bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estimating Meaningful Differences in Measures of Neuropathic Impairment, Health‐Related Quality of Life, and Nutritional Status in Patients With Hereditary Transthyretin Amyloidosis
Authors: Folkvaljon Folke , Gertz Morie , Gillmore Julian D. , Khella Sami , Masri Ahmad , Maurer Mathew S. , Cruz Márcia Waddington , Wixner Jonas , Chen Jersey , Reicher Barry , Kwoh Jesse , Yarlas Aaron , Berk John L. 
Published: November 2024

ABSTRACTIntroduction/AimsThe degree of change in neuropathic impairment and quality of life (QoL) that is clinically meaningful to patients with hereditary transthyretin amyloidosis with polyneuropathy (ATTRv‐PN) is not established. This study aimed to estimate the magnitude of treatment differences that are meaningful to patients in measures of neuropathy and QoL and to determine whether eplontersen achieved a meaningful improvement versus placebo.MethodsData from the NEURO‐TTRansform trial on patients with ATTRv‐PN treated with eplontersen (n = 141) or historical placebo (n = 59) were used. Anchor‐based approaches were used to estimate thresholds for meaningful differences in the modified Neuropathy Impairment Score +7 (mNIS+7) composite score, Norfolk QoL‐Diabetic Neuropathy (Norfolk QoL‐DN) total score, Neuropathy Symptoms and Change (NSC) total score, and modified body mass index (mBMI). Differences between the least squares means of the treatment groups were analyzed.ResultsMeaningful improvement in mNIS+7 was estimated as −4.0 points and deterioration as 1.8 points. The estimated ranges of meaningful improvement and deterioration in Norfolk QoL‐DN were −12.8 to −4.0 points, and 5.9 to 14.7 points, respectively. For NSC, ranges were −2.4 to −1.3 points for meaningful improvement, and 0.6 to 5.8 points for deterioration. The estimated meaningful improvement in mBMI was 9.8 kg/m2 × g/L and deterioration was −40.9 kg/m2 × g/L. Improvements in each measure with eplontersen versus placebo were greater than the estimates of meaningful differences.DiscussionEplontersen demonstrated a clinically meaningful effect on neuropathic impairment, QoL, and nutritional status. Such estimates have implications for clinical practice and trials.
Underneath the Surface: Examining “Hidden Lesions” With Paleoimaging at Moita do Sebastião, Mesolithic Muge, Portugal
Authors: Coutinho Nogueira Dany , Ramos Gaspar Rosa , Carreiro Inês , Godinho Ricardo Miguel , Umbelino Cláudia 
Published: November 2024

ABSTRACTDiscovered 160 years ago, the Muge archaeological sites in Portugal yield the most significant documentation of human skeletons from the Mesolithic period in Western Europe (8200–7100 cal B.P.). However, sediment weight has caused significant postmortem alterations that have limited previous studies. Paleoimaging techniques were applied to overcome these limitations and provide previously inaccessible information. Thirteen crania from Moita do Sebastião (one of the Muge shell middens) were CT scanned for virtual reconstruction and morphological analysis. Meticulous examination of 2D and 3D images revealed bone changes not visible to the naked eye and unrelated to postmortem alterations. A comprehensive differential diagnosis was carried out identifying various pathological conditions including epidermoid or dermoid cysts, intraosseous hemangioma, and a possible case of anemia. These “hidden pathologies” offer new insights into the health status of one of Europe's last hunter–gatherer populations.
Potential Bias Models With Bayesian Shrinkage Priors for Dynamic Borrowing of Multiple Historical Control Data
Authors: Ohigashi Tomohiro , Maruo Kazushi , Sozu Takashi , Sawamoto Ryo , Gosho Masahiko 
Published: November 2024

