bluuebunny/crossref_metadata_2025 huggingface dataset:
Carbon dioxide and evapotranspiration fluxes in an urban area of Krakow, Poland
Authors: Jasek‐Kamińska Alina , Szostak Radosław , Chmura Łukasz , Bartyzel Jakub , Zimnoch Mirosław
Published: October 2024

Urban areas play an essential role in the global carbon balance, being responsible for more than 70% of anthropogenic carbon emissions, entering the atmosphere mainly in the form of carbon dioxide (CO2). Another crucial component of the carbon balance of the urban atmosphere is CO2 exchange with the biosphere, expressed in both emission and absorption fluxes. The biosphere component of the net CO2 flux is inseparably linked to the water (H2O) balance due to evapotranspiration. This article presents an estimation of CO2 and H2O net fluxes based on eddy covariance (EC) tower measurements and in‐depth analysis of its temporal and spatial variability for a typical urban site at mid‐latitude of the northern hemisphere. The source area was divided into two sectors, one representing dense urban development with sources of CO2 from traffic and households, and the second containing predominantly recreation and sports areas. Temporal variability analysis of evapotranspiration showed a clear seasonal cycle closely correlated with incoming radiation and air temperature, with the seasonal mean ranging from 0.4 mm·day−1 in winter to 1.6 mm·day−1 in summer. As a result of similar green coverage between the urban and green sectors, spatial variability was statistically insignificant. The net CO2 flux over a seasonal cycle was less pronounced for the total source area with a mean of 5.0 g C·m−2·day−1 in summer and 7.5 g C·m−2·day−1 in winter. However, significant variations between urban and green sectors were observed with the highest seasonal mean difference of 4.5 g C·m−2·day−1 in winter. The results confirm that while on the local, short time‐scale urban vegetation has a potential to mitigate the emissions, it is not able to offset them.
Green public procurement as an effective way for sustainable development: A systematic literature review and bibliometric analysis
Authors: Ortega Carrasco Pablo , Iannone Fabio , Ferrón Vílchez Vera , Testa Francesco
Published: October 2024

Green public procurement (GPP) has emerged as a strategic tool for sustainable development. However, the drivers and barriers to effective GPP implementation remain unclear. Additionally, the growing volume of GPP research necessitates interlinking with sustainability concepts, such as sustainable development, to guide future research. This paper presents a systematic literature review and bibliometric analysis of GPP research between 2003 and 2023 to identify key themes, trends and research gaps. A dataset of 201 documents retrieved from the Web of Science database was analysed using CitNetExplorer and VOSViewer. By analysing prior literature on the effect of GPP on the achievement of sustainable development, we have found, among others concerns, that: (1) richer qualitative analysis on GPP is needed; (2) there is a gap in understanding localised factors influencing GPP in developing countries; and (3) the transformative role of digitalisation in promoting social and environmental outcomes in GPP is an essential factor. These findings will inform policymakers, practitioners and researchers on the effective implementation of GPP for sustainable development.
Empowering marginalised communities: Leveraging indigenous knowledge for sustainable energy development in South Africa
Authors: Mawere Joshua , Mukonza Ricky Munyaradzi
Published: October 2024

Amidst South Africa's volatile energy landscape—characterised by political turbulence, economic instability and Eskom's chronic financial and operational challenges—the imperative for transformative reform is both urgent and indispensable. Municipalities are confronted with deteriorating infrastructure, recurrent power disruptions and widespread electricity theft, which collectively exacerbate the national energy crisis. This paper investigates the integration of indigenous knowledge systems within the country's energy sector as a strategic response to these persistent challenges, promoting the empowerment of marginalised communities and advancing environmental sustainability. Anchored in the theoretical frameworks of environmental justice and indigenous rights, the paper advocates for Afrocentric paradigms such as traditional resource governance and community‐driven energy solutions. Employing thematic analysis of secondary data, it evaluates the viability and prospective benefits of this paradigm shift. The paper posits that the inclusion of indigenous knowledge in energy practices not only presents tangible solutions to the energy crisis but also cultivates socio‐economic empowerment and reinforces environmental stewardship.
From sustainable development towards resilience: Does digital finance matter in enhancing ecological resilience?
Authors: Jiang Wei , Jiang Nana
Published: October 2024

Digital finance, as a representative of the digital economy, provides unprecedented opportunities for enhancing the adaptability and resilience of ecosystems. However, there is currently no literature that integrates digital finance and urban ecological resilience into the same research framework. In light of this, we utilize panel data from 2011 to 2019 to investigate the impact of digital finance on ecological resilience. Our results indicate that (1) Digital finance can effectively enhance ecological resilience, a conclusion corroborated by both theoretical frameworks and empirical evidence. Specifically, the coverage breadth and usage depth of digital finance can effectively enhance ecological resilience, while the digitization level has not shown a significant impact. (2) Green technological innovation, improvements in energy efficiency, and the agglomeration of producer services are identified as effective channels through which digital finance promotes ecological resilience. (3) The impact of digital finance on ecological resilience exhibits significant regional heterogeneity, with more pronounced effects observed in cities with advanced traditional financial systems, non‐resource‐based cities, and central cities. These findings will help policymakers better understand the relationship between digital finance and urban ecological resilience, and formulate targeted policies that leverage digital finance development to enhance ecological resilience.
A Hybrid Machine Learning‐Based Data‐Centric Cybersecurity Detection in the 5G‐Enabled IoT
Authors: Zeng Lingcheng , An Yunzhu , Zhou Heng , Luo Qifeng , Lin Yuede , Zhang Zhiqiang
Published: October 2024

