
Get PDFAvailability of data and materials: No datasets were generated or analysed during the current study.Mössbauer parameters of low-spin six-coordinate [Fe(II)(Por)L2] complexes (where Por is a synthetic porphyrin; L is a nitrogenous aliphatic, an aromatic base or a heterocyclic ligand, a P-bonding ligand, CO or CN) and low-spin [Fe(Por)LX] complexes (where L and X are different ligands) are reported. A known point charge calculation approach was extended to investigate how the axial ligands and the four porphyrinato-N atoms generate the observed quadrupole splittings (ΔEQ) for the complexes. Partial quadrupole splitting (p.q.s.) and partial chemical shifts (p.c.s.) values were derived for all the axial ligands, and porphyrins reported in the literature. The values for each porphyrin are different emphasising the importance/uniqueness of the [Fe(PPIX)] moiety, (which is ubiquitous in nature). This new analysis enabled the construction of figures relating p.c.s and p.q.s values. The relationships presented in the figures indicates that strong field ligands such as CO can, and do change the sign of the electric field gradient in the [Fe(II)(Por)L2] complexes. The limiting p.q.s. value a ligand can have and still form a six-coordinate low-spin [Fe(II)(Por)L2] complex is established. It is shown that the control the porphyrin ligands exert on the low-spin Fe(II) atom limits its bonding to a defined range of axial ligands; outside this range the spin state of the iron is unstable and five-coordinate high-spin complexes are favoured. Amongst many conclusions, it was found that oxygen cannot form a stable low-spin [Fe(II)(Por)L(O2)] complex and that oxy-haemoglobin is best described as an [Fe(III)(Por)L(O2−)] complex, the iron is ferric bound to the superoxide molecule.Innovate UK Grant Number 10110040 to G.F. J.S thanks ICI for support for part of this work
Semi-Supervised 3D Medical Image Segmentation Using Multi-Consistency Learning With Fuzzy Perception-Guided Target Selection
Get PDFSemi-supervised learning methods based on the mean teacher model have achieved great success in the field of 3D medical image segmentation. However, most of the existing methods provide auxiliary supervised signals only for reliable regions, but ignore the effect of fuzzy regions from unlabeled data during the process of consistency learning, which results in the loss of more valuable information. Besides, some of these methods only employ multi-task learning to improve models’ performance, but ignore the role of consistency learning between tasks and models, thereby weakening geometric shape constraints. To address the above issues, in this paper, we propose a semi-supervised 3D medical image segmentation framework with multi-consistency learning for fuzzy perception-guided target selection. First, we design a fuzzy perception-guided target selection strategy from multiple perspectives and adopt the fusion method of fuzziness minimization and the fuzzy map momentum update to obtain a fuzzy region. By incorporating the fuzzy region into consistency learning, our model can effectively exploit more useful information from the fuzzy region of unlabeled data. Second, we design a multi-consistency learning strategy that employs intra-task and inter-model mutual consistency learning as well as cross-model cross-task consistency learning to effectively learn the shape representation of fuzzy regions. The strategy can encourage the model to agree on predictions for different tasks in fuzzy regions. Experiments demonstrate that the proposed framework outperforms the current mainstream methods on two popular 3D medical datasets, the left atrium segmentation dataset, and the brain tumor segmentation dataset. The code will be released at: https://github.com/SUST-reynole.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62201334 and 62271296);
Scientific Research Program Funded by Shaanxi Provincial Education Department (Grant Number: 23JP014 and 23JP022)
Life and death of a thin liquid film
