bluuebunny/crossref_metadata_2025 huggingface dataset:
Ionic Liquids as Extreme Pressure Additives for Bearing Steel Applications
Authors: Donato Mariana T. , Nautiyal Pranjal , Deuermeier Jonas , Branco Luís C. , Saramago Benilde , Colaço Rogério , Carpick Robert W.
Published: August 2024

The protection of steel surfaces from wear under extreme pressure conditions is of major importance in several industries as it provides better performance and longer life of machinery. The motivation for this work was to study the lubrication of steel by ionic liquids (ILs), which have recently emerged as greener alternatives to commercial lubricants and additives. Three ILs based on sulfur-containing anions, used as 2-wt% additives in polyethylene glycol base oil (MW 200; PEG 200), were tested in the lubrication of ASTM 52100 bearing steel contacts in extreme pressure conditions (under mixed lubrication with a Hertzian pressure of 1.12 GPa) using a mini traction machine (MTM). Due to the poor resistance to corrosion of bearing steel, a semi-ester of succinic acid derivative corrosion inhibitor (Lanxess RC 4801) was added to the mixtures at a 1 wt% concentration. The ILs 1-hexyl-methylimidazolium trifluoromethanesulfonate ([C6mim][TfO]) and 1-hexyl-4-picolinium trifluoromethanesulfonate ([C6-4-pic][TfO]) revealed promising results in terms of surface protection of bearing steel. In contrast, 4-picolinium hydrogen sulfate ([4-picH][HSO4]) as 2-wt% additive to PEG 200 + 1% RC 4801 did not show any improvement in wear performance compared to neat PEG 200 + 1% RC 4801. PEG 200 + 2% [C6mim][TfO] + 1%RC 4801 allowed for a decrease in wear up to ~ 76% and PEG 200 + 2% [C6-4-pic][TfO] + 1%RC 4801 up to ~ 46% when compared with neat PEG 200 + 1% RC 4801. Optical microscopy images suggest the formation of an adsorbed layer, which was further supported by chemical analysis via x-ray photoelectron spectroscopy (XPS) data for [C6mim][TfO].

Graphical abstract
Search for natural products from actinomycetes of the genus Nocardia
Authors: Hara Yasumasa
Published: August 2024

The genus Nocardia are gram-positive bacteria, many of which possess pathogenicity and infect human lungs, skin, brain, and other organs. Since research on the genus Nocardia has not progressed as rapidly as that on the genus Streptomyces, the genus Nocardia is considered a useful undeveloped resource for exploring natural products. On the other hand, when the genus Nocardia infects the human body, the strains are attacked by immune cells such as macrophages. Therefore, we suggested a new method for screening natural products by culturing the genus Nocardia in the presence of animal cells. In this review, we describe our recent results in searching for natural products from the genus Nocardia.

Graphical abstract
A proposed methodology for investigating student-chatbot interaction patterns in giving peer feedback
Authors: Lin Michael Pin-Chuan , Chang Daniel H. , Winne Philip H.
Published: August 2024

A chatbot is artificial intelligence software that converses with a user in natural language. It can be instrumental in mitigating teaching workloads by coaching or answering student inquiries. To understand student-chatbot interactions, this study is engineered to optimize student learning experience and instructional design. In this study, we developed a chatbot that supplemented disciplinary writing instructions to enhance peer reviewer’s feedback on draft essays. With 23 participants from a lower-division post-secondary education course, we delved into characteristics of student-chatbot interactions. Our analysis revealed students were often overconfident about their learning and comprehension. Drawing on these findings, we propose a new methodology to identify where improvements can be made in conversation patterns in educational chatbots. These guidelines include analyzing interaction pattern logs to progressively redesign chatbot scripts that improve discussions and optimize learning. We describe new methodology providing valuable insights for designing more effective instructional chatbots by enhancing and engaging student learning experiences through improved peer feedback.
Duale und schulische Berufsausbildungen in Deutschland: Schritte zu einem umfassenden Verständnis von beruflicher Bildung
Authors: Weitz Jennifer , Ludwig-Mayerhofer Wolfgang
Published: August 2024

Die berufliche Ausbildung in Deutschland wird auch heute noch häufig mit der dualen Ausbildung gleichgesetzt. Schulische Berufsausbildungen können im doppelten Sinn als Ausbildungen zweiter Klasse gesehen werden: Sie werden in Öffentlichkeit und Wissenschaft seltener wahrgenommen; geraten sie aber in den Blick, so wird oftmals angenommen, dass die (überwiegend weiblichen) Personen, die solche Ausbildungen absolvieren, im Vergleich zu dual Ausgebildeten schlechtere Arbeitsmarktchancen haben. Der Beitrag skizziert zunächst duale Ausbildungen, Ausbildungen an Schulen des Gesundheitswesens sowie Ausbildungen an Berufsfachschulen (unter gesonderter Betrachtung der Erzieher:innen) im gesellschaftlich-historischen Kontext und zeigt, wie dieser Kontext letztlich auch mit unzureichender Forschung zu den schulischen Ausbildungen einhergeht. Mit Daten des Nationalen Bildungspanels (NEPS) werden anschließend die Chancen von Absolvent:innen der verschiedenen Ausbildungssegmente beim Übergang in den Arbeitsmarkt analysiert (Dauer bis zur ersten Beschäftigung, Merkmale des ersten Beschäftigungsverhältnisses sowie Arbeitslosigkeit nach der ersten Beschäftigung). Im Ergebnis zeigt sich, dass die (nicht bundesweit, sondern per Ländergesetzgebung geregelten) Ausbildungen an Berufsfachschulen tatsächlich mit etwas schlechteren Arbeitsmarktchancen verknüpft sind. Auffällig ist das Profil der Erzieher:innen, die besonders häufig befristet beschäftigt sind. Mit Blick auf den Beschäftigungsbedarf der Zukunft sind mehr öffentliche Aufmerksamkeit und mehr staatliches Engagement für die schulische Berufsbildung dringend erforderlich.
Designing for collective action: a knowledge co-production process to address water governance challenges on the island of Öland, Sweden
Authors: Seiferth Carolin , Tengö Maria , Andersson Erik
Published: August 2024

