bluuebunny/crossref_metadata_2025_split huggingface dataset:
Can multifarious types of green bonds be accused of greenwashing with a durative analysis? Insights from a permanent causality vs. temporary causality phenomenon
Authors: Ghaemi Asl Mahdi , Smutka Lubos , Nasr Isfahani Mohammad , Raza Syed Ali , Vasa László 
Published: February 2024

AbstractGreen bonds are useful monetary tools that can finance sustainable endeavors to bolster an eco-friendly economy. This research inspects the frequency-domain causal relationship between diverse green bond types and the green economy from June 30, 2014 to August 3, 2023. The goal is to understand both permanent and temporary causal phenomena between them. The findings reveal that only pioneering green bonds display a robust bidirectional causal link with an eco-efficient economy. Meanwhile, other green bond types, like conventional, municipal, and currency-dominated green bonds, may be susceptible to greenwashing due to the absence of a thorough permanent causal tie with an ecologically sustainable economy. Additionally, enhancing pioneering green bonds by integrating ESG (Environmental, Social, and Governance) stocks can transform the cause-and-effect dynamic between specific green bonds and the green economy. It shifts from a bilateral cause to a unilateral one stemming from the environmentally friendly economy and extending to distinguished green bonds. This phenomenon persists whether the 5% annual fee for sustaining and managing the index combining green bonds and ESG equities is considered or not. Interestingly, an environmentally conscious economy, in both persistent and transient associations, consistently affects ecological bonds with diverse traits. This highlights the importance of the overall state of an environmentally responsible economy in enhancing green bonds. These discoveries provide novel perspectives for green market regulators and policymakers to design improved standards for green assets.
Improvement of biogas yields in an anaerobic digestion process via optimization technique
Authors: Obileke KeChrist , Makaka Golden , Tangwe Stephen , Mukumba Patrick 
Published: February 2024

AbstractAnaerobic digestion for biogas production was first used in 1895 for electricity generation and treating municipal solid waste in 1939. Since then, overcoming substrate recalcitrance and methane production has been one way to assess the quality of biogas production in a sustainable manner. These are achieved through pre-treatment methods and mathematical modeling predictions. However, previous studies have shown that optimisation techniques (pre-treatment and mathematical modeling) improve biogas yield efficiently and effectively. The good news about these techniques is that they address the challenges of low efficiency, cost, energy, and long retention time usually encountered during anaerobic digestion. Therefore, this paper aims to comprehensively review different promising pre-treatment technologies and mathematical models and discuss their latest advanced research and development, thereby highlighting their contribution towards improving the biogas yield. The comparison, application, and significance of findings from both techniques, which are still unclear and lacking in the literature, are also presented. With over 90 articles reviewed from academic databases (Springer, ScienceDirect, SCOPUS, Web of Science, and Google Scholar), it is evident that artificial neural network (ANN) predicts and improves biogas yield efficiently and accurately. On the other hand, all the pre-treatment techniques are unique in their mode of application in enhancing biogas yield. Hence, this depends on the type of substrate used, composition, location, and conversion process. Interestingly, the study reveals research findings from authors concerning the enhancement of biogas yield to arrive at a conclusion of the best optimization technique, thereby making the right selection technique.
Graphical Abstract
Knowledge Graph Embedding via Triplet Component Interactions
Authors: Wang Tao , Shen Bo , Zhang Jinglin , Zhong Yu 
Published: February 2024

