bluuebunny/crossref_metadata_2025 huggingface dataset:
Beyond treatment: Understanding family experiences in pediatric palliative care
Authors: Del Villar Guerra Pablo , Andrés de Álvaro Marta , García Miralles Laura , Tamayo-Morales Olaya , Ramos Pollo Daniel
Published: December 2024

Objectives

This study aimed to explore the multifaceted experiences of families with children and adolescents enrolled in the pediatric palliative care (PPC) program, with a particular emphasis on understanding their perspectives regarding the quality and effectiveness of care provided. Our goals included exploring emotional, social, and practical caregiving dimensions within the PPC context to address gaps and find areas for improvement. The objectives encompassed an exploration of the perceived effects on physical, emotional, social, and spiritual dimensions, an investigation into pre-PPC inclusion experiences, and an identification of limitations and potential areas for enhancement within the program.

Methods

Using a qualitative descriptive approach with a phenomenological lens, we engaged 6 primary caregivers through semi-structured interviews, employing theoretical convenience sampling. Analysis involved meticulous transcription, alphanumeric coding, and thematic categorization using Atlas.ti 8.0® software.

Results

Consistently echoed across interviews were the positive impacts on family dynamics, characterized by a sense of tranquility, enhanced patient care, and substantial caregiver support. Emotional well-being improvements were marked by elevated mood, reduced anxiety, and a restored sense of normalcy. Noteworthy challenges identified encompassed communication gaps among health-care professionals, limited-service availability, and perceived constraints in home care.

Significance of results

The study underscores the profound positive influence of the PPC program on the perceived quality of life for families navigating the complexities of caring for children with life-limiting illnesses. The findings underscore the paramount importance of holistic, family-centric care and underscore the imperative to address caregiver needs comprehensively to mitigate the risk of burnout. The identified challenges serve as signposts for refining communication strategies, expanding service provisions, and augmenting support structures within the PPC program. Overall, the study highlights the profound positive impact of the PPC program on family well-being, while also identifying areas for program enhancement, particularly in communication and service availability.
Circularly polarized diversified MIMO antenna design for millimeter-wave on-body applications using characteristic mode theory
Authors: Modak Sumon , Lokam Anjaneyulu , Farooq Umar
Published: December 2024

This paper presents a systematic design approach for developing a semiflexible multiple-input–multiple-output antenna system operating in the millimeter wave frequency spectrum, specifically designed for body-worn applications in biotechnologies. The designed antenna features dual flower-shaped antenna radiators placed in a spatial diversity configuration. Strategic modifications have been implemented by integrating dual crescent-shaped slots in the ground layer to attain the targeted frequency band of 25.7–30.6 GHz. Later, the upper edge of the ground plane is truncated in order to achieve circularly polarized radiation characteristics at 29.4 GHz with 3 dB ARBW of 0.6 GHz (29.1–29.7 GHz). The realization of circular polarization in the antenna geometry is validated through the analysis of characteristic mode theory. A maximum gain of 5.6 dBi is attained along with a port isolation of >30 dB. The proposed antenna undergoes analysis to assess its performance in the bending conditions and specific absorption rate, besides validation of diversity metrics encompassing envelope correlation coefficient, diversity gain, channel capacity loss, total active reflection coefficient, and mean effective gain has also been conducted. Finally, the proposed antenna structure is fabricated, and its performance is validated and subsequently compared with that of its simulated counterpart.
Interactions Between Multiple Physical Particle Injection Pumps in the Southern Ocean
Authors: Thompson Andrew F. , Dove Lilian A. , Flint Ellie , Lacour Leo , Boyd Philip
Published: December 2024

Contributions to the biological pump that arise from the physical circulation are referred to as physical particle injection pumps. A synthesized view of how these physical pumps interact with each other and other components of the biological pump does not yet exist. Here, observations from a quasi‐Lagrangian float and an ocean glider, deployed in the Southern Ocean's Subantarctic Zone for one month during the spring bloom, offer insight into daily‐to‐monthly fluctuations in the mixed layer pump (MLP) and the eddy subduction pump (ESP). Estimated independently, each mechanism contributes intermittent export fluxes of roughly several hundred milligrams of particulate organic carbon (POC) per square meter per day. The glider‐based estimates indicate sustained weekly periods of MLP export fluxes across the base of the mixed layer with a magnitude of  mg POC  . Potential export fluxes from the ESP, based on a mixed layer instability scaling, occasionally exceed 400 mg POC  , with export elevated due to both strong inferred vertical velocities and enhanced isopycnal slopes. Significant export fluxes from the ESP are localized to the edges of mesoscale eddies and to fronts, whereas the MLP acts more broadly due to the larger scales of atmospheric forcing. Regimes occur when MLP and ESP export fluxes can have either the same or opposite sign. Simple summation of fluxes from existing parameterizations of the two pumps likely misrepresents the total physical carbon flux. Insights into how mesoscale stirring and submesoscale velocities set POC vertical structure is a key target to reduce uncertainty in global carbon export fluxes.
Climatic Controls on the Length and Shape of the World's Drainage Basins
Authors: Singer Michael Bliss , Grieve Stuart W. D. , Chen Shiuan‐An , Michaelides Katerina
Published: December 2024