Enabling diverse actors to address interlinked sustainability issues is important and challenging. This paper focuses on how to design a dialogue-based knowledge co-production process to nurture collective action. Using the conceptualization of systems, target, and operational knowledge as the guiding framework, we designed and combined different complementary activities to invite actors to look at a wicked problem through multiple lenses and reflect on their own positions, perspectives, knowledge, and values. With a carefully documented workshop series held with local actors on Öland, Sweden, as our empirical case study, we demonstrate how we moved from exploring the multifunctionality of landscapes and understanding actors’ different values, preferences, and priorities, to developing four strategies for effectively accelerating and expanding efforts to adapt to climate change. Our study reveals how the process of mobilizing, articulating, and connecting individually held systems, target, and operational knowledge nurtures collective action. It also leverages dialogue-based processes as cornerstones in addressing sustainability challenges in an inclusive and equitable way.
Importance of the (Pro)renin Receptor in Activating the Renin-Angiotensin System During Normotensive and Preeclamptic Pregnancies
Authors: Schofield Lachlan G. , Endacott Saije K. , Delforce Sarah J. , Lumbers Eugenie R. , Pringle Kirsty G.
Published: August 2024

Purpose of Review

For a healthy pregnancy to occur, a controlled interplay between the maternal circulating renin–angiotensin–aldosterone system (RAAS), placental renin-angiotensin system (RAS) and intrarenal renin-angiotensin system (iRAS) is necessary. Functionally, both the RAAS and iRAS interact to maintain blood pressure and cardiac output, as well as fluid and electrolyte balance. The placental RAS is important for placental development while also influencing the maternal circulating RAAS and iRAS. This narrative review concentrates on the (pro)renin receptor ((P)RR) and its soluble form (s(P)RR) in the context of the hypertensive pregnancy pathology, preeclampsia.

Recent Findings

The (P)RR and the s(P)RR have become of particular interest as not only can they activate prorenin and renin, thus influencing levels of angiotensin II (Ang II), but s(P)RR has now been shown to directly interact with and stimulate the Angiotensin II type 1 receptor (AT1R). Levels of both placental (P)RR and maternal circulating s(P)RR are elevated in patients with preeclampsia. Furthermore, s(P)RR has been shown to increase blood pressure in non-pregnant and pregnant rats and mice.

In preeclamptic pregnancies, which are characterised by maternal hypertension and impaired placental development and function, we propose that there is enhanced secretion of s(P)RR from the placenta into the maternal circulation. Due to its ability to both activate prorenin and act as an AT1R agonist, excess maternal circulating s(P)RR can act on both the maternal vasculature, and the kidney, leading to RAS over-activation. This results in dysregulation of the maternal circulating RAAS and overactivation of the iRAS, contributing to maternal hypertension, renal damage, and secondary changes to neurohumoral regulation of fluid and electrolyte balance, ultimately contributing to the pathophysiology of preeclampsia.
Infrared Thermal Image Processing Technique for Evaluating Superheated Steam as a Dry Sanitation Method
Authors: Park Hyeon Woo , Balasubramaniam V. M.
Published: August 2024

The objectives of this study were to develop a thermal image analysis method for assessing the surface temperature of stainless steel (30 cm × 30 cm) during pilot-scale superheated steam sanitation and evaluate the sanitation efficacy based on the inactivation of Enterococcus faecium. An infrared camera, calibrated to a root-mean-square error (RMSE) of 1.4 °C within a range of 25 °C and 250 °C, was utilized. The results showed that the surface temperature at the impingement point decreased linearly from 245.6 ± 3.2 to 157.6 ± 1.7 °C as the nozzle-to-surface distance was increased from 2 to 5 cm. Furthermore, at a 2 cm nozzle-to-surface distance, temperatures swiftly dropped from 245.6 ± 3.2 to 95.8 ± 6.0 °C as the radial distance increased from 0 to 10 cm. In the stagnation region (0–1 cm radial distance), where the steam jet directly contacts the surface, the time required to achieve a 3-log reduction of E. faecium was reduced from 3 to 1 min as the nozzle-to-surface distance decreased from 5 to 2 cm. The efficacy of superheated steam sanitation was further evaluated under practical sweeping conditions, demonstrating a 2.7 ± 0.4 log reduction of E. faecium on a 900 cm2 stainless steel surface within 10 min. This study thus highlights the potential use of thermal image analysis for optimizing superheated steam sanitation processes, particularly in dry food processing environments.
Dynamics of Freedom: Negotiating Constraints
Authors: Hejlesen Jonas Tellefsen
Published: August 2024