By increasing smart objects as high‐potential computing devices and 5G technology, the Internet of Things (IoT) has emerging technology to provide a data‐centric infrastructure for detecting safe device‐to‐device communications by supporting security and privacy issues. As a 5G‐enabled communication technology, vehicle‐to‐vehicle (V2V) communication provides a wireless exchange information connection between smart vehicles, intelligent devices, and a cloud‐edge computing environment. This connection should be established with a safe and secured run‐time protection system to avoid many critical anomalies and misbehavior problems. Detecting run‐time malicious transformations with data‐centric misbehaving reactions is a main challenge for autonomous vehicle communications with 5G‐enabled communication technology. This paper provides a hybrid genetic algorithm‐based ensemble bagged trees (GA‐EBT) algorithm for a data‐centric misbehavior detection approach to support the V2V communications against malicious and misbehavior transactions. In this hybrid algorithm, GA provides a beneficial performance on the training accuracy factor based on a single‐objective fitness function and EBT supports a high‐degree prediction and training process using multiple decision tree models with bootstrapped samples of the training data. For the evaluation of the proposed algorithm, four real test cases are applied for messaging injection attacks in the V2V environments in comparison to the state‐of‐the‐art machine learning algorithms. The experimental results show that the proposed hybrid approach can achieve an optimal high rate accuracy factor of 99.999, precision and recall factors of 100%, and an F1‐Score factor of 100% to detect unexpected cyber‐attacks for the V2V communications in the IoT environment.
An Efficient Algorithm for Exact Segmentation of Large Compositional and Categorical Time Series
Authors: Truong Charles , Runge Vincent
Published: October 2024

Change‐point detection, also known as signal segmentation, is an essential preprocessing step in many applications, ranging from industrial monitoring to bioinformatics. In short, it consists in finding the temporal boundaries of homogeneous regimes in long and non‐stationary time series. While this area of research is active, most existing methods are designed for Euclidean data. However, in many practical scenarios, the collected time series are compositional, meaning that each observation belongs to the probability simplex (the set of non‐negative vectors whose components sum to one). In this work, we propose an algorithm detecting change‐points in large compositional signals with an underlying piecewise stationary model. We cast the change‐point detection task as a discrete optimization problem, whose solution is shown to converge to the true change‐points. We introduce a new and time‐efficient dynamic programming algorithm that solves exactly this problem. To limit the number of operations, we describe a novel pruning rule that allows us to reduce the set of candidate change‐point indices. Our method is tested on a thorough simulation study, which confirms its efficiency. Additionally, we apply our method to a human activity segmentation task, highlighting the necessity for such novel techniques compared to standard algorithms.
Clinicopathological, Histopathological, and Immunohistochemical Analysis of Mandibular Fibrosarcoma in a DSH Cat: A Case Report
Authors: Ahmadi‐hamedani Mahmood , Moslemi Hamid Reza , Khaligh Sahar Ghaffari , Sedghi Mehdi , Sattari Kimia
Published: October 2024

A 4‐year‐old white male DSH cat was presented to the Veterinary Hospital on 18 December 2023, with a history of lethargy, loss of appetite, and salivation. During the inspection of the oral cavity, unilateral swelling was observed on the ventral side of the jaw. Before any therapeutic intervention, a cell blood count (CBC) test and FNA cytology were conducted. A five‐day course of adjunctive treatment, including ceftriaxone (5.5 mg/kg via IV) and clindamycin (25 mg/kg via IV), was given due to a suspicion of infection. Pantoprazole, metoclopramide (administered at 1 mg/kg via IV and IM), and duphalyte 500 mL (10 mL/kg IV) were used concurrently to alleviate nausea and stimulate appetite. Following a lack of improvement, a radical excision procedure was performed on tooth number 304 after the 5‐day treatment to excise the mass for histopathology and immunohistochemical analysis. The observation of mitotic bodies, pleomorphism, necrosis, and haemorrhage were consistent with malignancy, and squamous cell carcinoma (SCC) was suspected. Immunohistochemical staining was positive for the vimentin marker, the S‐100 protein, and desmin. This report describes a rare case of oral fibrosarcoma in a DSH cat in Iran.
Towards a Multi-dimensional Health Data Analysis Framework
Authors: Rabbi Fazle , Fatemi Bahareh , Mukhiya Suresh Kumar , Lamo Yngve
Published: October 2024

