bluuebunny/crossref_metadata_2025 huggingface dataset:
Abrupt physico-chemical changes in the limnology of Pyrenean mountain lakes necessitate urgent management actions
Authors: Sentenac Hugo , Schmeller Dirk S. , Chardon Emilie , Fisher Matthew C. , Loyau Adeline
Published: January 2025

Mountain lakes are rare ecological niches supporting unique species assemblages and are important sources of safe drinking water for wildlife, livestock and humans. Located at high altitude, these lakes are vulnerable to environmental stressors such as climate or land-use change, impacting their ecosystem functions. However, although trends in water temperature and physico-chemical composition have been fairly well studied in large mountain lakes, the same cannot be said for small- to medium-sized shallow lakes. Here, using measurements of the water chemistry of 25 Pyrenean mountain lakes and temperature records for 14 of them, we show that the environmental conditions which prevail in their littoral zones have undergone rapid changes between 2007 and 2023. Over this 16-year period, we found that, on average, the duration of the ice-cover period decreased by 58.35 days, and the average annual water temperature rose by 1.65 °C. We also found a significant overall decrease in pH, total organic carbon and nitrogen, as well as a significant increase in hardness and dissolved potassium. Our results demonstrate rapid abiotic environmental alterations in mountain lakes, with potential negative implications for humans, wildlife, livestock and ecosystem functioning. Likely consequences include declines in aquatic biodiversity, a degradation in the quality of drinking water and increased health risks from harmful algal blooms. Policy must urgently acknowledge the impacts of global change in mountains in order to take the necessary management actions.
Adding higher-level semantics to Functional Mock-up Units for easier, faster, and more robust co-simulation connections
Authors: Rindarøy Martin , Nordahl Håvard , Sadjina Severin , Skjong Stian , Hagaseth Marianne
Published: January 2025

The task of interfacing sub-simulators in a co-simulation often remains difficult, tedious, and prone to error. Here, we describe how this process, and the validation of the resulting interface connections, can be made simpler, faster, and more reliable. Especially when, as is often the case, several individuals or teams collaborate on modeling and simulating a full system. This is achieved by grouping functional mock-up interface (FMI) variables into types close to the relevant engineering domains using semantics formalized as an ontology. Several benefits, we argue, are gained from this: clearer communication, increased validation potential, and reduced number of interface connections to deal with. The validity and the limitations of our approach are demonstrated with a detailed case study of a real maritime system: A dynamic positioning (DP) hardware controller connected to several independent co-simulation models via 156 variables in 78 connections. The proposed solution greatly reduces the complexities and the error potential related to interfacing such systems. All results including reference implementations are openly available through the open simulation platform.
MHNet: Multi-view High-Order Network for Diagnosing Neurodevelopmental Disorders Using Resting-State fMRI
Authors: Li Yueyang , Zeng Weiming , Dong Wenhao , Cai Luhui , Wang Lei , Chen Hongyu , Yan Hongjie , Bian Lingbin , Wang Nizhuan
Published: January 2025

Deep learning models have shown promise in diagnosing neurodevelopmental disorders (NDD) like ASD and ADHD. However, many models either use graph neural networks (GNN) to construct single-level brain functional networks (BFNs) or employ spatial convolution filtering for local information extraction from rs-fMRI data, often neglecting high-order features crucial for NDD classification. We introduce a Multi-view High-order Network (MHNet) to capture hierarchical and high-order features from multi-view BFNs derived from rs-fMRI data for NDD prediction. MHNet has two branches: the Euclidean Space Features Extraction (ESFE) module and the Non-Euclidean Space Features Extraction (Non-ESFE) module, followed by a Feature Fusion-based Classification (FFC) module for NDD identification. ESFE includes a Functional Connectivity Generation (FCG) module and a High-order Convolutional Neural Network (HCNN) module to extract local and high-order features from BFNs in Euclidean space. Non-ESFE comprises a Generic Internet-like Brain Hierarchical Network Generation (G-IBHN-G) module and a High-order Graph Neural Network (HGNN) module to capture topological and high-order features in non-Euclidean space. Experiments on three public datasets show that MHNet outperforms state-of-the-art methods using both AAL1 and Brainnetome Atlas templates. Extensive ablation studies confirm the superiority of MHNet and the effectiveness of using multi-view fMRI information and high-order features. Our study also offers atlas options for constructing more sophisticated hierarchical networks and explains the association between key brain regions and NDD. MHNet leverages multi-view feature learning from both Euclidean and non-Euclidean spaces, incorporating high-order information from BFNs to enhance NDD classification performance.
Polynomial reduction from syndrome decoding problem to regular decoding problem
Authors: Zajac Pavol
Published: January 2025

