bluuebunny/crossref_metadata_2025 huggingface dataset:
Regression test prioritization leveraging source code similarity with tree kernels
Authors: Altiero Francesco , Corazza Anna , Di Martino Sergio , Peron Adriano , Libero Lucio Starace Luigi
Published: February 2024

Regression test prioritization (RTP) is an active research field, aiming at re‐ordering the tests in a test suite to maximize the rate at which faults are detected. A number of RTP strategies have been proposed, leveraging different factors to reorder tests. Some techniques include an analysis of changed source code, to assign higher priority to tests stressing modified parts of the codebase. Still, most of these change‐based solutions focus on simple text‐level comparisons among versions. We believe that measuring source code changes in a more refined way, capable of discriminating between mere textual changes (e.g., renaming of a local variable) and more structural changes (e.g., changes in the control flow), could lead to significant benefits in RTP, under the assumption that major structural changes are also more likely to introduce faults. To this end, we propose two novel RTP techniques that leverage tree kernels (TK), a class of similarity functions largely used in Natural Language Processing on tree‐structured data. In particular, we apply TKs to abstract syntax trees of source code, to more precisely quantify the extent of structural changes in the source code, and prioritize tests accordingly. We assessed the effectiveness of the proposals by conducting an empirical study on five real‐world Java projects, also used in a number of RTP‐related papers. We automatically generated, for each considered pair of software versions (i.e., old version, new version) in the evolution of the involved projects, 100 variations with artificially injected faults, leading to over 5k different software evolution scenarios overall. We compared the proposed prioritization approaches against well‐known prioritization techniques, evaluating both their effectiveness and their execution times. Our findings show that leveraging more refined code change analysis techniques to quantify the extent of changes in source code can lead to relevant improvements in prioritization effectiveness, while typically introducing negligible overheads due to their execution.
Recent Advances in Flexible Wearable Technology: From Textile Fibers to Devices
Authors: Zhao Yitao , Guo Xuefeng , Sun Hong , Tao Lei
Published: February 2024

Smart textile fabrics have been widely investigated and used in flexible wearable electronics because of their unique structure, flexibility and breathability, which are highly desirable with integrated multifunctionality. Recent years have witnessed the rapid development of textile fiber‐based flexible wearable devices. However, the pristine textile fibers still can't meet the high standards for practical flexible wearable devices, which calls for the development of some effective modification strategies. In this review, we summarize the recent advances in the flexible wearable devices based on the textile fibers, putting special emphasis on the design and modifications of textile fibers. In addition, the applications of textile fibers in various fields and the critical role of textile fibers are also systematically discussed, which include the supercapacitors, sensors, triboelectric nanogenerators, thermoelectrics, and other self‐powered electronic devices. Finally, the main challenges that should be overcome and some effective solutions are also manifested, which will guide the future development of more effective textile fiber‐based flexible wearable devices.
Learning the sparse prior: Modern approaches
Authors: Peng Guan‐Ju
Published: February 2024

The sparse prior has been widely adopted to establish data models for numerous applications. In this context, most of them are based on one of three foundational paradigms: the conventional sparse representation, the convolutional sparse representation, and the multi‐layer convolutional sparse representation. When the data morphology has been adequately addressed, a sparse representation can be obtained by solving the sparse coding problem specified by the data model. This article presents a comprehensive overview of these three models and their corresponding sparse coding problems and demonstrates that they can be solved using convex and non‐convex optimization approaches. When the data morphology is not known or cannot be analyzed, it must be learned from training data, thereby formulating dictionary learning problems. This article addresses two different dictionary learning paradigms. In an unsupervised scenario, dictionary learning involves the alternating or joint resolution of sparse coding and dictionary updating. Another option is to create a recurrent neural network by unrolling algorithms designed to solve sparse coding problems. These networks can then be used in a supervised learning setting to facilitate the training of dictionaries via forward‐backward optimization. This article lists numerous applications in various domains and outlines several directions for future research related to the sparse prior.

This article is categorized under:

Statistical Learning and Exploratory Methods of the Data Sciences > Modeling Methods

Statistical and Graphical Methods of Data Analysis > Modeling Methods and Algorithms

Statistical Models > Nonlinear Models
The Risk of Risk Regulation: A Thirty-Year LSE Perspective
Authors: Lodge Martin , Hood Christopher
Published: February 2024

Drawing on the analytic themes that featured in LSE’s teaching and research in the field since the early 1990s, this paper takes a ‘then and now’ three-decade perspective on the regulation of high-hazard industries. It argues there are some clear continuities in the underlying regulatory dilemma (namely, the costs and benefits of ‘togetherness’ versus social distance between regulators and regulatees) and in the recurring recipes for the handling of major risks. But it also shows that there have been shifts in the saliency of the various hazards in debate, new epistemic players (notably ethicists) figuring more prominently on the regulatory scene, and more awareness of political constraints on alternatives to classic regulation, such as enforced self-regulation and safety cultures in high-reliability organisation.
Auswirkungen des Klimawandels auf biogeochemische Stoffkreisläufe
Authors: Brüggemann Nicolas , Butterbach-Bahl Klaus
Published: February 2024

