bluuebunny/crossref_metadata_2025 huggingface dataset:
Demographics and treatment of patients with primary membranoproliferative glomerulonephritis in Japan using a national registry of clinical personal records
Authors: Nakagawa Naoki , Kimura Tomonori , Sakate Ryuichi , Isaka Yoshitaka , Narita Ichiei
Published: July 2023

Background

Membranoproliferative glomerulonephritis (MPGN) is a rare glomerular injury that causes nephrotic syndrome and end-stage kidney disease. The nationwide demographics and treatment of Japanese patients with primary MPGN have not yet been reported.

Methods

We collected clinical personal records of patients with primary MPGN between 2015 and 2018 from the national registry organized by the Japanese Ministry of Health, Labour, and Welfare and investigated the characteristics of primary MPGN throughout Japan.

Results

Of 258 patients with primary MPGN, 199 and 59 showed nephrotic and non-nephrotic syndrome, respectively. The median age at onset was higher in patients with nephrotic syndrome than in those with non-nephrotic syndrome (45 [24–63] vs. 35 [14–53] years, respectively; P = 0.010). The use of oral prednisolone was significantly higher in patients with nephrotic syndrome than in those with non-nephrotic syndrome (73.9% vs. 59.3%, respectively; P = 0.032). When patients were divided into three age groups: adolescent and young adult group (≤ 39 years; n = 80), middle adult group (40–64 years; n = 111), and older adult group (≥ 65 years; n = 67), the use of oral prednisolone, cyclosporine, and mizoribine was significantly higher in the adolescent and young adult group than in the middle adult group. The mean dosage of oral prednisolone and mizoribine showed no differences among the three age groups.

Conclusion

The national registry of clinical personal records of primary MPGN could provide an informative insight into the characteristics, clinical features, and treatment approaches for patients with primary MPGN in Japan.
The Next Challenges of Vestibular Implantation in Humans
Authors: Stultiens Joost Johannes Antonius , Lewis Richard F. , Phillips James O. , Boutabla Anissa , Della Santina Charles C. , Glueckert Rudolf , van de Berg Raymond
Published: July 2023

Patients with bilateral vestibulopathy suffer from a variety of complaints, leading to a high individual and social burden. Available treatments aim to alleviate the impact of this loss and improve compensatory strategies. Early experiments with electrical stimulation of the vestibular nerve in combination with knowledge gained by cochlear implant research, have inspired the development of a vestibular neuroprosthesis that can provide the missing vestibular input. The feasibility of this concept was first demonstrated in animals and later in humans. Currently, several research groups around the world are investigating prototype vestibular implants, in the form of vestibular implants as well as combined cochlear and vestibular implants. The aim of this review is to convey the presentations and discussions from the identically named symposium that was held during the 2021 MidWinter Meeting of the Association for Research in Otolaryngology, with researchers involved in the development of vestibular implants targeting the ampullary nerves. Substantial advancements in the development have been made. Yet, research and development processes face several challenges to improve this neuroprosthesis. These include, but are not limited to, optimization of the electrical stimulation profile, refining the surgical implantation procedure, preserving residual labyrinthine functions including hearing, as well as gaining regulatory approval and establishing a clinical care infrastructure similar to what exists for cochlear implants. It is believed by the authors that overcoming these challenges will accelerate the development and increase the impact of a clinically applicable vestibular implant.
Serum thymic stromal lymphopoietin (TSLP) levels in atopic dermatitis patients: a systematic review and meta-analysis
Authors: García-Reyes Marlenne Marisol , Zumaya-Pérez Luis Carlos , Pastelin-Palacios Rodolfo , Moreno-Eutimio Mario Adán
Published: July 2023

Thymic stromal lymphopoietin (TSLP) is critical in developing allergic responses, including atopic dermatitis (AD). We systematically reviewed the literature to complete a meta-analysis to quantitatively summarize the levels of serum TSLP in AD. The study was prospectively registered in the PROSPERO database (ID = CRD42021242628). The PUBMED, SCOPUS, and Cochrane Library databases were reviewed, and original articles investigating serum TSLP in AD patients were included. Differences in TSLP levels of AD patients and controls were summarized by standardized mean differences (SMD) using a random effects model. Study quality was assessed by applying the Newcastle‒Ottawa Scale. Fourteen studies, which included 1,032 AD patients and 416 controls, were included. Meta-analysis showed that TSLP levels were significantly higher in the AD group than in the control group (SMD = 2.21, 95% CI 1.37–3.06, p < 0.001). Stratification by geographical region, age, disease severity, TSLP determination method, sample size, and study quality revealed significantly elevated TSLP levels in European AD patients (SMD = 3.48, 95% CI 1.75–5.21, p < 0.0001), adult AD patients (SMD = 4.10, 95% CI 2.00–6.21, p < 0.0001), child AD patients (SMD = 0.83, 95% CI 0.08–1.59, p = 0.031), and all severity groups with AD compared with the control group (mild: SMD = 1.15, 95% CI 0.14–2.16, p = 0.025; moderate: SMD = 2.48, 95% CI 0.33–4.62, p = 0.024; and severe: SMD = 8.28, 95% CI 4.82–11.74, p = 2.72e−6). Noticeably, adults showed higher serum TSLP levels than children with AD, and serum TSL levels increased according to AD severity. In conclusion, our meta-analysis demonstrates that circulating TSLP levels are elevated in patients with AD. Future studies are warranted to further elucidate the sources of heterogeneity.
Left atrial sphericity in relation to atrial strain and strain rate in atrial fibrillation patients
Authors: Hopman Luuk H.G.A. , Bhagirath Pranav , Mulder Mark J. , Demirkiran Ahmet , Mathari Sulayman El , van der Laan Anja M. , van Rossum Albert C. , Kemme Michiel J.B. , Allaart Cornelis P. , Götte Marco J.W.
Published: July 2023