Healthcare processes need to be streamlined to offer better healthcare services. Data analysis can be crucial in reducing costs, optimizing processes, and analyzing treatment effectiveness. However, data analysis in healthcare is complex due to the variety and complexity of patient data. This paper proposes a multi-dimensional comparative analysis method that offers healthcare professionals a lens to delve into healthcare datasets from various perspectives. The paper discusses the importance of comparative analysis in healthcare illustrated by two examples on how we can understand the pattern of comorbidity and how we can analyze the effectiveness of internet delivered psychological interventions. The paper presents a multi-dimensional comparative analysis framework covering various use cases in analysing healthcare data. The framework allows healthcare professionals to compare and contrast healthcare data across multiple dimensions, including clinical dimensions such as diagnosis, outcome measures, time dimension, patient dimensions (engagement, involvement), cost dimension, and other relevant factors. This approach offers a more insightful understanding of healthcare data and facilitates informed decision-making in healthcare practices.
CRISP-PCCP – A Development Methodology Supporting FDA Approval for Machine Learning Enabled Medical Devices
Authors: Pechmann Ludwig , Potdevin Yannik , Brehmer Kai , Nowotka Dirk , Leucker Martin
Published: October 2024

The U.S. Food and Drug Administration (FDA) is the regulatory body that ensures the safety, efficacy, and security of medical devices and software in the healthcare sector in the U.S. However, its guidelines and regulations often set a global benchmark, influencing medical device standards in Europe and other regions. The FDA recently published a draft guidance, the Predetermined Change Control Plan (PCCP), aiming to support medical device manufacturers with the release of continual learning Machine Learning-Enabled Device Software Functions (ML-DSF). Such ML-DSFs are intended to change after initial market approval. We present a systematic process to support the implementation of the PCCP. Building upon the Cross-Industry Standard Process for the development of Machine Learning applications with Quality assurance methodology (CRISP-ML(Q)), we present an approach that a manufacturer may use to identify and evaluate the impact of anticipated changes to ML-DSF. Our process also indicates a forecast, whether the anticipated change would be accepted by the FDA as a part of the PCCP.
From Explanation Correctness to Explanation Goodness: Only Provably Correct Explanations Can Save the World
Authors: Schwammberger Maike
Published: October 2024

Explainability Engineering gets evermore important in the era of self-learning and automated systems. We motivate the necessity for interdisciplinary research to engineer verifiably correct and good explanations: Systems engineering research must ensure that correct and machine-understandable explanations can be derived from system specifications and social sciences research must ensure that a context-dependent and stakeholder-tailored explanation can be provided in a fitting manner. We describe our first steps in the direction of a holistic and interdisciplinary explainability engineering process for tackling these challenges.
Safeguarding AI-Based Software Development and Verification using Witnesses (Position Paper)
Authors: Beyer Dirk
Published: October 2024

This position paper accompanies a presentation and discussion at AISoLA 2023 on the topic of how (generative) AI influences software engineering, namely, the development and verification of software programs. We outline a few opportunities and challenges that are posed by the application of AI. AI-based techniques can be an efficient method to produce software code. Not only this, AI can also be efficient in producing invariants that help proving correctness of software programs. But unfortunately, the results generated by AI-based approaches are often still imprecise or wrong: Code produced with the help of AI often does not satisfy the specification, and AI-generated invariants are often not helpful to prove the correctness of the program. The solution is to safeguard the process by independently checking the results using verification witnesses and witness validation. The goal of this paper is to convince readers that software witnesses are important and that independent result validation is of utmost importance to ensure correctness.
Digitised Historical Sources and Non-digital Humanists: An Interdisciplinary Challenge?
Authors: Le Roux Maelle , Gasperini Anna
Published: October 2024

The digitisation of sources has opened new perspectives for humanities scholars. Digitisation allowed a larger access to sources, removing some financial and geographical limits, and the use of digital tools provided new perspectives for humanities scholars, who are able to read the sources differently. However, working with digitised sources also created new challenges that humanities scholars are not always equipped to overcome.

The ‘MedIcal Literature and Communication about Child Health’ (MILC) project uses historical medical books for a non-specialist audience to analyse discourses on children’s health in England, France and Italy between 1850 and 1914. Despite being born a non-digital humanities project, with a focus on manual qualitative analysis and a combination of history and literature methods, it took a digital turn when using digitised sources, with issues of digitisation and Optical Character Recognition (OCR) among others. The team working on the project is composed of three humanities scholars, with limited computer science skills. This required us to find digital humanities and in general IT tools adapted to our skillset, and suited to our needs. These tools did not always fit all our needs, and often presented issues in terms of accessibility and compatibility with the general standards of digital humanities.