AbstractIn knowledge graph embedding, multidimensional representations of entities and relations are learned in vector space. Although distance-based graph embedding methods have shown promise in link prediction, they neglect context information among the triplet components, i.e., the head_entity, relation, and tail_entity, limiting their ability to describe multivariate relation patterns and mapping properties. Such context information denotes the entity structural association inside the same triplet and implies the correlation between entities that are not directly connected. In this work, we propose a novel knowledge graph embedding model that explicitly considers context information in graph embedding via triplet component interactions (TCIE). To build connections between components and incorporate contextual information, entities and relations are represented as vectors comprised of two specialized parts, enabling comprehensive interaction. By simultaneously interacting with one-hop related head and tail entities, TCIE strengthens the connections between distant entities and enables contextual information to be transmitted across the knowledge graph. Mathematical proofs and experiments are performed to analyse the modelling ability of TCIE in knowledge graph embedding. TCIE shows a strong capacity for modelling four relation patterns (i.e., symmetry, antisymmetry, inverse, and composition) and four mapping properties (i.e., one-to-one, one-to-many, many-to-one, and many-to-many). The experimental evaluation of ogbl-wikikg2, ogbl-biokg, FB15k, and FB15k-237 shows that TCIE achieves state-of-the-art results in link prediction.
A Graph Contrastive Learning Model Based on Structural and Semantic View for HIN Recommendation
Authors: Yu Ruowang , Xin Yu , Dong Yihong , Qian Jiangbo 
Published: February 2024

AbstractWith the rapid growth of information in the Internet era, people are in great need of recommendation methods to filter information. At present, recommendation methods which based on heterogeneous information network (HIN) have attracted wide attention. Recently, HIN-based recommendation methods need to be modeled from two aspects: node structural association and semantic association. To this end, we propose a graph contrastive learning model based on structural and semantic view for HIN recommendation (GCL-SS). GCL-SS utilizes U-I interactive view to obtain node structural embeddings, and utilizes U-I semantic view to obtain node semantic embeddings. Based on these two kinds of embeddings, we establish a self-supervised contrastive learning mechanism to effectively integrate structural information and semantic information of user (item) nodes in HIN, and finally learn a more discriminative user (item) embedding. In addition, in order to strengthen the semantic association between nodes, we innovatively utilize time sequence encoder (TSE), such as LSTM, to encode semantic homogeneous network decomposed by HIN in U-I semantic view. At last, based on the user and item embeddings, we adopt bilinear decoder to model the potential association between user and item, so as to realize rating prediction of user to item. The experimental results on three real datasets confirm that our GCL-SS model performs better than state-of-the-art recommendation methods in rating prediction task. In addition, the results of four ablation experiments indicate that our GCL-SS model can effectively improve the performance of rating prediction in recommendation.
Hydropower Reservoir Optimization with Solar Generation-Changed Energy Prices in California
Authors: Dogan Mustafa Sahin , Medellin-Azuara Josue , Lund Jay R. 
Published: February 2024

AbstractGrowing solar photovoltaic supply has significantly reshaped energy prices, lowering them during solar generating hours. Large-scale hydropower reservoir operations need to adapt to changes in energy prices to maximize hydropower revenue. This paper evaluates effects of solar generation-changed energy prices on hydropower generation for five multipurpose reservoirs in California using a hydroeconomic optimization model. In California, major solar generation began in 2013, so years 2010–2012 are a pre-solar period, and years 2013–2018 are post-solar. Reservoir operations, hydropower generation and revenue between these periods are compared. Operations in the wet season (January to June), and the dry season (July to December) are evaluated. Results show that releases are more profitable when hydropower is generated twice a day during on-peak hours in the morning and evening in the wet season. When water is scarce, energy is generated only during the higher-price evening peak. Hydropower generation is mostly curtailed between 10am and 6pm due to large solar supplies, and increase during morning and evening peaks when solar generation is unavailable. However, by optimizing hydropower scheduling hours, the new energy price pattern can be more profitable. With increased energy price variability and adaptation, overall daily revenue can increase by about 14% in the wet season and 30% in the dry season.
Determination of Young’s Modulus of PET Sheets from Lamb Wave Velocity Measurement
Authors: Lu H. , Menary G. 
Published: February 2024

Abstract
Background
The elastic modulus of polyethylene terephthalate (PET) sheets is typically measured through destructive tests that require specific sample preparation and time-consuming testing procedures.

Objective
To improve the efficiency of measuring the elastic modulus of PET sheets, research on a non-destructive measurement approach using guided Lamb waves was conducted.

