bluuebunny/crossref_metadata_2025_split huggingface dataset:
Periostin-targeted SDSSD peptide decorated calcium phosphate nanocomposites incorporation with simvastatin for osteoporosis treatment
Authors: Pan Zian , Zhang Zhen , Deng Xiongwei , Hu Fanqi , Jia Fan , Lu Jianqing , Zhang Xuesong , Yang Xiaoqing , Gao Yujuan , Wang Xuan , Cui Xinyue , Xu Chenlu , Wu Yan 
Published: November 2023

Abstract
The limited options of anabolic drugs restrict their application potential in osteoporosis treatment, despite their theoretical superiority in therapeutic efficacy over antiresorptive drugs. As a prevailing strategy, nano-delivery systems could offer a wider choice of anabolic drugs. In this study, calcium phosphate nanocomposites incorporated with simvastatin (Sim) with periostin-targeting ability were designed and prepared for osteoporosis treatment. Carboxymethyl dextran (CMD) as an anionic and hydrophilic dextran derivative was used to stabilize CaP. In addition, periosteum-targeted peptide (SDSSD) was further grafted on CMD to achieve the bone targeting function. In a one-step coordination assembly strategy, hydrophobic anabolic agent Sim and SDSSD-CMD graft (SDSSD-CMD) were incorporated into the CaP nanoparticles forming SDSSD@CaP/Sim nanocomposites. The resulting SDSSD@CaP/Sim possesses uniform size, great short-term stability and excellent biocompatibility. Moreover, SDSSD@CaP/Sim exhibited a reduced release rate of Sim and showed slow-release behaviour. As anticipated, the nanocomposites exhibited bone bonding capacity in both cellular and animal studies. Besides, SDSSD@CaP/Sim achieved obviously enhanced osteoporosis treatment effect compared to direct injection of Sim in vivo. Therefore, our findings highlight the potential of SDSSD-incorporated and CaP-based nanocomposites as a viable strategy to enhance the therapeutic efficacy of anabolic drugs for osteoporosis treatment.
Mitigating misalignment in MRI-to-CT synthesis for improved synthetic CT generation: an iterative refinement and knowledge distillation approach
Authors: Zhou Leyuan , Ni Xinye , Kong Yan , Zeng Haibin , Xu Muchen , Zhou Juying , Wang Qingxin , Liu Cong 
Published: November 2023

AbstractObjective.Deep learning has shown promise in generating synthetic CT (sCT) from magnetic resonance imaging (MRI). However, the misalignment between MRIs and CTs has not been adequately addressed, leading to reduced prediction accuracy and potential harm to patients due to the generative adversarial network (GAN)hallucination phenomenon. This work proposes a novel approach to mitigate misalignment and improve sCT generation.Approach.Our approach has two stages: iterative refinement and knowledge distillation. First, we iteratively refine registration and synthesis by leveraging their complementary nature. In each iteration, we register CT to the sCT from the previous iteration, generating a more aligned deformed CT (dCT). We train a new model on the refined 〈dCT, MRI〉 pairs to enhance synthesis. Second, we distill knowledge by creating a target CT (tCT) that combines sCT and dCT images from the previous iterations. This further improves alignment beyond the individual sCT and dCT images. We train a new model with the 〈tCT, MRI〉 pairs to transfer insights from multiple models into this final knowledgeable model.Main results.Our method outperformed conditional GANs on 48 head and neck cancer patients. It reduced hallucinations and improved accuracy in geometry (3% ↑ Dice), intensity (16.7% ↓ MAE), and dosimetry (1% ↑γ3%3mm). It also achieved <1% relative dose difference for specific dose volume histogram points.Significance.This pioneering approach for addressing misalignment shows promising performance in MRI-to-CT synthesis for MRI-only planning. It could be applied to other modalities like cone beam computed tomography and tasks such as organ contouring.
PCA and logistic regression in 2-[18F]FDG PET neuroimaging as an interpretable and diagnostic tool for Alzheimer’s disease
Authors: Gonçalves de Oliveira Carlos Eduardo , de Araújo Whemberton Martins , de Jesus Teixeira Ana Beatriz Marinho , Gonçalves Gustavo Lopes , Itikawa Emerson Nobuyuki ,   For the Alzheimer’s Disease Neuroimaging Initiative
Published: November 2023