In this paper, I grapple with the question of why we, at times, experience ourselves as not free. In doing so I outline a crude theory of agency (and our experience of ourselves as free) as a dynamic process happening in irreversible time. In attempting to answer this question, I define agency as the ability to pursue our desires, and I claim that we experience ourselves as free as long as we can do this – with the caveat that the ability to reason is a necessary criterion. I show that agency is a sociocultural development that manifests as the ability to reason gradually develops through social interaction during infancy and into adulthood. Crucially, I point out that reason is a double-edged sword: It allows us to question our actions and desires and whether they are worth pursuing, which is what elevates us to agentic beings. However, it also allows us to alienate ourselves from our actions and desires, and thus rob ourselves of our experience of freedom. Lastly, I show how our subjective freedom is lost and gained in a constant process, generated by a reflexive-relating-to ourselves. As we act, we continually encounter constraints (physical and psychological) that bar us from acting upon our desires. This compels us to reflect on our actions and desires, and so, our feeling of freedom evaporates. However, through a retrospective forgetting, or reconstruction, of the constraints we encounter, we may regain our experience of being free.
Nonassociative cyclic algebras and the semiassociative Brauer monoid
Authors: Pumplün S.
Published: August 2024

We look at classes of semiassociative algebras, with an emphasis on those that canonically generalize associative (generalized) cyclic algebras, and at their behaviour in the semiassociative Brauer monoid defined by Blachar, Haile, Matzri, Rein, and Vishne. A possible way to generalize this monoid in characteristic p that includes nonassociative differential algebras is briefly considered.
A memetic algorithm for improved joint route selection and split-level management in next-generation wireless communications
Authors: Garza-Fabre Mario , Erazo-Agredo Cristian C. , Rubio-Loyola Javier
Published: August 2024

The complexity of next-generation wireless communications, especially Beyond 5G and 6G communication systems, will be handled by artificial intelligence-based management paradigms. The joint selection of routes and functional split levels involves critical decisions that network infrastructure providers need to make to support requests from virtual Mobile Network Operators (vMNOs). These decisions comprise the assignment and configuration of physical network resources, which must comply with the specific quality of service restrictions of each vMNO request. Recent work defined a detailed mathematical model for this complex challenge, its formulation as a constrained, discrete optimization problem, and the first algorithmic approaches. It was also found that an evolutionary algorithm delivers higher-quality solutions than an ad-hoc heuristic, and faster running times compared to a well-known commercial solver. This paper introduces a memetic algorithm that exploits the strengths of the former evolutionary method while incorporating several key innovations: a domain-specific recombination operator; a specialized repairing procedure; an enhanced fitness evaluation scheme; and a multiobjective archiving strategy that preserves promising solution trade-offs. We conduct a comprehensive evaluation of the performance and behavior of this proposal, as well as the contribution of each specific design component. The results highlight that our memetic algorithm consistently outperforms previous approaches from the literature, providing better trade-offs in terms of solution quality and the rate at which vMNO requests are successfully fulfilled.
When is blockchain worth it? Value and risk drivers of corporate blockchain announcements
Authors: Rogalski Timo , Schiereck Dirk
Published: August 2024

In the era of emerging technologies, many firms explore the role of blockchain technology and its impact on corporate market value. Past research has shown that companies benefit from executing blockchain projects, but little is known about specific value and risk drivers. Hence, we provide evidence for several conditions under which blockchain provides additional firm market value. Moreover, we test whether blockchain announcements lead to changes in the systematic risk of firms. Theoretically founded on the resource-based view, we utilize the event study methodology, supplemented by a multivariate regression and a firm’s beta analysis. We find that stock markets react positively to corporate blockchain news if the announcement is related to a blockchain consortium or partnership, is declared by a tech company, or if the announcement is a follow-up announcement to initial blockchain news. Moreover, our findings show that blockchain announcements do not lead to significant changes in a firm’s systematic risk.
Machine Learning as a Tool to Find New Pharmacological Targets in Mood Disorders: A Systematic Review
Authors: Romão Joana , Melo António , André Rita , Novais Filipa
Published: August 2024

Purpose of Review

Mood disorders (MD) are mental disorders that need accurate diagnosis and proper treatment. Growing volume of data from neurobehavioral sciences is becoming complex for traditional research to analyze. New drugs’ slow development fails to meet the needs of neurobehavioral disorders. Machine Learning (ML) techniques support research by refining the detection, diagnosis, treatment, and research, and are being employed to expedite the discovery of pharmacological targets. This review aims to assess evidence regarding the contribution of ML in finding new pharmacological targets in adults with MD.

Recent findings

The most significant area of research amongst MD is major depressive disorder. ML identified target gene candidates, pathways and biomarkers related to MD, which can pave the way for promising therapeutic strategies. ML was also found to enhance diagnostic accuracy.