Purpose

Left atrial (LA) sphericity is a novel, geometry-based parameter that has been used to visualize and quantify LA geometrical remodeling in patients with atrial fibrillation (AF). This study examined the association between LA sphericity, and LA longitudinal strain and strain rate measured by feature-tracking in AF patients.

Methods

128 AF patients who underwent cardiovascular magnetic resonance (CMR) imaging in sinus rhythm prior to their pulmonary vein isolation (PVI) procedure were retrospectively analyzed. LA sphericity was calculated by segmenting the LA (excluding the pulmonary veins and the LA appendage) on a 3D contrast enhanced MR angiogram and comparing the resulting shape with a perfect sphere. LA global reservoir strain, conduit strain, contractile strain and corresponding strain rates were derived from cine images using feature-tracking. For statistical analysis, Pearson correlations, multivariable logistic regression analysis, and Student t-tests were used.

Results

Patients with a spherical LA (dichotomized by the median value) had a lower reservoir strain and conduit strain compared to patients with a non-spherical LA (-15.4 ± 4.2% vs. -17.1 ± 3.5%, P = 0.02 and − 8.2 ± 3.0% vs. -9.5 ± 2.6%, P = 0.01, respectively). LA strain rate during early ventricular diastole was also different between both groups (-0.7 ± 0.3s− 1 vs. -0.9 ± 0.3s− 1, P = 0.001). In contrast, no difference was found for LA contractile strain (-7.2 ± 2.6% vs. -7.6 ± 2.2%, P = 0.30).

Conclusions

LA passive strain is significantly impaired in AF patients with a spherical LA, though this relation was not independent from LA volume.
Lignin nanoparticles as co-stabilizers and modifiers of nanocellulose-based Pickering emulsions and foams
Authors: Agustin Melissa B. , Nematollahi Neda , Bhattarai Mamata , Oliaei Erfan , Lehtonen Mari , Rojas Orlando J. , Mikkonen Kirsi S.
Published: July 2023

Nanocellulose is very hydrophilic, preventing interactions with the oil phase in Pickering emulsions. This limitation is herein addressed by incorporating lignin nanoparticles (LNPs) as co-stabilizers of nanocellulose-based Pickering emulsions. LNP addition decreases the oil droplet size and slows creaming at pH 5 and 8 and with increasing LNP content. Emulsification at pH 3 and LNP cationization lead to droplet flocculation and rapid creaming. LNP application for emulsification, prior or simultaneously with nanocellulose, favors stability given the improved interactions with the oil phase. The Pickering emulsions can be freeze–dried, enabling the recovery of a solid macroporous foam that can act as adsorbent for pharmaceutical pollutants. Overall, the properties of nanocellulose-based Pickering emulsions and foams can be tailored by LNP addition. This strategy offers a unique, green approach to stabilize biphasic systems using bio-based nanomaterials without tedious and costly modification procedures.
Marine sense. The Sea beyond Explicit Knowledge
Authors: Simon Lionel
Published: July 2023

I explore what is known as “marine sense” to highlight the specificity of tacit understandings of the environment in which intuition is pivotal to practical action. I argue that the concept of “marine sense” affords a finer and more nuanced understanding of the ways in which populations interact with marine environments and posit that the fishers’ knowledge is operative because it is coupled with other skills that make it suitable for action and for adopting effective behaviors. Thus “marine sense” and “knowledge” become two distinct forms (or modalities) of understanding the marine environment. I outline what research on “marine sense” could constitute in relation to recent advances on the interactions between humans and oceans in the context of my ethnographic fieldwork among the Wayuu of Manaure (Colombia). I specifically highlight frames of reference that inform how freediving underwater fishers organize their (dialogical) relationship to the sea through perceptions and sensations that are on a general level central to an intuitive understanding of observable events.
PoseEdit: enhanced ligand binding mode communication by interactive 2D diagrams
Authors: Diedrich Konrad , Krause Bennet , Berg Ole , Rarey Matthias
Published: July 2023

