bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance of amide proton transfer imaging to differentiate true progression from therapy-related changes in gliomas and metastases
Authors: Essed Rajeev A. , Prysiazhniuk Yeva , Wamelink Ivar J. , Azizova Aynur , Keil Vera C.
Published: August 2024

Objectives

Differentiating true progression or recurrence (TP/TR) from therapy-related changes (TRC) is complex in brain tumours. Amide proton transfer-weighted (APT) imaging is a chemical exchange saturation transfer (CEST) MRI technique that may improve diagnostic accuracy during radiological follow-up. This systematic review and meta-analysis elucidated the level of evidence and details of state-of-the-art imaging for APT-CEST in glioma and brain metastasis surveillance.

Methods

PubMed, EMBASE, Web of Science, and Cochrane Library were systematically searched for original articles about glioma and metastasis patients who received APT-CEST imaging for suspected TP/TR within 2 years after (chemo)radiotherapy completion. Modified Quality Assessment of Diagnostic Accuracy Studies-2 criteria were applied. A meta-analysis was performed to pool results and to compare subgroups.

Results

Fifteen studies were included for a narrative synthesis, twelve of which (500 patients) were deemed sufficiently homogeneous for a meta-analysis. Magnetisation transfer ratio asymmetry performed well in gliomas (sensitivity 0.88 [0.82–0.92], specificity 0.84 [0.72–0.91]) but not in metastases (sensitivity 0.64 [0.38–0.84], specificity 0.56 [0.33–0.77]). APT-CEST combined with conventional/advanced MRI rendered 0.92 [0.86–0.96] and 0.88 [0.72–0.95] in gliomas. Tumour type, TR prevalence, sex, and acquisition protocol were sources of significant inter-study heterogeneity in sensitivity (I
2 = 62.25%; p < 0.01) and specificity (I
2 = 66.31%; p < 0.001).

Conclusion

A growing body of literature suggests that APT-CEST is a promising technique for improving the discrimination of TP/TR from TRC in gliomas, with limited data on metastases.

Clinical relevance statement

This meta-analysis identified a utility for APT-CEST imaging regarding the non-invasive discrimination of brain tumour progression from therapy-related changes, providing a critical evaluation of sequence parameters and cut-off values, which can be used to improve response assessment and patient outcome.

Key Points

Therapy-related changes mimicking progression complicate brain tumour treatment.

Amide proton imaging improves the non-invasive discrimination of glioma progression from therapy-related changes.

Magnetisation transfer ratio asymmetry measurement seems not to have added value in brain metastases.
Perioperative and extended outcomes of patients undergoing parastomal hernia repair following cystectomy and ileal conduit
Authors: Haque Taseen F. , Ghoreifi Alireza , Sheybaee Moghaddam Farshad , Kaneko Masatomo , Ginsberg David , Sotelo Rene , Gill Inderbir , Desai Mihir , Aron Monish , Schuckman Anne , Daneshmand Siamak , Djaladat Hooman
Published: August 2024

Purpose

To report perioperative and long-term postoperative outcomes of cystectomy patients with ileal conduit (IC) urinary diversion undergoing parastomal hernia (PSH) repair.

Method

We reviewed patients who underwent cystectomy and IC diversion between 2003 and 2022 in our center. Baseline variables, including surgical approach of PSH repair and repair technique, were captured. Multivariable Cox regressionanalysis was performed to test for the associations between different variables and PSH recurrence.

Results

Thirty-six patients with a median (IQR) age of 79 (73–82) years were included. The median time between cystectomy and PSH repair was 30 (14–49) months. Most PSH repairs (32/36, 89%) were performed electively, while 4 were due to small bowel obstruction. Hernia repairs were performed through open (n=25), robotic (10), and laparoscopic approaches (1). Surgical techniques included direct repair with mesh (20), direct repair without mesh (4), stoma relocation with mesh (5), and stomarelocation without mesh (7). The 90-day complication rate was 28%. In a median follow-up of 24 (7–47) months, 17 patients (47%) had a recurrence. The median time to recurrence was 9 (7–24) months. On multivariable analysis, 90-day complication following PSH repair was associated with an increased risk of recurrence.

Conclusions

In this report of one of the largest series of PSH repair in the Urology literature, 47% of patients had a recurrence following hernia repair with a median follow-up time of 2 years. There was no significant difference in recurrence rates when comparing repair technique or the use of open or minimally invasive approaches.
Extensive macular atrophy with pseudodrusen-like appearance: comprehensive review of the literature
Authors: Carlà Matteo Mario , Giannuzzi Federico , Boselli Francesco , Crincoli Emanuele , Rizzo Stanislao
Published: August 2024

Purpose

This review focuses on extensive macular atrophy with pseudodrusen-like appearance (EMAP), a recently described maculopathy presenting with pseudodrusen-like lesions and chorioretinal atrophy more pronounced in the vertical axis.

Methods

Narrative review of the literature published until May 2024.

