bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simulating adiabatic quantum computing with parameterized quantum circuits
Authors: Kolotouros Ioannis , Petrongonas Ioannis , Prokop Miloš , Wallden Petros 
Published: September 2024

Abstract
Adiabatic quantum computing is a universal model for quantum computing whose implementation using a gate-based quantum computer requires depths that are unreachable in the early fault-tolerant era. To mitigate the limitations of near-term devices, a number of hybrid approaches have been pursued in which a parameterized quantum circuit prepares and measures quantum states and a classical optimization algorithm minimizes an objective function that encompasses the solution to the problem of interest. In this work, we propose a different approach starting by analyzing how a small perturbation of a Hamiltonian affects the parameters that minimize the energy within a family of parameterized quantum states. We derive a set of equations that allow us to compute the new minimum by solving a constrained linear system of equations that is obtained from measuring a series of observables on the unperturbed system. We then propose a discrete version of adiabatic quantum computing that can be implemented in a near-term device while at the same time is insensitive to the initialization of the parameters and to other limitations hindered in the optimization part of variational quantum algorithms. We compare our proposed algorithm with the variational quantum eigensolver on two classical optimization problems, namely MaxCut and number partitioning, and on a quantum-spin configuration problem, the transverse-field ising chain model, and confirm that our approach demonstrates superior performance.
Parametric optimization of weld bead of aluminium 6061 fabricated through wire arc additive manufacturing
Authors: Lekkala Nalini , Prasad Kondapalli Siva 
Published: September 2024

Abstract
Additive fabrication with wire arc shown tremendous advancements in recent years. The current study investigates the effect of welding conditions on the width of an additively produced layer by using Gas Metal Arc Welding - Cold Metal Transfer welding. Further, the Taguchi method was used to optimize the effect of weld settings on layer width which was additively deposited. The wire spool is made of Aluminium 6061, which has a wide range of industrial applications. Flaws, porosity, waviness,and weld bead's discontinuity on a surface could be minimized by the assortment and optimization of parameters or else, strange forms would emerge during creation of slender wall construction utilising Wire Arc Additive manufacturing. In Taguchi, an L9 Orthogonal array was utilised to investigate the input parameters namely wire feed speed, weld speed and voltage. The main plots identify the best parameter combination, while the analysis of variance determines the significant parameters. For the response variable, a linear regression approach is used to create a numerical model. The minimum width of bead of 2.39 mm is achieved at weld velocity of 0.9 m/min with wire feed speed of 6 m/min and at voltage of 12 V. The maximum width of the bead was 6.40 mm, achieved at weld velocity of 0.6 m/min with wire feed speed of 8 m/min at a voltage of 16 V. After optimising the parameters, confirmation tests are run, and the outcomes are compared to the initial outcome.
The effects of tool rotational speed and post-weld heat treatment of friction stir welded AZ31-B magnesium alloy
Authors: Kumaresh D , S Venkatesan 
Published: September 2024

Abstract
This research article examines the effect of increasing the tool rotational speed and post-weld heat treatment behavior of friction stir-welded AZ31-B magnesium alloy. The variable tool rotational speeds of 1000 rpm, 1200 rpm, 1400 rpm, and 1600 rpm with fixed tool traverse speeds of 30 mm min−1 were chosen based on the trial welding method. Results reveal that the as-welded tensile strength values of 133 MPa, 209 MPa, 215 MPa, and 213 MPa for the corresponding tool rotation speeds and post-weld heat-treated tensile strength values of 140 MPa, 213 MPa, 223 MPa, and 227 MPa significantly increased joint strength when compared to the as-welded process. The measured grain size values are reduced when the tool rotational speed increases due to material dynamic recrystallization. Al-Mg brittle intermetallic compounds significantly reduced the mechanical strength during the increase of the tool’s rotational speed. Fractography analysis reveals all welded samples fractured at the center of the stir zone with a ductile fracture angle of 45°.
Synthesis of chlorotoxin functionalized metallic nanoparticles and their in vitro evaluation of cytotoxic effects in nervous system cancer cell lines
Authors: Boltman Taahirah , Sibuyi Nicole Remaliah Samantha , Ekpo Okobi , Meyer Mervin 
Published: September 2024