In this article, we present PoseEdit, a new, interactive frontend of the popular pose visualization tool PoseView. PoseEdit automatically produces high-quality 2D diagrams of intermolecular interactions in 3D binding sites calculated from ligands in complex with protein, DNA, and RNA. The PoseView diagrams have been improved in several aspects, most notably in their interactivity. Thanks to the easy-to-use 2D editor of PoseEdit, the diagrams are extensively editable and extendible by the user, can be merged with other diagrams, and even be created from scratch. A large variety of graphical objects in the diagram can be moved, rotated, selected and highlighted, mirrored, removed, or even newly added. Furthermore, PoseEdit enables a synchronized 2D-3D view of macromolecule-ligand complexes simplifying the analysis of structural features and interactions. The representation of individual diagram objects regarding their visualized chemical properties, like stereochemistry, and general graphical styles, like the color of interactions, can additionally be edited. The primary objective of PoseEdit is to support scientists with an enhanced way to communicate ligand binding mode information through graphical 2D representations optimized with the scientist’s input in accordance with objective criteria and individual needs. PoseEdit is freely available on the ProteinsPlus web server (https://proteins.plus).
Leveraging SMEs technologies adoption in the Covid-19 pandemic: a case study on Twitter-based user-generated content
Authors: Saura Jose Ramon , Palacios-Marqués Daniel , Ribeiro-Soriano Domingo
Published: July 2023

The COVID-19 pandemic has caused many entrepreneurs and small and medium enterprises (SMEs) to adapt their business models and business strategies to the consequences caused by the pandemic. In order to identify the main innovations and technologies adopted by SMEs in the pandemic, in the present study, we used a database of 56,941 tweets related to the coronavirus to identify those that contained the hashtag #SMEs. The final sample was analyzed using several data-mining techniques such as sentiment analysis, topic modeling and textual analysis. The theoretical perspectives adopted in the present study were Computer-Aided Text Analysis, User-Generated Content and Natural Language Processing. The results of our analysis helped us to identify 15 topics (7 positive: Free support against Covid-19, Webinars tools, Time Optimizer and efficiency, Business solutions tools, Advisors tools, Software for process support and Back-up tools; 4 negative: Government support, Payment systems, Cybersecurity problems and Customers solutions in Cloud, and and 4 neutral: Social media and e-commerce, Specialized startups software, CRMs and Finance and Big data analysis tools). The results of the present study suggest that SMEs have used a variety of digital tools and strategies to adapt to the changing market conditions brought on by the pandemic, and have been proactive in adopting new technologies to continue to operate and reach customers in a connected era. Future research should be directed towards understanding the long-term effects of these technologies and strategies on entrepreneurial growth and value creation, as well as the sustainability of SMEs in the new era based on data-driven decisions.
Covid Vaccination Disputes in Czechia: Political Myth-Making and Boundary Work
Authors: Chlup Radek
Published: July 2023

The paper argues that one of the reasons the suppression of scientific dissent during the Covid pandemic has been so severe was because the dominant scientific Covid narrative has been turned into a political myth, i.e. a narrative mobilizing groups in support of key moral values. Taking the example of Covid vaccination, I show the key values with which it became linked in Czechia. Questioning vaccination came to be seen as endangering these values, which made scientific dissent appear as particularly dangerous. I further analyse how this schematic discourse dealt with “free-vax” scientists, who were not against Covid vaccination as such but only against its blanket application. I show that their discreditation was mainly carried out by various fact-checking NGOs or social media influencers, who attempted to delegitimize them not by scientific arguments but rather by associating them with more dubious groups of social actors, or labelling their views as “disinformation”. This discrediting strategy was largely successful, but it also had some undesirable social and political backfire effects, in that it pushed some of the free-vaxxers out of the liberal democratic mainstream and forced them to seek alliance with more anti-systemic segments of the population in attempts at political resistance.
LCCNN: a Lightweight Customized CNN-Based Distance Education App for COVID-19 Recognition
Authors: Wang Jiaji , Satapathy Suresh Chandra , Wang Shuihua , Zhang Yudong
Published: July 2023

In the global epidemic, distance learning occupies an increasingly important place in teaching and learning because of its great potential. This paper proposes a web-based app that includes a proposed 8-layered lightweight, customized convolutional neural network (LCCNN) for COVID-19 recognition. Five-channel data augmentation is proposed and used to help the model avoid overfitting. The LCCNN achieves an accuracy of 91.78%, which is higher than the other eight state-of-the-art methods. The results show that this web-based app provides a valuable diagnostic perspective on the patients and is an excellent way to facilitate medical education. Our LCCNN model is explainable for both radiologists and distance education users. Heat maps are generated where the lesions are clearly spotted. The LCCNN can detect from CT images the presence of lesions caused by COVID-19. This web-based app has a clear and simple interface, which is easy to use. With the help of this app, teachers can provide distance education and guide students clearly to understand the damage caused by COVID-19, which can increase interaction with students and stimulate their interest in learning.
Issues of Expertise in Perception and Imagination: Commentary on Stokes
Authors: Kind Amy
Published: July 2023

In this commentary on Dustin Stokes’ Thinking and Perceiving, I focus on his discussion of perceptual expertise. This discussion occurs in the context of his case against modularity assumptions that underlie much contemporary theorizing about perception. As I suggest, there is much to be gained from thinking about considerations about perceptual expertise in conjunction with considerations about imaginative skill. In particular, I offer three different lessons that we can learn by way of the joint consideration of these two phenomena.
Fiscal windfalls and entrepreneurship: fostering entry or promoting incumbents?
Authors: Garmaise Mark J. , Natividad Gabriel
Published: July 2023