Using examples from the issues faced by this project, and from the solutions found, this paper will argue that the challenges encountered by humanities scholars are interdisciplinary, not only because they overcome the traditional disciplinary boundaries inside the humanities, but also because they mirror challenges that computer scientists are working to solve. This paper will also argue that collaboration is a necessity which would benefit both humanities scholars and computer scientists in their work on the improvement and development of new tools, with the help of AI for example. Using the work done by a team of non-digital humanities scholars, it will argue that accessibility is a central issue in digital humanities and in the creation of IT tools, which needs to be addressed.
Studienergebnisse: Gemeinsame Faktoren eines NTE-Berichts
Authors: Nadile Stefan
Published: October 2024

Im Folgenden werden zunächst die Faktoren bestimmt, die die verschiedenen Berichte miteinander verbindet. Diese sind vor allem kulturell bedingte Eigenheiten, die das Erzählen von mitunter unglaublich scheinenden Ereignissen erschweren, ermöglichen oder begünstigen. Zunächst werden die Hauptkategorien des aus dem Datenmaterial generierten Kategoriensystems erörtert.
Zusammenfassung und Bewertung
Authors: Nadile Stefan
Published: October 2024

Die Studienergebnisse werden in der Folge zusammengetragen und bewertet. Dabei werden die Typen zunächst einander gegenübergestellt, Haupt- und Subkategorien typenübergreifend dargestellt sowie auf Gemeinsamkeiten und Unterschiede eingegangen. Daraufhin werden dann jeweils weitere gemeinsame, typenunspezifische Faktoren zusammenfassend eingeordnet.
Quark mass effects in Higgs production
Authors: Czakon Michał , Eschment Felix , Niggetiedt Marco , Poncelet Rene , Schellenberger Tom
Published: October 2024

Abstract

We examine the effect of finite top- and bottom-quark masses on the Higgs production cross section in the gluon-gluon fusion channel. We employ both $$ \overline{\textrm{MS}} $$

MS
¯

and on-shell renormalisation for the quark masses and provide a thorough comparison. Furthermore, we explore alternative treatments of quark masses, in particular in the four-flavour scheme, and investigate their impact on the cross section. Our work also presents novel predictions for differential cross sections in the Higgs rapidity. The results lead to a significant reduction of scale uncertainties, and our analysis enables us to offer well-grounded recommendations for future research in this area.
Low-virtuality splitting in the Standard Model
Authors: Nardi Filippo , Ricci Lorenzo , Wulzer Andrea
Published: October 2024

Abstract

When the available collision energy is much above the mass of the particles involved, scattering amplitudes feature kinematic configurations that are enhanced by the much lower virtuality of some intermediate particle. Such configurations generally factorise in terms of a hard scattering amplitude with exactly on-shell intermediate particle, times universal factors. In the case of real radiation emission, such factors are splitting amplitudes that describe the creation or the annihilation — for initial or final state splittings — of the low-virtuality particle and the creation of the real radiation particles. We compute at tree-level the amplitudes describing all the splittings that take place in the Standard Model when the collision energy is much above the electroweak scale. Unlike previous results, our splitting amplitudes fully describe the low-virtuality kinematic regime, which includes the region of collinear splitting, of soft emission, and combinations thereof. The splitting amplitudes are compactly represented as little-group tensors in an improved bi-spinor formalism for massive spin-1 particles that automatically incorporates the Goldstone Boson Equivalence Theorem. Simple explicit expressions are obtained using a suitably defined infinite-momentum helicity basis representation of the spinor variables. Our results, combined with the known virtual contributions, could enable systematic predictions of the leading electroweak radiation effects in high-energy scattering processes, with particularly promising phenomenological applications to the physics of future colliders with very high energy such as a muon collider.
On the non-perturbative bulk Hilbert space of JT gravity
Authors: Iliesiu Luca V. , Levine Adam , Lin Henry W. , Maxfield Henry , Mezei Márk
Published: October 2024

Abstract

What is the bulk Hilbert space of quantum gravity? In this paper, we resolve this problem in 2d JT gravity, both with and without matter, providing an explicit definition of a non-perturbative Hilbert space specified in terms of metric variables. The states are wavefunctions of the length and matter state, but with a non-trivial and highly degenerate inner product. We explicitly identify the null states, and discuss their importance for defining operators non-perturbatively. To highlight the power of the formalism we developed, we study the non-perturbative effects for two bulk linear operators that may serve as proxies for the experience of an observer falling into a two-sided black hole: one captures the length of an Einstein-Rosen bridge and the other captures the center-of-mass collision energy between two particles falling from opposite sides. We track the behavior of these operators up to times of order $$ {e}^{S_{\textrm{BH}}} $$

e

S
BH

, at which point the wavefunction spreads to the complete set of eigenstates of these operators. If these observables are indeed good proxies for the experience of an infalling observer, our results indicate an O(1) probability of detecting a firewall at late times that is self-averaging and universal.
Transverse dynamics of charmed hadrons in ultra-relativistic nuclear collisions
Authors: Andronic Anton , Braun-Munzinger Peter , Brunßen Hjalmar , Crkovská Jana , Stachel Johanna , Vislavicius Vytautas , Völkl Martin
Published: October 2024

Abstract

Transverse momentum pT spectra and anisotropic flow distributions are studied for charmonia and charmed hadrons produced in Pb-Pb collisions and measured with the ALICE detector at the CERN Large Hadron Collider (LHC). The investigations are performed within the framework of the Statistical Hadronization Model with the transverse dynamics evaluated using predictions from relativistic viscous hydrodynamics as implemented in the computer codes MUSIC and FluiduM. With this essentially parameter-free approach good agreement is obtained for pT spectra in the range pT < 10 GeV/c. The observed wide distribution in pT of anisotropic flow coefficients v2 and v3 for charmonia is also well reproduced, while their magnitude is generally somewhat over predicted. This finding may be connected to a difference in spatial distribution between light and charmed hadrons due to a different diffusion of light and heavy quarks in the hot fireball.
Revealing Yukon’s hidden treasure: an atomic-scale investigation of Carlin-type gold mineralization in the Nadaleen Trend, Canada
Authors: Gopon Phillip , Sack Patrick , Pinet Nicolas , Douglas James O. , Jenkins Benjamin M. , Johnson Brooke , Penny Ella , Moody Michael P. , Robb Laurence
Published: October 2024