Abstract
The treatment of glioblastoma (GB) and neuroblastoma (NB) remains a challenge, as current chemotherapies are plagued with systemic toxicity, drug resistance, and inadequate blood–brain barrier (BBB) penetration. Therefore, novel therapeutic strategies with high specificity and the capacity to bypass the BBB are required. Chlorotoxin (CTX) selectively targets gliomas and neuroectodermal tumors, hence the use of CTX-targeted nanoparticles (NPs) represents a promising therapeutic approach for nervous system (NS) cancers. Bimetallic NPs composed of two metals such as gold-platinum NPs (AuPtNPs) exhibit enhanced anticancer properties compared to single-metal NPs, however their application in studying NS tumors has been relatively limited. CTX-functionalized monometallic gold NPs (CTX-AuNPs) and bimetallic gold-platinum NPs (CTX-AuPtNPs) were synthesized in this study. The NPs were characterized by Ultraviolet-Visible Spectroscopy (UV–vis), Dynamic Light Scattering (DLS), Transmission Electron Microscopy (TEM) and Fourier Transform Infra-Red Spectroscopy (FTIR). Cytotoxicity of NPs was investigated in cancer (U87 and SH-SY5Y) and non-cancer (KMST-6) cells using the water-soluble tetrazolium (WST)-1 assay. The CTX-AuNPs and CTX-AuPtNPs had a core size of ∼5 nm. The CTX-AuPtNPs showed significant anticancer activity in U87 cells possibly due to the synergistic effects of combined metals. Findings obtained from this study demonstrated that CTX can be used to target NS cancers and that bimetallic NPs could be effective in their treatment. More studies are required to investigate the mechanisms of NPs toxicity, and further explore the hyperthermia treatment of NS cancer using the CTX-AuPtNPs.
Launaea cornuta (wild lettuce) leaf extract: phytochemical analysis and synthesis of silver-zinc oxide nanocomposite
Authors: Makauki Elizabeth , Rwiza Mwemezi , Machunda Revocatus , Basu Onita D 
Published: September 2024

Abstract
Access to quality drinking water is an essential human right and a fundamental aspect of human dignity, yet a challenge to many in developing countries. Over 2 billion people worldwide lack access to quality drinking water due to microbial contamination, among other factors. Silver-doped zinc oxide impregnated activated carbon nanocomposites, Ag-ZnO-AC NCs, a strong antimicrobial agent have been used at point-of-use to treat water treatment. Green synthesis of Ag-ZnO-AC NCs has played a vital role since it leads to the acquisition of non-toxic nanocomposites compared to chemical synthesis. In this study, Ag-ZnO-AC NCs were green-synthesized using Launaea cornuta leaf extract as a source of reducing and capping agents in place of synthetic chemicals. Antioxidants from Launaea cornuta (Wild Lettuce) leaves were extracted using 0, 50, and 100% EtOH solvents with different volumes and extraction circles. The highest phenolic (11044 ± 63 μg) and antioxidant (44112 ± 894 μg) contents were extracted using 50% EtOH and 20 ml of extract solvent with p < 0.05. The SEM and TEM images of the synthesized Ag-ZnO-AC NCs show the formation of highly porous AC with sheet-like structures and successful Ag-ZnO NCs impregnation within the pores and on the surface of the AC. Based on the inhibition zone, the antimicrobial activity of the Ag-ZnO AC NCs had significant results with 14.00 ± 0.37 for E. coli and 17.33 ± 0.36 mm for S. aureus, p < 0.05. These results confirm the significance of Launaea cornuta (Wild Lettuce) as a source of antioxidants that can be used as reducing and capping agents to synthesize Ag-ZnO-AC NCs.
From Colonialism to Self-determination: A Historical Study of Language Testing and Institutional Policy
Authors: Zakaria Azrifah , Aryadoust Vahid 
Published: September 2024

Abstract
This study examines the development of institutional policies on language testing, taking the case of a former British colony, Singapore. Using historical narrative inquiry to analyse the Ministry of Education’s archived documents, we investigate how institutions form part of the assessment ecosystem that continues to function in the present day. We identified two main themes in the development of English language testing in Singapore. The first theme From Free Enterprise to Governance describes the trajectory of language testing from the colonial era to independence, with a fragmented assessment landscape gradually moving towards centralized planning. The second theme Individual Agency and Institutional Change illustrates how the needs of the individual interact with the institution. Responses by the ministry and examination board provide important insights into the processes of test development from a micro perspective and how consequences for the individual intersect with macro issues. We highlight the necessity of taking a historical perspective to provide a more holistic picture of how we currently practice language testing.
The Study of the Safety and Effectiveness of Motiva SmoothSilk Silicone Gel-Filled Breast Implants in Patients Undergoing Primary and Revisional Breast Augmentation: Three-Year Clinical Data
Authors: Glicksman Caroline , Wolfe Andrew , McGuire Patricia 
Published: September 2024

