bluuebunny/crossref_metadata_2025 huggingface dataset:
Isolated optic nerve involvement in acute lymphoblastic leukaemia: a red flag for early relapse
Authors: Azad Shorya Vardhan , Banerjee Mousumi , Parmanand Kumar , Venkatesh Pradeep
Published: June 2021

Acute lymphoblastic leukaemia (ALL) is the most common childhood cancer, with 70%–80% of cases curable with modern chemotherapy. However, 20% of the cases suffer from disease relapse with bone marrow being the most common site. Isolated ocular involvement as the first sign of relapse is extremely rare, occurring in less than 2.2% of cases. The presentation of optic nerve involvement in leukaemia represents a visual emergency and a sign of isolated central nervous system relapse even in the absence of abnormal cerebrospinal fluid cytology. This case highlights the importance of routine ophthalmic screening in ALL even during maintenance phase and prompt initiation of treatment in cases with isolated optic nerve involvement.
Effect of algorithms and covariates in glaucoma diagnosis with optical coherence tomography angiography
Authors: You Qi Sheng , Tan Ou , Pi Shaohua , Liu Liang , Wei Ping , Chen Aiyin , Ing Eliesa , Jia Yali , Huang David
Published: June 2021

Purpose

To assess the effects of algorithms and covariates in glaucoma diagnosis with optical coherence tomography angiography (OCTA).

Methods

In this prospective cross-sectional study, one eye each of 36 normal controls and 64 patients with glaucoma underwent 4.5 mm disc-centred and 6 mm macula-centred OCTA scans. The peripapillary nerve fibre layer plexus capillary density (NFLP-CD) and macular superficial vascular complex vessel density (SVC-VD) were measured using both a commercial algorithm (AngioAnalytics) and a custom algorithm (Center for Ophthalmic Optics & Lasers Angiography Reading Toolkit (COOL-ART)). The nerve fibre layer and ganglion cell complex thicknesses were measured on structural OCT.

Results

The overall peripapillary NFLP-CD and macular SVC-VD measured with the two algorithms were highly correlated but poorly agreed. Among the normal controls, the perfusion measurements made by both algorithms were significantly correlated with age. AngioAnalytics measurements were also correlated with signal strength index, while COOL-ART measurements were not. These covariates were adjusted. The diagnostic accuracy, measured as the area under the receiver operating characteristic curve for glaucoma detection, was not significantly different between algorithms, between structural and perfusion parameters and between the peripapillary and macular regions (All p>0.05). The macular SVC-VD in the 6 mm square had a significantly higher diagnostic accuracy than that of the central 3 mm square area (p=0.005).

Conclusions

AngioAnalytics and COOL-ART vessel density measurements are not interchangeable but potentially interconvertible. Age and signal strength are significant covariates that need to be considered. Both algorithms and both peripapillary and macular perfusion parameters have similarly good diagnostic accuracy comparable to structural OCT. A larger macular analytic area provides higher diagnostic accuracy.
Design and implementation of a multifaceted injury prevention intervention in Bedouin children in southern Israel
Authors: Myers Vicki , Orr Daniella , Vered-Chen Liat , Baron-Epel Orna
Published: June 2021

Background

Child injury is prevalent in the Bedouin community of southern Israel, with higher injury rates compared with the general population. Bedouin children aged 0–4 were twice as likely as children from other population groups to suffer any injury, and for example, incidence of burns in Bedouin children was 0.91/1000 children, compared with 0.46/1000 in Jewish children.

Methods

A multifaceted injury prevention intervention was developed based on best practice methods, culturally adapted and implemented in nine Bedouin towns in collaboration with local authorities. Intervention elements included a youth leadership scheme, workshops for mothers in maternal child health centres, home safety visits, a preschool intervention and a media campaign. Outcome assessment of change following home visits was conducted. Process evaluation included a survey of mothers and focus groups with youth participants.

Results

High participation was demonstrated indicating acceptability of the programme. Assessment of home visits showed an improvement in the level of household safety between first and second visits, as measured by a checklist. Youth participants expressed satisfaction in the programme, which gave them confidence and practical tools.

Conclusion

A multifaceted intervention programme was conducted in the Bedouin community in southern Israel and found to be acceptable, with high participation levels. Collaboration between national and local authorities improved implementation, and multiple programmes in different settings enabled broad exposure to the programme.
Dynamic treatment units in forest planning using cell proximity
Authors: Wilhelmsson Pär , Sjödin Edward , Wästlund André , Wallerman Jörgen , Lämås Tomas , Öhman Karin
Published: June 2021

