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Functionalized nanodiamonds as a perspective green carbo-catalyst for removal of emerging organic pollutants
- Robert Bogdanowicz
2022 Pełny tekst CURRENT OPINION IN SOLID STATE & MATERIALS SCIENCE
Rapid industrial and urban development jointly with rising global population strongly affect the large-scale issues with drinking, groundwater, and surface water pollution. Concerns are not limited to environmental issues but also human health impact becoming serious global aspect. Organic pollution becomes a primarily serious hazard, therefore, the novel sophisticated approaches to treat them are thoroughly investigated. Among numerous materials, functionalized nanodiamonds are specific versatile nanocarbon material attracted ample attention thanks to their exceptional chemical, optical and electronic properties beneficial in the decomposition of harmful organic chemicals. This work delivers a comprehensive review of progress and perspectives on the green-friendly nanodiamonds, which are suitable for the degradation of emerging organic pollutants using numerous approaches utilizing them as an electro-oxidation catalyst; photocatalyst; oxidation agent, or adsorbing surface. Novel modification strategies of nanodiamonds (i.e., persulfates, oxides, or metals) remarkably improve pollutant removal efficiency and facilitate charge transfer and surface regeneration. Furthermore, we evaluated also the influence of various factors like pH, natural organic matters, or radical scavengers on the removal efficiency combining them with nanodiamond properties. The identified missing research gaps and development perspectives of nanodiamond surfaces in water remediation relating to other nanocarbon and metal catalysts were also here described.
Fundamentals of Data-Driven Surrogate Modeling
- Sławomir Kozieł
- Anna Pietrenko-Dąbrowska
2022
The primary topic of the book is surrogate modeling and surrogate-based design of high-frequency structures. The purpose of the first two chapters is to provide the reader with an overview of the two most important classes of modeling methods, data-driven (or approx-imation), as well as physics-based ones. These are covered in Chap-ters 1 and 2, respectively. The remaining parts of the book give an exposition of the specific aspects of particular modeling methodolo-gies and their applications to solving various simulation-driven de-sign tasks such as parametric optimization or uncertainty quantifica-tion. Data-driven models are by far the most popular types of surro-gates. This is due to several reasons, including versatility, low evalu-ation cost, a large variety of matured methods, and—important from the point of view of practical utility—widespread availability through third-party toolboxes implemented in programming envi-ronments such as Matlab. This chapter covers the fundamentals of approximation-based modeling. We discuss the surrogate modeling flow, design of experiments, selected modeling methods (e.g., kriging, radial basis functions, support vector regression, or polyno-mial chaos expansion), as well as discuss model validation ap-proaches. The presented material is intended to provide the readers who are new to the subject with the basics necessary to understand the remaining parts of the book. On the other hand, it is by no means exhaustive, and the readers interested in a more detailed exposition can refer to a rich literature of the subject.
Fundamentals of Physics-Based Surrogate Modeling
- Anna Pietrenko-Dąbrowska
- Sławomir Kozieł
2022
Chapter 1 was focused on data-driven (or approximation-based) modeling methods. The second major class of surrogates are physics-based models outlined in this chapter. Although they are not as popular, their importance is growing because of the challenges related to construction and handling of approximation surrogates for many real-world problems. The high cost of evaluating computational models, nonlinearity of system responses, dimensionality issues as well as combinations of these factors, may lead to a situation, where setting up a data-driven model is not possible or at least not practical. On the other hand, incorporation of the problem-specific knowledge, typically in the form of a lower-fidelity computational model, often alleviates the aforementioned difficulties. The enhancement of the low-fidelity models using a limited amount of high-fidelity data is the essence of physics-based surrogate modeling. This chapter provides a brief characterization of this class of surrogates, explains the concept and various types of low-fidelity models, as well as outlines several specific modeling approaches, also in the context of surrogate-assisted optimization.
