bluuebunny/crossref_metadata_2025_split huggingface dataset:
Combination gemcitabine and PD-L1xCD3 bispecific T cell engager (BiTE) enhances T lymphocyte cytotoxicity against cholangiocarcinoma cells
Authors: Wathikthinnakon Methi , Luangwattananun Piriya , Sawasdee Nunghathai , Chiawpanit Chutipa , Lee Vannajan Sanghiran , Nimmanpipug Piyarat , Tragoolpua Yingmanee , Rotarayanont Siriphorn , Sangsuwannukul Thanich , Phanthaphol Nattaporn , Wutti-in Yupanun , Somboonpatarakun Chalermchai , Chieochansin Thaweesak , Junking Mutita , Sujjitjoon Jatuporn , Yenchitsomanus Pa-thai , Panya Aussara 
Published: April 2022

Abstract
Cholangiocarcinoma (CCA) is a lethal cancer with rapid progression and poor survival. Novel and more effective therapies than those currently available are, therefore, urgently needed. Our research group previously reported the combination of gemcitabine and cytotoxic T lymphocytes to be more effective than single-agent treatment for the elimination of CCA cells. However, gemcitabine treatment of CCA cells upregulates the expression of an immune checkpoint protein (programmed death-ligand 1 [PD-L1]) that consequently inhibits the cytotoxicity of T lymphocytes. To overcome this challenge and take advantage of PD-L1 upregulation upon gemcitabine treatment, we generated recombinant PD-L1xCD3 bispecific T cell engagers (BiTEs) to simultaneously block PD-1/PD-L1 signaling and recruit T lymphocytes to eliminate CCA cells. Two recombinant PD-L1xCD3 BiTEs (mBiTE and sBiTE contain anti-PD-L1 scFv region from atezolizumab and from a published sequence, respectively) were able to specifically bind to both CD3 on T lymphocytes, and to PD-L1 overexpressed after gemcitabine treatment on CCA (KKU213A, KKU055, and KKU100) cells. mBiTE and sBiTE significantly enhanced T lymphocyte cytotoxicity against CCA cells, especially after gemcitabine treatment, and their magnitudes of cytotoxicity were positively associated with the levels of PD-L1 expression. Our findings suggest combination gemcitabine and PD-L1xCD3 BiTE as a potential alternative therapy for CCA.
Ion transport and limited currents in supporting electrolytes and ionic liquids
Authors: Schalenbach Maximilian , Durmus Yasin Emre , Tempel Hermann , Kungl Hans , Eichel Rüdiger-A. 
Published: April 2022

AbstractSupporting electrolytes contain inert dissolved salts to increase the conductivity, to change microenvironments near the electrodes and to assist in electrochemical reactions. This combined experimental and computational study examines the impact of supporting salts on the ion transport and related limited currents in electrochemical cells. A physical model that describes the multi-ion transport in liquid electrolytes and the resulting concentration gradients is presented. This model and its parameterization are evaluated by the measured limited current of the copper deposition in a CuSO4 electrolyte under a gradually increasing amount of Na2SO4 that acts as a supporting salt. A computational sensibility analysis of the transport model reveals that the shared conductance between the ions lowers the limited currents with larger supporting salt concentrations. When the supporting salt supplies most of the conductance, the electric-field-driven transport of the electrochemically active ions becomes negligible so that the limited current drops to the diffusion-limited current that is described by Fick’s first law. The transition from diluted supporting electrolyte to the case of ionic liquids is elucidated with the transport model, highlighting the different physical transport mechanisms in a non-conducting (polar) and a conducting (ionic) solvent.
Case Study: CRISPR 101 – a novel online learning course harnessing innovative ways to teach a complex biomolecular technology
Authors: Pal Martin , Cranna Nicki , Herold Marco J. , Bumsted O’Brien Keely 
Published: April 2022

