bluuebunny/crossref_metadata_2025 huggingface dataset:
Model complexity optimization of equivalent dynamical linearization data models used in model‐free adaptive control
Authors: Salighe Soheil , Söffker Dirk
Published: October 2024

This paper discusses a strategy for optimizing the complexity of time‐varying data models as used in model‐free adaptive control (MFAC). Here the dynamic linearization in compact form (CFDL), partial form (PFDL), and full form (FFDL) are considered as data models used to describe input/output (I/O) data sets. These data models are built only for control purpose and can have various degrees of complexity depending on the size of the considered time‐window as well as the underlying algorithms. The methodology is to compare the performance of the data models according to an evaluation criterion, to analyze the order of different data models based on bias‐variance trade‐off, and to select the best‐performing model. The complexity of the selected model is compared with the reduced linear time‐invariant (LTI) model obtained by applying a combination of the eigensystem realization algorithm (ERA) and observer/Kalman filter identification (OKID) on the same I/O dataset. The I/O data are obtained from applying the MFAC controllers on a nonlinear three‐tank system (3TS) to track various desired references. The results indicate that the model complexity optimization can also be used for selecting an appropriate MFAC data model with optimal order to reduce the complexity and computational burden of the MFAC control algorithms.
How to increase nature connectedness? Effectiveness and mechanisms of a gratitude journal intervention
Authors: Samus Andreas , Dickinson Katharine J. M. , Freeman Claire , van Heezik Yolanda
Published: October 2024

Nature connectedness can promote pro‐environmental behaviour and psychological well‐being, but little is known about how nature connectedness can be strengthened. Interventions that seek to enhance nature connectedness by promoting direct nature contact may be impractical because urban areas often lack opportunities for interactions with nature in the daily lives of people.

This study examines the effects of a gratitude journal exercise on nature connectedness, psychological well‐being, and engagement in wildlife gardening. Participants (N = 114) were either asked to write down daily three things relating to nature that they were grateful for over a 14‐day period or they were assigned to one of two control groups (a traditional gratitude condition and an activity list condition).

Compared to the two control groups, there were no significant differences in any of the outcome variables during the 14‐day period and at 1‐week and 3‐month follow‐ups. However, significant increases in all those outcome variables emerged independent of the group. Qualitative data analysis suggests that the journal exercise promoted increases in the outcome variables by generating self‐knowledge as well as positive emotions and attitudes. Moreover, participants noted that the journal activity made them think about nature in new ways, presumably through answering daily survey questions on nature connectedness.

We suggest that the mere activity of regularly reflecting on one's relationship with nature may increase nature connectedness. Interventions that encourage people to contemplate the interconnectedness between themselves and nature could be a viable strategy to strengthen human–nature relationships, especially in urban areas that lack opportunities for interactions with nature. The findings of this study can inform future research concerned with the processes of strengthening nature connectedness and the design of interventions that employ nature‐based journal exercises.

Read the free Plain Language Summary for this article on the Journal blog.
Environmentally Benign High‐Performance Composites‐Based Hybrid Microcrystalline Cellulose/Graphene Oxide
Authors: Kabeb Siti M.
Published: October 2024

A novel silane functionalization prepared by a solution mixing approach of epoxy composites filled with eco‐friendly reinforcement filler, that is, graphene oxide (GO) and microcrystalline cellulose (MCC). The developed composites were subjected to comprehensive analysis using various characterization techniques, encompassing mechanical testing, water absorption analysis, thermal stability assessment, and scanning electron microscopy (SEM). The tensile strength and Young's Modulus of the epoxy composite filled with 1.0 wt.% of GO (EGO1.0) demonstrated the highest value viz. 29.83 MPa and 1991.71 MPa, respectively, when compared to neat epoxy composite (E0). Meanwhile, the thermal gravimetry analysis (TGA) studies, particularly char yield, highlight improvements in the thermal stability of the EGO2.5 composite, that is, 23.39% representing a 33.73% increment compared to the E0 composite. The synergistic effect of hybrid filler, achieved by a combination of micro and nanoparticle fillers within an epoxy matrix, was investigated as a virtuous alternative to the conventional epoxy nanocomposites. A uniform dispersion of GO on the MCC surface leads to significant improvements in the mechanical properties and thermal stability of the epoxy‐reinforced composite. The maximum tensile strength, Young's Modulus, and break strain of 39.77 MPa, 2591.27 MPa, and 2.90%, respectively, were observed for the modified EGO1.0MCC1.5 composite. The synergistic effect of hybrid eco‐friendly reinforcement fillers (GO/MCC) and a strong interfacial adhesion between the matrix and filler reduces the formation of defects, thereby resulting in good stress transfer from matrix to fillers.
A multi‐layer approach for additive manufacturing of continuous fiber composites
Authors: Tawfik Hussam , Goldsmith Peter
Published: October 2024

Additive manufacturing (AM) of continuous fiber reinforced polymer composites (cFRPCs) requires innovative tool‐pathing strategies that account for the anisotropic properties of the continuous fibers and ensure their continuous deposition as reinforcement along the designed structure, reducing fibers bending and cutting. Existing 3D printing slicing software, designed for isotropic materials like neat polymers, has been adapted for 3D printing of continuous fiber composites, resulting in a layer‐by‐layer approach that necessitates filament cutting after each layer deposition. This method introduces discontinuities, weakening the material and underutilizing continuous fibers strength. In this research, we propose a novel tool‐pathing strategy designed to address these challenges through (1) Ensuring fiber continuity across layers by allowing overlapping filaments and (2) Strategically positioning fiber cut points based on stress distribution, modeled using finite element analysis. A Multi‐Layer Continuous Fiber Path (ML‐CFP) approach was introduced and validated on a simple bracket structure featuring two load‐application inserts. 3D printed brackets using different tool paths were tested to failure under tension and compression after compression molding to improve interlayer adhesion. Mechanical investigations confirmed that the ML‐CFP approach enhances fiber utilization, improving tensile strength and work to fracture by up to 46% and 100% through promoting failure in fibers rather than at cut points.

