Real estate market analysis and place-based decision-making can both benefit from understanding house price development. Although considerable amounts of interest have been devoted to housing price modelling, the assessment of house price fluctuation still requires further comparing studies. Housing price prediction is challenging as contributing factors are quite dynamic and subject to a variety of regulating elements. The future understanding of the housing market trends not only provides sufficient customers’ investment trust potential but also enables the financial support to progress more realistic in advance. In this study, a comprehensive data-informed framework is developed to investigate and anticipate real estate house prices using historical data by combining explanatory features. We examined about 500 houses in the Boston area as a case study and discussed how the increase in housing prices could vary by each of the contributing components. Fourteen Machine Learning (ML) regressors imply to the dataset and lead to a comparative study of the accuracy of all the models. ML-based regressors forecast real estate home prices as a function of thirteen influencing factors. The most informative features were also selected by conducting the Permutation Feature Importance technique on all the features The study provides a comprehensive tool for evaluating the robustness and efficiency of ML models for housing price predictions. The results highlighted Random Forest as the best model has an R2 equals to 0.88 and Voting Regressor as the second highest rated model has R2 equals to 0.87. Results of multivariate exploratory data analysis also implied that the average number of rooms and percentage of the lower status of the population have the most significant impact on the price range predictions.

Aim. In the current study, we aimed at identifying resting-state brain networks, which are different in patients with depression compared to healthy individuals. Moreover, we analyzed the potential for clinical use of different network measures that could discriminate the two groups and thus help the diagnostic process. Method and subjects. We recruited 90 subjects: 49 healthy controls (HC) and 41 patients with a major depressive episode (MDE). All subjects underwent clinical evaluation and functional resting-state MRI. The data were processed to investigate functional connectivity network measures across the two groups using Brain Connectivity Toolbox. The statistical inferences were made at the functional networks level, using false discovery rate method. Independent samples t-test was performed on the network measures mean values to reveal differences between HC and MDE groups. Permutation-based statistical testing was used to test the significance of the difference between the distributions of the network measures by nodes for HC and MDE groups. Linear discriminant analysis was used to differentiate between the groups. Results and discussion. Significant differences in FC between depressed patients and healthy controls were found with the most prominent changes encompassing within-region as well as between-region connectivity of occipital lobe areas such as precuneus (PreCu), cuneus (Cu), superior occipital gyrus (SOG), lingual gyrus (LG), fusiform gyrus (FG), cerebellum, along with limbic structures including the hippocampus (Hipp) and cingulate gyrus. Linear discriminant analysis demonstrated that the full connectivity matrices, as well as those with only the significant connections identified in advance, were the most precise in differentiating between depression and health. These measures reached precision levels of 97% and 94%, respectively. Conclusion. Our study delivered further evidence about impairment of functional connectivity networks in MDE that may contribute to differentiate patients with depression from healthy subjects.

This paper investigates whether currency risk is priced differently in the different sectors (industrial, financial, and basic materials) of equity markets in a sample of developed United States of America (USA) and developing economies (Brazil, India, Poland, and South Africa). The paper makes use of the following techniques: (i) Univariate Autoregressive Fractionally Integrated Moving Average and Exponential General Autoregressive Conditional Heteroskedastic (ARFIMA-EGARCH), (ii) the Markov-Switching method (MS), and (iii) the Canonical Vine Copulas (C-Vine) techniques. Using a sample of daily data made of the foreign exchange rate against the domestic currency and equity market sectors; our findings show that there is an asymmetry effect between equities markets and the foreign exchange rate: there is a heterogeneous, strong, and positive dependence between the two. Higher equities prices are associated with depreciation of local currencies, according to US dollar (USD) exchange rates. In addition, we find that the selected emerging economies are pricing a positive and considerable currency risk. The pricing of currency risk has a varied effect in both regimes representing the states of the economy. In fact, when currency risk pricing has a beneficial impact on certain sectors of the economy, investors predict better returns.

Every month teachers face the dilemma of what exercises should their students practice, and what their consequences are on long-term learning. Since teachers prefer to pose their own exercises, this generates a large number of questions, each one attempted by a small number of students. Thus, we couldn’t use models based on big data such as deep learning. Instead, we developed a simple to understand state-space model that predicts end-of-year national test scores. We used 2,386 online fourth-grade mathematic questions designed by teachers and each attempted by some of the 500 students in 24 low socioeconomic schools. We found that the state-space model predictions improved month-by-month and that in most months it outperformed linear regression models. Moreover, the state-space estimator provides for each month a direct mechanism to simulate different practice strategies and compute their impact on the end-of-year standardized national test. We built iso-impact curves based on two critical variables: the number of questions solved correctly in the first attempt and the total number of exercises attempted. This allows the teacher to visualize the trade-off between asking students to do exercises more carefully or doing more exercises. To the best of our knowledge, this model is the first of its kind in education. It is a novel tool that supports teachers drive whole classes to achieve long-term learning targets.