Abstract
Complex biomolecular technologies revolutionise scientific research. Fully embedding scientific advances in the community requires innovative ways to educate learners on the molecular foundations upon which these technologies are based. In this case study, we present the conception and design of Walter and Eliza Hall Institute of Medical Research (WEHI’s) inaugural wholly online learning course focussed on explaining the revolutionary genome-editing technology, clustered regulatory interspaced palindromic repeats (CRISPR). Utilising WEHI’s strength in bringing science educators and world-leading CRISPR scientists together, we designed a multimodal online resource that introduces learners, without an extensive background in either science or genome editing, to the fundamental concepts of CRISPR technology. Using the online course creation tool, Articulate 360, we guided learners through three modules containing targeted lessons designed to focus on specific learning outcomes. Integrated videos, research articles, interviews, and other resources, allowed for self-paced learning that met various learning style needs. The extensive resources provided opportunities to delve deeper into the content for advanced learners. The effectiveness of the course, evaluated with survey responses collected upon completion of the course, highlighted the ease of use and functionality of the course, and an increased understanding of CRISPR technology after course completion. We anticipate future online learning course development to showcase complex molecular technology that will be valuable for tertiary education, as well as for those in the wider community interested in understanding important advances in biomedicine.
Spatiotemporal traffic data imputation via tensorial weighted Schatten‐p norm minimization
Authors: Wang Shaofan , Zhao Yongbo , Zhang Yong , Hu Yongli , Yin Baocai 
Published: April 2022

AbstractSpatiotemporal traffic data exhibit multi‐granular low‐rank structure due to their periodicity among different timelines. Traditional low rank data completion methods fail to characterize such properties and produce unsatisfactory results for data imputation. In this paper, a tensorial weighted Schatten‐p norm minimization (TWSN) is proposed for spatiotemporal traffic data imputation. TWSN consists of an approximation term and a low‐rank regularization term over the recovered tensor data, where the latter is a combination of the weighted Schatten‐p norm in the matrix form of each mode of the tensor. For each mode, TWSN utilizes a selection scheme of the mode‐wise weights to capture different properties of singular values of each mode of the tensor. Overall, TWSN not only plays a balancing role between the rank function and the nuclear norm, but also captures the anisotropic correlation of singular values of each mode of the tensor. TWSN is evaluated on four real‐world datasets with different ping frequencies (2, 5, 10 min) and its performance is compared with several state‐of‐the‐art methods. The experimental results show that TWSN outperforms other methods under various data missing scenarios.
Road geometry perception without accurate positioning and lane information
Authors: Li Kan , Yang Xiaoyu , Luo Yuehui , Li Huiyun 
Published: April 2022

AbstractRoad geometry perception indicates road direction and drivable area for Lane Keeping System and Lane Departure Warning System in Advanced Driver Assistance Systems or routing and decision‐making in Autonomous Driving. High‐definition map with accurate positioning or lane information is generally required. However, these two types of information are not always available because of positioning failure or lane mark degradation. In this paper, a road geometry estimation method is proposed without requirement of accurate positioning and lane information. Due to the fact the lane guides the front vehicle, the potential correlation between the relative azimuth of front vehicle and the direction of road is explored. The stable and observable information of front vehicles are exploited, such as the license plate location. A radar‐camera fusion system using image processing, and a nonlinear system is then built with Unscented Kalman Filter to estimate the road curvature. Simulation results with Carla demonstrate that the method enhances the road geometry perception by 77.1%, compared with the baseline method. The proposed method can provide reliable road geometry information for autonomous driving when accurate positioning and lane information are unavailable, so that it renders more robust and safer perception for future autonomous driving.
Thrust measurement of an ion thruster by a force probe approach and comparison to a thrust balance
Authors: Scharmann Steffen , Keil Konstantin , Zorn Jana , Dietz Patrick , Nauschütt Benny , Holste Kristof , Hannemann Klaus , Klar Peter J. , Kloss Samuel , Graubner Swen , Neumann Andreas , Simon Jens 
Published: April 2022

A key parameter when characterizing the performance of an electric propulsion system is obviously its thrust. The thrust can be either determined directly using a so-called thrust balance or deduced from indirect measurements. Here, we present a comparison of thrust measurements of the same radio frequency ion thruster in the thrust range from 250 μN to 1.5 mN using three different approaches: a conventional direct measurement employing a thrust balance and two indirect measurements, one based on a force probe located stationary in the thruster’s plume in conjunction with a scan of the ion beam profile using a Faraday-array scanner, and another one based on a measurement of the beam current at the grid system and a correction for beam divergence deduced from the Faraday-array scans. The results of the three approaches are compared for different beam currents, and pros and cons of the approaches are discussed.
Rotational dynamics and transition mechanisms of surface-adsorbed proteins
Authors: Zhang Shuai , Sadre Robbie , Legg Benjamin A. , Pyles Harley , Perciano Talita , Bethel E. Wes , Baker David , Rübel Oliver , De Yoreo James J. 
Published: April 2022