The regular decoding problem asks for (the existence of) regular solutions to a syndrome decoding problem (SDP). This problem has increased applications in post-quantum cryptography and cryptanalysis. Recently, Esser and Santini explored in depth the connection between the regular (RSD) and classical syndrome decoding problems. They have observed that while RSD to SDP reductions are known (in any parametric regime), a similar generic reduction from SDP to RSD is not known. In our contribution, we examine two different generic polynomial reductions from a syndrome decoding problem to a regular decoding problem instance. The first reduction is based on constructing a special parity check matrix that encodes weight counter progression inside the parity check matrix, which is then the input of the regular decoding oracle. The target regular decoding problem has a significantly longer code length, that depends linearly on the weight parameter of the original SDP. The second reduction is based on translating the SDP to a non-linear system of equations in the Multiple Right-Hand Sides form, and then applying RSD oracle to solve this system. The second reduction has better code length. The ratio between RSD and SDP code length of the second reduction can be bounded by a constant (less than 8).
Drill Pattern Optimisation for Large Complex Blasts to Improve Fragmentation and Dig Efficiency
Authors: Perincek Ozan , Loxton Ryan , Kulkarni Sarang , Arthur Daniel
Published: January 2025

At large-scale open-pit metallic mines, drill-and-blast designs can reach over 1,000 drill holes per blast. A critical input to the design of a blast is the location of sensitive zones where ground vibration, air overpressure or flyrock needs to be constrained. The other critical input is the hardness profile of the ground. Often, the hardness across such large blasts varies significantly from soft to extra hard. Traditional approaches for pattern design use constant distance (burden and spacing) between the production drill holes and vary the explosive product strength and amount in each hole to account for variation in hardness and to adhere to blast constraints. Although this approach is operationally easier to execute, it is challenging to meet fragmentation and diggability objectives. To better address these objectives, this work provides a nonlinear mathematical model for optimising drill hole locations in conjunction with explosive amounts. The model optimises the design using a three-stage methodology. In the first stage, a novel heuristic method is used to perform local optimisation to determine the number of holes. In the second stage, the precise hole locations are determined, and in the third stage the energy intensity in each hole is optimised. In a study of 10 blasts from a Pilbara iron ore mine, for the dig efficiency objective, results indicate that variable designs achieve

$$\sim $$

∼

2% better dig efficiency, with

$$\sim $$

∼

11% fewer holes. For the fragmentation objective, variable designs achieve

$$\sim $$

∼

9% better adherence to the target mean particle size, with

$$\sim $$

∼

5% less standard deviation and

$$\sim $$

∼

13% fewer holes.
Longitudinal relationships across sleep, physical activity, and mental wellbeing in early-to-mid-adolescence: a developmental cascades investigation
Authors: Marquez Jose , Panayioutou Margarita , Farzinnia Reihaneh , Cheng Qiqi , Humphrey Neil
Published: January 2025

Purpose

Sleep (SL), physical activity (PA), and wellbeing (WB) are three factors linked to positive development in adolescence. Despite theoretical support and some empirical evidence of developmental associations between these factors, few studies have rigorously investigated reciprocal associations over time separating between-person and within-person effects, and none have investigated all three in concert. Thus, it remains unclear how the interplay between SL, PA and WB unfolds across time within individuals. This study examines this question in the crucial early-to-mid-adolescence developmental transition.

Method

Separating between- and within-person effects, a random-intercept cross-lagged panel model was fitted to a dataset of N = 27,949 adolescents (age 12/13 at first timepoint) from Greater Manchester, England, using a three-by-three design (three annual timepoints: T1, T2, T3; three variables: SL, PA, WB).

Results

Analyses revealed gender-specific developmental cascade pathways. Specifically, we found positive reciprocal associations between SL and WB for girls (at T1→T2), whereas for boys, SL positively predicted WB (at both T1→T2 and T2→Τ3) but WB did not predict SL. We also found that WB predicted PA for boys (at T2→T3) but this finding was sensitive to model specification and yielded a smaller effect than other cross-lagged pathways.

Conclusion

Our results highlight the importance of sleep as a driver of adolescent wellbeing, and the role of gender in developmental cascade processes. Study strengths, limitations, and implications are discussed.
Concentration versus excellence: lessons learned of European R&D &I framework programs
Authors: Kosztyán Zsolt T. , Hausz Frigyes , Csizmadia Tibor , Katona Attila , Szabó István , Fehérvölgyi Beáta
Published: January 2025

