bluuebunny/crossref_metadata_2025_split huggingface dataset:
Performance analysis of solution-processed nanosheet strain sensors—a systematic review of graphene and MXene wearable devices
Authors: Boland Conor S 
Published: February 2024

AbstractNanotechnology has led to the realisation of many potentialInternet of Thingsdevices that can be transformative with regards to future healthcare development. However, there is an over saturation of wearable sensor review articles that essentially quote paper abstracts without critically assessing the works. Reported metrics in many cases cannot be taken at face value, with researchers overly fixated on large gauge factors. These facts hurt the usefulness of such articles and the very nature of the research area, unintentionally misleading those hoping to progress the field. Graphene and MXenes are arguably the most exciting organic and inorganic nanomaterials for polymer nanocomposite strain sensing applications respectively. Due to their combination of cost-efficient, scalable production and device performances, their potential commercial usage is very promising. Here, we explain the methods for colloidal nanosheets suspension creation and the mechanisms, metrics and models which govern the electromechanical properties of the polymer-based nanocomposites they form. Furthermore, the many fabrication procedures applied to make these nanosheet-based sensing devices are discussed. With the performances of 70 different nanocomposite systems from recent (post 2020) publications critically assessed. From the evaluation of these works using universal modelling, the prospects of the field are considered. Finally, we argue that the realisation of commercial nanocomposite devices may in fact have a negative effect on the global climate crisis if current research trends do not change.
A color image encryption scheme based on cellular neural networks and linear feedback shift registers
Authors: Yan Shaohui , Wang Jianjian , Li Lin 
Published: February 2024

Abstract
In this paper, a cellular neural network (CNN) chaotic system is constructed and the multiple stability of the system and its rich chaotic properties are confirmed by studying the effect of parameters on the system, coexisting attractors, and offset boosting behavior. As linear feedback shift registers (LFSR) can be applied to cryptography, this paper applies LFSR to generate encrypted key matrices to enhance the randomness of encryption algorithms. Based on CNN and LFSR, a new color image encryption algorithm is designed by combining DNA coding and bit-plane decomposition with high bit-plane Zigzag dislocation changes. Experimental results and security tests show that the algorithm is highly secure and resistant to a variety of common attacks, such as differential attacks, cropping attacks, and noise attacks.
Insights into the design principles of JF-ED-VTFET for biosensing application
Authors: Singh Shailendra , Agnihotri Suneet Kumar , Tewari Vijay Kumar , Bharti Kamlesh Kumar , Hossain M Khalid , Samajdar D P 
Published: February 2024

Abstract
In this research article, we have designed a junction-free electrostatically doped vertical tunnel field-effect transistor (JF-ED-VTEFT) for label-free biosensing applications. We incorporated a nano-cavity within the gate-oxide layer near the source end of the FET to enable the detection of biomolecules based on the principle of dielectric modulation and without the requirement of external labeling. The proposed biosensor is thoroughly analyzed, considering various aspects such as electric field, energy band, transfer characteristics, and sensitivity parameters including energy band diagram, ON-current, ION/IOFF ratio, electrical analysis, and surface potential characteristics. The investigation of sensitivity encompasses practical challenges, such as different filling factors and step-profiles resulting from steric hindrance. In addition, the performance of the biosensor is evaluated by analyzing the temperature and scaling fluctuation in the integrated nanocavities. Additionally, values of biomolecules that are close to standard have been taken to validate the performance and provide insight into the sensitivity of the biosensor for detecting and analyzing the molecules.
Dynamic analysis and circuit realization of a new controllable hyperchaotic system
Authors: Lalili Yehia , Bouden Toufik , Grimes Morad , Yalcin Mustak E , Lachouri Abderrazak , Elbasi Ersin 
Published: February 2024

Abstract
Amidst the realm of hyper-chaotic systems, a notable deficiency is the absence of amplitude control and signal polarity. This paper addresses this limitation by introducing a new 4-D hyper-chaotic system with a hidden equilibrium-free attractor. The study focuses on amplitude control, achieved by adjusting a specific parameter, enabling manipulation of variable magnitudes while maintaining the overall signal. The offset boosting technique is investigated, enabling flexible shifting of the attractor in a desired direction. A real circuit experiment validates the proposed system’s practical applicability, confirming consistency with theoretical analysis and numerical simulations. Through introducing this new-found, the study holds significant importance for various fields, such as communications engineering and chaos-based cryptography, where precise control of signal characteristics is paramount.
Defects induced changes in conduction bands of HfS2
Authors: Lin Yu , Xiao Shaozhu , Zhang Xin , Liu Wei , He Yunpeng , Zhou Zheng , Yang Xiufu , Zhang Shiju , He Shaolong , Guo Yanfeng , Zhao Yong 
Published: February 2024