Significance
The exquisite organization exhibited by hybrid biomolecular–inorganic materials in nature has inspired the development of synthetic analogues for numerous applications. Nevertheless, a mechanistic picture of the energetic controls and response dynamics leading to organization is lacking. Here, we pair high-speed atomic force microscopy with machine learning and Monte Carlo simulations to analyze the rotational dynamics of rod-like proteins on a crystal lattice, simultaneously quantifying the orientational energy landscape and transition probabilities between energetically favorable orientations. Although rotations largely follow Brownian diffusion, proteins often make large jumps in orientation, thus rapidly overcoming barriers that usually inhibit rotation. Moreover, the rotational dynamics can be tuned via protein size and solution chemistry, providing tools for controlling biomolecular assembly at inorganic interfaces.
Measuring the polarization reconstruction resolution of the ARIANNA neutrino detector with cosmic rays
Authors: Anker A. , Baldi P. , Barwick S.W. , Beise J. , Besson D.Z. , Bouma S. , Cataldo M. , Chen P. , Gaswint G. , Glaser C. , Hallgren A. , Hallmann S. , Hanson J.C. , Klein S.R. , Kleinfelder S.A. , Lahmann R. , Liu J. , Magnuson M. , McAleer S. , Meyers Z.S. , Nam J. , Nelles A. , Novikov A. , Paul M.P. , Persichilli C. , Plaisier I. , Pyras L. , Rice-Smith R. , Tatar J. , Wang S.-H. , Welling C. , Zhao L. 
Published: April 2022

Abstract
The ARIANNA detector is designed to detect neutrinos with energies above 1017 eV. Due to the similarities in generated radio signals, cosmic rays are often used as test beams for neutrino detectors. Some ARIANNA detector stations are equipped with antennas capable of detecting air showers. Since the radio emission properties of air showers are well understood, and the polarization of the radio signal can be predicted from the arrival direction, cosmic rays can be used as a proxy to assess the reconstruction capabilities of the ARIANNA neutrino detector. We report on dedicated efforts of reconstructing the polarization of cosmic-ray radio pulses. After correcting for difference in hardware, the two stations used in this study showed similar performance in terms of event rate and agreed with simulation. Subselecting high quality cosmic rays, the polarizations of these cosmic rays were reconstructed with a resolution of 2.5° (68% containment), which agrees with the expected value obtained from simulation. A large fraction of this resolution originates from uncertainties in the predicted polarization because of the contribution of the subdominant Askaryan effect in addition to the dominant geomagnetic emission. Subselecting events with a zenith angle greater than 70° removes most influence of the Askaryan emission, and, with limited statistics, we found the polarization uncertainty is reduced to 1.3° (68% containment).
Classification of Fermi-LAT blazars with Bayesian neural networks
Authors: Butter Anja , Finke Thorben , Keil Felicitas , Krämer Michael , Manconi Silvia 
Published: April 2022

Abstract
The use of Bayesian neural networks is a novel approach for the classification of γ-ray sources. We focus on the classification of Fermi-LAT blazar candidates, which can be divided into BL Lacertae objects and Flat Spectrum Radio Quasars. In contrast to conventional dense networks, Bayesian neural networks provide a reliable estimate of the uncertainty of the network predictions. We explore the correspondence between conventional and Bayesian neural networks and the effect of data augmentation. We find that Bayesian neural networks provide a robust classifier with reliable uncertainty estimates and are particularly well suited for classification problems that are based on comparatively small and imbalanced data sets. The results of our blazar candidate classification are valuable input for population studies aimed at constraining the blazar luminosity function and to guide future observational campaigns.
Two-dimensional continuum percolation models with disks under the generalized Achlioptas process
Authors: Sun Weiqin , Qing Yuqi , Chen Fuxing , Liu Maoxin 
Published: April 2022