Methods
In this approach, the group velocity of the zero-order symmetric Lamb wave mode (S0 mode) at a single frequency is first measured from PET sheets. The semi-analytical finite element method (SAFEM) is used as the forward model to calculate the corresponding numerical group velocity. Particle swarm optimisation (PSO) is used to update the elastic modulus in the SAFEM model until the numerical group velocity from the model matches the experimental results.

Results
The results show that measuring the group velocity data at a single frequency is sufficient for elastic modulus measurement while the material thickness can be assumed as a constant, which improves the efficiency of the measurement. The identified modulus differs from the tensile modulus of the material due to the frequency dependence of the elastic modulus. However, this discrepancy could be eliminated by using a linear regression model.

Conclusions
The method mentioned above can achieve non-destructive and efficient measurement of the elastic modulus of PET sheets, which can potentially be applied for in-line quality inspection in PET bottle production processes.
Short selling and firm investment efficiency
Authors: Yu Chang 
Published: February 2024

AbstractThis paper investigates the informativeness of short sales on detecting firm investment inefficiency. Neoclassical and agency theory suggest that investment inefficiency destroys firm value by allocating resources to less-valued uses. This paper finds that short-sellers adjust their short positions before the announcement of a financial statement, to use their information advantage on firm investment inefficiency. The relation between the short positions in a firm and its future investment inefficiency is both statistically and economically significant, and robust to a broad set of control variables. Subsample analyses show that the informativeness of short sales positions about future investment inefficiency is concentrated on overinvestment firms, firms with little board independence, and firms with low CEO incentive pay.
New Potato Varieties Resistant to Late Blight and with High Quality for French Fries Generated in Peru
Authors: Gastelo Manuel , Pérez Willmer , Eyzaguirre Raul , Quispe Katherine , Sanabria Kimberlayn , Bastos Carolina , Otiniano Ronal , Pérez Juan M. , Mendoza Alejandro , Unda Trinidad , Andrade Jorge 
Published: February 2024

AbstractPotato is one of the main crops worldwide and generates income for small-scale farmers, and it is a primary component of the diet of rural inhabitants, especially in developing countries. In Peru, the demand for French fries in traditional restaurants, rotisserie chicken (“Pollerias”), and fast-food restaurants is increasing every day. However, supply is covered by imported pre-fried potatoes. During the 2019–2020 and 2020–2021 growing seasons, ten potato clones belong to the International Potato Center (CIP) breeding program, and two Peruvian varieties used for frying as controls UNICA (CIP392797.22) and INIA 303-CANCHAN (CIP380389.1) were tested in 13 trials in farmers' fields placed in the north, center, and south of Peru using a randomized complete block design with three replications of 150 plants. Late blight severity and yield were evaluated under field conditions, and the contents of dry matter and reducing sugars were determined with laboratory tests. Clones CIP395123.6, CIP396026.101, and CIP396034.103 were selected for their high level of resistance to late blight, yields over 30 t/ha, with more than 20% dry matter, less than 0.20% reducing sugars and excellent quality for French fries’ sticks. Selected clones have been registered in the official register of cultivars of Peru, as new varieties. The standard of living of small and medium-scale potato farmers can be improved with the production of these new varieties, which support the health of producers and consumers and the environment. New potato varieties can be used as parents in breeding programs around the world.
45S5/PEEK Coatings by Cold Gas Spray with In Vitro Bioactivity, Degradation, and Cellular Proliferation
Authors: Garrido Beatriz , Albaladejo-Fuentes Vicente , Dosta Sergi , Garcia-Giralt Natalia , Garcia-Cano Irene 
Published: February 2024