Garnet-type Ta-doped Li7La3Zr2O12 (LLZO) ceramic solid electrolytes with Ga2O3 additive were synthesized via a conventional solid-state reaction process. When the amounts of Ga2O3 additive were below 2 mol %, the sintered sample has a dense structure composed of grains with the averaged size of 5 to 10 μm, while 3 mol % or more Ga2O3 addition causes the significant increase in grain size above several 10 to 100 μm, due to the sintering with large amount of liquid Li-Ga-O phase at high temperature. The highest total (bulk + grain-boundary) ionic conductivity of 1.1 mS cm1 at room temperature was obtained in the sample with 5 mol % Ga2O3 addition. However, in galvanostatic testing of the symmetric cell with Li metal electrodes, this sample was shorted by Li dendrite growth into solid electrolyte at current density below 0.2 mA cm2. The tolerance for Li dendrite growth is maximized in sample sintered with 2 mol % Ga2O3 addition, which was shorted at 0.8 mA cm2 in the symmetric cell. Since the interfacial resistance between Li metal and solid electrolyte was nearly identical among the all samples, the difference in tolerance for Li dendrite growth is mainly attributed to the difference in microstructure of sintered samples depending on the amounts of Ga2O3.

Intratumoral heterogeneity can exist along multiple axes: Cancer Stem Cells (CSCs)/non-CSCs, drug-sensitive/drug-tolerant states and a spectrum of epithelial-hybrid-mesenchymal phenotypes. Further, these diverse cell-states can switch reversibly among one another, thereby posing a major challenge to therapeutic efficacy. Therefore, understanding the origins of phenotypic plasticity and heterogeneity remains an active area of investigation. While genomic components (mutations, chromosomal instability) driving heterogeneity have been well-studied, recent reports highlight the role of non-genetic mechanisms in enabling both phenotypic plasticity and heterogeneity. Here, we discuss various processes underlying phenotypic plasticity such as stochastic gene expression, chromatin reprogramming, asymmetric cell division and the presence of multiple “attractors”. These processes can facilitate a dynamically evolving cell population such that a subpopulation of (drug-tolerant) cells can survive lethal drug exposure and recapitulate population heterogeneity on drug withdrawal, leading to relapse. These drug-tolerant cells can be both pre-existing and also induced by the drug itself through cell-state reprogramming. The dynamics of cell-state transitions both in absence and presence of the drug can be quantified through mathematical models. Such a dynamical systems approach to elucidating patterns of intratumoral heterogeneity by integrating longitudinal experimental data with mathematical models can help design effective combinatorial and/or sequential therapies for better clinical outcomes.

In this work, we have developed a non-ordinary state-based peridynamic model for multiple crack initiation and propagation due to compression-compression fatigue load. In each loading cycle, the fatigue loading is redistributed among the peridynamic solid body, leading to the progressive fatigue damage initiation and propagation in an autonomous fashion. The proposed fatigue model parameters are firstly validated by 3D numerical benchmark tests, and then it is applied to simulate widespread fatigue damage evolution of the aircraft wing corner box. The modified constitutive damage model has been implemented into the peridynamics framework at finite strain. Furthermore, the criterion algorithm from multiple initiation to propagation is discussed. It is shown that the numerical results obtained from peridynamics simulations are in general agreement with those from the experiment data. The comparison of experimental and numerical results indicates that the proposed non-ordinary state-based peridynamics fatigue model has the ability to capture the multiple crack initiation and propagation and other features of the aluminium alloy material.

The description of stellar interiors remains as a big challenge for the nuclear astrophysics community. The consolidated knowledge is restricted to density regions around the saturation of hadronic matter $\rho _{0} = 2.8\times 10^{14} {\rm\ g\ cm^{-3}}$, regimes where our nuclear models are successfully applied. As one moves towards higher densities and extreme conditions up to five to twenty times $\rho_{0}$, little can be said about the microphysics of such obejects. Here, we employ an MCMC strategy in order to access the variability of polytropic three-pircewised models for neutron star equation of states. With a fixed description of the hadronic matter we explore a variety of models for the high density regimes leading to stellar masses up to 2.5 $M_{\odot}$. In addition, we also discuss the use of a Bayesian power regression model with heteroscedastic error. The set of EoS from LIGO was used as inputs and treated as data set for testing case.

This article will briefly review the progress of h-BN based solid-state metal semiconductor metal (MSM) neutron detectors. In the last decade, several groups have been working on hexagonal boron nitride (h-BN) based solid-state neutron detectors. Recently, the detection efficiency of 59% has been reported. Efficient, low-cost neutron detectors made from readily available materials are essential for various applications. Neutron detectors are widely used to detect fissile materials and nuclear power plants for security applications. The most common and widely used neutron detectors are 3He based, which are sometimes bulky, difficult to transport, have high absorption length, need relatively high bias voltage (>1000 V), and have low Q-value (0.764 MeV). Also, 3He is not readily available material. Thus, there is a strong need to find an alternative detection material. 10B isotope has a high neutron absorption cross-section, and it has been tested as a coating on the semiconducting materials. Due to the two-step process, neutron capture through 10B, and then electron-hole pair generation in a typical semiconducting material, the efficiency of these devices is not up to the mark. The progress in h-BN based detectors requires a review to envision the further improvement in this technology.