Abstract
We report on a comprehensive study of the electronic structures of the layered semiconductor 1T-HfS2 by employing angle-resolved photoemission spectroscopy (ARPES). With in-situ potassium doping, the band structures of HfS2 could be tuned, and both of the valence band and the conduction band could be observed. S vacancy defects could be induced by post-annealing of HfS2 and a certain amount of S vacancies would result in a peculiar change of the conduction band at

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point— the fracture of the conduction band bottom. Our results could provide key information for the defect studies and the application of HfS2.
Cryptanalysis and improvement of quantum secure multi-party summation using single photons
Authors: Tsai Chia-Wei , Lin Jason , Yang Chun-Wei 
Published: February 2024

Abstract
A previous study [Entropy 25.4 (2023): 590] proposed a quantum secure multi-party summation protocol wherein n participants could obtain the modulo-2 summation result using single photons and single-particle operations. Owing to the absence of an entanglement state, this protocol was more practical than other quantum summation protocols that used entanglement properties. Thus, this study investigated the claim that this proposed protocol prevented the participants’ secret inputs from being disclosed. It was found that the previously proposed protocol was vulnerable to a quantum Trojan horse attack owing to the circular qubit transmission mode. Using a security loophole, this study proposed an attack strategy that allowed an outside attacker to steal any participant’s secret input without being detected by a third party and participants. In addition, a simulation experiment was conducted to demonstrate the feasibility of the proposed attack and evaluate the number of quantum Trojan horse probes that the attacker must inject into regular qubit sequences. Finally, a solution was proposed by modifying the protocol to securely prevent quantum Trojan horse attacks.
Multi-source domain adaptation based tempo-spatial convolution network for cross-subject EEG classification in RSVP task
Authors: Wang Xuepu , Li Bowen , Lin Yanfei , Gao Xiaorong 
Published: February 2024

Abstract

Objective. Many subject-dependent methods were proposed for electroencephalogram (EEG) classification in rapid serial visual presentation (RSVP) task, which required a large amount of data from new subject and were time-consuming to calibrate system. Cross-subject classification can realize calibration reduction or zero calibration. However, cross-subject classification in RSVP task is still a challenge. Approach. This study proposed a multi-source domain adaptation based tempo-spatial convolution (MDA-TSC) network for cross-subject RSVP classification. The proposed network consisted of three modules. First, the common feature extraction with multi-scale tempo-spatial convolution was constructed to extract domain-invariant features across all subjects, which could improve generalization of the network. Second, the multi-branch domain-specific feature extraction and alignment was conducted to extract and align domain-specific feature distributions of source and target domains in pairs, which could consider feature distribution differences among source domains. Third, the domain-specific classifier was exploited to optimize the network through loss functions and obtain prediction for the target domain. Main results. The proposed network was evaluated on the benchmark RSVP dataset, and the cross-subject classification results showed that the proposed MDA-TSC network outperformed the reference methods. Moreover, the effectiveness of the MDA-TSC network was verified through both ablation studies and visualization. Significance. The proposed network could effectively improve cross-subject classification performance in RSVP task, and was helpful to reduce system calibration time.
An in vitro three-dimensional (3D) testicular organoid culture system for efficient gonocyte maintenance and propagation using frozen/thawed neonatal bovine testicular tissues
Authors: Tang Shiyan , Jones Celine , Mecca Rajwa , Davies Jill , Lane Sheila , Coward Kevin 
Published: February 2024