Framework programs (FPs) are the main research policy tools of the European Union (EU), attracting substantial attention from policy-makers and scholars. Therefore, an increasing number of studies have investigated the EU’s FPs from various angles; however, very few studies address the effect of the complex nature of the concentration of resources and their implementation. While several studies have examined the concentrations of collaboration structures, much less attention has been given to institutions, especially the concentrations that appear during implementation. Institutions that have been awarded several projects at the same time are forced to share their resources between the running projects, which can make the implementation of the projects riskier and thus jeopardize the project’s outcome. Therefore, the role of project management, which must allocate resources among complex implementation structures, such as multiprojects and programs, across portfolios, is appreciated. The aim of this study was to analyze the progression of the nature of concentration, such as institutional concentration in the four most recent framework programs (FPs), namely, FP5, FP6, FP7, and Horizon 2020 (H2020), and the structural and implementation concentrations in the last two framework programs. The study employed the CORDIS database, which encompasses both institutional and project-related information derived from four distinct framework programs. The findings indicated that the parameters of the collaboration network exhibited minimal changes; however, the concentrations of institutions experienced significant alterations. The concentration of complex project structures increased along with institutional concentration, which in turn led to greater efficiency and productivity and, in this way, excellence. Hence, it can be inferred that the output-increasing effect of the program structure is undermined in the deployment of other implementation structures by the need to share resources among several projects running in parallel. The strategy of using parallel projects involves inherent hazards because of the finite nature of resources, which consists primarily of human talent in the form of researchers. The results currently support policy-makers in three ways: (1) an improved understanding of how implementation structures evolve in EU-funded Framework Programs; (2) strengthened linkages among institutional concentration, productivity and excellence; and (3) insights into the design of the EU FP ecosystem.
Individual and classroom-level associations of within classroom friendships, friendship quality and a sense of peer community on bullying victimization
Authors: Kloo Mattias
Published: January 2025

For most students, attending school entails daily intense social interactions with classmates in a classroom context. While many of these interactions are positive and lead to the development of friendships and a shared classroom community, some students instead suffer peer harassment and bullying. According to the social-ecological theory these disparate social phenomena may be linked. The aim of this study was to examine how number of friends, perceived friendship quality, and a sense of peer community were associated with bullying victimization at both the individual and classroom level. Additionally, to thoroughly investigate the nuances of different types of friendship qualities the concept was analyzed both as one unified construct and as five distinct dimensions (companionship, conflict, help, security, and closeness). Survey data from 587 Swedish upper elementary school students (56.22% girls; M
age = 11.72, SD = 0.96) across 54 classrooms was collected and analyzed using multilevel regression. Results showed that having at least one friend was negatively associated with victimization and that victimization was less prevalent in classrooms where students experienced a shared sense of community. Furthermore, while high-quality friendships were associated with less victimization at both the individual and classroom level, when the five dimensions where considered, only conflictual and helpful friendships were significantly associated with victimization (on both levels of analysis for conflictual friendships and only on the individual level for helpful friendships). Together these results highlights the importance of schools helping students cultivate high-quality friendships, teaching constructive conflict management and promoting a more prosocial classroom community.
How many bees fit in the city? A spatial ecological case study to conserve urban wild bees
Authors: Lanner J. , Unglaub P , Rohrbach C. , Pachinger B. , Roberts S. , Kratschmer S.
Published: January 2025

Pollination is crucial for biodiversity and food security, with bees playing a significant role. The growing popularity of urban beekeeping is leading to increasing honeybee densities in cities, raising concerns about competition for pollen and nectar with wild bees due to limited foraging resources in densely urbanized areas. To assess the current bee occurrences of wild and honeybees in urbanized and protected areas of a Central European city, we focused on the ecological similarities between honeybees and wild bees. We compiled an inventory of 462 wild bee species documented since 1990 in Vienna (Austria) and conducted a survey of apiary locations in cooperation with beekeepers. We calculated apiary densities and indices for species richness, rarity, and, based on flower-visiting traits, the trait similarity between honeybees and wild bees. We found that approximately four times more honeybee colonies were kept in central Vienna in 2023 than the habitat may support. In parts of Vienna’s nature conservation areas, the number of colonies also exceeded the density of 3.5 colonies per km² recommended by the literature. Results indicate a significant spatial overlap of high apiary densities and wild bee hotspots, particularly in urban nature conservation areas like Natura 2000 protected areas. In Natura 2000 areas, the trait similarity of rare wild bee species was significantly increased, indicating a potential elevated competition between wild bees and honeybees for floral resources. This study highlights the need for spatial planning to balance urban beekeeping and wild bee conservation, recommending actions to match habitat quality to apiary densities to mitigate competitive pressures.
Weight censorial score: estimation of the weight loss during concurrent chemo-radiotherapy in nasopharyngeal carcinoma patients by image features predicts prognosis
Authors: Sun Jiachen , Lam Sai Kit Edmond , Zhang Jiang , Teng Xinzhi , Lee Francis Kar-ho , Yip Celia Wai-yi , Chow James Chung Hang , Lee Victor Ho Fun , Sun Ying , Cai Jing
Published: January 2025

Purpose

Bodyweight loss is commonly found in Nasopharyngeal Carcinoma patients during Concurrent Chemo-radiotherapy (CCRT) and has implications for treatment decisions. However, the prognostic value of this weight loss remains uncertain. We addressed it by proposing a novel index Weight Censorial Score (WCS) that characterizes the patient-specific CCRT response on actual to estimated weight loss.

Methods

A retrospective study included 315 patients from two independent hospitals. An Estimated WCS (eWCS) was obtained through linear regression of image and dosimetry features. The eWCS was converted to an estimated net weight loss (nWL), with its accuracy evaluated. The Determined WCS (dWCS) was calculated by centering and scaling the post-RT actual nWL with patient’s pre-RT body information. The ratio of dWCS to eWCS (WCS ratio) reflected the actual to estimated weight loss of a patient. The prognostic ability of WCS ratio dichotomized at 1 was evaluated.