It is shown that the representation theory of some finitely presented groups thanks to their $SL_2(\mathbb{C})$ character variety is related to algebraic surfaces. We make use of the Enriques-Kodaira classification of algebraic surfaces and the related topological tools to make such surfaces explicit. We study the connection of $SL_2(\mathbb{C})$ character varieties to topological quantum computing (TQC) as an alternative to the concept of anyons. The Hopf link $H$, whose character variety is a Del Pezzo surface $f_H$ (the trace of the commutator), is the kernel of our view of TQC. Qutrit and two-qubit magic state computing, derived from the trefoil knot in our previous work, may be seen as TQC from the Hopf link. The character variety of some two-generator Bianchi groups as well as that of the fundamental group for the singular fibers $\tilde{E}_6$ and $\tilde{D}_4$ contain $f_H$. A surface birationally equivalent to a $K_3$ surface is another compound of their character varieties.

A wide variety of applications require high peak laser intensity in conjunction with a narrow spectral linewidth. Typically, injection-locked amplifiers have been employed for this purpose, where a continuous wave oscillator is amplified in a secondary external resonant amplifier cavity using a pulsed pump laser. In contrast, here we demonstrate a setup that combines a CW Ti:sapphire oscillator and pulsed amplifier in a single optical cavity, resulting in a compact system. Dichroic beam combination of blue wavelength semiconductor diodes and the green wavelength of a Nd:YAG laser allowed the simultaneous excitation of the Ti:sapphire crystal by both continuous-wave and pulsed pump sources. A linewidth of <2MHz is achieved in continuous wave operation, while the linewidth increases to about 10MHz in the combined CW + pulsed mode with a pulse duration of 73ns. A peak pulse intensity of 0.2kW is achieved, which should enable efficient single-pass second harmonic generation in a nonlinear crystal.

One of the earliest hallmarks of plant immune response is production of reactive oxygen spe-cies (ROS) in different subcellular compartments, which regulate plant immunity. A suitable equilibrium, which is crucial to prevent ROS over-accumulation leading to oxidative stress, is maintained by salicylic acid (SA), a chief regulator of ROS. However, ROS are not only acting downstream of SA signaling, but were also proposed to be a central component of a self-amplifying loop that regulates SA signaling as well as the interaction balance between dif-ferent phytohormones. The exact role of this crosstalk, the position where SA interferes with ROS signaling and ROS interferes with SA signaling and the outcome of this regulation depend on the origin of ROS but also on the pathosystem. The precise spatiotemporal regulation of or-ganelle specific ROS and SA levels determine the effectiveness of pathogen arrest and is there-fore crucial for a successful immune response. However, the regulatory interplay behind still remain poorly understood, as up till now, the role of organelle specific ROS and SA in HR-conferred resistance has mostly been studied by altering the level of a single component. In order to address these aspects, a sophisticated combination of research methods for monitoring the spatiotemporal dynamics of key players and transcriptional activity in plants is needed, and will most probably consist of biosensors and precision transcriptomics.

As a critical transmitter, the compact 532 nm lasers operating on high repetition and narrow pulse widths have been used widely for airborne or space-borne laser active remote sensing. We developed a free space pumped TEM₀₀ mode sub-nanosecond 532 nm laser that occupied a volume of less than 125 mm × 50 mm × 40 mm (0.25 liters). The fundamental 1064 nm laser consists of a passively Q-switched composite crystal microchip laser and an off-axis, two-pass power amplifier. The pump sources were two single-emitter semiconductor laser diodes (LD) of 808 nm with a maximum continuous wave (CW) power of 10 W each. The average power of fundamental 1064 nm laser was 1.26 W with the laser operating at 16 kHz repetition rates, and 857ps pulse widths. Since the beam distortion would be severe in microchip lasers in terms of the increase in heat load, for obtaining a high beam quality of 532 nm, the beam distortion was compensated by adjusting the distribution of pumping beam in our experiment of fundamental amplification. Furthermore, better than 0.6 W average power, 770 ps, beam quality of M² ＜1.2, and 16 kHz pulse output at 532 nm was obtained by a Type I LiB₃O₅ (LBO) crystal in the critical phase matching (CPM) regime for second harmonic generation (SHG).

Mathematical models across the applied sciences often utilize a standard methodological representation called a state variable formulation more commonly referred to as state space form. Recent research in unmanned underwater vehicle motor turbine blade thermal modeling for fatigue-life is generalized here permitting the proposed novel state space from to be applied to electrodynamics, motion mechanics, and many other disciplines. Proposed here is a very compact form inherently representing time variance, with a convenient presentation of dynamic variables applicable to all proper transfer functions, where all the distinct, real poles, zeros and gain of the transfer function appear as explicit components in the state space. The resulting manifestation simplifies utilization of the state space methods broadly across the applied sciences.

