bluuebunny/crossref_metadata_2025 huggingface dataset:
An analysis of fog and low stratus life‐cycle regimes over central Europe
Authors: Pauli Eva , Cermak Jan , Andersen Hendrik , Fuchs Julia
Published: March 2024

A better understanding of fog and low stratus (FLS) life cycles, in particular the typical onset and dissipation times, can help traffic safety and solar power planning. Besides its high dependence on the prevalent meteorological conditions, the FLS life cycle is further determined by the FLS type as well as the underlying geography and climate. While satellite‐based FLS data sets with high temporal and spatial resolution are available, an objective, large‐scale, satellite‐based classification of FLS life‐cycle regions, which would allow for more targeted analyses of the FLS life cycle, is lacking. In this study, a hierarchical clustering algorithm is applied to identify regions of similar relationships of the FLS life cycle to environmental conditions over central Europe. The clustering reveals major FLS life‐cycle regimes with distinct differences in FLS occurrence, temporal FLS life‐cycle patterns, and climatic characteristics. Based on regime‐specific sensitivity analyses, the relationships of the FLS life cycle with near‐ground temperature and specific humidity are identified as the most relevant input relationships for the clustering algorithm, especially in the Mediterranean region. FLS life‐cycle regimes are further presented at a regional scale, outlining the applicability of the derived FLS life‐cycle regimes to future regional process‐oriented FLS life‐cycle studies.
eRPCA: Robust Principal Component Analysis for Exponential Family Distributions
Authors: Zheng Xiaojun , Mak Simon , Xie Liyan , Xie Yao
Published: March 2024

Robust principal component analysis (RPCA) is a widely used method for recovering low‐rank structure from data matrices corrupted by significant and sparse outliers. These corruptions may arise from occlusions, malicious tampering, or other causes for anomalies, and the joint identification of such corruptions with low‐rank background is critical for process monitoring and diagnosis. However, existing RPCA methods and their extensions largely do not account for the underlying probabilistic distribution for the data matrices, which in many applications are known and can be highly non‐Gaussian. We thus propose a new method called RPCA for exponential family distributions (), which can perform the desired decomposition into low‐rank and sparse matrices when such a distribution falls within the exponential family. We present a novel alternating direction method of multiplier optimization algorithm for efficient decomposition, under either its natural or canonical parametrization. The effectiveness of is then demonstrated in two applications: the first for steel sheet defect detection and the second for crime activity monitoring in the Atlanta metropolitan area.
Facile and Rapid Synthesis of Gold Nanoparticles on Unconventional Imine‐ Decorated Silica
Authors: Mohanapriya N. , Chandrasekaran Naveen
Published: March 2024

We demonstrate the reduction of gold (Au) on silica monoliths by surface decoration of amine and imine (formed by reaction of amine present in 3‐amino propyl triethoxy silane (APTES) and acetone) functionalities on the surface of silica. The reduction of Au3+ to Au0 was confirmed by X‐ray diffraction (XRD), UV‐Diffuse reflectance and X‐ray Photo electron spectroscopic techniques. Without employing the conventional strategies with reducing agents like sodium borohydride and sodium citrate, here, the surface functionalized amine and imine was found to reduce the metal ions, additionally, the surface silanols was found to anchor and serve as the adsorption sites to hold the metal ions prior to reduction. The control experiment was performed with silica monoliths without the surface functionalities displayed no evident reduction of Au3+ to their respective metallic form. Interestingly, the reduction of Au was found to be more facile on imine modified silica, due to the strong electrostatic interaction of highly polarized imine with Au3+ ions.
Co−Fe‐based Heterometallo‐Supramolecular Polymer for Non‐Enzymatic Electrochemical Nitrite Detection and the Study of Electron Transfer Kinetics
Authors: Akter Riva , Mia Md. Mithu , Awal Abdul , Hossain Md. Delwar , Ahammad A. J. Saleh
Published: March 2024

Here, we report the fabrication of Heterometallo‐supramolecular polymer (H‐SMP) for the selective oxidation of nitrite with the investigation of some kinetic parameters by the complex formation of Co(II) and Fe(II) salts with the symmetrical ligand which is composed of terpyridine moieties specially referred to as [4′,4′′′′‐(1,4‐Phenylene)bis(2,2′:6′,2′′‐terpyridine)] to form polyCoFe. The characterization of polyCoFe was carried out using UV‐Vis titration, FT‐IR and SEM. The viscosity measurement of H‐SMP was utilized to calculate its molecular weight using Mark‐Houwink‐Sakurada equation. The electrochemical performance of polyCoFe_GCE was evaluated using the CV and EIS techniques. The kinetics of the irreversible electro‐oxidation mechanism were investigated by introducing variations in scan‐rate and pH. The concurrence observed between the experimental and simulated CV results provided additional evidence supporting the accuracy and reliability of the determined kinetic parameters. We investigated the efficiency of polyCoFe_GCE for nitrite detection at various concentrations using CV as well as amperometry methods. The amperometric technique showed a wide linear range of 0.66 to 194.15 μM and a low detection limit of 0.11 μM. In addition, modified electrode underwent interference, stability, and reproducibility tests. Real samples were analyzed using both CV and amperometry methods, and the obtained results were compared with those obtained from standard solutions.
Plasma‐Driven Tuning of Dielectric Permittivity in Graphene
Authors: Tatarova Elena , Dias Ana , Dankov Plamen , Kissovski Jivko , Botelho do Rego Ana Maria , Bundaleska Neli , Felizardo Edgar , Abrashev Miroslav , Ferraria Ana Maria , Strunskus Thomas , Shvalya Vasyl , Santhosh Neelakandan M. , Ivanov Ivan Valeriev , Košiček Martin , Zavašnik Janez , Alves Luis Lemos , Gonçalves Bruno , Cvelbar Uroš
Published: March 2024

