bluuebunny/crossref_metadata_2025_split huggingface dataset:
Laser-forged transformation and encapsulation of nanoalloys: pioneering robust wideband electromagnetic wave absorption and shielding from GHz to THz
Authors: Zhang Shizhuo , Rao Senlin , Li Yunfan , Wang Shuai , Sun Dingyue , Liu Feng , Cheng Gary J 
Published: May 2024

Abstract
The emergence of the internet of things has promoted wireless communication’s evolution towards multi-band and multi-area utilization. Notably, forthcoming sixth-generation (6G) communication standards, incorporating terahertz (THz) frequencies alongside existing gigahertz (GHz) modes, drive the need for a versatile multi-band electromagnetic wave (EMW) absorbing and shielding material. This study introduces a pivotal advance via a new strategy, called ultrafast laser-induced thermal-chemical transformation and encapsulation of nanoalloys (LITENs). Employing multivariate metal-organic frameworks, this approach tailors a porous, multifunctional graphene-encased magnetic nanoalloy (GEMN). By fine-tuning pulse laser parameters and material components, the resulting GEMN excels in low-frequency absorption and THz shielding. GEMN achieves a breakthrough of minimum reflection loss of −50.6 dB in the optimal C-band (around 4.98 GHz). Computational evidence reinforces GEMN’s efficacy in reducing radar cross sections. Additionally, GEMN demonstrates superior electromagnetic interference shielding, reaching 98.92 dB under THz band (0.1–2 THz), with the mean value result of 55.47 dB. These accomplishments underscore GEMN’s potential for 6G signal shielding. In summary, LITEN yields the remarkable EMW controlling performance, holding promise in both GHz and THz frequency domains. This contribution heralds a paradigm shift in EM absorption and shielding materials, establishing a universally applicable framework with profound implications for future pursuits.
Multi-stage manufacturing process parameter optimization method based on improved marine predator algorithm
Authors: Jiang Xiaojun , Zhan Hongfei , Yu Junhe , Wang Rui 
Published: May 2024

Abstract
Product quality is a critical factor in manufacturing industry competition, and mechanical processing technology has been widely applied in manufacturing, directly affecting product quality. Therefore, it is very important to find the appropriate optimal parameters to improve the impact of processing on product quality. However, modern production processes are characterized by complex mechanisms and the mutual influence of multiple processes, which poses higher challenges for optimizing processing technology parameters. In this regard, the thesis proposes a method for optimizing process parameters in multi-process manufacturing based on an improved marine predator algorithm, aiming to optimize and improve process parameters in multi-process manufacturing processes. Firstly, a multi-process modeling strategy is adopted to explore the nonlinear relationship between process parameters and quality indicators based on multi-gene genetic planning, establishing a multi-process parameter optimization objective model. This effectively solves the problem of modeling difficulty caused by severe coupling of multiple processes. Then, to improve the efficiency of solving the optimization objective model, an improved marine predator algorithm is proposed, utilizing reverse learning strategies and mixed control parameters to enhance optimization capability, thereby obtaining the global optimal solution. Finally, using production process data from a certain factory as an example, the feasibility of the proposed method is verified, achieving the goal of multi-process process parameter optimization and ensuring the stability of product quality.
Economic complexity and the sustainability transition: a review of data, methods, and literature
Authors: Caldarola Bernardo , Mazzilli Dario , Napolitano Lorenzo , Patelli Aurelio , Sbardella Angelica 
Published: May 2024

Abstract
Economic Complexity (EC) methods have gained increasing popularity across fields and disciplines. In particular, the EC toolbox has proved particularly promising in the study of complex and interrelated phenomena, such as the transition towards a more sustainable economy. Using the EC approach, scholars have been investigating the relationship between EC and sustainability, and identifying the distinguishing characteristics of green activities and to assess the readiness of productive and technological structures for the sustainability transition. This article proposes to review and summarize the data, methods, and empirical literature that are relevant to the study of the sustainability transition from an EC perspective. We review three distinct but connected blocks of literature on EC and environmental sustainability. First, we survey the evidence linking measures of EC to indicators related to environmental sustainability. Second, we review articles that strive to assess the green competitiveness of productive systems. Third, we examine evidence on green technological development and its connection to non-green knowledge bases. Finally, we summarize the findings for each block, while identifying criticalities and avenues for further research in this recent and growing body of empirical literature.
Reinforcement learning pulses for transmon qubit entangling gates
Authors: Nam Nguyen Ho , Motzoi Felix , Metcalf Mekena , Birgitta Whaley K , Bukov Marin , Schmitt Markus 
Published: May 2024

