bluuebunny/crossref_metadata_2025_split huggingface dataset:
A tool for beam optics design and its application on the VEGA transport line at ELI-NP
Authors: Chen G.-L. , Tian S.-Q. , Schubert H. , Udup E. , Matei C. 
Published: April 2024

Abstract
The Variable Energy Gamma (VEGA) System, currently under
construction at Extreme Light Infrastructure-Nuclear Physics
(ELI-NP), is a storage ring-based gamma beam source that aims to
provide gamma-ray beams with a variable energy range from 1 MeV to
19.5 MeV to the users. The electron beam transport line has been
designed to connect the linear accelerator and the storage ring in
the VEGA electron beam system. Considering the geometrical
constraints in the accelerator halls and the location of the
injection point at the storage ring, the trajectory of the electron
beam in the transport line has to first ascend by a 36-degree
dog-leg elevation to align with a plane parallel to the storage
ring, undergo a 180-degree horizontal turn, and then descend by 36
degrees vertically to reach the injection point at the storage
ring. In this paper, we introduce a beam optics tool implemented for
the beam optics design and fine-matching in the electron beam
transport line. The design of the VEGA transport line including the
layout and lattice design, is also described. The tool has been
applied to the beam optics design and optimization, utilizing
tracking simulations and beam matching for the VEGA transport line
lattice. Furthermore, the tool's potential application to similar
lattice designs is also discussed.
Harer–Zagier transform of the HOMFLY–PT polynomial for families of twisted hyperbolic knots
Authors: Petrou Andreani , Hikami Shinobu 
Published: April 2024

AbstractIn an attempt to generalise knot matrix models for non-torus knots, which currently remains an open problem, we derived expressions for the Harer–Zagier transform—a discrete Laplace transform—of the HOMFLY–PT polynomial for some infinite families of twisted hyperbolic knots. Among them, we found a family of pretzel knots for which, like for torus knots, the transform has a fully factorised form, while for the remaining families considered it consists of sums of factorised terms. Their zero loci show a remarkable structure, which mostly lies on the unit circle and deviates from it only in pairs.
Determination of lubricating behavior of resin during the sliding process of unidirectional prepreg
Authors: Li Zhefu , Liu Jun , Liu Weiping , Song Qinghua , Chen Ping , Yue Guangquan 
Published: April 2024

Abstract
In this paper, the lubrication behavior of resin during the molding process of unidirectional prepreg materials was scrutinized using a custom-made device. The thickness of the resin between prepregs under various conditions was calculated using Inverse Hydrodynamic Lubrication (IHL) theory to elucidate the lubrication mechanism. This calculation was confirmed by examining the surface morphologies of the prepreg and employing Digital Image Correlation (DIC) techniques for validation. Furthermore, the effect of unidirectional fiber orientation on the process of inter-ply sliding was quantitatively analyzed through the combined roughness. The study showed that factors such as sliding velocity, normal pressure, and fiber orientation play a key role in the lubrication mechanism. The lubrication behavior of unidirectional prepreg transformed to mixed lubrication under specific conditions. The results in our study of the lubrication mechanism have significant implications for the refinement of molding process and the enhancement of numerical simulations of unidirectional prepregs.
High-temperature mechanical properties of additively manufactured 420 stainless steel
Authors: Bongao Harveen , M Manjaiah , de Yro Persia Ada , Pasco Jubert , McCarthy Thomas , Nyamuchiwa Kudakwashe , Aranas Clodualdo 
Published: April 2024