Highlights

Introduced the multi‐layer continuous fiber path method (ML‐CFP) in AM of cFRPCs.

Introduced the strategic cut point placement (SCPP) based on stress distribution.

Maintaining fiber continuity and reduce fiber bending by allowing filament overlap.

Mechanical testing to compare the ML‐CFP with conventional slicing methods.

Enhanced tensile strength by up to 46% and work to fracture by 100%.
Coping With Side Effects: A Daily Diary Study in Women With Breast Cancer Living With Adjuvant Endocrine Therapy
Authors: Bierbauer W. , Scholz U. , Güth U. , Tausch C. , Elfgen C.
Published: October 2024

Objective

Adjuvant endocrine therapy (AET) is increasingly being prescribed for up to 10 years to people diagnosed with hormone receptor‐positive breast cancer. AET intake is often accompanied by side effects that significantly impact the well‐being of people. The way individuals cope with medication‐related side effects might play a pivotal role in their emotional adaption.

Methods

This intensive‐longitudinal study investigated the association between self‐reported coping strategies (Brief COPE) and psychological well‐being (Patient Health Questionnaire‐4) among women undergoing AET. A multilevel factor analysis resulted in the identification of four coping factors, namely, problem‐focused, support‐focused, meaning‐focused, and avoidance‐focused coping. Daily coping efforts and experienced side effects were analyzed as predictors of psychological well‐being using multilevel modeling.

Results

A total of 215 women (Mage = 56.5 ± 10.9 years) participated, resulting in a total of n = 2080 daily surveys (M = 9.67 ± 1.08). On average, women reported 3.7 ± 2.2 different side effects per day. Days characterized by an elevated frequency of side effects and increased burden were associated with diminished well‐being. Using more problem‐ and meaning‐focused strategies than usual to cope with side effects correlated positively with well‐being. Conversely, employing more support‐ and avoidance‐focused coping strategies than usual was linked to reduced psychological well‐being. Exploratory analyses focusing on individual coping strategies provided nuanced insights into coping behaviors.

Conclusion

The present findings underscore the relationship between women's coping efforts concerning medication‐related side effects during AET and their daily well‐being. Psychosocial education (e.g., cognitive behavioral therapy) may offer valuable benefits for patients by helping them develop adaptive coping strategies to manage side effects.
Computational Exploration of the Impact of Low‐Spin and High‐Spin Ground State on the Chelating Ability of Dimethylglyoxime Ligand on Dihalo Transition Metal: A QTAIM, EDA, and CDA Analysis
Authors: Mazia Suzane Leonie Djendo , Jean Moto Ongagna , Idrice Adjieufack Abel , Lissouck Daniel , Ndom Jean Claude , Mama Désiré Bikele
Published: October 2024

We have explored the chelation of dimethylglyoxime ligand to divalent (ndx: x = 6, 7, 8) transition metal (TM) cations in two media (gas phase and water) at the B3LYP//LANL2DZ/6–311+G (d,p) and B3LYP/def2‐TZVP level at lower multiplicity and higher multiplicity states. Majority of the 18 optimized halide (chloride and bromide) complexes prefer square planar configuration. The correlations discerned between the experimental structural data and their estimated counterparts demonstrate a good credibility for complexes at lower multiplicity state. The basis set superposition errors (BSSEs) estimated is very small which reflects the fact that the choice of different basis sets (B3LYP//LANL2DZ/6–311+G (d,p)) introduces a slight bias in the calculation of energies. The ADMP (atom‐centered density matrix propagation) simulations in water on chloride complexes indicate the irreversible nature of these M—N dissociation in trajectory simulation process. This fact explains our exclusive focus on the examination of the [glyoxime ligand]…[MX2] interactions. In addition, the solvation of (3d and 4d) transition metal chloride complexes causes a sensitive augmentation of the metal ion affinity (MIA) with an average of 0.29 and 0.24 kcal/mol. In both multiplicity states, the topological parameters have illustrated that the M—N and M—X bonds are typical metal–ligand in both media. The average ΔEorb/ΔEsteric ratio equal to 0.45 and 0.11 in gas phase and water, respectively, reveals the predominance of the contributions from non‐covalent bonding interactions (NCI) compared to those of covalent bonding. But, the maximal value equal to 6.760 is obtained for bromide rhodium complex in water. NBO analysis in both media highlights the fact that a more pronounced ionic character is observed for the majority of the chloride complexes at both spin multiplicity states because of their higher retained charges on the metal atom. For [dimethylglyoxime]…[MX2] interaction (X = Cl and Br), the charge decomposition analysis demonstrates that the lowest value of the d/b ratio is found for the chloride platinum complex at lower multiplicity state in water. This is a proof of its strong relativistic effects.
Robust Collision Avoidance and Path‐Following of USVs With Reduced Conservativeness: A Control Barrier Function‐Based Approach
Authors: Wen Guanghui , Fu Junjie , Lu Hang , Sun Jianfei , Shen Han
Published: October 2024