Abstract
Fertility preservation in prepubertal boys with cancer requires the cryopreservation of immature testicular tissues (ITTs) prior to gonadotoxic treatment. However, the limited number of germ cells in small human ITT biopsies necessitates the development of an in vitro culture system for germ cell expansion using frozen-thawed ITTs. Here, we generated testicular organoids for the in vitro maintenance and expansion of gonocytes from frozen-thawed two-week-old neonatal bovine ITTs. We investigated the effects of different cell-seeding densities, culture serums, seeding methods, and gonadotropin supplementations, on the maintenance and proliferation of enriched gonocytes. Our results demonstrated that enriched gonocytes and testicular cells from frozen-thawed neonatal ITTs could self-assemble into spheroid organoids in three days in an appropriate Matrigel-based culture environment. For the optimal formation of prepubertal testicular organoids, a seeding density of 1 × 106 cells/well is recommended over other densities. This strategy results in organoids with a mean diameter of 60.53 ± 12.12 μm; the mean number of organoids was 5.57 ± 1.60/105 μm2 on day 11. The viability of organoids was maintained at 79.75 ± 2.99% after being frozen and thawed. Supplementing the culture medium with glial cell-derived neurotrophic factor, fibroblast growth factor 2, and leukemia inhibitory factor, increased the proportion of KI67-positive proliferating cells in organoids, elevated the expression of C-KIT but reduced the expression of GFRα1 at day 28 when compared to those without hormone supplements (p< 0.05). In addition, supplementing the culture medium with follicle-stimulating hormone and testosterone helped to maintain a significantly higher viability (p< 0.05) in ITT organoids at day 28. These organoids could be cryopreserved for storage and thawed as needed. The successful generation of ITT organoids provides a valuable tool for establishing in vitro spermatogenesis, propagating human germ cells, investigating testicular physiology and the origin of germ cell tumors, and testing the toxicity of new drugs in future clinical applications.
Bioactive gelatin-sheets as novel biopapers to support prevascularization organized by laser-assisted bioprinting for bone tissue engineering
Authors: Kérourédan Olivia , Washio Ayako , Handschin Charles , Devillard Raphaël , Kokabu Shoichiro , Kitamura Chiaki , Tabata Yasuhiko 
Published: February 2024

Abstract
Despite significant advances in the management of patients with oral cancer, maxillofacial reconstruction after ablative surgery remains a clinical challenge. In bone tissue engineering, biofabrication strategies have been proposed as promising alternatives to solve issues associated with current therapies and to produce bone substitutes that mimic both the structure and function of native bone. Among them, laser-assisted bioprinting (LAB) has emerged as a relevant biofabrication method to print living cells and biomaterials with micrometric resolution onto a receiving substrate, also called ‘biopaper’. Recent studies have demonstrated the benefits of prevascularization using LAB to promote vascularization and bone regeneration, but mechanical and biological optimization of the biopaper are needed. The aim of this study was to apply gelatin-sheet fabrication process to the development of a novel biopaper able to support prevascularization organized by LAB for bone tissue engineering applications. Gelatin-based sheets incorporating bioactive glasses (BGs) were produced using various freezing methods and crosslinking (CL) parameters. The different formulations were characterized in terms of microstructural, physical, mechanical, and biological properties in monoculture and coculture. Based on multi-criteria analysis, a rank scoring method was used to identify the most relevant formulations. The selected biopaper underwent additional characterization regarding its ability to support mineralization and vasculogenesis, its bioactivity potential and in vivo degradability. The biopaper ‘Gel5wt% BG1wt%—slow freezing—CL160 °C 24 h′ was selected as the best candidate, due to its suitable properties including high porosity (91.69 ± 1.55%), swelling ratio (91.61 ± 0.60%), Young modulus (3.97 × 104 ± 0.97 × 104 Pa) but also its great cytocompatibility, osteogenesis and bioactivity properties. The preorganization of human umbilical vein endothelial cell using LAB onto this new biopaper led to the formation of microvascular networks. This biopaper was also shown to be compatible with 3D-molding and 3D-stacking strategies. This work allowed the development of a novel biopaper adapted to LAB with great potential for vascularized bone biofabrication.
Mechanical properties of concrete utilizing high volume palm oil fuel ash, fly ash and silica fume as blended binders
Authors: How C C , Salleh S , Hamid R 
Published: February 2024