Abstract
Martensitic stainless steels are indispensable alloys in various high stress and temperature applications such as plastic injection molds and components in steam generators. Subtractive manufacturing methods used to fabricate these parts, however, limits its functionality and performance due to design constraint of cooling channels. This limitation can be resolved by means of additive manufacturing while ensuring that acceptable high-temperature properties can be achieved. In this work, the mechanical behavior of additively manufactured 420 stainless steel (AM420SS) is explored through material constitutive modeling to determine the mathematical model that best describes its flow stress in extreme conditions. This is accomplished by subjecting the samples to hot compression under the strain rates of 0.1–1.0 s−1, and temperatures between 973–1423 K (700 °C–1150 °C) via Gleeble thermomechanical test. The experimental data were used to generate the predictive flow stress curves of constitutive models which includes Johnson-Cook, Zerilli-Armstrong, Zener-Hollomon, and Hensel-Spittel equations. Results showed that Zener-Hollomon and Hensel-Spittel models are the most accurate material constitutive equations with relatively high R values of 0.986 and 0.976, and low average absolute relative error values of 6.96% and 7.69%, respectively. The material constants derived from these models can be applied in finite element analysis simulations to assess the performance of using AM420SS parts at high temperature and strain conditions.
Potential contributions of digital finance to alleviating the ‘low-end lock-in’ dilemma for green innovation in enterprises
Authors: Yu Xinxin 
Published: April 2024

Abstract
As climate change risks intensify worldwide, green technological innovation by enterprises has become a crucial factor affecting the balance between economic development and ecological governance. This paper utilizes data from Chinese A-share listed companies in heavily polluting industries from 2011 to 2021 to investigate the impact and mechanism of the knowledge spillover effect of enterprise digital finance development on the phenomenon of ‘low-end lock-in’ in green innovation. The study finds that digital finance development significantly promotes green innovation in enterprises, with a more pronounced enhancement in high-end green innovation output, thereby mitigating the phenomenon of ‘low-end lock-in’ in green innovation. Mechanism analysis reveals that the development of digital finance in enterprises facilitates high-end green innovation by alleviating financing constraints and enhancing internal control levels through internal and external governance structures. Heterogeneity tests indicate that the promotion effect of digital finance development on high-end green innovation is more pronounced in samples of state-owned enterprises, large and medium-sized enterprises, and enterprises in central and eastern regions. This paper constructs an index of digital finance development for enterprises through text analysis, providing theoretical support for micro-enterprise research on digital finance development and empirical support for the impact of financial development trends on theories of enterprise green innovation.
Entrepreneurship promotion policies and urban carbon emission efficiency: does environmental concerns matter?
Authors: He Xiangmin , Zhou Jianhua 
Published: April 2024

Abstract
To foster economic and social development, many countries have adopted entrepreneurship promotion policies. However, existing research on entrepreneurship promotion policy primarily focuses on its employment incentive effect, while neglecting to examine the underlying impact mechanism and its effect on environmental sustainability. Based on the quasi-natural experiment of China’s National Entrepreneurial Pilot Cities, this paper employs the difference-in-differences model to examine the impact of the National Entrepreneurial Cities pilot policy on urban carbon emission efficiency. The study finds that China’s National Entrepreneurial Cities pilot policy has generally impaired urban carbon emission efficiency, and a series of robustness tests show that the results are robust. National Entrepreneurial Cities pilot policy decreases urban carbon emission efficiency by increasing the proportion of necessity entrepreneurship, inhibiting the upgrading of industrial structure, and increasing overcapacity. The government’s environmental concerns and the public’s environmental concerns play a prominent role in improving the adverse impact of the National Entrepreneurial Cities on carbon emission efficiency and mainly play a significant role in central and western cities, cities with low per capita GDP, cities with high economic growth pressure, and resource-dependent cities. The research of this paper provides a reference for the government to promote entrepreneurship while taking environmental effects into account.
A gyrator-C active inductor based tunable low noise amplifier for sub-GHz frequency range
Authors: Prashar Rajni , Kapur Garima 
Published: April 2024