ABSTRACTWhen multiple historical controls are available, it is necessary to consider the conflicts between current and historical controls and the relationships among historical controls. One of the assumptions concerning the relationships between the parameters of interest of current and historical controls is known as the “Potential biases.” Within the “Potential biases” assumption, the differences between the parameters of interest of the current control and of each historical control are defined as “potential bias parameters.” We define a class of models called “potential biases model” that encompass several existing methods, including the commensurate prior. The potential bias model incorporates homogeneous historical controls by shrinking the potential bias parameters to zero. In scenarios where multiple historical controls are available, a method that uses a horseshoe prior was proposed. However, various other shrinkage priors are also available. In this study, we propose methods that apply spike‐and‐slab, Dirichlet–Laplace, and spike‐and‐slab lasso priors to the potential bias model. We conduct a simulation study and analyze clinical trial examples to compare the performances of the proposed and existing methods. The horseshoe prior and the three other priors make the strongest use of historical controls in the absence of heterogeneous historical controls and reduce the influence of heterogeneous historical controls in the presence of a few historical controls. Among these four priors, the spike‐and‐slab prior performed the best for heterogeneous historical controls.
AutoMine: A Multimodal Dataset for Robot Navigation in Open‐Pit Mines
Authors: Li Yuchen , Teng Siyu , Wang Junhui , Ai Yunfeng , Tian Bin , Xuanyuan Zhe , Bing Zhenshan , Knoll Alois C. , Wang Fei‐Yue , Chen Long 
Published: November 2024

ABSTRACTIn the past decade, autonomous driving has witnessed significant advancements, largely attributable to the evolution of precise algorithms and efficient computing platforms. Nevertheless, the open‐pit mine, a typical scenario within closed‐field environments, has garnered limited attention in autonomous driving, primarily owing to the scarcity of data and experimental benchmarks. This work presents original data collected from five platforms, comprising one passenger vehicle, three wide‐body trucks, and one mining truck, across eight different mining sites. We provide a comprehensive elucidation of platform types, sensors, calibration methodologies, synchronization techniques, data collection approaches, and a thorough analysis of the data characteristics. In addition, we offer a detailed benchmark comparison of short and long odometry and navigation performance across multiple vehicles in open‐pit mines. With comprehensive data characteristics, experimental performance evaluations, and thorough analysis, we believe that this work establishes a robust research foundation for navigation and fusion methods in open‐pit mines, thereby constituting a significant contribution to the autonomous driving and field robotics communities.
How social and environmental investments attract and repel foreign investors: Insights on shareholder and stakeholder engagement
Authors: Khan Talat Mehmood , Zhu Naiping 
Published: November 2024

AbstractThis study investigates the diversifying impact of social and environmental investment (SEI) to attract and repel foreign investors (FIs) while determining to invest in environmental friendly firms. By analyzing SEI strategies within the Chinese context and employing panel data regression analysis, this study reveals numerous major insights. First, firms implementing average SEI strategies tend to attract greater investments from FI. On the other hand, above average SEI do not yield similar benefits, indicating that over‐investments in social and environmental projects could repel potential investors, and result in a transfer of wealth from shareholders to stakeholders. Furthermore, the present study reveals that firm performance strengthens the positive association between average SEI and FI. Finally, this study finds that the negative relationship between above‐average SEI and FI is intensified when firm performance is considered as a moderating factor. These insights are crucial for policymakers in formulating strategies to enhance foreign investments.
A Partially Randomized Patient Preference, Sequential, Multiple‐Assignment, Randomized Trial Design Analyzed via Weighted and Replicated Frequentist and Bayesian Methods
Authors: Wank Marianthie , Medley Sarah , Tamura Roy N. , Braun Thomas M. , Kidwell Kelley M. 
Published: November 2024

ABSTRACTResults from randomized control trials (RCTs) may not be representative when individuals refuse to be randomized or are excluded for having a preference for which treatment they receive. If trial designs do not allow for participant treatment preferences, trials can suffer in accrual, adherence, retention, and external validity of results. Thus, there is interest surrounding clinical trial designs that incorporate participant treatment preferences. We propose a Partially Randomized, Patient Preference, Sequential, Multiple Assignment, Randomized Trial (PRPP‐SMART) which combines a Partially Randomized, Patient Preference (PRPP) design with a Sequential, Multiple Assignment, Randomized Trial (SMART) design. This novel PRPP‐SMART design is a multi‐stage clinical trial design where, at each stage, participants either receive their preferred treatment, or if they do not have a preferred treatment, they are randomized. This paper focuses on the clinical trial design for PRPP‐SMARTs and the development of Bayesian and frequentist weighted and replicated regression models (WRRMs) to analyze data from such trials. We propose a two‐stage PRPP‐SMART with binary end of stage outcomes and estimate the embedded dynamic treatment regimes (DTRs). Our WRRMs use data from both randomized and non‐randomized participants for efficient estimation of the DTR effects. We compare our method to a more traditional PRPP analysis which only considers participants randomized to treatment. Our Bayesian and frequentist methods produce more efficient DTR estimates with negligible bias despite the inclusion of non‐randomized participants in the analysis. The proposed PRPP‐SMART design and analytic method is a promising approach to incorporate participant treatment preferences into clinical trial design.
Cutting‐Edge Strategies and Advancements for Combating Synthetic Polymer Pollution in Various Environmental Samples: A Review
Authors: Sajad Samreen , Allam Bharat Kumar , Banerjee Sushmita , Yahya M. Z. A. , Rahman Nor Mas Mira Abd , Singh Pramod Kumar 
Published: November 2024