ML techniques have the potential to bridge the gap between biological data and chemical drug information, providing new discoveries in pharmacological agents.
Utilizing Medical Student Feedback to Improve Teaching Cases in Pre-clerkship Curricula
Authors: Bruner Lia Pierson , Topper Leah , Baldwin Amy , House Ellen M. , Chappell M. Tresa , Hill Janette R.
Published: August 2024

Feedback is an essential part of continuous quality improvement of cases used in medical curricula. This report describes results of qualitative analysis of feedback to elucidate what worked well and what needed improvement from the lens of our pre-clerkship medical students. Complexity, realism, and use of media were themes identified as strengths. Increasing the complexity, realism, and media as well as clarifying test results were themes for suggested improvements. While some feedback themes were similar across pre-clerkship years, others differed between first- and second-year students, likely representing the evolution of our learners.
Incorporating Faculty and Student Co-leadership in Workgroup Structures
Authors: Kumar Chitra , Lowrie D. J. , Pritchard Tracy , Kelly Lisa
Published: August 2024

In 2020, the Dean of the University of Cincinnati College of Medicine created a college-wide task force to address inequities in the medical school curriculum. The task force consisted of four workgroups, each co-chaired by a faculty member and a student. This co-leadership model was chosen because it provided diverse perspectives and addressed the typical faculty-student power differentials. This co-leadership model balanced knowledge of medical education curriculum with the student experience. It also provided the opportunity for the co-chairs to take on new roles in leadership development: the student assumed a leadership role running the workgroup with guidance from the faculty member, while the faculty member gained insight and perspective on diversity and inclusion from the student. The purpose of this article is to describe our lessons learned during this co-leadership process.
Impact of Forest Operations in Four Biogeographical Regions in Europe: Finding the Key Drivers for Future Development
Authors: Engler Benjamin , Hartmann Gwendolin , Mederski Piotr S. , Bont Leo G. , Picchi Gianni , Alcoverro Gerard , Purfürst Thomas , Schweier Janine
Published: August 2024

Purpose of the Review

The aim of the review was to better understand the impacts of the dominant harvesting systems in Europe, namely harvester-forwarder (HFW), chainsaw-skidder (CSK), and chainsaw-cable yarder (CCY). Furthermore, we aimed to learn how the impact categories environment, economy, ergonomics, people and society, and quality optimization are related to the European biogeographical regions Boreal, Continental, Alpine, and Mediterranean forests. Based on this, key drivers for the future development of forest operations were identified. It was specifically not the aim to develop models through the outcome of this study.

Recent Findings

HFW harvesting systems dominate in Boreal (99%) and Continental forests (72%). In Alpine forests the most relevant, even when not dominant, harvesting system is CCY (47%). CSK harvesting systems are applied in all biogeographical regions, with a focus on Mediterranean (70%), Alpine (50%) and Continental (22%) forests. Major drivers for harvesting system development were identified: (i) increased environmental constraints, (ii) increased complexity of harvesting caused by an increasing area of mixed-forest stands, (iii) increased resource efficiency fostered by a growing demand for wood products, (iv) a reduced available work force resulting from heightened competition for skilled worker and an aging population, and (v) more transparent work and material flows through the introduction of digitalization.

A literature review from 110 journal articles and 975 datasets from four biogeographical regions in Europe, specifically from Estonia, Germany, Spain and Switzerland was performed. Most of the reviewed papers included information about economic or environmental impacts, while ergonomics, quality optimization and societal aspects were less in focus. The impacts from the HFW, CSK and CCY harvesting systems were evaluated against regional conditions. Unfortunately, a common understanding of harvesting system evaluation is missing, which limits the comparability of results between different regions.
Signal to Noise Ratio and Spectral Sampling Constraints on Olivine Detection and Compositional Determination in the Intermediate Infrared Region: Applications in Planetary Sciences
Authors: Pérez‐López S. A. , Kremer C. H. , Mustard J. F.
Published: August 2024

Spectral features of olivine across the intermediate infrared region (IMIR, 4–8 μm) shift systematically with iron‐magnesium content, enabling determination of olivine composition. Previous IMIR studies have used laboratory data with signal‐to‐noise ratios (SNRs) and spectral resolutions potentially greater than those of data derived from planetary missions. Here we employ a feature fitting algorithm to quantitatively assess the influence of data quality on olivine detection and compositional interpretation from IMIR data of 29 spectra of pure olivine of synthetic, terrestrial, lunar, and Martian origins, as well as 5 spectra of lunar pyroclastic beads measured as bulk samples. First, we demonstrate the effectiveness of the feature fitting algorithm in the interpretation of IMIR olivine spectra, predicting olivine composition with an average error of 6.4 mol% forsterite across all test spectra using laboratory‐quality data. We then extend this analysis to degraded test spectra with reduced SNRs and sampling rates and find a range of data qualities required to predict olivine composition within ±11 Mg# (molar Mg/[Mg + Fe] × 100) for the test spectra explored here. Spectra for the sample most relevant to lunar exploration, an Apollo 74002 drive tube consisting of microcrystalline olivine and glass‐rich pyroclastics, required SNRs ≥ 200 for sampling rates ≤25 nm to predict composition within ±11 Mg# of the sample's true composition. Derived limits on SNRs and sampling rates will serve as valuable inputs for the development of IMIR spectrometers, enabling comprehensive knowledge of olivine composition on the lunar surface.
Interannual Influence of Antarctic Sea Ice on Southern Hemisphere Stratosphere‐Troposphere Coupling
Authors: Rea Divya , Elsbury Dillon , Butler Amy H. , Sun Lantao , Peings Yannick , Magnusdottir Gudrun
Published: August 2024

