bluuebunny/crossref_metadata_2025 huggingface dataset:
On-treatment immune prognostic score for patients with relapsed and/or metastatic head and neck squamous cell carcinoma treated with immunotherapy
Authors: Nenclares Pablo , Gunn Lucinda , Soliman Heba , Bover Mateo , Trinh Amy , Leslie Isla , Wong Kee Howe , Melcher Alan , Newbold Kate , Nutting Chris M , ap Dafydd Derfel , Bhide Shreerang A , Harrington Kevin
Published: June 2021

Background

Previous studies have suggested that inflammatory markers (neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase (LDH) and fibrinogen) are prognostic biomarkers in patients with a variety of solid cancers, including those treated with immune checkpoint inhibitors (ICIs). We aimed to develop a model that predicts response and survival in patients with relapsed and/or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) treated with immunotherapy.

Methods

Analysis of 100 consecutive patients with unresectable R/M HNSCC who were treated with ICI. Baseline and on-treatment (day 28) NLR, fibrinogen and LDH were calculated and correlated with response, progression-free survival (PFS) and overall survival (OS) using univariate and multivariate analyses. The optimal cut-off values were derived using maximally selected log-rank statistics.

Results

Low baseline NLR and fibrinogen levels were associated with response. There was a statistically significant correlation between on-treatment NLR and fibrinogen and best overall response. On-treatment high NLR and raised fibrinogen were significantly associated with poorer outcome. In multivariate analysis, on-treatment NLR (≥4) and on-treatment fibrinogen (≥4 ng/mL) showed a significant negative correlation with OS and PFS. Using these cut-off points, we generated an on-treatment score for OS and PFS (0–2 points). The derived scoring system shows appropriate discrimination and suitability for OS (HR 2.4, 95% CI 1.7 to 3.4, p<0.0001, Harrell’s C 0.67) and PFS (HR 1.8, 95% CI 1.4 to 2.3, p<0.0001, Harrell’s C 0.68). In the absence of an external validation cohort, results of fivefold cross-validation of the score and evaluation of median OS and PFS on the Kaplan-Meier survival distribution between trained and test data exhibited appropriate accuracy and concordance of the model.

Conclusions

NLR and fibrinogen levels are simple, inexpensive and readily available biomarkers that could be incorporated into an on-treatment scoring system and used to help predict survival and response to ICI in patients with R/M HNSCC.
Iatrogenic immune-mediated neuropathies: diagnostic, epidemiological and mechanistic uncertainties for causality and implications for clinical practice
Authors: Goedee H Stephan , Attarian Shahram , Kuntzer Thierry , Van den Bergh Peter , Rajabally Yusuf A
Published: June 2021

Acute and chronic immune-mediated neuropathies have been widely reported with medical intervention. Although causal relationship may be uncertain in many cases, a variety of drugs, several vaccination types, surgical procedures and bone marrow transplants have been reported as possible cause or trigger of a putative immune-mediated response resulting in acute and chronic neuropathies. We conducted a systematic review of the literature from 1966 to 2020 on reported cases of possible iatrogenic immune-mediated neuropathies. We determined in each case the likelihood of causality based on frequency of the association, focusing primarily on clinical presentation and disease course as well as available ancillary investigations (electrophysiology, blood and cerebrospinal fluid and neuropathology). The response to immunotherapy and issue of re-exposure were also evaluated. We also considered hypothesised mechanisms of onset of immune-mediated neuropathy in the specific iatrogenic context. We believe that a likely causal relationship exists for only few drugs, mainly antitumour necrosis factor alpha agents and immune checkpoint inhibitors, but remains largely unsubstantiated for most other suggested iatrogenic causes. Unfortunately, given the lack of an accurate diagnostic biomarker for most immune-mediated neuropathies, clinical assessment will often override ancillary investigations, resulting in lower levels of certainty that may continue to cast serious doubts on reliability of their diagnosis. Consequently, future reports of suspected cases should collect and exhaustively assess all relevant data. At the current time, besides lack of evidence for causality, the practical implications on management of suspected cases is extremely limited and therapeutic decisions appear likely no different to those made in non-iatrogenic cases.
Diffusion-weighted imaging lesions and risk of recurrent stroke after intracerebral haemorrhage
Authors: Wiegertjes Kim , Dinsmore Lynn , Drever Jonathan , Hutchison Aidan , Stephen Jacqueline , Valdés Hernández Maria C , Bhatnagar Priya , Minks David P , Rodrigues Mark A , Werring David J , de Leeuw Frank-Erik , Klijn Catharina JM , Al-Shahi Salman Rustam , White Phillip M , Wardlaw Joanna M
Published: June 2021

Objective

To determine whether the presence of diffusion-weighted imaging-positive (DWI+) lesions is associated with recurrent stroke after intracerebral haemorrhage (ICH).

Methods

The REstart or STop Antithrombotics Randomised Trial (RESTART) assessed the effect of restarting versus avoiding antiplatelet therapy after ICH on major vascular events for up to 5 years. We rated DWI sequences of MRI done before randomisation for DWI+ lesion presence, masked to outcome and antiplatelet use. Cox proportional hazards regression models were used to quantify associations.

