bluuebunny/crossref_metadata_2025_split huggingface dataset:
A windowed fourier transform-based method of numerically analyzing phase shifts of SPR sensors
Authors: Peng Shikang , Wang Guofu , Liu Yansheng , Jia Xiaobo , Zhou Jin 
Published: March 2024

Abstract
This study presents a simple and reliable method for numerical evaluation of the sensitivity of SPR systems. A Windowed Fourier Transform (WFT) based method is applied to extract shifts of SPR interferogram. By applying the WFT, the frequencies consisting of SPR interferogram are extracted, and phase shifts of relevant frequencies are also obtained. The normalized amplitude of the frequencies larger than 0.35 is regarded as the most prominent frequency. The summation of the phase shifts of the most prominent frequencies is regarded as an index to numerically analyzing phase shifts of SPR sensors. Through this method, the small change in the sensing surface can be monitored. By using a homemade SPR system with the proposed calculation method, it can detect the NaCl solutions ranging from 0.00003% to 0.03% (wt%), indicating its great promise for applications in fields such as medicine, food safety, and biotechnology.
Error state prediction method for electronic voltage transformer based on empirical mode decomposition and auto-regressive moving average
Authors: Li Binbin , Liu Chen , Huang Jie 
Published: March 2024

Abstract
Electronic voltage transformers have been used in the power system in conjunction with the development of power grid intelligence due to their good insulation structure, economy, volume, and other advantages. However, in its long-term operation, the phenomena of error overshooting and unstable operation will inevitably occur, and the existing periodic off-line testing methods require a high calibration cycle, which is difficult to achieve. To solve these problems, an error state prediction method based on empirical mode decomposition and autoregressive moving average model is proposed. Firstly, according to the physical correlation between the secondary output signal and the error, the output signal is quantified as a statistic Q by the method of principal component analysis, and then the statistic is used as the prediction object to establish a prediction model for predicting the operating state of the electronic voltage transformer. The simulation results show that the model can accurately predict the trend of the transformer error, which meets the prediction requirements.
Experimental study of the effect of different 3D printing parameters on tensile strength, using artificial neural network
Authors: Hamouti Lahcen , El Farissi Omar , Laouardi Maryam 
Published: March 2024

Abstract
Numerous research studies have been conducted to optimize printing parameters using the fused deposition modeling technique (FDM) to improve mechanical properties. The large number of process parameters creates a need to search for optimal combinations of parameters to improve mechanical properties. This study examines the effects of three parameters when printing 3D with melted filament of a PLA material (Polylactic Acid) on the ultimate tensile strength of the printed parts. This search combines an experimental study of the most influential printing parameters on the tensile strength property, namely layer thickness, printing temperature, and feed rate. The experimental results are then analyzed and modeled as a linear regression model. Then develop an intelligent artificial model based on ANN (Artificial Neural Network) derived from these experimental results capable of predicting the optimal combination of parameters providing maximum tensile strength. The observed results showed that the feed rate dominates among the other variables, followed by the thickness of the layer. Also, at the level of prediction, the artificial model provides a better prediction of the tensile strength with a value of 36.1625 MPa by combining the following parameters: Feed rate: 70 mm s−1, temperature: 200 °C, and layer thickness: 0.26 mm, compared to the prediction obtained by the linear regression model. Neural networks enable more accurate optimization of 3D process parameters, leading to an overall improvement in the quality of finished products. predictive models, significantly reducing the iteration time required to obtain optimal parameters. The quality of the data used to train neural networks is crucial.
Design and characterization of cell topology effect on SiC VDMOSFETs for high power and frequency applications
Authors: Hung Chia Lung , Hsiao Yi-Kai , Kuo Hao-Chung 
Published: March 2024