We study the impact of government fiscal windfalls on entrepreneurship through an analysis of shocks to transfer payments in Peru. These pure transfers generate higher government spending, and we contrast the impacts on incumbent firms and entrants. Incumbent exits from the financial system are reduced, but previously troubled firms experience deteriorating performance. Increased transfers result in higher rates of firm entry into formal borrowing and superior entrant outcomes. Overall, startups outperform non-startups after heightened transfers.
Evaluation of combinatorial optimisation algorithms for c-optimal experimental designs with correlated observations
Authors: Watson Samuel I. , Pan Yi
Published: July 2023

We show how combinatorial optimisation algorithms can be applied to the problem of identifying c-optimal experimental designs when there may be correlation between and within experimental units and evaluate the performance of relevant algorithms. We assume the data generating process is a generalised linear mixed model and show that the c-optimal design criterion is a monotone supermodular function amenable to a set of simple minimisation algorithms. We evaluate the performance of three relevant algorithms: the local search, the greedy search, and the reverse greedy search. We show that the local and reverse greedy searches provide comparable performance with the worst design outputs having variance$$<10\%$$<10%greater than the best design, across a range of covariance structures. We show that these algorithms perform as well or better than multiplicative methods that generate weights to place on experimental units. We extend these algorithms to identifying modle-robust c-optimal designs.
Course map learning with graph convolutional network based on AuCM
Authors: Xia Jianing , Li Man , Tang Yifu , Yang Shuiqiao
Published: July 2023

Concept map provides a concise structured representation of knowledge in the educational scenario. It consists of various concepts connected by prerequisite dependencies. With the abundance of educational resources available through MOOCs, encyclopedias, and electronic textbooks, extracting prerequisite dependencies and building concept maps becomes feasible. However, publicly accessible taxonomies or learning object information that can help identify prerequisites are rare. To address this, we have constructed a comprehensive dataset called the Australian Course Map data (AuCM), specifically tailored for training concept maps in the IT/CS field. The dataset comprises course descriptions from 14 different Australian universities. To identify prerequisite relationships between course concepts, we have employed an embedding-based approach that combines the Graph Convolutional Network (GCN) with pairwise features of concepts. We have evaluated the performance of our model with non-neural classifiers and neural networks for extracting these prerequisite relations.
Mechanism of bonding, surface property, electrical behaviour, and environmental friendliness of carbon/ceramic composites produced via the pyrolysis of coal waste with polysiloxane polymer
Authors: Eterigho-Ikelegbe Orevaoghene , Trammell Ryan , Ricohermoso Emmanuel , Bada Samson
Published: July 2023

A simple mixing-pressing followed by thermal curing and pyrolysis process was used to upcycle coal waste into high-value composites. Three coal wastes of different physicochemical properties were investigated. The hypothetical mechanisms of bonding between the coal particles and the preceramic polymer are presented. The textural properties of the coals indicated that the lowest volatile coal waste (PCD) had a dense structure. This limited the diffusion and reaction of the preceramic polymer with the coal waste during pyrolysis, thereby leading to low-quality composites. The water contact angles of the composites up to 104° imply hydrophobic surfaces, hence, no external coating might be required. Analysis of the carbon phase confirmed that the amorphous carbon structure is prevalent in the composites compared to the coal wastes. The dc volume resistivity of the composites in the range of 22 to 82 Ω-cm infers that the composites are unlikely to suffer electrostatic discharge, which makes them useful in creating self-heating building parts. The leached concentrations of heavy metal elements from the composites based on the end-of-life scenario were below the Toxicity Characteristic Leaching Procedure regulatory limits. Additionally, the release potential or mobility of the metals from the composites was not influenced by the pH of the eluants used. On the basis of the reported results, these carbon/ceramic composites show tremendous prospects as building materials due to these properties.

Graphical Abstract
Sextus and the Nature of Suspension
Authors: Dunphy Robb
Published: July 2023

This article is an investigation of the nature of suspension of judgement as it is conceived by Sextus Empiricus. I carry out this investigation by examining what I take to be Sextus’ most pertinent remarks on the topic and by considering them in the context of contemporary philosophical work on the nature of suspension. Against the more frequently encountered idea that Sextus is operating with a privative conception of suspension, I argue that Sextus instead has a metacognitive account of suspension, whereby suspending constitutively involves acknowledging that one is not in a position to tell whether or not p.
The Reliability of Single-Step and Double-Step Quench and Partitioning Heat Treatments on an AISI 420A Low Carbon Martensitic Stainless Steel
Authors: Barella S. , Gruttadauria A. , Menezes J. T. O. , Castrodeza E. M. , Quaini S. E. , Pelligra C. , McNally E. A.
Published: July 2023

