bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reconciling ice core CO2 and land-use change following New World-Old World contact
Authors: King Amy , Bauska Thomas , Brook Edward , Kalk Michael , Nehrbass-Ahles Christoph , Wolff Eric , Strawson Ivo , Rhodes Rachael 
Published: July 2023

Abstract
Ice core records of carbon dioxide (CO2) throughout the last 2000 years provide context for the unprecedented anthropogenic rise in atmospheric CO2 and insights into global carbon cycle dynamics on centennial and multidecadal timescales. Yet the atmospheric history of CO2 remains uncertain in some time intervals. A particular source of debate is the exact timing and magnitude of the decrease in atmospheric CO2 after 1550 CE. Here we present new ice core measurements of CO2 and methane (CH4) in the Skytrain Ice Rise ice core from 1450 to 1700 CE. The measurements, alongside analysis of the effects of gas record smoothing, suggest that a sudden decrease in ice core CO2 around 1610 CE in one widely used record is most likely an artefact of a small number of anomalously low values. Instead, our analysis suggests a more gradual decrease in CO2 of 0.5 ppm per decade between 1516 and 1670 CE, with an inferred land carbon sink of 2.7 PgC per decade. Furthermore, a rapid decrease in CO2 at 1610 CE is incompatible with even the most extreme modelled scenarios for land-use change, whereas our data support scenarios of large-scale reorganization of land use in the Americas following New World-Old World contact.
CNF Encodings of Symmetric Functions
Authors: Emdin Gregory , Kulikov Alexander , Mihajlin Ivan , Slezkin Nikita 
Published: July 2023

Abstract
Many Boolean functions that need to~be encoded as~CNF in~practice, have only exponential size CNF representations. To~avoid this effect, one usually introduces nondeterministic variables. For example, whereas the minimum number of~clauses in a~CNF computing the parity function $x_1\oplus x_2 \oplus \dotsb \oplus x_n$ is~$2^{n-1}$, one can use $n-1$ nondeterministic variables to~get a~CNF encoding with $4n$~clauses. In~this paper, we prove tradeoffs between various parameters (the number of~clauses, the width of~clauses, and the number of~nondeterministic variables) of~CNF encodings of~various symmetric functions. In~particular, we~show that a~folklore way of~encoding parity as~CNF is~provably optimal. We~do this by~using a~tight connection between CNF encodings and depth-3 circuits. This connection shows that CNF encodings is an~interesting computational model for Boolean functions: on~the one hand, it~is routinely used in~practice when translating a~practical computational problem to~a~format acceptable by a~SAT solver, on~the other hand, lower bounds on~the size of~CNF encodings imply depth-3 circuit lower bounds.
CSF α-synuclein seed amplification kinetic profiles are associated with cognitive decline in PD
Authors: Brockmann Kathrin , Lerche Stefanie , Baiardi Simone , Rossi Marcello , Wurster Isabel , Quadalti Corinne , Roeben Benjamin , Mammana Angela , Zimmermann Milan , Hauser Ann-Kathrin , Deuschle Christian , Schulte Claudia , Liepelt-Scarfone Inga , Gasser Thomas , Parchi Piero 
Published: July 2023

Abstract
Seed amplification assays have been implemented in Parkinson’s disease to reveal disease-specific misfolded alpha-synuclein aggregates in biospecimens. While the assays’ qualitative dichotomous seeding response is valuable to stratify and enrich cohorts for alpha-synuclein pathology in general, more quantitative parameters that are associated with clinical dynamics of disease progression and that might potentially serve as exploratory outcome measures in clinical trials targeting alpha-synuclein would add important information. To evaluated whether the seeding kinetic parameters time required to reach the seeding threshold (LAG phase), the peak of fluorescence response (Imax), and area under the curve (AUC) are associated with clinical trajectories, we analyzed LAG, Imax, and AUC in relation to the development of cognitive decline in a longitudinal cohort of 199 people with Parkinson’s disease with positive CSF alpha-synuclein seeding status. Patients were stratified into tertiles based on their individual CSF alpha-synuclein seeding kinetic properties. The effect of the kinetic parameters on longitudinal development of cognitive impairment was analyzed by Kaplan-Meier survival curves and Cox-Regression. Patients with a higher number of positive seeding replicated and tertile groups of shorter LAG, higher Imax, and higher AUC showed a higher prevalence of and a shorter duration until cognitive impairment longitudinally. Prevalence of patients carrying a GBA mutation was higher in the tertile groups of short LAG phase and high AUC. We conclude that a more prominent alpha-synuclein seeding kinetic profile translates into a more rapid development of cognitive decline.
Association of Antibiotic Exposure with Residual Cancer Burden and Pathologic Complete Response in Patients with HER2-negative stage II or III breast cancer Treated with Neoadjuvant Pembrolizumab in the ISPY-2 Trial
Authors: Kulkarni Amit , Jain Aditya , Jewett Patricia , Desai Nidhi , Veer Laura Van 'T , Hirst Gillian , Yee Douglas , Blaes Anne 
Published: July 2023