The collision avoidance and path‐following problem is fundamental for unmanned surface vehicles (USVs) to accomplish various tasks in different water environments. However, addressing this issue is challenging, as USVs are inevitably affected by environmental disturbances in practice. In this study, we address the robust collision avoidance path‐following problem for USVs with unknown bounded environmental disturbances by using the control barrier function (CBF)‐based approach. To reduce the conservativeness for the collision avoidance actions, the elliptical shape of the USV is considered when designing the control law. Furthermore, a high‐order control barrier function (HOCBF)‐based approach is proposed to achieve the robust collision avoidance with respect to both static and dynamic obstacles. Specifically, a nominal robust path‐following controller is first designed utilizing the predefined‐time observers without considering the collision avoidance requirement. Then, by considering the elliptical USV and the circular obstacles, collision avoidance input constraints are derived by the proper HOCBFs. Finally, a local quadratic programming (QP)‐based controller is proposed to achieve robust collision avoidance and path‐following of the USV. Simulation and experimental results are presented to demonstrate the effectiveness of the proposed control strategy.
Corporate social responsibility in the age of activist directorships
Authors: Connelly Brian L. , DesJardine Mark R. , Shi Wei , Sun Zhihui
Published: October 2024

Research Summary

We draw attention to a rapidly emerging phenomenon—the appointment of activist‐nominated directors to boards—that could have consequences for stakeholders. Although appointing an activist director tends to improve firm value for shareholders, we uncover a hidden externality wherein it also yields increased reports of stakeholder harm. We introduce activist directors to the management literature and examine an array of considerations with a view toward launching a stream of literature that explores nuanced forms of activist directorships, intemporal trade‐offs in their influence, and the breadth and depth of their behavioral consequences for firms.

Managerial Summary

Historically, activist shareholders have primarily tried to affect managerial decision‐making from their vantage point as outsiders. Today, activist investors are going further by demanding their own seats at the boardroom table. We examine the consequences of these activist directorships, finding that they are associated with increased reports of stakeholder harm. Supplemental analyses show that, while activist directors bring immediate benefits to shareholders, they appear to impose a managerial myopia wherein executives become less inclined to make long‐term investments. Moreover, the adverse effects on stakeholder harm are most profound when a director is a delegate, meaning they work directly for an activist investor, as opposed to a trustee, who is appointed by, but does not work for, an activist investor.
Correlating Catalyst Growth with Liquid Water Distribution in Polymer Electrolyte Fuel Cells
Authors: Sharma Preetam , Aaron Douglas , Boillat Pierre , Cheng Lei , Johnston Christina , Mench Matthew M.
Published: October 2024

This study investigates the impact of liquid water distribution in a polymer electrolyte fuel cell (PEFC) on the spatially heterogeneous platinum (Pt) catalyst degradation. The membrane electrode assemblies (MEAs) are aged using accelerated stress tests (ASTs) in varied cathode gas environments (N2 and air) to instigate Pt catalyst degradation. The study employs high‐resolution neutron imaging and synchrotron micro‐X‐ray diffraction (micro‐XRD) to map liquid water distribution and Pt particle size, respectively. Neutron radiographs reveal liquid water accumulation primarily within the diffusion media, especially under flow field lands, due to thermal resistance differences between channels and lands. Aged MEAs exhibit increased water retention, likely due to increased hydrophilicity of the diffusion media with aging. Synchrotron micro‐XRD maps unveil significant heterogeneity in Pt particle size distribution in the aged MEAs, correlated with preferential liquid water accumulation under flow field lands. This study highlights the critical role of flow field design and water distribution in catalyst degradation, underscoring the need for innovative strategies to enhance fuel cell durability and performance.
Trace Ru Incorporation Boosted Co2P Nanorods for Superior Water Electrolysis and Substrate‐Paired Electrolysis Toward Value‐Added Chemicals in Alkaline Medium
Authors: Ganguly Souradip , Basera Pooja , Ahmed Sahnawaz , Saha Sukanta , Dutta Arnab , Loha Chanchal , Ghosh Sirshendu
Published: October 2024

Electro‐valorization of biomass‐derived chemicals has ensured sustainable production of value‐added products, an effective approach for reducing carbon footprint, through renewable energy. Electrochemical oxidation and reduction reactions in aqueous media using H2O as a potential source for active hydrogenated and oxygenated species fulfill the purpose. In this study, Ru─Co2P nanorods are explored as a bifunctional electrocatalyst toward valorization of Organics at basic media. The in‐situ electrogenerated Co3+ and Co4+ species act as active oxidants toward product selectivity. An overpotential of 68 mV is found for hydrogen evolution reaction (1 m NaOH) with Ru─Co2P. Further, used as cathode, Ru─Co2P effectively reduces furfuraldehyde to furfuryl alcohol and p‐nitrophenol to p‐aminophenol. Ru doping enables ease of formation of active species both for reduction and oxidation, faster charge transfer between catalyst to absorbates. Density Functional Theory calculation establishes Ru incorporation in Co2P surface results in enhanced adsorption of substrates. Ru doping modulates the electronic structure of Co2P which changes the density of states resulting in faster water dissociation and water splitting. To reach 10 mA cm−2 current density only 1.6 V is required for water electrolysis, whereas 1.4 V is enough for substrate‐paired electrolysis with simultaneous oxidation of benzyl alcohol and reduction of p‐nitro phenol.
Enhanced Stability of Melt‐Processable Organic–Inorganic Hybrid Manganese Halides for X‐Ray Imaging
Authors: Chen Shichuan , Guo Cuiling , Chen Shan‐Ci , Di Yiming , Fang Xin , Lin Mei‐Jin , Yang Huanghao
Published: October 2024