AbstractPlastic debris is unavoidably released into the ecosystems, and their physicochemical and mechanical qualities deteriorate when exposed to the environment. This, ultimately, leads to the generation of tiny fragments of plastic, which are known as nanoplastics (<1000 nm) and microplastics (<5 mm). Over the past few years, the pollution of synthetic polymers has been reported in almost all the compartments of the environment across the globe. It is regarded as a hazard to both human health and natural systems. In addition, synthetic polymers act as vectors for contaminants as they can adsorb and accumulate contaminants from seawater. The accumulation of plastic waste in the environment and its widespread presence have drawn the attention of policymakers and the public. This global issue has led to the creation of numerous remediation solutions by innovators in previous decades, either to clear up old waste or to stop plastic from entering the various matrices of the environment. This review focused on the extensive scientific research available on effective techniques for removing plastic debris to promote positive action and progress in this important area. Despite the various challenges, these techniques offer vital opportunities, from increasing awareness to enhancing environmental quality. Further, the article has been enriched by incorporating bibliometric data that illustrates the widely used methods for removing microplastics from various environmental matrices. According to the data analysis, numerous remediation techniques have been developed to date (2010 and 2024). These techniques encompass various approaches, among which the chemical‐based methods enjoy more success. This success can be attributed to the diverse advantages offered by chemical‐based methods over other remediation techniques. Much research is now focused on overcoming the disadvantages and developing more efficient and environmentally sound technologies.
Fluoride Ions Sequestration From Contaminated Water Using PVA‐Agar‐Based Green Anion‐Exchanger
Authors: Balram  , Singh Kaith Balbir 
Published: November 2024

AbstractThe current work is focused on the designing of a green interpenetrating polymer network (IPN) PA@polyAAm:AN using polyvinyl alcohol‐agar hybrid backbone and its subsequent conversion into an anion‐exchanger PA@polyAAm:AN‐AE through reduction of nitrile group in presence of LiAlH4. Further, the reduced form of IPN was quaternized using methyl iodide so that anion to anion exchange could take place between F− and I− anions. The primary objective of synthesizing an anion‐exchanger was to eliminate F− ions from contaminated water through the utilization of a prepared device. During the optimization of different experimental parameters for getting the optimal anion‐exchange capacity (AEC), the favorable conditions found were: pH, 9.0; contact period, 120 min; adsorbent dosage, 30 mg and initial F− ion concentration, 8.0 mg L−1. The pseudo‐second order kinetic model best described the F− ions adsorption kinetics, with a 0.97 R2 value. The rate constant (KF) was found to be 2.3, which further supported the validity of the Freundlich isotherm. Thus, the current study has remarkable potential with a 79.99% adsorption capacity for eliminating F− ions. Moreover, the ecofriendly anion‐exchanger prepared was found effective in the removal of F− ions from aqueous medium up to four cycles during reusability analysis.
Localized Vibrations and Bound Exciton Mediated Emission in 2D Dion–Jacobson Perovskites
Authors: Choudhary Shivani , Maurya Naresh Chandra , Tailor Naveen Kumar , Adarsh K. V. , Satapathi Soumitra 
Published: November 2024