Abstract

Objective. to develop an optimization and training pipeline for a classification model based on principal component analysis and logistic regression using neuroimages from PET with 2-[18F]fluoro-2-deoxy-D-glucose (FDG PET) for the diagnosis of Alzheimer’s disease (AD). Approach. as training data, 200 FDG PET neuroimages were used, 100 from the group of patients with AD and 100 from the group of cognitively normal subjects (CN), downloaded from the repository of the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Regularization methods L1 and L2 were tested and their respective strength varied by the hyperparameter C. Once the best combination of hyperparameters was determined, it was used to train the final classification model, which was then applied to test data, consisting of 192 FDG PET neuroimages, 100 from subjects with no evidence of AD (nAD) and 92 from the AD group, obtained at the Centro de Diagnóstico por Imagem (CDI). Main results. the best combination of hyperparameters was L1 regularization and C ≈ 0.316. The final results on test data were accuracy = 88.54%, recall = 90.22%, precision = 86.46% and AUC = 94.75%, indicating that there was a good generalization to neuroimages outside the training set. Adjusting each principal component by its respective weight, an interpretable image was obtained that represents the regions of greater or lesser probability for AD given high voxel intensities. The resulting image matches what is expected by the pathophysiology of AD. Significance. our classification model was trained on publicly available and robust data and tested, with good results, on clinical routine data. Our study shows that it serves as a powerful and interpretable tool capable of assisting in the diagnosis of AD in the possession of FDG PET neuroimages. The relationship between classification model output scores and AD progression can and should be explored in future studies.
Integration of vertically-aligned carbon nanotubes with superconducting nanowire single photon detectors
Authors: Rampini D S , Yung C S , Oripov B G , Woods S , Lehman J , Nam S W , McCaughan A N 
Published: November 2023

Abstract
We report on initial fabrication efforts in the integration of superconducting nanowire single-photon detectors (SNSPDs) with vertically aligned carbon nanotubes (VACNTs) with the goal of creating a wideband single-photon detector. SNSPDs provide high detection efficiencies and low dark count rates, while the VACNTs are excellent broadband optical absorbers. Combining these technologies could potentially enable the development of highly sensitive and versatile optical sensors for a variety of applications, such as spectroscopy, optical communication, and imaging in light starved environments. We developed two fabrication processes for the integration of VACNTs on SNSPDs. The first involves capping the SNSPDs with a protective layer and growing the VACNTs directly above nanowires. Thermal and electrical characterizations of the devices demonstrated a degradation of the superconducting qualities of the SNSPDs. The second process involved suspending the SNSPDs on a thin membrane via a backside etch, where VACNTs were then grown on the backside of the membranes below the nanowires. The membrane style devices showed no degradation in the superconducting properties of the nanowires. Measurements of the membrane style devices before and after the VACNT growth display similar superconducting properties and photon count rates.
Highly responsive self-driven broadband hybrid photodetector with high detectivity and on/off ratio based on Hibiscus sabdariffa
Authors: Yuca Hafize , Karakaya Songül , Yıldırım Fatma , İncekara Ümit , Aydoğan Şakir 
Published: November 2023

Abstract
A Hibiscus sabdariffa (HBS)/n-Si hybrid photodetector was fabricated and it was observed that the device has a high rectification ratio of 10.2 × 104 in dark and superior photoresponse at different intensities of visible light in addition to UV and IR lights. The non-linear response to light intensity in visible light was attributed to phase change effects and the presence of traps, which are the result of the hibiscus sabdariffa’ response to light. The responsivity at 850 nm reaches 1.16 A W−1 (at V = −2.0 V) and a high specific detectivity of 2.0 × 1012 Jones (for self-driven mode) with an external quantum efficiency of 411% was obtained. In addition, in self-driven mode of UV and IR lights, the highest on/off ratio and NPDR values reached ∼105 and ∼109 W−1 levels, respectively. Moreover, HBS/n-Si hybrid broad-band photodetector showed long-term stability (40 days) without encapsulation both in the dark and under the light.
A novel time domain analysis of the modes perturbed by a lossy material in a cavity
Authors: Erden Fatih 
Published: November 2023