Get PDFData availability: Configuration files for molecular dynamics simulations are publicly available at: https://doi.org/10.5281/zenodo.12633918. Any additional data is available upon reasonable request to the corresponding author.Code availability: Codes to reproduce the data reported in this manuscript can be found at the github public repository: https://github.com/MuhammadRRahman/Thin-Film-Rupture-NEMD.git.Supplementary information is available online at: https://www.nature.com/articles/s42005-024-01745-z#Sec12 .Thin films, bubbles and membranes are central to numerous natural and engineering processes, i.e., in solar cells, coatings, biosensors, foams, and emulsions. Yet, the characterization and understanding of their rupture is limited by the scarcity of atomic detail. We present here the complete life-cycle of freely suspended films using non-equilibrium molecular dynamics simulations of a simple atomic fluid free of surfactants and surface impurities, thus isolating the fundamental rupture mechanisms. We identified a short-term ‘memory’ by rewinding in time from a rupture event, extracting deterministic behaviors from apparent stochasticity. A comprehensive investigation of the key rupture-stages including both unrestrained and frustrated propagation is made—characterization of the latter leads to a first-order correction to the classical film-retraction theory. The highly resolved time window reveals that the different modes of the morphological development, typically characterized as nucleation and spinodal rupture, continuously evolve seamlessly with time from one into the other.M.R.R. thanks Shell, and the Beit Fellowship for Scientific Research for PhD funding. L.S. thanks the Engineering and Physical Sciences Research Council (EPSRC) for a Postdoctoral Fellowship (EP/V005073/1). J.P.E. was supported by the Royal Academy of Engineering (RAEng) through their Research Fellowships scheme. D.D. acknowledges a Shell/RAEng Research Chair in Complex Engineering Interfaces, and the EPSRC for an Established Career Fellowship (EP/N025954/1)
Joint Optimization of Cost and Scheduling for Urban Air Mobility Operation Based on Safety Concerns and Time-Varying Demand
Get PDFData Availability Statement: Data are contained within the article.As the value and importance of urban air mobility (UAM) are being recognized, there is growing attention towards UAM. To ensure that urban air traffic can serve passengers to the greatest extent while ensuring safety and generating revenue, there is an urgent need for a transportation scheduling plan based on safety considerations. The region of Beijing–Tianjin–Hebei was selected as the case study in this research. A real-time demand transportation scheduling model for a single day was constructed, with the total service population and total cost as objective functions, and safety intervals, eVTOL performance, and passenger maximum waiting time as constraints. A Joint Optimization of Cost and Scheduling Particle Swarm Optimization (JOCS-PSO) algorithm was utilized to obtain the optimal solution. The optimal solution obtained in this study can serve 138,610,575 passengers during eVTOLs’ entire lifecycle (15 years) with a total cost of CNY 368.57 hundred million, with the cost of CNY 265.9 per passenger. Although it is higher than the driving cost, it saves 1–1.5 h and thus has high cost effectiveness during rush hours.National Key Research and Development Project (2022YFC3002502], National Natural Science Foundation of China (U1933103 and 62206062); Special Fund for Basic Scientific Research Operations of Central Universities—Civil Aviation University of China (3122024QD18)
Standardisation efforts of ISO/TC 261 “additive manufacturing” 23rd plenary meeting of ISO/TC 261 “additive manufacturing”
Get PDFThe main objective of ISO/TC 261 is to standardise the processes of Additive Manufacturing, the process chains (Data, Materials, Processes, Hard- and Software, Applications), test procedures, quality parameters, supply agreements, environment, health and safety, fundamentals and vocabularies. This section provides readers with news regarding standardisation efforts of ISO/TC 261. Further up-to-date information regarding recently published documents, such as new standards, revised standards, and the status of standards, can be found in the ISO/TC261 webpages: https://www.iso.org/committee/629086.html and from the committee webpages: https://committee.iso.org/sites/tc261/home/news.html
Decoupling Analysis of Ignition Processes of Ammonia/N-Heptane Mixtures