Results

The early onset age of EMAP (50–55 years) and its distinctive natural history, which includes night blindness followed by severe vision loss, differentiate it from atrophic age-related macular degeneration (AMD). A clear pathogenesis has not been determined, but risk factors include female gender and complement system abnormalities (altered levels of C3 and CH50). Moreover, lifelong exposure to pesticides has been suggested as risk factor for direct neuronal degeneration involving rods and cones. In the early phase of the disease, reticular pseudodrusen-like lesions appear in the superior perifovea and tend to coalescence horizontally into a flat, continuous, reflective material localized between the retinal pigmented epithelium and Bruch’s membrane. Over time, EMAP causes profound RPE and outer retinal atrophy in the macular area, with a recent classification reporting a 3-stages evolution pattern. Blue autofluorescence showed rapidly evolving atrophy with either hyperautofluorescent or isoautofluorescent borders. Significant similarities between the diffuse-trickling phenotype of geographic atrophy and EMAP have been reported. Macular neovascularization is a possible complication.

Conclusion

EMAP is specific form of early-onset atrophic macular degeneration with rapid evolution and no treatment. Further studies are needed to assess the best management.
Conditional image-to-image translation generative adversarial network (cGAN) for fabric defect data augmentation
Authors: Mohammed Swash Sami , Clarke Hülya Gökalp
Published: August 2024

The availability of comprehensive datasets is a crucial challenge for developing artificial intelligence (AI) models in various applications and fields. The lack of large and diverse public fabric defect datasets forms a major obstacle to properly and accurately developing and training AI models for detecting and classifying fabric defects in real-life applications. Models trained on limited datasets struggle to identify underrepresented defects, reducing their practicality. To address these issues, this study suggests using a conditional generative adversarial network (cGAN) for fabric defect data augmentation. The proposed image-to-image translator GAN features a conditional U-Net generator and a 6-layered PatchGAN discriminator. The conditional U-Network (U-Net) generator can produce highly realistic synthetic defective samples and offers the ability to control various characteristics of the generated samples by taking two input images: a segmented defect mask and a clean fabric image. The segmented defect mask provides information about various aspects of the defects to be added to the clean fabric sample, including their type, shape, size, and location. By augmenting the training dataset with diverse and realistic synthetic samples, the AI models can learn to identify a broader range of defects more accurately. This technique helps overcome the limitations of small or unvaried datasets, leading to improved defect detection accuracy and generalizability. Moreover, this proposed augmentation method can find applications in other challenging fields, such as generating synthetic samples for medical imaging datasets related to brain and lung tumors.
Vpit: real-time embedded single object 3D tracking using voxel pseudo images
Authors: Oleksiienko Illia , Nousi Paraskevi , Passalis Nikolaos , Tefas Anastasios , Iosifidis Alexandros
Published: August 2024

In this paper, we propose a novel voxel-based 3D single object tracking (3D SOT) method called Voxel Pseudo Image Tracking (VPIT). VPIT is the first method that uses voxel pseudo images for 3D SOT. The input point cloud is structured by pillar-based voxelization, and the resulting pseudo image is used as an input to a 2D-like Siamese SOT method. The pseudo image is created in the Bird’s-eye View (BEV) coordinates; and therefore, the objects in it have constant size. Thus, only the object rotation can change in the new coordinate system and not the object scale. For this reason, we replace multi-scale search with a multi-rotation search, where differently rotated search regions are compared against a single target representation to predict both position and rotation of the object. Experiments on KITTI [1] Tracking dataset show that VPIT is the fastest 3D SOT method and maintains competitive Success and Precision values. Application of a SOT method in a real-world scenario meets with limitations such as lower computational capabilities of embedded devices and a latency-unforgiving environment, where the method is forced to skip certain data frames if the inference speed is not high enough. We implement a real-time evaluation protocol and show that other methods lose most of their performance on embedded devices; while, VPIT maintains its ability to track the object.
Incremental federated learning for traffic flow classification in heterogeneous data scenarios
Authors: Pekar Adrian , Makara Laszlo Arpad , Biczok Gergely
Published: August 2024

This paper explores the comparative analysis of federated learning (FL) and centralized learning (CL) models in the context of multi-class traffic flow classification for network applications, a timely study in the context of increasing privacy preservation concerns. Unlike existing literature that often omits detailed class-wise performance evaluation, and consistent data handling and feature selection approaches, our study rectifies these gaps by implementing a feed-forward neural network and assessing FL performance under both independent and identically distributed (IID) and non-independent and identically distributed (non-IID) conditions, with a particular focus on incremental training. In our cross-silo experimental setup involving five clients per round, FL models exhibit notable adaptability. Under IID conditions, the accuracy of the FL model peaked at 96.65%, demonstrating its robustness. Moreover, despite the challenges presented by non-IID environments, our FL models demonstrated significant resilience, adapting incrementally over rounds to optimize performance; in most scenarios, our FL models performed comparably to the idealistic CL model regarding multiple well-established metrics. Through a comprehensive traffic flow classification use case, this work (i) contributes to a better understanding of the capabilities and limitations of FL, offering valuable insights for the real-world deployment of FL, and (ii) provides a novel, large, carefully curated traffic flow dataset for the research community.
The Principles of Evaluating the Risk of Rock and Gas Outburst in Copper Ore Mines
Authors: Skoczylas Norbert , Kozieł Katarzyna , Sitek Libor
Published: August 2024