Abstract

Background
Silicone breast implant design has evolved over the last 50 years. Regulatory bodies including the FDA require data to support the modifications designed to improve the safety, efficacy, longevity, and biocompatibility of breast implants.

Objectives
The authors reviewed the 3-year data on the safety and effectiveness of Motiva (Establishment Labs Holdings, Inc., Alajuela, Costa Rica) SmoothSilk silicone gel-filled breast implants submitted to the FDA. The current submitted data include the primary breast augmentation and revisional augmentation cohorts.

Methods
The Motiva IDE is a prospective, single-arm, multicenter, 10-year pivotal study in which data are collected on breast augmentation, reconstruction, and revisional surgery. Three-year data were submitted to the FDA on adverse events, reoperations, patient and physician satisfaction, connective tissue diseases, and quality of life validated instruments. A subset of the patients underwent annual magnetic resonance imaging (MRI) at years 1, 2, and 3 to screen for implant rupture.

Results
A total of 451 patients were implanted in the primary augmentation cohort and 109 patients in the revisional augmentation cohort. There were 218 patients enrolled in the MRI cohort. Reported rates for reoperation for any reason were 6.1% in the primary augmentation cohort (92.4% follow-up) and 25.8% in the revisional augmentation cohort (88.7% follow-up).

Discussion
Motiva implants were first introduced in 2010. The 3-year Motiva data suggests that the leading cause of revisional surgery has shifted from capsular contracture and rupture to more subjective indications for reoperation such as malposition and size change.

Conclusions
Three-year data from the primary augmentation and revisional augmentation cohorts submitted to the FDA demonstrate the safety and efficacy of the Motiva implants. There were low complication rates for implant-related complications and high surgeon and patient satisfaction.

Level of Evidence: 2
nsDCC: dual-level contrastive clustering with nonuniform sampling for scRNA-seq data analysis
Authors: Wang Linjie , Li Wei , Zhou Fanghui , Yu Kun , Feng Chaolu , Zhao Dazhe 
Published: September 2024

Abstract
Dimensionality reduction and clustering are crucial tasks in single-cell RNA sequencing (scRNA-seq) data analysis, treated independently in the current process, hindering their mutual benefits. The latest methods jointly optimize these tasks through deep clustering. However, contrastive learning, with powerful representation capability, can bridge the gap that common deep clustering methods face, which requires pre-defined cluster centers. Therefore, a dual-level contrastive clustering method with nonuniform sampling (nsDCC) is proposed for scRNA-seq data analysis. Dual-level contrastive clustering, which combines instance-level contrast and cluster-level contrast, jointly optimizes dimensionality reduction and clustering. Multi-positive contrastive learning and unit matrix constraint are introduced in instance- and cluster-level contrast, respectively. Furthermore, the attention mechanism is introduced to capture inter-cellular information, which is beneficial for clustering. The nsDCC focuses on important samples at category boundaries and in minority categories by the proposed nearest boundary sparsest density weight assignment algorithm, making it capable of capturing comprehensive characteristics against imbalanced datasets. Experimental results show that nsDCC outperforms the six other state-of-the-art methods on both real and simulated scRNA-seq data, validating its performance on dimensionality reduction and clustering of scRNA-seq data, especially for imbalanced data. Simulation experiments demonstrate that nsDCC is insensitive to “dropout events” in scRNA-seq. Finally, cluster differential expressed gene analysis confirms the meaningfulness of results from nsDCC. In summary, nsDCC is a new way of analyzing and understanding scRNA-seq data.
Meeting the challenge of genomic analysis: a collaboratively developed workshop for pangenomics and topological data analysis
Authors: Contreras-Peruyero Haydeé , Guerrero-Flores Shaday , Zirión-Martínez Claudia , Mejía-Ponce Paulina M , Navarro-Miranda Marisol , Lovaco-Flores J Abel , Ibarra-Rodríguez José M , Pashkov Anton , Licona-Cassani Cuauhtémoc , Sélem-Mojica Nelly 
Published: September 2024