Materials with tunable negative electromagnetic performance, i.e., where dielectric permittivity becomes negative, have long been pursued in materials research due to their peculiar electromagnetic (EM) characteristics. Here, this promising feature is reported in materials on the case of plasma‐synthesized nitrogen‐doped graphene sheets with tunable permittivity over a wide (1–40 GHz) frequency range. Selectively incorporated nitrogen atoms in a graphene scaffold tailor the electronic structure in a way that provides an ultra‐low energy (0.5–2 eV) 2D surface plasmon excitation, leading to subunitary and negative dielectric constant values in the Ka‐band, from 30 up to 40 GHz. By allowing the tailoring of structures at atomic scale, this novel plasma‐based approach creates a new paradigm for designing 2D nanomaterials like nanocarbons with controllable and tunable permittivity, opening a path to the next generation of 2D metamaterials.
Ferroelectric Bi2O2Te‐Based Plasmonic Biosensor for Ultrasensitive Biomolecular Detection
Authors: Wang Zheng , Liu Lixuan , Li Penghui , Nie Anmin , Zhai Kun , Xiang Jianyong , Mu Congpu , Wen Fusheng , Wang Bochong , Xue Tianyu , Liu Zhongyuan
Published: March 2024

Ultrasensitive detection of biomarkers, particularly proteins, and microRNA, is critical for disease early diagnosis. Although surface plasmon resonance biosensors offer label‐free, real‐time detection, it is challenging to detect biomolecules at low concentrations that only induce a minor mass or refractive index change on the analyte molecules. Here an ultrasensitive plasmonic biosensor strategy is reported by utilizing the ferroelectric properties of Bi2O2Te as a sensitive‐layer material. The polarization alteration of ferroelectric Bi2O2Te produces a significant plasmonic biosensing response, enabling the detection of charged biomolecules even at ultralow concentrations. An extraordinary ultralow detection limit of 1 fm is achieved for protein molecules and an unprecedented 0.1 fm for miRNA molecules, demonstrating exceptional specificity. The finding opens a promising avenue for the integration of 2D ferroelectric materials into plasmonic biosensors, with potential applications spanning a wide range.
Enhanced Alkaline Hydrogen Evolution Reaction via Electronic Structure Regulation: Activating PtRh with Rare Earth Tm Alloying
Authors: Li Qingqing , Zhang Botao , Sun Chang , Sun Xiaolei , Li Zhenxing , Du Yaping , Liu Jin‐Cheng , Luo Feng
Published: March 2024

Developing high‐performance electrocatalysts for alkaline hydrogen evolution reaction (HER) is crucial for producing green hydrogen, yet it remains challenging due to the sluggish kinetics in alkaline environments. Pt is located near the peak of HER volcano plot, owing to its exceptional performance in hydrogen adsorption and desorption, and Rh plays an important role in H2O dissociation. Lanthanides (Ln) are commonly used to modulate the electronic structure of materials and further influence the adsorption/desorption of reactants, intermediates, and products, and noble metal‐Ln alloys are recognized as effective platforms where Ln elements regulate the catalytic properties of noble metals. Here Pt1.5Rh1.5Tm alloy is synthesized using the sodium vapor reduction method. This alloy demonstrates superior catalytic activity, being 4.4 and 6.6 times more effective than Pt/C and Rh/C, respectively. Density Functional Theory (DFT) calculations reveal that the upshift of d‐band center and the charge transfer induced by alloying promote adsorption and dissociation of H2O, making Pt1.5Rh1.5Tm alloy more favorable for the alkaline HER reaction, both kinetically and thermodynamically.
Harnessing Natural Evaporation for Electricity Generation using MOF‐Based Nanochannels
Authors: Liu Huimin , Cui Peng , Zhang Jingjing , Wang Jingjing , Ge Ying , Zhou Zunkang , Meng Yao , Huang Zanying , Yang Ke , Du Zuliang , Cheng Gang
Published: March 2024

Functionalized nanochannels can convert environmental thermal energy into electrical energy by driving water evaporation. This process involves the interaction between the solid–liquid interface and the natural water evaporation. The evaporation‐driven water potential effect is a novel green environmental energy capture technology that has a wide range of applications and does not depend on geographical location or environmental conditions, it can generate power as long as there is water, light, and heat. However, suitable materials and structures are needed to harness this natural process for power generation. MOF materials are an emerging field for water evaporation power generation, but there are still many challenges to overcome. This work uses MOF‐801, which has high porosity, charged surface, and hydrophilicity, to enhance the output performance of evaporation‐driven power generation. It can produce an open circuit voltage of ≈2.2 V and a short circuit current of ≈1.9 µA. This work has a simple structure, easy preparation, low‐cost and readily available materials, and good stability. It can operate stably in natural environments with high practical value.
A Wind Bell Inspired Triboelectric Nanogenerator for Extremely Low‑Speed and Omnidirectional Wind Energy Harvesting
Authors: Huang Jinlong , Shao Jiang , Zhong Wei , Sun Chao , Zhang Gengchen , Chen Longyi , Fang Jiwen , Li Chong , Wang Jia , Feng Xiaoming , Zhou Lijun , Mi Hongliang , Chen Jiawei , Dong Xiaohong , Liu Xue
Published: March 2024