The invisible-gold deposits known as Carlin-type are becoming more important as easier to find deposits are progressively depleted. The combination of the invisible nature of the Au in these deposits, as well as the limited surface indicators of these deposits, makes exploration to find new Carlin-type deposits extremely difficult. Comprehensive mineralization models are essential to find new Carlin-type deposits in similar geologic settings. The Nadaleen Trend of Yukon, Canada, is one such district where an improved understanding of this deposit type has led to new discoveries. Previous studies compared and contrasted the tectonic setting, host rock depositional setting, structural preparation, and mineralization style of the Nadaleen Trend with those in Carlin-type localities, Nevada. However, the comparisons at an atomic scale, between Carlin-type Au deposits in the Nadaleen Trend and those in Nevada, has yet to be investigated. This study fills this knowledge gap by combining high resolution microanalytical techniques with atom probe tomography to examine the distribution of Au and other trace elements in the Nadaleen Trend, compare them to a representative Carlin-type deposit in Nevada (Turquoise Ridge), and determine how widespread the mineralization model is. Our findings show that in the Nadaleen Trend, as in Nevada, Au is generally directly linked with As at the macro to atomic scale, and is incorporated into As/Au rich overgrowths on sedimentary/diagenetic pyrite. Gold-rich pyrite rims in the Nadaleen Trend are generally smaller than those found in Nevada (0.5–2 µm vs > 10 µm), although the ore grades appear comparable. We find that the Au in the pyrite of the Nadaleen Trend is homogenously distributed (i.e. lattice bound) at the atomic scale, but that there is a notable enrichment of As surrounding individual Au atoms. These findings are in agreement with those from previous work on a representative deposit in Nevada, and support the assertation that As is the key ingredient in facilitating the incorporation of Au into the pyrite lattice. Arsenic as an essential component in the trapping mechanisms of Au in CTG deposits, is something that has been as to yet underappreciated in the current models of CTG deposit formation.
Investment casting of porous Mg-alloy networks biomechanically tuned for bone implant applications
Authors: Dmitruk Anna , Díaz Lantada Andrés , Ferraris Sara , Łobacz-Raźny Natalia , Spriano Silvia , Naplocha Krzysztof
Published: October 2024

Manufacturing technology has been refined and described for the fabrication of honeycomb-based bioresorbable networks for temporal bone replacement applications. Two novel techniques, digital light processing and investment casting, were utilized to produce customized, shape-optimized cellular constructs with additional orifices promoting tissue ingrowth during osteo-regeneration. For this purpose, a conventional magnesium casting alloy (AZ91) was chosen. Numerical simulations were conducted to predict the compressive behavior of the proposed biodegradable lightweight scaffolds. Spatial castings were adjusted to possess mechanical properties comparable to the ones of cortical or trabecular bones. Two kinds of protective coatings (plasma electrolytic oxidation and organic ones based on natural polyphenols from tea extract) were deposited and characterized. They can be utilized to control the degradation rate during exploitation to achieve a predictable implant lifespan. The elaborated layers aim to mitigate the rapid corrosion of magnesium substrates by prolonging their bioresorption time and thus expanding their applicability in osseointegration. To evaluate this assumption, immersion tests in phosphate-buffered saline were performed, showing better chemical resistance of PEO coating and as-cast sample (for both mass gain by below 1%), and visible increase in mass of sample coated with organic coating (increase by almost 5%). Compressive strength results from numerical approach were further validated by experimental compression tests, showing that PEO coating deteriorated compressive strength by almost 3%, and organic coating improved it by over 9%. Results achieved in numerical approach were better than expected for stiffer sample, and slightly lower for the one with bigger pores.
Prostate cancer lesions in transition zone exhibit a higher propensity for pathological upgrading in radical prostatectomy
Authors: Chen Xin , Wang He , Wang Chaozhong , Qian Chengbo , Lin Yuxin , Huang Yuhua , Wei Xuedong , Hou Jianquan
Published: October 2024

Background

The varying malignancy and lethality of different grades of prostate cancer (PCa) highlight the importance of accurate diagnosis. This study aims to evaluate the upgrading of transition zone (TZ) prostate cancer biopsies and identify factors to improve TZ biopsy accuracy.

Materials and methods

This retrospective study included 217 patients who underwent laparoscopic radical prostatectomy after 12 + X cores transperineal transrectal ultrasound-magnetic resonance imaging (MRI)-guided targeted prostate biopsy from 2018 to 2021 in our center.