Results

The mean absolute error of estimated to actual nWL was 1.84 kg. Patients who had their actual WL larger than estimated WL were found to have significantly worse OS (p = 0.005, HR = 3.35[1.45–7.73]), PFS (p = 0.038, HR = 1.86[1.03–3.35]), and DMFS (p = 0.050, HR = 2.20[1.00–4.85]), respectively, in multivariable cox analysis. They were also found not to benefit from adjuvant chemotherapy (p = 0.572), whereas the adjuvant chemotherapy provided significant PFS benefit in patients with actual WL smaller than estimated WL (p = 0.036, HR = 0.53[0.29–0.96]).

Conclusion

The nWL of patient during CCRT can be reasonably estimated by dosimetry factors at pre-RT stage. The prognostic value of the actual to expected weight loss holds promise for highlighting vulnerable patients after CCRT.
Description of STRIVE-ON Study Protocol: Safety and Tolerability of GTX-104 (Nimodipine Injection for IV Infusion) Compared with Oral Nimodipine in Patients Hospitalized for Aneurysmal Subarachnoid Hemorrhage (aSAH): A Prospective, Randomized, Phase III Trial (STRIVE-ON)
Authors: Choi Alex H. , Chou Sherry Y. , Ducruet Andrew F. , Kimberly W. Taylor , Loch Macdonald R. , Rabinstein Alejandro A.
Published: January 2025

Oral nimodipine is the only drug approved in North America for patients with aneurysmal subarachnoid hemorrhage (aSAH). However, bioavailability is variable and frequently poor, leading to fluctuations in peak plasma concentrations that cause dose-limiting hypotension. Furthermore, administration is problematic in patients who cannot swallow. An oral liquid formulation exists but causes diarrhea. An intravenous nimodipine formulation (GTX-104) has been developed that has bioavailability approaching 100% and is not affected by feeding or gastrointestinal absorption. GTX-104 causes less hypotension and has more consistent peak plasma concentrations than oral nimodipine in human volunteers. Herein, we describe the protocol of a prospective, randomized, open-label safety, and tolerability study of GTX-104 compared with oral nimodipine in patients with aSAH (Safety and Tolerability of GTX-104 [Nimodipine Injection for Intravenous Infusion] Compared with Oral Nimodipine; ClinicalTrials.gov identifier: NCT05995405). The study is designed to seek approval of GTX-104 by the Food and Drug Administration 505(b)(2) pathway. Inclusion and exclusion criteria match the prescribing information for oral nimodipine and include adult patients with aSAH of all Hunt and Hess grades who can receive investigational product within 96 h of aSAH. Study participants at imminent risk of death will be excluded. Study participants will be randomly assigned 1:1 to receive GTX-104 or oral nimodipine for up to 21 days. The primary end point is the proportion of study participants with clinically significant hypotension, defined as hypotension requiring treatment that has a reasonable likelihood of being due to investigational product as determined by an independent, blinded end point adjudication committee. No statistical analysis of the end point is planned. Secondary end points include all episodes of hypotension, all adverse events, delayed cerebral ischemia, rescue therapy, and suicidal ideation. Clinical and health economic outcomes include quality of life using the EuroQol 5-dimension/3-level, modified Rankin Scale score at 30 and 90 days after aSAH and hospital resource use. The planned sample size is 100 study participants across 25 sites in the United States and Canada.
Does Imagination Justify the Belief that Supra-Persons Are Physically Possible?
Authors: Dragomir Alexandru , Rusu Mihai
Published: January 2025

Human enhancement technologies offer prospects for improving the mental capacities that are typically considered to ground moral status. Bioethicists, posthumanists and transhumanists have raised the worry that the radical enhancement of our moral status-relevant capacities is open to the possibility of creating supra-persons. The worry is that supra-persons would further reduce the moral inviolability of mere persons. If the possibility is plausible, then radical enhancement would put mere persons at risk. In order to assess the plausibility of possibility claims, epistemologists have investigated the role of imagination in justifying our beliefs about what is possible. Philosophy has abounded with imaginability arguments for various entities like zombies, experience machines, super-spartans, and perfect actors. The aim of this paper is to investigate a newcomer in the bestiary of bioethics, the supra-person, using the utensils of imaginability-based modal epistemology. We will argue for an epistemic claim: that no imaginative act is sufficient to justify the belief that supra-persons are possible. In order to support our thesis, we will employ two influential accounts of the relation between imaginative acts and acquiring justification for beliefs about what is possible.
Automated design of state transition rules in ant colony optimization by genetic programming: a comprehensive investigation
Authors: Lin Bo-Cheng , Mei Yi , Zhang Mengjie
Published: January 2025