Results

Of 537 participants in RESTART, 247 (median (IQR) age 75.7 (69.6–81.1) years; 170 men (68.8%); 120 started vs 127 avoided antiplatelet therapy) had DWI sequences on brain MRI at a median of 57 days (IQR 19–103) after ICH, of whom 73 (30%) had one or more DWI+ lesion. During a median follow-up of 2 years (1–3), 18 participants had recurrent ICH and 21 had ischaemic stroke. DWI+ lesion presence was associated with all stroke, (adjusted HR 2.2 (95% CI 1.1 to 4.2)) and recurrent ICH (4.8 (95% CI 1.8 to 13.2)), but not ischaemic stroke (0.9 (95% CI 0.3 to 2.5)). DWI+ lesion presence (0.5 (95% CI 0.2 to 1.3)) vs absence (0.6 (95% CI 0.3 to 1.5), pinteraction=0.66) did not modify the effect of antiplatelet therapy on a composite outcome of recurrent stroke.

Conclusions

DWI+ lesion presence in ICH survivors is associated with recurrent ICH, but not with ischaemic stroke. We found no evidence of modification of effects of antiplatelet therapy on recurrent stroke after ICH by DWI+ lesion presence. These findings provide a new perspective on the significance of DWI+ lesions, which may be markers of microvascular mechanisms associated with recurrent ICH.

Trial registration number

ISRCTN71907627.
Healthcare students support opt-out organ donation for practical and moral reasons
Authors: Qian Long , Li Miah T , King Kristen L , Husain Syed Ali , Cohen David J , Mohan Sumit
Published: June 2021

Background and purpose

Changes to deceased organ donation policy in the USA, including opt-out and priority systems, have been proposed to increase registration and donation rates. To study attitudes towards such policies, we surveyed healthcare students to assess support for opt-out and priority systems and reasons for support or opposition.

Methods

We investigated associations with supporting opt-out, including organ donation knowledge, altruism, trust in the healthcare system, prioritising autonomy and participants’ evaluation of the moral severity of incorrectly assuming consent in opt-in systems (‘opt-in error’) or opt-out systems (‘opt-out error’), by conducting an online survey among healthcare students at a large academic institution.

Results

Of 523 respondents, 86% supported opt-out, including 53% who strongly supported the policy. The most popular reason for supporting opt-out was the potential for increased donation rates, followed by convenience for those not registered but willing to donate. The most popular reason for opposing opt-out was the belief that presuming consent is morally wrong. Those strongly supporting opt-out viewed the opt-in error as more morally unacceptable, and had higher knowledge and altruism scores. Those opposing opt-out viewed the opt-out error as more unacceptable, and had higher autonomy scores. 48% of respondents supported priority within opt-in systems; 31% supported priority in opt-out.

Conclusions

There is strong support for opt-out organ donation among healthcare students, influenced by both practical and moral considerations.
On sprays with vanishing χ-curvature
Authors: Shen Zhongmin
Published: June 2021

Every Riemannian metric or Finsler metric on a manifold induces a spray via its geodesics. In this paper, we discuss several expressions for the [Formula: see text]-curvature of a spray. We show that the sprays obtained by a projective deformation using the S-curvature always have vanishing [Formula: see text]-curvature. Then we establish the Beltrami Theorem for sprays with [Formula: see text].
Effect of nonlinear radiation on flow and heat transfer of dusty fluid over a stretching cylinder with Cattaneo–Christov heat flux
Authors: Alhumade Hesham , Radhika M. , Sowmya G. , Manjunatha P. T. , Alam Mohammad Mahtab , Ahmad Irfan , Gorji M. R. , Prasannakumara B. C.
Published: June 2021

The heat transfer through the thermal radiation is very significant in many industrial processes, biomedical engineering, technological devices and thermal therapeutic process. These comprise nuclear power plants, propulsion of rockets, missiles, satellites and space vehicles, photochemical reactors, solar collector performance, heat exchangers. The boundary layer flow and the heat transport of dusty liquid over a stretching cylinder are discussed. The impact of nonlinear thermal radiation is explored. Cattaneo–Christov heat flux model is considered to formulate the energy equation. The resulting equations of the physical system are converted into a system of nonlinear ordinary coupled differential equations with the help of suitable similarity transformations and numerically solved by using Runge–Kutta–Fehlberg’s method along with shooting technique. The influence of nondimensional parameters is analyzed and interpreted graphically. The heat transfer rate and local coefficient of skin friction are also calculated for diverse nondimensional constraints and plotted.
An Effective Memetic Algorithm for the Distributed Integrated Scheduling of Tree-Structured Products
Authors: Gao Yilong , Xie Zhiqiang , Jia Qing , Yu Xu
Published: June 2021

Aiming at the distributed integrated scheduling of complex products with tree structure, a memetic algorithm-based distributed integrated scheduling algorithm is proposed. Based on the framework of the memetic algorithm, the algorithm uses a distributed estimation algorithm for global search and performs a local search strategy based on the critical operation set for the current optimal solution obtained in each evolutionary generation. A bi-chain-based individual representation method is presented and a simple greedy insertion-based decoding method is given; two position-based probability models are built, which are used to describe the distribution of the operation priority and factory assignment, respectively. Based on the designed probability models, two learning-based updating mechanisms and an improved sampling method are given, which ensures that the population evolves towards a promising region. In order to enhance the searchability for the superior solutions, nine disturbance operators based on the critical operation set are presented. The parameters are determined by the design-of-experiment (DOE) test, and the effectiveness of the proposed algorithm is verified by comparative experiments.
ROBUST UTILITY MAXIMIZATION IN A MULTIVARIATE FINANCIAL MARKET WITH STOCHASTIC DRIFT
Authors: SASS JÖRN , WESTPHAL DOROTHEE
Published: June 2021