Mn‐based metal halides scintillators with high photoluminescence quantum yield (PLQY) have recently emerged as promising large‐size candidates for X‐ray imaging but still remains as difficult challenge in stability and high processing temperatures. Here, three manganese halides are designed by introducing branched chains into organic cations and extending the carbon chains, namely (i‐PrTPP)2MnBr4, (i‐BuTPP)2MnBr4 and (i‐AmTPP)2MnBr4, successfully lowered the melting point of manganese halides to 120.2 °C. Three materials show striking light yields of 59 000, 40 000, and 52 000 photons MeV−1, respectively. The lowest detection limits are 42.30, 50.92, and 45.71 nGy s−1, respectively. Meanwhile, compared to their counterparts with linear carbon chains, the introduction of branched chains has significantly enhanced the stability of the scintillators in the glass state. A transparent glass has been prepared using a melt‐quenching method, which exhibited 80% transmittance at 400–700 nm. The glass is utilized for X‐ray imaging, achieving a high spatial resolution up to 46.6 lp mm−1. This result provides a new approach to enhancing the performance of such scintillator materials.
Questioning the Representativeness of Damage Mechanisms in Single‐Fiber Composites via In Situ Synchrotron X‐Ray Holo‐Tomography
Authors: Chatziathanasiou Thanasis , Lee Yeajin , Villanova Julie , Stamati Olga , AhmadvashAghbash Sina , Fazlali Babak , Breite Christian , Sinclair Ian , Mavrogordato Mark N. , Spearing S. Mark , Mehdikhani Mahoor , Swolfs Yentl
Published: October 2024

In fiber‐reinforced polymer composites, the fiber‐matrix interface controls stress transfer mechanisms, thereby affecting mechanical performance. Interfacial properties are often extracted via single‐fiber composite tests. In these tests, the load is transferred from the polymer to the fiber through interfacial shear stresses, necessitating the evaluation of interfacial shear properties. To adopt these properties in the design of industrially relevant composites, one must assume that the damage mechanisms in single‐fiber composites are representative of those in multi‐fiber composites, consisting of highly aligned, unidirectional plies with high fiber volume fractions. That assumption, however, has never been validated. In this paper, the real‐time damage development is monitored in single‐fiber and multi‐fiber composites using in situ X‐ray holo‐tomography at 150‐nm pixel size. The technique enables the first‐ever 3D detection of longitudinal interfacial debonding in carbon and glass single‐fiber composites. This mechanism is not detected in multi‐fiber composite specimens, suggesting that single‐fiber composites are intrinsically unrepresentative of realistic composite behavior.
Enhancing Energy Density in Aqueous Ammonium‐Ion Supercapacitors via CuCo2S4@MoS2 Core@Shell Heterostructure Design
Authors: Ma Zhengxin , Zhang Yuhao , Wu Qingfeng , Cui Xiaosha , Wu Tianyu , Jiang Haiqing , Sui Xinyi , Tao Kun , Xie Erqing , Zhang Zhenxing
Published: October 2024

Aqueous ammonium‐ion supercapacitors (AASCs) are recognized for their rapid charge‐discharge capability, long cycle life, and excellent power density. However, they still confront the challenges of low energy density. To address the above issue, this work proposes a novel strategy involving the establishment of CuCo2S4@MoS2 core@shell heterostructures to enhance the capacity of electrode material. The double electric layer energy storage mechanism of the MoS2 shell facilitates the storage and provision of a substantial ammonium source for NH4+ insertion into CuCo2S4, thereby enhancing the electrochemical performance of AASCs. The density functional theory (DFT) calculations demonstrate that the CuCo2S4@MoS2 core@shell heterostructures exhibit better affinity for NH4+ and improved conductivity. Furthermore, the internal electric field at the heterojunction accelerates NH4+ transfer, thereby enhancing the pseudocapacitive behavior of CuCo2S4. Owing to the abundant active sites and pronounced pseudo‐capacitance, the CuCo2S4@MoS2 electrode achieves a specific capacity of 2045 C g−1 at 1 A g−1. With activated carbon (AC) as the negative electrode, the fabricated CuCo2S4@MoS2//AC AASC device attains a specific capacity of 591 C g−1 and an energy density of 83.23 Wh kg−1. This work presents a promising new strategy for the next generation of AASCs.
Electrical Doping in Sc‐III‐Nitrides: Toward Multifunctional Devices at the Single Device Level
Authors: Fathabadi Milad , Vafadar Mohammad Fazel , Lamanque Jean‐Christophe , Zhao Songrui
Published: October 2024