The automated design of Ant Colony Optimization (ACO) algorithms has become increasingly significant, particularly in addressing complex combinatorial optimization problems. Although existing methods have achieved some success, they still face limitations, particularly the high dependency on expert knowledge, pre-solved data, and challenges in interpretability. Genetic Programming (GP), as a proven technology, has shown potential in optimizing the automated design state transition rules of ACO. However, existing research on GP-ACO is insufficient, particularly in terms of experimental validation and systematic evaluation. To address these issues, this study conducts comprehensive experiments to explore several key questions: the generality of GP-ACO on homogeneously distributed maps, the impact of different ACO variants on the learning capabilities of GP-ACO, the effect of 2-opt local search on the learning capabilities of GP-ACO, the enhancement of learning capabilities through the addition of more global information, and the interpretability of GP-ACO. The findings indicate that GP-ACO exhibits robust generality; variations among ACO variants have minimal impact on learning performance; 2-opt local search can somewhat diminish the performance of GP-ACO in the Max–Min Ant System; additional global information can significantly enhance the learning capabilities of GP-ACO; and GP-ACO has good interpretability.
Effects of Combined Utilization of Active Cooler/Heater and Blade-Shaped Nanoparticles in Base Fluid for Performance Improvement of Thermoelectric Generator Mounted in Between Vented Cavities
Authors: Selimefendigil Fatih , Oztop Hakan F.
Published: January 2025

A wide range of technical applications, including solar power, waste heat recovery, electronics thermal management, and heat exchangers, employ thermoelectric generators. They can be mounted in between channels / cavities where hot and cold fluid streams exist. In this study, two novel methods of enhancing the power generation from thermoelectric generator device mounted in between vented cavities are proposed by combined utilization of active heater/cooler rectangular blocks and blade-shaped nanoparticles in base fluid. Finite element method investigation is conducted numerically for a range of hot and cold stream Reynolds numbers (250–1000), non-dimensional hot and cold block sizes (0.01

$$-$$

-

0.4), and heating/cooling increments (0–10), with nanoparticle loading limited to 0.03. Higher values of Reynolds number results in a rise in thermoelectric generator power. When comparing the cases of lowest and highest Reynolds number combinations, a 219

$$\%$$

%

increase in power is achieved. The thermoelectric generator power will rise by around 27.5

$$\%$$

%

when the object size reaches its maximum. However, for moderate object sizes, up to 31.6

$$\%$$

%

reduction in power generation can be realized. Greater temperature differences result in a linearly rising power generation, with an achievable power increase of up to 22

$$\%$$

%

. When nanoparticle loading in the base fluid for both cavities is raised to its maximum value, the resultant power increases by around

$$30\%$$

30
%

. Thermoelectric generator power rises by 67.8

$$\%$$

%

when an active heater/cooler with nanofluid is used in vented cavities, as opposed to the reference scenario of employing no object and only water. The thermoelectric generator device’s hot and cold interface temperatures are accurately estimated using the artificial neural network based method. The estimated temperature can be used as boundary condition for the solution of the governing equations in the thermoelectric generator device domain which will decrease the computational cost when dealing with very complex channel configurations.
Multi-objective optimization for layout planning of matrix manufacturing system
Authors: Park Jisoo , Lee Changha , Oh Seog-Chan , Do Noh Sang
Published: January 2025

The automotive industry is experiencing rapid changes due to the rise of the Industry 4.0 manufacturing paradigm, which requires strategic implementation of advanced manufacturing systems to meet diverse customer needs. The Matrix Manufacturing System, characterized by modular facilities and autonomous mobile robots, offers greater flexibility compared to traditional dedicated production systems. This paper conducts a multi-objective optimization of facility layout planning within the matrix manufacturing system to enhance efficiency and responsiveness to market volatility. To solve the optimization problem, three heuristic algorithms—Simulated Annealing, Particle Swarm Optimization, and Non-dominated Sorting Genetic Algorithm-II are employed and their performance is compared. For the comparative analysis, frequency maps are used, visualizing the optimization processes and outcomes between metaheuristic algorithms. The framework with methodologies presented in this report is expected to improve productivity and flexibility of a matrix manufacturing system in the automotive industry.
Delay Discounting of Monetary Outcomes by Justice-Involved Male Adolescents and College Students
Authors: Brogan Kristen M. , Rapp John T. , Newland M. Christopher
Published: January 2025

Delay discounting of hypothetical monetary outcomes by justice-involved youth adolescents was compared to that of college students to lay a foundation for future discounting work with justice-involved youth. We administered a hypothetical monetary delay-discounting task to three groups: (1) justice-involved adolescent males; (2) college student males; and (3) college student females. Using nonlinear regression, we fit the exponential, hyperbolic, and hyperboloid models to each data set both individually and at the group level. We determined the best fitting model for individual data sets and group data using the Information-Theoretic approach to model comparisons. For group averages, a hyperbolic model was slightly better than hyperboloid for justice-involved youth and college males, but the hyperboloid model was marginally better for college females. The evidence for any one model was modest to marginal, however. There was considerable variability in which model fit individual data best within all groups, each model being best for some participants. Regardless of the model, justice-involved youth discounted delayed monetary outcomes much more steeply than college males or females. The last two groups did not differ from each other. Two limitations can be noted. The mode for delivering the discounting tasks was different for the justice-involved youth as compared with the college students, an accommodation to the COVID-19 pandemic. Discounting functions from many justice-involved youth had to be discarded because of poor control by delay to the larger-later option. Findings from this study will inform future work on delay discounting by justice-involved youth and may help to inform treatment of this population in the future.
Additive Manufacturing of Ni–Ti SMA by the Sinter-Based MoldJet Method
Authors: Addess Alon , Shilo Doron , Glass Boaz , Paskovitch Yael , Burkhardt Carlo , Vogel Lucas , Rabkin Eugen , Faran Eilon
Published: January 2025