Abstract
The propose exhibits a tunable low noise amplifier (LNA), which provides the tunability at sub-GHz frequency range and hence can become choicest frequency range for 5 G applications. Common source (CS) with source degeneration inductor LNA is proposed; in which the inductor in source branch is replaced by gyrator-c active inductor which not only reduced the overall area of the circuit but can also be used to provide the feature of tunability by changing the bias voltage of CMOS based active resistor in feedback branch. Therefore, instead of having a LNA circuit for the fixed frequency, a single tunable LNA design can be used over a range of frequency from 1 GHz to 5 GHz. The proposed approach will provide the direct tuning to the circuit. The forward voltage gain achieved is greater than 10 dB, input matching parameter is less than −10 dB and the output matching parameter is less than −10 dB. The average power dissipated is 0.02 W. The results can be tuned by controlling the feedback voltage of tunable active inductor (Tunable_AI). The tunable results can be achieved up to the bandwidth of 1 GHz.
Discovering quantum circuit components with program synthesis
Authors: Sarra Leopoldo , Ellis Kevin , Marquardt Florian 
Published: April 2024

Abstract
Despite rapid progress in the field, it is still challenging to discover new ways to leverage quantum computation: all quantum algorithms must be designed by hand, and quantum mechanics is notoriously counterintuitive. In this paper, we study how artificial intelligence, in the form of program synthesis, may help overcome some of these difficulties, by showing how a computer can incrementally learn concepts relevant to quantum circuit synthesis with experience, and reuse them in unseen tasks. In particular, we focus on the decomposition of unitary matrices into quantum circuits, and show how, starting from a set of elementary gates, we can automatically discover a library of useful new composite gates and use them to decompose increasingly complicated unitaries.
Event attribution of a midlatitude windstorm using ensemble weather forecasts
Authors: Ermis Shirin , Leach Nicholas J , Lott Fraser C , Sparrow Sarah N , Weisheimer Antje 
Published: April 2024

AbstractThe widespread destruction incurred by midlatitude storms every year makes it an imperative to study how storms change with climate. The impact of climate change on midlatitude windstorms, however, is hard to evaluate due to the small signals in variables such as wind speed, as well as the high resolutions required to represent the dynamic processes in the storms. Here, we assess how storm Eunice, which hit the UK in February 2022, was impacted by anthropogenic climate change using the ECMWF ensemble prediction system. This system was demonstrably able to predict the storm, significantly increasing our confidence in its ability to model the key physical processes and their response to climate change. Using modified greenhouse gas concentrations and changed initial conditions for ocean temperatures, we create two counterfactual scenarios of storm Eunice in addition to the forecast for the current climate. We compare the intensity and severity of the storm between the pre-industrial, current, and future climates. Our results robustly indicate that Eunice has become more intense with climate change and similar storms will continue to intensify with further anthropogenic forcing. These results are consistent across forecast lead times, increasing our confidence in them. Analysis of storm composites shows that this process is caused by increased vorticity production through increased humidity in the warm conveyor belt of the storm. This is consistent with previous studies on extreme windstorms. Our approach of combining forecasts at different lead times for event attribution enables combining event specificity and a focus on dynamic changes with the assessment of changing risks from windstorms. Further work is needed to develop methods to adjust the initial conditions of the atmosphere for the use in attribution studies using weather forecasts but we show that this approach is viable for reliable and fast attribution systems.
‘This smoke will finish us’: impacts of cooking with polluting fuels on air quality, health and education in three schools in Nairobi, Kenya
Authors: Nix Emily , Nabukwangwa Willah , Mwitari James , Lorenzetti Federico , Gohole Arthur , Saligari Serena , Shupler Matthew , Abbott Michael , Rosa Ghislaine , Anderson de Cuevas Rachel , Nyongesa Margaret , Puzzolo Elisa , Pope Daniel 
Published: April 2024