We study a utility maximization problem in a financial market with a stochastic drift process, combining a worst-case approach with filtering techniques. Drift processes are difficult to estimate from asset prices, and at the same time optimal strategies in portfolio optimization problems depend crucially on the drift. We approach this problem by setting up a worst-case optimization problem with a time-dependent uncertainty set for the drift. Investors assume that the worst possible drift process with values in the uncertainty set will occur. This leads to local optimization problems, and the resulting optimal strategy needs to be updated continuously in time. We prove a minimax theorem for the local optimization problems and derive the optimal strategy. Further, we show how an ellipsoidal uncertainty set can be defined based on filtering techniques and demonstrate that investors need to choose a robust strategy to be able to profit from additional information.
An Efficient Image Privacy-Preserving Scheme Based On Mixed Chaotic Map and Compression
Authors: Tanveer Muhammad , Shah Tariq , Ali Asif , Shah Dawood
Published: June 2021

In the digital modern era, multimedia security has turned into a major concern by the rapid growth of network technologies and digital communications. Accordingly, from the last few decades, the application of nonlinear dynamics and chaotic phenomena for multimedia data security earn significant attention. In this paper, an efficient image-encryption technique based on a two-dimensional (2D) chaotic system combine with the finite field of the specific order is introduced. The proposed scheme consists of four modules which are the separation of bits, compression, 2D chaotic map, and small S-boxes. Initially, the suggested scheme separates the pixels of the image into the least significant bits (LSB) and the most significant bits (MSB). Subsequently, the compression algorithm on these separated bits is applied and instantly transformed the MSB of the image into LSB. The key objective of the first module is to minimize the range of the pixel value up to eight times less than the original image, which consequently reduces the time complexity of the scheme. In the end, a 2D chaotic map is used to reshuffle the bytes to interrupt the internal correlation amongst the pixels of the image. At the tail end, the small S-boxes have been used to substitute the permuted image. The significance of small S-boxes plays a vital role to maintain the optimum security level, prevent computational effort, and reduced time complexity. The result of the suggested encryption system is tailor-made for instantaneous communication.
Sensitive and Specific Detecting Biomarker of Radiation-Resistant Nasopharyngeal Carcinoma by TpTta-COF Nanosheet
Authors: Han Zhaoyu , Li Sen , Yin Shaoxian , Cai Yanfei , Jin Jian , Huang Gang , Yang Zhaoqi
Published: June 2021

An important attribute of microRNA-205 (MiR-205) is their potential use as predictive biomarker for anti-radiation of nasopharyngeal carcinoma (NPC), and it is pivotal to monitor the dynamic change of MiR-205 for personalized precise treatment strategies. So far, there are several methods aiming at detecting MiR-205 while rarely has worked out questions such as limited complex detection processes, poor sample detection limit or spending lots of time. Therefore, a method for detecting MiR-205 based on 2D COF nanosheets and fluorescent oligonucleotide probe was constructed and investigated in this study. The 2D COF nanosheet quenches the fluorescence of the fluorescent single-stranded DNA (ss-DNA) probes through fluorescence resonance energy transfer (FRET). The method enables to capture MiR-205 sensitively in aqueous solution with a detection limit of 4.78[Formula: see text]nM in the range 0–500[Formula: see text]nM and [Formula: see text], and the method offers great specificity in that it can distinguish the target miRNA from mismatch nontarget miRNAs. Considering its simple operability and excellent specificity, it has great application prospects in the detection of miRNA biomarker in clinical diagnosis and personalized treatment plan.
New Analytical Solution to Predict the Vertical Impedance of a Large-Diameter Pipe Pile in Soil Considering Wave Propagation in Visco-Elastic Continuum
Authors: Cui Chunyi , Liang Zhimeng , Xu Chengshun , Xin Yu , Wang Benlong , Meng Kun
Published: June 2021

According to the theories of wave propagation in visco-elastic continuum and Rayleigh-Love rod, a simplified model in axisymmetric conditions for the longitudinal vibration of large-diameter pipe pile (LDPP) in radially heterogeneous surrounding soil with viscous damping is presented. The relevant analytical solution for dynamic impedance at pile head is derived by using complex stiffness transfer method, which is also validated via independent comparisons with previous solutions. Besides, parametric analyses are carried out to reveal both the radial heterogeneity of surrounding soil and the lateral inertia effect of pile shaft on the dynamic impedance of LDPP. The obtained analytical solutions are suitable for the longitudinal vibration issues of floating LDPP in visco-elastic surrounding soil with radial heterogeneity, which can be conveniently degenerated to describe the longitudinal vibration of a floating solid pile in soil with radial heterogeneity as well as a floating LDPP or solid pile in radially homogenous soil.
Dynamics of a discrete predator-prey model with Holling-II functional response
Authors: Liu Yuqing , Li Xianyi
Published: June 2021