As one of the most promising renewable energies, wind energy is abundant in the natural environment. However, it is still challenging to effectively collect wind energy because of its variable wind speed and unpredictable direction. Here, a triboelectric nanogenerator, which is inspired by ancient Chinese wind bells, has been developed to collect energy from variable‐speed and multi‐directional wind. The wind‐bell‐inspired triboelectric nanogenerator (W‐TENG) has the capability to generate electricity even at a very low wind speed of 0.5 m s−1. Furthermore, it is able to harvest wind energy effectively from all directions (0–360 degrees). The parameter‐optimized W‐TENG achieves a maximum output voltage of 9.3 V and a maximum current of 0.63 µA. Electronic devices including a digital watch and 40 light‐emitting diodes (LEDs) are successfully powered by the designed W‐TENG, demonstrating its applicability. In this study, it is believed that a novel and effective strategy is provided to harvest energy from variable‐speed and multi‐directional wind.
Xanthine oxidase and nitric oxide inhibitory activities of compounds isolated from Gomphrena celosioides
Authors: Quang Ngo Van , Phuong Nguyen Thi Mai , Luong Dang Vu , Huyen Nguyen Thi Trang , Xuan Do Thi Thanh , Thuy Thanh Thi Thu
Published: March 2024

In this study, the investigation of xanthine oxidase and nitric oxide formation inhibitory activities of three compounds isolated from aerial part of Gomphrena celosioides, a folk medicinal plant for treatment of gout disease, is reported. The isolated compounds were determined based on NMR and ESI‐MS spectra, they are umbellatosides B, 20‐hydroxyecdysone, and 20‐hydroxyecdysone‐20,22‐monoacetonide. Biological activity results indicated that three compounds showed great activities, in which, umbellatosides B has good activity with IC50 value of 33.78 ± 0.49 and 19.55 ± 0.61 µm for xanthine oxidase and nitric oxide inhibitory activities, respectively. This is the report on the xanthine oxidase and nitric oxide inhibitory activities of three compounds that were first time isolated from the G. celosioides.
A small‐bore wire‐guided chest tube for the initial stabilisation of septic uroperitoneum in a dog
Authors: Elisa Pizzi , Veronica Cola , Chiara Ferrari , Sofia Segatore , Sara Del Magno
Published: March 2024

The purpose of this report was to describe the emergency management and subsequent surgical treatment of a 6‐year‐old, entire, male Epagneul Breton referred for septic uroperitoneum of 5 days duration. Clinical stabilisation was achieved by the insertion of a percutaneous small‐bore wire‐guided chest tube as an abdominal drain in association with conventional medical treatment. The small‐bore wire‐guided chest tube was inserted percutaneously into the abdomen, under ultrasound guidance, using a modified Seldinger technique. It was connected to a closed active collection system, and successfully drained the peritoneal urinary effusion. The medical treatment associated with the application of the small‐bore wire‐guided chest tube contributed to the patient's stabilisation, which was reached within 5 hours from arrival, allowing for an exploratory laparotomy with repair of the bladder laceration. The small‐bore wire‐guided chest tube was replaced during surgery by a Jackson–Pratt drain, which remained in place for 4 days postoperatively. The dog has completely recovered, and no complications were recorded.
Security Compliance in Model-Driven Software Development
Authors: Peldszus Sven
Published: March 2024

To ensure the security of a software system, it is vital to keep up with changing security precautions, attacks, and mitigations. Although model-based development enables addressing security already at design-time, design models are often inconsistent with the implementation or among themselves. Such inconsistencies hinder the effective realization and verification of secure software systems. In addition, variants of software systems are another burden to developing secure systems. Vulnerabilities must be identified and fixed on all variants or else attackers could be well-guided in attacking unfixed variants. To ensure security in this context, in the thesis (Peldszus, Security Compliance in Model-driven Development of Software Systems in Presence of Long-Term Evolution and Variants. Springer, Berlin; 2022), we present GRaViTY, an approach that allows security experts to specify security requirements on the most suitable system representation. To preserve security, based on continuous automated change propagation, GRaViTY automatically checks all system representations against these security requirements. To systematically improve the object-oriented design of a software-intensive system, GRaViTY provides security-preserving refactorings. For both continuous security compliance checks and refactorings, we show the application to variant-rich software systems. To support legacy systems, GRaViTY allows to automatically reverse-engineer variability-aware UML models and semi-automatically map existing design models to the implementation. Besides evaluations of the individual contributions, we demonstrate applicability of the approach in two real-world case studies, the iTrust electronics health records system and the Eclipse Secure Storage. This book chapter provides a summary of the thesis, focusing on the addressed problems, identified and answered research questions, the general solution, and its application of it to two case studies. For details on the individual solutions, please refer to the thesis and the corresponding publications referenced in this book chapter.
Loop amplitudes in the Coulomb branch of $$ \mathcal{N} $$ = 4 super-Yang-Mills theory
Authors: Abhishek Md. , Hegde Subramanya , Jatkar Dileep P. , Saha Arnab Priya , Suthar Amit
Published: March 2024