Abstract
In this paper, we present a comprehensive investigation of the impact of cell topology and pitch reduction on the DC and AC characteristics of 1200V-rated 4H-SiC planar VDMOSFETs. We have designed and fabricated four different cell topologies, namely linear, square, hexagonal, and staggered cell, in order to characterize their performance. Among the various cell types, the hexagonal cell exhibits the most favorable specific on-state resistance (Ron,sp) value. However, it is worth noting that the breakdown values of both the hexagonal and staggered square cells fall significantly below the simulated values. This is attributed to the interaction between the irregular cell boundaries and the edge cell termination region. Furthermore, we observed that the linear cell has the highest gate resistance compared to the other cell types. Additionally, the linear cell also demonstrates a lower input capacitance than the other cells. This can be attributed to its longer gate trasmission line and smaller area. Lastly, we performed dynamic double pulse tests on the fabricated VDMOSFETs to compare their switching characteristics. It was concluded that linear cell VDMOS is suitable for high switching applications, while square, hexagonal and S.S cell VDMOS are better suited for lower switching applications that require a high output current.
The photodiode performances of NDI-appended ruthenium complexes
Authors: Seven Sibel , Yigit Evin , Bayindir Sinan , Akman Feride , Sevgili Ömer , Dayan Osman , Orak İkram 
Published: March 2024

Abstract
The synthesis and investigation of photoelectric studies of simple organic compounds as organic interlayers are of significant importance and widely studied. As such, we synthesized naphthalene diimide (NDI)-appended ruthenium complexes (Ru-NDIs) to function as the interface layer, and have fabricated novel Al/NDIs or Ru-NDIs/p-Si devices (D1-D4) to investigate their photoelectric properties. Subsequently, we compared and discussed the photoelectric properties of these devices after synthesis and fabrication. According to this, the band-gap energy (E

g
) values of organic materials were found to range from 2.95 eV to 3.14 eV, making them ideal for solar cells applications. Additionally, the photoresponse (Pr) values of Al/NDIs or Ru-NDIs/p-Si devices (D1-D4) were found to be 59.25, 1593.08, 198.77, and 134.47, respectively. Moreover, the Al/Ru-NDIs/p-Si D2 structure exhibited the highest Pr values. Experimental results indicate that since the four optoelectronic devices arranged with the derivation of synthesized compounds have good photoresponse characteristics, they can be utilized as a photosensor or photodiodes in different electronic and optoelectronic technologies.
Atomic-scale oxygen-vacancy engineering in Sub-2 nm thin Al2O3/MgO memristors
Authors: Dodson Berg , Goul Ryan , Marshall Angelo , Aafiya  , Bray Kevin , Ewing Dan , Walsh Michael , Wu Judy Z 
Published: March 2024

Abstract
Ultrathin (sub-2 nm) Al2O3/MgO memristors were recently developed using an in vacuo atomic layer deposition (ALD) process that minimizes unintended defects and prevents undesirable leakage current. These memristors provide a unique platform that allows oxygen vacancies (VO) to be inserted into the memristor with atomic precision and study how this affects the formation and rupture of conductive filaments (CFs) during memristive switching. Herein, we present a systematic study on three sets of ultrathin Al2O3/MgO memristors with VO-doping via modular MgO atomic layer insertion into an otherwise pristine insulating Al2O3 atomic layer stack (ALS) using an in vacuo ALD. At a fixed memristor thickness of 17 Al2O3/MgO atomic layers (∼1.9 nm), the properties of the memristors were found to be affected by the number and stacking pattern of the MgO atomic layers in the Al2O3/MgO ALS. Importantly, the trend of reduced low-state resistance and the increasing appearance of multi-step switches with an increasing number of MgO atomic layers suggests a direct correlation between the dimension and dynamic evolution of the conducting filaments and the VO concentration and distribution. Understanding such a correlation is critical to an atomic-scale control of the switching behavior of ultrathin memristors.
Computational design of single-atom catalysts embedded on reduced graphitic carbon nitride monolayers
Authors: Jakhar Mukesh , Ding Yi , Fahlman Bradley D , Barone Veronica 
Published: March 2024