AbstractHerein, the emission characteristics of diammonium N,N,N′,N′‐tetramethyl‐1,4‐phenylenediammonium (TMPDA) are investigated based on lead iodide (TMPDA)PbI4 perovskite single crystals correlated with the localized lattice vibrations. Dual emission characteristics are ascribed to the existence of free exciton and bound exciton. The photoluminescence spectra as a function of excitation power and temperature show that structural distortion and exciton‐phonon coupling impact emission characteristics substantially. The coupling strength between excitons and phonons in (TMPDA)PbI4 is estimated as γac = 308.96 µeV and γLO = 62.3 meV, which is much higher than inorganic semiconductors. Further, bound exciton band recombination is significantly suppressed at lower temperatures due to increased localization of carriers. Specific heat deviation from the Dulong–Petit law indicates strong coupling in the lattice. The Debye‐Einstein model reveals multiple low‐energy localized independent vibrations, leading to phonon coupling with bound excitons. This interplay, along with Bosonic features, significantly influences emission properties. Further, it is observed that photocurrent as a function of the incident intensity follows a law ∝ I0α with α = 0.54, attributed to substantial bimolecular recombination of carriers. The findings of the study provide an in‐depth understanding of emission characteristics, lattice distortion, and interplay of electron‐phonon coupling in DJ phase 2D perovskite system.
Incongruous Harmonics of Vibrating Solid‐Solid Interface
Authors: Biglarbeigi Pardis , Morelli Alessio , Bhattacharya Gourav , Ward Joanna , Finlay Dewar , Bhalla Nikhil , Payam Amir Farokh 
Published: November 2024

AbstractDeconvoluting the vibrations and harmonics in solid‐solid interfaces is crucial for designing materials with improved performance, durability, and functionality. The measured vibrating microcantilever signal in the dynamic atomic force microscopy (AFM) encompasses a multitude of distinct signatures reflecting a diverse array of material properties. Nevertheless, uncertainties persist in decoding these signatures, primarily arising from the interplay between attractive and repulsive forces. Consequently, it is challenging to correlate the generated harmonics within the solid‐solid interfaces with the imaged phase and topography of materials, as well as the occasional observed contrast reversal. In this study, the vibration harmonics produced at solid‐solid interfaces are correlated, linking them to short‐range nano‐mechanical characteristics through a comprehensive blend of theory, simulation, and experimental methods. These findings shed light on the roots of harmonic generation and contrast reversals, opening avenues for designing innovative materials with customized properties.
Interface Engineering of Network‐Like 1D/2D (NHCNT/Ni─MOF) Hybrid Nanoarchitecture for Electrocatalytic Water Splitting
Authors: Bhosale Mrunal , Murugan Nagaraj , Kim Yoong Ahm , Thangarasu Sadhasivam , Oh Tae‐Hwan 
Published: November 2024

AbstractHere, integrated functional components into a hybrid heterostructure via highly stabilized network‐like interconnected electronic nanoarchitecture of 1D N‐doped holey‐carbon nanotube (NHCNT) with 2D nickel─metal–organic framework (Ni─MOF) nanosheets are developed as high‐performance electrocatalyst for overall water splitting. The NHCNT promoting electron transport pathways in electrocatalyst, and formation of holes in nanotubes further enables excellent diffusion of ions for promoting the overall reaction rate. An excellent combination of 1D/2D structure of NHCNT/Ni─MOF‐4 electrocatalyst exhibits excellent oxygen evolution reaction (η10 = 207.8 mV, and Tafel = 62.6 mV dec−1) and reasonable hydrogen evolution reaction (η10 = 159.8 mV, and Tafel = 107.69 mV dec−1) activity with consistent and stable performance in a 1 m KOH. The highly interconnected network structure contains Ni2+ and Ni3+ species in the NHCNT/Ni─MOF‐4 electrocatalyst, which possesses high specific surface area (SSA) (235.53 m2 g−1), electrochemically active surface area (ECSA) (796.2 cm2), mass activity (4.76 mA mg−1), and turnover frequency (3.99 × 10−2 s−1), which provide remarkable electrocatalytic performance via generating synergy between the NHCNT and Ni─MOF. For overall water splitting, NHCNT/Ni─MOF‐4 attains a low cell voltage (1.77 V@10 mA cm−2).
Semi‐Blind Watermarking and Blockchain‐Based Approach for Copyright Protection of Medical Images
Authors: Kaur Gurleen , Gupta Bakul , Anand Ashima 
Published: November 2024