In this paper, we use a semidiscretization method to derive a discrete predator–prey model with Holling type II, whose continuous version is stated in [F. Wu and Y. J. Jiao, Stability and Hopf bifurcation of a predator-prey model, Bound. Value Probl. 129 (2019) 1–11]. First, the existence and local stability of fixed points of the system are investigated by employing a key lemma. Then we obtain the sufficient conditions for the occurrence of the transcritical bifurcation and Neimark–Sacker bifurcation and the stability of the closed orbits bifurcated by using the Center Manifold theorem and bifurcation theory. Finally, we present numerical simulations to verify corresponding theoretical results and reveal some new dynamics.
Synthesis and characterization of reporter molecules embedded core-shell nanoparticles as SERS nanotags
Authors: Duffield Chloe , Lyu Nana , Wang Yuling
Published: June 2021

Surface-enhanced Raman scattering (SERS) spectroscopy is presented as a sensitive and specific molecular tool for clinical diagnosis and prognosis monitoring of various diseases including cancer. In order for clinical application of SERS technique, an ideal method of bulk synthesis of SERS nanoparticles is necessary to obtain sensitive, stable and highly reproducible Raman signals. In this contribution, we determined the ideal conditions for bulk synthesis of Raman reporter (Ra) molecules embedded silver-gold core-shell nanoparticles (Au@Ra@ AgNPs) using hydroquinone as reducing agent of silver nitrate. By using UV-Vis spectroscopy, Raman spectroscopy and transmission electron microscopy (TEM), we found that a 2:1 ratio of silver nitrate to hydroquinone is ideal for a uniform silver coating with a strong and stable Raman signal. Through stability testing of the optimized Au@Ra@AgNPs over a two-week period, these SERS nanotags were found to be stable with minimal signal change occurred. The stability of antibody linked SERS nanotags is also crucial for cancer and disease diagnosis, thus, we further conjugated the as-prepared SERS nanotags with anti-EpCAM antibody, in which the stability of bioconjugated SERS nanotags was tested over eight days. Both UV-Vis and SERS spectroscopy showed stable absorption and Raman signals on the anti-EpCAM conjugated SERS nanotags, indicating the great potential of the synthesized SERS nanotags for future applications which require large, reproducible and uniform quantities in order for cancer biomarker diagnosis and monitoring.
A comparative study on machine learning-based classification to find photothrombotic lesion in histological rabbit brain images
Authors: Jo Sang Hee , Kim Yoonhee , Lee Yoon Bum , Oh Sung Suk , Choi Jong-ryul
Published: June 2021

Recently, research has been conducted to assist in the processing and analysis of histopathological images using machine learning algorithms. In this study, we established machine learning-based algorithms to detect photothrombotic lesions in histological images of photothrombosis-induced rabbit brains. Six machine learning-based algorithms for binary classification were applied, and the accuracies were compared to classify normal tissues and photothrombotic lesions. The lesion classification model consisting of a 3-layered neural network with a rectified linear unit (ReLU) activation function, Xavier initialization, and Adam optimization using datasets with a unit size of [Formula: see text] pixels yielded the highest accuracy (0.975). In the validation using the tested histological images, it was confirmed that the model could identify regions where brain damage occurred due to photochemical ischemic stroke. Through the development of machine learning-based photothrombotic lesion classification models and performance comparisons, we confirmed that machine learning algorithms have the potential to be utilized in histopathology and various medical diagnostic techniques.
General sum-connectivity index of unicyclic graphs with given diameter and girth
Authors: Vetrík Tomáš
Published: June 2021

Topological indices of graphs have been studied due to their extensive applications in chemistry. We obtain lower bounds on the general sum-connectivity index [Formula: see text] for unicyclic graphs [Formula: see text] of given girth and diameter, and for unicyclic graphs of given diameter, where [Formula: see text]. We present the extremal graphs for all the bounds. Our results generalize previously known results on the harmonic index for unicyclic graphs of given diameter.
Application of Early Warning Nursing System During COVID-19 Epidemic in Children’s Hospital
Authors: Yao Wenying , Yang Jinxia , Wang Xin , Shen Min
Published: June 2021

Aim: To develop a nursing early warning system in children’s hospital during the outbreak of the novel coronavirus pneumonia, and to accomplish the construction and application of this system, so as to provide decision-support of the prevention and control for COVID-19 in children’s medical institutions. Method: Children’s hospital nursing early warning system was divided into three modules: hospital nursing early warning platform includes internal and external early warning platform, nursing staff early warning program includes protection, human resources early warning plan and patient early warning program includes outpatient, emergency and ward early warning plan. The data of epidemic training, assessment, prevention and control screening from January to June 2020 were collected from the nursing early warning system to evaluate the application effect of the system. Results: A total of 18 procedures and specifications were formulated, nine hospital-level trainings and about 1000 department-level trainings were organized, two hospital-level assessments (pass rate 95.6% and 98.2%), and 78 nurses were reserved, and 10 popular science articles, five popular science videos were published during the application of the nursing early warning system. A total of 583,435 children and 139,308 caregivers were screened in outpatient, emergency and wards during pre-checks, 2385 suspected cases of novel coronavirus pneumonia were confirmed (0.41%) after the screening and 1 case (0.0002%) was finally confirmed. Conclusion: The nursing early warning system of children’s hospital can prevent and control the novel coronavirus pneumonia epidemic from each module, ensure early warning and triage of suspected infected patients, reduce the risk of cross-infection in hospital and improve the safety of the children’s hospital medical environment.
Ridgelized Hotelling’s T2 test on mean vectors of large dimension
Authors: Ha Gao-Fan , Zhang Qiuyan , Bai Zhidong , Wang You-Gan
Published: June 2021