Additive Manufacturing (AM) of Shape Memory Alloys (SMA), and specifically Ni–Ti alloys, is an evolving field with significant potential to applications in actuation, energy harvesting, and refrigeration. Sinter-based AM technologies show promise in tailoring and controlling the microstructure and properties of Ni–Ti, because the metal particles remain in the solid-state throughout the process. Here, we report on the manufacturing and characterization of Ni–Ti produced using a novel sinter-based MoldJet method: a wax-based mold is deposited layer-by-layer using jet-printing, and its cavities are simultaneously filled with metallic paste. This additive process produces a green body that is sintered to form a dense metal part. The low content of organic binder in the metallic paste results in reduced carbon and oxygen contamination compared to other sinter-based AM methods. Consequently, the reduced formation of carbides and oxides enhances the thermomechanical properties. Here, we show that Ni–Ti produced via MoldJet exhibits a superelastic response with a substantial recoverable strain of 5.6% in tension and 4.5% in compression, and irrecoverable plastic strain below 0.2%. The results indicate that MoldJet is a promising method for AM of Ni–Ti for advanced applications. Specifically, we show that the obtained material properties are adequate for elastocaloric cooling devices.
Millingtonia hortensis L.f. (tree jasmine): botany, ethnopharmacology, chemical constituents, biological activities of extracts and essential oils—an updated review
Authors: Ashokkumar Kaliyaperumal , Murugan Muthusamy , Murugesan P. , Venkatesh Thangaraj
Published: January 2025

Millingtonia hortensis is extensively grown for decorative purposes due to its beautiful flowers and fragrant characteristics. Millingtonia hortensis is an unexplored plant for utilization of its chemical constituents for therapeutic applications. Therefore, the present review thoroughly analyzes the botanical features, chemical composition, and biological and pharmacological effects of M. hortensis essential oil (MHEO) and extracts. This review employed the leading scientific databases Google Scholar, Scopus, Web of Science, and PubMed between 2013 and the end of September 2024 and combined terms, Millingtonia hortensis, Botany, essential oil, phytochemistry and pharmacological activity. The MHEO yield varied between 0.02 and 3.57%. The main constituents of M. hortensis extract and essential oil include solanesol (25.7%), trans-farnesol (19.7%), and nerolidol (8.2%). MHEO and its active chemical constituents exhibit various biological capabilities, such as antioxidant, antimicrobial, anticancer, anti-inflammatory, and larvicidal, among other activities. However, several biological and pharmacological investigations lacked appropriate experimental settings, such as proper doses and positive and negative controls. Furthermore, many pharmacological investigations were exclusively carried out utilizing cell lines and animal models. Thus, this study suggested that further research investigations should be carried out in a proper scientific experimental setting to perform MHEO on human patients. This would broaden its scope of use in the pharmaceutical industry.
Initial stage of crusted scabies and possible diagnostic characteristics: A case series
Authors: Li Wanchen , Song Lin , Guo Tao , Wu Yaliu , Li Xiaoli , Li Hongfeng , Li Jianjun , Li Simiao
Published: January 2025

Scabies is a neglected tropical disease caused by the ectoparasitic mite, Sarcoptes scabiei var. hominis (S. scabiei). Common scabies, the most prevalent clinical subtype of scabies, is characterized by pruritus, multiple skin lesions and low mite burden. In contrast, crusted scabies, an extremely contagious variant, is characterized by hyperkeratosis and high mite burden, with or without pruritus. Scabies can be diagnosed based on clinical manifestations, with confirmation obtained through microscopic identification of diagnostic features of S. scabiei. However, owing to the diversity and non-specific nature of its clinical manifestations and insufficient knowledge regarding early-stage clinical manifestations, the diagnosis of crusted scabies continues to be delayed. Herein, we present three cases of scabies with varying degrees of crusting and mite burden. Three patients with physical and microscopic results suggesting scabies were selected for this study. Case 1 had mild crusting and low mite burden, case 2 had severe crusting and high mite burden and case 3 had mild crusting and high mite burden. In this case report, ‘the initial stage of crusted scabies’ refers to the progression from common to crusted scabies. The discussion regarding the diagnostic characteristics of the initial stage of crusted scabies is expected to aid the early diagnosis of crusted scabies.
Defining variances in practice for use of electrophysiology studies in risk stratification of patients with repaired tetralogy of Fallot: a PACES survey
Authors: Haththotuwegama Kishanee J. , Wu Sarah Z. , Anderson Charles C.
Published: January 2025