Abstract
The utility of a quantum computer is highly dependent on the ability to reliably perform accurate quantum logic operations. For finding optimal control solutions, it is of particular interest to explore model-free approaches, since their quality is not constrained by the limited accuracy of theoretical models for the quantum processor—in contrast to many established gate implementation strategies. In this work, we utilize a continuous control reinforcement learning algorithm to design entangling two-qubit gates for superconducting qubits; specifically, our agent constructs cross-resonance and CNOT gates without any prior information about the physical system. Using a simulated environment of fixed-frequency fixed-coupling transmon qubits, we demonstrate the capability to generate novel pulse sequences that outperform the standard cross-resonance gates in both fidelity and gate duration, while maintaining a comparable susceptibility to stochastic unitary noise. We further showcase an augmentation in training and input information that allows our agent to adapt its pulse design abilities to drifting hardware characteristics, importantly, with little to no additional optimization. Our results exhibit clearly the advantages of unbiased adaptive-feedback learning-based optimization methods for transmon gate design.
Estimating and presenting hazard ratios and absolute risks from a Cox model with complex nonlinear interactions
Authors: Bellavia Andrea , Melloni Giorgio E M , Park Jeong-Gun , Discacciati Andrea , Murphy Sabina A 
Published: May 2024

Abstract
Interaction analysis is a critical component of clinical and public health research and represents a key topic in precision health and medicine. In applied settings, however, interaction assessment is usually limited to the test of a product term in a regression model and to the presentation of results stratified by levels of additional covariates. Stratification of results often relies on categorizing or making linearity assumptions for continuous covariates, with substantial loss of precision and of relevant information. In time-to-event analysis, moreover, interaction assessment is often limited to the multiplicative hazard scale by inclusion of a product term in a Cox regression model, disregarding the clinically relevant information that is captured by the absolute risk scale. In this paper we present a user-friendly procedure, based on the prediction of individual absolute risks from the Cox model, for the estimation and presentation of interactive effects on both the multiplicative and additive scales in survival analysis. We describe how to flexibly incorporate interactions with continuous covariates, which potentially operate in a nonlinear fashion, provide software for replicating our procedure, and discuss different approaches to deriving CIs. The presented approach will allow clinical and public health researchers to assess complex relationships between multiple covariates as they relate to a clinical endpoint, and to provide a more intuitive and precise depiction of the results in applied research papers focusing on interaction and effect stratification.
A critique and examination of the polysocial risk score approach: predicting cognition in the Health and Retirement Study
Authors: Jawadekar Neal , Zimmerman Scott , Lu Peiyi , Riley Alicia R , Glymour M Maria , Kezios Katrina , Al Hazzouri Adina Zeki 
Published: May 2024