In this paper, a ridgelized Hotelling’s [Formula: see text] test is developed for a hypothesis on a large-dimensional mean vector under certain moment conditions. It generalizes the main result of Chen et al. [A regularized Hotelling’s [Formula: see text] test for pathway analysis in proteomic studies, J. Am. Stat. Assoc. 106(496) (2011) 1345–1360.] by relaxing their Gaussian assumption. This is achieved by establishing an exact four-moment theorem that is a simplified version of Tao and Vu’s [Random matrices: universality of local statistics of eigenvalues, Ann. Probab. 40(3) (2012) 1285–1315] work. Simulation results demonstrate the superiority of the proposed test over the traditional Hotelling’s [Formula: see text] test and its several extensions in high-dimensional situations.
INVESTMENT LIBERALIZATION, CREDIT CONSTRAINTS, AND INTERNATIONAL TRADE
Authors: XIONG TINGTING , SUN HAO
Published: June 2021

This paper investigates the effect of bilateral investment treaties (BITs) on the extensive and intensive product margins of exports in sectors with different credit constraints. The model in this paper demonstrates that such investment liberalization increases the extensive product margin by lowering the variable costs of selling abroad, while it decreases the intensive product margin by lowering both the fixed investment costs and the variable costs. Moreover, the effects of investment liberalization are stronger in financially more vulnerable sectors. Using a detailed dataset of 190 countries and 27 manufacturing sectors from 1988 to 2006, this paper furnishes robust evidence that BITs increase the extensive margin of exports from developed countries and decrease the intensive margin of exports. It further shows that BITs decrease the intensive margin of exports from developed countries more in the sectors that are more dependent on external finance. Similarly, the intensive margin of exports from developed countries in low tangibility sectors falls by 11.81% because of BITs, while the intensive margin in high tangibility sectors is quite stable with BITs.
The Analysis of Turkey’s Fight Against the COVID-19 Outbreak Using K-Means Clustering and Curve Fitting
Authors: Şenel Fatih Ahmet
Published: June 2021

The COVID-19 is a global disease that occurred at the end of 2019 and it has shown its effects all over the world in a very short time. World Health Organization has mobilized all the countries of the world to survive with minimal damage from this outbreak. The situation in some countries was under control as their health infrastructure is robust enough. On the other hand, many countries suffered significant damage from the outbreak. The countries that have already taken their precautions have suffered less, Turkey is one of the leading countries. Besides taking precautions in advance, countries are guiding each other throughout the outbreak. Therefore, the countries leading the fight against the outbreak should be analyzed and each country should update its precautions to fight the outbreak. In this study, COVID-19 deaths are taken into account and similar countries to Turkey are identified by K-means clustering. Later, by comparing the various characteristics of Turkey with these similar countries, Turkey’s status in fighting the outbreak is revealed. The precautions Turkey took before the outbreak showed that Turkey can fight the COVID-19 outbreak successfully.
A study of lead-free (K0.5N0.5)NbO3 piezoelectric ceramics processed by additive manufacturing
Authors: Zhang Lei , Wang Teng , Sun Jinxing , Chen Xiaoteng , Hong Xing , Zhou Peng , Bai Jiaming
Published: June 2021

Lead-free (K[Formula: see text]N[Formula: see text]NbO3 piezoelectric ceramics have drawn wide attention due to its environment-friendly and excellent piezoelectric performance. Since the difficulty of post-processing of ceramics limit its further development and practical application, three-dimensional (3D) printing technology has been developed in this work. A homogeneous piezoelectric ceramic suspension with 40 vol% modified (K[Formula: see text]N[Formula: see text]NbO3 nanoparticles can be 3D printed well based on a stereolithography process. In addition, by the post heat treatment under different sintering temperature, a density value of 4.31[Formula: see text]g[Formula: see text]cm[Formula: see text] with the relative density of about 96% was obtained in the sample sintered at 1120[Formula: see text]C, which results in the larger dielectric constant and lower dielectric loss in this sample. These printed ceramics exhibit two successive phase transitions and reduce with increase of sintering temperature at measured temperature range.
Crystal transfer from magma to wallrock during syntectonic granite emplacement
Authors: Hayes Ben , Lehmann Jérémie , Bybee Grant M. , Owen-Smith Trishya M.
Published: June 2021

Field, microstructural and mineral compositional evidence from the Mesoproterozoic K-feldspar megacrystic Red Granite at Oncócua Platform (southwestern Angola) is consistent with crystal transfer from magma to wallrock during syntectonic intrusion. K-feldspar megacrystic Red Granite intruded during folding of wallrock tonalite. Enclaves of the wallrock tonalite are elongated parallel to Red Granite intrusive contacts, a K-feldspar megacryst and hornblende-defined magmatic foliation, and a gneissosity in the Red Granite. Stromatic layering present in the tonalite is crosscut by the Red Granite intrusive contacts or is isoclinally folded with fold axial planes and hinges filled with Red Granite. K-feldspar megacryst clusters and curved grain boundaries (i.e. contact melting), as well as thin Red Granite fold axial planar sheets containing K-feldspar megacrysts that are typically wider than the sheets themselves, are all consistent with melt loss and crystal accumulation during solidification. The wallrock tonalite also hosts K-feldspar megacrysts and hornblende phenocrysts that are interpreted to be the same population as those in Red Granite, on the basis of their size, shape, nature of inclusions, compositions and compositional zoning. We propose that these crystals were transferred from the intrusive Red Granite magma to the wallrock tonalite via magmatic conduits that subsequently collapsed due to external stresses, leaving behind the larger crystals. The pristine preservation of intrusive relations at Oncócua Platform may mean that crystal transfer from magma to wallrock is more common in incrementally assembled granitoid plutons than previously thought.