AbstractThis study evaluated the biological response of cold-sprayed coatings composed of bioactive glass 45S5 and polyetheretherketone (PEEK). The functional coatings were produced by cold gas spray (CGS) technology, a technique that allows the deposition of powders at significantly low temperatures, avoiding heat damage to polymeric surfaces. By CGS, blends with different ratios of bioactive glass and PEEK powders have been deposited onto PEEK substrates to improve the response of the bio-inert polymer. The bioactivity of the coatings when immersed in a simulated body fluid solution was evaluated by observation with scanning electron microscopy (SEM) and x-ray diffraction (XRD). Results verify that bioactive glass particles in the composite coatings enhance their bioactivity. A degradation test was performed with Tris–HCl solution. From the results obtained by inductively coupled plasma optical emission spectroscopy (ICP-OES) and the weight loss of the samples, it was noticed that the degradation was directly related to the amount of glass in the coatings. Finally, the ability of bone-forming cells to adhere and proliferate on the coatings was evaluated. These experiments showed that the presence of glass particles does not cause a significant increase in cell proliferation. Combining a bioactive material with PEEK leads to forming a final component that provides suitable bioactivity to the final implant.
Fretting Behavior of WC-Co-Cr Coatings Against QT Steel in Bolted Joint
Authors: Haaja Vilma , Varis Tommi , Laurila Jussi , Isakov Matti 
Published: February 2024

AbstractFretting damage on contacting surfaces introduces major challenges in mechanical assemblies. Thermal sprayed hardmetal coatings are extensively used for surface modification in tribological applications under demanding conditions and may also be subjected to fretting-inducing loading. In the present work, the fretting behavior of High Velocity Oxy-Fuel (HVOF) and High Velocity Air–Fuel (HVAF) sprayed WC-10Co-4Cr coatings against quenched and tempered (QT) steel was studied by using a single bolt joint-type fretting experiment. This experimental approach was selected to obtain realistic data on the fretting fatigue performance of the contact pairs (both coating-to-steel and coating-to-coating). Experimental results were completed with continuum-scale linear elastic finite element method (FEM) calculations.
A new approach to pedestal differentiation for soil loss estimation—a case study from a burnt area in north-central Portugal
Authors: Verheijen Frank G. A. , Martins Martinho A. S. , Prats Sergio A. , Keizer Jan J. 
Published: February 2024

AbstractSoil pedestals have long been used as qualitative indicators of soil splash erosion. In rangelands, plant-capped pedestals, generally grass tussocks, have also been used to quantitatively estimate soil loss since the first half of the twentieth century. In agricultural lands, forests, and badlands, stone-capped pedestals have been used as qualitative and semi-quantitative indicators of active, ‘extreme’ erosion. Little work has been reported on using capstone pedestal data for quantifying soil loss. We postulate that three distinct capstone pedestal types may be present in any given location and that a detailed analysis of a pedestal height histogram may be used to recognize their populations. This analysis can subsequently inform if soil loss can be reliably estimated and if so, which of the existing methods using pedestal height data will provide more accurate results. The three proposed capstone pedestal types are: (1) neo-pedestals formed underneath surface stones exposed by (partial) removal of the soil surface cover; (2) endo-pedestals formed underneath stones that were buried in the soil but have been exposed by erosion; and (3) phoenix-pedestals formed underneath stones from collapsed pedestals. In the pedestal height histogram of any given location, a skew to smaller heights may indicate the existence of endo- and/or phoenix-pedestals, which may be revealed as a bi-(or tri) modal distribution when using a smaller bin size. This concept was applied to a case study where soil loss had been monitored for control plots and mulched plots during a 5-year period following wildfire in a eucalypt plantation. We measured pedestal heights and used methods to quantitatively assess soil loss from soil pedestal data in the available literature. Soil pedestal data at the end of the 5-year period under or overestimated soil loss in the control treatment, with results ranging from 60 to 115% of measured soil loss, depending on the method. It is postulated that phoenix- and endo-pedestals may be a driving factor behind the observed discrepancies. We discuss how future research may provide more insight into dominant processes, and how frequency distributions may be used to select the best methods for estimating soil loss from pedestals.
Corporate sustainability, organizational resilience, and corporate purpose: a review of the academic traditions connecting them
Authors: Florez-Jimenez M. P. , Lleo A. , Ruiz-Palomino P. , Muñoz-Villamizar A. F. 
Published: February 2024