Der Klimawandel wirkt sich auf biogeochemische Stoffkreisläufe aus. So kann davon ausgegangen werden, dass sich die ökosystemaren Kohlenstoff- und Stickstoffflüsse zwischen Biosphäre, Atmosphäre und Hydrosphäre zukünftig deutlich verändern werden, mit positiven wie auch negativen Rückkopplungseffekten auf den Klimawandel. Der Schwerpunkt dieses Kapitels liegt auf wenig intensiv bis nicht genutzten terrestrischen Ökosystemen, da intensiv landwirtschaftlich genutzte Systeme deutlich stärker von Nutzung und Management beeinflusst werden als durch den Klimawandel. Die zu erwartenden Veränderungen für die einzelnen betroffenen terrestrischen Ökosysteme werden, soweit möglich, nach Faktoren getrennt dargestellt. Im Fokus stehen Wälder, Moore und Küstengebiete.
Böden und ihre Funktionen im Klimawandel
Authors: Pfeiffer Eva-Maria  , Eschenbach Annette , Munch Jean Charles , Vereecken Harry
Published: February 2024

Auch wenn die Risiken bisher kaum quantifizierbar sind, ist davon auszugehen, dass aufgrund der Einbindung des Bodens in die Energie-, Wasser- und Stoffkreisläufe die zu erwartenden Temperatur- und Niederschlagsänderungen die Funktionen dieser zentralen Lebensgrundlage auch in Deutschland gefährden. Nach einer Darstellung der Vielfältigkeit von Böden (Pedodiversität), die ein wesentlicher Faktor für Biodiversität ist, geht es in diesem Kapitel um mögliche Änderungen der Standortfunktion von Böden und ihrer Leistungen im Ökosystem sowie um den Bodenwasserhaushalt. An herausgehobener Stelle diskutieren die Autorinnen und Autoren die Klimafunktion von Böden und stellen mögliche Strategien zu ihrem Schutz vor. Eine große Rolle spielt die Verschränkung mit den anderen Themenbereichen von Teil III, etwa Landwirtschaft, Forstwirtschaft und Wasser.
Das Politikfeld „Anpassung an den Klimawandel“ im Überblick
Authors: Vetter Andreas , Eisenack Klaus , Kind Christian , Mahrenholz Petra , Naumann Sandra , Pechan Anna , Willen Luise
Published: February 2024

In Deutschland ist – wie in vielen Mitgliedstaaten der EU – Anpassung an den Klimawandel als eigenes Politikfeld mit einer nationalen Strategie, einem Maßnahmenplan sowie zuständigen Institutionen etabliert. Während zu Beginn die Informationsgewinnung und praxisorientierte Modellprojekte im Vordergrund standen, liegt der Fokus zunehmend auf einer breiten gesellschaftlichen Umsetzung von Klimaanpassungsmaßnahmen, um den bekannten Klimafolgen zu begegnen. Im Mittelpunkt des Kapitels stehen Klimaanpassungsstrategien auf den unterschiedlichen politischen Ebenen – von der EU bis zur Kommune – sowie Hemmnisse und Ansätze erfolgreicher Umsetzung von Klimaanpassung.
Weiterentwicklung von Strategien zur Klimawandelanpassung
Authors: Mahrenholz Petra , Daschkeit Achim , Knieling Jörg , Knierim Andrea , Martinez Grit , Molitor Heike , Schlipf Sonja
Published: February 2024

Anpassung an den Klimawandel kann zur nachhaltigen Entwicklung beitragen, insbesondere wenn sie mit sozialen Innovationen einhergeht. Das Kapitel untersucht transformative Ansätze zur Anpassung, die im Angesicht von tiefgreifenden Klimarisiken notwendig werden und die über Maßnahmen hinausgehen, die den ökologischen und gesellschaftlichen Status quo aufrechterhalten. Geschildert werden Beispiele gelungener Steuerungs- und Gestaltungsansätze, etwa mithilfe von Rechts-, ökonomischen und zunehmend auch informellen Instrumenten.
The role of the peripheral and central adrenergic system in the construction of the subjective emotional experience of panic
Authors: de Vos Jette H. , Schruers Koen R. J. , Debard Glen , Bonroy Bert , Linden David E. J. , Leibold Nicole K.
Published: February 2024

Rationale

Although the study of emotions can look back to over 100 years of research, it is unclear which information the brain uses to construct the subjective experience of an emotion.

Objective

In the current study, we assess the role of the peripheral and central adrenergic system in this respect.

Methods

Healthy volunteers underwent a double inhalation of 35% CO2, which is a well-validated procedure to induce an intense emotion, namely panic. In a randomized, cross-over design, 34 participants received either a β1-blocker acting selectively in the peripheral nervous system (atenolol), a β1-blocker acting in the peripheral and central nervous system (metoprolol), or a placebo before the CO2 inhalation.

Results

Heart rate and systolic blood pressure were reduced in both β-blocker conditions compared to placebo, showing effective inhibition of the adrenergic tone. Nevertheless, the subjective experience of the induced panic was the same in all conditions, as measured by self-reported fear, discomfort, and panic symptom ratings.

