Search Results (899)

This study aims to develop and characterize novel dermatocosmetic formulations designed to hydrate the skin, improve its appearance, reduce wrinkles, and provide antioxidant, anti-ageing, antimicrobial, and anti-inflammatory benefits, along with potential protection against UVA and UVB radiation. The formulations contain the following ingredients: xanthan gum (0.5%), Calendula officinalis oil (5%), Argania spinosa oil (5%), Helianthus annuus oil (5%), liposomes containing a hydroalcoholic extract of pomace from local red or white grapes (2%), an olive oil-based emulsifier (6%), vitamin E (0.5%), cetearyl alcohol (3%), propylene glycol (8%), and purified water (up to 100%). The natural ingredients used in these formulations, i.e., the red or white grape pomace extract from the aforementioned Romanian varieties, the oils of Calendula officinalis, Argania spinosa, and Helianthus annuus, xanthan gum, and the olive oil-based emulsifier (Olliva), promote the concept of ‘green cosmetics’. The use of liposomes to deliver bioactive substances from hydroalcoholic extracts allows the gradual release of active ingredients into the skin. An alternative for incorporating grape pomace extract into a cream-type matrix involves the use of liposomes. Liposomes loaded with red or white grape pomace extract were prepared using the thin-film hydration technique, followed by ultrasonication and extrusion. The obtained formulations were characterized using bio-physico-chemical analysis procedures in terms of consistency, colour, homogeneity, aroma, pH, stretch, texture, stability, and antioxidant activity/free radical scavenging capacity, as well as in vitro polyphenol release behaviour. These newly developed dermatocosmetic formulations were the subject of a patent application in Romania. Full article

Existing research on green transformation predominantly emphasizes “hard constraints” such as carbon taxes and environmental regulations, while neglecting “soft constraints” shaped by environmental sentiment expressions from key actors such as the public, financial institutions, media, and government. In particular, the collective influence of these multi-actor environmental sentiments remains insufficiently explored. This study fills that gap by constructing a collaborative governance framework using multi-source heterogeneous data from China spanning 2013–2023, including 330 provincial government work reports, 1862 bank annual reports, 2472 newspaper articles, and 68,519 Weibo posts, matched to 4708 firm-year observations of Chinese A-share energy companies. We quantify environmental sentiment tendencies through natural language processing, calculating the index as (negative word frequency − positive word frequency)/total word frequency at the province-year level, thus higher index value indicates more negative sentiment tendency, while green transformation is proxied by ln(green patent applications + 1). The results reveal the following: (1) More negative environmental sentiment tendencies from financial institutions, media, public, and government significantly promote green transformation in energy enterprises, with stronger effects observed from financial institutions and government. (2) Economic and climate policy uncertainty selectively weaken the impact of financial institutions’ sentiment, while the moderating effects for other actors are statistically insignificant. (3) The effect of multi-actor environmental sentiment is more pronounced for firms located in eastern China, operating under high competition or stricter environmental regulations. This study provides a novel, quantified approach to assessing multi-actor environmental sentiment tendencies, affirms the effectiveness of informal governance, and highlights the importance of stable policy in guiding corporate green transformation in emerging economies. Full article

This study utilizes digital transformation and patent data from A-share listed companies on the Shanghai and Shenzhen stock exchanges in China between 2011 and 2021 to examine the influence of digital transformation on the quality of cross-regional collaborative innovation. The findings reveal that the cooperative innovation network exhibits pronounced small-world characteristics. In terms of spatio-temporal evolution, China’s urban collaborative innovation network demonstrates a notable quadrilateral spatial structure and has evolved toward a multicenter pattern. Moreover, the advancement of digital transformation positively contributes to both the quality and quantity of cross-regional cooperative innovation. By enhancing the relational embeddedness among cities, digital transformation facilitates improved outcomes in collaborative innovation. Furthermore, when the volume of digital patent applications surpasses a certain threshold, its positive effect on the quality of cross-regional collaborative innovation accelerates. These results provide empirical evidence from a major emerging economy, offering insights that can inform policies and strategies in other regions undergoing digital transition. The mechanisms identified, such as network structure evolution and relational embeddedness, contribute to a broader understanding of how digital transformation shapes innovation dynamics across geographical boundaries in a globalized knowledge economy. Full article