Abstract
The design of efficient single-atom catalysts (SACs) with optimal activity and selectivity for sustainable energy and environmental applications remains a challenge. In this work, comprehensive first-principles calculations are performed to validate the feasibility of single TM atoms (3d, 4d, and 5d series) embedded in two different conformations of graphitic carbon nitride (g-C3N4) monolayers. Additionally, we investigate the effect of nitrogen vacancies in the g-C3N4 monolayers on the absorption of SACs considering three potential absorption scenarios that correspond to different experimental conditions. Our results point to the most stable configurations with the lowest formation energies and indicate that the absorption of single TM atoms on-vacancy and on-center sites are more favorable than via-substitution. In addition to the thermodynamic stability, electrochemical stability is also investigated through the calculation of the dissolution potential of the SACs. Within the scenarios considered in this study, we find that Pt, Pd, Rh, Au, Ru, Ir, Cu, Co, Fe, and Ni will produce the most robust SACs on both (edge and bridge) N vacancy site of reduced g-C3N4. Our findings provide guidance for the design and development of g-C3N4 sheets decorated with single TM atoms for technological applications such as pollutant degradation, CO2 reduction, N2 fixation, selective oxidation, water splitting, and metal ion-based batteries.
Convergence of Langevin-simulated annealing algorithms with multiplicative noise
Authors: Bras Pierre , Pagès Gilles 
Published: March 2024

We study the convergence of Langevin-Simulated Annealing type algorithms with multiplicative noise, i.e. for

V
:

R

d

→

R

V : \mathbb {R}^d \to \mathbb {R}

a potential function to minimize, we consider the stochastic differential equation

d

Y
t

=
−
σ

σ
⊤

∇
V
(

Y
t

)

dY_t = - \sigma \sigma ^\top \nabla V(Y_t)

d
t
+
a
(
t
)
σ
(

Y
t

)
d

W
t

+
a
(
t

)
2

Υ
(

Y
t

)
d
t

dt + a(t)\sigma (Y_t)dW_t + a(t)^2\Upsilon (Y_t)dt

, where

(

W
t

)

(W_t)

is a Brownian motion, where

σ
:

R

d

→

M

d

(

R

)

\sigma : \mathbb {R}^d \to \mathcal {M}_d(\mathbb {R})

is an adaptive (multiplicative) noise, where

a
:

R

+

→

R

+

a : \mathbb {R}^+ \to \mathbb {R}^+

is a function decreasing to

0
0

and where

Υ
\Upsilon

is a correction term. This setting can be applied to optimization problems arising in Machine Learning; allowing

σ
\sigma

to depend on the position brings faster convergence in comparison with the classical Langevin equation

d

Y
t

=
−
∇
V
(

Y
t

)
d
t
+
σ
d

W
t

dY_t = -\nabla V(Y_t)dt + \sigma dW_t

. The case where

σ
\sigma

is a constant matrix has been extensively studied; however little attention has been paid to the general case. We prove the convergence for the

L
1

L^1

-Wasserstein distance of

Y
t

Y_t

and of the associated Euler scheme

Y
¯

t

\bar {Y}_t

to some measure

ν
⋆

\nu ^\star

which is supported by

argmin
⁡
(
V
)

\operatorname {argmin}(V)

and give rates of convergence to the instantaneous Gibbs measure

ν

a
(
t
)

\nu _{a(t)}

of density

∝
exp
⁡
(
−
2
V
(
x
)

/

a
(
t

)
2

)

\propto \exp (-2V(x)/a(t)^2)

. To do so, we first consider the case where

a
a

is a piecewise constant function. We find again the classical schedule

a
(
t
)
=
A

log

−
1

/

2

⁡
(
t
)

a(t) = A\log ^{-1/2}(t)

. We then prove the convergence for the general case by giving bounds for the Wasserstein distance to the stepwise constant case using ergodicity properties.
Conclusion
Authors: Herold-Zanker Katharina 
Published: March 2024

Abstract
The conclusion re-evaluates the paradox of Orientalism in decadent texts, being simultaneously a means of imperial oppression and cosmopolitan affiliation. It offers a fresh example of this paradoxical relationship by examining an article by Edmund Gosse which he contributed to The Gypsy (1915–1916), a conservative modernist art magazine published by Arthur Symons, Henry Savage, and Alan Odle. In his article Gosse reviews cartoons on English foreign policies in Turkey and Egypt during the First World War which were published in the Munich-based newspaper Simplicissimus. The conclusion argues that, to a decadent sensibility, the importance of national belonging is relativized by cultural affiliation, which has been demonstrated in the book by linking English and German literary examples of decadent Orientalism.
Re-Embodying Biblical Prophecy
Authors: Portier-Young Anathea E 
Published: March 2024