While weakening of the boreal polar vortex may be caused by autumnal Arctic sea ice loss, less is known about the interannual influence of Antarctic sea ice on stratosphere‐troposphere coupling in the Southern Hemisphere. Identifying any relationship over the short satellite period is difficult due to sampling variability and anthropogenic modification of the austral polar vortex. To circumvent these issues, we use large ensembles of fixed boundary condition simulations from the Community Atmosphere Model (CAM) and Whole Atmosphere Community Climate Model (WACCM) to assess if and how interannual fluctuations in winter Antarctic sea ice influence spring planetary‐scale waves and the coupled stratosphere‐troposphere circulation. Low Antarctic sea ice conditions are found to modulate tropospheric stationary waves to project constructively onto the climatological stationary wave, enhancing upward planetary wave propagation into the austral polar stratosphere. In WACCM, the resulting vortex weakening coincides with development of negative Southern Annular Mode conditions during September–November.
Geochemistry of Olivine Melt Inclusion Reveals Interactions Between Deeply Derived Carbonated Melts From the Big Mantle Wedge and Pyroxenite in the Lithospheric Mantle Beneath Eastern Asia
Authors: Wei Zhen , Li Hong‐Yan , Ma Liang , Hou Yong‐Sheng , Wang Yu , Xu Yi‐Gang
Published: August 2024

Our current knowledge regarding the distribution patterns of ancient and recent recycled materials, as well as the origin of intraplate basalts in the eastern Asia Big Mantle Wedge (BMW), is limited. To address this, we conducted a detailed geochemical analysis of olivine melt inclusions (OLMI) in nephelinite samples. The normal OLMIs detected in our investigation exhibit geochemical features that closely resemble those of the hosting nephelinite, indicating a consistent association with a carbonated mantle source. Additionally, we identified a distinct group of anomalous OLMIs that displayed different geochemical characteristics from the hosting nephelinite but showed similarities to regional alkali basalts sourced from pyroxenite. The observed geochemical diversity in the nephelinite OLMIs suggests an interaction between deeply derived carbonated melts originating from the flattened Pacific slab in the mantle transition zone and pyroxenite in the lithospheric mantle. Carbonated fluid‐fluxed melting is key to basalt formation in the BMW.
Longwave Radiative Feedback Due To Stratiform and Anvil Clouds
Authors: Luschen Emily , Ruppert James
Published: August 2024

Studies have implicated the importance of longwave (LW) cloud‐radiative forcing (CRF) in facilitating or accelerating the upscale development of tropical moist convection. While different cloud types are known to have distinct CRF, their individual roles in driving upscale development through radiative feedback is largely unexplored. Here we examine the hypothesis that CRF from stratiform regions has the greatest positive effect on upscale development of tropical convection. We do so through numerical model experiments using convection‐permitting ensemble WRF (Weather Research and Forecasting) simulations of tropical cyclone formation. Using a new column‐by‐column cloud classification scheme, we identify the contributions of five cloud types (shallow, congestus, and deep convective; and stratiform and anvil clouds). We examine their relative impacts on longwave radiation moist static energy (MSE) variance feedback and test the removal of this forcing in additional mechanism‐denial simulations. Our results indicate the importance stratiform and anvil regions in accelerating convective upscale development.
Continuing Current Seen Above and Below the Cloud: Comparing Observations From GLM and High‐Speed Video Cameras
Authors: Ding Ziqin , Zhu Yanan , Lapierre Jeff , DiGangi Elizabeth , Ringhausen Jacquelyn , Lauria Paola B. , Saba Marcelo M. F. , Rakov Vladimir A. , Abbasi Rasha U. , da Silva Diego R. R. , da Silva Tagianne P.
Published: August 2024

This study assesses the reliability and limitations of the Geostationary Lightning Mapper (GLM) in detecting continuing currents by comparing observations from ground‐based high‐speed cameras with GLM‐16 data. Our findings show that the GLM's one‐group detection efficiency (DE_1) is 53%, while the more stringent five‐consecutive‐group detection efficiency (DE_5) is 10%. Optical signals detected by the GLM predominantly occur during the early stages of continuing currents. Additionally, there is a notable disparity in detection efficiencies between positive and negative continuing currents, with positive continuing currents being detected more frequently. The application of the logistic regression model developed by Fairman and Bitzer (2022) further illustrates the limitations in continuing current identification. The study underscores the challenges of relying solely on satellite data to monitor and analyze continuing currents, emphasizing the need for advancements in detection technologies and methodologies to reliably detect continuing current at a large spatial scale.
Seasonal Dependency of the Solar Cycle, QBO, and ENSO Effects on the Interannual Variability of the Wind DW1 in the MLT Region
Authors: Wu Chen , Ridley Aaron J. , Cullens Chihoko Y.
Published: August 2024

The migrating diurnal tide (DW1) is derived by fitting Hough Mode Extensions to the TIMED/TIDI near‐global wind measurements within the mesosphere and lower thermosphere between 85 and 100 km from 2004 to 2014. The tidal amplitude peaks around the equinoxes with a large interannual variability of up to 50%. The correlation coefficients between the tidal amplitude variability and the solar cycle as represented by F10.7, stratospheric Quasi‐Biennial Oscillation (QBO), and El Niño‐Southern Oscillation (ENSO) are calculated every 10 days revealing seasonal dependencies. The interannual variability is positively correlated with QBO from spring to fall, maximizing around the equinoxes; anti‐correlated to the solar cycle in early winter; and anti‐correlated to ENSO in early winter and slightly in March. Multivariate linear regressions are performed to quantitatively analyze the linear relationships between the DW1 amplitude and those factors. The fittings perform best with the QBO at 30 and 50 hPa both being considered. The contribution of QBO peaks around January and October may be related to the polar vortex modulated by QBO in the northern and southern hemispheres, respectively. The correlation between the DW1 amplitude and ENSO is negative with time lags <∼5 months during early winter and spring.
Deep Entry of Low‐Energy Ions Into Mercury’s Magnetosphere: BepiColombo Mio’s Third Flyby Observations
Authors: Harada Yuki , Saito Yoshifumi , Hadid Lina Z. , Delcourt Dominique , Aizawa Sae , Rojo Mathias , André Nicolas , Persson Moa , Fraenz Markus , Yokota Shoichiro , Fedorov Andréi , Miyake Wataru , Penou Emmanuel , Barthe Alain , Sauvaud Jean‐André , Katra Bruno , Matsuda Shoya , Murakami Go
Published: August 2024