Abstract
Polysocial risk scores were recently proposed as a strategy for improving the clinical relevance of knowledge about social determinants of health. Our objective in this study was to assess whether the polysocial risk score model improves prediction of cognition and all-cause mortality in middle-aged and older adults beyond simpler models including a smaller set of key social determinants of health. We used a sample of 13 773 individuals aged ≥50 years at baseline from the 2006-2018 waves of the Health and Retirement Study, a US population-based longitudinal cohort study. Four linear mixed models were compared: 2 simple models including a priori–selected covariates and 2 polysocial risk score models which used least absolute shrinkage and selection operator (LASSO) regularization to select covariates among 9 or 21 candidate social predictors. All models included age. Predictive accuracy was assessed via R2 and root mean-squared prediction error (RMSPE) using training/test split validation and cross-validation. For predicting cognition, the simple model including age, race, sex, and education had an R2 value of 0.31 and an RMSPE of 0.880. Compared with this, the most complex polysocial risk score selected 12 predictors (R2 = 0.35 and RMSPE = 0.858; 2.2% improvement). For all-cause mortality, the simple model including age, race, sex, and education had an area under the receiver operating characteristic curve (AUROC) of 0.747, while the most complex polysocial risk score did not demonstrate improved performance (AUROC = 0.745). Models built on a smaller set of key social determinants performed comparably to models built on a more complex set of social “risk factors.”
Racial and ethnic differences in epithelial ovarian cancer risk: an analysis from the Ovarian Cancer Association Consortium
Authors: Meagher Nicola S , White Kami K , Wilkens Lynne R , Bandera Elisa V , Berchuck Andrew , Carney Michael E , Cramer Daniel W , Cushing-Haugen Kara L , Jordan Susan , Kaufmann Scott H , Le Nhu D , Pike Malcolm C , Riggan Marjorie , Qin Bo , Rothstein Joseph H , Titus Linda , Winham Stacey J , Anton-Culver Hoda , Doherty Jennifer A , Goode Ellen L , Pearce Celeste Leigh , Risch Harvey A , Webb Penelope M , Cook Linda S , Goodman Marc T , Harris Holly R , Le Marchand Loic , McGuire Valerie , Pharoah Paul D P , Sarink Danja , Schildkraut Joellen M , Sieh Weiva , Terry Kathryn L , Thompson Pamela J , Whittemore Alice S , Wu Anna H , Peres Lauren C , Merritt Melissa A 
Published: May 2024

Abstract
Limited estimates exist on risk factors for epithelial ovarian cancer (EOC) in Asian, Hispanic, and Native Hawaiian/Pacific Islander women. Participants in this study included 1734 Asian (n = 785 case and 949 control participants), 266 Native Hawaiian/Pacific Islander (n = 99 case and 167 control participants), 1149 Hispanic (n = 505 case and 644 control participants), and 24 189 White (n = 9981 case and 14 208 control participants) from 11 studies in the Ovarian Cancer Association Consortium. Logistic regression models estimated odds ratios (ORs) and 95% CIs for risk associations by race and ethnicity. Heterogeneity in EOC risk associations by race and ethnicity (P ≤ .02) was observed for oral contraceptive (OC) use, parity, tubal ligation, and smoking. We observed inverse associations with EOC risk for OC use and parity across all groups; associations were strongest in Native Hawaiian/Pacific Islander and Asian women. The inverse association for tubal ligation with risk was most pronounced for Native Hawaiian/Pacific Islander participants (odds ratio (OR) = 0.25; 95% CI, 0.13-0.48) compared with Asian and White participants (OR = 0.68 [95% CI, 0.51-0.90] and OR = 0.78 [95% CI, 0.73-0.85], respectively). Differences in EOC risk factor associations were observed across racial and ethnic groups, which could be due, in part, to varying prevalence of EOC histotypes. Inclusion of greater diversity in future studies is essential to inform prevention strategies.
This article is part of a Special Collection on Gynecological Cancers.
Do Absorbable Sutures Work for Rectus Diastasis Repair in Abdominoplasty Patients?
Authors: Jackson Brandon T , Moradian Simon , Bricker Jonathan T , Termanini Kareem M , Ferenz Sarah , Bai Jennifer , Kim John Y 
Published: May 2024

Abstract

Background
The standard treatment for rectus diastasis is rectus sheath plication during abdominoplasty. Lasting correction of diastasis is essential, but there is currently a debate as to whether absorbable or nonabsorbable rectus plication achieves a lower rate of recurrence.

Objectives
The goal of this study is to assess long-term patient outcomes and the recurrence of rectus diastasis after plication with long-lasting absorbable sutures.

Methods
A retrospective study of abdominoplasties performed by the senior author between 2018 and 2022 was performed. Only female patients with &gt;6 months of follow-up were included. Plication of the rectus muscles was performed with a combination of interrupted, buried, figure of eight #0 polydioxanone suture and running #0 Maxon (Covidien, Mansfield, MA). Outcomes were assessed by physical examination at postoperative visits. A retrospective chart review was used to obtain demographic and perioperative information.