Galerkin Finite Element Process for Entropy Production and Thermal Evaluation of Third-Grade Fluid Flow: A Thermal Case Study
- Faisal Shahzad
- Wasim Jamshed
- El Sayed M. Tag El Din
- Rabia Safdar
- Nor Air Azeany Mohd Nazir
- Rabha W. Ibrahim
- Syed M. Hussain
- Ikram Ullah
- Muhammad Bilal Hafeez
- Marek Krawczuk
2022 Pełny tekst Applied Sciences-Basel
: A fluid’s moving class improves its heat transmission capability, as well as its rigidity, owing to multivariate molecule suspension. In this way, nanofluids are superior to common fluids. In this study, we evaluated the features of ease and heat transfer. Furthermore, we investigated permeable media, heat source, variable heat conductivity, and warm irradiation results. A mathematical technique known as the Galerkin finite element (G-FEM) approach was used to solve the supervising conditions. Third-grade nanofluid (TGNF), which consists of two types of nanoparticles (NPs), single-walled carbon nanotubes (SWCNT), and multi-walled carbon nanotubes (MWCNTs) distributed in a base liquid of carboxymethyl cellulose (CMC) water, was used for this examination. The main conclusion of this study is that MWCNT-CMC nanofluid has a higher heat transfer velocity than SWCNT-CMC nanofluid. The entropy of the framework can be increased by adjusting the thermal conductivity. Additionally, we found that increasing the main volume section decreases the speed but increases the dispersion of atomic energy. In order to separately account for the development properties of inertial forces and shallow heat dispersion forces, Reynolds and Brinkman values can be used to accelerate the entropy rate of the heating framework.
Galerkin formulations with Greville quadrature rules for isogeometric shell analysis: Higher order elements and locking
- T.j.r. Hughes
- Zhihui Zou
- M.a. Scott
- Roger Sauer
- E.j. Savitha
2022
We propose new Greville quadrature schemes that asymptotically require only four in-plane points for Reissner-Mindlin (RM) shell elements and nine in-plane points for Kirchhoff-Love (KL) shell elements in B-spline and NURBS-based isogeometric shell analysis, independent of the polynomial degree of the elements. For polynomial degrees 5 and 6, the approach delivers high accuracy, low computational cost, and alleviates membrane and transverse shear locking.
Game-based Sprint retrospectives: multiple action research
- Adam Przybyłek
- Marta Albecka
- Olga Springer
- Wojciech Kowalski
2022 Pełny tekst EMPIRICAL SOFTWARE ENGINEERING
In today’s fast-paced world of rapid technological change, software development teams need to constantly revise their work practices. Not surprisingly, regular reflection on how to become more effective is perceived as one of the most important principles of Agile Software Development. Nevertheless, running an effective and enjoyable retrospective meeting is still a challenge in real environments. As reported by several studies, the Sprint Retrospective is an agile practice most likely to be implemented improperly or sacrificed when teams perform under pressure to deliver. To facilitate the implementation of the practice, some agile coaches have proposed to set up retrospective meetings in the form of retrospective games. However, there has been little research-based evidence to support the positive effects of retrospective games. Our aim is to investigate whether the adoption of retrospective games can improve retrospective meetings in general and lead to positive societal outcomes. In this paper, we report on an Action Research project in which we implemented six retrospective games in six Scrum teams that had experienced common retrospective problems. The received feedback indicates that the approach helped the teams to mitigate many of the “accidental difficulties” pertaining to the Sprint Retrospective, such as lack of structure, dullness, too many complaints, or unequal participation and made the meetings more productive to some degree. Moreover, depending on their individual preferences, different participants perceived different games as having a positive impact on their communication, motivation-and-involvement, and/or creativity, even though there were others, less numerous, who had an opposite view. The advantages and disadvantages of each game as well as eight lessons learned are presented in the paper.
Gdańsk Urban Initiative Laboratory
- Joanna Bach-Głowińska
- Jacek Łubiński
- Karolina Krośnicka
- Joanna Tobolewicz
2022
Gdansk is Poland's principal seaport, situated on the southern edge of the Gdansk Bay on the Baltic Sea. The city is the capital and largest city of the Pomeranian Voivodeship. Gdansk, in a conurbation with the city of Gdynia and the resort town of Sopot, and suburban communities, jointly forms Poland's fourth largest metropolitan area, with a population approaching 1.4 million. The pathways towards the Micro ULL FWE Nexus Square were established together by academics, city experts, business partners, and international experts as stakeholders. The several thematic Urban Living Labs undertaken within carefully selected groups had created chances for user friendly innovations. The integrated multi-channel monitoring system will allow for the detailed tracking of individual use of media by devices on board.
