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Greening the future: assessing the influence of technological innovation, energy transition and financial globalization on ecological footprint in selected emerging countries

Laszlo Vasa Xiqiang Xia Muhammad Sibt-e-Ali Muhammad Qasim Javaid Kashif Javed

Publication Name: Environment Development and Sustainability

Publication Date: 2026-01-01

Volume: 28

Issue: 1

Page Range: 2105-2131

Description:

Environmental dangers have escalated due to human ecological pressure during the past few decades. This pressure can be measured by the environmental footprint (EFT) that humanity has left behind. At this point, the most effective methods for achieving sustainable development without causing damage to the environment include green technological innovation (TCH), climatic technology (CLT), energy transition (ENT), financial globalization (FGL), and economic growth. In light of this, the primary purpose of this research is to examine the impact of economic development, TCH, CLT, ENT, and FGL, as well as economic growth on the EFT in a selection of rising countries between the years 1990 and 2021. We use a unique DOLS and FMOLS model to analyze the relationships between the variables. In addition, the MMQR model is utilized in our research to validate the results produced using the DOLS and FMOLS methodologies. Through a reduction in the EFP, the findings indicate that TCH, CLT, and ENT all contribute significantly to an improvement in the quality of the environment. On the contrary, FGL, economic expansion, and urbanization all have a significant positive impact on EFT and contribute to climate degradation. Last but not least, the MMQR model's outcomes also demonstrated that TCH, CLT, ENT, FGL, urbanization, and economic expansion cause EFT. Based on the findings, it is recommended that governments and policymakers encourage investments in green innovation and renewable energy industries to attain ecological sustainability.

Open Access: Yes

DOI: 10.1007/s10668-024-05076-5

Preface II

Vikas Sharma Attila Kurucz Ewelina Idziak Vikas Sharma José Braga de Vasconcelos

Publication Name: World Sustainability Series

Publication Date: 2026-01-01

Volume: Part F1269

Issue: Unknown

Page Range: ix

Description:

No description provided

Open Access: Yes

DOI: DOI not available

Ride-Sharing Services in Regional Context: Consumer Attitudes and Reuse Intentions in Western Hungary

Boglárka Eisingerné Balassa Dániel Csikor Réka Koteczki Boglárka Eisinger Balassa Ferenc Szauter

Publication Name: Applied Sciences Switzerland

Publication Date: 2026-01-01

Volume: 16

Issue: 2

Page Range: Unknown

Description:

This study examines consumer attitudes and experiences related to ride-sharing services in the Western Transdanubia region of Hungary. Despite the growing global popularity of shared mobility solutions, there is little empirical evidence on regional consumer acceptance patterns in the Hungarian context. Based on a structured questionnaire survey involving 500 respondents, this research explores the relationship between satisfaction with past ride-sharing experiences and the intention to reuse such services in the future. The results reveal a high willingness to reuse among those who have already tried ridesharing, yet the correlation analysis shows that satisfaction dimensions alone are not significant predictors of reuse intention. In contrast, attitudinal factors, such as preference over other transport modes, willingness to make recommendations, and perceived accessibility, exhibit strong correlations with acceptance of ride-sharing. The findings emphasise the key role of attitudes and trust in shaping consumer decisions. The paper contributes to the literature by providing regionally grounded empirical insights and offers practical and policy-level recommendations to support the diffusion of sustainable shared mobility services.

Open Access: Yes

DOI: 10.3390/app16021055

Innovating for Net-Zero: Collaborative and Digital Decarbonisation Strategies in Sunset Industries' Global Value Chains

Muhammad Mustafa Kamal Narain Gupta Attique ur Rehman Justin Zuopeng Zhang Ashem Emmanuel Egila Remsei Sándor Jianwen Zheng

Publication Name: Business Strategy and the Environment

Publication Date: 2026-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Global net-zero ambitions require transformative strategies to decarbonise carbon-intensive global value chains (GVCs). This study examines how multinational enterprises (MNEs) in sunset industries integrate carbon capture technologies (CCT) with operational and supply chain dynamics (OSCD) to advance decarbonisation. Drawing on institutional theory (InsT) and dynamic capabilities theory (DCT), we investigate how external decarbonisation pressures activate internal capability routines that shape the adoption of technological and supply chain innovations. Using qualitative insights from 55 industry professionals across energy-intensive sectors, we analyse how firms navigate regulatory fragmentation, mobilise early-stage decarbonisation investments and develop collaborative and digital mechanisms to support low-carbon transitions. The findings reveal that coercive and normative pressures primarily stimulate sensing and seizing capabilities, while transforming capabilities develop more gradually through experiential learning and organisational reconfiguration. Firms often pursue hybrid CCT–OSCD strategies, combining technological interventions with operational and supply chain adjustments to manage institutional complexity. This study contributes theoretically by offering an integrated InsT–DCT framework that explains how institutional constraints and dynamic capabilities interact to enable decarbonisation in sunset industries. Managerially, the findings identify priority capability areas, including policy sensing, digital resource mobilisation and supply chain reconfiguration that can accelerate decarbonisation across global value chains.