Conclusions

These results indicate that information from the peripheral and central adrenergic system does not play a major role in the construction of the subjective emotion.
Klinische Ergebnisse des eyeWatch-Systems: 1-Jahres-Outcome
Authors: Weber Constance , Hundertmark Sarah , Holz Frank G. , Mercieca Karl
Published: February 2024

Hintergrund

Das eyeWatch-System (EWS) (Rheon Medical, Lausanne, Schweiz) wurde als Glaukomdrainageimplantat (GDI) entwickelt, um den Augeninnendruck (IOD) präzise kontrollieren zu können und insbesondere in der frühen postoperativen Phase die Entwicklung einer Hypotonie und ihrer Komplikationen zu verhindern.

Ziel der Arbeit

Wir berichten über die 1‑Jahres-Ergebnisse der mit dem EWS versorgten Patienten.

Material und Methoden

Retrospektive Analyse von Augen, die eine EWS-Operation an der Universitäts-Augenklinik Bonn, Deutschland, zwischen 05/2021 und 09/2022 erhielten.

Ergebnisse

Insgesamt wurden in dieser Studie 5 Augen der ersten 5 konsekutiv mit dem EWS behandelten Patienten eingeschlossen. Der mittlere Augeninnendruck (IOD) lag präoperativ bei 34,6 mm Hg (23–45 mm Hg) und reduzierte sich auf 12,2 mm Hg (9–18 mm Hg) mit einer durchschnittlichen Reduktion von 60 %. Die lokale drucksenkende Therapie konnte von 2,8 Wirkstoffen präoperativ (1 bis 4) auf 0,60 Wirkstoffe nach 1 Jahr gesenkt werden. Alle Patienten erreichten einen IOD-Zielwert von unter 21 mm Hg, davon 4 Patienten ohne weitere Medikation. Die Komplikationsrate war gering. Ein Patient musste 2‑mal chirurgisch revidiert werden, da der IOD nach der Operation auf über 30 mm Hg erhöht war und im Verlauf sich eine Tube-Exposition zeigte, sodass ein zweiter Spenderpatch aufgenäht wurde. Derselbe Patient hatte nach einer cMRT-Untersuchung einen erhöhten IOD von mehr als 30 mm Hg. Bei diesem Patienten wurde mittels des eyeWatch Pen (EWP, Rheon Medical, Lausanne, Schweiz) eine Adjustierung des EWS durchgeführt um den IOD wieder zu senken. IOD-Anpassungen mit dem EWP wurden bei 4 von 5 Patienten im ersten Jahr nach der Operation durchgeführt, der mittlere IOD vor der Anpassung betrug 21,33 mm Hg (15–37 mm Hg) und wurde auf einen Mittelwert von 8,58 mm Hg (4–16 mm Hg) gesenkt.

Diskussion

Das EWS senkt wirksam den IOD und die Menge benötigter drucksenkender Augentropfen. Mithilfe des EWP sind postoperative Anpassungen des IOD ohne weitere invasive Maßnahmen möglich.
Fully endoscopic microvascular decompression for hemifacial spasm: a clinical study and analysis
Authors: Zheng Xialin , Zhang Binbin , Shao Dongqi , Cai Longjie , Xie Shan , Li Yu , Jiang Zhiquan
Published: February 2024

Fully endoscopic microvascular decompression (MVD) of the facial nerve is the main surgical treatment for hemifacial spasm. However, the technique presents distinct surgical challenges. We retrospectively analyzed prior cases to consolidate surgical insights and assess clinical outcomes. Clinical data from 16 patients with facial nerve spasms treated at the Department of Neurosurgery in the First Affiliated Hospital of Bengbu Medical College, between August 2020 and July 2023, were retrospectively examined. Preoperatively, all patients underwent magnetic resonance angiography to detect any offending blood vessels; ascertain the relationship between offending vessels, facial nerves, and the brainstem; and detect any cerebellopontine angle lesions. Surgery involved endoscopic MVD of the facial nerve using a mini Sigmoid sinus posterior approach. Various operative nuances were summarized and analyzed, and clinical efficacy, including postoperative complications and the extent of relief from facial paralysis, was evaluated. Fully endoscopic MVD was completed in all patients, with the offending vessels identified and adequately padded during surgery. The offending vessels were anterior inferior cerebellar artery in 12 cases (75%), vertebral artery in 3 cases (18.75%), and posterior inferior cerebellar artery in 1 case (6.25%). Intraoperative electrophysiological monitoring revealed that the lateral spread response of the facial nerve vanished in 15 cases and remained unchanged in 1 case. Postoperative facial spasms were promptly alleviated in 15 cases (93.75%) and delayed in 1 case (6.25%). Two cases of postoperative complications were recorded—one intracranial infection and one case of tinnitus—both were resolved or mitigated with treatment. All patients were subject to follow-up, with no instances of recurrence or mortality. Fully endoscopic MVD of the facial nerve is safe and effective. Proficiency in endoscopy and surgical skills are vital for performing this procedure.
Satellite laser ranging to Galileo satellites: symmetry conditions and improved normal point formation strategies
Authors: Steindorfer Michael A. , Koidl Franz , Kirchner Georg , Wang Peiyuan , Dilssner Florian , Schoenemann Erik , Strangfeld Aaron , Gonzalez Francisco
Published: February 2024