Abstract

We study four point planar loop amplitudes at an arbitrary point in the Coulomb branch of $$ \mathcal{N} $$
N
= 4 super-Yang-Mills theory. We study two particle unitary cuts up to four loop order. We explicitly verify that bubble and triangle graphs do not contribute at one loop level and show that the results hold at higher loop level as well. We also write down an all loop recursion relation for two particle reducible graphs for four point amplitudes.
Coupling a Cosmic String to a TQFT
Authors: Brennan T. Daniel , Hong Sungwoo , Wang Lian-Tao
Published: March 2024

Abstract

A common framework of particle physics consists of two sectors of particles, such as the Standard Model and a dark sector, with some interaction between them. In this work, we initiate the study of a qualitatively different setup in which one of the sectors is a topological quantum field theory (TQFT). Instead of particles, the physics of a TQFT only manifests itself in non-trivial spacetime topologies or in the presence of topological defects. In particular, we consider two possible ways in which axionic cosmic strings can interact with a ℤn TQFT. One of them, by extending the structure of the axion coupling, leads to specific predictions for the localized degrees of freedom on the cosmic string, which can in turn effect their evolution and leave observable signals. The second approach, by gauging a discrete subgroup of the axionic shift symmetry, leads to dramatic changes in the string spectrum. We stress that the scenario considered here should be regarded as a plausible way for new physics to arise since it can be the low energy effective field theory for quite generic scenarios at high energies. To demonstrate this point and further illustrate the physical implications, we construct UV completions for both of the cases of couplings to TQFTs. While detailed predictions for observable signals of such scenarios require further investigation, our results demonstrate that there are rich new phenomena in this scenario.
Human presencing: an alternative perspective on human embodiment and its implications for technology
Authors: Fester-Seeger Marie-Theres
Published: March 2024

Human presencing explores how people’s past encounters with others shape their present actions. In this paper, I present an alternative perspective on human embodiment in which the re-evoking of the absent can be traced to the intricate interplay of bodily dynamics. By situating the phenomenon within distributed, embodied, and dialogic approaches to language and cognition, I am overcoming the theoretical and methodological challenges involved in perceiving and acting upon what is not perceptually present. In a case study, I present strong and weak dimensions of human presencing. In the former, a person uses their body in distinct ways and shapes their immediate ecology to make others present to them. In contrast, in the latter, a person’s past encounter with others powerfully shapes the projections they make onto written digital inscriptions. These findings have implications for how people act in online learning environments and how human activity shapes the machines we use every day. In this way, the paper highlights the complexity of a person as a social being and allows for different approaches to human embodiment in technology.
A generic functional inequality and Riccati pairs: an alternative approach to Hardy-type inequalities
Authors: Kajántó Sándor , Kristály Alexandru , Peter Ioan Radu , Zhao Wei
Published: March 2024

We present a generic functional inequality on Riemannian manifolds, both in additive and multiplicative forms, that produces well known and genuinely new Hardy-type inequalities. For the additive version, we introduce Riccati pairs that extend Bessel pairs developed by Ghoussoub and Moradifam (Proc. Natl. Acad. Sci. USA, 2008 & Math. Ann., 2011). This concept enables us to give very short/elegant proofs of a number of celebrated functional inequalities on Riemannian manifolds with sectional curvature bounded from above by simply solving a Riccati-type ODE. Among others, we provide alternative proofs for Caccioppoli inequalities, Hardy-type inequalities and their improvements, spectral gap estimates, interpolation inequalities, and Ghoussoub-Moradifam-type weighted inequalities. Concerning the multiplicative form, we prove sharp uncertainty principles on Cartan-Hadamard manifolds, i.e., Heisenberg-Pauli-Weyl uncertainty principles, Hydrogen uncertainty principles and Caffarelli-Kohn-Nirenberg inequalities. Some sharpness and rigidity phenomena are also discussed.
Aesthetic Surgery Fellowship at Akademikliniken Stockholm: Survey among Graduates
Authors: Montemurro Paolo , Diehm Yannick F. , Hedén Per , Fischer Sebastian , Wagner Johannes M.
Published: March 2024

Background

Aesthetic Surgery is one of the most competitive fields of plastic surgery. Although there is a certain demand for highly educated surgeons in this field, training in cosmetic procedures remains challenging. Akademikliniken Stockholm offers a highly appreciated fellowship program for aesthetic plastic surgeons and trained more than 200 surgeons from all over the world.

Objectives

The aim of the present work was to provide insights into this fellowship program, analyze what graduates have learned and if this had implications on their further professional orientation.

Methods

Participants of the Akademikliniken fellowship program, who graduated between 10/2008 and 10/2018 (n = 66) were invited to take part in an online survey which included 30 questions about general demographics and about experience before, during and after the fellowship.