Results

Patients with TZ lesions showed a higher incidence of International Society of Urological Pathology (ISUP) grade upgrading from 1 to higher grade compared to peripheral zone lesions (16.9% vs. 5.0%, p = 0.005). Multivariate analysis confirmed TZ lesions as an independent risk factor (OR: 4.594, 97.5% CI: 1.569–15.238, p = 0.008) for upgrading from 1 to higher. Additionally, the number of positive biopsy cores (OR: 0.586, 97.5% CI: 0.336–0.891, p = 0.029) and anterior TZ lesion location (OR: 10.797, 97.5% CI: 1.503-248.727, p = 0.048) were independent factors for the upgrading in TZ patients.

Conclusions

This study found that PCa lesions located in the TZ, particularly the anterior TZ, have a higher risk of ISUP grade upgrading. This elevated risk arises from the insufficient distribution of biopsy cores around the TZ lesion. The findings underscore the importance of having an adequate number of biopsy cores around the lesion area to improve the accuracy of ISUP grade assessments.
Postoperative complications in patients with Behçet’s disease
Authors: Jung You Jin , Park Eun Hye , Kim Ju Yeon , Lee Eun Kyoung , Choi Yunhee , Lee Eun Bong
Published: October 2024

Objective

To assess the proportion of postoperative complications of various surgeries in patients with Behçet’s disease (BD) and compare the risk of surgical complications between BD patients and controls.

Methods

We analyzed 389 BD patients who underwent surgeries at Seoul National University Hospital between January 2003 and December 2019. Controls were 1:1 matched with BD patients based on age at surgery, sex, and type of surgery. Generalized estimating equation analyses were performed to compare the postoperative complications between BD patients and controls.

Results

Among 632 surgeries in BD patients, 36 (5.7%) surgical site complications, including wound dehiscence (38.9%), bleeding (13.9%), infections (8.3%), anastomotic dehiscence (22.2%), and stricture (5.6%), occurred after median 12 days (IQR 7.8–22.0). Surgical site complications developed frequently after cardiac (33.3%) and vascular (22.2%) surgeries and rarely occurred after ophthalmic (1.5%) surgeries. Seventeen (2.7%) cases required reoperation within median 15 days (IQR 7.0–43.0). Four patients died within median 21 days (IQR 8.3–41.3 days). After adjustment for confounders, BD patients exhibited a significantly higher risk of surgical site complications (OR 3.4, 95% CI 1.4–8.0) and reoperation (OR 5.2, 95% CI 1.2–22.8) after cardiovascular surgery than controls. However, the risks of surgical site complications and reoperation after other types of surgery were similar in both groups.

Conclusions

The risk of postoperative complications varies according to the type of surgeries among BD patients. While cardiovascular surgeries result in higher perioperative complications in BD patients, ophthalmic surgeries show a safety profile similar to those in non-BD patients.

Key Points• Patients with Behçet’s disease exhibited an increased risk of surgical site complications and subsequent reoperations after cardiovascular surgery than controls.• The safety profile of ophthalmic surgery was comparable between patients with Behçet’s disease and controls.• In patients with Behçet’s disease, the risk of postoperative complications varies according to the type of surgery.
Impact of age on surgical outcomes for world federation of neurosurgical societies grade I and II aneurysmal subarachnoid haemorrhage: a novel prognostic model using recursive partitioning analysis
Authors: Umekawa Motoyuki , Yoshikawa Gakushi
Published: October 2024

This study aimed to evaluate age as a prognostic factor and develop a comprehensive prognostic model for patients undergoing clipping surgery for World Federation of Neurosurgical Societies (WFNS) grade I/II aneurysmal subarachnoid haemorrhage (SAH). We retrospectively investigated 188 patients with WFNS grade I/II SAH who underwent microsurgical clipping at our institute between December 2010 and January 2020. The data of 176 patients (75 with grade I and 101 with grade II) were analysed. Data on patient demographics, aneurysm characteristics, SAH factors, surgical details, and clinical outcomes were collected. Prognostic factors were assessed using bivariate and multivariable logistic regression analyses, and recursive partitioning analysis. Favourable outcomes (mRS 0–2) were observed in 76% of patients. Age, a significant negative prognostic factor in multivariable analysis (odds ratio 0.55, 95% confidence interval 0.40–0.76, p < 0.001), was cutoff at 70 years by the receiver operating characteristic curve. Patients aged ≤ 70 years had significantly better outcomes than those aged > 70 years (84% vs. 46%, respectively; p < 0.001). Epileptic seizures were significantly associated with poor outcomes in older adults (p < 0.001). A prognostic model (favourable, intermediate, and poor) based on age and postoperative adverse events showed significantly different outcomes between age groups (p < 0.001). Age was a stronger prognostic factor than WFNS grading for patients with grade I/II SAH undergoing microsurgical clipping. For patients aged ≤ 70 years, precise microsurgeries with fewer complications were associated with favourable outcomes beyond WFNS grade. For older patients, postoperative intensive seizure management may prevent poor outcomes.
A review of time-series analysis for cyber security analytics: from intrusion detection to attack prediction
Authors: Landauer Max , Skopik Florian , Stojanović Branka , Flatscher Andreas , Ullrich Torsten
Published: October 2024