Rock and gas outburst is one of the most significant natural hazards faced by the mining industry. In the last decade, this issue has appeared in firm rock mining (including copper ore mines) in addition to coal mining. A number of methods have been developed for coal mining to assess the hazard posed by gasogeodynamic phenomena, but in the case of copper ore mines, no studies have led to forecasts of this risk. To face the challenge, the authors decided to propose their own concept of risk assessment principles based on a threshold analysis of the phenomenon and a continuous analysis using fuzzy logic. A series of tests were performed to support the paper, investigating selected parameters which directly affect the risk. The evaluation principles for gasogeodynamic phenomena presented herein were the result of experimental investigations carried out by the authors.
Design, synthesis, and biological evaluation of novel halogenated chlorido[N,N′-bis(salicylidene)-1,2-bis(3-methoxyphenyl)ethylenediamine]iron(III) complexes as anticancer agents
Authors: Bernkop-Schnürch Astrid Dagmar , Huber Klaus , Clauser Armida , Cziferszky Monika , Leitner Daniel , Talasz Heribert , Hermann Martin , Hohloch Stephan , Gust Ronald , Kircher Brigitte
Published: August 2024

Iron(III) complexes based on N,N´-bis(salicylidene)ethylenediamine (salene) scaffolds have demonstrated promising anticancer features like induction of ferroptosis, an iron dependent cell death. Since poor cellular uptake limits their therapeutical potential, this study aimed to enhance the lipophilic character of chlorido[N,N′-bis(salicylidene)-1,2-bis(3-methoxyphenyl)ethylenediamine]iron(III) complexes by introducing lipophilicity improving ligands such as fluorine (X1), chlorine (X2) and bromine (X3) in 5-position in the salicylidene moieties. After detailed characterization the binding to nucleophiles, logP values and cellular uptake were determined. The complexes were further evaluated regarding their biological activity on MDA-MB 231 mammary carcinoma, the non-tumorous SV-80 fibroblast, HS-5 stroma and MCF-10A mammary gland cell lines. Stability of the complexes in aqueous and biological environments was proven by the lack of interactions with amino acids and glutathione. Cellular uptake was positively correlated with the logP values, indicating that higher lipophilicity enhanced cellular uptake. The complexes induced strong antiproliferative and antimetabolic effects on MDA-MB 231 cells, but were inactive on all non-malignant cells tested. Generation of mitochondrial reactive oxygen species, increase of lipid peroxidation and induction of both ferroptosis and necroptosis were identified as mechanisms of action. In conclusion, halogenation of chlorido[N,N′-bis(salicylidene)-1,2-bis(3-methoxyphenyl)ethylenediamine]iron(III) complexes raises their lipophilic character resulting in improved cellular uptake.

Graphical abstract
Effectiveness and safety of rituximab in severely relapsed antineutrophil cytoplasmic antibody–associated vasculitis: a retrospective analysis of a Japanese multicentre cohort from the J-CANVAS
Authors: Kidoguchi Genki , Yoshida Yusuke , Watanabe Hirofumi , Sugimoto Tomohiro , Mokuda Sho , Kida Takashi , Yajima Nobuyuki , Omura Satoshi , Nakagomi Daiki , Abe Yoshiyuki , Kadoya Masatoshi , Takizawa Naoho , Nomura Atsushi , Kukida Yuji , Kondo Naoya , Yamano Yasuhiko , Yanagida Takuya , Endo Koji , Matsui Kiyoshi , Takeuchi Tohru , Ichinose Kunihiro , Kato Masaru , Yanai Ryo , Matsuo Yusuke , Shimojima Yasuhiro , Nishioka Ryo , Okazaki Ryota , Takata Tomoaki , Ito Takafumi , Moriyama Mayuko , Takatani Ayuko , Miyawaki Yoshia , Ito-Ihara Toshiko , Kawaguchi Takashi , Kawahito Yutaka , Hirata Shintaro ,   on behalf of Japan Collaborative Registry of ANCA-Associated Vasculitis (J-CANVAS)
Published: August 2024

We aimed to clarify the long-term safety and efficacy of rituximab (RTX) as a remission induction therapy following severe relapse in patients with antineutrophil cytoplasmic antibody (ANCA)–associated vasculitis (AAV). We retrospectively collected the data of patients with severely relapsed AAV from a Japanese multicentre cohort. The primary exposure was RTX use; the primary outcome was complete remission (CR) proportions at week 24. Baseline characteristics were compared between the RTX and non-RTX groups. We performed multivariate logistic regression analysis and one-to-one propensity score matching analysis as a sensitivity analysis. Totally, 100 patients were enrolled: 52 in the RTX group and 48 in the non-RTX group. Baseline characteristics were comparable between the two groups, except for age, AAV subtype and ANCA serotype. The median age was 71 vs. 75 years, and the PR3-ANCA positivity rate was 44.2% vs. 18.8% in the RTX and non-RTX groups, respectively. No significant difference was observed in CR proportions at week 24 between the two groups (79.2% vs. 68.1%, p = 0.321), with an adjusted odds ratio of 1.27 (95% confidence interval [CI] 0.47–3.51). At week 48, CR proportions were significantly higher in the RTX group (91.7% vs. 64.9%, p = 0.005), with an adjusted odds ratio of 2.95 (95% CI 0.97–9.91). Serious infection rates were lower in the RTX group than in the non-RTX group, with no statistically significant difference. RTX was not superior to conventional immunosuppressive therapies at week 24 but showed significantly favourable results at week 48 for severely relapsed AAV.