Sudden cardiac death poses a significant risk in patients with surgically repaired tetralogy of Fallot. Despite extensive research, risk stratification practices vary. This study surveyed the Pediatric and Adult Congenital Electrophysiology Society to identify these differences. Results showed diverse practices in indications, methods, and interpretation of electrophysiology studies, highlighting a need for standardised algorithms to improve patient outcomes.
Successful biventricular repair following strategic treatment focused on left ventricular growth in a patient with hypoplastic left heart complex and unbalanced right dominant atrioventricular septal defect: a case report
Authors: Araki Kanta , Kagisaki Koji , Ozawa Hideto
Published: January 2025

A patient with borderline left ventricle successfully underwent biventricular repair following a staged surgical approach to promote left ventricular growth. Despite initial concerns about left ventricle size, apex formation and adequate size of atrioventricular valve indicated potential for future growth. The patient demonstrated significant left ventricular growth, resulting in stable biventricular circulation and a favourable outcome over a three-year postoperative follow-up period.

Clinical Registration Number: Institutional Review Board of Osaka City General Hospital, number 1902139.
The Role of Secondary Recoil Leaders in the Formation of Subsequent Return Strokes
Authors: Cruz Ivan T. , Saba Marcelo M. F. , Silva José Claudio O. , Schumann Carina
Published: January 2025

Recoil leaders develop in lightning flash decayed channels. The propagation of a recoil leader depends on the charges stored at its tip and the conductivity of the decayed channel. When the recoil leader propagates over the entire channel, a subsequent return stroke happens. Recoil leaders very often cease propagating before they reach the ground, that is, only part of the decayed channel is reionized. The present work aims to analyze the herein named secondary recoil leader that connect with the primary recoil leaders and cause them to start propagating again. We believe that the secondary recoil leader injects additional charge into the primary recoil leader, allowing the recoil leader reionize the whole decayed channel of the lightning flash. High‐speed videos analysis of upward lightning flashes shows that secondary recoil leaders play an important role on the formation and progression of dart leaders/subsequent return strokes.
A Fluid Flow‐Based Deep Learning (FFDL) Architecture for Subsurface Flow Systems With Application to Geologic CO2 Storage
Authors: Qin Zhen , Liu Yingxiang , Zheng Fangning , Jafarpour Behnam
Published: January 2025

Prediction of the spatial‐temporal dynamics of the fluid flow in complex subsurface systems, such as geologic storage, is typically performed using advanced numerical simulation methods that solve the underlying governing physical equations. However, numerical simulation is computationally demanding and can limit the implementation of standard field management workflows, such as model calibration and optimization. Standard deep learning models, such as RUNET, have recently been proposed to alleviate the computational burden of physics‐based simulation models. Despite their powerful learning capabilities and computational appeal, deep learning models have important limitations, including lack of interpretability, extensive data needs, weak extrapolation capacity, and physical inconsistency that can affect their adoption in practical applications. We develop a Fluid Flow‐based Deep Learning (FFDL) architecture for spatial‐temporal prediction of important state variables in subsurface flow systems. The new architecture consists of a physics‐based encoder to construct physically meaningful latent variables, and a residual‐based processor to predict the evolution of the state variables. It uses physical operators that serve as nonlinear activation functions and imposes the general structure of the fluid flow equations to facilitate its training with data pertaining to the specific subsurface flow application of interest. A comprehensive investigation of FFDL, based on a field‐scale geologic storage model, is used to demonstrate the superior performance of FFDL compared to RUNET as a standard deep learning model. The results show that FFDL outperforms RUNET in terms of prediction accuracy, extrapolation power, and training data needs.
Semi-mechanistic efficacy model for PARP + ATR inhibitors—application to rucaparib and talazoparib in combination with gartisertib in breast cancer PDXs
Authors: Villette Claire C. , Dupuy Nathalie , Brightman Frances A. , Zimmermann Astrid , Lignet Floriane , Zenke Frank T. , Terranova Nadia , Bolleddula Jayaprakasam , El Bawab Samer , Chassagnole Christophe
Published: January 2025

Background

Promising cancer treatments, such as DDR inhibitors, are often challenged by the heterogeneity of responses in clinical trials. The present work aimed to build a computational framework to address those challenges.

Methods

A semi-mechanistic pharmacokinetic-pharmacodynamic model of tumour growth inhibition was developed to investigate the efficacy of PARP and ATR inhibitors as monotherapies, and in combination. Key features of the DNA damage response were incorporated into the model to allow the emergence of synthetic lethality, including redundant DNA repair pathways that may be impaired due to genetic mutations, and due to PARP and ATR inhibition. Model parameters were calibrated using preclinical in vivo data for PARP inhibitors rucaparib and talazoparib and the ATR inhibitor gartisertib.

Results

The model successfully captured the monotherapy efficacies of rucaparib and talazoparib, as well as the combination efficacy with gartisertib. The model was evaluated against multiple tumour xenografts with diverse genetic backgrounds and was able to capture the observed heterogeneity of response profiles.