Climate is thought to affect the structure and evolution of drainage basins, but it is not clear how climate impacts the power law scaling between channel length and drainage area. Since climate controls runoff, streamflow, and erosion regimes, we looked for dependency of drainage basin morphometrics on climate within a near‐global data set. We show that increasingly arid regions have longer channels and narrower drainage basins, and power law scaling between channel length and basin area (Hack's Law) increases monotonically with aridity. We suggest these results arise due to downstream channel extension by rare large floods that erode channels into previously unchanneled terrain, yielding a morphometric signature in drylands that is preserved over long timescales due to a lack of subsequent topographic smoothing. This new understanding of drainage basin morphometrics on Earth may be used to inform interpretations of past climates on our planet and other solar system bodies.
Microfluidics and Spectral Induced Polarization for Direct Observation and Petrophysical Modeling of Calcite Dissolution
Authors: Rembert F. , Leroy P. , Lassin A. , Roman S.
Published: December 2024

We investigate how micro‐geoelectrical monitoring is promising for studying microscale coupled processes since it facilitates the upscaling of pore‐scale observations and enhances the petrophysical interpretation of the geoelectrical measurements. Microscale geophysics using microfluidics emerges and combines direct visualization of pore scale dynamics and chemical reactivity with geoelectrical monitoring. Calcite dissolution is a usual geochemical reaction considered as an analog of water–mineral interactions involved in the critical zone. We develop a numerical workflow combining image processing and geochemical simulation as inputs for the petrophysical modeling applied to a published data set of microscale induced polarization monitoring of calcite dissolution under partially saturated conditions. The successful interpretation provides the cation exchange capacity and specific surface area evolution; essential parameters in field‐scale surveys.
Deep Nitrogen Fluxes and Sources Constrained by Arc Lava Phenocrysts
Authors: Hudak Michael R. , Barry Peter H. , Bekaert David V. , Turner Stephen J. , Broadley Michael W. , Walowski Kristina , Tyne Rebecca L. , Li Kan , Nielsen Sune G. , Curtice Joshua M. , Kurz Mark D. , Cahoon Emily , Wallace Paul , Muth Michelle , Shaw Alison M.
Published: December 2024

Nitrogen (N) dominates Earth's atmosphere (78% N2) but occurs in trace abundances in silicate minerals, making it a sensitive tracer of recycled surface materials into the mantle. The mechanisms controlling N transfer between terrestrial reservoirs remain uncertain because low N abundances in mineral‐hosted fluid inclusions (FIs) are difficult to measure. Using new techniques, we analyzed N and He isotope compositions and abundances in olivine‐ and pyroxene‐hosted FIs from arc volcanoes in Southern Chile, Cascadia, Central America, and the Southern Marianas. These measurements enable an estimate of the global flux of N outgassing from arcs (4.0 × 1010 mol/yr). This suggests that Earth is currently in a state of net N ingassing, with roughly half of subducted N returned to the mantle. Additionally, the N outgassing flux of individual arcs correlates with the thickness of subducting pelagic sediment, suggesting that N cycling in the modern solid Earth is largely controlled by sediment subduction.
Greenland Ice Cores Reveal a South‐To‐North Difference in Holocene Thermal Maximum Timings
Authors: Martin Kaden C. , Buizert Christo , Brook Ed , Williams Olivia L. , Edwards Jon S. , Riddell‐Young Ben , Fudge T. J. , Mederbel Farhana , Beaudette Ross , Severinghaus Jeff , Oyabu Ikumi , Kawamura Kenji , Kirk Marie , Koldtoft Iben , Steffensen J. P. , Blunier Thomas
Published: December 2024

Holocene temperature evolution remains poorly understood. Proxies in the early and mid‐Holocene suggest a Holocene Thermal Maximum (HTM) where temperatures exceed the pre‐industrial, whereas climate models generally simulate monotonic warming. This discrepancy may reflect proxy seasonality biases or errors in climate model internal feedbacks or dynamics. Using seasonally unbiased ice core reconstructions at NEEM, NGRIP, and Greenland Ice Sheet Project 2, we identify a Greenland HTM of ∼2°C above pre‐industrial, in agreement with other Northern Hemisphere proxy reconstructions. The firn‐based reconstructions are verified through borehole thermometry, producing a multi‐core, multi‐proxy reconstruction of Greenland climate from the last glacial to pre‐industrial. HTM timing across Greenland is heterogenous, occurring earlier at high elevations. Total air content measurements suggest a temperature contribution from elevation changes; regional oceanographic conditions, a weakened polar lapse rate, or variable near‐surface inversions may also be important sensitivities. Our reconstructions support climate simulations with dynamic Holocene vegetation, highlighting the importance of vegetation feedbacks.
HF Radar Observations and Modeling of the Impact of the 8 April 2024 Total Solar Eclipse on the Ionosphere‐Thermosphere System
Authors: Kunduri B. S. R. , Baker J. B. H. , Ruohoniemi J. M. , Thomas E. G. , Huba J. D. , Emmons D. J. , Themens D. R. , Sterne K. T. , Farinas Perez G. , Bristow W. A. , Shepherd S. G. , Holmes J. M. , Dao E. V. , Chartier A. T. , Perry G. W. , Pandey K.
Published: December 2024