In forest management planning, the dynamic treatment unit (DTU) approach has become an increasingly relevant alternative to the traditional planning approach using fixed stands, due to improved remote sensing techniques and optimization procedures, with the potential for the higher goal fulfillment of forest activities. For the DTU approach, the traditional concept of fixed stands is disregarded, and forest data are kept in units with a high spatial resolution. Forest operations are planned by clustering cells to form treatment units for harvest operations. This paper presents a new model with an exact optimization technique for forming DTUs in forest planning. In comparison with most previous models, this model aims for increased flexibility by modelling the spatial dimension according to cell proximity rather than immediate adjacency. The model is evaluated using a case study with harvest flow constraints for a forest estate in southern Sweden, represented by 3587 cells. The parameter settings differed between cases, resulting in varying degrees of clustered DTUs, which caused relative net present value losses of up to 4.3%. The case without clustering had the lowest net present value when considering entry costs. The solution times varied between 2.2 s and 42 min 6 s and grew rapidly with increasing problem size.
Masses and thermodynamic properties of a quarkonium system
Authors: Inyang Etido P. , Inyang Ephraim P. , Akpan I.O. , Ntibi J.E. , William E.S.
Published: June 2021

Hulthen plus Hellmann potentials are adopted as the quark–antiquark interaction potential for studying the thermodynamic properties and the mass spectra of heavy mesons. The potential was rendered temperature dependent by replacing the screening parameter with Debye mass. We solved the radial Schrödinger equation analytically using the Nikiforov–Uvarov method. The energy eigenvalues and corresponding wave function in terms of Laguerre polynomials were obtained. The present results are applied for calculating the mass of heavy mesons, such as charmonium [Formula: see text] and bottomonium [Formula: see text], and thermodynamic properties, such as the mean energy, the specific heat, the free energy, and the entropy. Four special cases were considered when these potential parameters were set to zero, resulting in Hellmann potential, Yukawa potential, Coulomb potential, and Hulthen potential, respectively. The present potential provides satisfying results in comparison with experimental data and the work of other researchers.
Numerical simulation of natural convection in a porous cavity with internal hot and cold sources using the lattice Boltzmann method
Authors: Zhang Ying , Huang Xuhui , Huang Yichen , Xu Meng , Lei Jie
Published: June 2021

Based on the non-orthogonal multiple-relaxation-time lattice Boltzmann method (MRT–LBM), natural convection in a porous square cavity with a pair of isothermally hot and cold blocks inside was studied numerically in the current study. The influence of arrangements (Cases 1, 2, 3, 4, and 5), spacing ratio (S), and size ratio (A) of the hot and cold sources and the Rayleigh number (Ra) on the heat exchange efficiency were studied. The results show that different arrangements produce different heat-transfer effects. Two arrangements, hot and cold blocks placed horizontally (Case 1) and a cold block located in the upper left corner while a hot block is located in the bottom right corner (Case 4), have better heat exchange performance than the other three cases because the flow directions of hot and cold fluids are closer to that of the heat transfer. Then, the influence of the spacing between blocks and the size of the blocks on the heat transfer rate was further studied in Cases 1 and 4. Heat transfer performance improved with increasing A. Additionally, the variation in the heat transfer performance with spacing is related to the arrangement and size ratio of the blocks. For Ra = 104, 105, and 106, the best heat transfer characteristics were obtained in Case 1 when S = 0.05 and A = 0.20. For Ra = 107, Case 4 exhibited the best heat transfer effect when S = 0.35 and A = 0.20.
Thermodynamic quantities in the high-temperature limit in the GUP framework
Authors: Abbasiyan-Motlaq M.
Published: June 2021

We study the values of thermodynamic quantities of physical systems at high temperatures in the framework of the generalized uncertainty principle (GUP). First, we obtain the semi-classical partition function, internal energy, and heat capacity for physical systems in a general case of deformed algebra. We show that at the high-temperature limit the heat capacity vanishes and the internal energy is maximized. We calculate this temperature for the ultra-relativistic system in approximate form. Finally, the maximum temperature and maximum energy for the ultra-relativistic system are obtained in the framework of two different GUPs.
Moving the epidemic tipping point through topologically targeted social distancing
Authors: Ansari Sara , Anvari Mehrnaz , Pfeffer Oskar , Molkenthin Nora , Moosavi Mohammad R. , Hellmann Frank , Heitzig Jobst , Kurths Jürgen
Published: June 2021

The epidemic threshold of a social system is the ratio of infection and recovery rate above which a disease spreading in it becomes an epidemic. In the absence of pharmaceutical interventions (i.e. vaccines), the only way to control a given disease is to move this threshold by non-pharmaceutical interventions like social distancing, past the epidemic threshold corresponding to the disease, thereby tipping the system from epidemic into a non-epidemic regime. Modeling the disease as a spreading process on a social graph, social distancing can be modeled by removing some of the graphs links. It has been conjectured that the largest eigenvalue of the adjacency matrix of the resulting graph corresponds to the systems epidemic threshold. Here we use a Markov chain Monte Carlo (MCMC) method to study those link removals that do well at reducing the largest eigenvalue of the adjacency matrix. The MCMC method generates samples from the relative canonical network ensemble with a defined expectation value of $$\lambda _{\text {max}}$$