Conclusions

By enabling simulation of in vivo tumour growth inhibition with PARP and ATR inhibitors for specific tumour types, the model provides a rational approach to support the optimisation of dosing regimens to stratified populations.
Nucleophilicity at copper(-I) in a compound with a Cu–Mg bond
Authors: Jackson Ross A. , Evans Nicholas J. , Babula Dawid J. , Horsley Downie Thomas M. , Charman Rex S. C. , Neale Samuel E. , Mahon Mary F. , Liptrot David J.
Published: January 2025

Copper is ubiquitous as a structural material, and as a reagent in (bio)chemical transformations. A vast number of chemical reactions rely on the near-inevitable preference of copper for positive oxidation states to make useful compounds. Here we show this electronic paradigm can be subverted in a stable compound with a copper-magnesium bond, which conforms to the formal oxidation state of Cu(-I). The Cu-Mg bond is synthesized by the reaction of an N-heterocyclic carbene (NHC) ligated copper alkoxide with a dimeric magnesium(I) compound. Its identity is confirmed by single-crystal X-ray structural analysis and NMR spectroscopy, and computational investigations provide data consistent with a high charge density at copper. The Cu-Mg bond acts as a source of the cupride anion, transferring the NHC-copper fragment to electrophilic s-, p-, and d-block atoms to make known and new copper-containing compounds.
Ferromagnetic Fe-TiO2 spin catalysts for enhanced ammonia electrosynthesis
Authors: Wang Jingnan , Zhao Kaiheng , Yao Yongbin , Xue Fan , Lu Fei , Yan Wensheng , Yuan Fangli , Wang Xi
Published: January 2025

Magnetic field effects (MFE) of ferromagnetic spin electrocatalysts have attracted significant attention due to their potential to enhance catalytic activity under an external magnetic field. However, no ferromagnetic spin catalysts have demonstrated MFE in the electrocatalytic reduction of nitrate for ammonia (NO3RR), a pioneering approach towards NH3 production involving the conversion from diamagnetic NO3
− to paramagnetic NO. Here, we report the ferromagnetic Fe-TiO2 to investigate MFE on NO3RR. Fe-TiO2 possesses a high density of atomically dispersed Fe sites and exhibits an intermediate-spin state, resulting in magnetic ordering through ferromagnetism. Assisted by a magnetic field, Fe-TiO2 achieves a Faradaic efficiency (FE) of up to 97% and an NH3 yield of 24.69 mg mgcat
−
1 at −0.5 V versus reversible hydrogen electrode. Compared to conditions without an external magnetic field, the FE and NH3 yield for Fe-TiO2 under an external magnetic field is increased by ~21.8% and ~ 3.1 times, respectively. In-situ characterization and theoretical calculations show that spin polarization enhances the critical step of NO hydrogenation to NOH by optimizing electron transfer pathways between Fe and NO, significantly boosting NO3RR activity.
A travelable area boundary dataset for visual navigation of field robots
Authors: Zhang Kai , Yuan Xia , Xu Jiachen , Wang Kaiyang , Wu Shiwei , Zhao Chunxia
Published: January 2025

Travelable area boundaries not only constrain the movement of field robots but also indicate alternative guiding routes for dynamic objects. Publicly available road boundary datasets have outlined boundaries by binary segmentation labels. However, hard post-processes have to be done to extract from detected boundaries further semantics including the shapes of the boundaries and guiding routes, which poses challenges to a real-time visual navigation system without detailed prior maps. In addition, boundary detectors suffer from insufficient data collected from complex roads with severe occlusion and of different shapes. In this paper, a travelable area boundary dataset is semi-automatically built. 82.05% of the data is collected from bends, crossroads, T-shape roads and other irregular roads. Novel guiding semantics labels, shape labels and scene complexity labels are assigned to boundaries. With the support of the new dataset, travelable area boundary detectors could be trained, evaluated and fairly compared. The dataset can also be used to train, evaluate or test detectors for the road boundary detection task.
Dataset for developing deep learning models to assess crack width and self-healing progress in concrete
Authors: Jakubowski Jacek , Tomczak Kamil
Published: January 2025

The presented dataset comes from an experimental study on the autogenous self-healing of high-strength concrete and the development of deep learning metasensor for crack width assessment and self-healing evaluation. Concrete specimens were prepared, matured, cracked, and exposed to self-healing. High-resolution scanning of the specimen surface and scale-invariant image processing were performed, multiple grid lines crossing cracks were established, and brightness degree profiles along grid lines were extracted. Then, reference measurements of the crack widths were obtained by an operator. The dataset comprises 19,098 records of brightness profiles, reference measurements, and benchmark measurements by deep learning and analytic models. The source images, stacked and marked with grid lines, are provided. The considerable number of brightness profiles coupled with manual reference measurements make the dataset well suited for developing an image-based deep CNN models or analytic algorithms for assessing crack widths in concrete. The technical validation study explored three factors that affect crack measurement: the specimen position in relation to the scanner, the surface moisture level, and the operator performing manual measurements.