This present work explores the performance of a thermal-magnetic engine of Otto type, considering as a working substance an effective interacting spin model corresponding to the q− state clock model. We obtain all the thermodynamic quantities for the q = 2, 4, 6, 8 cases in a small lattice size (3×3 with free boundary conditions) by using the exact partition function calculated from the energies of all the accessible microstates of the system. The extension to bigger lattices was performed using the mean-field approximation. Our results indicate that the total work extraction of the cycle is highest for the q=4 case, while the performance for the Ising model (q=2) is the lowest of all cases studied. These results are strongly linked with the phase diagram of the working substance and the location of the cycle in the different magnetic phases present, where we find that the transition from a ferromagnetic to a paramagnetic phase extracts more work than one of the Berezinskii–Kosterlitz–Thouless to paramagnetic type. Additionally, as the size of the lattice increases, the extraction work is lower than smaller lattices for all values of q presented in this study.

Hematological and biochemical reference values in sickle cell disease (SCD) are crucial for patient management and evaluation of interventions. This study was conducted at Muhimbili National Hospital (MNH) in Dar es Salaam, to establish laboratory reference ranges in SCD at steady-state. Patients were grouped into five age groups with respects to their sex. Aggregate functions were used to handle repeated measures within the indi-vidual level in each age group. A nonparametric approach was used to smooth the curves and a parametric approach was used to determine SCD normal ranges. Comparison between males and females and against the general population was documented. Data from 4,422 patients collected from 2004-2015 were analyzed. The majority of the patients (35.41%) were children aged between 5-11 years. There were no significant differences (p≥0.05) in mean corpuscular hemoglobin concentration (MCHC), lymphocytes, basophils and bilirubin direct observed between males and females. Significant differences (p<0.05) were observed in all selected parameters across age groups except neutrophils and MCHC in adults, as well as platelets and alkaline phosphatase in infants when SCD estimates were compared to the general population. Laboratory reference ranges in SCD at steady-state were different from those of the general population and varied with sex and age. The established reference ranges for SCD at steady-state will be a helpful in the management and monitoring of the progress of SCD.

At the level of the 50 U.S. states, an interconnected nexus of well-being variables exists. These variables have been shown to strongly correlate with estimates of state IQ in interesting ways. But the state IQ estimates (McDaniel 2006) are now more than 16 years old, and the state well-being estimates (Pesta et al., 2010) are over 12 years old. Updated state IQ and well-being estimates are therefore needed. I thus first created new state IQ estimates by analyzing scores from both the Program for the International Assessment of Adult Competency (for adults), and the National Assessment of Educational Progress (for fourth and eighth grade children) exams. I also created new global well-being scores by analyzing state variables from the following four well-being subdomains: crime, income, health, and education. When validating the nexus, several interesting correlations existed among the variables. For example, state IQ most strongly predicted FICO credit scores, alcohol consumption (directly), income inequality, and state temperature. Interestingly, state IQ derived here also correlated .58 with state IQ estimates from over 100 years ago. Global well-being likewise correlated with many old and new variables in the nexus, including a correlation of .80 with IQ. In sum, at the level of the U.S. state, a nexus of important, strongly correlated variables exists. These variables comprise well-being, and state IQ is a central node in this network.

Schizophrenia is widely seen as a disorder of dysconnectivity. Neuroimaging studies have examined both structural and functional connectivity in the disorder, but these modalities have rarely been integrated directly. We scanned 29 patients with schizophrenia and 25 healthy control subjects and acquired resting state fMRI and diffusion tensor imaging. The Functional and Tractographic Connectivity Analysis Toolbox (FATCAT) was used to estimate functional and structural connectivity of the default mode network. Correlations between modalities were investigated, and multimodal connectivity scores (MCS) were created using principal components analysis. Nine of 28 possible region pairs showed consistent (>80%) tracts across participants. Correlations between modalities were found among those with schizophrenia for the prefrontal cortex, posterior cingulate, and lateral temporal lobes with frontal and parietal regions, consistent with frontotemporoparietal network involvement in the disorder. In patients, MCS values correlated with several aspects of the Positive and Negative Syndrome Scale, positively with those involving inwardly directed psychopathology, and negatively with those involving external psychopathology. In this preliminary sample, we found FATCAT to be a useful toolbox to directly integrate and examine connectivity between imaging modalities. A consideration of conjoint structural and functional connectivity can provide important information about the network mechanisms of schizophrenia.

We provide methodology and numerical results for the Hattendorff differential equa- tion for the continuous time evolution of the variance of L(j)t , the loss at time t random variable for a multi-state process, given that the state at time t is j.

The conformational dependence of the matrix element for spin-orbit coupling and of the electronic coupling for charge separation are determined for an electron donor-acceptor system containing a pyrene acceptor and a dimethylaniline donor. Different kinetic and energetic aspects that play a role in the spin-orbit charge transfer intersystem crossing (SOCT-ISC) mechanism are discussed. This includes parameters related to initial charge separation and the charge recombination pathways using the (Semi-Classical) Marcus Theory for electron transfer. The spin-orbit coupling, which plays a significant role in charge recombination to the triplet state can be probed by (TD-)DFT, using the latter as a tool to understand and predict the SOCT-ISC mechanism. The matrix elements for spin-orbit coupling for acetone and 4-thio-thymine are used for benchmarking. (Time Dependent-) Density Functional Theory (DFT and TD-DFT) calculations are applied using the quantum chemical program Amsterdam Density Functional (ADF).