Gender differences in the perception of the Quality of College Life in Spanish University
- Juan Jose Blazquez-Resino
- Edyta Gołąb-Andrzejak
- Santiago Gutierrez-Broncano
2022 Pełny tekst International Journal of Intelligent Enterprise
Through the current research, we intend to analyse how students differ in their levels of quality of college life (QCL) according to gender, and how this relates to overall quality of life (QoL) and loyalty [measured by Identification and word of mouth (WoM)] to their specific university. The survey included 243 students attending public university in Spain. The results obtained through the analysis of data allow affirming that there are differences between women and men both in the configuration of the quality of their college life and in its effect on the loyalty shown towards the college. This paper contributes towards an improved comprehension regarding the differences between the students according to their gender, so that managers can develop strategies better adapted to students.
Generalized Dobrushin Coefficients on Banach Spaces
- Wojciech Bartoszek
- Marek Beśka
- Wiktor Florek
2022 Pełny tekst Bulletin of the Iranian Mathematical Society
The asymptotic behavior of iterates of bounded linear operators (not necessarily positive), acting on Banach spaces, is studied. Through the Dobrushin ergodicity coefficient, we generalize some ergodic theorems obtained earlier for classical Markov semigroups acting on L1 (or positive operators on abstract state spaces).
Generalized Dold sequences on partially-ordered sets
- Grzegorz Graff
- Jacek Gulgowski
- Małgorzata Lebiedź
2022 Pełny tekst ELECTRONIC JOURNAL OF COMBINATORICS
Dold sequences constitute an important class of integer sequences that play an important role in combinatorics, number theory, topology and dynamical systems. We generalize the notion of Dold sequence for the case of partially ordered sets and describe their properties. In particular we give two alternative descriptions of generalized Dold sequences: by some class of elementary sequences as well as by different generalized arithmetical functions, both defined on a partially ordered set. We also define vector Dold sequences and show their combinatorial interpretation in terms of periodic points.
Generalized Formulation of Response Features for Reliable Optimization of Antenna Input Characteristics
- Anna Pietrenko-Dąbrowska
- Sławomir Kozieł
2022 Pełny tekst IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
Electromagnetic (EM)-driven parameter adjustment has become imperative in the design of modern antennas. It is necessary because the initial designs rendered through topology evolution, parameter sweeping, or theoretical models, are often of poor quality and need to be improved to satisfy stringent performance requirements. Given multiple objectives, constraints, and a typically large number of geometry parameters, the design closure should be carried out through numerical optimization. Unfortunately, standard algorithms entail high CPU expenses and are prone to failure. Feature-based optimization (FBO) is one of the methods developed to alleviate these difficulties by reformulating the design task in terms of the characteristic points extracted from EM-simulated responses. FBO capitalizes on a less nonlinear relationship between the feature point coordinates and antenna dimensions as compared to the original responses (e.g., frequency characteristics). This leads to flattening the functional landscape to be handled, faster convergence of the optimization algorithms, and a possibility of mitigating the issues pertinent to multi-modality. Notwithstanding, the response features have to be individually defined for each type of antenna response and tailored to a particular type of design specifications. This requires user experience and hinders a widespread application of FBO. This paper proposes a generalized and unified feature point definition, which is suitable for majority of typical antenna input characteristics (narrow-, multi-band, enhanced bandwidth, wideband), and performance specifications (matching improvement, bandwidth enhancement, mixture thereof). Our framework allows for an automated definition of the feature points given the performance specifications, along with their extraction from EM-simulated responses. The operation of the framework is illustrated using a range of planar antennas and favorably compared to conventional (non-feature-based) design closure task formulation.
Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
- Adeel Mirza
- Syed Kamran Haider
- Abbas Ahmed
- Ateeq Ur Rehman
- Muhammad Shafiq
- Mohit Bajaj
- Hossam M. Zawbaa
- Paweł Szczepankowski
- Salah Kamel
2022 Pełny tekst Energy Reports
The thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition, several maximum power points (MPPs) appear on the P/V curve. In multiple MPPs, the true global maximum power points (GMPP) are very important for optimum action. The existing conventional technologies have slow tracking speed, low productivity, and unwanted fluctuations in voltage curves. To overcome the TEG system behavior and shortcomings, A novel control technology for the TEG system is proposed, which utilizes the improved generalized regression neural network and fitness dependent optimization (GRNNFDO) to track the GMPP under dynamic operating conditions. Conventional TEG system control techniques are not likely to trace true GMPP. Our novel GRNNFDO can trace the true GMPP for NUTD and under varying temperature conditions In this article, some major contributions in the area of the TEG systems are investigated by solving the issues such as NUTD global maxima tracking, low efficiency of TEG module due to mismatch, and oscillations around optimum point. The results of GRNNFDO are compared with the Cuckoo-search algorithm (CSA), and grasshopper optimization (GHO) algorithm and particle swarm optimization (PSO) algorithm. Results of GRNNFDO are verified with experiments and authenticated with MATLAB/SIMULINK. The proposed GRNNFDO control technique generates up to 7% more energy than PSO and 60% fast-tracking than meta-heuristic algorithms.
Genetic and pharmacologic proteasome augmentation ameliorates Alzheimer’s-like pathology in mouse and fly APP overexpression models
- E. Sandra Chocron
- Erin Munkácsy
- Harper S. Kim
- Przemyslaw Karpowicz
- Nisi Jiang
- Candice E. Van Skike
- Nicholas DeRosa
- Andy Q. Banh
- Juan P. Palavicini
- Paweł Wityk
- Leszek Kalinowski
- Veronica Galvan
- Pawel A. Osmulski
- Elzbieta Jankowska
- Maria Gaczynska
- Andrew M. Pickering
2022 Pełny tekst Science Advances
The proteasome has key roles in neuronal proteostasis, including the removal of misfolded and oxidized proteins, presynaptic protein turnover, and synaptic efficacy and plasticity. Proteasome dysfunction is a prominent feature of Alzheimer’s disease (AD). We show that prevention of proteasome dysfunction by genetic manipulation delays mortality, cell death, and cognitive deficits in fly and cell culture AD models. We developed a transgenic mouse with neuronal-specific proteasome overexpression that, when crossed with an AD mouse model, showed reduced mortality and cognitive deficits. To establish translational relevance, we developed a set of TAT-based proteasome- activating peptidomimetics that stably penetrated the blood-brain barrier and enhanced 20 S /26 S proteasome activity. These agonists protected against cell death, cognitive decline, and mortality in cell culture, fly, and mouse Downloaded from https://www.science.org at Medical University of Gdansk on June 11, 2022 AD models. The protective effects of proteasome overexpression appear to be driven, at least in part, by the pro- teasome’s increased turnover of the amyloid precursor protein along with the prevention of overall proteostatic dysfunction.
Genetic and pharmacologic proteasome augmentation ameliorates Alzheimer’s-like pathology in mouse and fly APP overexpression models
- Paweł Wityk
- E. Sandra Chocron
- Erin Munkácsy
- Harper S. Kim
- Przemyslaw Karpowicz
- Nisi Jiang
- Van Skike E. Candice
- Nicholas DeRosa
- Banh Q. Andy
- Palavicini P. Juan
- Leszek Kalinowski
- Veronica Galvan
- Pawel A. Osmulski
- Elzbieta Jankowska
- Maria Gaczynska
- Andrew M. Pickering
2022 Pełny tekst Science Advances
The proteasome has key roles in neuronal proteostasis, including the removal of misfolded and oxidized proteins, presynaptic protein turnover, and synaptic efficacy and plasticity. Proteasome dysfunction is a prominent feature of Alzheimer’s disease (AD). We show that prevention of proteasome dysfunction by genetic manipulation delays mortality, cell death, and cognitive deficits in fly and cell culture AD models. We developed a transgenic mouse with neuronal-specific proteasome overexpression that, when crossed with an AD mouse model, showed reduced mortality and cognitive deficits. To establish translational relevance, we developed a set of TAT-based proteasome-activating peptidomimetics that stably penetrated the blood-brain barrier and enhanced 20S/26S proteasome activity. These agonists protected against cell death, cognitive decline, and mortality in cell culture, fly, and mouse AD models. The protective effects of proteasome overexpression appear to be driven, at least in part, by the proteasome’s increased turnover of the amyloid precursor protein along with the prevention of overall proteostatic dysfunction.
