bluuebunny/crossref_metadata_2025_split huggingface dataset:
Inferring router ownership based on the classification of intra- and inter-domain links
Authors: Liu Yan , Zhao Yi , Guo Xiaoyu , Liu Lian 
Published: March 2023

AbstractResearch on router ownership inference is central to many Internet studies, such as network failure diagnosis, network boundary identification, network resilience assessment, and inter-domain congestion detection. The existing router ownership inference method bdrmapIT has relatively few constraints on routers at the end of traceroute paths, resulting in some inference errors. In this paper, a router ownership inference method based on the classification of intra- and inter-domain links is proposed. In this method, the differentiating Internet Protocol (IP) address vector distance feature, the autonomous system relationship feature of the IP link, and the fan-in and fan-out features are designed to support the discrimination of IP link types. The use of additional information derived from the link type enriches the basis for router ownership inference and improves the accuracy of the inference result. Experimental results show that the accuracy reaches 96.4% and 94.6% on the two verification sets, respectively, which is 3.2–11.2% better than the existing typical methods.
Prediction of breast cancer using blood microbiome and identification of foods for breast cancer prevention
Authors: An Jeongshin , Yang Jinho , Kwon Hyungju , Lim Woosung , Kim Yoon-Keun , Moon Byung-In 
Published: March 2023

AbstractThe incidence of breast cancer (BC) is increasing in South Korea, and diet is closely related to the high prevalence of BC. The microbiome directly reflects eating habits. In this study, a diagnostic algorithm was developed by analyzing the microbiome patterns of BC. Blood samples were collected from 96 patients with BC and 192 healthy controls. Bacterial extracellular vesicles (EVs) were collected from each blood sample, and next-generation sequencing (NGS) of bacterial EVs was performed. Microbiome analysis of patients with BC and healthy controls identified significantly higher bacterial abundances using EVs in each group and confirmed the receiver operating characteristic (ROC) curves. Using this algorithm, animal experiments were performed to determine which foods affect EV composition. Compared to BC and healthy controls, statistically significant bacterial EVs were selected from both groups, and a receiver operating characteristic (ROC) curve was drawn with a sensitivity of 96.4%, specificity of 100%, and accuracy of 99.6% based on the machine learning method. This algorithm is expected to be applicable to medical practice, such as in health checkup centers. In addition, the results obtained from animal experiments are expected to select and apply foods that have a positive effect on patients with BC.
Nanocomposite formulation for a sustained release of free drug and drug-loaded responsive nanoparticles: an approach for a local therapy of glioblastoma multiforme
Authors: Erthal Luiza C. S. , Shi Yang , Sweeney Kieron J. , Gobbo Oliviero L. , Ruiz-Hernandez Eduardo 
Published: March 2023

AbstractMalignant gliomas are a type of primary brain tumour that originates in glial cells. Among them, glioblastoma multiforme (GBM) is the most common and the most aggressive brain tumour in adults, classified as grade IV by the World Health Organization. The standard care for GBM, known as the Stupp protocol includes surgical resection followed by oral chemotherapy with temozolomide (TMZ). This treatment option provides a median survival prognosis of only 16–18 months to patients mainly due to tumour recurrence. Therefore, enhanced treatment options are urgently needed for this disease. Here we show the development, characterization, and in vitro and in vivo evaluation of a new composite material for local therapy of GBM post-surgery. We developed responsive nanoparticles that were loaded with paclitaxel (PTX), and that showed penetration in 3D spheroids and cell internalization. These nanoparticles were found to be cytotoxic in 2D (U-87 cells) and 3D (U-87 spheroids) models of GBM. The incorporation of these nanoparticles into a hydrogel facilitates their sustained release in time. Moreover, the formulation of this hydrogel containing PTX-loaded responsive nanoparticles and free TMZ was able to delay tumour recurrence in vivo after resection surgery. Therefore, our formulation represents a promising approach to develop combined local therapies against GBM using injectable hydrogels containing nanoparticles.
Establishing the contribution of active histone methylation marks to the aging transcriptional landscape of Drosophila photoreceptors
Authors: Jauregui-Lozano Juan , McGovern Sarah E. , Bakhle Kimaya M. , Hagins Arrianna C. , Weake Vikki M. 
Published: March 2023