Abstract
We investigate the disk percolation phase transitions in continuum models in two dimensions under four kinds of generalized product rule and four kinds of generalized sum rule, respectively. We study the critical behaviors of the largest, second largest clusters and their size ratio to characterize the universality class of percolation transition. Using the finite size scaling analysis and the Monte Carlo simulation, we calculate the critical exponents of the percolation transitions under the above rules. We find that the universality classes of continuum percolation under the generalized product rule, under the generalized sum rule, and the lattice percolation are different.
Numerical simulation of a low Prandtl number flow with a four-parameters turbulence model through an explicit algebraic definition of Reynolds stress and turbulent heat flux
Authors: Barbi G , Chierici A , Chirco L , Giovacchini V , Manservisi S , Sirotti L 
Published: April 2022

Abstract
Computational Fluid Dynamics codes usually adopt the Reynolds analogy in order to simulate dynamic and thermal flow fields for ordinary fluids like water and air. On the other hand, in low Prandtl fluids, such as heavy liquid metals like Lead-Bismuth Eutectic (LBE), the time scales of temperature and velocity fields are rather different and therefore similarity hypothesis cannot be used. Furthermore, to properly predict a complex flow field characterized by anisotropic behavior, it is necessary to overcome eddy-viscosity models and move to more advanced turbulence models. In the present work, we propose a nonlinear method for the computation of the Reynolds stress tensor and of the turbulent heat flux. Explicit algebraic models (EAM) and new time scales have been implemented using a logarithmic four parameters turbulence model (i.e. K-Ω-K
θ
-Ω
θ
). This new model is validated through the simulation of plane channel and cylinder flows and results are compared with DNS data.
Numerical Model of an Evaporative Condenser for the Food Refrigeration Industry
Authors: Giovannini Michael , Lorenzini Marco 
Published: April 2022

Abstract
Evaporative condensers play a key role in refrigeration plants for industrial applications, as they are needed to dispose of the thermal and electric power required by the process. Modelling them as lumped capacitance systems is very expedient when trying to simulate e. g. the steady-state and dynamic behaviour of the whole refrigeration plant, but at the expenses of loss of information and often oversimplifying assumptions. This paper analyses two models for heat and mass transfer in cooling equipment, Poppe’s and its earlier, simpler version, Merkel’s. The two approaches are applied to describe the transport phenomena in an evaporative condenser and the predicted cooling power compared to the data declared by the manufacturer under certain operating conditions. It is demonstrated that predictions are accurate within less than 10%.
A numerical approach to the fractional Laplacian operator with applications to quasi-geostrophic flows
Authors: Barbi G , Capacci D , Chierici A , Chirco L , Giovacchini V , Manservisi S 
Published: April 2022

Abstract
The quasi-geostrophic models have been very successful for the study of oceanic and atmospheric dynamics in the mid-to-high latitude region of the earth where the Coriolis effect is significant. The governing equation of a quasi-geostrophic model is a transport equation with a fractional dissipation term. Although fractional operators have become a topic of great interest in the research community, the numerical discretization of such operators is very challenging due to their non-local behavior. In this work, we propose the numerical approximations of the bounded fractional Laplacian on a finite element discretization. In particular, we rely on the Riesz method and use a semi-analytical technique to approximate all the integrals involving the interaction between the inner local and the outer region. We test the implemented algorithm with numerical benchmarks, and we apply it to quasi-geostrophic flows. All the presented simulations are computationally expensive, due to the non-local behavior of the fractional Laplacian. For this reason, a parallel implementation of the numerical code has been developed.
Analysis of Fukushima Daiichi unit 4 spent fuel pool using MELCOR
Authors: D’Onorio M. , Maggiacomo A. , Giannetti F. , Caruso G. 
Published: April 2022

