bluuebunny/crossref_metadata_2025 huggingface dataset:
Biomarkers for immunotherapy for treatment of glioblastoma
Authors: Lynes John P , Nwankwo Anthony K , Sur Hannah P , Sanchez Victoria E , Sarpong Kwadwo A , Ariyo Oluwatobi I , Dominah Gifty A , Nduom Edjah K
Published: May 2020

Immunotherapy is a promising new therapeutic field that has demonstrated significant benefits in many solid-tumor malignancies, such as metastatic melanoma and non-small cell lung cancer. However, only a subset of these patients responds to treatment. Glioblastoma (GBM) is the most common malignant primary brain tumor with a poor prognosis of 14.6 months and few treatment advancements over the last 10 years. There are many clinical trials testing immune therapies in GBM, but patient responses in these studies have been highly variable and a definitive benefit has yet to be identified. Biomarkers are used to quantify normal physiology and physiological response to therapies. When extensively characterized and vigorously validated, they have the potential to delineate responders from non-responders for patients treated with immunotherapy in malignancies outside of the central nervous system (CNS) as well as GBM. Due to the challenges of current modalities of radiographic diagnosis and disease monitoring, identification of new predictive and prognostic biomarkers to gauge response to immune therapy for patients with GBM will be critical in the precise treatment of this highly heterogenous disease. This review will explore the current and future strategies for the identification of potential biomarkers in the field of immunotherapy for GBM, as well as highlight major challenges of adapting immune therapy for CNS malignancies.
Tocilizumab, but not dexamethasone, prevents CRS without affecting antitumor activity of bispecific antibodies
Authors: Kauer Joseph , Hörner Sebastian , Osburg Lukas , Müller Stefanie , Märklin Melanie , Heitmann Jonas S , Zekri Latifa , Rammensee Hans-Georg , Salih Helmut R , Jung Gundram
Published: May 2020

Bispecific antibodies (bsAb) and chimeric antigen receptor (CAR) T cells allow for antibody guided recruitment of T cells against tumors. Both are successfully used for treatment of CD19 expressing leukemias, but may cause cytokine release syndrome (CRS) as a major dose-limiting side effect. For CRS prevention, steroids are recommended prior to bsAb treatment, despite their well-known lymphotoxic activity. The IL-6 receptor antibody tocilizumab is established for treatment of CRS induced by CAR T cells, but was not considered for CRS prevention in bsAb therapy. We here compared the influence of dexamethasone and tocilizumab on bsAb-mediated T cell proliferation and tumor lysis in vitro and in vivo and found that dexamethasone profoundly inhibited T cell proliferation and antitumor activity as induced by two different bsAb, particularly at low effector:target ratios, whereas tocilizumab did not affect efficacy. When we applied tocilizumab early during treatment of three patients with a newly developed PSMAxCD3 bsAb, significant CRS attenuation despite high IL-6 serum levels was observed. Thus, early IL-6 blockade may reduce the undesired sequelae of CRS upon bsAb therapy without affecting therapeutic activity, allowing in turn for safe application of effective doses.
Anesthesia residency training in regional anesthesiology and acute pain medicine: a competency-based model curriculum
Authors: Woodworth Glenn , Maniker Robert B , Spofford Christina M , Ivie Ryan , Lunden Nathalie I , Machi Anthony T , Elkassabany Nabil M , Gritsenko Karina , Kukreja Promil , Vlassakov Kamen , Tedore Tiffany , Schroeder Kris , Missair Andres , Herrick Michael , Shepler John , Wilson Elizabeth H , Horn Jean-Louis , Barrington Michael
Published: May 2020

The Accreditation Council for Graduate Medical Education has shifted to competency-based medical education. This educational framework requires the description of educational outcomes based on the knowledge, skills and behaviors expected of competent trainees. It also requires an assessment program to provide formative feedback to trainees as they progress to competency in each outcome. Critical to the success of a curriculum is its practical implementation. This article describes the development of model curricula for anesthesiology residency training in regional anesthesia and acute pain medicine (core and advanced) using a competency-based framework. We further describe how the curricula were distributed through a shared web-based platform and mobile application.
Adjuncts to local anesthetic wound infiltration for postoperative analgesia: a systematic review
Authors: Bai Johnny Wei , An Dong , Perlas Anahi , Chan Vincent
Published: May 2020

Local anesthetics (LAs) are commonly infiltrated into surgical wounds for postsurgical analgesia. While many adjuncts to LA agents have been studied, it is unclear which adjuncts are most effective for co-infiltration to improve and prolong analgesia. We performed a systematic review on adjuncts (excluding epinephrine) to local infiltrative anesthesia to determine their analgesic efficacy and opioid-sparing properties. Multiple databases were searched up to December 2019 for randomized controlled trials (RCTs) and two reviewers independently performed title/abstract screening and full-text review. Inclusion criteria were (1) adult surgical patients and (2) adjunct and LA agents infiltration into the surgical wound or subcutaneous tissue for postoperative analgesia. To focus on wound infiltration, studies on intra-articular, peri-tonsillar, or fascial plane infiltration were excluded. The primary outcome was reduction in postoperative opioid requirement. Secondary outcomes were time-to-first analgesic use, postoperative pain score, and any reported adverse effects. We screened 6670 citations, reviewed 126 full-text articles, and included 89 RCTs. Adjuncts included opioids, non-steroidal anti-inflammatory drugs, steroids, alpha-2 agonists, ketamine, magnesium, neosaxitoxin, and methylene blue. Alpha-2 agonists have the most evidence to support their use as adjuncts to LA infiltration. Fentanyl, ketorolac, dexamethasone, magnesium and several other agents show potential as adjuncts but require more evidence. Most studies support the safety of these agents. Our findings suggest benefits of several adjuncts to local infiltrative anesthesia for postoperative analgesia. Further well-powered RCTs are needed to compare various infiltration regimens and agents.