Results

Thirty-four graduates participated in the survey (52%). Twenty-four graduates (71%) had been already specialists in plastic surgery before commencing the fellowship program. Mean length of fellowship was 7 months (range 3–24months). Numbers of aesthetic procedures performed by the applicants significantly increased after the fellowship, and moreover, the scope of daily clinical practice shifted toward aesthetics in almost all applicants.

Conclusions

A well-designed dedicated aesthetic surgery fellowship can improve the lack of training, aesthetic surgeons have during their residency. Graduates of our fellowship program reported great improvements in confidence in performing aesthetic procedures and a benefit for their future career.

Level of Evidence III

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.
Automated graded prognostic assessment for patients with hepatocellular carcinoma using machine learning
Authors: Gross Moritz , Haider Stefan P. , Ze’evi Tal , Huber Steffen , Arora Sandeep , Kucukkaya Ahmet S. , Iseke Simon , Gebauer Bernhard , Fleckenstein Florian , Dewey Marc , Jaffe Ariel , Strazzabosco Mario , Chapiro Julius , Onofrey John A.
Published: March 2024

Background

Accurate mortality risk quantification is crucial for the management of hepatocellular carcinoma (HCC); however, most scoring systems are subjective.

Purpose

To develop and independently validate a machine learning mortality risk quantification method for HCC patients using standard-of-care clinical data and liver radiomics on baseline magnetic resonance imaging (MRI).

Methods

This retrospective study included all patients with multiphasic contrast-enhanced MRI at the time of diagnosis treated at our institution. Patients were censored at their last date of follow-up, end-of-observation, or liver transplantation date. The data were randomly sampled into independent cohorts, with 85% for development and 15% for independent validation. An automated liver segmentation framework was adopted for radiomic feature extraction. A random survival forest combined clinical and radiomic variables to predict overall survival (OS), and performance was evaluated using Harrell’s C-index.

Results

A total of 555 treatment-naïve HCC patients (mean age, 63.8 years ± 8.9 [standard deviation]; 118 females) with MRI at the time of diagnosis were included, of which 287 (51.7%) died after a median time of 14.40 (interquartile range, 22.23) months, and had median followed up of 32.47 (interquartile range, 61.5) months. The developed risk prediction framework required 1.11 min on average and yielded C-indices of 0.8503 and 0.8234 in the development and independent validation cohorts, respectively, outperforming conventional clinical staging systems. Predicted risk scores were significantly associated with OS (p < .00001 in both cohorts).

Conclusions

Machine learning reliably, rapidly, and reproducibly predicts mortality risk in patients with hepatocellular carcinoma from data routinely acquired in clinical practice.

Clinical relevance statement

Precision mortality risk prediction using routinely available standard-of-care clinical data and automated MRI radiomic features could enable personalized follow-up strategies, guide management decisions, and improve clinical workflow efficiency in tumor boards.

Key Points

• Machine learning enables hepatocellular carcinoma mortality risk prediction using standard-of-care clinical data and automated radiomic features from multiphasic contrast-enhanced MRI.

• Automated mortality risk prediction achieved state-of-the-art performances for mortality risk quantification and outperformed conventional clinical staging systems.

• Patients were stratified into low, intermediate, and high-risk groups with significantly different survival times, generalizable to an independent evaluation cohort.
Tropical cyclones in global high-resolution simulations using the IPSL model
Authors: Bourdin Stella , Fromang Sébastien , Caubel Arnaud , Ghattas Josefine , Meurdesoif Yann , Dubos Thomas
Published: March 2024

Despite many years of extensive research, the evolution of Tropical Cyclone (TC) activity in our changing climate remains uncertain. This is partly because the answer to that question relies primarily on climate simulations with horizontal resolutions of a few tens of kilometers. Such simulations have only recently become accessible for most modeling centers, including the Institut Pierre-Simon Laplace (IPSL). Using recent numerical developments in the IPSL model, we perform a series of historical atmospheric-only simulations that follow the HighResMIP protocol. We assess the impact of increasing the resolution from $${\sim }\, 200$$

∼

200

to 25 km on TC activity. In agreement with previous work, we find a systematic improvement of TC activity with increasing resolution with respect to the observations. However, a clear signature of TC frequencies convergence with resolution is still lacking. Cyclogenesis geographical distributions also improve at the scale of individual basins. This is particularly true of the North Atlantic, where the agreement with the observed distribution is impressive at 25 km. In agreement with the observations, TC activity correlates with the large-scale environment and ENSO in that basin. By contrast, TC frequencies remain too small in the Western North Pacific at 25 km, where significant biases of humidity and vorticity are found compared to the reanalysis. Despite the few minor weaknesses we identified, our results demonstrate that the IPSL model is a suitable tool for studying TCs on climate time scales. This work thus opens the way for further studies contributing to our understanding of TC climatology.
Operational wind and turbulence nowcasting capability for advanced air mobility
Authors: Chrit Mounir , Majdi Marwa
Published: March 2024