Although solar wind‐driven convection is expected to dominate magnetospheric circulation at Mercury, its exact pattern remains poorly characterized by observations. Here we present BepiColombo Mio observations during the third Mercury flyby indicative of convection‐driven transport of low‐energy dense ions into the deep magnetosphere. During the flyby, Mio observed an energy‐dispersed ion population from the duskside magnetopause to the deep region of the midnight magnetosphere. A comparison of the observations with backward test particle simulations suggests that the observed energy dispersion structure can be explained in terms of energy‐selective transport by convection from the duskside tail magnetopause. We also discuss the properties and origins of more energetic ions observed in the more dipole‐like field regions of the magnetosphere in comparison to previously reported populations of the plasma sheet horn and ring current ions. Additionally, forward test particle simulations predict that most of the observed ions on the nightside will precipitate onto relatively low‐latitude regions of the nightside surface of Mercury for a typical convection case. The presented observations and simulation results reveal the critical role of magnetospheric convection in determining the structure of Mercury's magnetospheric plasma. The upstream driver dependence of magnetospheric convection and its effects on other magnetospheric processes and plasma‐surface interactions should be further investigated by in‐orbit BepiColombo observations.
Efficient HLA imputation from sequential SNPs data by transformer
Authors: Tanaka Kaho , Kato Kosuke , Nonaka Naoki , Seita Jun
Published: August 2024

Human leukocyte antigen (HLA) genes are associated with a variety of diseases, yet the direct typing of HLA alleles is both time-consuming and costly. Consequently, various imputation methods leveraging sequential single nucleotide polymorphisms (SNPs) data have been proposed, employing either statistical or deep learning models, such as the convolutional neural network (CNN)-based model, DEEP*HLA. However, these methods exhibit limited imputation efficiency for infrequent alleles and necessitate a large size of reference dataset. In this context, we have developed a Transformer-based model to HLA allele imputation, named “HLA Reliable IMpuatioN by Transformer (HLARIMNT)” designed to exploit the sequential nature of SNPs data. We evaluated HLARIMNT’s performance using two distinct reference panels; Pan-Asian reference panel (n = 530) and Type 1 Diabetes genetics Consortium (T1DGC) reference panel (n = 5225), alongside a combined panel (n = 1060). HLARIMNT demonstrated superior accuracy to DEEP*HLA across several indices, particularly for infrequent alleles. Furthermore, we explored the impact of varying training data sizes on imputation accuracy, finding that HLARIMNT consistently outperformed across all data size. These findings suggest that Transformer-based models can efficiently impute not only HLA types but potentially other gene types from sequential SNPs data.
Systematic review and meta-analysis on the effects of chronic peri-adolescent cannabinoid exposure on schizophrenia-like behaviour in rodents
Authors: Li Zhikun , Mukherjee Diptendu , Duric Bea , Austin-Zimmerman Isabelle , Trotta Giulia , Spinazzola Edoardo , Quattrone Diego , Murray Robin M. , Di Forti Marta
Published: August 2024

Background

The link between cannabis use and schizophrenia is well-established in epidemiological studies, especially among adolescents with early-onset use. However, this association in rodent models is less clear. This meta-analysis examined the effects of adolescent cannabinoid exposure on distinct schizophrenia-like behaviours in rodents and how experimental variations influence outcomes.

Methods

Following a pre-registered protocol (CRD42022338761), we searched PubMed, Ovid Medline, Embse and APA PsychInfo for English-language original studies until May 2024. We synthesised data from experiments on schizophrenia-like behaviour in rats and mice after repeated peri-pubertal (onset between P23-P45) cannabinoid exposure. Risk of bias was assessed using the SYRCLE’s tool.

Results

We included 359 experiments from 108 articles across 9 behavioural tests. We found meta-analytic evidence supporting that CB1R agonists, both natural and synthetic, elicited broad schizophrenia-like behavioural alterations, including impaired working memory [g  = −0.56; (CI: −0.93, −0.18)], novel object recognition [g = −0.66; (CI: −0.97, −0.35)], novel object location recognition [g = −0.70; (CI: −1.07, −0.33]), social novelty preference [g = −0.52; (CI: −0.93, −0.11)], social motivation [g = −0.21; (CI: −0.42, −0.00)], pre-pulse inhibition [g = −0.43; (CI: −0.76, −0.10)], and sucrose preference [g = −0.87; (CI: −1.46, −0.27)]. By contrast, effects on novelty-induced locomotion were negligible. Subgroup analyses revealed similar effects across sexes and species. Substantial variance in the protocols and moderate-to-high heterogeneity in behavioural outcomes were observed. We found CBD may enhance fear memory recall, but data was limited.