Protocol registration

PROSPERO (CRD42018103851) (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=103851)
New insights into the systemic effects of oral lactoferrin: transcriptome profiling
Authors: Kruzel Marian L. , Olszewska Paulina , Pazdrak Barbara , Krupinska Anna M. , Actor Jeffrey K.
Published: May 2020

The immunomodulatory nature of lactoferrin (LF) derives from its ability to bridge innate and adaptive immunity in obtaining physiological equilibrium. LF is an attractive molecule for treatment of diseases that compromise immune homeostasis. Oral delivery is a preferable method for LF administration; however, its bioavailability is affected by protein degradation and absorption. The aim of this study was to evaluate the systemic effects of orally and intravenously (IV) administered recombinant human LF (rhLF) on blood cell transcriptome profiling. Rats were administered a single dose of rhLF by gavage or IV. The transcriptome profiles from the control and the rhLF-treated rats after 3, 6, and 24 h were analyzed using a Clariom D microarray. The results showed differentially expressed genes in response to IV as well as oral administered rhLF including coding and noncoding RNAs. Moreover, a comparison of the differentially expressed genes between oral and IV administration of LF, after 6 h, revealed that the majority (72.8%) of the genes altered in response to oral administration of rhLF were the same as for the IV treatment. The pathway profiles showed similarities in up-regulation of specific genes involved in oxidative stress and inflammatory responses for both routes of treatments. These findings provide evidence of the systemic signal transduction effects of orally administered rhLF.
Absence of genetic structure reflects post-glacial history and present-day host use in Mapleleaf (Quadrula quadrula) mussel from Manitoba, Canada
Authors: VanTassel N.M. , Beaver C.E. , Watkinson D.A. , Morris T.J. , Zanatta D.T.
Published: May 2020

Our study documents and analyzes the absence of genetic diversity and structure of the Mapleleaf (Quadrula quadrula (Rafinesque, 1820)) (Bivalvia: Unionidae) mussel in the Lake Winnipeg, Assiniboine River, and Red River drainages (Manitoba, Canada). Previous studies have revealed patterns of genetic diversity and structure in the Mississippi and Ohio river drainages, as well as in the Laurentian Great Lakes drainage. Genotypes from six variable microsatellite loci showed that the Q. quadrula population in Manitoba was significantly differentiated from the population in the Great Lakes drainage (Ontario, Canada), supporting the existence of two Designatable Units in Canada. Conversely, there was no evidence of genetic structure within the sampled range of Q. quadrula in Manitoba. The lack of genetic structure in Q. quadrula across its distribution in Manitoba reflected its post-glacial history and use of a vagile host and necessitates that efforts should be made to ensure connectivity and maintain gene flow across the region. Given that the evidence suggests that Manitoba Q. quadrula belong to a single genetic population, movement of hatchery-propagated juvenile Q. quadrula, adult Q. quadrula, or glochidia-carrying host catfish sourced from any location in Manitoba could be used to augment declining populations or at-risk locations in Manitoba.
Novel POC Bionanosensor for Direct Detection of RNA-Virus Infections in Minutes
Authors: Maung May , Cui Chengde , Sinha Saion
Published: May 2020

Viral infections (like different types of influenza virus) are becoming alarmingly common often leading to epidemics. Since Viruses can multiply from genomic materials it can spread the infection quickly as well as cause other complications like birth defects, autoimmune disease and even cancer. Diagnostics of viral infection traditionally is performed using antigen-antibody reaction, which is time consuming and labor intensive. Also, viral infections can be latent or show false negative results when antibody reaction is tested. In-situ direct hybridization detection is possible by expensive, long and difficult radiation-based methods. Our group has developed a Carbon Nanotube (CNT) & Graphene based Bionanosensor (BNS) for rapid and direct detection of specific DNA sequences. In this technique, single-stranded (ss) DNA probe (known as priming) is immobilized on a substrate. This recognizes a specific complementary target DNA in a sample solution and gets hybridized leading to a detectable electrical signal. In this study we have expanded the scope of this BNS by using it to detect quick in-situ RNA hybridization. A sample of RNA was tested simultaneously in an array of 4 biosensors (each primed by the complementary sequence). The resistance across each of the biosensors was measured with a self-designed, feed-back controlled, balanced Wheatstone bridge circuit with an Arduino interface. A specific pattern related to hybridization was observed and a weighted average performed over 30 experiments. The sensors primed with the forward RNA was able to detect the complementary sequence in a mixed sample in 10 minutes from the starting time.
Thin Film Deposition and Carbon Nanotube Synthesis
Authors: Frey Jerome , Schwendemann Todd C.
Published: May 2020