The path of totality of the 8 April 2024 solar eclipse traversed the fields‐of‐view of four US SuperDARN radars. This rare scenario provided an excellent opportunity to monitor the large‐scale ionospheric response to the eclipse. In this study, we present observations made by the Blackstone (BKS) SuperDARN radar and a Digisonde during the eclipse. Two striking effects were observed by the BKS radar: (a) the Doppler velocities associated with ground scatter coalesced into a pattern clearly organized by the line of totality, with a reversal in sign across this line, and, (b) a delay of 45 min between time of maximum obscuration and maximum effect on the skip distance. The skip distance estimated using a SAMI3 simulation of the eclipse did not however capture the asymmetric time‐delay. These observations suggest that the neutral atmosphere plays an important role in controlling ionospheric plasma dynamics, which were missing in SAMI3 simulations.
Dispersal of the Changjiang River Water in East Asian Shelf Seas
Authors: Cheng Peng
Published: December 2024

River plumes are crucial in transporting terrestrial materials from rivers to oceans. Knowledge gaps, however, still exist in understanding the transport pathway and the ultimate fate of riverine water in coastal oceans. This study conducted a 50‐year climatological numerical simulation to investigate the long‐term transport processes of Changjiang River water in the East Asian shelf seas. The Changjiang River water exhibits distinct seasonal patterns near the estuary mouth and in the coastal area south of the estuary, and it tends to be retained within the shelf seas, which influences its far‐field transport. The Changjiang River water takes less than 1 year to reach the eastern shelf edge of the East China Sea and over 12 years to enter the Bohai Sea. The Kuroshio current impedes the cross‐shelf transport of Changjiang water, with water in the Kuroshio region over 6 years old. The Taiwan Warm Current not only acts as a barrier that regulates the pathways of Changjiang River water but also serves as an important conduit for water exiting the East China Sea. The Changjiang River water leaves the estuary through four branches, forming eight major transport pathways in the Yellow and East China Seas. Approximately 85% of Changjiang River water flows through the Tsushima/Korea Straits, about 14% exits from the shelf edge of the East China Sea, and less than 1% passes through the Taiwan Strait. The results underscore the importance of water renewal and shelf circulation in the long‐term transport of river water within coastal oceans.
Thermohaline Intrusions as Seen by Argo Floats: The Case of the Black Sea
Authors: Stanev E. V. , Gramcianinov C. B. , Staneva J. , Slabakova V.
Published: December 2024

Understanding the dynamics of thermohaline intrusions is crucial for predicting changes in water masses and their impact on marine ecosystems, especially in highly stratified semi‐enclosed seas and other coastal environments. We use high‐resolution (up to 1–2 m) Argo profiling float data collected over 15 years in the Black Sea, an excellent test area for studying thermohaline intrusions. Our analysis challenges the conventional view of stagnant intermediate and deep waters, revealing active mixing processes that reshape the thermohaline structure. We identified two main mechanisms driving these intrusions, related to dense water inflows from the Marmara Sea and boundary mixing enhanced by frontal instabilities. Argo data also allowed us to identify areas with favorable conditions for double‐diffusive processes. The variability of intrusions is due to changes in the thermohaline state of the upper ocean as well as to quasi‐periodic changes in the inflow caused by local conditions. Trends in the intensity and frequency of intrusions indicate shifts in water mass properties that are likely to be associated with climate variability and extreme weather events. Such trends can affect nutrient cycling, oxygen distribution and the overall stability of the water column, thereby affecting biogeochemical cycles and the resilience of marine ecosystems. Similar ventilation mechanisms may operate in other highly stratified marine systems, such as the Baltic Sea and the Arctic Ocean, so our findings may have wider implications for understanding climate‐induced changes in water masses at regional and global scales.
Evolution of the Double Warm‐Core Structure in the Eyewall Replacement Cycle of Typhoon Trami (2018)
Authors: Li Xiangcheng , Cheng Xiaoping , Fei Jianfang , Huang Xiaogang , He Shunzhi
Published: December 2024

The evolution of double warm‐cores (DWC) during the secondary eyewall formation (SEF) and the subsequent eyewall replacement cycle (ERC) in Typhoon Trami (2018) was investigated in this study. Using a coupled atmosphere‐ocean model, the impacts of the typhoon‐induced sea surface cooling (SSC) on the DWC structure were also examined. In both the coupled and uncoupled simulations, the middle‐level warm‐core (MWC) decayed as the tangential wind expanded outward during the SEF, even in the absence of SSC. Under the thermal wind balance, the cooling of the MWC was an inherent result to ensure the dynamic consistency during the SEF. In contrast to the uncoupled simulation, the upper‐level warm‐core (UWC) decayed under the influence of SSC, significantly contributing to the rapid weakening of Trami. The negative effects of the SSC on the UWC were more detrimental to the intensity of Trami. Results from the potential temperature (PT) budget of improved accuracy indicated that the decrease in the warming due to the radial eddy advection was mainly responsible for the decay of the MWC. The flattened radial gradient of PT during the SEF accounted for the reduction in the dynamical eye warming associated with the asymmetric mixing. In addition to the convectively induced subsidence, the upper‐level asymmetric structures could also be affected by the SSC. Consequently, the increase in the cooling due to the enhanced asymmetry collaborated with the decrease in the adiabatic warming, leading to the decay of the UWC in the coupled simulation.
Simulating Precipitation Efficiency Across the Deep Convective Gray Zone
Authors: Kukulies Julia , Prein Andreas F. , Morrison Hugh
Published: December 2024