High-energy small electron beams generated by linear accelerators are used for radiotherapy of localized superficial tumors. The aim of the present study is to assess the dosimetric performance under small radiation therapy electron beams of the novel PTW microSilicon detector by comparison with commercially available dosimeters. Relative dose measurements of circular fields with 20, 30, 40 and 50 mm aperture diameters were performed for 4 to 12 MeV energy range of electron beams generated by an Elekta Synergy linac. Percentage depth dose, transverse profiles and output factors normalized to the 10 × 10 cm2 reference field were measured. All dosimetric data were collected in a PTW MP3 motorized water phantom at SSD of 100cm by using the novel PTW microSilicon detector. The PTW diode E and the PTW microDiamond were also used in all beam aperture for benchmarking. Data for the biggest field size were also measured by the PTW Advanced Markus ionization chamber.Measurements performed by the microSilicon are in good agreement with the reference values for all the tubular applicators and beam energies, within the stated uncertainties. This confirms the reliability of the microSilicon detector for relative dosimetry of small radiation therapy electron beams collimated by tubular applicators.

Li₇La₃Zr₂O₁₂Solid-state reaction was used for Li₇La₃Zr₂O₁₂ material synthesis from Li₂CO₃, La₂O₃ and ZrO₂ powders. Phase investigation by XRD, SEM and EDS methods of Li₇La₃Zr₂O₁₂ were carried out. The molar heat capacity of Li₇La₃Zr₂O₁₂ at constant pressure in the temperature range 298-800 K should be calculated as Cp,m = 518.135+0.599 × T - 8.339 × T−2, where T is absolute temperature, . Thermodynamic characteristics of Li₇La₃Zr₂O₁₂ were determined as next: entropy S0298 = 362.3 J mol-1 K-1, molar enthalpy of dissolution ΔdHLlZO = ˗ 1471.73 ± 29.39 kJ mol−1, the standard enthalpy of formation from elements ΔfH0 = ˗ 9327.65 ± 7.9 kJ mol−1, the standard Gibbs free energy of formation ∆f G0298 = ˗9435.6 kJ mol-1.

AbstractIn the evolving modern era of neuromodulation for movement disorders in adults and children, much progress has been made recently characterizing the human motor network (MN) with potentially important treatment implications. Herein is a focused review of relevant resting state fMRI functional and effective connectivity of the human motor network across the lifespan in health and disease. The goal is to examine how the transition from static functional to dynamic effective connectivity may be especially informative of network-targeted movement disorder therapies, with hopeful implications for children.Impact StatementWhile functional connectivity has elucidated much MN properties with relation to age, disease, and behavior, effective connectivity has been shown to be useful in MN-informed therapies in adults. Thus, effective connectivity may have potential to impact childhood movement disorder therapies, given the lower to no patient demand.

The measurements of the proton electromagnetic form factors in the time-like region using the initial state radiation technique are reviewed. Recent experimental studies have shown that initial state radiation processes at high luminosity electron-positron colliders can be effectively used to probe the electromagnetic structure of hadrons. The BABAR experiment at the B-factory PEP-II in Stanford and the BESIII experiment at the $\tau$-charm factory BEPC-II in Beijing have measured the time-like form factors of the proton using the initial state radiation process $e^{+}e^{-}\to pbar{p}\gamma$. The two kinematical regions where the photon is emitted from the initial state at small and large polar angles have been investigated. In the first case the photon is in the region not covered by the detector acceptance and is not detected. The Born cross section and the proton effective form factor have been measured over a wide and continuous range of the the momentum transfer squared $q^2$ from threshold up to ~42 (GeV/c)$^2$. The ratio of electric and magnetic form factors of the proton has been also determined. In this report, the theoretical aspect and the experimental studies of the initial state radiation process $e^{+}e^{-}\to p\bar{p}\gamma$ are described. The measurements of the Born cross section and the proton form factors obtained in these analyses near the threshold region and in the relatively large $q^2$ region are examined. The experimental results are compared to the predictions from theory and models. Their impact on our understanding of the nucleon structure is discussed.

Sub-Saharan social-ecological systems are undergoing changes in environmental conditions, including modifications in rainfall pattern and biodiversity loss. Consequences of such changes depend on complex causal chains which call for integrated management strategies whose efficiency could benefit from ecosystem dynamic modelling. However, ecosystem models often require lots of quantitative information for estimating parameters, which is often unavailable. Alternatively, qualitative modelling frameworks have proved useful for explaining ecosystem response to perturbations, while requiring fewer information and providing more general predictions. However, current qualitative methods have some shortcomings which may limit their utility for specific issues. In this paper, we propose the Ecological Discrete-Event Network (EDEN), an innovative qualitative dynamic modelling framework based on "if-then" rules which generates many alternative event sequences (trajectories). Based on expert knowledge, observations and literature, we use this framework to assess the effect of permanent changes in surface water and herbivores diversity on vegetation and socio-economic transitions in an East African savanna. Results show that water availability drives changes in vegetation and socio-economic transitions, while herbivore functional groups had highly contrasted effects depending on the group. This first use of EDEN in a savanna context is promising for bridging expert knowledge and ecosystem modelling.