Carbon nanotubes (CNTs) are a viable product for many different markets. One specific area of promise is the use of CNTs in supercapacitors. The CNT synthesis is a two-step process with the first being the formation of a thin film layer. The thin film substrate is created by means of the Thermal Evaporation Physical Vapor Deposition (TPVD) process. After the thin film substrate is deposited, the CNTs are grown in a Chemical Vapor Deposition (CVD) growth chamber. Analysis of the thin film substrate and CNTs is performed primarily using Scanning Electron Microscopy (SEM). The results show the inclusion of ultrapure water in the CVD process contributed to the success of CNT growth. Multiple prong CNT grow is seen for CVDs trails of silver thin film layer deposited on silicon substrates. The silver nanoparticle had a large diameter with an acute contact angle. The single prong growth indicates the iron nanoparticles formed an obtuse contact angle due to the amorphic surface of alumina substrate. The focus of this project is to explore and investigate different materials and conditions for optimal CNT synthesis in the hopes of creating a uniform forest of vertically aligned carbon nanotubes.
Comparative Study on in-situ Ellipsometric Monitoring of III-Nitride Film Growth via Plasma-Enhanced Atomic Layer Deposition
Authors: Mohammad Adnan , Shukla Deepa , Ilhom Saidjafarzoda , Willis Brian , Okyay Ali Kemal , Biyikli Necmi
Published: May 2020

In this paper a comparative in-situ ellipsometric analysis is carried out on plasma-assisted ALD-grown III-nitride (AlN, GaN, and InN) films. The precursors used are TMA, TMG, and TMI for AlN, GaN, and InN respectively, while Ar is used as purge gas. For all of the films N2/H2/Ar plasma was used as the co-reactant. The work includes real-time in-situ monitored saturation curves, unit ALD cycle analysis, and >500 cycle film growth runs. In addition, the films are grown at different substrate temperatures to observe the impact of temperature not only on the growth rate but on how it influenced the precursor chemisorption, ligand removal, and nitrogen incorporation surface reactions. All three nitride films confirm fairly linear growth character. The growth rate per cycle (GPC) for each film is also measured with respect to rf-plasma power to obtain the surface saturation conditions during ALD growth. The real-time in-situ monitoring of the film growth can really be beneficial to understand the atomic layer growth and film formation in each individual ALD cycle.
Masked FPGA Bitstream Encryption via Partial Reconfiguration
Authors: Gong Yanping , Qian Fengyu , Wang Lei
Published: May 2020

Field Programmable Gate Arrays (FPGA), as one of the popular circuit implementation platforms, provide the flexible and powerful way for different applications. IC designs are configured to FPGA through bitstream files. However, the configuration process can be hacked by side channel attacks (SCA) to acquire the critical design information, even under the protection of encryptions. Reports have shown many successful attacks against the FPGA cryptographic systems during the bitstream loading process to acquire the entire design. Current countermeasures, mostly random masking methods, are effective but also introduce large hardware complexity. They are not suitable for resource-constrained scenarios such as Internet of Things (IoT) applications. In this paper, we propose a new secure FPGA masking scheme to counter the SCA. By utilizing the FPGA partial reconfiguration feature, the proposed technique provides a light-weight and flexible solution for the FPGA decryption masking.
Modeling of Multi-State Si and Ge Cladded Quantum Dot Gate FETs Using Verilog and ABM Simulations
Authors: Gudlavalleti R. H. , Saman B. , Mays R. , Lingalugari M. , Heller E. , Chandy J. , Jain F.
Published: May 2020

Quantum dot gate (QDG) field-effect transistors (FETs) fabricated using Si and Ge quantum dot layers, self-assembled in the gate region over the tunnel oxide, have exhibited 3- and 4-state behavior applicable for ternary and quaternary logic, respectively. This paper presents simulation of QDG-FETs comprising mixed Ge and Si quantum dot layers over tunnel oxide using an analog behavior model (ABM) and Verilog model. The simulations reproduce the experimental I-V characteristics of a fabricated mixed dot QDG-FET. GeOx-cladded Ge quantum dot layer is in interface to the tunnel oxide and is deposited over with a SiOx-cladded Si quantum dot layer. The fabricated QDG-FET has one source and one gate. The ABM simulation models QDG-FET using conventional BSIM 3V3 FETs with capacitances and other device parameters. In addition, VERILOG model is presented. The agreement in circuit and quantum simulations and experimental data will further advance in the designing of QDG-FET-based analog-to-digital converters (ADCs), 2-bit logic gates and SRAM cells.
Tetramethylpyrazine Attenuated Sevoflurane-Induced Neurotoxicity by Enhancing Autophagy through GPR50/CREB Pathway in SH-SY5Y Cells
Authors: Xu Lili , Shen Jianjun , Dai Shaobing , Sun Lihong , Chen Xinzhong
Published: May 2020