Key Points

• RTX might be superior to traditional treatments as an induction therapy for severely relapsed AAV.• RTX has the potential to sustain long-term remission with fewer occurrences of infections in the treatment of severely relapsed AAV.
Predicting satisfaction with democracy in Germany using local economic conditions, social capital, and individual characteristics
Authors: Friehe Tim , Pfeifer Christian
Published: August 2024

This paper explores the empirical relationship between local economic conditions, social capital, and individual characteristics on the one hand and satisfaction with democracy on the other hand, using detailed information from the German Socio-Economic Panel. In contrast to previous literature, we focus on economic conditions at the state level instead of the national one. We find that local economic conditions, proxies of social capital, and individual characteristics (e.g., risk attitude, reciprocity, past unemployment experience) are important correlates of satisfaction with democracy and that some heterogeneity between genders, West and East Germany, and people with and without college degree exists in the data.
Real-world experience with CDK4/6 inhibitors in hormone receptor-positive metastatic and recurrent breast cancer: findings from an Asian population
Authors: Chen Bo-Fang , Tsai Yi-Fang , Chao Ta-Chung , Lien Pei-Ju , Lin Yen-Shu , Feng Chin-Jung , Chen Yen-Jen , Cheng Han-Fang , Liu Chun-Yu , Lai Jiun-I , Tseng Ling-Ming , Huang Chi-Cheng
Published: August 2024

Purpose

Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) combined with endocrine therapy have demonstrated significant clinical benefits in progression-free and overall survival. This study investigates the outcomes associated with two kinds of CDK4/6i in patients with hormone receptor (HR)-positive metastatic and relapsed breast cancer to inform real-world evidence of treatment strategies.

Methods

This retrospective study included 340 Taiwanese patients with HR-positive advanced breast cancer from the Taipei Veterans General Hospital, between 2018 and 2023. We analyzed patient characteristics, treatment strategies and outcomes associated with two CDK4/6i. The efficacy of patients who experienced economic burden and interrupted CDK4/6i treatment after 2 years of National Health Insurance (NHI) reimbursement was also investigated.

Results

Patients receiving ribociclib and palbociclib showed no significant differences in age, histology, body mass index(BMI), or pathologic status. The distribution of disease status and endocrine therapy partners was comparable between the two groups. Dose reduction was similar, while patients with palbociclib tended to discontinue CDK4/6i usage, and those with ribociclib tended to switch to the other CDK4/6i or endocrine partners. There was no significant difference in progression-free survival (PFS) between the two CDK4/6i in the first-line setting. Adverse prognostic factors were increasing HER2 IHC score, higher Ki-67 levels, visceral and liver metastasis, prior chemotherapy, and endocrine therapy resistance, while higher BMI, bone-only metastasis, and letrozole treatment were associated with a lower risk of progression. The limited follow-up time in our study was insufficient to assess the outcomes of patients treated with interrupted CDK4/6i for up to two years under the NHI reimbursement policy.

Conclusion

Treatment outcomes between the two types of CDK4/6i did not differ significantly, indicating the safety and efficacy of CDK4/6i for the Asian population. Ribociclib and palbociclib showed similar efficacy in PFS in the real-world setting.
Domain generalization for semantic segmentation: a survey
Authors: Rafi Taki Hasan , Mahjabin Ratul , Ghosh Emon , Ko Young-Woong , Lee Jeong-Gun
Published: August 2024

Deep neural networks (DNNs) have proven explicit contributions in making autonomous driving cars and related tasks such as semantic segmentation, motion tracking, object detection, sensor fusion, and planning. However, in challenging situations, DNNs are not generalizable because of the inherent domain shift due to the nature of training under the i.i.d. assumption. The goal of semantic segmentation is to preserve information from a given image into multiple meaningful categories for visual understanding. Particularly for semantic segmentation, pixel-wise annotation is extremely costly and not always feasible. Domain generalization for semantic segmentation aims to learn pixel-level semantic labels from multiple source domains and generalize to predict pixel-level semantic labels on multiple unseen target domains. In this survey, for the first time, we present a comprehensive review of DG for semantic segmentation. we present a comprehensive summary of recent works related to domain generalization in semantic segmentation, which establishes the importance of generalizing to new environments of segmentation models. Although domain adaptation has gained more attention in segmentation tasks than domain generalization, it is still worth unveiling new trends that are adopted from domain generalization methods in semantic segmentation. We cover most of the recent and dominant DG methods in the context of semantic segmentation and also provide some other related applications. We conclude this survey by highlighting the future directions in this area.
An in-depth survey of the artificial gorilla troops optimizer: outcomes, variations, and applications
Authors: Hussien Abdelazim G. , Bouaouda Anas , Alzaqebah Abdullah , Kumar Sumit , Hu Gang , Jia Heming
Published: August 2024