Geodezyjne wyznaczanie przemieszczeń pionowych obiektów inżynierskich z pomiarów uzyskanych metodą niwelacji hydrostatycznej
- Waldemar Kamiński
2022 Inżynieria Morska i Geotechnika
Niwelacja hydrostatyczna (NH) jest obecnie często stosowaną metodą wyznaczenia przemieszczeń pionowych obiektów inżynierskich takich jak: mosty, wiadukty, estakady, tunele, wysokie budynki, obiekty zabytkowe, specjalistyczne obiekty inżynierskie (np. synchrotron), hale sportowe, widowiskowe, itp. Zastosowane w systemach niwelacji hydrostatycznej (SNH) sensory (czujniki) pomiarowe obejmują sensor referencyjny (RS) oraz czujniki umieszczone w punktach kontrolowanych (PK). Sensor referencyjny jest to czujnik umieszczony w takim miejscu i w takim punkcie, który w założeniach teoretycznych nie podlega przemieszczeniom pionowym i w stosunku do jego wysokości wyznaczane są przemieszczenia PK. Zasada NH wynika z prawa Bernoulliego. Wykorzystując w NH prawo Bernoulliego, należy uwzględnić między innymi następujące parametry: ciśnienie atmosferyczne, siłę grawitacji, gęstość cieczy przepływającej przez sensory pomiarowe. Wymienione parametry wyznaczane są z pewnymi błędami średnimi mającymi wpływ na oszacowanie dokładności rezultatów przemieszczeń pionowych. Należy dodać, że w literaturze przedmiotu przedstawiono szereg prac dotyczących między innymi analiz dokładności indywidualnych wymienionych wyżej parametrów i ich wpływu na otrzymane przemieszczenia pionowe. W niniejszym artykule przedstawiono koncepcję geodezyjnego wyznaczania przemieszczeń SNH, oceny dokładności i istotności otrzymanych wielkości. Do oceny dokładności wykorzystano macierze kofaktorów (estymatorów wariancji). Posługując się modelem kinematycznym przemieszczających się PK badanego obiektu inżynierskiego przedstawiono problematykę predykcji przemieszczeń pionowych na dowolną epokę pomiarową. Wyznaczono także współczynnik korelacji liniowej Pearsona dla analizowanych w artykule parametrów. Przemieszczenia pionowe i analizę dokładności uzyskanych wartości wykonano dla zmodyfikowanego przykładu praktycznego zaczerpniętego z literatury przedmiotu [2]. Natomiast problem predykcji przedstawiono w oparciu o symulowane wyniki pomiaru przyspieszeń trzech PK badanego obiektu i ich błędów średnich. Prezentowane opracowanie jest uzupełnieniem i rozszerzeniem teoretyczno- empirycznych analiz przedstawionych w pracy [5].
Glass-ceramic joining of Fe22Cr porous alloy to Crofer22APU: interfacial issues and mechanical properties
- Fabiana D'Isanto
- Milena Salvo
- Sebastian Molin
- Damian Koszelow
- Hassan Javed
- Sufyan Akram
- Andreas Chrysanthou
- Federico Smeacetto
2022 Pełny tekst CERAMICS INTERNATIONAL
This work deals with the joining of porous Fe22Cr ferritic stainless steel to a dense Crofer22APU plate by using a silica-based, Ba-containing glass-ceramic. The chemical and interfacial stability and the mechanical properties of the joints were evaluated before and after thermal ageing at 700 ◦C for 500hrs. The sintering behaviour of the glass was assessed by using heating stage microscopy (HSM) to study the influence of a porous metal substrate on the shrinkage of the joining material. Scanning electron microscopy revealed that there were no defects or cracks at the porous alloy/glass-ceramic interface for both the as-joined samples and the samples after thermal ageing at 700 ◦C for 500 h. However, at this exposure temperature, the porous alloy started to form an oxide scale at the interface with the glass-ceramic and the internal surface of the porous alloy. Finally, the evaluation of the mechanical properties by tensile testing showed that the properties were not affected by thermal ageing at 700 ◦C.