Abstract
This study delves into the intricate dynamics of time-domain electromagnetic phenomena within an irregular rectangular cavity perturbed by a lossy conducting body. Focusing on coupled degenerate (singular) TM and TE solenoidal modes, the analysis reveals eigenfrequency splitting due to irregularities like a lossy body. By employing an upgraded version of the Evolutionary Approach to Electromagnetics with novel Maxwell’s equations in SI units, our explicit solution adheres to the causality principle. This united dynamic system exhibits both forced and free oscillations, initiated by a finite duration signal. The study highlights the dual nature of oscillations: forced oscillations excited by the signal and subsequent free oscillations. In irregular cavities, the eigenvalues undergo splitting, signifying a dissipative dynamic system. Our work significantly advances the understanding of these complex electromagnetic systems, demonstrating practical relevance in electromagnetics and offering a novel perspective on irregular cavity dynamics.
Point-symmetry in SNR G1.9+0.3: A Supernova that Destroyed its Planetary Nebula Progenitor
Authors: Soker Noam 
Published: November 2023

Abstract
I analyze a new X-ray image of the youngest supernova remnant (SNR) in the Galaxy, which is the type Ia SNR G1.9+0.3, and reveal a very clear point-symmetrical structure. Since explosion models of type Ia supernovae (SNe Ia) do not form such morphologies, the point-symmetrical morphology must come from the circumstellar material (CSM) into which the ejecta expands. The large-scale point-symmetry that I identify and the known substantial deceleration of the ejecta of SNR G1.9+0.3 suggest a relatively massive CSM of ≳1M
⊙. I argue that the most likely explanation is the explosion of this SN Ia into a planetary nebula. The scenario that predicts a large fraction of SN Ia inside PNe (SNIPs) is the core degenerate scenario. Other SN Ia scenarios might lead to only a very small fraction of SNIPs or none at all.
Data science in wind energy: a case study for Norwegian offshore wind
Authors: Chen Hao , Birkelund Yngve , Zhang Qixia 
Published: November 2023

Abstract
In the digital and green transitions, rapidly growing renewable energies are accumulating more and more data. Big data gives room to apply emerging data science to solve challenges in the energy sector. Offshore wind power receives accelerating attention due to its sufficient resources and cleanness. This paper uses data science, including statistical analysis and machine learning, to systematically analyse three coastal wind sites in Norway. The results show that although Norway possesses ample offshore resources, its development could be improved by natural, technical, and economic challenges that can be addressed with the help of data science. Technically, the statistical attributes and forecasting intricacy of offshore wind resources differ across various regions of Norway.
Application of EMD combined with wavelet algorithm for filtering slag noise in steel cord conveyor belt
Authors: Sun Guoxin , Zhang Runze , Liu Zejiang , Wu Linfeng , Yu Qihui , Tan Xin 
Published: November 2023

Abstract
This study proposes a noise reduction technique that combines empirical mode decomposition (EMD) with wavelet thresholding to remove noise interference generated by metal slag in the damage signal of steel cord conveyor belts. The initial step involves decomposing the original signal into high-frequency and low-frequency intrinsic mode function (IMF) components using empirical mode decomposition (EMD), guided by the metal slag signal characteristics analysis. The high-frequency noise is filtered away while the low-frequency IMF components are kept intact through the wavelet threshold de-noising technique. The slag noise-containing IMF components are deleted, and the filtered signal and the low-frequency IMF components are utilized for signal reconstruction to provide the optimum noise reduction result. The study demonstrates that this method is more effective in suppressing metal slag noise, environmental noise, and other noise interferences than traditional EMD decomposition noise reduction and wavelet threshold noise reduction methods. This research provides a valuable reference for noise reduction in steel cord conveyor belt detection data.
RF-wave induced CBRAM characteristic modulation specific to sheet-like conductive filaments
Authors: Yin Yifei , Tsukamoto Keito , Hayashi Hitoshi , Nakaoka Toshihiro 
Published: November 2023

Abstract
The shape of conductive filaments in CBRAM is important for resistance switching and conductance modulation, especially in applications like neuromorphic and reservoir computing that use conductance as weight. We report on RF-induced modulation of CBRAM using Ge2Sb3.4Te6.2 with sheet-like filaments and compared it to those with dendritic filaments. RF input below 100 MHz reduced SET and RESET voltages, similar to CBRAM with dendritic filaments, but showed significantly different resistance changes. Repeated RF on/off input gradually increased the resistance of low-resistance state, unlike the dendritic filament CBRAM, where the resistance decreased. The increased resistance suggests RF-induced denser sheet-like filaments. Furthermore, the resistance of the high-resistance state showed a peculiar RF-induced resistance change not observed in dendritic filaments. The resistance decreased during RF input and increased to nine times the initial value when RF was switched off. The results show that the conductance modulation by RF input strongly depends on the filament type.
Solar thermoelectric generator and thermoelectric cooler performance: analysis and comparison using a different shape geometry
Authors: Khalil ALkhadher , Sahnoun Smail , Elhassnaoui Ahmed , Yadir Said , Obbadi Abdellatif , Errami Youssef 
Published: November 2023