Precipitation efficiency (PE) relates cloud condensation to precipitation and thus reflects how much of the total atmospheric condensate reaches the surface as precipitation. Because the PE in convective storms is directly linked to their updraft and downdraft dynamics, it is a helpful metric to identify convective processes that influence precipitation. However, km‐scale model simulations do not properly resolve convective processes such as individual updrafts and entrainment, which raises the question if such simulations can accurately represent PE. Here, we present two methods to derive PE from standard model output because condensation is usually not available as an output variable. The first method estimates PE from the state variables vertical velocity, temperature, and pressure, whereas the second method estimates PE from ice water path (IWP) and precipitation. We validate the proposed methods with the explicitly calculated PE using a set of idealized Weather Research and Forecast model simulations of organized midlatitude convective storms at different horizontal grid spacings. We show that PE can be reliably estimated from state variables with an error of less than 5%, partly due to error cancellation effects. Additionally, PE can be simulated by km‐scale models within ∼15% accuracy compared to large‐eddy simulations (LESs). The IWP method is slightly less accurate with a stronger grid spacing dependency of the error, but since it is based on observable quantities, it allows for a validation of simulated PE with satellite observations. Finally, we analyze the grid spacing dependency of the climate change signal of PE and find that future decreases in PE in LESs are robustly captured by km‐scale models.
Short‐Term Prediction of the Dst Index and Estimation of Efficient Uncertainty Using a Hybrid Deep Learning Network
Authors: Wang Ruyao , Wang Jianhui , Liang Tuo , Zhang Huixiong
Published: December 2024

In this study, we developed a novel deep learning model to predict the disturbance storm time (Dst) index 1–4 hr ahead. We also employed the Monte Carlo (MC) dropout technique to estimate the uncertainty and provide the prediction interval by introducing a recalibration factor. The proposed model achieves excellent scalability by extracting representative embeddings from the Dst index time series through an encoder‐decoder framework and integrating these with external solar wind parameters via a prediction network. We utilized magnetic storm data from 1998 to 2018 to evaluate the performance of the prediction model. Experimental results indicate that the proposed model reduces root mean square errors (RMSE) and improves the coefficient of determination (R2) compared to existing methods. Quantitative uncertainty analysis demonstrates that the prediction interval is reliable in most cases. The percent distribution across test storms by comparing the uncertainty‐based prediction of the minimum peak with the mean prediction indicates the probabilistic forecast model is competitive.
Membrane potential states gate synaptic consolidation in human neocortical tissue
Authors: Mittermaier Franz X. , Kalbhenn Thilo , Xu Ran , Onken Julia , Faust Katharina , Sauvigny Thomas , Thomale Ulrich W. , Kaindl Angela M. , Holtkamp Martin , Grosser Sabine , Fidzinski Pawel , Simon Matthias , Alle Henrik , Geiger Jörg R. P.
Published: December 2024

Synaptic mechanisms that contribute to human memory consolidation remain largely unexplored. Consolidation critically relies on sleep. During slow wave sleep, neurons exhibit characteristic membrane potential oscillations known as UP and DOWN states. Coupling of memory reactivation to these slow oscillations promotes consolidation, though the underlying mechanisms remain elusive. Here, we performed axonal and multineuron patch-clamp recordings in acute human brain slices, obtained from neurosurgeries, to show that sleep-like UP and DOWN states modulate axonal action potentials and temporarily enhance synaptic transmission between neocortical pyramidal neurons. Synaptic enhancement by UP and DOWN state sequences facilitates recruitment of postsynaptic action potentials, which in turn results in long-term stabilization of synaptic strength. In contrast, synapses undergo lasting depression if presynaptic neurons fail to recruit postsynaptic action potentials. Our study offers a mechanistic explanation for how coupling of neural activity to slow waves can cause synaptic consolidation, with potential implications for brain stimulation strategies targeting memory performance.
How measurement noise limits the accuracy of brain-behaviour predictions
Authors: Gell Martin , Eickhoff Simon B. , Omidvarnia Amir , Küppers Vincent , Patil Kaustubh R. , Satterthwaite Theodore D. , Müller Veronika I. , Langner Robert
Published: December 2024