Tetramethylpyrazine has shown neuroprotective and axonal outgrowth-promoting effects and can improve cognitive deficit in a rat model of chronic hypoperfusion. However, the role of tetramethylpyrazine in sevoflurane-induced neurotoxicity is still vague. Therefore, this study was designed to investigate the effects and mechanisms of tetramethylpyrazine on sevoflurane-induced autophagy, apoptosis, and the expression of BACE1 and A[Formula: see text] in SH-SY5Y cells. We measured the expression levels of the apoptosis protein markers Bax and Bcl-2, autophagy protein markers Atg5 and LC3-II, BACE1, and A[Formula: see text] in SH-SY5Y cells after sevoflurane treatment and determined the effects of tetramethylpyrazine on sevoflurane-induced expression of these proteins after silencing GPR50 or Atg5 with siRNA in vitro. We found that exposure to 3.4% sevoflurane for 6 h decreased the expression of autophagy protein markers and increased the expression of the apoptosis protein markers, BACE1, and A[Formula: see text] in SH-SY5Y cells. The number of red puncta (autolysosomes) and yellow puncta (autophagosomes) in each SH-SY5Y cell decreased after transient transfection with the mRFP-GFP-LC3 expression plasmid. Silencing of GPR50 decreased the expression of pCREB, Atg5, and LC3-II, while silencing of Atg5 increased the expression of BACE1 and A[Formula: see text] in SH-SY5Y cells. Our results demonstrate that tetramethylpyrazine attenuated sevoflurane-induced neurotoxicity by enhancing autophagy through the GPR50/CREB pathway in SH-SY5Y cells.
Lancemaside A Isolated from the Root of Codonopsis lanceolata Inhibits Ovarian Cancer Cell Invasion via the Reactive Oxygen Species (ROS)-Mediated p38 Pathway
Authors: Ahn Ji-Hye , Jang Dae Sik , Choi Jung-Hye
Published: May 2020

Codonopsis lanceolata roots have been widely used in Korean cuisine and traditional medicine. This study aimed to investigate the antimetastatic effects of lancemaside A, a major triterpenoid saponin, isolated from the roots of C. lanceolata, in human ovarian cancer cells. Lancemaside A significantly suppressed the migration and invasion and the expression of matrix metalloproteinases (MMPs)-2 and -9 in ovarian cancer A2780 and SKOV3 cells. Treatment with lancemaside A generated reactive oxygen species (ROS) in ovarian cancer cells. However, treatment with anti-oxidant N-acetyl-L-cysteine (NAC) significantly negated the anti-invasive activity of lancemaside A. Additionally, lancemaside A activated p38 MAP kinase, which is mediated by ROS generation. This is the first study, to our knowledge, to reveal that lancemaside A isolated from the roots of C. lanceolata exerts antimetastatic activity through inhibition of MMP expression and cancer cell invasion via activation of the ROS-mediated p38 pathway.
Unsteady flow simulation of a variable-sweep morphing aircraft coupled with flight control system
Authors: Guo Zhong-Zhou , Dai Gang , Yang Hua , Chen Wei-Fang
Published: May 2020

Morphing aircraft has adjustable aerodynamic shapes and is suitable for variable flight conditions. And there have been growing interests in recent years. However, the forces and moments are highly nonlinear, bringing challenges in design and modeling of flight control system (FCS). In this paper, unsteady Computational Fluid Dynamics (CFD) simulations are performed by solving the Arbitrary Lagrangian–Eulerian (ALE) governing equations on unstructured dynamic mesh, then unsteady aerodynamic characteristics of a variable-sweep morphing aircraft at hypersonic speed are acquired. The nonlinearity index theory is employed to analyze the nonlinearity of pitching moments. FCS is designed using nonlinear dynamic inversion control, taking attitude angles and sweep angle into consideration. Unsteady flow simulation is performed using unsteady CFD coupled with FCS. Cases of open and close loop morphing flight over the variation of sweep angle corresponding to flight conditions are studied. Results show that the nonlinearity of unsteady forces and moments are significant. The combination of unsteady CFD and FCS provides a powerful approach to the study of morphing aircraft.
A DDES study of the flow past a prolate spheroid using a high-order U-MUSCL scheme
Authors: Yang Yu-Chen , Wang Zhen-Ming , Zhao Ning
Published: May 2020

Flow past a prolate spheroid, which is a representative simplified configuration for vehicles such as maneuvering ships, submarines and missiles, comprises a series of complex flow phenomena including pressure-induced flow separation, which results in unsteady forces and movements that may be detrimental to vehicles’ performance. In this paper, a Delayed Detached Eddy Simulation (DDES) method combined with a new high-order U-MUSCL scheme is proposed to more precisely and accurately capture the flow separation and vortex structure. This method is applied to simulate the aerodynamic performance of the 6:1 prolate spheroid at an AOA of [Formula: see text] with the Reynolds number of [Formula: see text]. Axial pressure distribution of five individual chord wise sections and flow field structure of the aft body are analyzed. Numerical results agree well with the experimental data. It can be concluded that DDES combined with three-order U-MUSCL scheme demonstrates reliable performance since it captures the vortex structure of aft body distinctly and predicts the separation and reattachment points of the secondary vortex precisely.
Effects of inlet turbulence intensity on wall heat transfer in a turbine guide vane
Authors: Hu Ke-Qi , Xia Yi-Fan , Zheng Yao , Wang Gao-Feng
Published: May 2020