A recently developed algorithm inspired by natural processes, known as the Artificial Gorilla Troops Optimizer (GTO), boasts a straightforward structure, unique stabilizing features, and notably high effectiveness. Its primary objective is to efficiently find solutions for a wide array of challenges, whether they involve constraints or not. The GTO takes its inspiration from the behavior of Gorilla Troops in the natural world. To emulate the impact of gorillas at each stage of the search process, the GTO employs a flexible weighting mechanism rooted in its concept. Its exceptional qualities, including its independence from derivatives, lack of parameters, user-friendliness, adaptability, and simplicity, have resulted in its rapid adoption for addressing various optimization challenges. This review is dedicated to the examination and discussion of the foundational research that forms the basis of the GTO. It delves into the evolution of this algorithm, drawing insights from 112 research studies that highlight its effectiveness. Additionally, it explores proposed enhancements to the GTO’s behavior, with a specific focus on aligning the geometry of the search area with real-world optimization problems. The review also introduces the GTO solver, providing details about its identification and organization, and demonstrates its application in various optimization scenarios. Furthermore, it provides a critical assessment of the convergence behavior while addressing the primary limitation of the GTO. In conclusion, this review summarizes the key findings of the study and suggests potential avenues for future advancements and adaptations related to the GTO.
Spatiotemporal patterns of public attention to invasive species across an invasion front: a case study of lionfish (Pterois miles) from the Mediterranean Sea
Authors: Fazzari Lara , Vardi Reut , Jaric Ivan , Correia Ricardo A. , Coll Marta , Sbragaglia Valerio
Published: August 2024

Understanding societal interest in invasive species is crucial as greater public attention can support the success of conservation efforts. One of the main challenges in monitoring societal interest to support conservation is the absence of near-real-time indicators to track large-scale spatiotemporal dynamics of public attention. However, the digital revolution has opened up new opportunities to develop such indicators in support of invasive species research and management. Here, we aim to evaluate public awareness and interest in the invasive lionfish (Pterois miles) in the Mediterranean Sea and investigate spatiotemporal patterns of public interest in the species along its invasion front by using Google search volumes as a proxy for public attention. We implemented topic searches for the lionfish to download Google search volumes from 2013 to 2022 and used these data to test two hypotheses: (1) countries experiencing lionfish invasion exhibit higher public attention than those without lionfish, and (2) in invaded countries, public attention peaks around the arrival year, followed by a decline to baseline levels. Our study confirmed the first hypothesis, showing higher public attention in invaded countries. However, temporal patterns of attention did not fully align with the year of lionfish arrival, suggesting that the socio-political complexity of the region (e.g., cultural trends or internet accessibility), may be a key aspect to consider in future studies. Overall our study shows that digital data sources provide a unique opportunity to monitor social aspects of biological invasions with low associated costs and quick access to a great amount of data generated by internet users.
Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds
Authors: Ryan Kevin A. , Garayburu-Caruso Vanessa A. , Crump Byron C. , Bambakidis Ted , Raymond Peter A. , Liu Shaoda , Stegen James C.
Published: August 2024

Quantifying the relative influence of factors and processes controlling riverine ecosystem function is essential to predicting future conditions under global change. Dissolved organic matter (DOM) is a fundamental component of riverine ecosystems that fuels microbial food webs, influences nutrient and light availability, and represents a significant carbon flux globally. The heterogeneous nature of DOM molecular composition and its propensity for interaction (i.e., functional diversity) can characterize riverine ecosystem function across spatiotemporal scales. To investigate fundamental drivers of DOM diversity, we collected seasonal water samples from 42 nested locations within five watersheds spanning multiple watershed sizes (~ 5 to 30,000 km2) across the United States. Patterns in DOM molecular richness, aromaticity, relative abundance of N-containing formulas, and putative biochemical transformations derived from high-resolution mass spectrometry were assessed across gradients of explanatory variables associated with watershed characteristics (e.g., watershed area, water residence time, land cover). We found that putative biochemical transformations were more strongly related to explanatory variables across watersheds than common bulk DOM parameters and that watershed area, surface water residence time and derived Damköhler numbers representing DOM reactivity timescales were strong predictors of DOM diversity. The data also indicate that catchment-specific land cover factors can significantly influence DOM diversity in diverging directions. Overall, the results highlight the importance of considering water residence time and land cover when interpreting longitudinal patterns in DOM chemistry and the continued challenge of identifying generalizable drivers that are transferable across watershed and regional scales for application in Earth system models. This work also introduces a Findable Accessible Interoperable Reusable (FAIR) dataset (> 300 samples) to the community for future syntheses.
Spotting Portfolio Greenwashing in Environmental Funds
Authors: Abouarab Rabab , Mishra Tapas , Wolfe Simon
Published: August 2024