Understanding the current threat landscape as well as timely detection of imminent attacks are primary objectives of cyber security. Through time-series modeling of security data, such as event logs, alerts, or incidents, analysts take a step towards these goals. On the one hand, extrapolating time-series to predict future occurrences of attacks and vulnerabilities is able to support decision-making and preparation against threats. On the other hand, detection of model deviations as anomalies can point to suspicious outliers and thereby disclose cyber attacks. However, since the set of available techniques for time-series analysis is just as diverse as the research domains in the area of cyber security analytics, it can be difficult for analysts to understand which approaches fit the properties of security data at hand. This paper therefore conducts a broad literature review in research domains that leverage time-series analysis for cyber security analytics, with focus on available techniques, data sets, and challenges imposed by applications or feature properties. The results of our study indicate that relevant approaches range from detective systems ingesting short-term and low-level events to models that produce long-term forecasts of high-level attack cases.
The European energy crisis and the US natural gas market dynamics: a structural VAR investigation
Authors: Rubaszek Michał , Szafranek Karol
Published: October 2024

The Russian invasion of Ukraine triggered severe disruptions in the European energy market, causing also significant shifts in global natural gas flows. We investigate how this European shock has affected the dynamics and altered the estimates of the elasticities on the US natural gas market. We use the Bayesian Structural Vector Autoregression framework proposed by Baumeister and Hamilton (Am Econ Rev 109(5):1873–1910, 2019, BH) for the crude oil market and applied by Rubaszek et al. (Energy Econ 103:105526, 2021, RSU) to analyze the dynamics of the US natural gas market. By extending the RSU model for natural gas exports and imports and deriving model’s posterior using most recent data, we approximate the impact of the European energy crisis on the US natural gas market. We show that the estimates of the US natural gas market elasticities change due to our modification, while simply updating the same prior beliefs with most recent data impacts the posterior estimates to a very limited extent. We also find that a shock even as major as the European energy crisis has only marginally affected the US natural gas market, thus confirming the results from the literature that the EU and US natural gas markets evolve independently.
Lattice Fundamental Measure Theory Beyond 0D Cavities: Dimers on Square Lattices
Authors: Zimmermann Michael , Oettel Martin
Published: October 2024

Using classical density functional theory, we study the behavior of dimers, i.e. hard rods of length $$L=2$$

L
=
2

, on a two-dimensional cubic lattice. For deriving a free energy functional, we employ Levy’s prescription which is based on the minimization of a microscopic free energy with respect to the many-body probability under the constraint of a fixed density profile. Using that, we recover the "0D cavity" functional originally found by Lafuente and Cuesta and derive an extension by applying a more general "cluster density functional theory" method introduced by Lafuente and Cuesta as well. Moreover, we introduce a new free energy functional, which is based on approximated configurational probabilities. Both derived free energy functionals are exact on cavities that can hold at most two particles simultaneously. The first functional allows to improve the prediction of the free energy in bulk and both of them improve the prediction in highly confined systems, especially for high packing fractions, in comparison to the "0D cavity" functional.
Luigi Lugiato’s “Madmen, deranged, criminals”: Dostoevsky and Italian psychiatry after Cesare Lombroso
Authors: Ghidini Maria Candida
Published: October 2024

This essay provides an exploration of the intertwining realms of psychiatry and literature, focusing particularly on the case of Fyodor Dostoevsky. The paper gives an overview of the interest in Dostoevsky’s opus and biography displayed by Italian psychiatry, in particular by Cesare Lombroso and the connection he made between genius and mental illness. The essay is divided into two parts: the first, more theoretical, aims to address the question of the osmosis between psychiatry and literature, paying particular attention to the fact that, in the last twenty years of the nineteenth century, this osmosis seems to have centered mainly around Dostoevsky. The first section delves into the theoretical underpinnings of this intersection, highlighting the influence of figures like Cesare Lombroso and the attraction Dostoevsky’s works and biography held for psychiatrists and alienists. The second section examines Luigi Lugiato’s unpublished study on Dostoevsky. Luigi Lugiato (1879-1950), an Italian psychiatrist and alienist, is a perfect example to demonstrate how decades following Lombroso’s death and notwithstanding all the polemics and critiques surrounding his theories, his strong positivist paradigm continues to shape psychiatric analysis and remains influential in the European cultural panorama. The “law of contradiction”, observed in Dostoevsky’s works and life, permeates Lugiato’s own examination of the author.
Divergent trajectories of Arctic change: Implications for future socio-economic patterns
Authors: Tingstad Abbie , Van Abel Kristin , Bennett Mia M. , Winston Isabelle , Brigham Lawson W. , Stephenson Scott R. , Wilcox Margaret , Pezard Stephanie
Published: October 2024