Results
Seventy-one patients underwent abdominoplasty with an average follow-up of 21.1 months. The average age was 43 years, and the average BMI was 27 kg/m2. Correction of rectus diastasis was performed using absorbable sutures in all patients with no recurrence of diastasis in any patient (0% diastasis recurrence rate). Complications included delayed wound healing (11%), seroma (8.5%), hematoma (2.8%), and deep vein thrombosis/pulmonary embolism (2.8%). No patients needed reoperation.

Conclusions
Abdominal wall plication using a double-layered, long-lasting absorbable suture closure is a safe, reliable, and effective method to address rectus diastasis during abdominoplasty. Our technique achieved no recurrence of diastasis in any patient and a low complication profile.

Level of Evidence: 3
Predicting tall-cell subtype of papillary thyroid carcinomas independently with preoperative multimodal ultrasound
Authors: Ye Bei-Bei , Liu Yun-Yun , Zhang Ying , Liu Bo-Ji , Guo Le-Hang , Wei Qing , Zhang Yi-Feng , Xu Hui-Xiong 
Published: May 2024

Abstract

Objectives
This study aimed to explore the differences between tall-cell subtype of papillary thyroid carcinoma (TCPTC) and classical papillary thyroid carcinoma (cPTC) using multimodal ultrasound, and identify independent risk factors for TCPTC to compensate the deficiency of preoperative cytological and molecular diagnosis on PTC subtypes.

Methods
Forty-six TCPTC patients and 92 cPTC patients were included. Each patient received grey-scale ultrasound, colour Dopplor flow imaging (CDFI) and shear-wave elastography (SWE) preoperatively. Clinicopathologic information, grey-scale ultrasound features, CDFI features and SWE features of 98 lesions were compared using univariate analysis to find out predictors of TCPTC, based on which, a predictive model was built to differentiate TCPTC from cPTC and validated with 40 patients.

Results
Univariate and multivariate analyses identified that extra-thyroidal extension (odds ratio [OR], 15.12; 95% CI, 2.26-115.44), aspect ratio (≥0.91) (OR, 29.34; 95% CI, 1.29-26.23), and maximum diameter ≥14.6 mm (OR, 20.79; 95% CI, 3.87-111.47) were the independent risk factors for TCPTC. Logistic regression equation: P = 1/1+ExpΣ[−5.099 + 3.004 × (if size ≥14.6 mm) + 2.957 × (if aspect ratio ≥ 0.91) + 2.819 × (if extra-thyroidal extension). The prediction model had a good discrimination performance for TCPTC: the area under the receiver-operator-characteristic curve, sensitivity, and specificity were 0.928, 0.848, and 0.954 in cohort 1, and the corresponding values in cohort 2 were 0.943, 0.923, and 0.926, respectively.

Conclusion
Ultrasound has the potential for differential diagnosis of TCPTC from cPTC. A prediction model based on ultrasound characteristics (extra-thyroidal extension, aspect ratio ≥0.91, and maximum diameter ≥14.6 mm) was useful in predicting TCPTC.

Advances in knowledge
Multimodal ultrasound prediction of TCPTC was a supplement to preoperative cytological diagnosis and molecular diagnosis of PTC subtypes.
Synthetic data in radiological imaging: current state and future outlook
Authors: Sizikova Elena , Badal Andreu , Delfino Jana G , Lago Miguel , Nelson Brandon , Saharkhiz Niloufar , Sahiner Berkman , Zamzmi Ghada , Badano Aldo 
Published: May 2024

Abstract
A key challenge for the development and deployment of artificial intelligence (AI) solutions in radiology is solving the associated data limitations. Obtaining sufficient and representative patient datasets with appropriate annotations may be burdensome due to high acquisition cost, safety limitations, patient privacy restrictions, or low disease prevalence rates. In silico data offers a number of potential advantages to patient data, such as diminished patient harm, reduced cost, simplified data acquisition, scalability, improved quality assurance testing, and a mitigation approach to data imbalances. We summarize key research trends and practical uses for synthetically generated data for radiological applications of AI. Specifically, we discuss different types of techniques for generating synthetic examples, their main application areas, and related quality control assessment issues. We also discuss current approaches for evaluating synthetic imaging data. Overall, synthetic data holds great promise in addressing current data availability gaps, but additional work is needed before its full potential is realized.
Potential for in vivo visualization of intracellular pH gradient in the brain using PET imaging
Authors: Yamasaki Tomoteru , Mori Wakana , Ohkubo Takayuki , Hiraishi Atsuto , Zhang Yiding , Kurihara Yusuke , Nengaki Nobuki , Tashima Hideaki , Fujinaga Masayuki , Zhang Ming-Rong 
Published: May 2024