Major efforts in human neuroimaging strive to understand individual differences and find biomarkers for clinical applications by predicting behavioural phenotypes from brain imaging data. To identify generalisable and replicable brain-behaviour prediction models, sufficient measurement reliability is essential. However, the selection of prediction targets is predominantly guided by scientific interest or data availability rather than psychometric considerations. Here, we demonstrate the impact of low reliability in behavioural phenotypes on out-of-sample prediction performance. Using simulated and empirical data from four large-scale datasets, we find that reliability levels common across many phenotypes can markedly limit the ability to link brain and behaviour. Next, using 5000 participants from the UK Biobank, we show that only highly reliable data can fully benefit from increasing sample sizes from hundreds to thousands of participants. Our findings highlight the importance of measurement reliability for identifying meaningful brain–behaviour associations from individual differences and underscore the need for greater emphasis on psychometrics in future research.
Copper chelation redirects neutrophil function to enhance anti-GD2 antibody therapy in neuroblastoma
Authors: Rouaen Jourdin R. C. , Salerno Antonietta , Shai-Hee Tyler , Murray Jayne E. , Castrogiovanni Giulia , McHenry Charlotte , Jue Toni Rose , Pham Vu , Bell Jessica Lilian , Poursani Ensieh , Valli Emanuele , Cazzoli Riccardo , Damstra Naomi , Nelson Delia J. , Stevens Kofi L. P. , Chee Jonathan , Slapetova Iveta , Kasherman Maria , Whan Renee , Lin Francis , Cochran Blake J. , Tedla Nicodemus , Veli Feyza Colakoglu , Yuksel Aysen , Mayoh Chelsea , Saletta Federica , Mercatelli Daniele , Chtanova Tatyana , Kulasinghe Arutha , Catchpoole Daniel , Cirillo Giuseppe , Biro Maté , Lode Holger N. , Luciani Fabio , Haber Michelle , Gray Juliet C. , Trahair Toby N. , Vittorio Orazio
Published: December 2024

Anti-disialoganglioside (GD2) antibody therapy has provided clinical benefit to patients with neuroblastoma however efficacy is likely impaired by the immunosuppressive tumor microenvironment. We have previously defined a link between intratumoral copper levels and immune evasion. Here, we report that adjuvant copper chelation potentiates anti-GD2 antibody therapy to confer durable tumor control in immunocompetent models of neuroblastoma. Mechanistic studies reveal copper chelation creates an immune-primed tumor microenvironment through enhanced infiltration and activity of Fc-receptor-bearing cells, specifically neutrophils which are emerging as key effectors of antibody therapy. Moreover, we report copper sequestration by neuroblastoma attenuates neutrophil function which can be successfully reversed using copper chelation to increase pro-inflammatory effector functions. Importantly, we repurpose the clinically approved copper chelating agent Cuprior as a non-toxic, efficacious immunomodulatory strategy. Collectively, our findings provide evidence for the clinical testing of Cuprior as an adjuvant to enhance the activity of anti-GD2 antibody therapy and improve outcomes for patients with neuroblastoma.
Evolution of a SHOOTMERISTEMLESS transcription factor binding site promotes fruit shape determination
Authors: Hu Zhi-Cheng , Majda Mateusz , Sun Hao-Ran , Zhang Yao , Ding Yi-Ning , Yuan Quan , Su Tong-Bing , Lü Tian-Feng , Gao Feng , Xu Gui-Xia , Smith Richard S. , Østergaard Lars , Dong Yang
Published: December 2024

In animals and plants, organ shape is primarily determined during primordium development by carefully coordinated growth and cell division1–3. Rare examples of post-primordial change in morphology (reshaping) exist that offer tractable systems for the study of mechanisms required for organ shape determination and diversification. One such example is morphogenesis in Capsella fruits whose heart-shaped appearance emerges by reshaping of the ovate spheroid gynoecium upon fertilization4. Here we use whole-organ live-cell imaging and single-cell RNA sequencing (scRNA-seq) analysis to show that Capsella fruit shape determination is based on dynamic changes in cell growth and cell division coupled with local maintenance of meristematic identity. At the molecular level, we reveal an auxin-induced mechanism that is required for morphological alteration and ultimately determined by a single cis-regulatory element. This element resides in the promoter of the Capsella rubella SHOOTMERISTEMLESS
5 (Cr
STM) gene. The CrSTM meristem identity factor positively regulates its own expression through binding to this element, thereby providing a feed-forward loop at the position and time of protrusion emergence to form the heart. Independent evolution of the STM-binding element in STM promoters across Brassicaceae species correlates with those undergoing a gynoecium-to-fruit shape change. Accordingly, genetic and phenotypic studies show that the STM-binding element is required to facilitate the shape transition and suggest a conserved molecular mechanism for organ morphogenesis.
Widespread outdoor exposure to uncompensable heat stress with warming
Authors: Fan Yuanchao , McColl Kaighin A.
Published: December 2024

Previous studies projected an increasing risk of uncompensable heat stress indoors in a warming climate. However, little is known about the timing and extent of this risk for those engaged in essential outdoor activities, such as water collection and farming. Here, we employ a physically-based human energy balance model, which considers radiative, wind, and key physiological effects, to project global risk of uncompensable heat stress outdoors using bias-corrected climate model outputs. Focusing on farmers (approximately 850 million people), our model shows that an ensemble median 2.8% (15%) would be subject to several days of uncompensable heat stress yearly at 2 (4) °C of warming relative to preindustrial. Focusing on people who must walk outside to access drinking water (approximately 700 million people), 3.4% (23%) would be impacted at 2 (4) °C of warming. Outdoor work would need to be completed at night or in the early morning during these events.
How much longer do you have to drive than the crow has to fly?
Authors: Wang Shanshan , Bette Henrik M. , Schreckenberg Michael , Guhr Thomas
Published: December 2024