Abstract
Links between cooking with polluting fuels (e.g. wood and charcoal), air pollution and health in domestic settings are well-established. However, few studies have been conducted in schools that rely on such fuels for catering. This study is the first investigation of air pollution, cooking, and health in schools in Nairobi, Kenya. We carried out an in-depth mixed-methods study in three schools (two primary schools and a college) in an informal settlement using wood and/or charcoal for catering. In each school, repeated 24-hour air pollution measurements (fine particulate matter (PM2.5) and carbon monoxide (CO)) were collected to assess concentrations in the main kitchen and a nearby classroom, in addition to personal exposure for the main cook. Surveys with catering staff collected data on perspectives on air pollution and health symptoms. Focus groups were conducted with catering staff, teachers and senior management to understand perceived impacts on health and the school environment. 24 hour levels of PM2.5 were found to surpass world health organization interim target level 1 (IT-1) (35 μg m−3) in all schools—with levels three times higher (107.6 μg m−3) in classrooms, ten times higher (316.2 μg m−3) in kitchens and nearly six times higher (200.9 μg m−3) among cooks. Peak levels of pollution were closely linked to times of stove use, as concentrations doubled in classrooms and tripled in kitchens during cooking. Catering staff reported being concerned about their health, and reported experiencing wheezing, chest pains, eye irritation and headaches and attempted to avoid the smoke to reduce exposure. Disturbance to classes from cooking smoke was reported by teachers, with students reporting coughing and sneezing from exposure. Support is needed to enable clean cooking transitions in schools to create a healthy and safe learning environment.
“An Infinite Variety of Fragments”
Authors: Reznick Scott M 
Published: April 2024

AbstractThe chapter examines how the nullification crisis of the 1830s registers in Robert Montgomery Bird’s 1836 novel of fragmented selfhood, Sheppard Lee, and how the competing constitutional visions of Senators John Calhoun and Daniel Webster inform the highly metaphysical exploration of the constitution of selfhood that Bird’s novel undertakes. It argues that Bird turned to philosopher David Hume’s exploration of identity and his notion of a common point of view to examine the fate of moral vision amid the protagonist’s—and the nation’s—fundamentally disjointed experiences in the 1830s.
Epistemic Reciprocity Through a Decolonial Crip Literacy in Accommodated Language Education for Adults
Authors: Hedman Christina , Adams Lyngbäck Liz , Paul Enni , Rosén Jenny 
Published: April 2024

AbstractThis linguistic ethnography was conducted in accommodated language education in Sweden, aimed at adult learners with deafness, hearing impairment, post-traumatic stress disorder, migration stress, or intellectual disability, here, focusing on the latter group, who attended Swedish language learning courses. We empirically investigate a decolonial crip literacy, by connecting language education to epistemic reciprocity. The decolonial lens is understood with regard to the marginalized and dis-abled body, under-represented in Applied Linguistics. More specifically, we focus on teacher positionality and ethical stance-taking among three of the teachers, to contribute an in-depth and situated account of a decolonial crip literacy, as counteracts of ableism and linguicism, and an orientation toward epistemic justice. Based on our linguistic ethnographic data, we suggest that the decolonial crip literacy project engages with disability-as-difference, positioning the dis-abled body as knower, via epistemic reciprocity, which is communicated through a multiplicity of communicative resources, materialities, and creativity. The paper contributes both to the theorizing of injustice in language education and to alternatives in pedagogical practice.
9-point Injection Technique for Lip Augmentation and Lip Corner Lifting Using Sonographic Imaging of the Labial Artery Pathway
Authors: Kim Jong Seo 
Published: April 2024

Abstract

Background
As lip enhancement with fillers has grown in popularity, practitioners have sought to identify injection methods that achieve aesthetically pleasing results while avoiding adverse events such as arterial injury due to intravascular injection.

Objectives
The primary objective of this study was to establish a safe injection technique for creating appealing, proportionate, and aesthetically pleasing lips while elevating the lip corners with filler.

Methods
Before injection, the locations of the superior and inferior labial arteries were established by sonography and a 9-point injection technique (9-PIT) was devised to reliably achieve fashionable lips. Particle hyaluronic acid filler was administered to 50 patients by the 9-PIT and these patients were monitored for 3 months. The extent of lip corner elevation and the angle of lip corners were quantified by 3-dimensional analysis, while changes in the length and curvature along the upper peristomal lines were evaluated after 1 week.