A homogeneous integration of various types of devices using a single material platform is an ideal route toward multifunctional devices at the single‐device level for miniaturized, fast, and energy‐efficient systems. However, such a single material platform is still missing. Scandium‐containing III‐nitrides (Sc‐III‐nitrides) are promising, but their electrical doping properties remain unknown. In this work, the electrical doping in Sc‐III‐nitrides is investigated and optoelectronic devices using Sc‐III‐nitrides on silicon (Si) are further demonstrated. The material format of the nanowire is used, with magnesium (Mg) serving as the impurity dopant to control the electrical doping. It is discovered that, by adjusting the Mg doping concentrations, the Sc‐III‐nitrides can be tuned from n‐type to p‐type. Device application in light‐emitting is further demonstrated using the p‐type Sc‐III‐nitrides as the hole injection layer. The performance comparison between devices using the regrown Sc‐containing p‐type contact layers and non‐Sc‐containing p‐type contact layers indicates the advantage of Sc incorporation in improving the quality of the regrown p‐type layer in a device structure. The electrical doping in Sc‐III‐nitrides demonstrated in this study represents an important step toward a homogeneous integration of different types of devices using a single material platform.
Wide Bandgap Donor can Offer High‐Efficiency LED Indoor Organic Photovoltaic with Indium‐Doped Zinc Oxide Electron Transport Layer
Authors: Lee Hyeong Won , Biswas Swarup , Choi Hyojeong , Lee Yongju , Kim Hyeok
Published: October 2024

Indoor organic photovoltaic (OPV) cells offer a compelling solution for powering diverse electronic devices integrated into the Internet of Things (IoT) network. They are prized for their robust power conversion efficiency (PCE), mechanical resilience, and ultra‐thin nature. The recent surge in inverted‐structure OPVs reflects their enhanced stability over conventional designs. Despite the advantage, their adaptation for indoor light utilization remains underexplored. Optimal selection of an electron transport layer (ETL) with precise energy band alignment is critical in this system. Herein, an inverted‐structured OPV is fabricated utilizing PBDB‐T as the wide bandgap donor, with a focus on enhancing its PCE under 1000 lx LED illumination through the doping of the zinc oxide‐ (ZnO‐) based ETL with indium (In). The results indicate that the device utilizing undoped ZnO as the ETL achieves a peak PCE of 9.42% under these specified conditions. Conversely, the OPV utilizing In‐doped ZnO as the ETL achieves a significantly higher PCE of 29.78% with 5 at% In, indicates the usefulness of ETL doping by In. This may be caused by the tuning of energy band alignment, improvement in electron mobility, and reduction in surface roughness of ZnO by In doping.
Camphorsulfonic‐Salified Chitosan Allowing MACl‐Free Stabilization of Pure FAPbI3 α‐Phase via Gravure Printing in Ambient Air
Authors: Vanni Nadir , Giuri Antonella , Calora Mario , Podda Edoardo , Caricato Anna Paola , Sparnacci Katia , Suhonen Riikka , Ylikunnari Mari , Covarelli Amanda , Gregori Luca , De Angelis Filippo , Marra Gianluigi , Biagini Paolo , Po Riccardo , Rizzo Aurora
Published: October 2024

Metal–halide perovskites have gained extreme interest in the photovoltaic field with formamidinium lead iodide (FAPbI3) currently being one of the best‐performing materials for single‐junction solar cells. Despite the outstanding record efficiencies, there are still several major issues hindering the large‐scale fabrication of perovskite solar cells. The vulnerability to environmental agents along with the need of controlled atmosphere and crystallization aids for the perovskite film deposition represents the major roadblocks. This is particularly true for FAPbI3 for which the thermodynamically stable phase at room temperature is photovoltaically inactive δ‐phase. To address those challenges, herein, a camphorsulfonic‐salified chitosan is specifically designed with the aid of DTF calculations to strongly interact with the perovskite and, as a result, improve the morphology and optoelectronic quality of the FAPbI3. Thanks to the numerous interactions and then the modulation of the solution viscosity, FAPbI3 devices are fabricated by gravure printing deposition without either antisolvent bath or inclusion of methylammonium chloride (MACl) as additive. The gravure‐printed devices with the chitosan feature an enhanced efficiency and stability in air, retaining 80% of the original efficiency after 1200 h in ambient air without any encapsulation.
An Efficient Algorithm for Exploitative Monetization Scam Video Detection Over Social Media Platforms
Authors: Tripathi Ashutosh , Bharti Kusum Kumari , Ghosh Mohona
Published: October 2024

In recent years, there has been a surge in scam videos on YouTube which make false assurances of monetary benefits to the viewers by performing trivial tasks such as watching videos, downloading dubious apps, and sharing personal identifiable information (PII). The present work aims to detect such videos referred to as exploitative monetization scam videos. In the first step of the proposed two‐step algorithm, two new features are derived, named as scam–parent comment ratio features and nonscam parent comment ratio features using Word2Vec‐based comment classifier. The next step combines these features and other video metadata features to perform the final labeled video classification using machine learning algorithms. Five different algorithms, namely Gaussian Naive Bayes, logistic regression, support vector machine, adaboost and random forest have been used in the video classification task. The results illustrate that the area‐under‐curve (AUC) score of 91% is obtained for the video classification. A comparative analysis of the proposed model with the other state‐of‐the‐art methods shows that our model outperforms others in the exploitative monetization scam video classification task.
Effect of Rare Earth Ce on Structure and Properties in 7CrSiMnMoV Die Steel Castings
Authors: Long Qian , Li Zongbo , Zeng Jie , Gao Xu , Wang Wanlin , Feng Yan
Published: October 2024