This paper examines greenwashing practices in environmental funds. We utilize a unique data set of US equity mutual fund holdings between 2012 and 2021 to calculate the funds’ carbon footprints. Using a difference-in-differences analysis, we find that, following their commitments to sustainability, environmental funds fail to reduce their carbon footprints relative to a matched group of conventional funds. We also find, using an event study, a significant increase in the flows of environmental funds in response to these commitments. The combination of the failure to reduce carbon footprints and the surge in inflows provides evidence of greenwashing by environmental funds, raising concerns about their fiduciary duty. Our findings also show that greenwashers tend to initially have low flows and high portfolio carbon emissions suggesting that they announce their commitments to sustainability just to attract investors.
Dynamics in Realized Volatility Forecasting: Evaluating GARCH Models and Deep Learning Algorithms Across Parameter Variations
Authors: Akgun Omer Burak , Gulay Emrah
Published: August 2024

The modeling and forecasting of return volatility for the top three cryptocurrencies, which are identified by the highest trading volumes, is the main focus of the study. Eleven different GARCH-type models were analyzed using a comprehensive methodology in six different distributions, and deep learning algorithms were used to rigorously assess each model’s forecasting performance. Additionally, the study investigates the impact of selecting dynamic parameters for the forecasting performance of these models. This study investigates if there are any appreciable differences in forecast outcomes between the two different realized variance calculations and variations in training size. Further investigation focuses on how the use of expanding and rolling windows affects the optimal window type for forecasting. Finally, the importance of choosing different error measurements is emphasized in the framework of comparing forecasting performances. Our results indicate that in GARCH-type models, 5-minute realized variance shows the best forecasting performance, while in deep learning models, median realized variance (MedRV) has the best performance. Moreover, it has been determined that an increase in the training/test ratio and the selection of the rolling window approach both play important roles in achieving better forecast accuracy. Finally, our results show that deep learning models outperform GARCH-type models in volatility forecasts.
Static analysis driven enhancements for comprehension in machine learning notebooks
Authors: Venkatesh Ashwin Prasad Shivarpatna , Sabu Samkutty , Chekkapalli Mouli , Wang Jiawei , Li Li , Bodden Eric
Published: August 2024

Jupyter notebooks have emerged as the predominant tool for data scientists to develop and share machine learning solutions, primarily using Python as the programming language. Despite their widespread adoption, a significant fraction of these notebooks, when shared on public repositories, suffer from insufficient documentation and a lack of coherent narrative. Such shortcomings compromise the readability and understandability of the notebook. Addressing this shortcoming, this paper introduces HeaderGen, a tool-based approach that automatically augments code cells in these notebooks with descriptive markdown headers, derived from a predefined taxonomy of machine learning operations. Additionally, it systematically classifies and displays function calls in line with this taxonomy. The mechanism that powers HeaderGen is an enhanced call graph analysis technique, building upon the foundational analysis available in PyCG. To improve precision, HeaderGen extends PyCG’s analysis with return-type resolution of external function calls, type inference, and flow-sensitivity. Furthermore, leveraging type information, HeaderGen employs pattern matching techniques on the code syntax to annotate code cells. We conducted an empirical evaluation on 15 real-world Jupyter notebooks sourced from Kaggle. The results indicate a high accuracy in call graph analysis, with precision at 95.6% and recall at 95.3%. The header generation has a precision of 85.7% and a recall rate of 92.8% with regard to headers created manually by experts. A user study corroborated the practical utility of HeaderGen, revealing that users found HeaderGen useful in tasks related to comprehension and navigation. To further evaluate the type inference capability of static analysis tools, we introduce TypeEvalPy, a framework for evaluating type inference tools for Python with an in-built micro-benchmark containing 154 code snippets and 845 type annotations in the ground truth. Our comparative analysis on four tools revealed that HeaderGen outperforms other tools in exact matches with the ground truth.
A Graph Multi-separator Problem for Image Segmentation
Authors: Irmai Jannik , Zhao Shengxian , Schöne Mark , Presberger Jannik , Andres Bjoern
Published: August 2024

We propose a novel abstraction of the image segmentation task in the form of a combinatorial optimization problem that we call the multi-separator problem. Feasible solutions indicate for every pixel whether it belongs to a segment or a segment separator, and indicate for pairs of pixels whether or not the pixels belong to the same segment. This is in contrast to the closely related lifted multicut problem, where every pixel is associated with a segment and no pixel explicitly represents a separating structure. While the multi-separator problem is np-hard, we identify two special cases for which it can be solved efficiently. Moreover, we define two local search algorithms for the general case and demonstrate their effectiveness in segmenting simulated volume images of foam cells and filaments.
A two-phase sequential algorithm for global optimization of the standard quadratic programming problem
Authors: Júdice Joaquim , Sessa Valentina , Fukushima Masao
Published: August 2024