The microstructural and mechanical effects of various single-step (SS) and double-step (DS) quench and partition (Q&P) heat treatments applied to an AISI 420A low carbon martensitic stainless steel (MSS) has been studied. The goal with this work is to reach a total elongation (E pct) of 12 pct and an ultimate tensile strength (UTS) above 1200/1300 MPa, but ultimately to achieve a superior strength-ductility balance in comparison to its traditional Quench and Temper (Q&T) counterpart. This is being done by retaining austenite within the steel’s martensitic matrix at room temperature (RT) using novel SS and conventional DS Q&P heat treatments. Considerable work has been done to optimize DS Q&P heat treatments, but little has been done to understand the effects of removing a subsequent heating cycle through SS Q&P heat treatments has on MSSs. With that being said, partitioning is performed at the same quench interruption temperature for the SS Q&P heat treatments, and reheated to a higher temperature for the DS Q&P heat treatments. Experimental investigations were carried out on 1 mm thick, sheet samples to increase the number of potential applications for this steel and heat treatment. The microstructure of different SS and DS Q&P heat treatments was investigated through X-ray diffraction (XRD) and transmission electron microscopy (TEM) while mechanical property investigations were carried out using tensile and fracture toughness testing. DS Q&P heat treated samples quenched to 130 °C and partitioned for industrially relevant times of 10 and 30 minutes featured the highest values in terms of total elongation, tensile strength and fracture toughness. The SS Q&P heat treatments, on the other hand, were able to achieve improved mechanical properties to its Q&T counterpart. Overall, this work opens up the possibility of increased MSS usage for reliable, thin-walled component production with improved properties through Q&P heat treatment methods. The best results achieved in this study are a UTS of 1585 MPa, E pct of 22 pct, and a fracture toughness of 77 kJ/m2. Their lower total elongation of 9.6 pct is balanced by high tensile strength of 1812 MPa, ensuring higher toughness compared to traditional Q&T samples.
A survey of metaheuristic algorithms for the design of cryptographic Boolean functions
Authors: Djurasevic Marko , Jakobovic Domagoj , Mariot Luca , Picek Stjepan
Published: July 2023

Boolean functions are mathematical objects used in diverse domains and have been actively researched for several decades already. One domain where Boolean functions play an important role is cryptography. There, the plethora of settings one should consider and cryptographic properties that need to be fulfilled makes the search for new Boolean functions still a very active domain. There are several options to construct appropriate Boolean functions: algebraic constructions, random search, and metaheuristics. In this work, we concentrate on metaheuristic approaches and examine the related works appearing in the last 25 years. To the best of our knowledge, this is the first survey work on this topic. Additionally, we provide a new taxonomy of related works and discuss the results obtained. Finally, we finish this survey with potential future research directions.
The path from mindfulness to self-esteem: self-concept-clarity and cognitive flexibility as mediators
Authors: Stenhaug Andreas , Solem Stian
Published: July 2023

Mindfulness is positively associated with self-esteem, yet little is known about possible mediators underlying this relation. In this study, the role of self-concept clarity and cognitive flexibility is examined as potential mediators. A predominantly female (78.9%) sample (N = 204) with a mean age of 31 years participated in a cross-sectional survey. They completed the Five Facet Mindfulness Questionnaire, the Rosenberg Self-Esteem Scale, the Self-Concept Clarity Scale, and the Cognitive Flexibility Scale. To examine relations between study variables, a multiple linear regression analysis was conducted, and a parallel mediation model was performed using the Hayes’ process macro. The regression analysis explained 56% of variance in self-esteem, and all study variables were significant predictors, with self-concept clarity as the strongest predictor. The results found support for partial mediation, with self-concept clarity exhibiting a strong association with self-esteem (β = 0.47). The effect of cognitive flexibility was weaker but significant (β = 0.16). Self-concept clarity and cognitive flexibility partially explained the path from dispositional mindfulness to self-esteem. This could indicate an explanatory role of these two factors, and suggests possible processes by which mindfulness may enhance self-esteem.
Iron-laden blasts in refractory acute myeloid leukemia
Authors: Vossen Christopher , Im Roeun , Horna Pedro
Published: July 2023

We report a case of refractory acute myeloid leukemia with DEK-NUP214 rearrangement showing circulating monocytic blasts with abundant green cytoplasmic granules on the Wright-Giemsa stain. The granules were strongly positive for Perls’ Prussian blue, consistent with hemosiderin deposits. This previously unreported finding is suggestive of siderophage activity by leukemic blasts, likely associated with monocytic differentiation.
The dispersal capacity of Mollusca—a test on the South Azorean Seamount Chain
Authors: Herrera José Antonio Caballero , Hoffman Leon , Freiwald André , Gofas Serge
Published: July 2023