The present study introduces “WindAware”, a wind and turbulence prediction system that provides nowcasts of wind and turbulence parameters every 5 min up to 6 h over a predetermined airway over Chicago, Illinois, USA, based on 100 m high-resolution simulations (HRSs). This system is a long short-term memory-based recurrent neural network (LSTM-RNN) that uses existing ground-based wind data to provide nowcasts (forecasts up to 6 h every 5 min) of wind speed, wind direction, wind gust, and eddy dissipation rate to support the Uncrewed Aircraft Systems (UASs) safe integration into the National Airspace System (NAS). These HRSs are validated using both ground-based measurements over airports and upper-air radiosonde observations and their skill is illustrated during lake-breeze events. A reasonable agreement is found between measured and simulated winds especially when the boundary layer is convective, but the timing and inland penetration of lake-breeze events are overall slightly misrepresented. The WindAware model is compared with the classic multilayer perceptron (MLP) and the eXtreme Gradient Boosting (XGBoost) models. It is demonstrated by comparison to high-resolution simulations that WindAware provides more accurate predictions than the MLP over the 6 h lead times and has almost similar performance as the XGBoost model although the XGBoost’s training is the fastest using its parallelized implementation. WindAware also has higher prediction errors when validated against lake-breeze events data due to their under-representation in the training dataset.
HayCAMJ: A new method to uncover the importance of main filter for small objects in explainable artificial intelligence
Authors: Ornek Ahmet Haydar , Ceylan Murat
Published: March 2024

Visual XAI methods enable experts to reveal importance maps highlighting intended classes over input images. This research paper presents a novel approach to visual explainable artificial intelligence (XAI) for object detection in deep learning models. The study investigates the effectiveness of activation maps generated by five different methods, namely GradCAM, GradCAM++, EigenCAM, HayCAM, and a newly proposed method called "HayCAMJ", in detecting objects within images. The experiments were conducted on two datasets (Pascal VOC 2007 and Pascal VOC 2012) and three models (ResNet18, ResNet34, and MobileNet). Zero padding was applied to resize and center the objects due to the large objects in the images. The results show that HayCAMJ performs better than other XAI techniques in detecting small objects. This finding suggests that HayCAMJ has the potential to become a promising new approach for object detection in deep classification models.
Lumbar percutaneous transforaminal endoscopic discectomy: a retrospective survey on the first 172 adult patients treated in Denmark
Authors: Terkelsen Jacob Holmen , Hundsholt Torben , Bjarkam Carsten Reidies
Published: March 2024

Purpose

To evaluate patient demographics, surgery characteristics, and patient-reported clinical outcomes related to the implementation of lumbar PTED in Denmark by surgeons novice to the PTED technique.

Methods

All adult patients treated with a lumbar PTED from our first surgery in October 2020 to December 2021 were included. Data was generated by journal audit and telephone interview.

Results

A total of 172 adult patients underwent lumbar PTED. Surgery duration was a median of 45.0 (35.0–60.0) minutes and patients were discharged a median of 0 (0–1.0) days after. Per operatively one procedure was converted to open microdiscectomy due to profuse bleeding. Post operatively one patient complained of persistent headache (suggestive of a dural tear), two patients developed new L5 paresthesia, and three patients had a newly developed dorsal flexion paresis (suggestive of a root lesion). Sixteen patients did not complete follow-up and 24 (14.0%) underwent reoperation of which 54.2% were due to residual disk material. Among the remaining 132 patients, lower back and leg pain decreased from 7.0 (5.0–8.5) to 2.5 (1.0–4.5) and from 8.0 (6.0–9.1) to 2.0 (0–3.6) at follow-up, respectively (p < 0.001). Additionally, 93.4% returned to work and 78.8% used less analgesics. Post hoc analysis comparing the early half of cases with the latter half did not find any significant change in surgery time, complication and reoperation rates, nor in pain relief, return to work, or analgesia use.

Conclusion

Clinical improvements after lumbar PTED performed by surgeons novel to the technique are satisfactory, although the reoperation rate is high, severe complications may occur, and the learning curve can be longer than expected.
Resection status and margin control in intraoperative frozen sectioning analysis of oral squamous cell carcinoma
Authors: Neumann Felix , Straub Xenia , Mrosk Friedrich , Rubarth Kerstin , Wolfsberg Johanna , Piwonski Iris , Doll Christian , Voss Jan , Heiland Max , Kreutzer Kilian , Koerdt Steffen
Published: March 2024

Purpose

Intraoperative frozen section analysis (IFSA) is a well-established procedure for determining the intraoperative soft tissue resection status in patients with oral squamous cell carcinoma (OSCC). Margin status is a major predictor of the patient´s outcome, histologically free margins of ≥ 5 mm are demanded. This study evaluates the accuracy of IFSA, the impact of margin status and the impact of intraoperative margin revision on disease-free survival (DFS) and overall survival (OS).

Methods

This retrospective study included 213 patients with OSCC. IFSA results were compared with definitive histopathological reports, Kaplan–Meier analysis was performed. Cut-off values were calculated for resection margins considering known risk factors.

Results

IFSA showed positive margins in 8 cases (3.8%). Kaplan–Meier analysis revealed no significant differences for OS or DFS if R0-status was achieved by initial resection or immediate re-resection.

Final histopathological evaluation revealed false-positive IFSA in 3/8 cases (37.5%) and false-negative IFSA in 1/205 cases (0.5%). Sensitivity was 83.3% and specificity was 98.6%.