We introduce a new sequential algorithm for the Standard Quadratic Programming Problem (StQP), which exploits a formulation of StQP as a Linear Program with Linear Complementarity Constraints (LPLCC). The algorithm is finite and guarantees at least in theory a $$\delta $$
δ
-approximate global minimum for an arbitrary small $$\delta $$
δ
, which is a global minimum in practice. The sequential algorithm has two phases. In Phase 1, Stationary Points (SP) with strictly decreasing objective function values are computed. Phase 2 is designed for giving a certificate of global optimality for the last SP computed in Phase 1. Two different Nonlinear Programming Formulations for LPLCC are proposed for each one of these phases, which are solved by efficient enumerative algorithms. New procedures for computing a lower bound for StQP are also proposed, which are easy to implement and give tight bounds in general. Computational experiments with a number of test problems from known sources indicate that the two-phase sequential algorithm is, in general, efficient in practice. Furthermore, the algorithm seems to be an efficient way to study the copositivity of a matrix by exploiting an StQP with this matrix.
Managing the threat of decoupling in the U.S. affordable housing industry
Authors: Read Dustin C. , Sedgwick Donna
Published: August 2024

Decoupling, or the practice of communicating different organizational values and goals than those rigorously pursued, is a concept discussed in the organization theory literature. Organizations engage in it when their legitimacy hinges on obtaining the support of stakeholders with disparate interests, and they attempt to appease some stakeholders with words and others with actions. One problem with decoupling is that it can lead organizations to operate in ways that are not reflective of their stated missions. With this concern in mind, the analysis presented here explores the prevalence of decoupling in the U.S. affordable housing industry and considers how, when, and why it occurs, and to what effect. Thematic analysis of interview data collected from industry practitioners suggests decoupling is common, comes in multiple forms, and must be effectively managed if municipal governments hope to partner with for-profit and nonprofit affordable housing providers to achieve their social policy goals.
Berry–Esseen-Type Estimates for Random Variables with a Sparse Dependency Graph
Authors: Janisch Maximilian , Lehéricy Thomas
Published: August 2024

We obtain Berry–Esseen-type bounds for the sum of random variables with a dependency graph and uniformly bounded moments of order $$\delta \in (2,\infty ]$$

δ
∈
(
2
,
∞
]

using a Fourier transform approach. Our bounds improve the state-of-the-art obtained by Stein’s method in the regime where the degree of the dependency graph is large.
Isothermal crystallization kinetics of commercial PA66 and PA11
Authors: Vázquez Laura S. , Pereira Mercedes , Díaz-Díaz Ana-María , López-Beceiro Jorge , Artiaga Ramón
Published: August 2024

This study is aimed at investigating the crystallization kinetics of two structurally related polymers, Nylon 6,6 (PA66) and Nylon 11 (PA11), by differential scanning calorimetry (DSC) in the scope of a logistic-based model using a model fitting approach. By this method, the values of the rate parameters for each specific temperature are obtained from fitting all points of the crystallization exotherm that were accurately recorded at that temperature. This method differs from Arrhenius-based model fitting approaches, in which the initial and final parts of the exotherm do not usually match the shape of Arrhenius-based models and are therefore discarded for fitting. Furthermore, in other kinetic approaches that fall outside the scope of this article, kinetic parameters are typically obtained from specific points in the crystallization exotherm, and good fits cannot generally be obtained nor is that the goal of those approaches. The DSC curves of both polymers obtained at different temperatures are analysed to determine the crystallization kinetics. One of the most insightful parameters of the model is the crystallization rate. Its dependence on temperature is analysed for both polymers and compared to others. The other parameters can also help to better understand some of the crystallization features of these polymers. In addition, the information retrieved from this study can be useful to adjust processing conditions.
Balancing riderless electric scooters at zero speed in the presence of a feedback delay
Authors: Horvath Hanna Zsofia , Takacs Denes
Published: August 2024

The nonlinear dynamics of electric scooters are investigated using a spatial mechanical model. The equations of motion are derived with the help of Kane’s method. Two control algorithms are designed in order to balance the e-scooter in a vertical position at zero forward speed. Hierarchical, linear state feedback controllers with feedback delay are considered. In the case of a delay-free controller, the linear stability properties are analyzed analytically, with the help of the Routh–Hurwitz criteria. The linear stability charts of the delayed controllers are constructed with the help of the D-subdivision method and semi-discretization. The control gains of the controllers are optimized with respect to the robustness against perturbations. The effects of the feedback delay of the controllers, the rake angle, the trail, and the center of gravity of the handlebar on the linear stability are shown. The performance of the control algorithms is verified by means of numerical simulations.
Correlation between shear wave velocity (Vs) and penetration resistance along with the stress condition of Eskisehir(Turkey) case
Authors: Civelekler Ebru , Afacan Kamil B.
Published: August 2024