Abstract
The increasing complexity of economic, environmental, and social systems causes crises, uncertainty and risk to become common global issues, and organizations that want to achieve long-term prosperity must pursue corporate sustainability, i.e., the joint pursuit of environmental, social, and economic goals, in order to successfully face the complex and uncertain environment in which these organizations find themselves. To achieve the above, organizational resilience would also seem to be critical, as it is a capacity which enables the organization to build a risk-aware culture that helps it better position itself to deal with the demands of high-impact events as well as to be able to find opportunities through uncertainty. Yet, both corporate sustainability and organizational resilience are organizational capabilities that can nourish (and/or be nurtured by) a corporate purpose that leads organizations to have a clear and inspiring sense of direction, fostering the development of strong responsible and adaptive behaviors. Nevertheless, the academic traditions that relate and explain “how” these concepts are related are non-existent. To bridge the above gap, we conducted a science mapping analysis and discovered that by 2022, a total of 34 documents had presented the relationship between sustainability, organizational resilience and corporate purpose. The analysis of these 34 papers yields five different academic traditions from which the relationship between these three concepts has been studied and reveals several gaps that future research should address to gain a holistic understanding of the interconnectedness of these three concepts to help organizations achieve long-term prosperity.
Desmoglein-2 Affects Vascular Function in Moyamoya Disease by Interacting with MMP-9 and Influencing PI3K Signaling
Authors: Wang Ajun , Li Nan , Zhang Nan , Liu Jian , Yang Tao , Li Dongxue , Li Changwen , Li Rui , Jiang Tongcui , Xia Chengyu 
Published: February 2024

AbstractThe pathogenesis and development of Moyamoya disease are still unclear. This study aimed to investigate the effect of desmoglein-2 (DSG2) on Moyamoya disease and determine the inhibitory effect of DSG2 in vascular remodeling in Moyamoya disease.RNA sequencing, immunohistochemistry (IHC), and western blotting were used to detect the expression of DSG2 in the superficial temporal artery (STA) tissues of Moyamoya disease. The association between DSG2 and endothelial cells’ biological activities was investigated by cell counting kit-8 (CCK-8), migration assay, tube formation assay, flow cytometry with Annexin V-FITC/PI staining, and TUNEL apoptotic cell detection kit. Pathways affected by overexpression or knockdown of DSG2 were identified in endothelial cells.The expression of DSG2 in the STA tissues of Moyamoya disease was lower than that in normal controls. Overexpression of DSG2 inhibits the proliferation and migration but promotes apoptosis in endothelial cells, and low DSG2 levels result in impaired angiogenesis. In addition, there was an interaction between DSG2 and MMP-9, and DSG2 acted through the PI3K signaling in endothelial cells.Our results indicate that DSG2 affects PI3K signaling in vascular endothelial cells, and MMP-9 is involved in DSG2-mediated vascular changes in Moyamoya disease.
Bilateral cavernous sinus and ophthalmic vein thrombosis secondary to Trueperella pyogenes rhinosinusitis
Authors: Calo’ Lea , Scarano Emanuele , Brigato Francesca , Di Cintio Giovanni , Galli Jacopo 
Published: February 2024

AbstractOphthalmic vein thrombosis is a severe clinical entity with proptosis, eyelid swelling, orbital pain and reduction of visual acuity; its incidence is rare with 3–4 cases /million /year. Clinical manifestations result from venous congestion caused by septic (orbital cellulitis) or aseptic aetiologies (coagulopathies, trauma) and in some cases it could be associated with cavernous sinus thrombosis. In this paper, we describe a case report unique in the literature, of bilateral cavernous sinus and ophthalmic veins thrombosis due to both septic and aseptic causes characterized by unilateral sphenoid sinusitis sustained by Trueperella pyogenes infection. Trueperella pyogenes is an opportunistic animal pathogen, and its infections occur in both domestic and wild animals worldwide but are rare in humans; this is the first instance of human infection in the head and neck with an unknown hypercoagulable state.