Abstract
Palm oil fuel ash (POFA) has limited pozzolanic capability, only 10% can be used as cement replacement without decreasing concrete strength. Fly ash (FA) is known for low pozzolanic reactivity at early age. This study combines different ratios of hybrid POFA and FA to find an optimum combination that will produce optimum strength at early age. The fresh and mechanical properties were studied at ratios of POFA and FA at 60% replacing type II composite cement plus 2% silica fume (SF) addition. The experimental findings indicate that the highest and lowest slumps are POFA0FA60 and POFA30FA30, respectively. The compressive strength (7 days) of POFA30FA30 mix is the highest at 22 MPa and single replacement binders (POFA60FA0, POFA0FA60) are lowest at 12 MPa. However, at 28 days, mixes with higher ratios of FA shows higher increment of strength at 27 MPa, indicating that FA has started its pozzolanic activities and contributing to strength. The ratio of tensile and flexural strength POFA30FA30 to its corresponding compression strength is 25% and 61% lower than the control. For high early-age strength, POFA30FA30SF2 hybrid mix performs optimally, 7 days strength 80% of the 28 days and using a single material (60% POFA or FA), yields low early-age strength (50% at 7 days).
Effects of pyrolysis bio-oil derived from palm kernel shell on modified bitumen properties
Authors: Gungat Lillian , Manan Nur Afeera Syakirin Binti Abdul , Makinda Jodin , Ladin Mohd Azizul Bin 
Published: February 2024

Abstract
Economical and environmental friendly materials that able to replace petroleum based binder has become an urgent demand in road industry. Bio oil from palm oil waste is relatively more economical and has the potential to used as bitumen replacement as bio asphalt. The performance of bio asphalt derived from different source and process to produce bio oils are varies. Hence, this study aims to investigate the effects of palm kernel shell bio-oil in terms of physical properties, the chemical functional group, and the morphology. The bitumen properties were evaluated by the conventional physical tests, Fourier Transform Infrared Spectroscopy, and Scanning Electron Microscopy. The palm kernel shell bio-oil was added into the bitumen by weight of bitumen at 0%, 2%, 3%, 5%, 10%, 15%, and 20% and blended using mechanical stirrer. From the conventional physical test, it was found that bio-oil modified bitumen increased in penetration and ductility with decreased softening point. This indicate that direct addition of bio oil soften the modified bitumen. The change of the functional group in FTIR is significantly influenced by the increasing content of bio-oil. The morphology of the modified bitumen showed inhomogenous surface with noticeable wrinkles as the bio oil content increase. Based on the physicochemical evaluation, 3% bio oil replacement passed all the physical tests requirement with less changes in FTIR result. Therefore, 3% bio oil content is proposed for further tests for direct inclusion of bio oil into bitumen for local road construction utilization.
Prediction of River Water Treatment Plant Operational Performances using Optimization Approach in Artificial Neural Network Model
Authors: Mohiyaden H. A. , Sidek L.M. , Hayder G. 
Published: February 2024

Abstract
Uncontrolled development at the upstream of the river catchment have led to detrimental effect to the environment, including degradation of river water quality. River Water Treatment Plant (RWTP) technology was introduced to reduce the contamination loading into the river water system, worldwide. The technology offers the best biological treatment process including simplicity and stable removal efficiency. However, the plant performance plan is difficult task to predict, thus might have influence the operational control. Recently, artificial neural network (ANN) models have been widely applied in environmental engineering area due to the ability to skip the complexity process to assume of the unknown variables compare to conventional physical based model. In this study, the results of 3-yrs performance using ANN of RWTP were developed. Feed-forward back-propagation using Levenberg–Marquardt (trainlm) used as for this predictive approach. The ideal configuration involves utilizing the tangent sigmoid transfer function (Tansig) in the hidden layer and a linear transfer function (Purelin) in the output layer, with 25 neurons. This configuration yields an R2 value of 0.963 and the most least mean square error (MSE) of 30.39. From the comparison between two model (bio-kinetic and ANN), performance indicator for ANN model shows the best and the most optimum model. Ultimately, RWTP optimization using black-box model ANN is more reliable and timesaving as compared to conventional bio-kinetic model. The development of the proposed model can be implemented and used for various water quality improvement facilities and predict the effluent target parameter in RWTP with higher degree of accuracy.
A nonlinear variant of Ball’s Inequality
Authors: Duncan Jennifer 
Published: February 2024