Open Access: Yes

DOI: 10.1002/bse.70762

Adoptive T-cell therapies for persistent COVID-19 in immunocompromised patients: Comparison of IFN-γ virus-specific T-cell therapy and CD45RA+ T-cell depleted donor lymphocyte infusion

Dóra Mathiász Nóra Meggyesi János Sinkó Gabriella Bekő Botond Lakatos Andrea Ceglédi Hajnalka Andrikovics István Vályi-Nagy Bálint Gergely Szabó Szabolcs Tasnády Borisz Rabán Petrik Judit Bogyó Katalin Dobos Laura Giba-Kiss Orsolya Kis Gottfried Miskolczi Noémi Németh Ilona Bobek László Gopcsa János Szlávik Péter Reményi Marienn Réti Zsuzsanna Várnai Anikó Szilvási

Publication Name: Geroscience

Publication Date: 2026-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Advanced age, comorbidities, and immunocompromised states remain major risk factors for severe or persistent COVID-19 despite vaccination and antivirals, underscoring the need for innovative treatments such as adoptive T-cell therapy (ATT). In this prospective single-center study, we evaluated the safety, feasibility, and efficacy of two ATT approaches in immunocompromised patients with high-risk or persistent SARS-CoV-2 infection: interferon-γ cytokine capture system virus-specific T cells (IFN-γ CCS VST, n = 12; median age 59) and CD45RA + T-cell depleted donor lymphocyte infusion (CD45RA+ TCD DLI, n = 11; median age 46). Most patients (73.9%) had undergone prior hematopoietic stem cell transplantation (HSCT). Both treatments were safe, with no adverse events observed. One-year overall survival (OS) did not differ significantly between groups (p = 0.8907 overall; p = 0.5907 in HSCT recipients). However, CD45RA+ TCD DLI showed a trend toward improved 1-year COVID-19–free survival (p = 0.058) and significantly better survival among HSCT recipients (p = 0.0362). Viral clearance was achieved in most patients (90.9% vs. 83.3%). Immunomonitoring revealed distinct immune dynamics: between weeks 5–8, IFN-γ CCS VST promoted naïve T-cell expansion with broad cytokine elevation, while CD45RA+ TCD DLI expanded memory T cells with a more restricted cytokine profile. IFN-γ CCS VST also elicited stronger in vivo expansion of SARS-CoV-2–specific CD4 + and CD8 + T cells. In summary, both ATT approaches are safe and effective in immunocompromised patients with persistent COVID-19. CD45RA+ TCD DLI, which can be generated from convalescent donors as an off-the-shelf product, may provide a practical strategy for pandemic preparedness and treatment of vulnerable patients with immune senescence.

Open Access: Yes

DOI: 10.1007/s11357-025-02050-5

Cognitive Approaches to Multimodal Mobility: Integrating E-Scooters with Public Transport in Győr, Hungary

Ágoston Winkler Petra Szakonyi

Publication Name: Lecture Notes in Networks and Systems

Publication Date: 2026-01-01

Volume: 1768 LNNS

Issue: Unknown

Page Range: 72-77

Description:

The Public transport and micromobility roles, particularly electric scooters (e-scooters), are increasingly recognised as pivotal for sustainable urban mobility when integrated rather than made to compete. Cognitive mobility behaviour—how individuals select and combine transport modes—was examined through a systematic literature review, traffic counts conducted at peak-hour junctions, and an online survey of residents’ travel habits in Győr, Hungary. It was found that 46% of trips are made by private car, 24% by public transport, 8% by bicycle, 22% on foot, and only 1–3% by e-scooter. E-scooters were observed to be primarily used for short trips and first/last-mile connections, and reductions in car dependence were noted when e-scooters were integrated with public transport. The survey revealed that e-scooters most often replace walking (42%) and public transport (36%), with limited substitution of private car trips (13%). Significant gaps were identified in multimodal integration, infrastructure, legal frameworks, traffic monitoring, and public awareness. It is recommended that multimodal hubs, dedicated e-scooter lanes, improved traffic counting, and clearer regulations be implemented to support modal shift, enhance safety, and maximise environmental benefits.