Abstract
Thermoelectric devices are one of the technologies used either to generate electricity by applying a temperature difference using thermal energy or as a heating/cooling system by applying an electrical voltage. The number of materials required to produce a product is an important factor in determining its price. Production costs associated with these materials, as well as their availability and quality, play a crucial role in price determination by manufacturers. In this context, a method that employs a uniform volume distribution was implemented. This approach enabled the analysis to focus on other variables, thereby promoting a more precise and relevant evaluation of overall performance. Based on the finite element method, this study investigated the influence of geometric shape, including Rect-leg, Y-leg, Pin-leg and X-leg designs, on the performance of solar thermoelectric generators and thermoelectric coolers. The study was conducted considering the same hot alumina junction surface that receives solar radiation; however, the effective surface, which corresponded to the heat flow area and had a similar area near the exposed surface, varied depending on the chosen leg geometry, thus impacting the heat flux due to the variation in thermal resistance. In the case of a solar thermoelectric generator, the Rect-leg model, having the same effective surface area, presented the lowest heat loss value resulting from convection and radiation in the heat spreader and the hot alumina plate. Under the same conditions, the Y-leg showed the highest value. The Rect-leg design generated, by using thermal and optical concentration, the highest output power of 0.028 and 0.054 W, and efficiency of 3.47% and 4.7%, respectively, whereas the Y-leg generated lower values of 0.006523 and 0.018744 W for power, and 2.83% and 2.71% for efficiency, respectively. In the case of the thermoelectric coolers, the Y-leg generated the highest temperature difference between the hot and cold sides of 67.28 K at an electric current value of 1.8 A, whereas the Rect-leg, Pin-leg and X-leg generated ~66.25, ~67.02 and ~67.19 K at 6.1, 2.7 and 2.6 A.
A Simple and Rapid High-Performance Liquid Chromatography Method for Preparation and Content Detection of the Mainly Numbing Taste Substances of Zanthoxylum bungeanum Maxim
Authors: Wang Zixu , Liu Yue , Sun Guoqing , Yang Liu , Huang Shuai , Chen Lin , Zhou Xianli 
Published: November 2023

Abstract
As the characteristic numbing taste substances, hydroxyl-α-sanshool (HAS) and hydroxyl-β-sanshool (HBS) were considered vital indicators to evaluate the quality of Zanthoxylum bungeanum Maxim. However, it is very difficult to obtain their high-purity monomers individually, as the only difference between HAS and HBS is that C-6 cis-trans isomerism. In our study, a simple and rapid Ag +-HPLC method was developed to pure the standard chemicals of Z. bungeanum with numbing taste, and 1H NMR and 13C NMR were employed to determine the purity and structure. Moreover, an HPLC method was established to determine the content of numbing taste components of 16 varieties of Z. bungeanum from different regions. The analytical methods were validated for accuracy, precision, and linearity, respectively. The validated method was accurate (spiked recoveries 0.94–1.10), precise in terms of peak area (intra-day RSDs &lt;1.25% and inter-day RSDs &lt;1.61%), and linear (r2 ≥ 0.999). It was found that there were significant differences in the content of HAS and HBS among different types of Z. bungeanum, with HAS content ranging from 60.06 ± 1.14 to 164.13 ± 3.28 mg/g and HBS ranging from 7.81 ± 0.36 to 21.11 ± 0.75 mg/g. The RSDs of HAS range were 1.73–3.80% and that of HBS range 2.03–4.73% (RSDs ≤5%), which indicated that the measurements of HAS and HBS were reliable.
Pre-exposure Prophylaxis Use History in People With Antiretroviral Resistance at HIV Diagnosis: Findings From New York City HIV Surveillance and Partner Services, 2015–2022
Authors: Misra Kavita , Huang Jamie S , Udeagu Chi-Chi N , Forgione Lisa , Xia Qiang , Torian Lucia V 
Published: November 2023

Abstract

Background
Drug resistance may be acquired in people starting human immunodeficiency virus (HIV) preexposure prophylaxis (PrEP) during undiagnosed infection. Population-based estimates of PrEP-related resistance are lacking.