High-precision satellite laser ranging measurements to Galileo retroreflector panels are analyzed to determine the angle of incidence of the laser beam based on specific orientations of the panel with respect to the observing station. During the measurements, the panel aligns with respect to the observing station in such a way that multiple retroreflectors appear at the same range, forming regions of increased data density—separated by a few millimeters. First, measurements to a spare IOV-type retroreflector mounted on an astronomical mount at a remote location 32 km away from the Graz laser ranging station are performed. In addition, more than 100 symmetry passes to Galileo satellites in orbit have been measured. Two novel techniques are described to form laser ranging normal points with improved precision compared to traditional methods. An individual normal point can be formed for each set of retroreflectors at a constant range. The central normal point was shown to be up to 4 mm more accurate when compared with a precise orbit solution. Similar offsets are determined by applying a pattern correlation technique comparing simulated with measured data, and the first method is verified. Irregular reflection patterns of Galileo FOC panels indicate accumulated far-field diffraction patterns resulting from non-uniform retroreflector distributions.
A novel metaheuristic inspired by horned lizard defense tactics
Authors: Peraza-Vázquez Hernán , Peña-Delgado Adrián , Merino-Treviño Marco , Morales-Cepeda Ana Beatriz , Sinha Neha
Published: February 2024

This paper introduces HLOA, a novel metaheuristic optimization algorithm that mathematically mimics crypsis, skin darkening or lightening, blood-squirting, and move-to-escape defense methods. In crypsis behavior, the lizard changes its color by becoming translucent to avoid detection by its predators. The horned lizard can lighten or darken its skin, depending on whether or not it needs to decrease or increase its solar thermal gain. The skin darkening or lightening strategy is modeled by including the stimulating hormone melanophore rate( $$\alpha$$
α
-MHS) that influences these skin color changes. Further, the move-to-evasion strategy is also mathematically described. The horned lizard’s shooting blood defense mechanism, described as a projectile motion, is also modeled. These strategies balance exploitation and exploration mechanisms for local and global search over the solution space. HLOA performance is benchmarked with sixty-three optimization problems from the literature, testbench problems provided in IEEE CEC- 2017 “Constrained Real-Parameter Optimization”, analyzed for dimensions 10, 30, 50, and 100, as well as testbench functions from IEEE CEC-06 2019 “100-Digit Challenge”. Moreover, three real-world constraint optimization applications from IEEE CEC2020 and two engineering problems, the multiple gravity assist optimization and the optimal power flow problem, are also studied. Wilcoxon and Friedman statistics tests compare the HLOA algorithm results against ten recent bio-inspired algorithms. Wilcoxon shows that HLOA provides the optimal solution for most testbench functions more effectively than competing algorithms. At the same time, the Friedman statistics test ranks the HLOA first, and the n-dimensional analysis shows that it performs better on the constrained optimization problems for dimensions 50 and 100. The source code is free and available from https://www.mathworks.com/matlabcentral/fileexchange/159658-horned-lizard-optimization-algorithm-hloa.
Short-Term Effects of Heart Rate Variability Biofeedback on Working Memory
Authors: Bahameish Mariam , Stockman Tony
Published: February 2024

Drawing upon the well-documented impact of long-term heart rate variability biofeedback (HRVB) on psychophysiological responses, this study seeks to explore the short-term effects arising from a single HRVB session during and after paced breathing exercise. The research aligns with the neurovisceral integration model, emphasizing the link between heart rate variability (HRV) levels and cognitive performance. Therefore, a randomized controlled trial employing a between-subjects design was conducted with 38 participants. Each participant was assigned to either the paced breathing intervention group or the spontaneous breathing control group. The study assessed various parameters such as cardiac vagal tone, evaluated through vagally mediated HRV measures, and working memory, measured using the N-back task. Additionally, participants’ affective states were assessed through self-reported questionnaires, specifically targeting attentiveness, fatigue, and serenity. The results notably reveal enhancements in the working memory task and an elevated state of relaxation and attention following the HRVB session, as evidenced by higher averages of correct responses, serenity and attentiveness scores. However, the findings suggest that this observed improvement is not influenced by changes in cardiac vagal tone, as assessed using a simple mediation analysis. In conclusion, this study presents promising insights into the impact of a single HRVB session, laying the foundation for future research advancements in this domain.
Tarlov Cysts and Premature Ejaculation
Authors: Liu Yuanyuan , Sun Dalin , Gao Zhenghong , Wang Zhongjiang , Jin Baofang
Published: February 2024

Tarlov cysts adjacent to the spinal cord are usually asymptomatic and found incidentally via magnetic resonance imaging. On rare occasions, they increase in size to produce symptoms resembling disk herniation. We report a rare case of a sacral cyst resulting in premature ejaculation in a 32-year-old man who presented with pelvic pain and acquired premature ejaculation. Spinal nerve root decompression, excision of intraspinal Tarlov cyst, and spinal nerve root adhesion release surgery significantly improved his pain and premature ejaculation at a six-month follow-up.
Morphometrics predicts the differential regurgitant fraction in bilateral pulmonary arteries of patients with repaired tetralogy of fallot
Authors: Teng Hui-Chung , Chen Yi-Chun , Chen Yung-Lin , Weng Ken-Pen , Pan Jun-Yen , Chang Ming-Hua , Cheng Hsiu-Wen , Wu Ming-Ting
Published: February 2024