Abstract
Chapter 2 delineates the scope, methodology, and guiding assumptions for the remainder of the study. It offers a working definition of biblical prophecy and argues for the multiplicity of its forms, content, and directionality. A survey of biblical Hebrew terms commonly grouped under the broader label “prophet” and the diverse roles associated with them helps to clarify and illustrate the wide range of mediatory roles biblical prophecy entails. This breadth and diversity of prophetic mediation requires analysis of similarly diverse aspects of embodiment. Developments in anthropology and the study of embodied cognition contribute to the approach taken in subsequent chapters. The chapter concludes with a methodological caveat regarding the complex relationship between the study of religious experience and practice and the study of texts.
Genome-Wide Genetic Analysis of Dropout in a Controlled Exercise Intervention in Sedentary Adults With Overweight or Obesity and Cardiometabolic Disease
Authors: Jiang Rong , Collins Katherine A , Huffman Kim M , Hauser Elizabeth R , Hubal Monica J , Johnson Johanna L , Williams Redford B , Siegler Ilene C , Kraus William E 
Published: March 2024

AbstractBackgroundDespite the benefits of exercise, many individuals are unable or unwilling to adopt an exercise intervention.PurposeThe purpose of this analysis was to identify putative genetic variants associated with dropout from exercise training interventions among individuals in the STRRIDE trials.MethodsWe used a genome-wide association study approach to identify genetic variants in 603 participants initiating a supervised exercise intervention. Exercise intervention dropout occurred when a subject withdrew from further participation in the study or was otherwise lost to follow-up.ResultsExercise intervention dropout was associated with a cluster of single-nucleotide polymorphisms with the top candidate being rs722069 (T/C, risk allele = C) (unadjusted p = 2.2 × 10−7, odds ratio = 2.23) contained within a linkage disequilibrium block on chromosome 16. In Genotype-Tissue Expression, rs722069 is an expression quantitative trait locus of the EARS2, COG7, and DCTN5 genes in skeletal muscle tissue. In subsets of the STRRIDE genetic cohort with available muscle gene expression (n = 37) and metabolic data (n = 82), at baseline the C allele was associated with lesser muscle expression of EARS2 (p &lt; .002) and COG7 (p = .074) as well as lesser muscle concentrations of C2- and C3-acylcarnitines (p = .026).ConclusionsOur observations imply that exercise intervention dropout is genetically moderated through alterations in gene expression and metabolic pathways in skeletal muscle. Individual genetic traits may allow the development of a biomarker-based approach for identifying individuals who may benefit from more intensive counseling and other interventions to optimize exercise intervention adoption.Clinical Trial informationSTRRIDE I = NCT00200993; STRRIDE AT/RT = NCT00275145; STRRIDE-PD = NCT00962962.
Patient-Reported Outcome Measures in High-Risk Medical Device Registries: A Scoping Review
Authors: Merenda Michelle , Earnest Arul , Ruseckaite Rasa , Tse Wai Chung , Elder Elisabeth , Hopper Ingrid , Ahern Susannah 
Published: March 2024

Abstract

Little is known about the methods and outcomes of patient-reported outcome measure (PROM) use among high-risk medical device registries. The objective of this scoping review was to assess the utility and predictive ability of PROMs in high-risk medical device registries. We searched Ovid Medline, Embase, APA PsychINFO, Cochrane Library, and Scopus databases for published literature. After searching, 4323 titles and abstracts were screened, and 262 full texts were assessed for their eligibility. Seventy-six papers from across orthopedic (n = 64), cardiac (n = 10), penile (n = 1), and hernia mesh (n = 1) device registries were identified. Studies predominantly used PROMs as an outcome measure when comparing cohorts or surgical approaches (n = 45) or to compare time points (n = 13) including pre- and postintervention. Fifteen papers considered the predictive ability of PROMs. Of these, 8 treated PROMs as an outcome, 5 treated PROMs as a risk factor through regression analysis, and 2 papers treated PROMs as both a risk factor and as an outcome. One paper described PROMs to study implant survival. To advance methods of PROM integration into clinical decision-making for medical devices, an understanding of their use in high-risk device registries is needed. This scoping review found that there is a paucity of studies using PROMs to predict long-term patient and clinical outcomes in high-risk medical device registries. Determination as to why PROMs are rarely used for predictive purposes in long-term data collection is needed if PROM data are to be considered suitable as real-world evidence for high-risk device regulatory purposes, as well as to support clinical decision-making.