λ
max

. We call this the “well-controlling network ensemble” (WCNE) and compare its structure to randomly thinned networks with the same link density. We observe that networks in the WCNE tend to be more homogeneous in the degree distribution and use this insight to define two ad-hoc removal strategies, which also substantially reduce the largest eigenvalue. A targeted removal of 80% of links can be as effective as a random removal of 90%, leaving individuals with twice as many contacts. Finally, by simulating epidemic spreading via either an SIS or an SIR model on network ensembles created with different link removal strategies (random, WCNE, or degree-homogenizing), we show that tipping from an epidemic to a non-epidemic state happens at a larger critical ratio between infection rate and recovery rate for WCNE and degree-homogenized networks than for those obtained by random removals.
Generalized coherent states of exceptional Scarf-I potential: Their spatio-temporal and statistical properties
Authors: Shreecharan T. , Sree Ranjani S.
Published: June 2021

We construct generalized coherent states for the rationally extended Scarf-I potential. Statistical and geometrical properties of these states are investigated. Special emphasis is given to the study of spatio-temporal properties of the coherent states via the quantum carpet structure and the auto-correlation function. Through this study, we aim to find the signature of the “rationalization” of the conventional potentials and the classical orthogonal polynomials.
Robust sliding mode control of uncertain nonlinear systems with chattering alleviating scheme
Authors: Musmade Bhausaheb B. , Patre Balasaheb M.
Published: June 2021

In this paper, a class of uncertain nonlinear systems is investigated and a sliding mode control (SMC) design is presented. The method is proposed for uncertain systems with model uncertainties, nonlinear dynamics and external disturbances. Using nominal system and related bounds of uncertainties, a chattering alleviating scheme is also proposed, which can ensure the robust SMC law. The performance and the significance of the controlled system are investigated under variation in system parameters and also in presence of an external disturbance. The simulation results indicate that performance of the proposed controller is effective compared to the existing controllers.
Fast graph clustering in large-scale systems based on spectral coarsening
Authors: Sun Dasong
Published: June 2021

Complex networks depict the individual relationship in a population, which can help to deeply mine the characteristics of complex networks and predict the potential collaboration between individuals by analyzing their interaction within different groups or clusters. However, the existing algorithms are with high complexity, which cost much computational time. In this paper, an efficient graph clustering algorithm based on spectral coarsening is proposed, to deal with the large time complexity of the traditional spectral algorithm. We first find the subset most possibly belonged to the same cluster in the original network, and merge them into a single node. The scale of the network will decrease with the network being coarsened. Then, the spectral clustering algorithm is performed on the coarsened network with the maintained advantages and the improved time efficiency. Finally, the experimental results on the multiple datasets demonstrate that the proposed algorithm, compared with the current state-of-the-art methods, has superior performance.
EXPERIMENTAL INVESTIGATION AND PARAMETRIC OPTIMIZATION OF NEUROSURGICAL BONE GRINDING UNDER BIO-MIMIC ENVIRONMENT
Authors: BABBAR ATUL , JAIN VIVEK , GUPTA DHEERAJ , PRAKASH CHANDER
Published: June 2021

Bone grinding is a craniotomy procedure which is used to remove a bone flap from the skull to expose and create an access for the dissection of tumors. In this study, a computer-controlled neurosurgical bone grinding has been used to explore the effect of various neurosurgical bone grinding parameters, such as cutting forces, torque, grinding force ratio, and temperature generated during bone grinding have been investigated. Bone samples after grinding have been assessed for morphological analysis. Based on the outcomes, a multi-attribute decision-making methodology based on grey relational analysis has been adopted. Regression models have been developed and then validated to ensure the adequacy of the developed models. Subsequently, a comparative analysis of experimental and predicted results have been presented. It is revealed that grinding forces and torque decreased with the escalation of rotational speed from 35,000 revolutions per minute (rpm) to 55,000[Formula: see text]rpm. The optimum combination of process parameters found as rotational speed of 55,000[Formula: see text]rpm, feed rate of 20[Formula: see text]mm/min, and depth of cut of 0.50[Formula: see text]mm.
Medium-Low-Temperature NO2 Sensor Based on YSZ Solid Electrolyte and Mesoporous WO3 Sensing Electrode for Detection of Vehicle Emissions
Authors: Zhang Cheng , Jiang Chuning , Zheng Xiaohong , Hong Xin
Published: June 2021

A mixed potential-type NO2 sensor was fabricated using yttria-stabilized zirconia (YSZ) as the electrolyte and mesoporous WO3 as the sensing electrode for the detection of NO2 in vehicle exhausts. The mesoporous WO3 with a diameter of 7 nm was synthesized using the hard template method. The sensor showed excellent performance in the detection of 30–500[Formula: see text]ppm of NO2 at 300∘C and 500∘C. However, commercial WO3 only operate well at 500∘C. The response of the mesoporous WO3 was higher and the test temperature was lower compared to that of commercial WO3. XPS combined with NO2-TPD was used to explain the high activity of mesoporous WO3 at medium-low temperature, and the mechanism of mixed electromotive force was verified by electrochemical impedance spectroscopy. Furthermore, the sensor exhibited high NO2 selectivity in the presence of interfering gases, such as NO, CO, CO2 and NH3. Most importantly, the sensor had excellent repeatability and stability.
Global dynamical behavior of a multigroup SVIR epidemic model with Markovian switching
Authors: Liu Qun , Jiang Daqing
Published: June 2021