AbstractStudies in multiple organisms have shown that aging is accompanied by several molecular phenotypes that include dysregulation of chromatin. Since chromatin regulates DNA-based processes such as transcription, alterations in chromatin modifications could impact the transcriptome and function of aging cells. In flies, as in mammals, the aging eye undergoes changes in gene expression that correlate with declining visual function and increased risk of retinal degeneration. However, the causes of these transcriptome changes are poorly understood. Here, we profiled chromatin marks associated with active transcription in the aging Drosophila eye to understand how chromatin modulates transcriptional outputs. We found that both H3K4me3 and H3K36me3 globally decrease across all actively expressed genes with age. However, we found no correlation with changes in differential gene expression. Downregulation of the H3K36me3 methyltransferase Set2 in young photoreceptors revealed significant changes in splicing events that overlapped significantly with those observed in aging photoreceptors. These overlapping splicing events impacted multiple genes involved in phototransduction and neuronal function. Since proper splicing is essential for visual behavior, and because aging Drosophila undergo a decrease in visual function, our data suggest that H3K36me3 could play a role in maintaining visual function in the aging eye through regulating alternative splicing.
An immune indicator based on BTK and DPEP2 identifies hot and cold tumors and clinical treatment outcomes in lung adenocarcinoma
Authors: Han Tao , Liu Yafeng , Wu Jing , Bai Ying , Zhou Jiawei , Hu Chunxiao , Zhang Wenting , Guo Jianqiang , Wang Qingsen , Hu Dong 
Published: March 2023

AbstractIn lung adenocarcinoma (LUAD), immune heterogeneity of hot and cold tumors has been recognized as one of the major factors affecting immunotherapy and other common treatments. However, there is still a lack of biomarkers that can effectively identify the immunophenotype of cold and hot tumors. First, the immune signatures were obtained based on literature mining, including macrophage/monocyte, IFN-γ response, TGF-β response, IL12 response, lymphocyte activation, and ECM/Dve/immune response. Subsequently, LUAD patients were further clustered into different immune phenotypes based on these immune signatures. Next, the key genes related to the immune phenotypes were screened by WGCNA analysis, univariate analysis, and lasso-cox analysis, and the risk signature was established via the key genes. In additional, we compared the clinicopathological characteristics, drug sensitivity, the abundance of immune infiltration, and the efficacy of immunotherapy and commonly used therapies between patients in the high- and low-risk groups in LUAD. LUAD patients were divided into immune hot phenotype and immune cold phenotype groups. The clinical presentation showed that patients with the immune hot phenotype had higher immunoactivity (including higher MHC, CYT, immune, stromal, ESTIMATE scores, higher abundance of immune cell infiltration, higher abundance of TIL, and enrichment of immune-enriched subtypes) and better survival outcomes than those with the immune cold phenotype. Subsequently, WGCNA analysis, univariate analysis, and lasso-cox analysis identified the genes highly associated with the immune phenotype: BTK and DPEP2. The risk signature, consisting of BTK and DPEP2, is highly correlated with the immune phenotype. High-risk scores were enriched in patients with immune cold phenotype and low-risk scores were enriched in patients with immune hot phenotype. Compared to the high-risk group, the low-risk group had better clinical performance, higher drug sensitivity, and a higher degree of immunoactivity, as well as better efficacy in receiving immunotherapy and common adjuvant therapy. This study developed an immune indicator consisting of BTK and DPEP2 based on the heterogeneity of hot and cold Immunophenotypes of the tumor microenvironment. This indicator has good efficacy in predicting prognosis and assessing the efficacy of immunotherapy, chemotherapy, and radiotherapy. It has the potential to facilitate personalized and precise treatment of LUAD in the future.
A proficiency assessment of integrating machine learning (ML) schemes on Lahore water ensemble
Authors: Shahid Nazish 
Published: March 2023