Supplementary material:
Mineral chemical data are available at
https://doi.org/10.6084/m9.figshare.c.5448664
Diamondiferous kimberlites from recently explored Upper Muna Field (Siberian Craton): petrology, mineralogy and geochemistry insights
Authors: Yakovlev D. A. , Kostrovitsky S. I. , Fosu B. R. , Ashchepkov I. V.
Published: June 2021

Petrographic, geochemical and mineralogical characteristics of diamond deposits from the Upper Muna field have been investigated. Geochemically, diamondiferous kimberlites from Upper Muna belong to the most widespread Fe–Mg-rich rocks in the Yakutian kimberlite province (average FeO
total
= 8.4 wt%, MgO = 32.36 wt%, TiO
2
= 1.6 wt%). Striking mineralogical features of Upper Muna kimberlites are: (1) abundance of monticellite and perovskite in the groundmass; (2) rare occurrence of Mg-ilmenite; (3) abundance of phlogopite megacrysts (up to 8 cm across); and (4) coexistence of low-Cr (0.1–4 wt% Cr
2
O
3
, with 0.8–1.2 wt% TiO
2
) and high-Cr (3–8 wt% Cr
2
O
3
, with 0.1–0.6 wt% TiO
2
) garnet megacrysts with contrasting rare earth element patterns. The compositional features of groundmass minerals, the relatively low CaO and CO
2
contents in kimberlites and few deuteric alteration in Upper Muna kimberlites suggest high-temperature melt crystallization during pipe emplacement. Based on the compositional data of garnet and Cr-diopside from megacrysts and peridotites, we suggest a poor Cr dunite–harzburgitic and lherzolitic mantle source beneath the Upper Muna field where Cr-diopside crystallized within a wide pressure and temperature range (40–65 kbar and 900–1350°С). The mineral geochemistry, trace element distribution and Sr–Nd isotope variations of Upper Muna kimberlites are typical for group I kimberlites and reflect a deep-seated asthenospheric (convective mantle) source for the kimberlites.
Performance Modeling and Practical Use Cases for Black-Box SSDs
Authors: Kim Joonsung , Choi Kanghyun , Lee Wonsik , Kim Jangwoo
Published: June 2021

Modern servers are actively deploying Solid-State Drives (SSDs) thanks to their high throughput and low latency. However, current server architects cannot achieve the full performance potential of commodity SSDs, as SSDs are complex devices designed for specific goals (e.g., latency, throughput, endurance, cost) with their internal mechanisms undisclosed to users. In this article, we propose
SSDcheck
, a novel SSD performance model to extract various internal mechanisms and predict the latency of next access to commodity black-box SSDs. We identify key performance-critical features (e.g., garbage collection, write buffering) and find their parameters (i.e., size, threshold) from each SSD by using our novel diagnosis code snippets. Then, SSDcheck constructs a performance model for a target SSD and dynamically manages the model to predict the latency of the next access. In addition, SSDcheck extracts and provides other useful internal mechanisms (e.g., fetch unit in multi-queue SSDs, background tasks triggering idle-time interval) for the storage system to fully exploit SSDs. By using those useful features and the performance model, we propose multiple practical use cases. Our evaluations show that SSDcheck’s performance model is highly accurate, and proposed use cases achieve significant performance improvement in various scenarios.
MKEL: Multiple Kernel Ensemble Learning via Unified Ensemble Loss for Image Classification
Authors: Shen Xiangjun , Lu Kou , Mehta Sumet , Zhang Jianming , Liu Weifeng , Fan Jianping , Zha Zhengjun
Published: June 2021

In this article, a novel ensemble model, called Multiple Kernel Ensemble Learning (MKEL), is developed by introducing a unified ensemble loss. Different from the previous multiple kernel learning (MKL) methods, which attempt to seek a linear combination of basis kernels as a unified kernel, our MKEL model aims to find multiple solutions in corresponding Reproducing Kernel Hilbert Spaces (RKHSs) simultaneously. To achieve this goal, multiple individual kernel losses are integrated into a unified ensemble loss. Therefore, each model can co-optimize to learn its optimal parameters by minimizing a unified ensemble loss in multiple RKHSs. Furthermore, we apply our proposed ensemble loss into the deep network paradigm and take the sub-network as a kernel mapping from the original input space into a feature space, named Deep-MKEL (D-MKEL). Our D-MKEL model can utilize the diversified deep individual sub-networks into a whole unified network to improve the classification performance. With this unified loss design, our D-MKEL model can make our network much wider than other traditional deep kernel networks and more parameters are learned and optimized. Experimental results on several mediate UCI classification and computer vision datasets demonstrate that our MKEL model can achieve the best classification performance among comparative MKL methods, such as Simple MKL, GMKL, Spicy MKL, and Matrix-Regularized MKL. On the contrary, experimental results on large-scale CIFAR-10 and SVHN datasets concretely show the advantages and potentialities of the proposed D-MKEL approach compared to state-of-the-art deep kernel methods.
CacheInspector
Authors: Song Weijia , Delimitrou Christina , Shen Zhiming , Renesse Robbert Van , Weatherspoon Hakim , Benmohamed Lotfi , Vaulx Frederic De , Mahmoudi Charif
Published: June 2021