In this paper, we are concerned with the global dynamical behavior of a multigroup SVIR epidemic model, which is formulated as a piecewise-deterministic Markov process. We first obtain sufficient criteria for extinction of the diseases. Then we establish sufficient criteria for persistence in the mean of the diseases. Moreover, in the case of persistence, we find a domain which is positive recurrence for the solution of the stochastic system by constructing an appropriate Lyapunov function with regime switching.
Fundamental group of Galois covers of degree 6 surfaces
Authors: Amram M. , Gong C. , Sinichkin U. , Tan S.-L. , Xu W.-Y. , Yoshpe M.
Published: June 2021

In this paper, we consider the Galois covers of algebraic surfaces of degree 6, with all associated planar degenerations. We compute the fundamental groups of those Galois covers, using their degeneration. We show that for 8 types of degenerations, the fundamental group of the Galois cover is non-trivial and for 20 types it is trivial. Moreover, we compute the Chern numbers of all the surfaces with this type of degeneration and prove that the signatures of all their Galois covers are negative. We formulate a conjecture regarding the structure of the fundamental groups of the Galois covers based on our findings.
Advancement in Nanomaterials for Rapid Sensing, Diagnosis, and Prevention of COVID-19
Authors: Das Dipak Kumar , Kumar Anuj , Vashistha Vinod Kumar
Published: June 2021

During last two decades, the biggest global epidemic had been associated with middle east respiratory syndrome, severe acute respiratory syndrome, and novel coronavirus-19 (COVID-19) with clinical symptoms of bronchitis, pneumonia, and fetal respiratory illness. Infection caused by COVID-19 initially assumed to be milder in nature but consequently spreading across the globe and devastating mortality rate rapidly made it a pandemic. Having enormous challenges, many significant issues are yet to be addressed. Scientific community is engaged in designing and developing effective nano-biosensors for the quick detection of COVID-19, easy diagnosis as well as absolute tracking of infected population in order to prevent pandemic outbreak further. In this paper, key stages like suppressing the immune response of COVID-19 patients, diagnosis of COVID-19, and prevention of COVID-19 using nanomaterials have been discussed. Further, the unresolved challenges and drawbacks toward treatments and vaccine development at the earliest to win over this war have also been critically discussed.
Demarcating Endogenous and Exogenous Opinion Dynamics: An Experimental Design Approach
Authors: Koley Paramita , Saha Avirup , Bhattacharya Sourangshu , Ganguly Niloy , De Abir
Published: June 2021

The networked opinion diffusion in online social networks is often governed by the two genres of opinions—
endogenous
opinions that are driven by the influence of social contacts among users, and
exogenous
opinions which are formed by external effects like news and feeds. Accurate demarcation of endogenous and exogenous messages offers an important cue to opinion modeling, thereby enhancing its predictive performance. In this article, we design a suite of unsupervised classification methods based on experimental design approaches, in which, we aim to select the subsets of events which minimize different measures of mean estimation error. In more detail, we first show that these subset selection tasks are NP-Hard. Then we show that the associated objective functions are weakly submodular, which allows us to cast efficient approximation algorithms with guarantees. Finally, we validate the efficacy of our proposal on various real-world datasets crawled from Twitter as well as diverse synthetic datasets. Our experiments range from validating prediction performance on unsanitized and sanitized events to checking the effect of selecting optimal subsets of various sizes. Through various experiments, we have found that our method offers a significant improvement in accuracy in terms of opinion forecasting, against several competitors.
Learning Graph Neural Networks with Positive and Unlabeled Nodes
Authors: Wu Man , Pan Shirui , Du Lan , Zhu Xingquan
Published: June 2021

Graph neural networks (GNNs) are important tools for transductive learning tasks, such as node classification in graphs, due to their expressive power in capturing complex interdependency between nodes. To enable GNN learning, existing works typically assume that labeled nodes, from two or multiple classes, are provided, so that a discriminative classifier can be learned from the labeled data. In reality, this assumption might be too restrictive for applications, as users may only provide labels of interest in a single class for a small number of nodes. In addition, most GNN models only aggregate information from short distances (
e.g.
, 1-hop neighbors) in each round, and fail to capture
long-distance relationship
in graphs. In this article, we propose a novel GNN framework, long-short distance aggregation networks, to overcome these limitations. By generating multiple graphs at different distance levels, based on the adjacency matrix, we develop a long-short distance attention model to model these graphs. The direct neighbors are captured via a short-distance attention mechanism, and neighbors with long distance are captured by a long-distance attention mechanism. Two novel risk estimators are further employed to aggregate long-short-distance networks, for PU learning and the loss is back-propagated for model learning. Experimental results on real-world datasets demonstrate the effectiveness of our algorithm.
App2Vec: Context-Aware Application Usage Prediction
Authors: Wang Huandong , Li Yong , Du Mu , Li Zhenhui , Jin Depeng
Published: June 2021