In patients with repaired tetralogy of Fallot (rTOF), the regurgitant fraction (RF) in left pulmonary artery (LPA) and right pulmonary artery (RPA) is usually unequal. The morphometrics may play a crucial role in this RF discrepancy. Cardiovascular MR of 79 rTOF patients and 20 healthy controls were retrospectively enrolled. Forty-four from the 79 patients were matched in age, sex and body surface area to the 20 controls and were investigated for: (1) phase-contrast flow of main pulmonary artery (MPA), LPA, and RPA; (2) vascular angles: the angles between the thoracic anterior–posterior line (TAPL) with MPA (θM–AP), MPA with RPA (θM–R), and MPA with LPA (θM–L); (3) cardiac angle, the angle between TAPL and the interventricular septum; (4) area ratio of bilateral lung and hemithorax regions. Compared with the 20 controls, the 44 rTOF patients exhibited wider θM–AP, sharper θM–L angle, and a smaller θM–L/θM–R ratio. In the 79 rTOF patients, LPA showed lower forward, backward, and net flow, and greater RF as compared with RPA. Multivariate analysis showed that the RF of LPA was negatively associated with the θM–L/θM–R ratio and the age at surgery (R2 = 0.255). Conversely, the RF of RPA was negatively associated with the left lung/left hemithorax area ratio and cross-sectional area (CSA) of LPA, and positively associated with CSA of RPA and MPA (R2 = 0.366). In rTOF patients, the RF of LPA is more severe than that of RPA, which may be related to the vascular morphometrics. Different morphometric parameters are independently associated with the RF of LPA or RPA, which may offer potential insights for surgical strategies.
Multi-phase-field approach to fracture demonstrating the role of solid-solid interface energy on crack propagation
Authors: Jafarzadeh Hossein , Shchyglo Oleg , Steinbach Ingo
Published: February 2024

A multi-phase-field approach for crack propagation considering the contribution of the interface energy is presented. The interface energy is either the grain boundary energy or the energy between a pair of solid phases and is directly incorporated into to the Ginzburg–Landau equation for fracture. The finite difference method is utilized to solve the crack phase-field evolution equation and fast Fourier method is used to solve the mechanical equilibrium equation in three dimensions for a polycrystalline material. The importance of the interface (grain boundary) energy is analyzed numerically for various model problems. The results show how the interface energy variations change the crack trajectory between the intergranular and transgranular fracture.
A Novel Heterozygous Variant in AICDA Impairs Ig Class Switching and Somatic Hypermutation in Human B Cells and is Associated with Autosomal Dominant HIGM2 Syndrome
Authors: Della Mina Erika , Jackson Katherine J. L. , Crawford Alexander J. I. , Faulks Megan L. , Pathmanandavel Karrnan , Acquarola Nicolino , O’Sullivan Michael , Kerre Tessa , Naesens Leslie , Claes Karlien , Goodnow Christopher C. , Haerynck Filomeen , Kracker Sven , Meyts Isabelle , D’Orsogna Lloyd J. , Ma Cindy S. , Tangye Stuart G.
Published: February 2024

B cells and their secreted antibodies are fundamental for host-defense against pathogens. The generation of high-affinity class switched antibodies results from both somatic hypermutation (SHM) of the immunoglobulin (Ig) variable region genes of the B-cell receptor and class switch recombination (CSR) which alters the Ig heavy chain constant region. Both of these processes are initiated by the enzyme activation-induced cytidine deaminase (AID), encoded by AICDA. Deleterious variants in AICDA are causal of hyper-IgM syndrome type 2 (HIGM2), a B-cell intrinsic primary immunodeficiency characterised by recurrent infections and low serum IgG and IgA levels. Biallelic variants affecting exons 2, 3 or 4 of AICDA have been identified that impair both CSR and SHM in patients with autosomal recessive HIGM2. Interestingly, B cells from patients with autosomal dominant HIGM2, caused by heterozygous variants (V186X, R190X) located in AICDA exon 5 encoding the nuclear export signal (NES) domain, show abolished CSR but variable SHM. We herein report the immunological and functional phenotype of two related patients presenting with common variable immunodeficiency who were found to have a novel heterozygous variant in AICDA (L189X). This variant led to a truncated AID protein lacking the last 10 amino acids of the NES at the C-terminal domain. Interestingly, patients’ B cells carrying the L189X variant exhibited not only greatly impaired CSR but also SHM in vivo, as well as CSR and production of IgG and IgA in vitro. Our findings demonstrate that the NES domain of AID can be essential for SHM, as well as for CSR, thereby refining the correlation between AICDA genotype and SHM phenotype as well as broadening our understanding of the pathophysiology of HIGM disorders.
Recoverability of quantum channels via hypothesis testing
Authors: Jenčová Anna
Published: February 2024

A quantum channel is sufficient with respect to a set of input states if it can be reversed on this set. In the approximate version, the input states can be recovered within an error bounded by the decrease of the relative entropy under the channel. Using a new integral representation of the relative entropy in Frenkel (Integral formula for quantum relative entropy implies data processing inequality, Quantum 7, 1102 (2023)), we present an easy proof of a characterization of sufficient quantum channels and recoverability by preservation of optimal success probabilities in hypothesis testing problems, equivalently, by preservation of $$L_1$$

L
1

-distance.
Exploring biometric domain adaptation in human action recognition models for unconstrained environments
Authors: Freire-Obregón David , Barra Paola , Castrillón-Santana Modesto , De Marsico Maria
Published: February 2024