This study investigates the molluscan fauna of the South Azorean Seamount Chain (SASC), which comprises several seamounts culminating in 300–1600 m depth, separated by distances less than 200 km. Material was collected mainly by dredging and comprises mostly empty shells. A total of over 111,000 shells representing at least 439 species (409 identified) was collected. Larval development was inferred from protoconch morphology, and the assemblage comprises species with planktotrophic larvae, with non-feeding planktonic larva, and with lecithotrophic larvae with direct development. The direct developers are more prevalent among species endemic to the SASC in the upper bathyal part (300–800 m) of the seamounts, whereas most planktotrophic species are shared with the Lusitanian seamounts and/or the European mainland. Nevertheless, there are notable exceptions to this trend, where species with non-planktotrophic larvae are also widespread, and a large proportion of the species with non-feeding planktonic larvae are shared with Eastern and/or Western Atlantic. Level of endemism of Mollusca is high within the SASC (22.5% overall, 35.8% considering only the interval < 800 m) and even higher (32.6% overall) when considering together the SASC and the Azores. The generic composition and large set of overlapping fauna suggest a strong relation to the temperate Eastern Atlantic, whereas only 19% of the species are shared with the Western Atlantic.
Capability of DHA biosynthesis in a marine teleost, Pacific saury Cololabis saira: functional characterization of two paralogous Fads2 desaturases and Elovl5 elongase
Authors: Matsushita Yoshiyuki , Kabeya Naoki , Kawamura Wataru , Haga Yutaka , Satoh Shuichi , Yoshizaki Goro
Published: July 2023

The Pacific saury Cololabis saira is an important fishery resource in the Far East, where it is appreciated for its high lipid content, which includes long-chain polyunsaturated fatty acids (LC-PUFAs) such as docosahexaenoic acid (DHA). Although it has been hypothesized that these fatty acids are derived from their prey items, this study focused on evaluating the capacity of saury for endogenous production of LC-PUFAs. To describe its LC-PUFA biosynthetic pathway, we characterized fatty acid desaturase 2 (Fads2) and elongation of very long-chain fatty acid protein 5 (Elovl5) in Pacific saury. Two paralogous fads2 genes, namely fads2a and fads2b, were isolated from the saury and their recombinant protein showed ∆6∆8 and ∆4∆5 desaturase activities, respectively. Meanwhile, saury Elovl5 had elongase activity toward C18 and C20 PUFA. These three enzyme genes were expressed in the brain and liver, although fads2a was absent in the latter. Our results suggest that the saury has sufficient enzymatic functions, particularly in its brain, for DHA biosynthesis through the ∆4 pathway even from α-linolenic acid. This information provides novel insights into the origin of LC-PUFAs in Pacific saury and the future perspective for its potential as a source of such vital fatty acids for human consumption.
Testing for the Pareto type I distribution: a comparative study
Authors: Ndwandwe L. , Allison J. S. , Santana L. , Visagie I. J. H.
Published: July 2023

Pareto distributions are widely used models in economics, finance and actuarial sciences. As a result, a number of goodness-of-fit tests have been proposed for these distributions in the literature. We provide an overview of the existing tests for the Pareto distribution, focussing specifically on the Pareto type I distribution. To date, only a single overview paper on goodness-of-fit testing for Pareto distributions has been published. However, the mentioned paper has a much wider scope than is the case for the current paper as it covers multiple types of Pareto distributions. The current paper differs in a number of respects. First, the narrower focus on the Pareto type I distribution allows a larger number of tests to be included. Second, the current paper is concerned with composite hypotheses compared to the simple hypotheses (specifying the parameters of the Pareto distribution in question) considered in the mentioned overview. Third, the sample sizes considered in the two papers differ substantially. In addition, we consider two different methods of fitting the Pareto Type I distribution; the method of maximum likelihood and a method closely related to moment matching. It is demonstrated that the method of estimation has a profound effect, not only on the powers achieved by the various tests, but also on the way in which numerical critical values are calculated. We show that, when using maximum likelihood, the resulting critical values are shape invariant and can be obtained using a Monte Carlo procedure. This is not the case when moment matching is employed. The paper includes an extensive Monte Carlo power study. Based on the results obtained, we recommend the use of a test based on the phi divergence together with maximum likelihood estimation.
FUS-mediated blood–brain barrier disruption for delivering anti-Aβ antibodies in 5XFAD Alzheimer’s disease mice
Authors: Antoniou Anastasia , Stavrou Marios , Evripidou Nikolas , Georgiou Elena , Kousiappa Ioanna , Koupparis Andreas , Papacostas Savvas S. , Kleopa Kleopas A. , Damianou Christakis
Published: July 2023

Purpose

Amyloid-β (Aβ) peptides, the main component of amyloid plaques found in the Alzheimer's disease (AD) brain, are implicated in its pathogenesis, and are considered a key target in AD therapeutics. We herein propose a reliable strategy for non-invasively delivering a specific anti-Aβ antibody in a mouse model of AD by microbubbles-enhanced Focused Ultrasound (FUS)-mediated Blood–brain barrier disruption (BBBD), using a simple single stage MR-compatible positioning device.

Methods

The initial experimental work involved wild-type mice and was devoted to selecting the sonication protocol for efficient and safe BBBD. Pulsed FUS was applied using a single-element FUS transducer of 1 MHz (80 mm radius of curvature and 50 mm diameter). The success and extent of BBBD were assessed by Evans Blue extravasation and brain damage by hematoxylin and eosin staining. 5XFAD mice were divided into different subgroups; control (n = 1), FUS + MBs alone (n = 5), antibody alone (n = 5), and FUS + antibody combined (n = 10). The changes in antibody deposition among groups were determined by immunohistochemistry.