Heat transfer is an important phenomenon that exists in many industrial applications, especially for gas turbines, aeronautical engines. In this work, two different turbulence models ([Formula: see text] and SAS model) are used to investigate the effects of inlet turbulence on wall heat transfer and the characteristics of flow field in a well-known turbine guide vane (LS89). In order to handle the transition, Menter’s [Formula: see text] transition model is used. The simulations show that the inlet turbulence has an apparent effect on the wall heat transfer of the vane. Not only the maximum wall heat transfer coefficient is increased, the distribution of wall heat flux at the suction side is also modified. The isentropic Mach number along the vane surface is insensitive to the variance of inlet turbulence intensity. Besides, a shock appears in the throat and a laminar-to-turbulence transition position moves forward after the main flow turbulence is enhanced. Moreover, the results indicate that SAS model is capable of capturing more flow structures such as reflecting pressure waves and shedding vortexes while the [Formula: see text] model misses them due to the dissipation.
Rebuilding experimental nonequilibrium radiation in shock-heated Martian-like mixture flows using electronic state-to-state approach
Authors: Hong Qizhen , Wang Xiaoyong , Hu Yuan , Lin Xin , Sun Quanhua
Published: May 2020

An electronic state-to-state approach is developed to reproduce numerically the radiative processes in the experiments on the Electric Arc Shock Tube facility at NASA Ames Research Center. The experiments measured the spectral radiance of C2 Swan band and CO 4th Positive band behind the strong shock wave in a Martian-like mixture. The present state-to-state approach solves the electronic states of strong radiators by integrating the collisional-radiative model into the master equations in the frame of Euler equations. Particularly, the electron impact dissociation of CO is included, and the rate coefficients are proposed for the electronic state-specific heavy-particle impact excitation and dissociation of C2. The nonequilibrium radiation behind the shock is calculated by the line-by-line method, and it is then convoluted using the calibrated smearing function in order to compare with the experiments. The state-specific simulation results is found to agree well with both spectral and spatial measurement data. The simulated electronic state populations of CO and C2 deviate from Boltzmann distributions significantly, which could explain the failure of previous two-temperature quasi-steady-state based simulations.
The hydrodynamic FORCE of fluid–structure interaction interface in lattice Boltzmann simulations
Authors: Tong Ying , Xia Jian
Published: May 2020

The hydrodynamic force (HF) evaluation plays a critical role in the numerical simulation of fluid–structure interaction (FSI). By directly using the distribution functions of lattice Boltzmann equation (LBE) to evaluate the HF, the momentum exchange algorithm (MEA) has excellent features. Particularly, it is independent of boundary geometry and avoids integration on the complex boundary. In this work, the HF of lattice Boltzmann simulation (LBS) is evaluated by using the MEA. We conduct a comparative study to evaluate two lattice Boltzmann models for constructing the flow solvers, including the LBE with single-relaxation-time (SRT) and multiple-relaxation-time (MRT) collision operators. The second-order boundary condition schemes are used to address the curve boundary. The test case of flow past a cylinder asymmetrically placed in a channel is simulated. Comparing the numerical solutions of Lattice Boltzmann method (LBM) with those of Navier–Stokes equations in the literature, the influence of collision relaxation model, boundary conditions and lattice resolution is investigated. The results demonstrate that the MRT-LB improves the numerical stability of the LBM and the accuracy of HF.
Mixing character in the head part of a gravity current
Authors: Su Zhuang
Published: May 2020

The mixing within a full depth lock-exchange gravity current was investigated experimentally with planar laser-induced fluorescence PLIF. The scalar edge of the gravity current was identified via an edge detection algorithm. A strong mixing region located along this edge was extracted from the flow field and analyzed. A dimensionless background potential energy was defined to characterize the local mixing rate in this region, which showed a two-stage behavior. In the section near the nose, mixing rate oscillates strongly under the influence of the lobe and cleft shifting, while in the upper part, the mixing rate grows gradually under the mechanism of billows rolling up.
Investigating in novel CdZnSe/CdSe/CdZnSe quantum well with 97% PLQY
Authors: Zou Shi-Bing , Fan Hao , Yang Hao , Feng Lu-Xin , Duan Jun-Hong , Liu Wei-Qing , Wu Hua-Ming
Published: May 2020

Thick-shell not only provides colloidal quantum dots (QDs) stability and workability, but also plays a significant role in passivation of QDs surface defects and change of electron transport characteristics of QDs. Here, the dedicated design and synthesis of high luminescence CdZnSe/CdSe/CdZnSe quantum wells are reported by precisely controlled shell growth. By tuning the thicknesses of the CdSe and CdZnSe layers, photoluminescence quantum yields (PLQY) can be attained a maximum of 97% as the CdSe shell thickness is 4 monolayers and the CdZnSe shell thickness is 10 monolayers. These gradient thick shell CdZnSe/CdSe/CdZnSe quantum wells confirm the suppression of surface trap-state emission in gradient core/shell structures. Superior optical properties render CdZnSe/CdSe/CdZnSe quantum wells suitable for use in solid-state lightings.
An extended lattice hydrodynamic model with time delay based on non-lane discipline
Authors: Zhou Zhaomin , Zhao Min , Sun Di-Hua , Chen Dong , Zhang Yicai , Wang Shihui
Published: May 2020