Infrastructure-as-a-Service cloud providers sell virtual machines that are only specified in terms of number of CPU cores, amount of memory, and I/O throughput. Performance-critical aspects such as cache sizes and memory latency are missing or reported in ways that make them hard to compare across cloud providers. It is difficult for users to adapt their application’s behavior to the available resources. In this work, we aim to increase the visibility that cloud users have into shared resources on public clouds. Specifically, we present
CacheInspector
, a lightweight runtime that determines the performance and allocated capacity of shared caches on multi-tenant public clouds. We validate
CacheInspector
’s accuracy in a controlled environment, and use it to study the characteristics and variability of cache resources in the cloud, across time, instances, availability regions, and cloud providers. We show that
CacheInspector
’s output allows cloud users to tailor their application’s behavior, including their output quality, to avoid suboptimal performance when resources are scarce.
Spatial Interpolation Techniques on Participatory Sensing Data
Authors: Middya Asif Iqbal , Roy Sarbani
Published: June 2021

Spatial distributions of data of natural phenomena can be estimated by using different spatial interpolation techniques. These techniques can be used for the purpose of developing urban noise pollution monitoring applications, so they can truly describe the actual urban noise pollution scenario of any region of interest to make effective and informed decisions. In this context, our aim is to use IoT-cloud based framework to generate dynamic (i.e., changes in terms of time and space) noise maps as a service with the help of spatial interpolation techniques. Noise map generation is an effective method for visualizing and assessing urban noise pollution. In this article, we have proposed three spatial interpolation techniques (GLIDW, I-GLIDW, GLIDW-OK) that work on participatory sensing-based noise pollution data collected using smartphones as IoT devices to generate dynamic noise maps. Proposed techniques can address diverse scenarios such as
sparse datasets
,
high accuracy
,
better response time
, and so on. Depending on the situation, we can choose an appropriate technique. We evaluate our proposed methods based on a real-world urban noise pollution dataset collected by participants over a period of two years in an urban area of the city Kolkata. The results are compared with inverse distance weighting (IDW) and Ordinary Kriging (OK) methods. The method GLIDW is proposed for a dense dataset. The results validate that in the case of a dense dataset GLIDW dominates over other methods. But, when the data sparsity level is medium, I-GLIDW performs well. However, if the dataset is very sparse, then GLIDW-OK dominates in terms of predictive accuracy. The results also show that Relative Improvement (RI) of I-GLIDW and GLIDW-OK is always positive compared to baseline methods IDW and OK.
Recent Advances in Empirical Land-Use Modeling
Authors: Plantinga Andrew J.
Published: June 2021

Data sets providing repeated observations of land use at fine spatial scales have enabled a new generation of land-use studies. In the past decade, these analyses have put increasing emphasis on empirical research designs that provide more convincing causal estimates. I review the use of instrumental variables, matching, difference-in-differences, regression discontinuity design, and randomized controlled trials in the recent land-use economics literature, exploring how new data have made possible the use of these research designs. I show that these estimators have produced different results than were obtained with traditional approaches and have provided new insights into important land-use policy issues such as additionality and spillover effects.
Economic, Environmental, and Health Impacts of the Fracking Boom
Authors: Black Katie Jo , Boslett Andrew J. , Hill Elaine L. , Ma Lala , McCoy Shawn J.
Published: June 2021

The shale gas boom revolutionized the energy sector through hydraulic fracturing (fracking). High levels of energy production force communities, states, and nations to consider the externalities and potential risks associated with this unconventional oil and natural gas development (UOGD). In this review, we systematically outline the environmental, economic, and anthropogenic impacts of UOGD, while also considering the diverse methodological approaches to these topics. We summarize the current status and conclusions of the academic literature, in both economic and related fields, while also providing suggested avenues for future research. Causal inference will continue to be important for the evaluation of UOGD costs and benefits. We conclude that current economic, global, and health forces may require researchers to revisit outcomes in the face of a potential shale bust.
Dynamic Response of Parallel Overlapped Tunnel under Seismic Loading by Shaking Table Tests
Authors: Yang Tao , Rao Yunkang , Wu Honggang , Zhang Junyun , Lei Hao , Ding Haojiang
Published: June 2021