Abstract
Antibiotic exposure during immunotherapy (IO) has been shown to negatively affect clinical outcomes in various cancer types. The aim of this study was to evaluate whether antibiotic exposure during neoadjuvant pembrolizumab in the pembrolizumab-4 arm of I-SPY2 clinical trial patients impacted residual cancer burden (RCB) and pathologic complete response (pCR). We show that concurrent antibiotic exposure during neoadjuvant pembrolizumab in HER2-negative early-stage BC is associated with higher RCB and lower pCR rates.
Enhanced and Tuneable Ferromagnetism in CVD-Synthesized Metasurface Carbon Films
Authors: Chaiyachad Sujinda , Kaeokhamchan Yattiphong , Moontang Areeya , Chuewangkam Nattapong , Pinitsoontorn Supree , Janphuang Pattanaphong , Meevasana Worawat 
Published: July 2023

Abstract
Here, metasurface magnetic carbon films synthesized via chemical vapour deposition (CVD) by using adamantane as a precursor and electron beam lithography (EBL) exhibited tuneable magnetic properties. The magnetic properties of carbon films were previously reported to occur from dangling bonds[1]. In this study, we observed a significant increase in saturation magnetization compared to the baseline film by controlling the array size of the metasurface film. Magnetic force microscopy (MFM) measurements confirmed the increasing saturation magnetization of the metasurface film. Magnetization originated from surface dangling bonds; smaller film sizes resulted in higher magnetization due to increased surface area. Furthermore, the saturation magnetization of the CVD carbon film could be tuned by controlling the humidity, and its prediction could be achieved through the utilization of the Raman technique. These findings highlight the potential of metasurface magnetic carbon films for developing tuneable magnetic microscale devices in areas, such as data storage, spintronics, and sensing.
Mycofiltration of aqueous iron (III) and imidacloprid solutions, and the effects of the filtrates on selected biomarkers of the freshwater snail Helisoma duryi
Authors: Mnkandla Sanele Michelle , Mosoabisane Mafereka , Basopo Norah , Otomo Patricks 
Published: July 2023

Abstract
A mycofilter made of Pleurotus ostreatus was used for the removal of iron (III) and imidacloprid from aqueous solutions. Batch mycofiltration, at a dosage of 1g of mycofilter per 50 ml, was performed on iron (III) solutions of different concentrations (0.99, 10.7, 22.9, and 27.72 mg/L) and pH (3.3, 7 and 11). For column mycofiltration, the mycofilter was packed into pyrex columns (3.3 x 15 cm) to desired bed heights. Iron (III) and imidacloprid solutions of 18.99 mg/L and 234.70 ng/L, respectively, were filtered at a constant flow rate. Thereafter, Helisoma duryi snails were exposed for 96 hours to the respective filtrates, and their catalase and acetylcholinesterase activities were assessed. Batch mycofiltration showed iron (III) removal rates as high as 85%. Column mycofiltration showed removal rates of 94 and 31% for iron (III) and imidacloprid, respectively. Catalase activity was significantly reduced (p < 0.05) in the snails exposed to iron (III) or imidacloprid filtrates, compared to the snails exposed to the non-mycofiltered media. A significantly higher acetylcholinesterase activity was induced by iron (III) filtrates in comparison with the non-mycofiltered media (p < 0.05). There were no significant differences in acetylcholinesterase activity (p > 0.05) in the snails exposed to mycofiltered and non-mycofiltered imidacloprid media. Mycofilter characterisation using Fourier Transform Infrared Spectrophotometry revealed significant changes in transmittance intensity in the mycofilters used for the iron (III) vs the ones used for the imidacloprid solutions. Mycofiltration was found to improve water quality although iron (III) was removed more effectively than imidacloprid.
Understanding the relationship between the frequency of HbA1c monitoring, HbA1c changes over time, and the achievement of targets: a retrospective cohort study
Authors: Mukonda Elton , Westhuizen Diederick J van der , Dave Joel A , Cleary Susan , Hannan Luke , Lesosky Maia , Rusch Jody A 
Published: July 2023