Shear wave velocity (Vs) is an important characteristic in geotechnical earthquake engineering practices for estimating site response. Seismic refraction and well seismicity are the common ways to determine the shear wave velocity. However, these methods require on-site land studies. For this reason, there are empirical approaches that have been proposed to calculate Vs depending on the number of SPT-N obtained from the Standard Penetration experiment data. Studies in the literature have different aspects and correspond to varied empirical approaches. The study aims to establish empirical correlations between the Shear Wave Velocity (Vs), Standard Penetration Test results (SPT-N), and stress conditions of soils considering the soil types of the local sites in Eskişehir, Turkey. The Vs values of the soil from the data set we used in this study were obtained from seismic refraction-reflection studies in 22 different locations in Eskişehir. SPT-N values obtained from 42 boreholes representing the Eskişehir ground were used. The Vs values calculated from the empirical approaches given depending on the SPT-N values and the Vs values measured on the site were compared. In addition, regression analyses were performed between SPT- N and Vs. As a result of the regression analyses performed, new empirical correlations were developed according to soil types. Finally, new empirical correlations are established that can predict Vs at different soil depths and conditions taking the soil type and overburden pressure into account and contributing valuable insights for geotechnical earthquake engineering purpose. The regressions show that there is a good correlation between the Vs-SPT-N along with the total stress with high R2s and soil types are effective on predicting the shear wave velocity.
(Un)usual advocacy coalitions in a multi-system setting: the case of hydrogen in Germany
Authors: Löhr Meike , Markard Jochen , Ohlendorf Nils
Published: August 2024

Grand sustainability challenges span multiple sectors and fields of policymaking. Novel technologies that respond to these challenges may trigger the emergence of new policy subsystems at the intersection of established sectors. We develop a framework that addresses the complexities of ‘multi-system settings.’ Empirically, we explore belief and coalition formation in the nascent policy subsystem around hydrogen technologies in Germany, which emerges at the intersection of electricity, transport, heating, and industry and is characterised by a broad range of actors from different sectoral backgrounds. We find two coalitions: a rather unusual coalition of actors from industry, NGOs, and research institutes as well as an expectable coalition of gas and heat sector actors. Actors disagree over production, application, and import standards for hydrogen. However, there is widespread support for hydrogen and for a strong role of the state across almost all actors. We explain our findings by combining insights from the advocacy coalition framework and politics of transitions: Belief and coalition formation in a nascent subsystem are influenced by sectoral backgrounds of actors, technology characteristics, as well as trust and former contacts. Our study contributes to a better understanding of early stages of coalition formation in a multi-system setting.
Ride-pooling service assessment with heterogeneous travellers in non-deterministic setting
Authors: Bujak Michal , Kucharski Rafal
Published: August 2024

Ride-pooling remains a promising emerging mode with a potential to contribute towards urban sustainability and emission reductions. Recent studies revealed complexity and diversity among travellers’ ride-pooling attitudes. So far, ride-poling analyses assumed homogeneity of ride-pooling travellers. This, as we demonstrate, leads to a false assessment of ride-pooling system performance. We experiment with an actual NYC demand from 2016 and classify travellers into four groups of various ride-pooling behaviours (value of time and penalty for sharing), as reported in the recent SP study from Netherlands. We replicate their behavioural characteristics, according to the population distribution, to obtain meaningful performance estimations. Results vary significantly from the homogeneous benchmark: mileage savings were lower, while the utility gains for travellers were greater. Observing performance of heterogeneous travellers, we find that those with a low value of time are most beneficial travellers in the pooling system, while those with an average penalty for sharing benefit the most. Notably, despite the highly variable travellers’ behaviour, the confidence intervals for the key performance indicators are reasonably narrow and system-wide performance remains predictable. Our results show that the incorrect assumption of homogeneous traits leads to a high dissatisfaction of 18.5% and a cancellation rate of 36%. Such findings shed a new light on the expected performance of large scale ride-pooling systems.
Orthographic influences on phonological processing in children with and without reading difficulties: an eye-tracking study
Authors: Baron Lauren S. , Ehrhorn Anna M. , Shlanta Peter , Ashby Jane , Bell Bethany A. , Adlof Suzanne M.
Published: August 2024

Phonological processing is an important contributor to decoding and spelling difficulties, but it does not fully explain word reading outcomes for all children. As orthographic knowledge is acquired, it influences phonological processing in typical readers. In the present study, we examined whether orthography affects phonological processing differently for children with current reading difficulties (RD), children with a history of reading difficulties who are currently presenting with typical word reading skills (Hx), and children with typical development and no history of reading difficulties (TD). School-aged children completed a phonological awareness task containing spoken words and pictures while eye movements were recorded. In this task, children had to pair a spoken stimulus word with one of four pictures that ended with the same sound. Within the task, stimulus-target picture pairs varied in the congruency and consistency of the orthographic and phonological mappings of their final consonant sounds. Eye movements revealed that children with typical word reading (the Hx and TD groups) showed better discrimination of the target from the foils compared to peers with underdeveloped word reading skills. All children were more accurate when stimulus-target pairs were congruent and consistent than when they were incongruent or inconsistent. Orthography plays an important role in the completion of phonological awareness tasks, even in the absence of written words and for children with a wide range of reading abilities. Results highlight the importance of considering orthography during interventions for phonological awareness and word reading.