Discussion

This is the first meta-analysis to comprehensively assess the link between cannabinoids and schizophrenia-like behaviours in rodents. Our results support epidemiological links between early cannabis use and schizophrenia-like phenotypes, confirming the utility of animal models. Standardising protocols will optimise models to strengthen reproducibility and comparisons, our work provides a framework for refining rodent models to elucidate biological pathways linking cannabis and schizophrenia.
Topical NSAIDs impact on macular oedema and visual outcome after phacoemulsification: systematic review of RCTs with network meta-analysis
Authors: Almasri Malaz , Ismaiel Abdulrahman , Gavris Iulia , Leucuta Daniel-Corneliu , Gavris Monica M. , Nicoara Simona Delia
Published: August 2024

The aim of this Network Meta-analysis was to compare the efficacy of the different topical Nonsteroidal anti-inflammatory drugs (NSAIDs) when added or not to topical steroids in preventing the thickening of the macula and their impact on visual acuity and intraocular pressure after phacoemulsification. Five electronic databases were searched, including PubMed, Embase, Scopus, Cochrane Library, and ClinicalTrials.gov. Our primary outcome was one-month post-surgery visual outcome. We also considered change in Foveal thickness (FT) and Intraocular pressure (IOP) at one-month post-surgery. We summarized our analyses by calculating the mean differences (MD) with associated 95% confidence intervals (CI) using restricted maximum likelihood in random effects models for continuous outcomes. The methodological quality of the studies was assessed with Cochrane Collaboration’s tool. The network meta-analysis was conducted using frequentist approach considering Nepafenac 0.1% as a reference medication. Eleven Randomized controlled trials (RCTs) including 2175 subjects were selected for quantitative analysis. At one-month post-surgery, Bromfenac had statistically significant better visual acuity compared to Nepafenac 0.1% (p < 0.001), regarding FT, Nepafenac 0.3% had the least increase in FT compared to Nepafenac 0.1% (p = 0.09), regarding IOP, Diclofenac had the lowest IOP. No significant results regarding FT and IOP. Interestingly Ketorolac had the worst results regarding BCVA and IOP, and came last but one for FT. Overall, our network meta-analysis demonstrated that Bromfenac was associated with a significant improvement in visual acuity compared to Nepafenac 0.1% at one-month following cataract surgery, while Nepafenac 0.3% was associated with the least increase in foveal thickness.
GBA-AAV mitigates sleep disruptions and motor deficits in mice with REM sleep behavior disorder
Authors: Chen Ying , Xie Wei-Ye , Xia Dong , Zhang Mu-Tian , Sun Yan-Rui , Duan Wen-Xiang , Shen Yun , Wang Fen , Qu Wei-Min , Huang Zhi-Li , Liu Chun-Feng
Published: August 2024

Sleep disturbances, including rapid eye movement sleep behavior disorder (RBD), excessive daytime sleepiness, and insomnia, are common non-motor manifestations of Parkinson’s disease (PD). Little is known about the underlying mechanisms, partly due to the inability of current rodent models to adequately mimic the human PD sleep phenotype. Clinically, increasing studies have reported that variants of the glucocerebrosidase gene (GBA) increase the risk of PD. Here, we developed a mouse model characterized by sleep–wakefulness by injecting α-synuclein preformed fibronectin (PFF) into the sublaterodorsal tegmental nucleus (SLD) of GBA L444P mutant mice and investigated the role of the GBA L444P variant in the transition from rapid eye movement sleep behavior disorder to PD. Initially, we analyzed spectral correlates of REM and NREM sleep in GBA L444P mutant mice. Importantly, EEG power spectral analysis revealed that GBA L444P mutation mice exhibited reduced delta power during non-rapid eye movement (NREM) sleep and increased theta power (8.2–10 Hz) in active rapid eye movement (REM) sleep phases. Our study revealed that GBA L444P-mutant mice, after receiving PFF injections, exhibited increased sleep fragmentation, significant motor and cognitive dysfunctions, and loss of dopaminergic neurons in the substantia nigra. Furthermore, the over-expression of GBA-AAV partially improved these sleep disturbances and motor and cognitive impairments. In conclusion, we present the initial evidence that the GBA L444P mutant mouse serves as an essential tool in understanding the complex sleep disturbances associated with PD. This model further provides insights into potential therapeutic approaches, particularly concerning α-synuclein accumulation and its subsequent pathological consequences.
All-optical temporal logic gates in localized exciton polaritons
Authors: Li Hui , Chen Fei , Jia Haoyuan , Ye Ziyu , Zhou Hang , Luo Song , Shi Junheng , Sun Zhenrong , Xu Huailiang , Xu Hongxing , Byrnes Tim , Chen Zhanghai , Wu Jian
Published: August 2024

Exciton polaritons—quasi-particle excitations consisting of strongly coupled photons and excitons—present fascinating possibilities for photonic circuits, owing to their strong nonlinearity, ultrafast reaction times and their ability to form macroscopic quantum states at room temperature via non-equilibrium condensation. Past implementations of transistors and logic gates with exciton polaritons have been mostly realized using the spatial propagation of polariton fluids, which place high demands on the fabrication of the microcavities and typically require complex manipulations. In this work we have implemented the full set of logical gate functionalities (that is, temporal AND, OR and NOT gates) in localized exciton polaritons at room temperature, on the basis of precisely controlling the interplay between polariton condensate and exciton reservoir dynamics, using a two-pulse excitation scheme. The dynamics intrinsically covers the cascadability required by the logical operations, enabling efficient information processing without the need for spatial flow. The temporal polariton logic gates demonstrate advantages in ultrafast switching, universality and simplified compatibility with other dimensional controls, showing great potential for building polariton logic networks in strongly coupled light–matter systems.
Safety and reactogenicity of a controlled human infection model of sand fly-transmitted cutaneous leishmaniasis
Authors: Parkash Vivak , Ashwin Helen , Dey Shoumit , Sadlova Jovana , Vojtkova Barbora , Van Bocxlaer Katrien , Wiggins Rebecca , Thompson David , Dey Nidhi Sharma , Jaffe Charles L. , Schwartz Eli , Volf Petr , Lacey Charles J. N. , Layton Alison M. , Kaye Paul M.
Published: August 2024