This paper considers a principle for constructing transverse differential protection of two parallel 6–35 kV power transmission lines on the supply side, previously proposed by the authors and protected by a patent. Its implementation makes it possible to identify the damaged line without using current and voltage transformers, by employing signals from reed switches installed near the corresponding phases of the lines. The principle is based on monitoring the difference in magnetic field inductions produced by the currents in these phases and determining the damaged line according to the sequence of reed switch actuations. Based on experimental studies of the temporal characteristics of reed switches and on simulation of magnetic fields around the line phases, methodologies for selecting protection operating parameters and for evaluating its sensitivity, taking into account the influence of errors and currents in the phases of both lines, have been developed; the field of application of the protection, the cascade zone, and the locations for installing the reed switches have been determined. It is shown that the calculated cascade zone of the proposed protection can be up to 20% shorter than that of both the traditional protection and a similar reed-switch-based protection. At the same time, in comparison with the latter, implementation of the considered principle requires three times fewer reed switches. The elimination of current and voltage transformers, as shown by the calculations, creates prerequisites for reducing the resource intensity of the protection. Full article

Sustained innovation is pivotal for establishing long-term technological advantages and ensuring corporate sustainability, which holds particular significance for “specialized, refined, unique, and innovative” (SRUI) enterprises that concentrate on niche segments and are innovation-intensive. Grounded in signaling theory and principal–agent theory, and situated within the practical context of financing constraints, this paper investigates how environmental, social, and governance (ESG) performance contributes to sustaining innovation in such firms. Using panel data from Chinese SRUI enterprises between 2010 and 2023, we measure sustained innovation along two dimensions: sustained innovation input and sustained innovation output. The results demonstrate that ESG performance significantly enhances sustained innovation among SRUI enterprises. Mechanism analysis reveals that ESG operates through three pathways: optimizing talent structure, mitigating managerial myopia, and strengthening working capital management. Heterogeneity tests further indicate that the positive effect of ESG on overall innovation sustainability is stronger with a younger management team and lower government subsidies. Moreover, in firms with heightened climate risk perception, ESG strongly promotes the sustained innovation input but exhibits a weaker effect on the continuity of innovative output. In enterprises with stronger big-data technology application capabilities, ESG significantly improves the continuity of patent output yet does not significantly affect the continuity of innovative input. This study extends the literature on the economic consequences of ESG from the perspective of sustained innovation, while providing new mechanistic evidence for understanding how highly specialized small and medium-sized enterprises build long-term innovation capacity. Full article

Deepwater drilling operations face critical challenges including narrow pore-fracture pressure windows, wellbore instability, and environmental concerns from drilling discharge. This paper presents a comprehensive systematic review of Riserless Mud Recovery (RMR) technology, tracing its evolution from its conceptual origins to its current applications, critically analyzing its technical limitations, and identifying future research directions. A systematic literature review was conducted covering peer-reviewed journals, SPE/IADC conference proceedings, industry technical reports, and independent academic studies from 1990 to 2025. Databases searched included Web of Science, Scopus, OnePetro, and Google Scholar, supplemented by Derwent Innovation Index for patents. After screening over 100 publications, approximately 60 references were selected following a two-step process excluding vendor-only promotional materials. Key findings reveal the following: (1) RMR technology has evolved through three distinct hardware generations—flexible hose systems, steel-pipe return lines with tandem pumps enabling deepwater breakthrough to 1419 m, and hybrid riser configurations for conceptual designs beyond 3000 m; (2) documented field benefits include 70% drilling fluid reduction, 9 days’ time savings per well, and successful mitigation of shallow geohazards across more than 1000 global well applications; (3) integration with casing-while-drilling and managed pressure cementing has enabled record-breaking performance of 1710 m in a single run; (4) independent academic validation confirms fatigue mechanisms affecting mud return lines; (5) systematic failure mode analysis identifies critical reliability issues in suction hoses, seals, and control systems; (6) quantitative economic analysis shows RMR cost-effectiveness depends on water depth, geological conditions, and environmental regulations. RMR technology has matured into a reliable drilling solution, yet its continued evolution requires addressing hardware limitations, developing dedicated well-control protocols, expanding to ultra-deepwater and emerging applications, and integrating digitalization for real-time optimization. Full article

This study investigates the application of artificial intelligence for predicting the compressive strength of a high-performance, eco-efficient engineered cementitious composite (ECC), designated mix S8-1, A. The composite incorporates supplementary cementitious materials and alternative aggregates derived from recycled glass waste. The binder system combines waste glass powder and silica fume, while the aggregate fraction includes recycled cobalt glass. An extensive experimental program involving 14 mixtures tested at 7, 28, 56, 90, and 120 days was performed to establish the reference mechanical and rheological properties. Mix S8-1, A achieved strength class C60/75 and workability corresponding to consistency class S4. To substantiate long-term performance, microstructural and chemical analyses were conducted on specimens preserved since 2011, using scanning electron microscopy (SEM) and X-ray fluorescence (XRF). The results confirmed a stable, densified microstructure, evidencing the long-term durability of the patented ECC formulation. For predictive modeling, a shallow feedforward artificial neural network with three hidden layers was developed and trained on 70 dataset entries representing mixture proportions and curing ages. Model performance was evaluated using cross-validation, achieving a coefficient of determination (R²) of 0.968, a mean absolute error of 1.96 MPa, and a root mean square error of 2.52 MPa. The results demonstrate that AI-based approaches can accurately predict the compressive strength of high-performance, environmentally sustainable ECCs incorporating recycled glass constituents, supporting both performance optimization and resource-efficient material design. Full article