In conventional machine learning (ML), a fundamental assumption is that the training and test sets share identical feature distributions, a reasonable premise drawn from the same dataset. However, real-world scenarios often defy this assumption, as data may originate from diverse sources, causing disparities between training and test data distributions. This leads to a domain shift, where variations emerge between the source and target domains. This study delves into human action recognition (HAR) models within an unconstrained, real-world setting, scrutinizing the impact of input data variations related to contextual information and video encoding. The objective is to highlight the intricacies of model performance and interpretability in this context. Additionally, the study explores the domain adaptability of HAR models, specifically focusing on their potential for re-identifying individuals within uncontrolled environments. The experiments involve seven pre-trained backbone models and introduce a novel analytical approach by linking domain-related (HAR) and domain-unrelated (re-identification (re-ID)) tasks. Two key analyses addressing contextual information and encoding strategies reveal that maintaining the same encoding approach during training results in high task correlation while incorporating richer contextual information enhances performance. A notable outcome of this study is the comprehensive evaluation of a novel transformer-based architecture driven by a HAR backbone, which achieves a robust re-ID performance superior to state-of-the-art (SOTA). However, it faces challenges when other encoding schemes are applied, highlighting the role of the HAR classifier in performance variations.
Enhancing cervical cancer diagnosis with graph convolution network: AI-powered segmentation, feature analysis, and classification for early detection
Authors: Fahad Nur Mohammad , Azam Sami , Montaha Sidratul , Mukta Md. Saddam Hossain
Published: February 2024

Cervical cancer is a prevalent disease affecting the cervix cells in women and is one of the leading causes of mortality for women globally. The Pap smear test determines the risk of cervical cancer by detecting abnormal cervix cells. Early detection and diagnosis of this cancer can effectively increase the patient’s survival rate. The advent of artificial intelligence facilitates the development of automated computer-assisted cervical cancer diagnostic systems, which are widely used to enhance cancer screening. This study emphasizes the segmentation and classification of various cervical cancer cell types. An intuitive but effective segmentation technique is used to segment the nucleus and cytoplasm from histopathological cell images. Additionally, handcrafted features include different properties of the cells generated from the distinct cervical cytoplasm and nucleus area. Two feature rankings techniques are conducted to evaluate this study’s significant feature set. Feature analysis identifies the critical pathological properties of cervical cells and then divides them into 30, 40, and 50 sets of diagnostic features. Furthermore, a graph dataset is constructed using the strongest correlated features, prioritizes the relationship between the features, and a robust graph convolution network (GCN) is introduced to efficiently predict the cervical cell types. The proposed model obtains a sublime accuracy of 99.11% for the 40-feature set of the SipakMed dataset. This study outperforms the existing study, performing both segmentation and classification simultaneously, conducting an in-depth feature analysis, attaining maximum accuracy efficiently, and ensuring the interpretability of the proposed model. To validate the model’s outcome, we tested it on the Herlev dataset and highlighted its robustness by attaining an accuracy of 98.18%. The results of this proposed methodology demonstrate the dependability of this study effectively, detecting cervical cancer in its early stages and upholding the significance of the lives of women.
Neural Network Based Adaptive Inverse Optimal Control for Non-Affine Nonlinear Systems
Authors: Sancı Muhammet Emre , Öke Günel Gülay
Published: February 2024

In this paper, a novel methodology is introduced for the inverse optimal control of non-affine, nonlinear and discrete-time systems. Although inverse optimal control of affine systems is studied in detail in technical literature, there is no adequate research about its implementation on non-affine systems. here are two main contributions of this work. Firstly using the input–output data of the system to be controlled its NARMA-L2 model is obtained using a multi-layer feedforward neural network, this step provides a conversion from a non-affine to affine system model. After the affine system model is obtained, the inverse optimal control law is applied. The second contribution of this paper is the computation of the inverse optimal control signal. The selection of the P matrix in the control law is crucial since its value directly affects the control performance. Here a novel method is proposed where an adaptive and optimal P matrix is computed online using a recurrent neural network to minimize a predefined cost function. The performance of the proposed control method is evaluated by simulations performed on benchmark problems. The robustness of the method is also tested by additional simulations where noise and disturbance is imposed on the system. The obtained results justify the applicability of the proposed approach.
Finite-Time Stability of Inertial Neural Networks with Delayed Impulses
Authors: Wan Xuran , Li Lulu , Wang Lei
Published: February 2024

This paper studies the finite-time stability (FTS) of the inertial neural networks (INNs) with delayed impulses. Unlike previous related works, we consider the delayed impulses and propose a new impulsive control strategy. We extend the existing FTS results to the cases with delayed impulses. We also establish some global and local FTS criteria of INNs. Moreover, we estimate the settling-time in different cases and investigate the optimization strategy. We present three numerical examples to verify the validity of our theoretical results.
Bipartite Synchronization of Fractional Order Multiple Memristor Coupled Delayed Neural Networks with Event Triggered Pinning Control
Authors: Dhivakaran P. Babu , Gowrisankar M. , Vinodkumar A.
Published: February 2024