Potential earthquake‐induced damage to overlapped tunnels probably occurs during the operation and maintenance of mountain tunnel engineering, especially in the seismically active zone. This study investigated the dynamic response and the failure characteristics of the parallel overlapped tunnel under seismic loadings by employing shaking table tests. The failure mode of the parallel overlapped tunnels was analyzed through macroscopic test phenomena. The dynamic responses of the surrounding rock and tunnel lining were evaluated by acceleration and dynamic strain, respectively. In particular, wavelet packets were used to investigate the spectrum characteristics of the tunnel structure in depth. The failure process of the model can be divided into three stages. The upper‐span and the under‐crossing tunnels showed different failure characteristics. Additionally, the lining damage on the outer surface of the tunnel mainly occurred on the right side arch waist and the left side wall, whereas the lining damage on the inner surface of the tunnel mainly appeared on the crown and invert. Wavelet packet energy results showed that the energy characteristic distributions of the upper‐span and the under‐crossing tunnels were not consistent. Specifically, the energy eigenvalues of the crown of the upper‐span tunnel and the invert of the under‐crossing tunnel were the largest, which should be considered to be the weak parts in the seismic design.
Protective Effect of Optic Atrophy 1 on Cardiomyocyte Oxidative Stress: Roles of Mitophagy, Mitochondrial Fission, and MAPK/ERK Signaling
Authors: Wang Yue , Han Zhihua , Xu Zuojun , Zhang Junfeng
Published: June 2021

Myocardial infarction is associated with oxidative stress and mitochondrial damage. However, the regulatory mechanisms underlying cardiomyocyte oxidative stress during myocardial infarction are not fully understood. In the present study, we explored the cardioprotective action of optic atrophy 1‐ (Opa1‐) mediated mitochondrial autophagy (mitophagy) in oxidative stress‐challenged cardiomyocytes, with a focus on mitochondrial homeostasis and the MAPK/ERK pathway. Our results demonstrated that overexpression of Opa1 in cultured rat H9C2 cardiomyocytes, a procedure that stimulates mitophagy, attenuates oxidative stress and increases cellular antioxidant capacity. Activation of Opa1‐mediated mitophagy suppressed cardiomyocyte apoptosis by downregulating Bax, caspase‐9, and caspase‐12 and upregulating Bcl‐2 and c‐IAP. Using mitochondrial tracker staining and a reactive oxygen species indicator, our assays showed that Opa1‐mediated mitophagy attenuated mitochondrial fission and reduced ROS production in cardiomyocytes. In addition, we found that inhibition of the MAPK/ERK pathway abolished the antioxidant action of Opa1‐mediated mitophagy in these cells. Taken together, our data demonstrate that Opa1‐mediated mitophagy protects cardiomyocytes against oxidative stress damage through inhibition of mitochondrial fission and activation of MAPK/ERK signaling. These findings reveal a critical role for Opa1 in the modulation of cardiomyocyte redox balance and suggest a potential target for the treatment of myocardial infarction.
Comparison of Ultrasound-Guided Fine-Needle Cytology Quality in Thyroid Nodules with 22-, 23-, and 25-Gauge Needles
Authors: Dong YiJie , Gao LiLi , Sui Yang , Mao MinJing , Zhan WeiWei , Zhou JianQiao
Published: June 2021

Objective. To compare the cytology quality of ultrasound-guided fine-needle biopsy in thyroid nodules with 22-, 23-, and 25-gauge (G) needles prospectively. Methods. A total of 240 consecutive nodules underwent ultrasound-guided fine-needle aspiration (USG-FNA) and 240 nodules underwent ultrasound-guided fine-needle capillary (USG-FNC) were included in this prospective study from October 2014 to February 2016. Each nodule was sampled using 22 G, 23 G, and 25 G needle according to designed orders, and 1240 smears were finally obtained. Cytology quality was scored by a cytologist blinded to needle selection. Results. In USG-FNA, the average scores and standard deviations were

5.50
±
2.87

for 25 G needles,

4.82
±
2.95

for 23 G needles, and

5.19
±
2.81

for 22 G needles. In USG-FNC, the average scores and standard deviations of each group were

5.12
±
2.69

for 25 G,

4.60
±
2.90

for 23 G, and

4.90
±
2.90

for 22 G needles. The specimen quality scores of 25 G group were significantly higher than that of 23 G group (

P
<
0.017

) in both USG-FNA and USG-FNC. However, the differences were not statistically significant in nondiagnostic rate using different gauge of needles (

P
>
0.017

for all). Conclusions. 25 G needles obtained the highest scores of sample quality in thyroid FNA and FNC comparing with 22 G and 23 G needles. 25 G needle should be first choice of thyroid FNA and FNC in routine work.
An Improved Particle Number-Based Oil Spill Model Using Implicit Viscosity in Marine Simulator
Authors: Qiu Shaoyang , Ren Hongxiang , Li Haijiang , Tao Rui , Zhou Yi
Published: June 2021

Improving the physical realism of oil spill scenes in marine simulators can further enhance the emergency response capabilities of officials in charge and crew members and help reduce losses caused by oil spill disasters. In order to uniformly simulate the spreading, drift, breakup, and merging of oil spills at sea, we propose an improved divergence-free position-based fluid (DFPBF) framework based on the particle number density model. In our DFPBF framework, the governing equations for oil spills and ocean are discretized by Lagrangian particles, and the incompressibility of oil spills and ocean is ensured by solving the divergence-free velocity constraint solver and constant density constraint solver. In order to stably simulate the fate and transport of oil spills with higher viscosity, we introduce an implicit viscosity solution scheme for our DFPBF framework. The implicit solver uses a splitting concept to decouple viscosity solve and adopts an implicit scheme to discretize the integration of viscous force. Moreover, our DFPBF framework can ensure a divergence-free velocity field before applying the implicit viscosity scheme, which avoids the undesired bulk viscosity effects. The simulation results show that our DFPBF framework can stably simulate oil spills of various viscosities, especially high-viscosity crude oils.