In this study, rare earth (RE) Ce is used to modify the interaction between atoms in 7CrSiMnMoV die steel castings. The tensile properties are performed, and strengthening mechanism are analyzed by investigated fracture surface, and microstructure by optical microscopy (OM) and scanning electron microscope‐energy dispersive spectrometer (SEM‐EDS). And ab initio molecular dynamics (AIMD) is used to simulate the effect of the Ce element on the local atomic structure of the FeCeC system alloy steel. The results indicate the strength can increase from 722.55 to 1074.27 MPa, and the elongation can increase from 24.86% to 44.22% with a RE Ce concentration of 0.009%. It is attributed to that doping of Ce can inhibit the formation of network eutectic cementite, refine the lamellar spacing of pearlite, and even form granular cementite and martensite structures. AIMD simulation results show that C atoms tend to be surrounded by Fe, and the strong chemical bonds of FeC make the Fe‐centered C more stable with an increase in RE Ce concentration. And doping Ce can introduce new local topological and chemical orderings such that the FeCFe triplets predominantly form small and big angles shifting from near 75° and 136° to 47° and 81°, respectively.
A Unified Framework for Covariate Adjustment Under Stratified Randomisation
Authors: Tu Fuyi , Ma Wei , Liu Hanzhong
Published: October 2024

Randomisation, as a key technique in clinical trials, can eliminate sources of bias and produce comparable treatment groups. In randomised experiments, the treatment effect is a parameter of general interest. Researchers have explored the validity of using linear models to estimate the treatment effect and perform covariate adjustment and thus improve the estimation efficiency. However, the relationship between covariates and outcomes is not necessarily linear, and is often intricate. Advances in statistical theory and related computer technology allow us to use nonparametric and machine learning methods to better estimate the relationship between covariates and outcomes and thus obtain further efficiency gains. However, theoretical studies on how to draw valid inferences when using nonparametric and machine learning methods under stratified randomisation are yet to be conducted. In this paper, we discuss a unified framework for covariate adjustment and corresponding statistical inference under stratified randomisation and present a detailed proof of the validity of using local linear kernel‐weighted least squares regression for covariate adjustment in treatment effect estimators as a special case. In the case of high‐dimensional data, we additionally propose an algorithm for statistical inference using machine learning methods under stratified randomisation, which makes use of sample splitting to alleviate the requirements on the asymptotic properties of machine learning methods. Finally, we compare the performances of treatment effect estimators using different machine learning methods by considering various data generation scenarios, to guide practical research.
Seismic performance assessment of reinforced concrete coupled walls reinforced with different types of shape memory alloys
Authors: Feli Shahryar , Asgari Marnani Jafar , Ghasemi Abbas , Monajemi Nejad Soheil
Published: October 2024

Novel earthquake‐resistant materials are of interest to the academic community because they have the potential to reduce seismic residual displacements and, by extension, maintenance costs. Smart materials and technologies have enhanced the seismic response of reinforced concrete (RC) buildings, but the effect of these advancements on issues that arise after earthquakes in RC‐coupled walls has not yet been investigated. This research scrutinizes the seismic performance of RC‐linked walls reinforced with NiTi, FeNCATB, and CuAlMn superelastic shape memory rebar in the boundary regions. As a part of the case study, three RC‐linked wall systems with four, eight, and twelve stories were adopted. The highest critical values for the inter‐story drift ratio (IDR) and the residual inter‐story drift ratio (RIDR) were obtained through the OpenSees program. According to the results, RIDR markedly reduces whenever concerns about the quake's aftermath are highlighted. In accordance with findings, among the whole adopted shape memory alloy (SMA) types in this research, the RC‐coupled wall based on Cu demonstrates superior results concerning RIDR and performs adequately regarding the restoring effect. As a result, seismically involved areas exposed to significant ground motions are typically recommended to use Cu‐based SMA material.
Distinct trajectories of symptomatic response in ulcerative colitis during filgotinib therapy: A post hoc analysis from the SELECTION study
Authors: Schreiber Stefan , Feagan Brian G. , Louis Edouard , Hisamatsu Tadakazu , Hibi Toshifumi , Dron Louis , Jamoul Corinne , Patel Haridarshan , Harris Kristina , Taliadouros Virginia , Oortwijn Alessandra , Peyrin‐Biroulet Laurent
Published: October 2024

Background

Filgotinib is an oral, once‐daily, Janus kinase 1 preferential inhibitor approved for treatment of ulcerative colitis (UC) following the phase 2b/3 SELECTION trial. Identification of patient populations and factors associated with long‐term treatment response trajectories may improve UC management.

Objective

We aimed to identify and describe distinct patient subgroups of response to filgotinib based on partial Mayo Clinic Score (pMCS) trajectories over time.

Methods

In these post hoc analyses of SELECTION, group‐based trajectory modeling (GBTM) was applied to pMCS to describe groups of distinct, symptom‐based patient trajectories using data from patients who responded to filgotinib 200 or 100 mg and continued receiving filgotinib up to week 58. Patient demographics, disease characteristics, and week 10 response were compared between the groups. Achievement of a patient‐level multi‐component endpoint of comprehensive disease control (CDC) was assessed in each group.