When travelling by car from one location to another, our route is constrained by the road network. The network distance between the two locations is generally longer than the geodetic distance as the crow flies. We report a systematic relation between the statistical properties of these two distances. Empirically, we find a robust scaling between network and geodetic distance distributions for a variety of large motorway networks. A simple consequence is that we typically have to drive 1.3 ± 0.1 times longer than the crow flies. This scaling is not present in standard random networks; rather, it requires non-random adjacency. We develop a set of rules to build a realistic motorway network, also consistent with the above scaling. We hypothesise that the scaling reflects a compromise between two societal needs: high efficiency and accessibility on the one hand, and limitation of costs and other burdens on the other.
Electro-catalyzed, solvent-controlled divergent decarboxylative annulation and hydroaminomethylation of cyclic aldimines with N-arylglycines
Authors: Zhang Jie , Li Xiaolan , Chen Guisheng , Liu Haidong , Luo Haiqing
Published: December 2024

Herein, we reported a sustainable and simple method involving electrochemical-catalyzed decarboxylative annulation and hydroaminomethylation of cyclic aldimines with N-arylglycines, achieved through solvent-switching.
Defect-derived catalytic sites in Ce/Zr-UiO-66 for degradation of hexachlorobenzene
Authors: Wang Zhengyan , Yuan Chenhao , Yang Dong , Cui Mifen , Tang Jihai , Zhang Zhuxiu , Qiao Xu
Published: December 2024

The metal clusters in the Ce/Zr-UiO-66 generated open metal sites after post-treatment with methanol and water vapor, achieving complete catalytic degradation of hexachlorobenzene.
Introduction of substituents for tuning the redox properties of benzoate-bridged paddlewheel diruthenium(ii,ii) complexes: what does the OH group bring?
Authors: Kosaka Wataru , Watanabe Yudai , Kitayama Taku , Itoh Chisa , Miyasaka Hitoshi
Published: December 2024

A series of homoleptic/heteroleptic paddlewheel diruthenium(ii,ii) complexes with hydroxybenzoate containing additional substituents such as halogens were synthesized. The substituent effects obeyed the extended Hammett's law on a unified scale.
Rhodium-catalyzed transformations of diazo compounds via a carbene-based strategy: recent advances
Authors: Doraghi Fatemeh , Baghershahi Parsa , Ghasemi Mehran , Mahdavi Mohammad , Al-Harrasi Ahmed
Published: December 2024

As a carbene precursor, diazo compounds incorporate in Rh-catalyzed synthesis of heterocycles, carbocycles and functionalized compounds. The reaction involves C–H activation, carbene insertion and an annulation/functionalization sequence.
Controlled tuning of HOMO and LUMO levels in supramolecular nano-Saturn complexes
Authors: Maqbool Maria , Ayub Khurshid
Published: December 2024

Controlled tuning of HOMO and LUMO levels.
Iridium trihydride and tetrahydride complexes and their role in catalytic polarisation transfer from parahydrogen to pyruvate
Authors: Tickner Ben. J. , Duckett Simon B.
Published: December 2024

This work details formation of unusual [Ir(H)4(IMes)(sulfoxide)]Na and [Ir(H)3(IMes)(sulfoxide)2] from Ir(i) precursors, alongside binuclear products. Their role in the catalytic transfer of magnetisation from parahydrogen is investigated.
Determinants of regioselectivity of heterostructures in cation exchange reactions
Authors: Qu Xuelian , Zhang Huisheng , Gao Tianyi , Zhang Fei , Zhang Ying , Xue Ding-Jiang , Liu Yang
Published: December 2024

The local density of delocalized electrons between host lattice and guest cations determines the reaction heat on different facets, thereby dictating the regioselectivity of cation exchange reactions occurring primarily at the edges of nanoplates.
Total synthesis of (−)-flueggenine A and (−)-15′-epi-flueggenine D
Authors: Seo Seung Mo , Kim Dongwook , Kim Taewan , Han Sunkyu
Published: December 2024

We report the first total synthesis of (–)-flueggenine A and (–)-15′-epi-flueggenine D, featuring a key reductive Heck reaction-based dimerization with a silyl-tethered enone coupling partner to ensure the desired reactivity and stereoselectivity.
Electronic structure regulation of carbon atoms from wood for enhancing Zn–air battery performances
Authors: Zhang Shengyue , Chen Zhonghao , Xiong Zhong , Wang Zhicong , Zhao Zhihui , Xue Zhixin , Li Kang , Wang Kai , Hui Bin
Published: December 2024

A simple and scalable method was designed to convert balsa wood into non-metallic N, S-doped carbon catalysts with superior ORR performance and excellent application potential in ZABs.
Genetic algorithm‐based approach for torque control and increased efficiency across an optimised speed range in switched reluctance drives
Authors: MacRae Euan , Abdel‐Aziz Ali , Ahmed Khaled , Pollock Richard , Williams Barry W.
Published: December 2024