Get PDFData Availability Statement: The data presented in this study are available on request from the corresponding author.To further understand the influence of n-heptane on the ignition process of ammonia, an isotope labeling method was applied in the current investigation to decouple the influence of the chemical effect, the thermal effect, and the effect of O radical from the oxidation of n-heptane on the ignition delay times (IDTs) of ammonia. An analysis of the time evolution of fuel, analysis of the time evolution of temperature, rate of consumption and production (ROP) analysis, and sensitivity analysis were conducted to gain a further understanding of the mechanism of the influence of the chemical effect, the thermal effect, and the effect of O radical on the ignition of ammonia. The results showed that the negative temperature coefficient (NTC) behavior of n-heptane is mitigated by the blending of ammonia, and this mitigated effect of ammonia is mainly due to the chemical effect. The IDTs of ammonia under low and medium temperatures are significantly shortened by the chemical effect at a n-heptane mass fraction of 10%. The promoting effect of the chemical effect decreases when the n-heptane mass fraction increases. The time evolution of n-heptane for NC7H16/ND3-G can be classified into three stages at 800 K, and the rapid consumption stage is mitigated by an increase in temperature. The rapid consumption stage is suppressed by the chemical effect of ammonia, while O radical has a promoting effect on the rapid consumption stage. The chemical effect will enhance the sensitivities of reactions associated with ammonia. As the n-heptane mass fraction increases, the sensitivities of reactions associated with n-heptane are enhanced. Correspondingly, the effect of reactions associated with ammonia is weakened. When the n-heptane mass fraction is 30%, only reactions related to n-heptane have a great influence on the ignition of ammonia/n-heptane fuel blends under the thermal effect + the effect of O radical or only the thermal effect.Key Research and Development Projects of Ministry of Science and Technology of People’s Republic of China (2023YFE0115300); Industrial and Information Industry Transformation and Upgrading Special Project of Jiangsu Province and Major Science and Technology Project of Zhenjiang
Enhancing online clothing retail with generative AI: Innovations in virtual try-on and beyond
No full textThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe trend of customers purchasing clothing products online has seen a significant increase,
especially during the Covid-19 pandemic. Customers find it convenient to browse a wide range
of items and purchase from anywhere. However, one challenge is that online shopping does not
provide the same experience as shopping in physical stores. Customers miss out on the opportunity
to try on clothing before making a purchase, leading to potential issues such as dissatisfaction and
product returns. This thesis aims to demonstrate how generative AI can address these issues by
replicating the physical shopping experience and allowing more interactions.
This work contributes to improving existing generative AI models in the fashion context.
These models include image-based and multi-pose virtual try-ons. Image-based virtual try-ons
allow customers to apply desired clothing to an image of themselves. The proposed model refines
the input data to enhance the accuracy of segmentation synthesis and occlusion handling. The
virtual try-on model is faster than competitors due to the truncation of the U-Net and the use of
affine transformation to perform the geometrical transformation of the clothing.
The multi-pose variant enables customers to change the posture of the synthesised image,
allowing for a wider range of viewing angles and posture styles. The contribution led to the development
of a model combining techniques from virtual try-on and pose transfer. It is demonstrated
how multiple discriminators enhance the warping performance for high-resolution images. Additionally,
the method for fine-tuning the pose transfer module to adapt it for multi-pose virtual
try-on is outlined.
This thesis also innovates by proposing an image-to-video synthesis model for creating fashion
videos from a single image, a concept not previously explored. This model provides customers
with more detailed information about clothing products, showing how they would look while being
worn from various angles and how the clothing flows as the person moves. The contribution has
led to the development of a video diffusion model. It is shown how the conditioning image is
incorporated into the latent video through cross-attention. Using the conditioning image as the
initial frame enables subsequent frames to capture detailed clothing characteristics.
In order to encourage businesses to employ generative AI, this thesis introduces the MARKGEN
framework, which serves as a non-technical comprehensive guide on how to apply generative
AI for marketing purposes. This framework aims to simplify the integration of generative AI into
business platforms, enabling them to reap its benefits and enhance the overall shopping experience.EPSRC scholarshi
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