AbstractA synthesis of statistical inference and machine learning (ML) tools has been employed to establish a comprehensive insight of a coarse data. Water components’ data for 16 central distributing locations of Lahore, the capital of second most populated province of Pakistan, has been analyzed to gauge current water stature of the city. Moreover, a classification of surplus-response variables through tolerance manipulation was incorporated to debrief dimension aspect of the data. By the same token, the influence of supererogatory variables’ renouncement through identification of clustering movement of constituents is inquired. The approach of building a spectrum of colluding results through application of comparable methods has been experimented. To test the propriety of each statistical method prior to its execution on a huge data, a faction of ML schemes have been proposed. The supervised learning tools pca, factoran and clusterdata were implemented to establish an elemental character of water at elected locations. A location ‘LAH-13’ was highlighted for containing an out of normal range Total Dissolved Solids (TDS) concentration in the water. The classification of lower and higher variability parameters carried out by Sample Mean (XBAR) control identified a set of least correlated variables pH, As, Total Coliforms and E. Coli. The analysis provided four locations LAH-06, LAH-10, LAH-13 and LAH-14 for extreme concentration propensity. An execution of factoran demonstrated that specific tolerance of independent variability ‘0.005’ could be employed to reduce dimension of a system without loss of fundamental data information. A higher value of cophenetic coefficient, c = 0.9582 provided the validation for an accurate cluster division of similar characteristics’ variables. The current approach of mutually validating ML and SA (statistical analysis) schemes will assist in preparing the groundwork for state of the art analysis (SOTA) analysis. The advantage of our approach can be examined through the fact that the related SOTA will further refine the predictive precision between two comparable methods, unlike the SOTA analysis between two random ML methods. Conclusively, this study featured the locations LAH-03, LAH-06, LAH-12, LAH-13, LAH-14 and LAH-15 with compromised water quality in the region.
Quantum architecture search via truly proximal policy optimization
Authors: Zhu Xianchao , Hou Xiaokai 
Published: March 2023

AbstractQuantum Architecture Search (QAS) is a process of voluntarily designing quantum circuit architectures using intelligent algorithms. Recently, Kuo et al. (Quantum architecture search via deep
reinforcement learning. arXiv preprint arXiv:2104.07715, 2021) proposed a deep reinforcement learning-based QAS (QAS-PPO) method, which used the Proximal Policy Optimization (PPO) algorithm to automatically generate the quantum circuit without any expert knowledge in physics. However, QAS-PPO can neither strictly limit the probability ratio between old and new policies nor enforce well-defined trust domain constraints, resulting in poor performance. In this paper, we present a new deep reinforcement learning-based QAS method, called Trust Region-based PPO with Rollback for QAS (QAS-TR-PPO-RB), to automatically build the quantum gates sequence from the density matrix only. Specifically, inspired by the research work of Wang, we employ an improved clipping function to implement the rollback behavior to limit the probability ratio between the new strategy and the old strategy. In addition, we use the triggering condition of the clipping based on the trust domain to optimize the policy by restricting the policy within the trust domain, which leads to guaranteed monotone improvement. Experiments on several multi-qubit circuits demonstrate that our presented method achieves better policy performance and lower algorithm running time than the original deep reinforcement learning-based QAS method.
Optimization of Cd (II) removal from aqueous solution by natural hydroxyapatite/bentonite composite using response surface methodology
Authors: Desalegn Yiene Molla , Bekele Endrias Adane , Olu Femi Emmanuel 
Published: March 2023

AbstractToxic cadmium (Cd) was removed from water using eggshell-based hydroxyapatite (HAp) grafted bentonite (HAp/bentonite) composite through a straightforward chemical synthesis route. The as-prepared adsorbents were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and Brunauer–Emmett–Teller analysis (BET). Optimization of the initial adsorbate concentration, adsorbent dosage, pH, and contact time—all of which affect the adsorption process—was performed using the central composite design (CCD) of the response surface methodology (RSM). 99.3 percent adsorptive removal efficiency was observed at an initial concentration of 61.58 mg/L of Cd (II), with an adsorbent dosage of 1.58 g, a solution pH of 5.88, and a contact time of 49.63 min. The analysis of variance (ANOVA) was performed, and the multiple correlation coefficient (R2) was found to be 0.9915 which confirms the significance of the predicted model. The Langmuir isotherm model best represented the adsorption isotherm data, which also predicted a maximum sorption capacity of 125.47 mg/g. The kinetic data were best described by the pseudo-second order model.
Extreme mechanical tunability in suspended MoS2 resonator controlled by Joule heating
Authors: Chiout Anis , Brochard-Richard Cléophanie , Marty Laetitia , Bendiab Nedjma , Zhao Meng-Qiang , Johnson A. T. Charlie , Oehler Fabrice , Ouerghi Abdelkarim , Chaste Julien 
Published: March 2023