Methods
We used New York City surveillance and partner services data to measure the effect of PrEP use (tenofovir disoproxil fumarate/tenofivir alafenamide fumarate with emtricitabine) history on the baseline prevalence of M184I/V mutations in people with HIV diagnosed in 2015–2022. PrEP use was categorized as “recent” (defined as PrEP stopped ≤90 days before diagnosis), “past” (PrEP stopped &gt;90 days before diagnosis), or “no known use.” Resistance-associated mutations were determined using the Stanford algorithm. We used log binomial regression to generate the adjusted relative risk (aRR) of M184I/V by PrEP use history in people with or without acute HIV infection (AHI).

Results
Of 4246 people with newly diagnosed HIV and a genotype obtained within ≤30 days of diagnosis, 560 (13%) had AHI; 136 (3%) reported recent and 124 (35%) past PrEP use; and 98 (2%) harbored M184I/V. In people with AHI, recent PrEP use was associated with a 6 times greater risk of M184I/V than no known use (aRR, 5.86 [95% confidence interval, 2.49–13.77]). Among people without AHI, the risk of M184I/V in recent users was 7 times that in people with no known use (aRR, 7.26 [95% confidence interval, 3.98–13.24]), and in past users, it was 4 times that in those with no known use (4.46 [2.15–9.24]).

Conclusions
PrEP use was strongly associated with baseline M184I/V in New York City, regardless of AHI status. Ordering a nucleic acid test when indicated after assessment of exposure, antiretroviral history, and AHI symptoms can decrease PrEP initiation in people with undetected infection.
Left ventricular mechanical dispersion as a predictor of the need for pacemaker implantation after transcatheter aortic valve implantation: MeDiPace TAVI study
Authors: Kaya Esra , Andresen Kristoffer , Lie Øyvind H , Aaberge Lars , Haugaa Kristina H , Edvardsen Thor , Skulstad Helge 
Published: November 2023

Abstract

Aims
Permanent pacemaker (PM) implantation is common after transcatheter aortic valve implantation (TAVI). Left ventricular mechanical dispersion (MeDi) by speckle tracking echocardiography is a marker of fibrosis that causes alterations in the conduction system. We hypothesized that MeDi can be a predictor of the need for PM implantation after TAVI.

Methods and results
Consecutively, 200 TAVI patients were enrolled. Transthoracic echocardiography and electrocardiography examinations were recorded before TAVI to evaluate global longitudinal strain (GLS), MeDi, and conduction disturbances. PM implantation information was obtained 3 months after TAVI. Patients were stratified into PM or no PM group. Mean age was 80 + 7 years (44% women). Twenty-nine patients (16%) received PM. MeDi, QRS duration, existence of right bundle branch abnormality (RBBB), and first-degree atrioventricular (AV) block were significantly different between groups. MeDi was 57 ± 15 ms and 48 ± 12 ms in PM and no PM groups, respectively (P &lt; 0.001). In multivariate analysis, MeDi predicted the need for PM after TAVI independently of GLS, QRS duration, RBBB, and first-degree AV block [odds ratio (OR): 1.73, 95% confidence interval (CI): 1.22–2.45] with an area under the curve (AUC) of 0.68 in receiver operating characteristic (ROC) curves. Moreover, RBBB was an independent predictor of PM need after TAVI (OR: 8.98, 95% CI: 1.78–45.03). When added to RBBB, MeDi had an incremental predictive value with an AUC of 0.73 in ROC curves (P = 0.01).

Conclusion
MeDi may be used as an echocardiographic functional predictor of the need for PM after TAVI.
Chartist Studies and Malcolm Chase: A Re-appreciation
Authors: Navickas Katrina 
Published: November 2023

Abstract
Malcolm Chase (1957–2020) was the pre-eminent scholar of the Chartist democratic movement, and more broadly, of working-class political and social action in early nineteenth-century Britain. His work in many respects shaped a shift in the study of Chartism within labour and cultural history. Rejecting the inward-looking diversion into the ‘linguistic turn’ of the early 1990s, Chase offered a broader and holistic view of not only what class, political radicalism and the land meant to working-class people, but also how it was a lived experience expressed in action as well as words. This article is a re-appreciation of Chase’s major contribution to the field. It charts the origins and development of Chartist studies, and surveys recent publications, including the wide range of articles published on Chartism in the English Historical Review.