Abstract

Background
The goal of post-diagnosis diabetes management is the achievement and maintenance of glycaemic control. Most clinical practice guidelines recommend 3–6 monthly HbA1c monitoring. Despite this guidance, there are few data supporting the impact of monitoring frequency on clinical outcomes, particularly from low- and middle-income country settings. This study examined associations between adherence to monitoring recommendations and the achievement of HbA1c targets, and HbA1c changes, over time in a South African cohort.
Research Design and Methods:
The study utilised routinely collected HbA1c test data on patients with diabetes aged ≥ 18 years in the Western and Northern Cape between 2015 and 2020 to examine the relationship between mean change in HbA1c values and the duration between consecutive HbA1c tests (retest interval). The monitoring adherence rate, which represents the proportion of intervals between consecutive tests that met South Africa’s guideline recommendations, was calculated for each patient. Multistate modelling and linear mixed-effects modelling were then used to examine the effect of monitoring adherence on the achievement of glycemic control targets and longitudinal changes in HbA1c.
Results
The 132,859 diabetes patients with repeat tests had a median of three HbA1c test requests, a median follow-up time of 2.3 years and a median retest interval of 10.3 months. A retest interval 2–4 months maximised the downward trajectory in HbA1c, while individuals with low adherence to the monitoring guidelines were the least likely to achieve glycaemic control in one year. Moreover, patients with low monitoring adherence had higher mean HbA1c levels compared to patients with moderate or high monitoring adherence.
Conclusions
The results illustrated the importance of adherence to monitoring recommendations as adherent patients had better glycaemic control and lower mean HbA1c levels over time.
Forecasting patient census at a university hospital using the Prophet model
Authors: Rudas Akos , Weil Drew J. , Jahnke Scott L. , Chiang Jeffrey N. 
Published: July 2023

Abstract
The widespread emergence of machine learning-based solutions provides most fields with a range of available tools. Utilizing these tools requires resources unavailable to many institutions. Off-the-shelf methods could fill this gap, as they usually require little implementational effort, and are easily customizable to fit a wide range of tasks. To assess how easily off-the-shelf methods can be adapted to clinical tasks so that clinicians would be provided actionable predictions, we adopted the time series forecasting model Prophet to forecast patient census time series 3 days from the day of prediction. The underlying time series used for model training consisted of day-to-day census data collected in 2021 and 2022. Performance of the model had been evaluated daily against a baseline and the manual predictions of a business subject matter expert. The Prophet model outperformed the other methods and provided accurate predictions for several time series; it predicted adult intensive care unit census, overall adult census, and emergency department census with 2.1%, 3.2%, and 7.6% mean absolute percentage error, respectively. To acquire these predictions, necessary steps were installing Python, the library containing Prophet, and writing a script around it to train it on the time series of interest and generate actual predictions. The model has been operationalized in a large academic hospital. We conclude that medical facilities which accumulate time series data (patient census, resources, etc.) can benefit from advances in machine learning, or more specifically time series forecasting by adopting off-the-shelf methods to generate actionable predictions to enhance patient care.
Broadband Thermal Imaging using Meta-Optics
Authors: Majumdar Arka , Huang Luocheng , Han Zheyi , Wirth-Singh Anna , Saragadam Vishwanath , Mukherjee Saswata , Fröch Johannes E , Rollag Joshua , Gibson Ricky , Hendrickson Joshua , Hon Philip , Kigner Orrin , Koppens Zachary , Böhringer Karl , Veeraraghavan Ashok 
Published: July 2023

Abstract
Subwavelength diffractive optics known as meta-optics have demonstrated the potential to significantly miniaturize imaging systems. However, despite impressive demonstrations, most meta-optical imaging systems suffer from strong chromatic aberrations, limiting their utilities. Here, we employ inverse-design to create broadband metaoptics operating in the long-wave infrared (LWIR) regime (8-12 μm). Via a deep-learning assisted multi-scale differentiable framework that links meta-atoms to the phase, we maximize the wavelength-averaged volume under the modulation transfer functon(MTF) of the metaoptics. Our design framework merges local phase-engineering via metaatoms and global engineering of the scatterer within a single pipeline. We corroborate our design by fabricating and experimentally characterizing all-silicon LWIR meta-optics. Our engineered meta-optic is complemented by a simple computational backend that dramatically improves the quality of the captured image. We experimentally demonstrate a six-fold improvement of the wavelength-averaged Strehl ratio over the traditional hyperboloid metalens for broadband imaging.
Association between hyperthyroidism, subacute thyroiditis and twenty common cancers: A bidirectional mendelian randomization study
Authors: Wang Maoyu , Li Zhizhou , Wang Ziwei , Ying Yidie , Hua Meimian , Wang Huiqing , Zeng Shuxiong , Zhang Zhensheng , Xu Chuanliang 
Published: July 2023