The leishmaniases are globally important parasitic diseases for which no human vaccines are currently available. To facilitate vaccine development, we conducted an open-label observational study to establish a controlled human infection model (CHIM) of sand fly-transmitted cutaneous leishmaniasis (CL) caused by Leishmania major. Between 24 January and 12 August 2022, we exposed 14 participants to L. major-infected Phlebotomus duboscqi. The primary objective was to demonstrate effectiveness of lesion development (take rate) and safety (absence of CL lesion at 12 months). Secondary and exploratory objectives included rate of lesion development, parasite load and analysis of local immune responses by immunohistology and spatial transcriptomics. Lesion development was terminated by therapeutic biopsy (between days 14 and 42 after bite) in ten participants with clinically compatible lesions, one of which was not confirmed by parasite detection. We estimated an overall take rate for CL development of 64% (9/14). Two of ten participants had one and one of ten participants had two lesion recurrences 4–8 months after biopsy that were treated successfully with cryotherapy. No severe or serious adverse events were recorded, but as expected, scarring due to a combination of CL and the biopsy procedure was evident. All participants were lesion free at >12-month follow-up. We provide the first comprehensive map of immune cell distribution and cytokine/chemokine expression in human CL lesions, revealing discrete immune niches. This CHIM offers opportunities for vaccine candidate selection based on human efficacy data and for a greater understanding of immune-mediated pathology. ClinicalTrials.gov identifier: NCT04512742.
A brain cell atlas integrating single-cell transcriptomes across human brain regions
Authors: Chen Xinyue , Huang Yin , Huang Liangfeng , Huang Ziliang , Hao Zhao-Zhe , Xu Lahong , Xu Nana , Li Zhi , Mou Yonggao , Ye Mingli , You Renke , Zhang Xuegong , Liu Sheng , Miao Zhichao
Published: August 2024

While single-cell technologies have greatly advanced our comprehension of human brain cell types and functions, studies including large numbers of donors and multiple brain regions are needed to extend our understanding of brain cell heterogeneity. Integrating atlas-level single-cell data presents a chance to reveal rare cell types and cellular heterogeneity across brain regions. Here we present the Brain Cell Atlas, a comprehensive reference atlas of brain cells, by assembling single-cell data from 70 human and 103 mouse studies of the brain throughout major developmental stages across brain regions, covering over 26.3 million cells or nuclei from both healthy and diseased tissues. Using machine-learning based algorithms, the Brain Cell Atlas provides a consensus cell type annotation, and it showcases the identification of putative neural progenitor cells and a cell subpopulation of PCDH9high microglia in the human brain. We demonstrate the gene regulatory difference of PCDH9high microglia between hippocampus and prefrontal cortex and elucidate the cell–cell communication network. The Brain Cell Atlas presents an atlas-level integrative resource for comparing brain cells in different environments and conditions within the Human Cell Atlas.
Solid oxide fuel cell (SOFC) control strategy enhancement by adaptive neuro-fuzzy inference system (ANFIS)
Authors: Ramadan Sameh , Al-Gabalaw Mostafa , EL-Shimy Mohamed , Emarah Adel
Published: August 2024

Global warming is a vital problem that many researchers tried to solve with so many solutions such as: reducing electricity production with conventional generators by using renewable energy resources and using hydrogen as an alternative to fossil fuels. The universal Economic crisis came across to cut off certain quantities at scheduled times. This, directly, affects renewable energy sources connected to the grid due to voltage and frequency variations. To solve this dilemma, in this paper, the grid-connected solid oxide fuel cell (SOFC) model which is fed by green hydrogen to produce AC power, is developed by an Adaptive neuro-fuzzy inference system (ANFIS). It is one of the artificial intelligence applications to improve grid-connected SOFC dynamic response. ANFIS is mathematically presented and simulated using MATLAB/SIMULINK. The results show that the ANFIS controller has succeeded in enhancing most of the desired control and operation signals.
Genetic breeding for indoor vertical farming
Authors: Teo Zhi Wei Norman , Yu Hao
Published: August 2024

Indoor vertical farming emerges as a sustainable paradigm, enabling crop cultivation in vertically layered ecosystems under precisely controlled environmental parameters. This innovative approach not only bolsters climate resilience but also minimizes the strain on precious arable land and water resources, aligning with sustainable principles. While posited as a transformative solution to global food security challenges and the limitations of traditional agriculture, a pivotal facet within indoor farming necessitates sustainable optimization: the crops cultivated within. Conventional commercial crop varieties utilized in indoor vertical farming lack tailored adaptations to controlled environments, underscoring the imperative to cultivate crops endowed with distinct indoor-farming traits. These include better performance under energy-efficient artificial lighting, high growth rate, and unique flavours. In this review, we highlight recent technological advancements in crop breeding and elaborate these coveted indoor-farming traits. In addition, we illuminate potential genetic workflows essential for breeders to strategically refine crops as a foundation for the long-term sustainability of indoor farming.