Results

It was confirmed that the antibody could not normally enter the brain parenchyma. A single treatment with MBs-enhanced pulsed FUS using the optimized protocol (1 MHz, 0.5 MPa in-situ pressure, 10 ms bursts, 1% duty factor, 100 s duration) transiently disrupted the BBB allowing for non-invasive antibody delivery to amyloid plaques within the sonicated brain regions. This was consistently reproduced in ten mice.

Conclusion

These preliminary findings should be confirmed by longer-term studies examining the antibody effects on plaque clearance and cognitive benefit to hold promise for developing disease-modifying anti-Aβ therapeutics for clinical use.
Gremmeniella abietina: a Loser in the Warmer World or Still a Threat to Forestry?
Authors: Romeralo Carmen , Botella Leticia , Santamaría Oscar , Diez Julio Javier , Laflamme Gaston
Published: July 2023

Purpose of Review

Gremmeniella abietinais a destructive forest pathogen responsible for Scleroderris canker, shoot dieback, defoliation, and tree death in forests and tree nurseries. This review is aimed at providing a complete description of the fungus, its distribution, the conditions for its spread, and the impact of climate change and at summarising the relevant forest management methods. Due to the worldwide importance of the pathogen, a retrospective review is required to summarise the lessons learned in relation to the disease, considering application to future outbreaks.

Recent Findings

We revise available management methods, considering examples of control strategies, with special focus on the silvicultural approaches, and we also revise the recovery of the affected stands and the associated trade-offs. Forest disturbances such as pests and disease outbreaks are expected to be exacerbated by climate change, although the exact impact on all host-pathogen interactions remains unclear. In regions with a high risk ofG. abietinaepidemics, climate change is expected to affect the pathogen differently.

Gremmeniella abietinais a widely distributed forest pathogen in Europe and is also present in North America. Based on the conclusions reached in this review, forest stands may recover from pathogen outbreaks within 10 years, with considerable loss of growth and the risk of attack from secondary factors. Provenance selection is vital for preventing outbreaks. Climate change is expected to have different effects: in some areas, it is likely to increase the conditions conducive to the development of the fungus, while in others, it is likely to limit the spread because of high temperatures and low humidity. Preventing future outbreaks of this pathogen requires the use of mitigating strategies, together with forest monitoring, forecasting, and planning.
Designing Oxide Catalysts for Oxygen Electrocatalysis: Insights from Mechanism to Application
Authors: Han Ning , Zhang Wei , Guo Wei , Pan Hui , Jiang Bo , Xing Lingbao , Tian Hao , Wang Guoxiu , Zhang Xuan , Fransaer Jan
Published: July 2023

The electrochemical oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) are fundamental processes in a range of energy conversion devices such as fuel cells and metal–air batteries. ORR and OER both have significant activation barriers, which severely limit the overall performance of energy conversion devices that utilize ORR/OER. Meanwhile, ORR is another very important electrochemical reaction involving oxygen that has been widely investigated. ORR occurs in aqueous solutions via two pathways: the direct 4-electron reduction or 2-electron reduction pathways from O2 to water (H2O) or from O2 to hydrogen peroxide (H2O2). Noble metal electrocatalysts are often used to catalyze OER and ORR, despite the fact that noble metal electrocatalysts have certain intrinsic limitations, such as low storage. Thus, it is urgent to develop more active and stable low-cost electrocatalysts, especially for severe environments (e.g., acidic media). Theoretically, an ideal oxygen electrocatalyst should provide adequate binding to oxygen species. Transition metals not belonging to the platinum group metal-based oxides are a low-cost substance that could give a d orbital for oxygen species binding. As a result, transition metal oxides are regarded as a substitute for typical precious metal oxygen electrocatalysts. However, the development of oxide catalysts for oxygen reduction and oxygen evolution reactions still faces significant challenges, e.g., catalytic activity, stability, cost, and reaction mechanism. We discuss the fundamental principles underlying the design of oxide catalysts, including the influence of crystal structure, and electronic structure on their performance. We also discuss the challenges associated with developing oxide catalysts and the potential strategies to overcome these challenges.
Air-Stable Binary Hydrated Eutectic Electrolytes with Unique Solvation Structure for Rechargeable Aluminum-Ion Batteries
Authors: Meng Pengyu , Huang Jian , Yang Zhaohui , Jiang Min , Wang Yibo , Zhang Wei , Zhang Jiao , Sun Baode , Fu Chaopeng
Published: July 2023

Aluminum-ion batteries (AIBs) have been highlighted as a potential alternative to lithium-ion batteries for large-scale energy storage due to the abundant reserve, light weight, low cost, and good safety of Al. However, the development of AIBs faces challenges due to the usage of AlCl3-based ionic liquid electrolytes, which are expensive, corrosive, and sensitive to humidity. Here, we develop a low-cost, non-corrosive, and air-stable hydrated eutectic electrolyte composed of aluminum perchlorate nonahydrate and methylurea (MU) ligand. Through optimizing the molar ratio to achieve the unique solvation structure, the formed Al(ClO4)3·9H2O/MU hydrated deep eutectic electrolyte (AMHEE) with an average coordination number of 2.4 can facilely realize stable and reversible deposition/stripping of Al. When combining with vanadium oxide nanorods positive electrode, the Al-ion full battery delivers a high discharge capacity of 320 mAh g−1 with good capacity retention. The unique solvation structure with a low desolvation energy of the AMHEE enables Al3+ insertion/extraction during charge/discharge processes, which is evidenced by in situ synchrotron radiation X-ray diffraction. This work opens a new pathway of developing low-cost, safe, environmentally friendly and high-performance electrolytes for practical and sustainable AIBs.
Fixed and mobile broadband penetration and CO2 emissions: evidence from OECD countries
Authors: Quaglione Davide , D’Ingiullo Dario , Meleo Linda
Published: July 2023