An extended lattice hydrodynamic model with time delay is proposed under non-lane discipline. We try to grasp the impacts of the non-lane discipline of the considered lattice sites. Linear stability analysis of the proposed model is executed and the stability criterion is obtained. Using the reductive perturbation method, we investigate nonlinear analysis of the proposed model and derive the mKdV equation and its solution, which could reveal the propagation of density waves. We analyze the effect of time delay, the ratio of lane deviation and the control coefficient on the stability of traffic flow via numerical experiments. We find that those indices play an important role in the stability of traffic flow. The longer the time delay, the more unstable the system becomes. Also, the ratio of lane deviation and the control coefficient is able to more quickly dissipate the traffic congestions occurring in traffic flow.
Ultra-compact on-chip optical filters with narrow bandwidth
Authors: Li Wei , Zhang Lingxuan , Sun Qibing , Zeng Chao , Li Xingyi , Fan Weichen , Lei Huiping , Wu Wei , Wang Guoxi
Published: May 2020

A novel scheme for integrated optical filters with narrow bandwidth is proposed to dramatically improve its compactness on the basis of slow-light waveguide, which provides a large optical path in a short geometry length. By introducing the one-dimensional grating waveguide (ODGW), a kind of slow-light waveguide, into a micro-ring resonator (MRR), the area of MRR is reduced by three orders of magnitude compared to the MRR without ODGW. As a proof of concept, an ultra-compact on-chip filter with narrow bandwidth of 2.1 pm (263 MHz) is conceived by cascading six MRRs with ODGW. Additionally, the designed optical filter shows excellent performances of roll-down speed, out-of-band signal suppression, and in-band ripple. Our proposal offers a promising solution to miniaturize the integrated optical filters with narrow bandwidth, and hence improve the integration density of on-chip photonic networks.
Modified partially averaged Navier–Stokes model for turbulent flow in passages with large curvature
Authors: Ye Weixiang , Luo Xianwu , Li Ying
Published: May 2020

This study presents a partially averaged Navier–Stokes model, MSST PANS, based on a modified SST [Formula: see text] turbulence model to predict turbulent flows with large streamline curvature. The model was validated for turbulent flow in a [Formula: see text] curved rectangular duct (Re = 224,000) to assess the MSST PANS capabilities. The predictions are compared against flow simulations for the same curved rectangular duct using four turbulence models including the standard [Formula: see text] model, SST [Formula: see text] model, [Formula: see text] PANS model and SST [Formula: see text] PANS model. Comparisons among those numerical results and available experimental data show that the MSST PANS model more accurately predicts the velocity components in all three directions, especially in the wall-bounded region than the other models. The study also shows the advantages of the MSST PANS model for predicting the Reynolds stresses, vorticity, and smaller scale turbulent structures in the wall-bounded region not only qualitatively but quantitatively. Furthermore, the MSST PANS model requires fewer computations than the SST PANS model, indicating that this turbulence model, which takes large streamlines curvature effects into consideration, is an effective alternative for capturing the small-scale turbulence flow structures. This turbulence model is expected to be very useful for engineering applications, especially for flows in turbomachinery.
SMILE MODELING IN COMMODITY MARKETS
Authors: NASTASI EMANUELE , PALLAVICINI ANDREA , SARTORELLI GIULIO
Published: May 2020

We present a stochastic local volatility model for derivative contracts on commodity futures able to describe forward curve and smile dynamics with a fast calibration to liquid market quotes. A parsimonious parametrization is introduced to deal with the limited number of options quoted in the market. Cleared commodity markets for futures and options are analyzed to include in the pricing framework-specific trading clauses and margining procedures. Numerical examples for calibration and pricing are provided for different commodity products.
Richards Growth Model Driven by Multiplicative and Additive Colored Noises: Steady-State Analysis
Authors: Xu Chaoqun , Yuan Sanling
Published: May 2020

We consider a Richards growth model (modified logistic model) driven by correlated multiplicative and additive colored noises, and investigate the effects of noises on the eventual distribution of population size with the help of steady-state analysis. An approximative Fokker–Planck equation is first derived for the stochastic model. By performing detailed theoretical analysis and numerical simulation for the steady-state solution of the Fokker–Planck equation, i.e., stationary probability distribution (SPD) of the stochastic model, we find that the correlated noises have complex effects on the statistical property of the stochastic model. Specifically, the phenomenological bifurcation may be caused by the noises. The position of extrema of the SPD depends on the model parameter and the characters of noises in different ways.
Information-Based Classification of Electroencephalography (EEG) Signals for Healthy Adolescents and Adolescents with Symptoms of Schizophrenia
Authors: Namazi Hamidreza
Published: May 2020

Analysis of the brain activity is the major research area in human neuroscience. Besides many works that have been conducted on analysis of brain activity in case of healthy subjects, investigation of brain activity in case of patients with different brain disorders also has aroused the attention of many researchers. An interesting category of works belong to the comparison of brain activity between healthy subjects and patients with brain disorders. In this research, for the first time, we compare the brain activity between adolescents with symptoms of schizophrenia and healthy subjects, by information-based analysis of their Electroencephalography (EEG) signals. For this purpose, we benefit from the Shannon entropy as the indicator of information content. Based on the results of analysis, EEG signal in case of healthy subjects contains more information than EEG signal in case of subjects with schizophrenia. The result of statistical analysis showed the significant variation in the Shannon entropy of EEG signal between healthy adolescents and adolescents with symptoms of schizophrenia in case of P3, O1 and O2 channels. The employed method of analysis in this research can be further extended in order to investigate the variations in the information content of EEG signal in case of subjects with other brain disorders versus healthy subjects.
The Sorry State of TLS Security in Enterprise Interception Appliances
Authors: Waked Louis , Mannan Mohammad , Youssef Amr
Published: May 2020