Abstract
Objective:The epidemiological evidence regarding the causal relationship between hyperthyroidism, subacute thyroiditis (SAT), and tumors remains inconclusive. Therefore, we conducted a two-sample bidirectional Mendelian randomization (MR) study to establish the causal relationship between these conditions.
Methods: We conducted a bi-directional MR study using publicly available GWAS summary statistics to explore the causality between genetically predicted hyperthyroidism, SAT and the risk of 20 common cancers. The analysis was performed using inverse-variance weighted (IVW), MR-Egger, weighted median, simple mode, and weighted mode methods. The primary results were based on the IVW (random effects), followed by sensitivity analysis. Furthermore, maximum likelihood, penalized weighted median and IVW (fixed effects) were used to confirm the robustness of the findings.
Results:IVW analysis revealed a significant positive causal association between hyperthyroidism and breast cancer (OR = 2.20E+05, 95% CI: 7.7733–6.23E+09, P = 0.0187), ovarian cancer (OR =1.0949, 95% CI: 1.0250–1.1696, P = 0.0071), thyroid cancer (OR =3.05E+11, 95% CI: 1.06E+01–8.84E+21, P = 0.0314), and colorectal cancer (OR =1.1345, 95% CI: 1.0293–1.2505, P = 0.0110) ; while hyperthyroidism had an inverse association with bladder cancer (OR =0.9446, 95% CI: 0.9017–0.9896, P = 0.0164), prostate cancer (OR =0.6174, 95% CI: 0.4879–0.7813, P = 5.97E-05), liver and bile duct cancer (OR =0.9723, 95% CI: 0.9540–0.9910, P = 0.0038), brain cancer (OR =0.9699, 95% CI: 0.9460–0.9945, P = 0.0166), and malignant neoplasm of male genital organs (OR =0.8593, 95% CI: 0.7868–0.9385, P = 0.0007). Furthermore, the IVW analysis supported a positive causal relationship between SAT and endometrial cancer (OR =1.031, 95% CI: 1.0032–1.0596, P = 0.0288), while SAT had an inverse association with kidney cancer (OR =0.9015, 95% CI: 0.8255–0.9844, P = 0.0209) and thyroid cancer (OR =0.9143, 95% CI: 0.8390–0.9962, P =0.0407). However, we only observed an inverse association between malignant neoplasm of male genital organs and SAT in the reverse MR analyses.
Conclusions: The current investigation offers genetic evidence that hyperthyroidism could potentially elevate the risk of developing breast, ovarian, thyroid, and colorectal cancers. Likewise, SAT is identified as a possible risk factor for endometrial cancer. In light of these findings, further studies are necessary to uncover the underlying mechanisms that establish causal links between hyperthyroidism, SAT, and malignancies.
On Lie triple centralizers of von Neumann algebras
Authors: Fadaee Behrooz , Ghahramani Hoger 
Published: July 2023

Abstract
‎Let U be a von Neumann algebra endowed with the Lie product [A,B]=AB-BA (A,B in U)‎. ‎In this article‎, ‎we consider the subsequent condition on an additive mapping \phi on the von Neumann algebra U with a suitable projection P in U‎:
‎\phi([ [A‎ , ‎B]‎ , ‎C ]) = [ [\phi(A)‎, ‎B]‎ , ‎C ] = [ [ A‎, ‎\phi (B)‎ ] , ‎C ] ‎
‎for all A,B‎, ‎C in U with AB=P and we show that \phi(A)=WA+\xi(A) for all A in U$, ‎where W in Z(U)‎, ‎and \xi: U \to Z(U) (Z(U)$ is the center of U) is an additive map in which \xi([[A‎, ‎B ]‎, ‎C] )=0 for any A,B,C in U with AB=P‎. ‎We also give some results of the conclusion‎.
Decellularized extracellular matrix tissues from human gastric cancer tissues as a three-dimensional model for cancer cell growth and drug treatments
Authors: Du Hua , Zhang Wenqi , Shi Yingxu , Sun Wei , Liu Gang , Liu Honggang 
Published: July 2023