We adapt an induction-on-scales argument of Bennett, Bez, Buschenhenke, Cowling, and Flock [Duke Math J. 169 (2020), pp. 3291–3338] to establish a global near-monotonicity statement for the nonlinear Brascamp–Lieb functional under a certain heat-flow, from which follows a global stability result for nonlinear Brascamp–Lieb inequalities under bounded perturbations.
Deep reinforcement learning identifies personalized intermittent androgen deprivation therapy for prostate cancer
Authors: Lu Yitao , Chu Qian , Li Zhen , Wang Mengdi , Gatenby Robert , Zhang Qingpeng 
Published: February 2024

Abstract
The evolution of drug resistance leads to treatment failure and tumor progression. Intermittent androgen deprivation therapy (IADT) helps responsive cancer cells compete with resistant cancer cells in intratumoral competition. However, conventional IADT is population-based, ignoring the heterogeneity of patients and cancer. Additionally, existing IADT relies on pre-determined thresholds of prostate-specific antigen to pause and resume treatment, which is not optimized for individual patients. To address these challenges, we framed a data-driven method in two steps. First, we developed a time-varied, mixed-effect and generative Lotka–Volterra (tM-GLV) model to account for the heterogeneity of the evolution mechanism and the pharmacokinetics of two ADT drugs Cyproterone acetate and Leuprolide acetate for individual patients. Then, we proposed a reinforcement-learning-enabled individualized IADT framework, namely, I$^{2}$ADT, to learn the patient-specific tumor dynamics and derive the optimal drug administration policy. Experiments with clinical trial data demonstrated that the proposed I$^{2}$ADT can significantly prolong the time to progression of prostate cancer patients with reduced cumulative drug dosage. We further validated the efficacy of the proposed methods with a recent pilot clinical trial data. Moreover, the adaptability of I$^{2}$ADT makes it a promising tool for other cancers with the availability of clinical data, where treatment regimens might need to be individualized based on patient characteristics and disease dynamics. Our research elucidates the application of deep reinforcement learning to identify personalized adaptive cancer therapy.
505 - Once-daily roflumilast cream 0.15% for atopic dermatitis: pooled results from INTEGUMENT-1/2 phase 3 trials
Authors: Eichenfield Lawrence F , Boguniewicz Mark , Simpson Eric L , Blauvelt Andrew , Gooderham Melinda , Lain Edward , Chu David H , Higham Robert C 
Published: February 2024

Abstract

Introduction
Roflumilast cream 0.15% is a selective, highly potent phosphodiesterase 4 inhibitor under investigation as a non-steroidal, once-daily treatment for atopic dermatitis (AD).

Objectives
Here, pooled results from two identical Phase 3 randomized controlled trials (INTEGUMENT-1: NCT04773587 and INTEGUMENT-2: NCT04773600) are presented.

Methods
Patients with AD aged ≥6 years with baseline Eczema Area and Severity Index (EASI) score ≥5 and Validated Investigator Global Assessment-AD (vIGA-AD) score of Mild or Moderate were randomized 2:1 to apply roflumilast (n=884) or vehicle (n=453) once daily for 4 weeks.

Results
A significantly greater percentage of roflumilast- versus vehicle-treated patients achieved the primary endpoint, vIGA-AD Success (Clear or Almost Clear vIGA-AD plus ≥2-grade improvement from baseline) at Week 4 (31.3% vs. 14.1%; P&lt;0.0001). Significant differences favoring roflumilast were observed for multiple secondary endpoints at Week 4: percentage of patients achieving vIGA-AD of Clear or Almost Clear (41.1% vs. 21.4%; P&lt;0.0001), percentage achieving 75% reduction in EASI (42.7% vs. 20.6%; P&lt;0.0001), and percentage with baseline Worst Itch-Numeric Rating Scale ≥4 achieving a 4-point reduction (31.9% vs. 16.6%; P&lt;0.0001). Improvement in itch was reported as early as 24 hours. Both groups had low incidences of treatment-emergent adverse events (TEAE), serious adverse events, and TEAEs leading to discontinuation. Local tolerability was favorable, with &gt;90% of patients reporting no or mild sensation across both treatment groups at all timepoints.

Conclusions
Once-daily roflumilast cream 0.15% provided improvement across multiple efficacy endpoints by Week 4 with favorable safety and tolerability in patients aged ≥6 years with AD in two Phase 3 trials.