Mental stress state recognition using electroencephalogram (EEG) signals for real-life applications needs a conventional wearable device. This requires an efficient number of EEG channels and an optimal feature set. The main objective of the study is to identify an optimal feature subset that can best discriminate mental stress states while enhancing the overall performance. Thus, multi-domain feature extraction methods were employed, namely, time domain, frequency domain, time-frequency domain, and network connectivity features, to form a large feature vector space. To avoid the computational complexity of high dimensional space, a hybrid feature selection (FS) method of minimum Redundancy Maximum Relevance with Particle Swarm Optimization and Support Vector Machine (mRMR-PSO-SVM) is proposed to remove noise, redundant, and irrelevant features and keep the optimal feature subset. The performance of the proposed method is evaluated and verified using four datasets, namely EDMSS, DEAP, SEED, and EDPMSC. To further consolidate, the effectiveness of the proposed method is compared with that of the state-of-the-art heuristic methods. The proposed model has significantly reduced the features vector space by an average of 70% in comparison to the state-of-the-art methods while significantly increasing overall detection performance.

This paper aims to provide the smart grid research community with an open and accessible general mathematical framework to develop and implement optimal flexibility mechanisms in large-scale network applications. The motivation of this paper is twofold. On the one hand, flexibility mechanisms are currently a hot topic of research, which is aimed to mitigate variation and uncertainty of electricity demand and supply in decentralised grids with a high aggregated share of renewables. On the other hand, a large part of such related research is performed by heuristic methods, which are generally inefficient (such methods do not guarantee optimality) and difficult to extrapolate for different use cases. Alternatively, this paper presents an MPC-based (Model Predictive Control) framework explicitly including a generic flexibility mechanism which is easy to particularise to specific strategies such as Demand Response, Flexible Production and Energy Efficiency Services. The proposed framework is benchmarked with other non-optimal control configurations to better show the advantages it provides. The work of this paper is completed by the implementation of a generic use case which aims to further clarify the use of the framework and thus, to ease its adoption by other researchers in their specific flexibility mechanisms applications.

The on-state voltage of MOSFETs is a convenient and powerful temperature-sensitive electric parameter (TSEP) to determine the junction temperature, thus enabling device monitoring, protection, diagnostics and prognostics. The main hurdle in the use of the on-state voltage as a TSEP is the per-device characterization procedure, to be carried out in a controlled environment, with high costs. In this paper we compare two novel techniques for MOSFET junction temperature estimation: controlled shoot-through and direct heating by resistive heaters embedded in two Kapton (polyimide) films. Both allow in-place characterization of the TSEP curve with the device mounted in its final circuit and assembly, including the working heat sink. The two methods are also validated against the conventional procedure in a thermal chamber.

Li3FeN2 material was synthesized by two-step solid-state method from Li3N (adiabatic camera) and FeN2 (tube furnace) powders. Phase investigation of Li3N, FeN2 and Li3FeN2 were carried out. Discharge capacity of Li3FeN2 is 343 mAh g-1, that is about 44.7% of theoretic capacity. The molar heat capacity of Li3FeN2 at constant pressure in the temperature range 298-900 K should be calculated as Cp,m = 77,831 + 0,130 × T – 6,289 × T-2, where T is absolute temperature, . Thermodynamic characteristics of Li3FeN2 were determined as next: entropy S0298 = 116.2 J mol-1 K-1, molar enthalpy of dissolution ΔdHLFN = ˗ 206,537 ± 2,8 kJ mol−1, the standard enthalpy of formation ΔfH0 = ˗ 291.331 ± 5.7 kJ mol−1, entropy S0298 = 113.2 J mol-1 K-1 (Neumann-Kopp rule) and 116.2 J mol-1 K-1 (W.Herz rule), the standard Gibbs free energy of formation ∆f G0298 = ˗276,7 kJ mol-1.

With the automotive industry moving towards automated driving, sensing is increasingly important in enabling technology. The virtual sensors allow data fusion from various vehicle sensors and provide a prediction for measurement that is hard or too expensive to measure in another way or in the case of demand on continuous detection. In this paper, virtual sensing is discussed for the case of vehicle suspension control, where information about the relative velocity of the unsprung mass for each vehicle corner is required. The corresponding goal can be identified as a regression task with multi-input sequence input. The hypothesis is that the state-of-art method of Bidirectional Long-Short Term Memory (BiLSMT) can solve it. In this paper, a virtual sensor has been proposed and developed by training a neural network model. The simulations have been performed using an experimentally validated full vehicle model in IPG Carmaker. Simulations provided the reference data which was used for Neural Network (NN) training. The extensive dataset covering 26 scenarios has been used to obtain training, validation and testing data. The Bayesian Search was used to select the best neural network structure using root mean square error as a metric. The best network is made of 167 BiLSTM, 256 fully connected hidden units and 4 output units. Error histograms and spectral analysis of the predicted signal compared to the reference signal are presented. The results demonstrate the good applicability of neural network-based virtual sensors to estimate vehicle unsprung mass relative velocity.