Analysis of optimal cut-off values showed no general need for larger resection margins in patients with risk factors. Cut-off values were slightly higher for patients with the risk factor alcohol consumption (7 mm for OS and DFS) or pN + ECS- disease (7 mm for DFS). Optimal cut-off values for tumour-margin-distance were around 6 mm.

Conclusion

IFSA provides a valuable assessment method for intraoperative soft tissue resection margins. Risk factors seemingly do not significantly influence the extent of tumour resection.
Virtual reality based rehabilitation in adults with chronic neck pain: a systematic review and meta-analysis of randomized clinical trials
Authors: Brea-Gómez Beatriz , Laguna-González Alejandro , Pérez-Gisbert Laura , Valenza Marie Carmen , Torres-Sánchez Irene
Published: March 2024

Chronic neck pain is one of the most frequent musculoskeletal disorders, with high prevalence worldwide. Rehabilitation is an essential component of therapeutic strategy. Virtual reality based rehabilitation (VRBR) is a powerful distraction technique that could be beneficial for chronic neck pain patients. The objective of this systematic review was to analyse the effectiveness of VRBR in chronic neck pain treatment. We followed the PRISMA guidelines and used four databases (CINAHL, Medline (Via PubMed), Scopus and Web of Science) from their inception to August 2023. Eligibility criteria were established using PICOS. Methodological quality was evaluated with the Downs and Black scale and the risk of bias with the Revised Cochrane risk-of-bias tool. The meta-analysis was performed using the RevMan software. Six studies were included in the systematic review and the meta-analysis. We observed significant differences in favour of VRBR for pain intensity (SMD =  − 0.46; 95% CI =  − 0.74, − 0.19; p = 0.001), disability (MD =  − 2.84; 95% CI =  − 4.23, − 1.45; p < 0.0001), global perceived effect (MD = 0.49; 95% CI = 0.25, 0.72; p < 0.0001) and patient satisfaction (MD = 0.62; 95% CI = 0.38, 0.86; p < 0.00001). However, at short-term follow-up significant differences were only obtained for disability (MD =  − 3.52; 95% CI =  − 5.85, − 1.20; p = 0.003). VRBR can significantly improve pain intensity, disability, global perceived effect and patient satisfaction. The small number of articles included in the analysis is a limitation, even considering the good methodological quality of these studies. Investigating the effects of VRBR on mid and long-term follow-up and exploring different types of VR are needed.

PROSPERO database, registration number ID: CRD42020222129.
New proxemics in new space: proxemics in VR
Authors: Kim Ikhwan , Sung Junghan
Published: March 2024

With the development of computer technology, it is possible to design virtual reality (VR) media that provides services to multiple users. Hall’s proxemics theory, which holds that the distance varies depending on the relationship between people, has been applied when designing VR in such media. However, this concept was usually applied to designs without criticism and without confirming whether proxemic distances established in physical space are equally valid in VR. This study investigated how proxemics in VR activate differently from those in a physical space. We measured the distance and the number of instances of direct contact between people, with 69 participants from Korea and Turkiye. As a result, a proxemics pattern similar to that of a physical space appeared in VR. However, the average distance between participants in the VR was about 160% greater than in the physical space. Also, we could observe direct contact up to 260% more in the VR than in the physical space. We analyzed the collected data using Bayesian ANOVA and t-tests. We could clarify the difference between the two proxemics in physical space and VR, but the reason for the phenomenon has yet to be discovered. However, this study is meaningful because any industry designing VR, such as those in digital games, can directly apply the findings to manipulate multiple users’ emotions and experiences more efficiently. Additionally, this study provides directions for any future studies discussing VR design.
Prognostic modeling in early rheumatoid arthritis: reconsidering the predictive role of disease activity scores
Authors: Bird Alix , Oakden-Rayner Lauren , Smith Luke A. , Zeng Minyan , Ray Shonket , Proudman Susanna , Palmer Lyle J.
Published: March 2024

Objective

In this prospective cohort study, we provide several prognostic models to predict functional status as measured by the modified Health Assessment Questionnaire (mHAQ). The early adoption of the treat-to-target strategy in this cohort offered a unique opportunity to identify predictive factors using longitudinal data across 20 years.

Methods

A cohort of 397 patients with early RA was used to develop statistical models to predict mHAQ score measured at baseline, 12 months, and 18 months post diagnosis, as well as serially measured mHAQ. Demographic data, clinical measures, autoantibodies, medication use, comorbid conditions, and baseline mHAQ were considered as predictors.

Results

The discriminative performance of models was comparable to previous work, with an area under the receiver operator curve ranging from 0.64 to 0.88. The most consistent predictive variable was baseline mHAQ. Patient-reported outcomes including early morning stiffness, tender joint count (TJC), fatigue, pain, and patient global assessment were positively predictive of a higher mHAQ at baseline and longitudinally, as was the physician global assessment and C-reactive protein. When considering future function, a higher TJC predicted persistent disability while a higher swollen joint count predicted functional improvements with treatment.

Conclusion

In our study of mHAQ prediction in RA patients receiving treat-to-target therapy, patient-reported outcomes were most consistently predictive of function. Patients with high disease activity due predominantly to tenderness scores rather than swelling may benefit from less aggressive treatment escalation and an emphasis on non-pharmacological therapies, allowing for a more personalized approach to treatment.