Level of Evidence: 4
Decreasing Seroma Incidence Following Abdominoplasty: A Systematic Review and Meta-Analysis of High-Quality Evidence
Authors: Liao Christopher D , Zhao Kelley , Nikkhahmanesh Nia , Bui Duc T 
Published: March 2024

Abstract

Background
Seroma formation is the most common complication of abdominoplasties. Many preventive interventions have been proposed, but none have been recognized as a definitive solution, partly due to varying levels of evidence (LOE) in the literature.

Objectives
We aimed to analyze seroma prevention methods supported by high-level evidence.

Methods
The PubMed database was queried through August 2023. Primary articles of interest included randomized controlled trials (RCTs), prospective comparative studies, and meta-analyses of these studies. The LOE for each article was determined according to the American Society of Plastic Surgeons Rating Scale. The “seroma occurrence ratio,” or ratio of seroma events in the interventional group to respective control group, was calculated to compare incidence rates between techniques.

Results
Twenty articles and 9 categories of techniques were analyzed. Study designs included 10 RCTs, 2 prospective cohort studies, 7 prospective comparative studies, and 1 retrospective randomized study. The use of progressive-tension and quilting sutures had the most data supporting a statistically significant reduction in seroma (occurrence ratio 0.306, P &lt; .001). Tissue adhesives and preservation of Scarpa's fascia were also well reinforced (0.375, P &lt; .01 and 0.229, P &lt; .011, respectively), while increasing the number of drains was not (P = .7576). Meta-analysis demonstrated that compared with 2 drains alone, alternative techniques were more effective at reducing seroma occurrence (pooled risk ratio 0.33, 95% CI, 0.11-0.99).

Conclusions
This review highlights multiple seroma prevention techniques for abdominoplasty investigated in recent high-quality literature. We suggest future randomized comparative studies of the various seroma prevention methods to fully ascertain their efficacy following abdominoplasty.

Level of Evidence: 1
Associations of urinary fetuin-A with histopathology and kidney events in biopsy-proven kidney disease
Authors: Tsai Ming-Tsun , Tseng Wei-Cheng , Lee Kuo-Hua , Lin Chih-Ching , Ou Shuo-Ming , Li Szu-yuan 
Published: March 2024

ABSTRACT

Background
Fetuin-A is implicated in the pathogenesis of vascular calcification in chronic kidney disease (CKD); however, the relationship between fetuin-A, histopathologic lesions and long-term kidney outcomes in patients with various types of kidney disease remains unclear.

Methods
We measured urinary fetuin-A levels in 335 individuals undergoing clinically indicated native kidney biopsy. The expressions of fetuin-A mRNA and protein in the kidney were assessed using RNA sequencing and immunohistochemistry. The association of urinary fetuin-A with histopathologic lesions and major adverse kidney events (MAKE), defined as a decline in estimated glomerular filtration rate (eGFR) of at least 40%, kidney failure or death, was analyzed.

Results
Urinary fetuin-A levels showed a positive correlation with albuminuria (rs = 0.67, P &lt; .001) and a negative correlation with eGFR (rs = –0.46, P &lt; .001). After multivariate adjustment, higher urinary fetuin-A levels were associated with glomerular inflammation, mesangial expansion, interstitial fibrosis and tubular atrophy, and arteriolar sclerosis. Using a 1 transcript per million gene expression cutoff, we found kidney fetuin-A mRNA levels below the threshold in both individuals with normal kidney function and those with CKD. Additionally, immunohistochemistry revealed reduced fetuin-A staining in tubular cells of CKD patients compared with normal controls. During a median 21-month follow-up, 115 patients experienced MAKE, and Cox regression analysis confirmed a significant association between elevated urinary fetuin-A and MAKE. This association remained significant after adjusting for potential confounding factors.

Conclusion
Urinary fetuin-A is associated with chronic histological damage and adverse clinical outcomes across a spectrum of biopsy-proven kidney diseases.