Both app developers and service providers have strong motivations to understandwhenandwherecertain apps are used by users. However, it has been a challenging problem due to the highly skewed and noisy app usage data. Moreover, apps are regarded as independent items in existing studies, which fail to capture the hidden semantics in app usage traces. In this article, we propose App2Vec, a powerful representation learning model to learn the semantic embedding of apps with the consideration of spatio-temporal context. Based on the obtained semantic embeddings, we develop a probabilistic model based on the Bayesian mixture model and Dirichlet process to capturewhen,where, andwhatsemantics of apps are used to predict the future usage. We evaluate our model using two different app usage datasets, which involve over 1.7 million users and 2,000+ apps. Evaluation results show that our proposed App2Vec algorithm outperforms the state-of-the-art algorithms in app usage prediction with a performance gap of over 17.0%.
KernelFaRer
Authors: De Carvalho João P. L. , Kuzma Braedy , Korostelev Ivan , Amaral José Nelson , Barton Christopher , Moreira José , Araujo Guido
Published: June 2021

Well-crafted libraries deliver much higher performance than code generated by sophisticated application programmers using advanced optimizing compilers. When a code pattern for which a well-tuned library implementation exists is found in the source code of an application, the highest performing solution is to replace the pattern with a call to the library. Idiom-recognition solutions in the past either required pattern matching machinery that was outside of the compilation framework or provided a very brittle solution that would fail even for minor variants in the pattern source code. This article introduces Kernel Find & Replacer (
KernelFaRer
), an idiom recognizer implemented entirely in the existing LLVM compiler framework. The versatility of
KernelFaRer
is demonstrated by matching and replacing two linear algebra idioms, general matrix-matrix multiplication (GEMM), and symmetric rank-2k update (SYR2K). Both GEMM and SYR2K are used extensively in scientific computation, and GEMM is also a central building block for deep learning and computer graphics algorithms. The idiom recognition in
KernelFaRer
is much more robust than alternative solutions, has a much lower compilation overhead, and is fully integrated in the broadly used LLVM compilation tools.
KernelFaRer
replaces existing GEMM and SYR2K idioms with computations performed by BLAS, Eigen, MKL (Intel’s x86), ESSL (IBM’s PowerPC), and BLIS (AMD). Gains in performance that reach 2000× over hand-crafted source code compiled at the highest optimization level demonstrate that replacing application code with library call is a performant solution.
Strategic Knowledge Acquisition
Authors: Deuser Kaya , Naumov Pavel
Published: June 2021

The article proposes a trimodal logical system that can express the strategic ability of coalitions to learn from their experience. The main technical result is the completeness of the proposed system.
From 2-Sequents and Linear Nested Sequents to Natural Deduction for Normal Modal Logics
Authors: Martini Simone , Masini Andrea , Zorzi Margherita
Published: June 2021

We extend to natural deduction the approach of Linear Nested Sequents and of 2-Sequents. Formulas are decorated with a spatial coordinate, which allows a formulation of formal systems in the original spirit of natural deduction: only one introduction and one elimination rule per connective, no additional (structural) rule, no explicit reference to the accessibility relation of the intended Kripke models. We give systems for the normal modal logics from K to S4. For the intuitionistic versions of the systems, we define proof reduction, and prove proof normalization, thus obtaining a syntactical proof of consistency. For logics K and K4 we use existence predicates (à la Scott) for formulating sound deduction rules.
A Delay-Adjustable, Self-Testable Flip-Flop for Soft-Error Tolerability and Delay-Fault Testability
Authors: Lin Dave Y.-W. , Wen Charles H.-P.
Published: June 2021

As the demand of safety-critical applications (e.g., automobile electronics) increases, various radiation-hardened flip-flops are proposed for enhancing design reliability. Among all flip-flops, Delay-Adjustable D-Flip-Flop (DAD-FF) is specialized in arbitrarily adjusting delay in the design to tolerate soft errors induced by different energy levels. However, due to a lack of testability on DAD-FF, its soft-error tolerability is not yet verified, leading to uncertain design reliability. Therefore, this work proposes Delay-Adjustable, Self-Testable Flip-Flop (DAST-FF), built on top of DAD-FF with two extra MUXs (one for scan test and the other for latching-delay verification) to achieve both soft-error tolerability and testability. Meanwhile, a built-in self-test method is also developed on DAST-FFs to verify the cumulative latching delay before operation. The experimental result shows that for a design with 8,802 DAST-FFs, the built-in self-test method only takes 946 ns to ensure the soft-error tolerability. As to the testability, the enhanced scan capability can be enabled by inserting one extra transmission gate into DAST-FF with only 4.5 area overhead.
Deficiency of arcuate nucleus kisspeptin results in postpubertal central hypogonadism
Authors: Nandankar Nimisha , Negrón Ariel L. , Wolfe Andrew , Levine Jon E. , Radovick Sally
Published: June 2021

We demonstrate through a novel, conditional knockout mouse model of arcuate nucleus (ARC)-specific kisspeptin in the KNDy neuron that ARC kisspeptin is critical for estrous cyclicity in female mice and GnRH/LH pulsatility in both sexes. Our study reveals that ARC kisspeptin is essential for normal gametogenesis, and the loss of ARC kisspeptin results in significant hypogonadism, impacting fertility status. Our findings further confirm that normal puberty occurs despite a loss of ARC kisspeptin.
Vitamin D and lumisterol novel metabolites can inhibit SARS-CoV-2 replication machinery enzymes
Authors: Qayyum Shariq , Mohammad Taj , Slominski Radomir M. , Hassan Md Imtaiyaz , Tuckey Robert C. , Raman Chander , Slominski Andrzej T.
Published: June 2021