Results

GBTM identified five distinct patient populations with different response trajectories; 67.5% of patients had beneficial trajectories. The beneficial trajectory groups generally had higher proportions of patients who were recently diagnosed (<1 year), were receiving filgotinib 200 mg and were biologic‐naive versus the relapsing trajectory groups (4%–9% vs. 4%–5%; 43%–65% vs. 36%–46%; 54%–70% vs. 35%–58%, respectively). Furthermore, 55.4% of patients had sustained beneficial trajectories, with low baseline endoscopic subscores (≥43% of patients had a subscore of 2) and strong week 10 FCP responses (≥61% of patients with >50% decrease in FCP from baseline). Sustained beneficial trajectory groups had a higher probability of achieving CDC at week 58 than other groups (31%–32% vs. 0%–7%).

Conclusions

Beneficial long‐term response trajectories and achievement of CDC with filgotinib were associated with being biologic‐naive and having less severe disease at baseline. Early estimation of sustained and CDC may facilitate patient identification and development of personalized management strategies in UC.

ClinicalTrials.gov Identifier

NCT02914522.
Long‐term outcome of a canine longitudinal patellar fracture treated with lag screw and pin
Authors: Weniger Max Bernhard Hubertus , Feichtenschlager Christian , Linde Niklas , Peppler Christine
Published: October 2024

We report a rare case of a 4‐year‐old, female, mixed‐breed dog with a longitudinal patellar fracture of the left hindlimb. Orthopaedic examination revealed pain, swelling and crepitus in the patella. Stifle radiography and computed tomography confirmed a longitudinal patellar fracture with lateral displacement of the fragment. A lateral parapatellar approach was chosen to assess the stifle joint. Intraoperative findings were consistent with the diagnostic imaging findings, with an additional partial tear of the quadriceps tendon at the fracture location. The fracture was treated using a 2 mm lag screw combined with a 1.25 mm K‐wire, and the partial quadriceps tendon tear was repaired with a locking‐loop suture. Despite a soft tissue injury due to temporary external coaptation treated conservatively, recovery was uneventful, and lameness gradually decreased, remaining lameness‐free from postoperative Week 7. The dog finally returned to full activity without recurrence of lameness during long‐term follow‐up (422 days).
Consciousness Under the Spotlight: The Problem of Measuring Subjective Experience
Authors: Jimenez Mikel , Prieto Antonio , Hinojosa José Antonio , Montoro Pedro R.
Published: October 2024

The study of consciousness is considered by many one of the most difficult contemporary scientific endeavors and confronts several methodological and theoretical challenges. A central issue that makes the study of consciousness so challenging is that, while the rest of science is concerned with problems that can be verified from a “third person” view (i.e., objectively), the study of consciousness deals with the phenomenon of subjective experience, only accessible from a “first person” view. In the present article, we review early (starting during the late 19th century) and later efforts on measuring consciousness and its absence, focusing on the two main approaches used by researchers within the field: objective (i.e., performance based) and subjective (i.e., report based) measures of awareness. In addition, we compare the advantages and disadvantages of both types of awareness measures, evaluate them according to different methodological considerations, and discuss, among other issues, the possibility of comparing them by transforming them to a common sensitivity measure (d′). Finally, we explore several new approaches—such as Bayesian models to support the absence of awareness or new machine‐learning based decoding models—as well as future challenges—such as measuring the qualia, the qualitative contents of awareness—in consciousness research.
Intersymbolic AI
Authors: Platzer André
Published: October 2024

This perspective piece calls for the study of the new field of Intersymbolic AI, by which we mean the combination of symbolic AI, whose building blocks have inherent significance/meaning, with subsymbolic AI, whose entirety creates significance/effect despite the fact that individual building blocks escape meaning. Canonical kinds of symbolic AI are logic, games and planning. Canonical kinds of subsymbolic AI are (un)supervised machine and reinforcement learning. Intersymbolic AI interlinks the worlds of symbolic AI with its compositional symbolic significance and meaning and of subsymbolic AI with its summative significance or effect to enable culminations of insights from both worlds by going between and across symbolic AI insights with subsymbolic AI techniques that are being helped by symbolic AI principles. For example, Intersymbolic AI may start with symbolic AI to understand a dynamic system, continue with subsymbolic AI to learn its control, and end with symbolic AI to safely use the outcome of the learned subsymbolic AI controller in the dynamic system. The way Intersymbolic AI combines both symbolic and subsymbolic AI to increase the effectiveness of AI compared to either kind of AI alone is likened to the way that the combination of both conscious and subconscious thought increases the effectiveness of human thought compared to either kind of thought alone. Some successful contributions to the Intersymbolic AI paradigm are surveyed here but many more are considered possible by advancing Intersymbolic AI.
DiTEC: Digital Twin for Evolutionary Changes in Water Distribution Networks
Authors: Degeler Victoria , Hadadian Mostafa , Karabulut Erkan , Lazovik Alexander , van het Loo Hester , Tello Andrés , Truong Huy
Published: October 2024