This paper investigates the leader and leaderless bipartite synchronization with the signed network utilizing the model of multiple memristor and coupled delayed neural network in an event-triggered pinning control. The usage of the descriptor method in fractional-order neural networks in case of a non-differentiable delay can be seen in this paper. Further, Lyapunov functional criteria, including Lur’e Postnikov Lyapunov functional, is established, and bipartite leader and leaderless synchronization are proved. The obtained numerical results can be seen as accurate to the theoretical results.
Rethinking Position Embedding Methods in the Transformer Architecture
Authors: Zhou Xin , Ren Zhaohui , Zhou Shihua , Jiang Zeyu , Yu TianZhuang , Luo Hengfa
Published: February 2024

In the transformer architecture, as self-attention reads entire image patches at once, the context of the sequence between patches is omitted. Therefore, the position embedding method is employed to assist the self-attention layers in computing the ordering information of tokens. While many papers simply add the position vector to the corresponding token vector rather than concatenating them, few papers offer a thorough explanation and comparison beyond dimension reduction. However, the addition method is not meaningful because token vectors and position vectors are different physical quantities that cannot be directly combined through addition. Hence, we investigate the disparity in learnable absolute position information between the two embedding methods (concatenation and addition) and compare their performance on models. Experiments demonstrate that the concatenation method can learn more spatial information (such as horizontal, vertical, and angle) than the addition method. Furthermore, it reduces the attention distance in the final few layers. Moreover, the concatenation method exhibits greater robustness and leads to a performance gain of 0.1–0.5% for existing models without additional computation overhead.
GNNCL: A Graph Neural Network Recommendation Model Based on Contrastive Learning
Authors: Chen Jinguang , Zhou Jiahe , Ma Lili
Published: February 2024

In the field of recommendation algorithms, the representation learning for users and items has evolved from using single IDs or historical interactions to utilizing higher-order neighbors. This can be achieved by modeling the user–item interaction graph to capture user preferences for items. Despite the promising results achieved by these algorithms, they still suffer from the issue of data sparsity. In order to mitigate the impact of data sparsity, contrastive learning has been adopted in graph collaborative filtering to enhance performance. However, current recommendation algorithms using contrastive learning yield uneven representations after data augmentation and do not consider the potential relationships among users (or items). To address these challenges, we propose a graph neural network-based recommendation model that integrates contrastive learning (GNNCL). This model combines data augmentation with added noise and the exploration of semantic neighbors for nodes. For the structural neighbors on the interaction graph, we introduce a novel and straightforward contrastive learning approach, abandoning previous graph augmentation methods, and introducing uniform noise into the embedding space to create contrastive views. To unearth potential semantic neighbor relationships in the semantic space, we assume that users with similar representations possess semantic neighbor relationships and merge these semantic neighbors into the prototype contrastive learning. We utilize a clustering algorithm to obtain prototypes for users and items and employ the EM algorithm for prototype contrastive learning. Experimental results validate the effectiveness of our approach. Particularly, on the Yelp2018 and Amazon-book datasets, our method exhibits significant performance improvements compared to basic graph collaborative filtering models.
Gender differences in google scholar representation and impact: an empirical analysis of political communication, journalism, health communication, and media psychology
Authors: Goyanes Manuel , Tóth Tamás , Háló Gergő
Published: February 2024

Improving gender equality in top-tier scholars and addressing gender bias in research impact are among the significant challenges in academia. However, extant research has observed that lingering gender differences still undermine female scholars. This study examines the recognition of female scholars through Google Scholar data in four different subfields of communication, focusing on two pressing issues: (1) gender representation among the most cited scholars and (2) gender differences in citations. Our findings demonstrate significant differences in gender proportions among the most cited scholars across all subfields, but especially in Political Communication and Journalism. The regression analysis revealed significant differences in citation scores in Political Communication, Journalism, and the pooled sample. However, results revealed that gender differences in research impact were not statistically significant in Health Communication and Media Psychology. Our study advocates for shifts in the citing behavior of communication scholars, emphasizing the importance of actively recognizing and citing studies conducted by female researchers to drive advancements in communication research.
Are life forms real? Aristotelian naturalism and biological science
Authors: Lockhart Jennifer Ryan , Lott Micah
Published: February 2024

Aristotelian naturalism (AN) holds that the norms governing the human will are special instances of a broader type of normativity that is also found in other living things: natural goodness and natural defect. Both critics and defenders of AN have tended to focus on the thorny issues that are specific to human beings. But some philosophers claim that AN faces other difficulties, arguing that its broader conception of natural normativity is incompatible with current biological science. This paper has three aims. First, we consider a distinctive and nuanced critique of AN’s general understanding of natural normativity put forward by Tim Lewens. Second, after giving a defense of AN, we explore and evaluate Lewens’ proposed alternative view—Kantian projectivism about life forms. We present a problem for Kantian projectivism and suggest reasons for thinking that AN is, after all, the superior position. Finally, we clarify and explain how AN’s claims about life forms and our knowledge of them, relate to empirical observation and to contemporary biological science.
Complementary Mass Transport Investigations in Open-Cell Foams: Full-Field Computational Fluid Dynamics Simulation with Random-Walk Microscopic Particle Tracking and Methane Nuclear Magnetic Resonance Displacement Measurements
Authors: Sadeghi Mehrdad , Brix Andreas , Trunk Sebastian , Pesch Georg R. , Freund Hannsjörg , Thöming Jorg
Published: February 2024