The recent rapid increase in Internet data traffic and use of digital technologies—observed during the pandemic and forecasted as a consequence of the massive digital transition occurring in the world economies—are feeding concerns about the related possible negative environmental impacts, in terms of both energy consumption and Carbon Dioxide (CO2) emissions. We contribute to such debate by analysing the relation between two different digitalization dimensions, namely fixed and mobile broadband connections penetration, and CO2emissions at the country level. Our paper provides empirical evidence, based on a panel of 35 OECD countries, that higher fixed and mobile broadband penetration levels are associated with lower levels of CO2emissions, according to an Environmental Kuznets Curve-type relation. Moreover, we investigate whether the environmental effects of these two digitalization dimensions differ across high- and low-income OECD countries. By adopting fixed-effects models and fixed-effects two-stage least square estimators, the results, besides substantiating the Kuznet’s hypothesis in both groups of nations, confirm that higher fixed and mobile broadband penetration levels are associated to a reduction of CO2emissions.
Can’t see the forest for the trees
Authors: Szepannek Gero , Holt Björn-Hergen von
Published: July 2023

Random forests are currently one of the most popular algorithms for supervised machine learning tasks. By taking into account for many trees instead of a single one the resulting forest model is no longer easy to understand and also often denoted as a black box. The paper is dedicated to the interpretability of random forest models using tree-based explanations. Two different concepts, namely most representative trees and surrogate trees are analyzed regarding both their ability to explain the model and to be understandable by humans. For this purpose explanation trees are further extended to groves, i.e. small forests of few trees. The results of an application to three real world data sets underline the inherent trade of between both requirements. Using groves allows to control for the complexity of an explanation while simultaneously analyzing their explanatory power.
Numerical simulation for a Casson nanofluid over an inclined vessel surrounded by hot tissue at the microscale
Authors: Ismaeel A. M. , Kamel R. S. , Hedar M. R. , Hady F. M.
Published: July 2023

This study presents a theoretical model to mimic heat transfer and nanoparticle transport through the tumour interstitium surrounding an inclined cylindrical blood vessel exposed to an alternating magnetic field. Using similarity transformations, we convert the governing equations (partial differential equations) into a system of ordinary differential equations, which we solve numerically with a MATLAB built-in solver (bvp4c). The converence of the numerical solution is proved using the mesh convergence test. All parameters and their effects on fluid flow, heat, and mass transfer in the interstitium are studied and investigated. For instance, the nanoparticle penetration into the deep tissue can be enhanced by exposing the tumour to a magnetic field, increasing the tumour temperature and the nanoparticle Brownian motion, which is a consequence of increasing the tumour temperature. Moreover, we consider the case of non-Newtonian interstitial fluid in the tumour to mimic the nonlinearity of the fluid flow in the tumour tissue. The findings of this manuscript may optimise tumour ablation using hyperthermia by optimising nanoparticle delivery to deep tumour tissue and tumour temperature.
A Feasibility Study on Translation of RGB Images to Thermal Images: Development of a Machine Learning Algorithm
Authors: Li Yuchuan , Ko Yoon , Lee Wonsook
Published: July 2023

The thermal image is an important source of data in the fire safety research area, as it provides temperature information at pixel-level of a region. The combination of temperature value together with precise location information from thermal image coordinates enables a comprehensive and quantitative analysis of the combustion phenomenon of fire. However, it is not always easy to capture and save suitable thermal images for analysis due to several limitations, such as personnel load, hardware capability, and operating requirements. Therefore, it is necessary to have a substitution solution when thermal images cannot be captured in time. Inspired by the success of previous empirical and theoretical study of deep neural networks from deep learning on image-to-image translation tasks, this paper presents a feasibility study on translating RGB vision images to thermal images by a brand-new model of deep neural network. It is called dual-attention generative adversarial network (DAGAN). DAGAN features attention mechanisms proposed by us, which include both foreground and background attention, to improve the output quality for translation to thermal images. DAGAN was trained and validated by image data from fire tests with a different setup, including room fire tests, single item burning tests and open fire tests. Our investigation is based on qualitative and quantitative results that show that the proposed model is consistently superior to other existing image-to-image translation models on both thermal image patterns quality and pixel-level temperature accuracy, which is close to temperature data extracted from native thermal images. Moreover, the results of the feasibility study also demonstrate that the model could be further developed to assist in the analytics and estimation of more complicated flame and fire scenes based only on RGB vision images.