AbstractNanomechanical resonators are built into phones, as filters or accelerometers, but they lack a knob to effectively tune the frequency at the nanoscale when it’s easy to tune on an octave the tone of a classical musical instrument like a guitar string. Moreover, the control of deformation in nanomaterials, as two-dimensional (2D) materials, to tailor their electronic properties, i.e., straintronic, opens up avenues for applications in force detection, bolometry or quantum emitters. An accurate control of the deformation within these materials is thus necessary to fully exploit their potential. The precise study of deformations in 2D materials involves measurements of vibration modes and nanomechanics. By using a suspended MoS2 membrane heated by the Joule effect, we induce a strong softening of the mechanical resonance frequency as a function of the electrothermal heating, over one octave. A simple electrical tension is used to modulate the thermal mechanical tuning. Its amplitude is very large, greater than 100% modulation for one volt, compared to other approaches on 2D or 1D materials and, moreover, a very wide frequency range is accessible. Finally, we have related a photo-induced softening of the membrane over very long times with the current measurements and a photothermal effect.
Unconventional conductivity increase in multilayer black phosphorus
Authors: Koleśnik-Gray Maria , Meingast Laura , Siebert Martin , Unbehaun Tim , Huf Tobias , Ellrott Günter , Abellán Gonzalo , Wild Stefan , Lloret Vicent , Mundloch Udo , Schwarz Julian , Niebauer Michael , Szabo Maximilian , Rommel Mathias , Hutzler Andreas , Hauke Frank , Hirsch Andreas , Krstić Vojislav 
Published: March 2023

AbstractMultilayers of so-called 2D van der Waals materials have gained considerable attention as active components of next-generation electronic and optoelectronic technologies, with semiconducting black phosphorus (BP) regarded as one of the most promising systems. The applicability and performance limits of BP in both stand-alone and heterostructure-based multilayer devices are determined by individual flake charge transport properties, which synergistically depend on the number of layers and the strength of interlayer coupling between those. In this work, we study the DC electrical transport characteristics of high-quality BP field-effect devices within a wide range of flake thicknesses at room temperature. The experimental data show a non-trivial increase in conductivity and hole density with a reduced number of layers while maintaining constant field-effect mobility due to the prevalence of electron–phonon scattering. Based on the solution of the 1D Schrödinger–Poisson equation, we find that the observed phenomena are a direct consequence of non-negligible interlayer coupling, which in turn causes a local redistribution of free charge carriers towards the central layers. Our data show that due to the electrostatic conditions at the flake surfaces, a naturally protected 2D hole gas can be encapsulated in flakes as high as 10 nm, which preserves the bulk-like bandgap and effective carrier masses due to the electrostatic environment.
Understanding the impact of heavy ions and tailoring the optical properties of large-area monolayer WS2 using focused ion beam
Authors: Sarcan Fahrettin , Fairbairn Nicola J. , Zotev Panaiot , Severs-Millard Toby , Gillard Daniel J. , Wang Xiaochen , Conran Ben , Heuken Michael , Erol Ayse , Tartakovskii Alexander I. , Krauss Thomas F. , Hedley Gordon J. , Wang Yue 
Published: March 2023