Abstract
Intracellular pH is a valuable index for predicting neuronal damage and injury. However, no PET probe is currently available for monitoring intracellular pH in vivo. In this study, we developed a new approach for visualizing the hydrolysis rate of monoacylglycerol lipase, which is widely distributed in neurons and astrocytes throughout the brain. This approach uses PET with the new radioprobe [11C]QST-0837 (1,1,1,3,3,3-hexafluoropropan-2-yl-3-(1-phenyl-1H-pyrazol-3-yl)azetidine-1-[11C]carboxylate), a covalent inhibitor containing an azetidine carbamate skeleton for monoacylglycerol lipase. The uptake and residence of this new radioprobe depends on the intracellular pH gradient, and we evaluated this with in silico, in vitro and in vivo assessments. Molecular dynamics simulations predicted that because the azetidine carbamate moiety is close to that of water molecules, the compound containing azetidine carbamate would be more easily hydrolyzed following binding to monoacylglycerol lipase than would its analogue containing a piperidine carbamate skeleton. Interestingly, it was difficult for monoacylglycerol lipase to hydrolyze the azetidine carbamate compound under weakly acidic (pH 6) conditions because of a change in the interactions with water molecules on the carbamate moiety of their complex. Subsequently, an in vitro assessment using rat brain homogenate to confirm the molecular dynamics simulation-predicted behaviour of the azetidine carbamate compound showed that [11C]QST-0837 reacted with monoacylglycerol lipase to yield an [11C]complex, which was hydrolyzed to liberate 11CO2 as a final product. Additionally, the 11CO2 liberation rate was slower at lower pH. Finally, to indicate the feasibility of estimating how the hydrolysis rate depends on intracellular pH in vivo, we performed a PET study with [11C]QST-0837 using ischaemic rats. In our proposed in vivo compartment model, the clearance rate of radioactivity from the brain reflected the rate of [11C]QST-0837 hydrolysis (clearance through the production of 11CO2) in the brain, which was lower in a remarkably hypoxic area than in the contralateral region. In conclusion, we indicated the potential for visualization of the intracellular pH gradient in the brain using PET imaging, although some limitations remain. This approach should permit further elucidation of the pathological mechanisms involved under acidic conditions in multiple CNS disorders.
A comparative study of bifacial versus monofacial PV systems at the UK’s largest solar plant
Authors: Badran Ghadeer , Dhimish Mahmoud 
Published: May 2024

Abstract
This paper presents an extensive analysis of the UK’s largest bifacial photovoltaic (PV) power plant, located in North Yorkshire. Commissioned in January 2020, this trailblazing facility, with a total installed capacity of 34.7 MW, is a benchmark for the evaluation of bifacial solar technology within the region. This pioneering study provides a thorough comparative assessment of bifacial and monofacial PV systems through a methodical investigation of their energy production, degradation rates, and spectral responses over a 4-year operational period. Our findings reveal that bifacial PV modules, distributed across four segments of the power plant, demonstrate a remarkable average power gain ranging between 15.12% and 17.31% compared with monofacial modules. Despite experiencing marginally higher annual degradation rates—1.17% for bifacial compared with 0.91% for monofacial systems—bifacial modules show superior resilience and energy yield, particularly during winter months when albedo effects are pronounced due to snow coverage. The study also highlights the strategic importance of spectral response analysis in optimizing PV performance. Bifacial modules have shown greater efficiency in capturing infrared radiation—a property that could be exploited to enhance overall energy yield under specific environmental conditions. The empirical data indicate a consistent performance of bifacial modules with an average normalized energy output clustering around the expected efficiency level. Therefore, the results of this study are pivotal for understanding the practical implications of deploying bifacial PV technology on a large scale. They provide valuable data for stakeholders in the solar energy sector, guiding future installations and innovations in solar panel technology.