Conventional digital twins (DT) for critical infrastructures are widely used to model and simulate the system’s state. But fundamental environment changes bring challenges for DT adaptation to new conditions, leading to a progressively decreasing correspondence of the DT to its physical counterpart. This paper introduces the DiTEC system, a Digital Twin for Evolutionary Changes in Water Distribution Networks (WDN). This framework combines novel techniques, including semantic rule learning, graph neural network-based state estimation, and adaptive model selection, to ensure that changes are adequately detected, processed and the DT is updated to the new state. The DiTEC system is tested on the Dutch Oosterbeek region WDN, with results showing the superiority of the approach compared to traditional methods.
Risk factors for treatment-related sensorineural hearing loss and hearing aid use in medulloblastoma patients: an observational cohort study
Authors: Troschel Fabian M. , Steike David Rene , Roers Julian , Kittel Christopher , Siats Jan , Parfitt Ross , Hesping Amélie E. , am Zehnhoff-Dinnesen Antoinette , Neumann Katrin , Eich Hans Theodor , Scobioala Sergiu
Published: October 2024

Purpose

This study aimed to analyze treatment-related risk factors for sensorineural hearing loss (SNHL) and an indication for hearing aids (IHA) in medulloblastoma patients after craniospinal radiotherapy (CSRT) and platin-based chemotherapy (PCth).

Methods

A total of 58 patients (116 ears) with medulloblastoma and clinically non-relevant pre-treatment hearing thresholds were included. Cranial radiotherapy and PCth were applied sequentially according to the HIT 2000 study protocol or post-study recommendations, the NOA-07 protocol, or the PNET (primitive neuroectodermal tumor) 5 MB therapy protocol. Audiological outcomes up to a maximum post-therapeutic follow-up of 4 years were assessed. The incidence, post-treatment progression, and time-to-onset of SNHL, defined as Muenster classification grade ≥MS2b, were evaluated. Risk factors for IHA were analyzed separately.

Results

While 39 patients received conventionally fractionated RT (CFRT; group 1), 19 patients received hyperfractionated RT (HFRT; group 2). Over a median follow-up of 40 months, 69.2% of ears in group 1 experienced SNHL ≥MS2b compared to 89.5% in group 2 (p = 0.017). In multivariable Cox regressions analysis, younger age and increased mean cochlear radiation dose calculated as the equivalent dose in 2‑Gy fractions (EQD2) were associated with time-to-onset of SNHL ≥MS2b (p = 0.019 and p = 0.023, respectively) and IHA (p < 0.001 and p = 0.016, respectively). Tomotherapy and supine positioning were associated with a lower risk for IHA in univariable modelling only (p = 0.048 and p = 0.027, respectively).

Conclusion

Young age and cochlear EQD2 Dmean ≥40 Gy are significant risk factors for the incidence, degree, and time-to-event of SNHL as well as for IHA in medulloblastoma patients.
Level-set topology optimization with PDE generated conformal meshes
Authors: Schmidt Mathias R. , Barrera Jorge L. , Mittal Ketan , Swartz Kenneth E. , Tortorelli Daniel A.
Published: October 2024

This paper presents a level-set topology optimization approach that uses conformal meshes for the analysis of the displacement field. The structure’s boundary is represented by the iso-contour of a level-set field discretized on a fixed background design mesh. The conformal mesh is updated for each design iteration via a PDE based mesh morphing process that identifies the set of facets in the background mesh that are homeomorphic to the boundary and relaxes the homeomorphic mesh to conform to the structure’s boundary and ensure high element quality. The conformal mesh allows for a more accurate computation of the response versus density and some level-set based methods which interpolate material properties using the volume fraction. Numerical examples illustrate the proposed approach by optimizing linear-elastic two- and three-dimensional structures, wherein insight into the performance of the mesh morphing process is provided. The examples also highlight the scalability of the approach.
ESR Essentials: radiomics—practice recommendations by the European Society of Medical Imaging Informatics
Authors: Santinha João , Pinto dos Santos Daniel , Laqua Fabian , Visser Jacob J. , Groot Lipman Kevin B. W. , Dietzel Matthias , Klontzas Michail E. , Cuocolo Renato , Gitto Salvatore , Akinci D’Antonoli Tugba
Published: October 2024

Radiomics is a method to extract detailed information from diagnostic images that cannot be perceived by the naked eye. Although radiomics research carries great potential to improve clinical decision-making, its inherent methodological complexities make it difficult to comprehend every step of the analysis, often causing reproducibility and generalizability issues that hinder clinical adoption. Critical steps in the radiomics analysis and model development pipeline—such as image, application of image filters, and selection of feature extraction parameters—can greatly affect the values of radiomic features. Moreover, common errors in data partitioning, model comparison, fine-tuning, assessment, and calibration can reduce reproducibility and impede clinical translation. Clinical adoption of radiomics also requires a deep understanding of model explainability and the development of intuitive interpretations of radiomic features. To address these challenges, it is essential for radiomics model developers and clinicians to be well-versed in current best practices. Proper knowledge and application of these practices is crucial for accurate radiomics feature extraction, robust model development, and thorough assessment, ultimately increasing reproducibility, generalizability, and the likelihood of successful clinical translation. In this article, we have provided researchers with our recommendations along with practical examples to facilitate good research practices in radiomics.

Key Points

Radiomics’ inherent methodological complexity should be understood to ensure rigorous radiomic model development to improve clinical decision-making.

Adherence to radiomics-specific checklists and quality assessment tools ensures methodological rigor.

Use of standardized radiomics tools and best practices enhances clinical translation of radiomics models.