Abstract

Motivation
As genomics data analysis becomes increasingly intricate, researchers face the challenge of mastering various software tools. The rise of Pangenomics analysis, which examines the complete set of genes in a group of genomes, is particularly transformative in understanding genetic diversity. Our interdisciplinary team of biologists and mathematicians developed a short Pangenomics Workshop covering Bash, Python scripting, Pangenome, and Topological Data Analysis. These skills provide deeper insights into genetic variations and their implications in Evolutionary Biology. The workshop uses a Conda environment for reproducibility and accessibility. Developed in The Carpentries Incubator infrastructure, the workshop aims to equip researchers with essential skills for Pangenomics research. By emphasizing the role of a community of practice, this work underscores its significance in empowering multidisciplinary professionals to collaboratively develop training that adheres to best practices.

Results
Our workshop delivers tangible outcomes by enhancing the skill sets of Computational Biology professionals. Participants gain hands-on experience using real data from the first described pangenome. We share our paths toward creating an open-source, multidisciplinary, and public resource where learners can develop expertise in Pangenomic Analysis. This initiative goes beyond advancing individual capabilities, aligning with the broader mission of addressing educational needs in Computational Biology.

Availability and implementation
https://carpentries-incubator.github.io/pangenomics-workshop/
Identifying nucleotide-binding leucine-rich repeat receptor and pathogen effector pairing using transfer-learning and bilinear attention network
Authors: Qiao Baixue , Wang Shuda , Hou Mingjun , Chen Haodi , Zhou Zhengwenyang , Xie Xueying , Pang Shaozi , Yang Chunxue , Yang Fenglong , Zou Quan , Sun Shanwen 
Published: September 2024

Abstract

Motivation
Nucleotide-binding leucine-rich repeat (NLR) family is a class of immune receptors capable of detecting and defending against pathogen invasion. They have been widely used in crop breeding. Notably, the correspondence between NLRs and effectors (CNE) determines the applicability and effectiveness of NLRs. Unfortunately, CNE data is very scarce. In fact, we’ve found a substantial 91 291 NLRs confirmed via wet experiments and bioinformatics methods but only 387 CNEs are recognized, which greatly restricts the potential application of NLRs.

Results
We propose a deep learning algorithm called ProNEP to identify NLR-effector pairs in a high-throughput manner. Specifically, we conceptualized the CNE prediction task as a protein–protein interaction (PPI) prediction task. Then, ProNEP predicts the interaction between NLRs and effectors by combining the transfer learning with a bilinear attention network. ProNEP achieves superior performance against state-of-the-art models designed for PPI predictions. Based on ProNEP, we conduct extensive identification of potential CNEs for 91 291 NLRs. With the rapid accumulation of genomic data, we expect that this tool will be widely used to predict CNEs in new species, advancing biology, immunology, and breeding.

Availability and implementation
The ProNEP is available at http://nerrd.cn/#/prediction. The project code is available at https://github.com/QiaoYJYJ/ProNEP.
Discussion on “LEAP: the latent exchangeability prior for borrowing information from historical data” by Ethan M. Alt, Xiuya Chang, Xun Jiang, Qing Liu, May Mo, H. Amy Xia, and Joseph G. Ibrahim
Authors: Scott Darren , Lewin Alex 
Published: September 2024

Abstract
In the following discussion, we describe the various assumptions of exchangeability that have been made in the context of Bayesian borrowing and related models. In this context, we are able to highlight the difficulty of dynamic Bayesian borrowing under the assumption of individuals in the historical data being exchangeable with the current data and thus the strengths and novel features of the latent exchangeability prior. As borrowing methods are popular within clinical trials to augment the control arm, some potential challenges are identified with the application of the approach in this setting.
Use of Linked Administrative Adult Social Care Data for Research: A Scoping Review of Existing UK Studies
Authors: Lugg-Widger Fiona , Sydenham Mia , Oatley Rebecca , Scourfield Jonathan 
Published: September 2024