In the era of technological revolution, high-tech industries have gained prominence in national innovation systems. However, China’s high-tech sector faces challenges such as late development, weak foundations, and regional disparities. To address these issues, this study proposes a shared-input two-stage network DEA model. This model, based on an input-output perspective, considers resources that circulate and collaboratively function across multiple stages in the form of shared inputs. This paper analyzes data from 25 provinces (including municipalities) in China from 2011 to 2020 and divides the patent conversion process into two sub-stages: the upstream technology research and development stage and the downstream achievement transformation stage, measuring the stage efficiency values and overall efficiency values, respectively. To align with reality, this paper incorporates the intensity of the strength of intellectual property protection, strength of government financial support, and the expenditure on technology import as regional shared input variables. Meanwhile, expenditure on technological transformation is treated as a capital-type intermediate input variable. This approach unveils the “black box” of single-stage DEA, enabling more accurate efficiency measurement. Key findings reveal: (1) China’s high-tech research and development of patent technology, the achievement transformation and overall conversion efficiency show annual improvement, yet overall efficiency remains low with regional imbalances; (2) Achievement transformation efficiency exerts a greater impact on overall conversion efficiency than research and development of patent technology efficiency. Comparative analyses with single-stage and chained two-stage DEA models confirm the necessity of phased evaluation and shared-input variables, supported by input-output elasticity tests. The findings validate the applicability and interpretability of the proposed model in efficiency evaluation. Full article

This study examines a panel of 268 Chinese cities during 2013–2023, employing patent applications in Low-carbon technologies (LCTs) as a proxy indicator for the level of LCTs. The spatiotemporal patterns of LCTs are characterized through integrated Standard Deviation Ellipses and Spatial Autocorrelation Techniques, while their driving mechanisms are investigated using Geographic Detectors. The key findings identified in this study are: (1) The advancement of LCTs exhibits a swift increasing trajectory; (2) The eastern region and provincial capital cities have relatively high levels of LCT, while western cities have lower levels. The overall trajectory of the gravity center moves southwest, and typical global and local spatial autocorrelation characteristics are observed in the cities; (3) Infrastructure construction and government R&D funding significantly drive LCTs, while environmental regulations show limited predictive power. Full article

Analyzing customer feedback is critical for identifying unmet needs in product development and innovation processes. However, current studies often focus only on identifying customer-expressed problems, neglecting to systematically match these problems with technological solutions and transform them into potential product features. This study aims to propose a sentiment and semantic analysis-based approach that correlates problems derived from customer feedback with patent-based solutions. The proposed approach utilizes Aspect-Based Sentiment Analysis to identify unmet needs from customer feedback, the BERTopic algorithm to extract solution-oriented themes from patent documents, and short text semantic similarity methods to associate problem-solution pairs. The applicability of the approach is demonstrated using 476 customer product reviews and 3548 patents in the Heating, Ventilation, and Air Conditioning (HVAC) field. The results show that customer-expressed problems can be semantically correlated with patent-based technological solutions, and these matches contribute to the identification of potential product features. The resulting problem-solution matches are structured along technological development horizons and presented as a technology roadmap output. The proposed approach offers a framework supporting systematic problem–solution matching based on sentiment and semantic analysis in technology-intensive sectors with large volumes of unstructured text data. Full article

Africa’s expanding youth population and rapid digitalization present opportunities for innovation and, ultimately, entrepreneurship and economic growth relevant for Sustainable Development Goal (SDG) 8—Decent Work and Economic Growth. However, the role of social media in shaping these outcomes remains underexplored empirically. This study examines how platform-specific social media use influences innovation, operationalized through external search breadth and depth, while considering macroeconomic moderators. Using panel data from 52 African countries from 2009 to 2022 and fixed effects regressions, the study links activities on Facebook, X (formerly Twitter), YouTube, LinkedIn, and Google to innovation indicators such as R&D expenditure, patent applications, and scientific publications. The findings suggest that YouTube use is consistently and positively associated with all innovation indicators, highlighting its role in knowledge diffusion and creative expression. By contrast, X and LinkedIn display neutral or negative effects. High internet penetration alone is not sufficient enough to spur innovation, underscoring the need for enabling macroeconomics factors such as GDP per capita and ease of doing business. This study concludes that visual open-access platforms, supported by education and institutional capacity, are vital for inclusive and sustained economic growth. Full article