ABSTRACTThe security of Digital Healthcare Records (DHR) data remains significantly under‐researched, despite the extensive research conducted on watermarking for healthcare applications. This article introduces strong and secure watermarking algorithms designed to ensure the transmission and storage of DHR in blockchain‐based healthcare applications. The suggested method uses Non‐Subsampled Shearlet Transform (NSST) along with Multi‐Resolution Singular Value Decomposition (MRSVD) to add watermark data to the medical host image with as little distortion as possible. NSST has the advantage of being resistant to shift and is effective at gathering more directional data. To protect the image from unwanted access, the watermarked image is encrypted using Hybrid Chaotic Shift Transform and modified Henon Maps, rendering it resilient against various signal processing attacks. Additionally, Blockchain technology is implemented for the transfer of marked images, eliminating the necessity for any untrustworthy third party. The experimental findings of the watermarking technology demonstrate substantial resilience to various attacks while preserving the high quality of the marked image with the average PSNR and NC values of 55.03124 dB and 0.999203, respectively. This strategy demonstrates superior robustness compared to existing methods, with an optimal enhancement of 47.74%.
Upcycling of Beer Industry Wastewater: Biosurfactant Production and Application in Brewery Effluent Treatment
Authors: Sant'Ana Tatiana da Silva , Latorres Juliana Machado , Guimarães Martins Vilásia 
Published: November 2024

ABSTRACTThe beer processing industry generates large amounts of effluents rich in organic and inorganic material, and complex and expensive systems are commonly used for their treatment. Therefore, new alternatives capable of ensuring sustainable industrial growth through cost‐effective solutions are being studied. In this context, biosurfactants stand out due to their ability to degrade and remove contaminants from the environment. Therefore, the objective of this study was to evaluate the potential treatment of effluents from the beer industry using biosurfactants produced from wastewater from the beer industry. The biosurfactants were obtained by submerged cultivation at 30°C for 48 h using the bacterium Corynebacterium aquaticum in a mineral medium added of carbon source. The characterization of the biosurfactants was performed in relation to surface tension, emulsifying activity (EA), pH, and ionic character. The analyses were performed at 0, 24, and 48 h. The efficiency of the effluent treatments was evaluated by characterization in duplicate, before, during and after the treatment, regarding the concentrations of biochemical oxygen demand (BOD), chemical oxygen demand (COD), and total solids (TS). The best biosurfactant results were obtained using C. aquaticum in a medium with 10% (v/v) of brewing industry wastewater (BIW) as a carbon source after 48 h of cultivation, reaching a surface tension of 35.1 ± 0.2 mN/m, EA of 40.9 ± 0.5%, and stability under extreme conditions of temperature (−20°C to 121°C), salt (1% to 10%), and pH (4 to 10). Thus, the biosurfactant was applied for 10 days in an aerated biological treatment system. Best results were observed in biosurfactant concentrations of 0.5 CMD (critical micellar dilution), reaching improvement of up to 55.9% for BOD, 23.8% for COD, and 50.6% for TS. Thus, the biosurfactant produced (10% BIW) shows potential as an accelerator in the brewing industry effluent (BIE) treatment process, without purification and sterilization of the biocompound. Therefore, brewery wastewater proved to be a sustainable and nutritional substrate to obtain biosurfactants.
Generative Modelling of Stochastic Rotating Shallow Water Noise
Authors: Lobbe Alexander , Crisan Dan , Lang Oana 
Published: November 2024

AbstractIn recent work Crisan and co-authors (Foundations of Data Science, 2023), have developed a generic methodology for calibrating the noise in fluid dynamics stochastic partial differential equations where the stochasticity was introduced to parametrize subgrid-scale processes. The stochastic parameterization of sub-grid scale processes is required in the estimation of uncertainty in weather and climate predictions, to represent systematic model errors arising from subgrid-scale fluctuations. The methodology in Crisan (Foundations on Data Science, 2023) used a principal component analysis (PCA) technique based on the ansatz that the increments of the stochastic parametrization are normally distributed. In this chapter, the PCA technique is replaced by a generative model technique. This enables us to avoid imposing additional constraints on the increments. The methodology is tested on a stochastic rotating shallow water model with the elevation variable of the model used as input data. The numerical simulations show that the noise is indeed non-Gaussian. The generative modelling technology gives good RMSE, CRPS score and forecast rank histogram results.