Background: World Health Organization (WHO) estimates that there were 558000 new cases with resistance to Rifampicin, of which 82% had multidrug-resistant tuberculosis (MDR-TB). Objectives: We aimed to identify the prevalence of MDR-TB in River Nile state, Sudan, and the risk factors contributing to its occurrence. Methods: This was a descriptive cross-sectional hospital-based study involved 200 specimens taken from patients suspected of having MDR-TB tested using an automated GeneXpert assay. Results: Results of GeneXpert assay showed that the presence of Mycobacterium tuberculosis in 81 (40.5%), and out of 81 positive test results there were 13 (16%) had MDR-TB. Additionally, 7 cases of MDR-TB were previously treated which represented about (53%) of MDR patients, the remaining 6 MDR-TB patients were new cases and represented (47%) of MDR-TB patients. Moreover, there were 4 MDR-TB patients who had a history of contact with MDR-TB patients. Conclusion: Prevalence of MDR-TB in River Nile State, Sudan was 16%, which is greater than WHO estimation for Sudan (10.1%). The results revealed that the main risk factor to develop MDR-TB was a history of contact with MDR-TB, so adherence to treatment and social awareness about the spread of MDR-TB are crucial preventive measures.

In light of the self-simulation hypothesis, a simple form implementation of the principle of efficient language is discussed in a self-referential geometric quasicrystalline state sum model in three dimensions. Emergence is discussed in context of geometric state sum models.

The purpose of this study is to examine the relationship between the institutional investors which can affect financial performance for corporate sustainability on the income smoothing. Therefore, this study focus on the connection between the nature of stock rights and income smoothing in China. For this study, hypotheses were established on the relationship each state-controlled companies, income smoothing, and information equilibrium of individual investors, and empirical analysis was conducted through related variables. The analysis results are summarized in three categories as follows. First, this research finds that state-controlled firms (CONTs) prefer income smoothing activities compared to non-state-controlled firms for the long-term sustainable development of firms using data from 2011 to 2019. Second, this study found out that Institutional investors support the behavior of CONTs to smooth their earnings because this behavior is seen as an attempt by CONTs to convey valuable private information to other investors. Third, we was able to discover that institutional investors' monitoring effect is predominantly driven by pressure-resistant institutional investors. This research complements the lack of empirical research on income smoothing and enable to give a guideline that the type of stock rights is a critical key determinant of participation in income smoothing activities for stable growth and sustainability in the future.

The Epithelial- Mesenchymal Transition (EMT) is a biological phenomenon associated with explicit phenotypic and molecular changes in cellular traits. Unlike the earlier-held popular belief of it being a binary process, EMT is now thought of as a landscape including diverse hybrid E/M phenotypes manifested by varying degrees of the transition. These hybrid cells can co-express both epithelial and mesenchymal markers and/or functional traits, and can possess the property of collective cell migration, enhanced tumor-initiating ability, and immune/targeted therapy-evasive features, all of which are often associated with worse patient outcomes. These characteristics of the hybrid E/M cells have led to a surge in studies that map their biophysical and biochemical hallmarks that can be helpful in exploiting their therapeutic vulnerabilities. This review discusses recent advances made in investigating hybrid E/M phenotype(s) from diverse biophysical and biochemical aspects by integrating live cell-imaging, cellular morphology quantification and mathematical modeling, and highlights a set of questions that remain unanswered about the dynamics of hybrid E/M states.

Abstract: Coal bed methane (CBM) reservoirs are complex systems whose properties differ from those of conventional reservoirs. Coal seams are dual-porosity systems that comprise the porosities of the matrix and cleat system. Gas in the coal seams can be stored as free gas in the cleat system and as adsorbed gas in the porous medium. The flow mechanisms of the natural gas through the formation include desorption, diffusion, and Darcy’s flow regimes. The permeability of CBM reservoirs is more sensitive to pressure variations than conventional gas reservoirs. To study the flow behavior of CBM reservoirs it is mandatory to use a model that considers their unique characteristics. The objective of this study was to propose a physical and mathematical model of production performance for horizontal wells in CBM reservoirs whose permeability is dependent on pressure. A solution for the model was obtained by applying Pedrosa´s transformation, perturbation theory, Laplace transformation, the point source method, and Sthefest´s algorithm. The solution to this problem was validated with previous work thoroughly. The type curves of the model were built and the pressure transient behavior of the model was analyzed and discussed. The effects of several parameters on pressure behavior were also discussed.

In systems biology, biological phenomena are often modeled by ODE and distributed in the de facto standard file format SBML. The primary analyses performed with such models are dynamic simulation, steady-state analysis, and parameter estimation. These methodologies are mathematically formalized, and libraries for such analyses have been published. Several tools exist to create, simulate, or visualize models encoded in SBML. However, setting up and establishing analysis environments is a crucial hurdle for non-modelers. Therefore, easy access to perform fundamental analyses of ODE models is a significant challenge. We developed SBMLWebApp, a web-based service to execute SBML-based simulations, steady-state analysis, and parameter estimation directly in the browser without the need for any setup or prior knowledge to address this issue. SBMLWebApp visualizes the result and numerical table of each analysis and provides a download of the results. SBMLWebApp allows users to select and analyze SBML models directly from the BioModels Database. Taken together, SBMLWebApp provides barrier-free access to an SBML analysis environment for simulation, steady-state analysis, and parameter estimation for SBML models. SBMLWebApp is implemented in Java™ based on an Apache Tomcat® web server using COPASI, the SBSCL, and LibSBMLSim as simulation engines. SBMLWebApp is licensed under MIT with source code available from https://github.com/TakahiroYamada/SBMLWebApp. The program runs online at http://simulate-biology.org.