This paper presents a novel genetic algorithm (GA) design for current profiling in switched reluctance machines that eliminates torque ripple (TR) while inherently guaranteeing minimal RMS currents across the machines speed range. Minimising RMS current provides an increase to machine efficiency and the elimination of TR is required for potential SRM applications such as traction vehicles. This paper proposes a novel method for intentional greater‐than‐two‐phase overlap in the algorithm design. This allows any SRM configuration capable of three or more phase conduction to utilise its full speed range with zero torque ripple, in the case where it is limited using two‐phase torque sharing. An optimal set of current profiles is created using the algorithm across the full speed range of an exemplary 8/6 SRM and these are analysed. A current profiling‐based control scheme using these results is then proposed and simulated for the 8/6 SRM. This is then compared to classical and recently published SRM control methods to highlight the merits of the overall GA design and its resultant control scheme.
Fault diagnosis of power transformers based on dissolved gas analysis and improved LightGBM hybrid integrated model with dual‐branch structure
Authors: Lv Xuebin , Liu Fuzheng , Jiang Mingshun , Zhang Faye , Jia Lei
Published: December 2024

Aiming at the fault diagnosis problems of imbalanced data and insufficient mapping of characteristic information in fault samples collected by transformers at present, which lead to low accuracy and large diagnostic deviation in actual applications, a power transformer fault diagnosis method based on dissolved gas analysis and an improved LightGBM hybrid integrated model with a dual‐branch structure (DIL‐DS) is proposed. Firstly, multi‐characteristic dissolved gas ratio analysis is used to construct multi‐dimensional supplementary feature vectors, which enrich the characterisation features of transformers and facilitate efficient diagnosis of classification models. Secondly, a dual‐branch structure combining focal‐gradient harmonic loss and cross‐entropy loss is introduced to improve the attention and recognition ability of the model to a few categories in the dataset and alleviate the influence of data imbalance on the diagnostic results. Then, an improved grey wolf optimisation (GWO) is designed to improve LightGBM and realise the iterative optimisation of hyperparameters. At the same time, the Jacobian regularisation method is introduced to denoise LightGBM to solve the problem that the model is sensitive to noise. Finally, the LightGBM hybrid integrated model is developed to ensure the accuracy and stability of model diagnosis under the changeable and imbalanced dataset. Experiments show that the proposed DIL‐DS can effectively solve the limitation of class imbalance, improve the overall fault diagnosis performance, and is suitable for transformer fault identification.
Weakly supervised brain tumour segmentation with label propagation and level set loss
Authors: Abadian‐Zadeh Fatemeh‐Sadat , Mohammadi Mohammad Reza , Soryani Mohsen
Published: December 2024

Early diagnosis of brain tumors significantly enhances treatment success. However, accurate detection and segmentation of tumors, essential for diagnosis, rely heavily on costly manual annotation by experts. To mitigate these costs, weakly supervised methods have gained traction. This paper introduces a novel weakly supervised brain tumor segmentation approach utilizing point and scribble supervision. Experts annotate only the slice with the largest tumor area by marking a single point near the tumor center or drawing a scribble within the tumor region. The method operates in two phases. First, labels are propagated to unlabelled pixels, generating a pseudo‐ground‐truth with three labels: tumor, non‐tumor, and marginal pixels (unlabelled pixels surrounding the initial segmentation). Second, a segmentation model is trained using the pseudo‐ground‐truth and a loss function combining level‐set and binary cross‐entropy losses. Marginal pixels contribute to level‐set loss computation, refining the segmentation process. The approach is validated on 3D magnetic resonance imaging (MRI) volumes from BraTS2020, BraTS2021, and BraTS2023 benchmark datasets. Experimental results show Dice scores comparable to fully supervised methods for whole tumor segmentation, demonstrating the effectiveness of the proposed weakly supervised strategy. This method reduces annotation effort while maintaining competitive segmentation performance, making it valuable for clinical applications.
3D‐TabNetHS: A hyperspectral image classification method based on improved interpretable 3D attentive TabNet
Authors: Li Ning , Wei Daozhi , Huang Shucai , Zhang Yong
Published: December 2024

The classification methods for hyperspectral images (HSI) based on decision trees and convolutional neural networks have shown increasing advantages, but these methods often require a large number of labelled samples for learning, which is difficult for HSI, and the interpretability of the network is not high. Therefore, this paper proposes classification methods based on improved attention interpretable table learning (TabNet) named 3D TabNet HSI (3D‐TabNetHS) and unsupervised 3D TabNet HSI (U3D‐TabNetHS). These methods use sequential attention to select appropriate HSI spatial‐spectral features and add a space spectral information extraction (SSE) module composed of a 3D convolutional neural network (3D‐CNN) and fully connected layers to the Attention Transformer module in the original TabNet network to extract spatial‐spectral soft features. At the same time, unsupervised learning can be used to retrain the 3D‐TabNetHS network, and the classification accuracy of the resulting U3D‐TabNetHS network can be further improved. Compared with other HSI classification methods based on decision trees, the HSI classification accuracy of 3D‐TabNetHS is higher. On three typical HSI datasets, the accuracy metric overall accuracy of 3D‐TabNetHS reached as high as 98.71%, 94.73%, and 97.23%, respectively. Simultaneously, the consistency evaluation metric Kappa also reached 98.56%, 93.98%, and 96.31% respectively. The experimental results indicate the feasibility and reliability of the proposed method in HSI classification.
A new approach to manage the connection queue
Authors: Ostler Nicolas , Li Furong , Dale Lewis
Published: December 2024