This paper examines the relationship between innovation performance and international export competitiveness in four EU countries—Germany, Italy, Czechia, and Slovakia—during the period 2015–2024. The primary objective is to identify the relationship between the number of patent applications to the European Patent Office (EPO) and two key R&D input indicators: R&D expenditure per capita and the number of researchers and engineers per million inhabitants. Simultaneously, the study utilizes the Revealed Comparative Advantage (RCA) index to evaluate export specialization in medium-to-high innovation-intensive commodity groups. Although there are numerous studies on innovation, patents, or the significance of research and development, only rarely are these indicators linked to the competitiveness of countries according to comparative advantages in individual sectors. The results of the correlation analysis reveal significant national disparities: while a strong dependency was confirmed in Italy and Slovakia, the findings for Germany show a negative correlation, suggesting that German patenting activity is driven by factors beyond the examined R&D inputs. Panel regression also points out that simple correlation may not be able to clearly capture this relationship, as it may manifest itself with a time lag. From an absolute perspective, Germany maintains a leading position in all indicators, yet Italy demonstrates higher patent efficiency compared to Czechia despite having fewer researchers. The RCA analysis further highlights that while Germany and Italy maintain comparative advantages in high-innovation sectors, Czechia and Slovakia predominantly specialize in medium-innovation-intensive industries. Full article

This paper presents a patented design of a gravity flow rack with an energy recovery system, intended for pallet storage in first-in–first-out (FIFO) and last-in–first-out (LIFO) modes. Compared with conventional flow racks, the proposed solution integrates control of load-unit motion dynamics with energy recovery, thereby reducing losses and stabilising pallet flow. A Rack Energy Performance Index (REPI) is proposed to enable quantitative assessment of the energy consumption of storage racks in intralogistics applications. The research methodology comprised: (i) development of the mechanical architecture and pallet guidance principles; (ii) numerical modelling in the MSC Adams environment at Technology Readiness Level 3 (TRL-3); and (iii) validation using a full-scale prototype installed in a logistics centre. Operational tests confirmed stable operation, the required throughput, and the capability for energy compensation and recovery during storage cycles. The results indicate that energy-recovering racks can support the design of energetically passive warehouses. Full article

To comprehensively assess the emissions of flue gas pollutants from municipal solid waste incineration (MSWI) in China and their socioeconomic driving factors, this study employs a bottom-up approach to develop an integrated carbon and air pollutant emission inventory for 1016 MSWI plants in 2024. We apply a Random Forest (RF) model to analyze the underlying drivers. Results indicate that for air pollutants, NO_x has the highest emissions, whereas mercury (Hg) and dioxins (polychlorinated dibenzo-p-dioxins and dibenzofurans, PCDD/Fs) are identified as priority control pollutants due to their high toxicity. Spatially, emissions display a distinct “high in the east, low in the west” pattern, concentrated in eastern coastal provinces, with characteristic pollutants being prominent in specific regions. Meanwhile, among greenhouse gases (GHGs), CO₂ dominates mass emissions, while N₂O exhibits significant global warming potential. Driver analysis reveals that Gross Domestic Product (GDP) and MSWI treatment capacity are key common drivers, showing stable positive and negative contributions, respectively. The number of invention patent applications is specifically and strongly associated with NO_x and heavy metal emissions. This study provides a national-scale integrated quantification of MSWI emissions and a quantitative analysis of their driving mechanisms using RF, offering a critical data foundation and scientific basis for supporting synergistic pollution and carbon reduction. Full article

In the past two decades, important progress has allowed a better understanding of how light signals are perceived by plants, not only as a source of energy for photosynthesis but also as environmental cues that modulate growth, development, and stress responses. These advances open up promising prospects for light-based treatments in agriculture. This review synthesizes recent scientific findings on the application of specific wavelengths (from ultraviolet to infrared) to improve crop yield, quality, and resilience. The analysis focuses on controlled environment agriculture, where most experimental data have been generated and where the integration of lighting strategies is technically more feasible compared to open-field settings. Preharvest: we explore how spectral quality, intensity, and duration can be used to modulate plant growth, photosynthesis, defense pathways, and the accumulation of nutritional compounds. Postharvest: the focus shifts to how light can help maintain visual and nutritional quality, regulate ripening, limit pathogen development, and extend shelf-life. The review emphasizes plant photoreceptors and signal transduction pathways, as well as technical parameters such as spectrum selection, application timing, and lighting configuration. A selection of recent patents illustrates how fundamental research is being translated into deployable, energy-efficient lighting technologies for sustainable crop management. Full article