Results
The superior and inferior labial arteries originated from the deep lateral aspect of the lip and gradually traversed toward the midline in the superficial layer. Superficial arterial branches were identified in the submucosal layer near the midline. All patients expressed satisfaction with the lip shaping and corner elevation, without any adverse effects or vascular complications. The angle of lip corners decreased by 8.80%, and lip corners were lifted by 1.02 mm. The upper lip exhibited a more pronounced S-shape, with the upper lip line being elongated by 6.5%. This accentuated S-shape contributed to the appearance of lifted lip corners.

Conclusions
The 9-PIT facilitated safe and aesthetically pleasing lip volumization with corner elevation in a consistent manner, while elucidating vascular pathways. Lip corner elevation was achieved solely using HA filler.

Level of Evidence: 3
Evaluation of a Combination Approach to Improving Muscle Tone and Decreasing Subcutaneous Tissue Thickness Using a Sequential, Dual-Modality, Energy-Based Device
Authors: Rothaus Kenneth , Brown Courtney 
Published: April 2024

Abstract

Background
The body shaping market has long been at the forefront of the aesthetic industry. With technological advances, patient demand for body sculpting in terms of reduction in subcutaneous tissue and enhancement of muscle has seen continual growth. Several devices have emerged in the space; however, few achieve both subcutaneous tissue reduction (SQR) and voluntary muscle increase (VMI) as measured by thickness, during the same treatment session.

Objectives
This article presents the results of a pilot study on a unique approach to subcutaneous tissue reduction and increasing muscle thickness using a dual-modality, energy-based device.

Methods
Twelve compliant patients (8 females and 4 males with an average age of 40 years) were enrolled in this single center, prospective study. All patients were treated with the dual-modality device (850 nm superluminescent diode matrix and electrical muscle stimulation), with external applicators being placed over the lower abdomen. The patients received 5 weekly treatments. Ultrasound measurements, photographs, weight, and waist measurements were taken at baseline, prior to the start of the fifth treatment, and at the 2-week and 2-month follow-up visits.

Results
At the 2-month follow-up visit, the average SQR was 34.03% and the VMI measured 22.97% in all patients who completed the study. All patient and physician evaluations rated the results as satisfactory or better. There were no complications.

Conclusions
Preliminary data show this dual-modality, electrical muscle stimulation/superluminescent diode matrix system provides both a safe and effective treatment for the reduction of subcutaneous tissue thickness and an increase in muscle definition and thickness. Objective and subjective evaluations demonstrated high levels of efficacy and satisfaction in all patients.

Level of Evidence: 2
BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases
Authors: Das Adhikari Sikta , Cui Yuehua , Wang Jianrong 
Published: April 2024

Abstract
Genome-wide Association Studies (GWAS) methods have identified individual single-nucleotide polymorphisms (SNPs) significantly associated with specific phenotypes. Nonetheless, many complex diseases are polygenic and are controlled by multiple genetic variants that are usually non-linearly dependent. These genetic variants are marginally less effective and remain undetected in GWAS analysis. Kernel-based tests (KBT), which evaluate the joint effect of a group of genetic variants, are therefore critical for complex disease analysis. However, choosing different kernel functions in KBT can significantly influence the type I error control and power, and selecting the optimal kernel remains a statistically challenging task. A few existing methods suffer from inflated type 1 errors, limited scalability, inferior power or issues of ambiguous conclusions. Here, we present a new Bayesian framework, BayesKAT (https://github.com/wangjr03/BayesKAT), which overcomes these kernel specification issues by selecting the optimal composite kernel adaptively from the data while testing genetic associations simultaneously. Furthermore, BayesKAT implements a scalable computational strategy to boost its applicability, especially for high-dimensional cases where other methods become less effective. Based on a series of performance comparisons using both simulated and real large-scale genetics data, BayesKAT outperforms the available methods in detecting complex group-level associations and controlling type I errors simultaneously. Applied on a variety of groups of functionally related genetic variants based on biological pathways, co-expression gene modules and protein complexes, BayesKAT deciphers the complex genetic basis and provides mechanistic insights into human diseases.