The connection queue has seen unparalleled growth over the last 24 months. With the record number of connection agreement applications representing a pivotal time for system development as we drive investment that will enable us to transition into an electrified future. The authors look to address challenges posed to the connection queue through congestion management‐based techniques. Conducting a top down approach, the authors first visualise the state of the queue. Observing highest growth in pure storage based applications distributed close to traditional load centres, followed by wind projects along the East Coast and Northern Scotland. Supporting close analysis is performed on the representative B6 boundary. The authors compare methodologies, validate a process for the attribution of congestion cost and quantify the value of investment given by unit power changes. Finding that most significant value of investment in storage lies in the Southeast of England and the North of Scotland. This reflects the identified current state of constraint and most efficient current utilisation of available capacity. These approaches have been aligned with current system thinking and progress towards a new industry data sharing standard, forming strategy by which we look to transition the energy system and country into a decarbonised future.
A step towards digital transformation within a utility company through process automation for a sustainable energy transition
Authors: Parra Nhora , Giraldo Sandra , la Rotta David , Gómez Betsy , Mejía Yissel , Morales Laidi , Nieto‐Londoño César , Vásquez Rafael E.
Published: December 2024

Sustainable energy management systems are part of the global energy transition by digitally transforming utility companies throughout the past decade. Industry 4.0 (4IR) has been adopted to improve competitiveness and align its processes with trends that require changes in the producer‐consumer relationship. This study examines how AES Colombia uses Industry 4.0 to improve efficiency and promote a sustainable energy transition. It focuses on automating key processes within the company's hydropower operations, representing 6% of Colombia's energy market. The research shows that robotic‐process‐automation technologies reduce pricing simulation time from 27 to 5 h and tax declaration manual labour from 1560 to 584 h. These advancements enhance operational efficiency and significantly improve decision‐making capabilities, thereby boosting the reliability of information utilized across various operational domains, including financial, market, and regulatory processes. The findings underscore the critical role of flexibility, cultural change, and continuous training in facilitating successful digital transformation initiatives. This work contributes to understanding how intelligent systems can optimize energy companies’ processes while promoting a human‐centred approach to Industry 4.0 technologies. The results underscore the importance of aligning technological advancements with sustainability goals to drive significant improvements in the energy sector, paving the way for a more resilient and adaptable energy landscape.
The Galaxy Activity, Torus, and Outflow Survey (GATOS)
Authors: Poitevineau R. , Combes F. , Garcia-Burillo S. , Cornu D. , Alonso Herrero A. , Ramos Almeida C. , Audibert A. , Bellocchi E. , Boorman P. G. , Bunker A. J. , Davies R. , Díaz-Santos T. , García-Bernete I. , García-Lorenzo B. , González-Martín O. , Hicks E. K. S. , Hönig S. F. , Hunt L. K. , Imanishi M. , Pereira-Santaella M. , Ricci C. , Rigopoulou D. , Rosario D. J. , Rouan D. , Villar Martin M. , Ward M.
Published: December 2024

The detailed feeding and feedback mechanisms of active galactic nuclei (AGNs) are not yet well known. For low-luminosity AGNs, obscured AGNs, and late-type galaxies, the masses of their central black holes (BH) are difficult to determine precisely. Our goal with the GATOS sample is to study the circum-nuclear regions and, in the present work, to better determine their BH mass, with more precise and accurate estimations than those obtained from scaling relations. We used the high spatial resolution of ALMA to resolve the CO(3–2) emission within ∼100 pc around the supermassive black hole (SMBH) of seven GATOS galaxies and try to estimate their BH mass when enough gas is present in the nuclear regions. We studied the seven bright (LAGN(14 − 150 keV)≥1042 erg/s) and nearby (< 28 Mpc) galaxies from the GATOS core sample. For the sake of comparison, we first searched the literature for previous BH mass estimations. We also made additional estimations using the MBH–σ relation and the fundamental plane of BH activity. We developed a new method using supervised machine learning to estimate the BH mass either from position-velocity diagrams or from first-moment maps computed from ALMA CO(3–2) observations. We used numerical simulations with a large range of parameters to create the training, validation, and test sets. Seven galaxies had sufficient gas detected, thus, we were able to make a BH estimation from the ALMA data: NGC 4388, NGC 5506, NGC 5643, NGC 6300, NGC 7314, NGC 7465, and NGC 7582. Our BH masses range from 6.39 to 7.18 log(MBH/M⊙) and are consistent with the previous estimations. In addition, our machine learning method has the advantage of providing a robust estimation of errors with confidence intervals. The method has also more growth potential than scaling relations. This work represents the first step toward an automatized method for estimating MBH using machine learning.