Active forms of vitamin D and lumisterol can inhibit SARS-CoV-2 replication machinery enzymes, which indicates that novel vitamin D and lumisterol metabolites are candidates for antiviral drug research.
Renal NG2-expressing cells have a macrophage-like phenotype and facilitate renal recovery after ischemic injury
Authors: Kittikulsuth Wararat , Nakano Daisuke , Kitada Kento , Suzuki Norio , Yamamoto Masayuki , Nishiyama Akira
Published: June 2021

Brain pericytes have macrophage-like activities after injury. However, such properties of pericytes in peripheral tissues have not been investigated. Here, we provide evidence that nerve/glial antigen 2-positive cells increase after renal injury. The population of nerve/glial antigen 2-positive cells, which does not increase expression of myofibroblast-associated gene, express macrophage markers and anti-inflammatory cytokine genes, have phagocytic activity, and play a role in renal recovery after kidney injury.
Convective Mass/Heat Analysis of an Electroosmotic Peristaltic Flow of Ionic Liquid in a Symmetric Porous Microchannel with Soret and Dufour
Authors: Yasmin Humaira , Iqbal Naveed
Published: June 2021

This research deals with the mathematical model for the development of the peristaltic principle of the combination of the pressure and electroosmotic flow (EOF) of ionic liquid across microchannels with electrokinetic effects. For thermomechanical dynamics, the convective conditions on the boundary for mass and heat transfer at the walls of the channel are quantified. For the microchannel, a porous structure is presumed. Soret, Dufour, and Joule heating are also listed in the scope of the problem addressed. The corresponding equations for the ionic fluid flow, mass, and heat transfer along with the Poisson–Boltzmann equation within the electrical double layer (EDL) are studied. The exact solution has been obtained based on lubrication theory (i.e., low Reynolds number and long wavelength approximations). The channel height is therefore believed to be much higher than the electrical double layer (EDL) thickness. Various dimensionless pertinent parameters illustrate the important aspects of electroosmotically controlled flow and subsequent convective mass/heat transfer attributes in a microchannel. A linear dependency on the fluid flow rate is exhibited by the pressure drop. The analysis shows that the electroosmotic parameter gives a reducing effect on the channel permeability. The distribution of temperature and concentration is greatly affected by convective heat and mass parameters, respectively. In biomedical engineering, the application areas of the study proposed are for the design of the devices such as a microfluidic pump to pump a small amount of ionic liquids by regulating the variation in temperature and concentration.
Deep Learning-Based Identification of Spinal Metastasis in Lung Cancer Using Spectral CT Images
Authors: Fan Xiaojie , Zhang Xiaoyu , Zhang Zibo , Jiang Yifang
Published: June 2021

In this study, deep learning algorithm-based energy/spectral computed tomography (CT) for the spinal metastasis from lung cancer was used. A dilated convolutional U-Net model (DC-U-Net model) was first proposed, which was used to segment the energy/spectral CT image of patients with the spinal metastasis from lung cancer. Subsequently, energy/spectral CT images under different energy levels were collected for the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) comparison. It was found the learning rate of the model decreased exponentially as the number of training increased, with the lung contour segmented out of the image. Under 40–65 keV, the CT value of bone metastasis from lung cancer decreased with increasing energy, as with the average rank sum test result. The SNR and CNR values were the highest under 60 keV. The detection rate of the deep learning algorithm below 60 keV was 81.41%, and that of professional doctors was 77.56%. The detection rate of the deep learning algorithm below 140 keV was 66.03%, and that of professional doctors was 64.74%. In conclusion, the DC-U-Net model demonstrates better segmentation effects versus the convolutional neutral networ k (CNN), with the lung contour segmented. Further, a higher energy level leads to worse segmentation effects on the energy/spectral CT image.
Evaluation of the Hypoglycemic Potential of Leaves Extract of Spondias pinnata (L.f.) Kurz. from Nepal
Authors: Sai Kusum , Chhetri Sumit Bahadur Baruwal , Devkota Shankar Raj , Khatri Deepa
Published: June 2021

Spondias pinnata (L.f.) Kurz. (family: Anacardiaceae) is a wild deciduous tree indigenous to southeast Asian countries. Different parts of this plant are used traditionally for the treatment and cure of various disorders and illnesses. S. pinnata leaves are used to prevent and treat diabetes in traditional Balinese medicine. However, scientific study on the antihyperglycemic effect of its leaves has not been reported yet. Therefore, this study aims to perform phytochemical screening and investigate the hypoglycemic potential of S. pinnata leaves extract. Preliminary phytochemical screening of the hydroethanolic extract was performed following the standard tests. In vivo hypoglycemic activity of the leaves extract was evaluated using normal and glucose-loaded rats. The results displayed the presence of phytochemical constituents such as saponins, phenolic compounds, flavonoids, and terpenoids. S. pinnata (500 mg/kg) and metformin (100 mg/kg) exhibited a significant (