Network traffic inspection, including TLS traffic, in enterprise environments is widely practiced. Reasons for doing so are primarily related to improving enterprise security (e.g., phishing and malicious traffic detection) and meeting legal requirements (e.g., preventing unauthorized data leakage and copyright violations). To analyze TLS-encrypted data, network appliances implement a Man-in-the-Middle (MITM) TLS proxy by acting as the intended web server to a requesting client (e.g., a browser) and acting as the client to the actual/outside web server. As such, the TLS proxy must implement both a TLS client and a server and handle a large amount of traffic, preferably in real-time. However, as protocol and implementation layer vulnerabilities in TLS/HTTPS are quite frequent, these proxies must be at least as secure as a modern, up-to-date web browser and a properly configured web server (e.g., an A+ rating in SSLlabs.com). As opposed to client-end TLS proxies (e.g., as in several anti-virus products), the proxies in network appliances may serve hundreds to thousands of clients, and
any
vulnerability in their TLS implementations can significantly downgrade enterprise security.

To analyze TLS security of network appliances, we develop a comprehensive framework, combining and extending tests from existing work on client-end and network-based interception studies. We analyze 13 representative network appliances over a period of more than a year (including versions before and after notifying affected vendors, a total of 17 versions) and uncover several security issues. For instance, we found that four appliances perform no certificate validation at all, three use pre-generated certificates, and eleven accept certificates signed using MD5, exposing their clients to MITM attacks. Our goal is to highlight the risks introduced by widely used TLS proxies in enterprise and government environments, potentially affecting many systems hosting security, privacy, and financially sensitive data.
Threats to Online Advertising and Countermeasures
Authors: Chua Mark Yep-Kui , Yee George O. M. , Gu Yuan Xiang , Lung Chung-Horng
Published: May 2020

Online advertising, also known as web advertising or Internet marketing, is the means and process of promoting products and services on the Internet, and it has been one of the important business models for the Internet. Due to its lucrative nature and its large scale of adoption, it has also been a target for malicious parties with various attack aims such as getting a cut of online advertising revenues, obtaining a user’s privacy, and spreading malware. Over the years, a great deal of research has been conducted on online advertising. Recently, the health of the online advertising ecosystem has become more of a concern for both advertisers and regular Internet users. Advertising budgets have been abused, and Internet users’ privacy and security have been infringed. In this article, we broadly study threats to online advertising and trace the root causes from a systems point of view. Existing threat mitigation strategies are also reviewed and analyzed. To protect online advertising, which has been an essential funding source of many free Internet services, several challenges still need to be addressed, including the need for transparency of the advertising ecosystem and software vulnerabilities on the client-side. To overcome these challenges, we conclude by brainstorming some innovative ideas on some potentially interesting and useful research directions.
Thinking Unveiled
Authors: Shukla Diksha , KUNDU Partha Pratim , Malapati Ravichandra , Poudel Sujit , Jin Zhanpeng , Phoha Vir V.
Published: May 2020

Very few studies have explored linkages between physiological, such as electroencephalograph (EEG), and behavioral patterns, such as wrist movements. These linkages provide us a unique mechanism to predict one set of patterns from other related patterns. Unlike conventional biometrics, EEG biometrics are hard to spoof using standard presentation attack methods, given the intrinsic liveness resulting from the bounded randomness of EEG signals specific to an individual. In this article, we propose a novel attack on the EEG-based authentication systems by investigating and leveraging the strong correlation between hand movements and brain signals captured through the motion sensors on a smartwatch and the wearable EEG headset, respectively. Based on this technique, we can successfully estimate the user’s EEG signals from the stolen hand movement data while the user was typing on the keyboard. Our attack results on the EEG biometric authentication system show an increase in the mean equal error rates of the classifiers by between 180% and 360% based on a dataset of 59 users. In summary, our pilot study calls for a rethinking of EEG-based authentication mechanisms from the perspective of unique vulnerabilities, particularly for multimodal biometric systems involving a variety of wearable or mobile devices.
On CSI-Based Vital Sign Monitoring Using Commodity WiFi
Authors: Wang Xuyu , Yang Chao , Mao Shiwen
Published: May 2020

Vital signs, such as respiration and heartbeat, are useful for health monitoring because such signals provide important clues of medical conditions. Effective solutions are needed to provide contact-free, easy deployment, low-cost, and long-term vital sign monitoring. In this article, we present PhaseBeat to exploit channel state information, in particular, phase difference data to monitor breathing and heart rates with commodity WiFi devices. We provide a rigorous analysis of channel state information phase difference with respect to its stability and periodicity. Based on the analysis, we design and implement the PhaseBeat system with off-the-shelf WiFi devices and conduct an extensive experimental study to validate its performance. Our experimental results demonstrate the superior performance of PhaseBeat over existing approaches in various indoor environments.
Conformance Checking Methodology Across Discharge Summaries and Standard Treatment Guidelines
Authors: Chikka Veera Raghavendra , Karlapalem Kamalakar
Published: May 2020