Open Access: Yes

DOI: 10.1007/978-3-032-13898-9_8

HEAT AND MASS FLUX EFFECTS ON THE THERMODYNAMICS AND HYDRODYNAMICS OF TERNARY HYBRID NANOFLUID THROUGH A DISK

Mustafa Inc Wei Sin Koh C. Ganteda N. F.M. Noor U. V. Kalyani G. Pavani A. Anupama G. V.R. Reddy Ilyas Khan C. Ganteda G. V.R. Reddy Wei Sin Koh Siti Sabariah Abas D. Baba Basha

Publication Name: Fractals

Publication Date: 2026-01-01

Volume: 34

Issue: 6

Page Range: Unknown

Description:

This research examines the dynamics of heat transfer while highlighting the crucial role of Fourier heat flux concerning the thermodynamic and hydrodynamic characteristics of ternary hybrid nanofluids (HNFs) traversing a disk. The physical model and flow configuration were thoroughly analyzed under the influences of various parameters. The major equations that characterize the flow dynamics are formulated as partial differential equations (PDEs). By utilizing appropriate correspondence variables, the system of PDEs was altered keen on ordinary differential equations (ODEs). The coordination of coupled nonlinear equations is resolved arithmetically utilizing the “bvp4c function in MATLAB.” The influence of the principal appropriate factors on the radial speed, axial speed, and warmth is illustrated realistically. Ultimately, a table is constructed to demonstrate the interrelationships of numerous perilous issues on the Skin friction and Nusselt number. It was observed that an enhancement in the attractive constraint significantly diminishes the speed outline, attributable to the Lorentz influence caused by the applied attractive subject. Additionally, an enhancement in thermal transfer was observed as a consequence of an increase in thermal radiation.

Open Access: Yes

DOI: 10.1142/S0218348X26400542

Description of an arboreal oribatid mite species of the genus Ovobates (Acari, Oribatida, Oribatulidae), based on adult and nymphs from Vietnam

Sergey G. Ermilov Jenő Kontschán

Publication Name: Zootaxa

Publication Date: 2025-12-31

Volume: 5740

Issue: 1

Page Range: 112-124

Description:

The genus Ovobates (oribatida, oribatulidae) comprises two species distributed in the oriental region. A new species—Ovobates ochrocarpicus sp. nov.—is described, based on adult and nymphal instars, collected from branches of the ochrocarp tree in southern Vietnam. the adult of the new species is characterized by the presence of the five pairs of notogastral porose areas and the epimeral formula 3-1-3-3. the nymphs of the new species are characterized by presence of clavate bothridial seta; setiform interlamellar seta; short, setiform, thin gastronotic setae c1, c2, da, la; medium-sized to long, setiform, gastronotic setae dm c3, lm, p2, and p3; medium-sized, bacilliform gastronotic setae dp, h1, and h3; long, subflagellate, gastronotic setae lp, h2, and p1; epimeral formula 3-1-2-2 in tritonymph; and seven setae on the leg tarsus IV in protonymph. the generic diagnosis and a morphological comparison of adults and juvenile instars of the known species of Ovobates are presented.

Open Access: Yes

DOI: 10.11646/zootaxa.5740.1.9

An AI-Driven Framework for Network Intrusion Detection Using ANOVA-Based Feature Selection

Sándor Répás Salam Allawi Hussein

Publication Name: International Journal of Advanced Computer Science and Applications

Publication Date: 2025-12-31

Volume: 16

Issue: 12

Page Range: 853-861

Description:

In the last few years, cyberattacks have become more complex, and it is becoming increasingly necessary to establish secure networks. This study examines enhancements to intrusion detection systems (IDSs) with the implementation of machine learning for the categorization of network traffic attacks. For the current study, we utilize four publicly available datasets: CICIDS2017, CIC-DoS2017, CSE-CIC-IDS2018, and CIC-DDoS2019. We examined three machine learning techniques: LightGBM, Random Forest, and XGBoost. Experimental results showed that RandomForest and XGBoost achieved the highest accuracy of 0.99 in both binary and multi-class intrusion detection tasks, maintaining balanced performance with macro F1-scores around 0.86. LightGBM exhibited slightly lower overall performance, but benefited from ANOVA-based feature selection, which improved its recall and model stability. Feature selection also enhanced computational efficiency by reducing feature redundancy while preserving accuracy across models. These results highlight how AI tools could help network security deal with emerging threats and improve the performance of IDS. The study underscores the critical role of feature selection in enhancing model efficiency, hence promoting advancements in automated network security systems that can adapt to evolving cyber threats.

Open Access: Yes

DOI: 10.14569/IJACSA.2025.0161280