Abstract
A spent fuel pool is a temporary storage facility designed to store the nuclear fuel assemblies removed from the reactor core. Here, the depleted fuel is vertically arranged in racks structures, accurately spaced to ensure subcriticality safety margins. Until the events occurred at the Fukushima Daiichi power plants, severe accidents in spent fuel pools had never been considered as a major safety concern, mainly because of their slow progression. However, extremely unlikely accident events, aggravated by the loss of site power, highlighted the vulnerability of nuclear fuel stored within spent fuel pools. During these accident sequences, reactor fuel rods can generate enough decay heat to vaporize the coolant around them, causing, during unmitigated scenarios, the uncovering and melting of fuel bundles after several days. In past years, new features have been introduced in the MELCOR code for the evaluation of potential risks associated to accident progression in spent fuel pools. In this paper, the accidental sequence of a loss of cooling accident in a boiling water reactor spent fuel pool is analysed with version 2.2 of the MELCOR code. The spent fuel pool of the Fukushima Daiichi unit 4 has been selected as reference. Main accident events, such as fuel uncovering, claddings oxidation, hydrogen generation, and fission products release, have been analysed assuming the unavailability of safety systems.
elastoCaloric (eC) Cooling: recent studies and preliminary results on materials and devices
Authors: Cirillo Luca , Farina Adriana Rosaria , Greco Adriana , Masselli Claudia 
Published: April 2022

Abstract
Refrigeration is a process aimed at lowering the temperature of an environment compared to the outside temperature. It has always played a fundamental role in modern industry: food, for the preservation of food; in the air conditioning of buildings, to make them habitable and even in the field of medicine and biology, for the preservation of samples and particular therapies. Today refrigeration systems, are responsible for about 17% of the world's electricity consumption. Therefore, the scientific community is researching solid-state refrigeration, which is 50% more efficient than vapour compression systems. Solid-state refrigeration is based on some materials' caloric effect, which can release or absorb latent heat when subjected to an external field (magnetic, electric, pressure or strain) release. Elastocaloric Refrigeration is one of the most minor explored frontiers, unlike magnetocaloric and electro-caloric systems. Some preliminary studies confirm that the eC systems have the advantage of being able to decrease the intensity of the external field (with a relative increase of the COP). In this work, a review on Ec systems is carried out, with particular attention to the description of the properties of the materials used, the various types of stress application. The results have been presented in terms of temperature, entropy, latent heat and COP.
Functionally-graded foams for volumetric solar receivers
Authors: Iasiello M. , Chiu W. K. S. , Andreozzi A. , Bianco N. , Naso V. 
Published: April 2022

Abstract
The open volumetric receiver, one of the most important components of a Concentrated Solar Power (CSP) plant, is made up by a ceramic foam on which the concentrated solar radiation impinges. Ceramic foams are employed in volumetric solar receivers because of their high specific surfaces and their operating temperatures higher than those of metal foams. Thermo- fluid-dynamics in the graded ceramic foam of a volumetric solar air receiver for concentrated solar power is investigated numerically. Variable porosities and Pores Per Inch (PPI), according to different power laws, are accounted for. Governing equations are written with the Volume Averaging Technique (VAT) and are solved with the commercial software Comsol Multiphysics. The effects of different porosity and PPI laws, on the fluid velocity, pressure drop and temperatures, under different thermo-fluid-dynamic conditions, are highlighted.
Adiabatic frictional pressure gradient during flow boiling of pure refrigerant R1233zd and non-azeotropic mixtures R448A, R452A and R455A
Authors: Arcasi A , Mastrullo R , Mauro A W , Viscito L 
Published: April 2022

Abstract
The research on two-phase flow characteristics of refrigerants is of primary importance in several fields, such as air conditioning and refrigeration systems. Therefore, the determination of the pressure drop during flow boiling is important for the correct design of evaporators and heat spreaders systems. This paper presents a collection of experiments on flow boiling pressure drop using pure refrigerant R1233zd and new low-GWP refrigerant mixtures R448A, R452A and R455A. All tests were performed in adiabatic conditions, in a smooth horizontal stainless-steel tube having an internal diameter of 6.0 mm and a thickness of 1.0 mm. The effect of operating parameters, such as (bubble) saturation temperature (from 25 to 65 °C) and mass flux (from 150 to 600 kg/m2s) is investigated and discussed, and the performance of the chosen fluids is also compared. Finally, an assessment of existing prediction methods is carried-out to find the most suitable correlations for two-phase pressure drop evaluation.