Key Points• Long-term use of the treat-to-target strategy in this patient cohort offers a unique opportunity to develop prognostic models for functional outcomes using extensive longitudinal data.• Patient reported outcomes were more consistent predictors of function than traditional prognostic markers.• Tender joint count and swollen joint count had discordant relationships with future function, adding weight to the possibility that disease activity may better guide treatment when the components are considered separately.
Acute treatment of migraine: quantifying the unmet need through real-world data in Italy
Authors: Sacco Simona , Di Ciaccio Sonia , Di Virgilio Roberto , Pegoraro Valeria , Ornello Raffaele
Published: March 2024

Objective

This study is describing subjects with migraine interrupting or not receiving triptans for acute treatment and providing a national-level estimate of people who might benefit from different therapeutic approaches.

Methods

This is a retrospective analysis using IQVIA Longitudinal Patient Database. Starting from 18 + years old individuals with migraine, we selected two cohorts: subjects with triptans prescriptions before and no triptans prescriptions after Index Date (triptan withdraw) and subjects without triptans prescriptions both before and after Index Date (no triptan prescriptions). Index Date was the first record of a health encounter for migraine in 2019. Individuals with cardiovascular disease (CVD) within no triptan prescriptions group were also quantified.

Results

Triptan withdraw and no triptan prescriptions cohorts numbered 605 and 3270, respectively, 5% and 29% of subjects with migraine. Mean age was 47 and 51 years respectively; women were more represented (~ 80%). Hypertension and thyroid disease were most frequent comorbidities; non-steroidal anti-inflammatory drugs were among most frequently recorded treatments. Subjects with CVD within no triptan prescriptions cohort were 621 and with triptan withdraw cohort subjects represented the basis to estimate those who might benefit from alternative options for the acute treatment of migraine, who were around 60,000 and accounted for 11% of subjects seeking primary care due to migraine.

Conclusions

This analysis provides a real-word estimate of Italian people that might benefit from different therapeutic approaches as an alternative to triptans, which sometimes might be not effective and/or poorly tolerated. Such estimate should be intended as the lower limit of a wider range due to strict criteria adopted.
Machine learning in risk prediction of continuous renal replacement therapy after coronary artery bypass grafting surgery in patients
Authors: Zhang Qian , Zheng Peng , Hong Zhou , Li Luo , Liu Nannan , Bian Zhiping , Chen Xiangjian , Wu Hengfang , Zhao Sheng
Published: March 2024

Objectives

This study aimed to develop machine learning models for risk prediction of continuous renal replacement therapy (CRRT) following coronary artery bypass grafting (CABG) surgery in intensive care unit (ICU) patients.

Methods

We extracted CABG patients from the electronic medical record system of the hospital. The endpoint of this study was the requirement for CRRT after CABG surgery. The Boruta method was used for feature selection. Seven machine learning algorithms were developed to train models and validated using 10 fold cross-validation (CV). Model discrimination and calibration were estimated using the area under the receiver operating characteristic curve (AUC) and calibration plot, respectively. We used the SHapley Additive exPlanations (SHAP) method to illustrate the effects of the features attributed to the model and analyze the effects of individual features on the output of the mode.

Results

In this study, 72 (37.89%) patients underwent CRRT, with a higher mortality compared to those patients without CRRT. The Gaussian Naïve Bayes (GNB) model with the highest AUC were considered as the final predictive model and performed best in predicting postoperative CRRT. The analysis of importance revealed that cardiac troponin T, creatine kinase isoenzyme, albumin, low-density lipoprotein cholesterol, NYHA, serum creatinine, and age were the top seven features of the GNB model. The SHAP force analysis illustrated how created model visualized individualized prediction of CRRT.

Conclusions

Machine learning models were developed to predict CRRT. This contributes to the identification of risk variables for CRRT following CABG surgery in ICU patients and enables the optimization of perioperative managements for patients.
A three-stage approach to identify biomarker signatures for cancer genetic data with survival endpoints
Authors: Wu Xue , Chen Chixiang , Li Zheng , Zhang Lijun , Chinchilli Vernon M. , Wang Ming
Published: March 2024

The identification of prognostic and predictive biomarker signatures is crucial for drug development and providing personalized treatment to cancer patients. However, the discovery process often involves high-dimensional candidate biomarkers, leading to inflated family-wise error rates (FWERs) due to multiple hypothesis testing. This is an understudied area, particularly under the survival framework. To address this issue, we propose a novel three-stage approach for identifying significant biomarker signatures, including prognostic biomarkers (main effects) and predictive biomarkers (biomarker-by-treatment interactions), using Cox proportional hazard regression with high-dimensional covariates. To control the FWER, we adopt an adaptive group LASSO for variable screening and selection. We then derive adjusted p-values through multi-splitting and bootstrapping to overcome invalid p values caused by the penalized approach’s restrictions. Our extensive simulations provide empirical evaluation of the FWER and model selection accuracy, demonstrating that our proposed three-stage approach outperforms existing alternatives. Furthermore, we provide detailed proofs and software implementation in R to support our theoretical contributions. Finally, we apply our method to real data from cancer genetic studies.