Global defensive secure structures
- Michał Małafiejski
- Kacper Wereszko
2022
Let S ⊂ V (G) for a given simple non-empty graph G. We define for any nonempty subset X of S the predicate SECG,S(X) = true iff |NG[X]∩S| ≥ |NG[X]\S|. Let H be a non-empty family of graphs such that for each vertex v ∈ V (G) there is a subgraph H of G containing v and isomorphic to a member of H. We introduce the concept of H-alliance extending the concept of global defensive secure structures. By an H-alliance in a graph G we mean a set S ⊂ V (G) such that (1) each vertex v ∈ S belongs to a subgraph H of G that is isomorphic to a member of H, and (2) for each H ⊂ G[S] isomorphic to a member of H, SECG,S(V (H)) = true. If S is also a dominating set of G, we call it a global H-alliance of G. If H = {K1}, then such an H-alliance we call a defensive alliance (GA) [1] or a vertex alliance. If H = {K2}, then such an H-alliance we call an edge alliance [2]. In the case of H is a class of all complete graphs (i.e., K1, K2, . . .), then an H-alliance we call a complete alliance [3]. If H = {K1, . . . , Kk}, then an H-alliance we call k-complete alliance. In this talk we present general properties of global defensive secure structures (i.e., H-alliances), algorithms for H-alliance problems (exact and approximation ones), and we provide new N P-complete results for global defensive secure structures for bounded degree graphs. We formulate also H-alliance problem in some special cases as ILP problem and study a few algorithmic approaches.
Global Design Optimization of Microwave Circuits Using Response Feature Inverse Surrogates
- Anna Pietrenko-Dąbrowska
- Sławomir Kozieł
- Leifur Leifsson
2022
Modern microwave design has become heavily reliant on full-wave electromagnetic (EM) simulation tools, which are necessary for accurate evaluation of microwave components. Consequently, it is also indispensable for their development, especially the adjustment of geometry parameters, oriented towards performance improvement. However, EM-driven optimization procedures incur considerable computational expenses, which may become impractical even in the case of local tuning, and prohibitive whenever global search is vital (e.g., multi-model tasks, simulation-based miniaturization, circuit re-design within extended ranges of operating frequencies). This work presents a novel approach to a computationally-efficient globalized parameter tuning of microwave components. Our framework employs the response feature technology, along with the inverse surrogate models. The latter permit low-cost exploration of the parameter space, and identification of the most advantageous regions that contain designs featuring performance parameters sufficiently close to the assumed target. The initial parameter vectors rendered in such a way undergo then local, gradient-based tuning. The incorporation of response features allows for constructing the inverse model using small training data sets due to simple (weakly-nonlinear) relationships between the operating parameters and dimensions of the circuit under design. Global optimization of the two microstrip components (a coupler and a power divider) is carried out for the sake of verification. The results demonstrate global search capability, excellent success rate, as well as remarkable efficiency with the average optimization cost of about a hundred of EM simulations of the circuit necessary to conclude the search process.
Global Surrogate Modeling by Neural Network-Based Model Uncertainty
- Leifur Leifsson
- Jethro Nagawkar
- Laurel Barnet
- Kenneth Bryden
- Sławomir Kozieł
- Anna Pietrenko-Dąbrowska
2022
This work proposes a novel adaptive global surrogate modeling algorithm which uses two neural networks, one for prediction and the other for the model uncertainty. Specifically, the algorithm proceeds in cycles and adaptively enhances the neural network-based surrogate model by selecting the next sampling points guided by an auxiliary neural network approximation of the spatial error. The proposed algorithm is tested numerically on the one-dimensional Forrester function and the two-dimensional Branin function. The results demonstrate that global surrogate modeling using neural network-based function prediction can be guided efficiently and adaptively using a neural network approximation of the model uncertainty.
Global value chains and labour markets – simultaneous analysis of wages and employment
- Sabina Szymczak
- Joanna Wolszczak-Derlacz
2022 Pełny tekst Economic Systems Research
This study examines the overall effect of global value chains (GVCs) on wages and labour demand. It exploits the World Input–Output Database to measure GVC involvement via recently developed participation indices (using both backward and forward linkages) and the relative GVC position using three-stage least squares regression. We find that the relative GVC position is negatively correlated with wages and employment and that the GVC participation effect depends on whether backward or forward linkages are considered. Moreover, we find heterogeneity across both countries (middle- vs high-income) and sectors (manufacturing versus services). Notably, the effect of GVC involvement on the labour market differs from that produced by traditional domestic trade.