AbstractFocused ion beam (FIB) is an effective tool for precise nanoscale fabrication. It has recently been employed to tailor defect engineering in functional nanomaterials such as two-dimensional transition metal dichalcogenides (TMDCs), providing desirable properties in TMDC-based optoelectronic devices. However, the damage caused by the FIB irradiation and milling process to these delicate, atomically thin materials, especially in extended areas beyond the FIB target, has not yet been fully characterised. Understanding the correlation between lateral ion beam effects and optical properties of 2D TMDCs is crucial in designing and fabricating high-performance optoelectronic devices. In this work, we investigate lateral damage in large-area monolayer WS2 caused by the gallium focused ion beam milling process. Three distinct zones away from the milling location are identified and characterised via steady-state photoluminescence (PL) and Raman spectroscopy. The emission in these three zones have different wavelengths and decay lifetimes. An unexpected bright ring-shaped emission around the milled location has also been revealed by time-resolved PL spectroscopy with high spatial resolution. Our findings open up new avenues for tailoring the optical properties of TMDCs by charge and defect engineering via focused ion beam lithography. Furthermore, our study provides evidence that while some localised damage is inevitable, distant destruction can be eliminated by reducing the ion beam current. It paves the way for the use of FIB to create nanostructures in 2D TMDCs, as well as the design and realisation of optoelectrical devices on a wafer scale.
Graphene/MoS2/SiOx memristive synapses for linear weight update
Authors: Krishnaprasad Adithi , Dev Durjoy , Shawkat Mashiyat Sumaiya , Martinez-Martinez Ricardo , Islam Molla Manjurul , Chung Hee-Suk , Bae Tae-Sung , Jung Yeonwoong , Roy Tania 
Published: March 2023

AbstractMemristors for neuromorphic computing have gained prominence over the years for implementing synapses and neurons due to their nano-scale footprint and reduced complexity. Several demonstrations show two-dimensional (2D) materials as a promising platform for the realization of transparent, flexible, ultra-thin memristive synapses. However, unsupervised learning in a spiking neural network (SNN) facilitated by linearity and symmetry in synaptic weight update has not been explored thoroughly using the 2D materials platform. Here, we demonstrate that graphene/MoS2/SiOx/Ni synapses exhibit ideal linearity and symmetry when subjected to identical input pulses, which is essential for their role in online training of neural networks. The linearity in weight update holds for a range of pulse width, amplitude and number of applied pulses. Our work illustrates that the mechanism of switching in MoS2-based synapses is through conductive filaments governed by Poole-Frenkel emission. We demonstrate that the graphene/MoS2/SiOx/Ni synapses, when integrated with a MoS2-based leaky integrate-and-fire neuron, can control the spiking of the neuron efficiently. This work establishes 2D MoS2 as a viable platform for all-memristive SNNs.
Japanese urban household carbon footprints during early-stage COVID-19 pandemic were consistent with those over the past decade
Authors: Long Yin , Yoshida Yoshikuni , Jiang Yida , Huang Liqiao , Wang Wentao , Mi Zhifu , Shigetomi Yosuke , Kanemoto Keiichiro 
Published: March 2023

AbstractAs urbanization accelerates worldwide, substantial energy and services are required to meet the demand from cities, making cities major contributors to adverse environmental consequences. To bridge the knowledge gap in the absence of fine-grained city-level climate protection measures due to data availability and accuracy, this study provides a detailed carbon emission inventory for analyzing the monthly fluctuations based on citizens’ daily consumption behaviors. Here, carbon emissions embodied in approximately 500 household consumption items were calculated in 47 prefectural-level cities in Japan from 2011 to June 2021. We analyzed the results considering the regional, seasonal, demand, and emission way-specific aspects, and compared the emission before and during the COVID-19 pandemic. Notably, the carbon footprints during the pandemic were consistent with the previous level despite downtrends in specific categories. This study provides an example of utilizing city-level emission data to improve household green consumption behavior as references for enriching city-level decarbonization paths.
Enabling connections between a multi-country urban research programme and the practices of an African urban research centre
Authors: Tucker Andrew 
Published: March 2023

AbstractSignificant interest exists within urban scholarship regarding both the need to explore diverse urban situated knowledge while enabling effective forms of global comparison, and the place and utility of new urban science approaches. This article considers such interests in relation to the implementation of a multi-country urban research programme and its interface with the pre-existing interests and methodological practices of an African urban research centre. It suggests, when partners engage dialectically, large-scale research programmes may speak to and help offer new perspectives on local realities as much as local realities may help enrich the frameworks of international large-scale research programmes.