Conformance checking of treatment plans in discharge summary data would facilitate the development of clinical decision support system, treatment plan quality assurance, and new treatment plan discovery. Conformance checking requires extraction of medical entities and relationships among them to form a computable representation of the treatment plan present in the discharge summary. We propose a workflow representation of patient’s discharge summary that is referred to as workflow instance. We employ a multi-layer perceptron neural network to extract relationships between medical entities to construct the workflow instance. The aim of this work is to check the conformance of the workflow instance against standard treatment plan. Standard treatment plans are extracted from the treatment guidelines provided on healthcare websites such as WebMD, Mayo Clinic, and Johns Hopkins. For each disease, these guidelines are curated, aggregated, and represented as a workflow specification. We commend multiple measures to compute the conformance of workflow instance with workflow specification. We validate our conformance checking methodology using discharge summary data of three diseases, namely colon cancer, coronary artery disease, and brain tumor, collected from THYME corpus and MIMIC III clinical database. Our approach and the solution can be used by hospitals and patients to determine adherence, gaps, and additions to standard treatment plans. Further, our work can facilitate to identify common errors and goodness in actual enactment of treatment plans, which can further lead to refinement of standard treatment plans.
Reliability Analysis for Unreliable FSM Computations
Authors: Sabet Amir Hossein Nodehi , Qiu Junqiao , Zhao Zhijia , Krishnamoorthy Sriram
Published: May 2020

Finite State Machines (FSMs) are fundamental in both hardware design and software development. However, the reliability of FSM computations remains poorly understood. Existing reliability analyses are mainly designed for generic computations and are unaware of the special error tolerance characteristics in FSM computations. This work introduces RelyFSM -- a state-level reliability analysis framework for FSM computations. By modeling the behaviors of unreliable FSM executions and qualitatively reasoning about the transition structures, RelyFSM can precisely capture the inherent error tolerance in FSM computations. Our evaluation with real-world FSM benchmarks confirms both the accuracy and efficiency of RelyFSM.
IoT-Inspired Smart Toilet System for Home-Based Urine Infection Prediction
Authors: Bhatia Munish , Kaur Simranpreet , Sood Sandeep K.
Published: May 2020

The healthcare industry is the premier domain that has been significantly influenced by incorporation of Internet of Things (IoT) technology resulting in smart healthcare application. Inspired by the enormous potential of IoT technology, this research provides a framework for an IoT-based smart toilet system, which enables home-based determination of Urinary Infection (UI) efficaciously. The overall system comprises a four-layered architecture for monitoring and predicting infection in urine. The layers include the Urine Acquisition, Urine Analyzation, Temporal Extraction, and Temporal Prediction layers, which enable an individual to monitor his or her health on daily basis and predict UI so that precautionary measures can be taken at early stages. Moreover, probabilistic quantification of urine infection in the form of Degree of Infectiousness (DoI) and Infection Index Value (IIV) were performed for infection prediction based on a temporal Artificial Neural Network. In addition, the presence of UI is displayed to the user based on a Self-Organized Mapping technique. For validation purposes, numerous experimental simulations were performed on four individuals for 60 days. Results were compared with different state-of-the-art techniques for measuring the overall efficiency of the proposed system.
Field Note on CVE-2019-11510
Authors: Koot Matthijs
Published: May 2020

This Field Note describes the case of a critical unauthenticated RCE vulnerability in an SSL-VPN product that remained unpatched at a large scale-up and until after exploits became public. Approximately 14,500 systems worldwide were reportedly unpatched at the end of August 2019. Two weeks after exploits emerged in public, both GCHQ and NSA released notices that the vulnerability was being exploited by APT actors. The present Field Note describes observations from the Netherlands and includes reflections in an attempt to stimulate thinking on how to improve the status quo, such as through coordinated proactive measures by CSIRTs.
Target-Focused Feature Selection Using Uncertainty Measurements in Healthcare Data
Authors: Goldstein Orpaz , Kachuee Mohammad , Karkkainen Kimmo , Sarrafzadeh Majid
Published: May 2020

Healthcare big data remains under-utilized due to various incompatibility issues between the domains of data analytics and healthcare. The lack of generalizable iterative feature acquisition methods under budget and machine learning models that allow reasoning with a model’s uncertainty are two examples. Meanwhile, a boost to the available data is currently under way with the rapid growth in the Internet of Things applications and personalized healthcare. For the healthcare domain to be able to adopt models that take advantage of this big data, machine learning models should be coupled with more informative, germane feature acquisition methods, consequently adding robustness to the model’s results. We introduce an approach to feature selection that is based on Bayesian learning, allowing us to report the level of uncertainty in the model, combined with false-positive and false-negative rates. In addition, measuring target-specific uncertainty lifts the restriction on feature selection being target agnostic, allowing for feature acquisition based on a target of focus. We show that acquiring features for a specific target is at least as good as deep learning feature selection methods and common linear feature selection approaches for small non-sparse datasets, and surpasses these when faced with real-world data that is larger in scale and sparseness.