Climate change is causing rapid warming in the Arctic, which, alongside other physical, socio-economic, cultural, geopolitical, and technological factors, is driving change in the far north. This research presents a conceptual model summarizing Arctic change factors which in turn was used in the design of a Delphi exercise which leveraged a variety of experts to forecast trajectories in different parts of the Arctic. Based on these experts’ expectations for economic and governance outcomes by 2050, we find that our results illustrate the “many Arctics” concept or some of the ways in which the Arctic is heterogenous now, and perhaps becoming increasingly so in the future. Sub-regions of the Arctic differed in expert expectations about the future of resource extraction, tourism, Indigenous self-determination, and military activity, among other outcomes. This work also discusses the post-2022 geopolitical situation and some potential implications of “many Arctics” for policy and future governance.
Gefühlt rechts
Authors: Kempke Kevin
Published: October 2024

In neurechten Reflexionen über das Lesen werden die Bildung und die Lektürefähigkeit der eigenen Szenemitglieder immer wieder krisenhaft verhandelt. Der Beitrag analysiert die Funktionen solcher ›Lesekrisen‹-Narrative und zeigt auf, in welchem Zusammenhang diese Thematisierungen mit den jeweils entwickelten Literaturkonzepten stehen. Ein Fokus liegt dabei auf dem Jungeuropa-Podcast Von rechts gelesen, der in Abgrenzung von dem in der Neuen Rechten hegemonialen Kubitschek-Kreis eine eigene, dezidiert als ›jung‹ markierte Programmatik entwirft. Das wird besonders an den jeweils unterschiedlichen affektiven Begründungen und Aufladungen der Lektüren verdeutlicht.
Yield curve extrapolation with machine learning
Authors: Akiyama Shinobu , Matsuyama Naoki
Published: October 2024

Yield curve extrapolation to unobservable tenors is a key technique for the market-consistent valuation of actuarial liabilities required by Solvency II and forthcoming similar regulations. Since the regulatory method, the Smith–Wilson method, is inconsistent with observable yield curve dynamics, parsimonious parametric models, the Nelson–Siegel model and its extensions, are often used for yield curve extrapolation in risk management. However, it is difficult for the parsimonious parametric models to extrapolate yield curves without excessive volatility because of their limited ability to represent observed yield curves with a limited number of parameters. To extend the representational capabilities, we propose a novel yield curve extrapolation method using machine learning. Using the long short-term memory architecture, we achieve purely data-driven yield curve extrapolation with better generalization performance, stability, and consistency with observed yield curve dynamics than the previous parsimonious parametric models on US and Japanese yield curve data. In addition, our method has model interpretability using the backpropagation algorithm. The findings of this study prove that neural networks, which have recently received considerable attention in mortality forecasting, are useful for yield curve extrapolation, where they have not been used before.
Multifaceted implementation strategy to improve the evaluation of penicillin allergies in perioperative patients: a pre-post feasibility implementation study
Authors: Carter Eileen J. , Zavez Katherine , Schramm Carol , Zolla Meagan M. , Baron Katelyn , Banach David B.
Published: October 2024

Objective:

The U.S. Centers for Disease Control and Prevention encourages nurses to evaluate penicillin allergies as part of hospital-based antibiotic stewardship programs. We evaluated the feasibility of an implementation strategy to improve nurses’ comprehensive documentation of penicillin allergies. We defined feasibility as the uptake and acceptability of documentation procedures.

Design:

Six-month pre-post feasibility implementation study.

Setting:

Outpatient surgical areas of an academic medical center located in the U.S.

Intervention:

The implementation strategy was guided by the Capability, Opportunity, Motivation Model for Behavior Change and included, building an interdisciplinary coalition to iteratively evaluate the implementation effort, educational meetings with surgical prescribers and perioperative nurses, the development and distribution of educational pocket cards, and structured communication messages in the electronic medical record.

Results:

A total of 426 patients with 487 penicillin allergy records (216 records pre-implementation period, 271 records post-implementation period) were analyzed. Penicillin allergy documentation contained the following information in the pre- versus post-implementation period: symptoms of the reaction (87% vs 87%), timing/years since reaction (8% vs 26%), onset of reaction in relation to taking penicillin (0% vs 21%), how symptoms resolved (0% vs 21%), and penicillin re-exposure (3% vs 21%). Focus groups revealed nurses perceived documentation procedures as highly acceptable. Major drivers of acceptability included the perceived effectiveness of a detailed allergy history and self-efficacy in conducting a detailed allergy history.

Conclusions:

Nurses perceived the comprehensive documentation of penicillin allergy history intervention as acceptable, and uptake improved following a theory-informed implementation strategy. We offer implementation strategy components to facilitate nurses’ engagement in penicillin allergy evaluation.
Operationalizing an adverse event detection surveillance system to support antimicrobial stewardship activities: perceptions and insights from the SHEA research network
Authors: Al Lawati Hawra J. , Harvey Kimberly L. , Shin Marlena , Mull Hillary , Lamkin Rebecca P. , Golenbock Samuel , Basnet-Thapa Dipandita , Strymish Judith M. , Lee Matthew , Gold Howard , Bidwell Goetz Matthew , Branch-Elliman Westyn
Published: October 2024

A surveillance system for measuring patient-level antimicrobial adverse drug events (ADE) may support stewardship activities, however, design and implementation questions remain. In this national survey, stewardship experts favored simple, laboratory-based ADE definitions although there were tensions between feasibility, ability to identify attribution without chart review, and importance of specific ADE.