Numerical simulation can provide detailed understanding of mass transport within complex structures. For this purpose, numerical tools are required that can resolve the complex morphology and consider the contribution of both convection and diffusion. Solving the Navier–Stokes equations alone, however, neglects self-diffusion. This influences the simulated displacement distribution of flow especially in porous media at low Péclet numbers (Pe < 16) and in near-wall regions where diffusion is the dominant mechanism. To address this problem, this study uses μCT-based computational fluid dynamics (CFD) simulations in OpenFOAM coupled with the random-walk particle tracking (PT) module disTrackFoam and cross-validated experimentally using pulsed-field gradient (PFG) nuclear magnetic resonance (NMR) measurements of gas flow within open-cell foams (OCFs). The results of the multi-scale simulations—with a resolution of 130–190 µm—and experimental PFG NMR data are compared in terms of diffusion propagators, which are microscopic displacement distributions of gas flows in OCFs during certain observation times. Four different flow rates with Péclet numbers in the range of 0.7–16 are studied in the laminar flow regime within 10 and 20 PPI OCFs, and axial dispersion coefficients were calculated. Cross-validation of PFG NMR measurements and CFD-PT simulations revealed a very good matching with integral differences below 0.04%, underpinning the capability of both complementary methods for multi-scale transport analysis.
Investigating the Critical Period for Alcohol or Other Drug-Related Presentations Following Access to Residential Substance Use Treatment: a Data Linkage Study
Authors: Tisdale Calvert , Leung Janni , de Andrade Dominique , Hides Leanne
Published: February 2024

Individuals who access residential treatment for substance use disorders are at a greater risk of negative health and substance-use outcomes upon exiting treatment. Using linked data, we aimed to identify predictive factors and the critical period for alcohol or other drug (AOD)-related events following discharge. Participants include 1056 individuals admitted to three residential treatment centres in Queensland, Australia from January 1 2014 to December 31 2016. We linked participants’ treatment data with administrative data from hospitals, emergency departments, AOD services, mental health services and the death registry up to December 31 2018. We used survival analysis to examine presentations for AOD-related events within two-years of index discharge. A high proportion of individuals (57%) presented to healthcare services for AOD-related events within 2 year of discharge from residential treatment, with the first 30 days representing a critical period of increased risk. Completing residential treatment (aHR = 0.49 [0.37–0.66], p < .001) and high drug-abstaining self-efficacy (aHR = 0.60 [0.44–0.82], p = .001) were associated with a reduced likelihood of AOD-related events. Individuals with over two previous residential treatment admissions (aHR = 1.31 [1.04–1.64], p = .029), identifying as Indigenous Australian (aHR = 1.34 [1.10–1.63], p < .001), alcohol as a primary substance (aHR = 1.58 [1.30–1.92], p < .001), and receiving a Disability Support Pension (aHR = 1.48 [1.06–2.06], p = 0.022) were at a greater likelihood. The high proportion of individuals that present to health and drug services for AOD-related events, especially in the first 30 days post-discharge, highlights the need for continued support following discharge from substance use treatment.
Assessing the relevance of different proximity dimensions for knowledge exchange and (co-)creation in sustainability-oriented innovation networks
Authors: Wilke Ulrich , Pyka Andreas
Published: February 2024

Innovations incorporating environmental and social considerations can address many sustainability challenges. Such sustainable innovations emerge in networks often comprising actors from business, academia, civil society, and government. The crucial interactions here are the (co-)creation and transfer of knowledge, mutual learning, and experimentation in different environments. To better understand these knowledge processes and hence the eventual outcome of sustainable innovations, we analyze the actors’ relationships with the help of proximity and its five dimensions, namely geographical, cognitive, institutional, organizational, and social proximity. Building upon findings from sustainability science and innovation system theory, we present a refined proximity framework, introducing a differentiation of institutional proximity into micro- and macro-institutional proximity and a differentiation of cognitive proximity into systems-cognitive, normative-cognitive, and transformative-cognitive proximity. Analyzing examples from the literature by applying this framework, we see that all proximity dimensions and their interdependencies help to better understand knowledge processes and innovations in sustainability-oriented innovation networks. We find that such networks often depict low levels of micro-institutional and systems-cognitive proximity, which coheres with the prevalence of inter- and transdisciplinary approaches and the wide inclusion of relevant stakeholders for addressing sustainability issues. Our framework further reveals that successful networks show high levels in other proximity dimensions, with normative-cognitive proximity appearing to play a crucial role, highlighting the importance of shared goal orientations. Our results provide valuable input for the formation of sustainability-oriented innovation networks by pointing out the necessary combination of distances that allow for creativity and learning, combined with appropriate proximities for exchange and mutual understanding.
Overview of Highly Solvating Electrolytes for Lean Electrolyte Conditions in Lithium–Sulfur Batteries
Authors: Kang Taemin , Kang Naehyun , Choi Jang Wook
Published: February 2024

Lithium-sulfur (Li–S) batteries are considered the next generation of lithium-ion batteries due to their high energy density, but they face challenges in operation under lean electrolyte conditions. Among the potential strategies, highly solvating electrolytes (HSEs) have become a prominent option. These electrolytes offer strong solvation of polysulfide intermediates, leading to modified sulfur reaction pathways and deposition morphologies compared to conventional electrolytes. This review presents a comprehensive summary of HSEs in Li–S batteries, with a focus on their development and optimization for broad applications.