Abstract
Administrative data provide unique coverage of populations using care and the use of new datasets and advancing digital technologies only contribute to this growing area. There are ongoing limitations in the linkage of administrative datasets, which for adult social care have been exacerbated by inconsistent coding and varied IT systems. The aim of this review was to provide an overview of all studies to date that have used linked adult social care administrative data in the UK. This scoping review included primary quantitative research using individual-level adult social care service or workforce data when linked with at least one other data source. The search strategy was developed systematically and two authors independently screened and reviewed full-texts for inclusion. Fourteen articles were included—a mix of national and local projects. Definitions for the adult social care population ranged, with only four including all ages. One included unpaid carers and one included the domiciliary care workforce. Where described, linkage of datasets was slow, with challenges in the governance and linkage process.
This review demonstrates that administrative data can be a rich source of information for the adult social care sector and linkage can expand its utility and impact.
Organisational Leadership and Service Quality of Child and Adolescent Social Workers: A Hierarchical Linear Modelling Approach
Authors: Zhang Huan , Lin Junwei , Xu Shuge , Wang Yean 
Published: September 2024

Abstract
Enhancing the quality of services provided by child and adolescent social workers is crucial for promoting the healthy development of children and adolescents. However, limited research has integrated both organisational and individual factors into the examination of the influencing factors of social work service quality. This study uses the hierarchical linear model to study how organisational leadership can improve the service quality of child and adolescent social workers through the mediating influence of professional identity. The hypotheses were examined using data from 2,248 child and adolescent social workers in 157 social service organisations collected during the China Social Work Longitudinal Study in 2019. The findings reveal two critical insights: (i) there is a significant correlation between organisational leadership in social service organisations and the service quality provided by child and adolescent social workers and (ii) professional identity appears to play a fully mediating role in this relationship. These findings encourage the boards of social service organisations to implement appropriate measures for reinforcing internal governance, exporting effective leadership and nurturing the professional identity of child and adolescent social workers, thereby elevating the quality of their services.
Glutamine promotes the proliferation of intestinal stem cells via inhibition of TP53-induced glycolysis and apoptosis regulator promoter methylation in burned mice
Authors: Zhang Panyang , Wu Dan , Zha Xule , Su Sen , Zhang Yajuan , Wei Yan , Xia Lin , Fan Shijun , Peng Xi 
Published: September 2024

Abstract

Background
Intestinal stem cells (ISCs) play a pivotal role in maintaining intestinal homeostasis and facilitating the restoration of intestinal mucosal barrier integrity. Glutamine (Gln) is a crucial energy substrate in the intestine, promoting the proliferation of ISCs and mitigating damage to the intestinal mucosal barrier after burn injury. However, the underlying mechanism has not yet been fully elucidated. The objective of this study was to explore the mechanism by which Gln facilitates the proliferation of ISCs.

Methods
A mouse burn model was established to investigate the impact of Gln on intestinal function. Subsequently, crypts were isolated, and changes in TP53-induced glycolysis and apoptosis regulator (TIGAR) expression were assessed using real-time quantitative polymerase chain reaction (RT-qPCR), western blotting, immunohistochemistry, and immunofluorescence. The effects of TIGAR on cell proliferation were validated through CCK-8, EdU, and clonogenicity assays. Furthermore, the effect of TIGAR on Yes-associated protein (YAP) nuclear translocation and ferroptosis was examined by western blotting and immunofluorescence staining. Finally, dot blot analysis and methylation-specific PCR were performed to evaluate the effect of Gln on TIGAR promoter methylation.

Results
The mRNA and protein levels of TIGAR decreased after burn injury, and supplementation with Gln increased the expression of TIGAR. TIGAR accelerates the nuclear translocation of YAP, thereby increasing the proliferation of ISCs. Concurrently, TIGAR promotes the synthesis of nicotinamide adenine dinucleotide phosphate (NADPH) and glutathione to suppress ferroptosis in ISCs. Subsequent investigations demonstrated that Gln inhibits TIGAR promoter methylation by increasing the expression of the demethylase ten-eleven translocation. This change increased TIGAR transcription, increased NADPH synthesis, and reduced oxidative stress, thereby facilitating the restoration of intestinal mucosal barrier integrity post-burn injury.

Conclusions
Our data confirmed the inhibitory effect of Gln on TIGAR promoter methylation, which facilitates YAP translocation into the nucleus and suppresses ferroptosis, ultimately promoting the proliferation of ISCs.