Abstract
Tissue engineering strategies based on three-dimensional (3D) structures and components of decellularized extracellular matrix (dECM) have been used in cancer research and regenerative research. With dECM tissues and a 3D culture system not being applied to gastric cancer tissue, there is a great need for a therapeutic approach targeting human gastric cancer tissue that will benefit the in vitro optimization and development of chemotherapy drugs. In our study, we aimed to analyze the effect of dECM tissues on the proliferation and epithelial-mesenchymal transition (EMT) process of MKN-45 cells following recellularization with MKN-45 cells. The potential effect of dECM tissues on in vivo cancer progression was confirmed by in vivo xenograft assay after subcutaneous transplantation. In addition, the effect of dECM tissues on the transcriptomic profiles of MKN-45 cells was analyzed by RNA-seq. Based on the enhanced EMT process of MKN-45 cells, it was significantly increased in the 3D culture system with increased expression levels of ABCB1, ABCG2, LRP, MRP1, and MDR1 during the culture process. The up-regulation expression levels of CK8 and Villin in xenograft tissues also confirmed the promising effect of dECM tissues on in vivo cancer progression. Interestingly, the dECM tissues significantly improved the drug resistance of MKN-45 cells to 5-Fu treatments. The data of RNA-seq further confirmed that the potential effect of dECM tissues on the transcriptomic profiles of MKN-45 cells was positively associated with cytokine-cytokine receptor interaction, synaptic vesicle cycle, and MAPK signaling pathway. Given the biological activities preserved in dECM tissues, we believe that the approaches for the decellularization of gastric cancer tissues and 3D culture may bring the field one step closer to developing a therapy to address these unmet clinical needs.
Iaso: Enhancing Syntax Error Correction using Deep Learning Techniques
Authors: Li Wei , Wong Weng-Fai 
Published: July 2023

Abstract
Syntax errors can significantly impede students' progress and comprehension of programming concepts. AI-generated programs are also prone to syntax bugs, highlighting the importance of effectively addressing and resolving such errors. This paper presents Iaso, an automated program repair tool designed specifically to rectify syntax errors in student and AI-generated C programs. Iaso consists of three components: a syntax-based C program generator, an error localization model, and an ensemble code corrector. The program generator is trained on a seed dataset to generate complete and compilable C programs, which are then used to train the corrector. The corrector, trained on a combination of the seed dataset and a synthetic dataset, adopts an ensemble approach to gather fixes from multiple correctors trained on different datasets. During the repair process, Iaso's error localization model utilizes information from the deep learning model, raw code, and compiler messages to precisely identify the required repairs. To evaluate our method, we compare it against two automated program correctors: DrRepair and TransRepair. Iaso demonstrates notable performance, achieving a full repair rate of 78.8\% (+4.2\%) on the Deepfix test set and 91.0\% (+6.8\%) on the Tracer test set, generating over 1,300,000 erroneous C programs. Compared to the large language model PaLM, our strategy showcases a significant 6\% improvement in accuracy, considering the unlimited edit size used by PaLM. Furthermore, when compared to the state-of-the-art dialogue model ChatGPT, our method exhibits only a slight 1.4\% deviation while utilizing significantly fewer resources.
Dynamics and stability of ultrashort laser in Kerr nonlinear optical materials: competing effects between K-photon absorption and the higher-order correction term to the nonlinear refractive index
Authors: Nteutse Peguy Kameni , Geletu Abebe 
Published: July 2023

Abstract

Ultrashort laser micromachining is a versatile technology used in modern industries for manipulating transparent materials with precision. In these applications, laser systems are customized for specific power levels and wavelengths, requiring an understanding of different laser operation regimes to optimize their utilization, as well as technological advancement. This study proposes a theoretical analysis to investigate the impact of the competition between multiphoton absorption and the higher order correction term to the nonlinear refractive index on laser propagation and stability in Kerr nonlinear transparent materials. The study focuses on the mathematical model that includes a complex nonlinear K-order Ginzburg-Landau equation coupled to the Drude equation that captures the growth rate of the electron plasma density. Through global stability investigation, a diverse range of fixed points is revealed in the amplitude-frequency plane. An examination of the steady-state stability of these fixed point solutions reveals that, depending on the sign of the spatial noise, the combination of the multipho-ton absorption process with the higher-order correction term to the nonlinear refractive index can be detrimental or beneficial to the continuous-wave regime. According to numerical simulations of the mathematical model in the fully non-linear regime, we found that low values of the higher-order correction term to the nonlinear refractive index, denoted as M0 promote stable pulse trains patterns, mainly when the multiphoton absorption rate is high, whereas high values of M0 1 induced a train of anharmonic wave patterns as the multiphoton absorption rate gets stronger.