p
<
0.05

) decrease in blood glucose level at 1, 2, and 3 h in normal rats when compared to the control group. Metformin- (100 mg/kg)- and S. pinnata- (500 mg/kg)- treated groups showed a maximum decrease in the blood glucose level at 3 h after single-dose administration in the oral glucose tolerance test (OGTT). In conclusion, S. pinnata leaves possess a significant hypoglycemic activity in the animal model and thus support its traditional use to treat diabetes. Therefore, a detailed mechanism-based study and isolation of bioactive compounds from S. pinnata leaves would be beneficial in the future for the search of new hypoglycemic agents.
Study on Dynamic Evolution Law of Blasting Cracks in Elliptical Bipolar Linear Shaped Charge Blasting
Authors: Wu Bo , Xu Shixiang , Meng Guowang , Cai Junhua , Wei Han , Li Hualong , Zhang Jinglong
Published: June 2021

Based on LS‐DYNA numerical simulation analysis and comparison with laboratory tests, the blasting crack development dynamic evolution mechanism of elliptical bipolar linear shaped charge is analyzed. The development law of rock crack and optimal radial decoupling coefficient under different blast hole diameters were studied. The results revealed that the blasting with elliptical bipolar linear shaped charge had a remarkable effect on the directional crack formation, and the maximum effective stress of rock close to the position of shaped charge in the direction of concentrating energy is about 2.3 times of that in the direction of nonconcentrated energy. Moreover, the directional crack could be formed by blasting with elliptical bipolar linear shaped charge with different hole diameters, whilst the length of the main crack was related to the radial decoupling coefficient. Particularly, the main crack reached the longest when the radial decoupling coefficient was 3.36.
Seaweed as a Source of Natural Antioxidants: Therapeutic Activity and Food Applications
Authors: Kumar Yogesh , Tarafdar Ayon , Badgujar Prarabdh C.
Published: June 2021

Seaweed is a valuable source of bioactive compounds, polysaccharides, antioxidants, minerals, and essential nutrients such as fatty acids, amino acids, and vitamins that could be used as a functional ingredient. The variation in the composition of biologically active compounds in seaweeds depends on the environmental growth factors that make seaweed of the same species compositionally different across the globe. Nevertheless, all seaweeds exhibit extraordinary antioxidant potential which can be harnessed for a broad variety of food applications such as in preparation of soups, pasta, salads, noodles, and other country specific dishes. This review highlights the nutritional and bioactive compounds occurring in different classes of seaweeds while focusing on their therapeutic activities including but not limited to blood cell aggregation, antiviral, antitumor, anti-inflammatory, and anticancer properties. The review also explores the existing and potential application of seaweeds as a source of natural antioxidant in food products. Seaweed-derived compounds have great potential for being used as a supplement in functional foods due to their high stability as well as consumer demand for antioxidant-rich foods.
Application of Green Building Design Based on the Internet of Things in the Landscape Planning of Characteristic Towns
Authors: Xu Ying
Published: June 2021

China is a large agricultural country. In the past, relying on the accumulation of agriculture and the contribution of farmers, it laid a solid foundation for China’s economic construction. However, with the improvement of the national economy and industrialization system, the dual structure of urban and rural areas has become more and more obvious, and the broad masses of farmers have not enjoyed the fruits of industrialization and urbanization. Based on the theoretical research on green rural dwellings, drawing lessons from relevant theories and cases at home and abroad, this paper proposes green rural construction techniques suitable for northern China and studies how to participate in the whole process of rural construction in an all‐round way. In the middle and late stages, green concepts should be integrated, especially considering the feasibility of three‐star farmhouse standards, from land saving (land planning), energy saving (environmental protection structure, heating, ventilation, and new energy utilization), water saving (rainwater collection and greening), material saving (resource reuse and on‐site materials), and indoor environmental quality control (noise control and anticondensation), these five aspects are used to design buildings. The deformation monitoring system can monitor the deformation of agricultural building structures in real time. The experimental results show that the Internet‐based agricultural building deformation monitoring system studied in this paper can perform real‐time deformation monitoring of various agricultural buildings, thereby improving the safety of agricultural buildings and ensuring agriculture the safety of production, and transportation plays an important role in the protection and accumulation of agricultural information loss. The service life of the building is increased by at least 30%. It is hoped that the research results in this article can provide guidance and reference for the construction and planning of beautiful rural areas. In the future, the construction of beautiful villages will be more beautiful and more distinctive.
DDPG‐Based Energy‐Efficient Flow Scheduling Algorithm in Software‐Defined Data Centers
Authors: Yao Zan , Wang Ying , Meng Luoming , Qiu Xuesong , Yu Peng
Published: June 2021

With the rapid development of data centers, the energy consumption brought by more and more data centers cannot be underestimated. How to intelligently manage software‐defined data center networks to reduce network energy consumption and improve network performance is becoming an important research subject. In this paper, for the flows with deadline requirements, we study how to design the rate‐variable flow scheduling scheme to realize energy‐saving and minimize the mean completion time (MCT) of flows based on meeting the deadline requirement. The flow scheduling optimization problem can be modeled as a Markov decision process (MDP). To cope with a large solution space, we design a DDPG‐EEFS algorithm to find the optimal scheduling scheme for flows. The simulation result reveals that the DDPG‐EEFS algorithm only trains part of the states and gets a good energy‐saving effect and network performance. When the traffic intensity is small, the transmission time performance can be improved by sacrificing a little energy efficiency.
Selection of Comprehensive Assessment Categories Based on the International Classification of Functioning, Disability, and Health for Elderly Patients with Heart Failure: A Delphi Survey among Registered Instructors of Cardiac Rehabilitation
Authors: Shiota Shigehito , Naka Makiko , Kitagawa Toshiro , Hidaka Takayuki , Mio Naoki , Kanai Kana , Mochizuki Mariko , Kimura Hiroaki , Kihara Yasuki
Published: June 2021

The development of a comprehensive assessment tool based on the International Classification of Functioning, Disability, and Health (ICF) for elderly patients with heart failure is urgently required. In this study, we classified the ICF categories relevant to heart failure in the elderly through a Delphi survey (3-step questionnaire survey) of 108 Registered Instructors of Cardiac Rehabilitation in the Hiroshima Prefecture. Questionnaires were conducted using postal mail or a web-based platform. The survey was conducted three times, and the survey results were provided as feedback to the participants in the second and third rounds. More than 80% of the respondents selected categories according to the ICF core set methodology. Data were collected from December 2018 to March 2019, with 67, 54, and 46 participants in the first, second, and third rounds, respectively. A total of 58 ICF items were adopted based on the results: 27 body function items, 4 body structure items, 20 activity and participation items, and 7 environmental factor items. This study is characterised by the inclusion of a large number of ICF items for mental function. This result seems to be influenced by the increasing interest in cognitive dysfunction in elderly patients with heart failure. The ICF categories selected for this study allow for a comprehensive assessment of clients for occupational therapy. The findings of this study are expected to provide a basis for an outcome measure to determine the effectiveness of occupational therapy for these patients.
New Extended Quantitative Local and Global Regularity Index for Single‐ and Multiframe RC Bridges Based on Modal Vector Correlation
Authors: Aboutorabian Elham , Raissi Dehkordi Morteza
Published: June 2021

Seismic demand and performance of bridges are highly dependent upon the level of irregularity. Although previous studies have proposed methodologies so as to quantify the irregularity of the bridges in terms of global regularity index, it still remains unclear how to determine the distribution of irregularity along a bridge, as well as to discover the irregularity sources. This research project is intended to develop a quantitative vector regularity criterion for single‐ and multiframe bridges based on the modified correlation function for spatial locations of scaled mode shapes of deck‐alone and whole bridge. The proposed criterion calculates two types of regularity indices, namely, local (LRI) and global regularity indices (GRI). The GRI is a scalar value representing the overall regularity of the entire bridge, whereas the LRI highlights vector irregularity distribution along the bridge. Since the deck discontinuity due to the in‐span hinges is one of the leading causes for irregularity, the proposed index has been employed in case of multiframe bridges as well. Furthermore, the current study aims to investigate the correlation between the proposed irregularity indicators and the nonlinear to linear demand ratio. Therefore, the appropriate analysis method can be chosen based on irregularity extent of bridges. Obtained results of the proposed indices reveal that in‐span hinge is one of the main parameters affecting the distribution of local irregularity along a bridge. Therefore, multiframe bridges need to be investigated in detail so as to validate the special design requirements recommended by design codes.
High-Precision Guide Stiffness Analysis Method for Micromechanism Based on the Boundary Element Method
Authors: Yang Manzhi , Lv Zhenyang , Jing Gang , Guo Wei , Huang Yumei , Li Linyue , Wei Kaiyang , Feng Bin , Ge Hongyu
Published: June 2021

The guide stiffness performance directly affects the motion of the micromechanism in accuracy and security. Therefore, it is crucial to analyze the guide stiffness precisely. In this paper, a high-precision guide stiffness analysis method for the micromechanism by the boundary element method (BEM) is proposed. The validity and accuracy of the analysis method are tested by a guide stiffness experiment. In order to ensure the accuracy and safety during the micromechanism motion, a guiding unit of the micromechanism was designed based on the guiding principle. The guiding unit can provide parasitic motion and additional force in the motion of the micromechanism. Then, the stiffness equations of the beam element are derived by the boundary element method. The stiffness equation of straight circular flexure hinge is analyzed by rigid discretization and rigid combination, and the guide stiffness of the mechanism is investigated by rigid combination. Finally, according to the actual situation, the stiffness matrix of the guide rail (Kb) was proposed, and the analytical value of the guide stiffness was calculated to be 22.2 N/μm. The guide stiffness performance experiment was completed, and the experimental value is 22.3 N/μm. Therefore, the error between the analysis method and the experimental results is 0.45%. This study provides a new method for the stiffness analysis of high-precision micromechanisms and presents a reference for the design and stiffness analysis of complex structures. This method is helpful for stiffness analysis of the microrotary mechanism with high accuracy.