This paper reports applying Minimax principle and impulsive differential inequality to derive the existence of multiple stationary solutions and the global stability of a positive stationary solution for a delayed feedback Gilpin-Ayala competition model with impulsive disturbance. The conclusion obtained in this paper reduces the conservatism of the algorithm compared with the known literature, for the impulsive disturbance is not limited to impulsive control.

Hydrogenated amorphous silicon (a-Si:H) can be produced by plasma-enhanced chemical vapour deposition (PECVD) of SiH4 (Silane) mixed with Hydrogen. The resulting material shows outstanding radiation resistance properties and can be deposited on a wide variety of different substrates. These devices have been used to detect many different kinds of radiation namely: MIPs, x-rays, neutrons and ions as well as low energy protons and alphas. However, MIP detection using planar diodes has always been difficult due to the unsatisfactory S/N ratio arising from a combination of high leakage current, high capacitance and a limited charge collection efficiency (50% at best for a 30 µm planar diode). To overcome these limitations the 3D-SiAm collaboration proposes to use a 3D detector geometry. The use of vertical electrodes allows for a small collection distance to be maintained while conserving a large detector thickness for charge generation. The depletion voltage in this configuration can be kept below 400 V with consequent reduction in the leakage current. In this paper, following a detailed description of the fabrication process, the results of the tests performed on the planar p-i-n structures made with ion implantation of the dopants and with carrier selective contacts will be illustrated.

This study used structural equation modelling (SEM) to evaluate the direct effect of sex and age on stroke types and outcomes in Tertiary Health Facilities in Rives State, Nigeria. The study was a cross-sectional retrospective hospital-based research that utilized specific stroke patients’ information between 2015-2019. The study obtained the sex and age, stroke type (ischemic/hemorrhagic), and outcomes (No disability/disability/death) from the records. The retrieved data was Microsoft Excel (2016), then analyzed using SPSS (version 21, Amos) and STATGRAPHICS centurion (Stat Point Tech., Inc.). From the result, out of the recorded 1916 stroke patients, 1229 (64.1%) were female, while 687 (35.9%) were males. The older adults (>55 years) had more recorded cases (n=1289) than young adults (ages 18–35 years; n=77) and middle-aged adults (ages 36–55 years, n=550). The SEM results showed that age was significantly associated with stroke type (P<0.001) and outcomes (P=0.038), while sex was significantly associated with stroke outcomes (P<0.001). The likelihood of death was 1.3 times higher in hemorrhagic stroke than ischemic stroke. In conclusion, age and sex had direct effects on stroke type, while age had a direct effect on stroke outcome. Hemorrhagic stroke was more likely to cause death than ischemic stroke in the studied population.

Beyond the usual ferromagnetic and paramagnetic phases present in spin systems, the usual q-state clock model, presents an intermediate vortex state when the number of possible orientations q for the system is equal to 5 or larger. Such vortex states give rise to the Berezinskii-Kosterlitz-Thouless (BKT) phase present up to the XY model in the limit q→∞. Based on information theory, we present here an analysis of the classical order parameters plus new short-range parameters defined here. Thus, we show that even using the first nearest neighbors spin-spin correlations only, it is possible to distinguish the two transitions presented by this system for q greater than or equal to 5. Moreover, the appearance at relatively low temperature and disappearance of the BKT phase at a rather fix higher temperature is univocally determined by the short-range interactions recognized by the information content of classical and new parameters.

Clausius’ virial theorem set a basis for relating kinetic energy in a body of independent material particles to its potential energy, pointing to their complementary role with respect to the second law of maximum entropy. In action mechanics, expressing the entropy of ideal gases as a capacity factor for sensible heat or enthalpy plus the configurational work to sustain the relative translational, rotational and vibrational action yields algorithms for estimating chemical reaction rates and positions of equilibrium. All properties of state including entropy, work potential as Helmholtz and Gibbs energies and activated transition state reaction rates can be estimated, using easily accessible molecular properties, such as atomic weights, bond lengths, moments of inertia and vibrational frequencies. Understanding how Clausius’ virial theorem balances the internal kinetic energy with field potential energy justifies partitioning between thermal and statistical properties of entropy, yielding a more complete view of the evolutionary nature of the second law of thermodynamics. The ease of performing these operations is illustrated by three important chemical gas phase reactions, the reversible dissociation of the hydrogen molecules, lysis of water to hydrogen and oxygen and the reversible formation of ammonia from nitrogen and hydrogen. Employing the ergal also introduced by Clausius to define the reversible internal work to overcome molecular interactions plus the configurational internal work of negative Gibbs energy as a function of volume or pressure may provide a practical guide for managing risk in industrial processes and climate change at the global scale.

Port state control inspections implemented under the Paris Memorandum of Understanding (MoU) have become known as one of the best instruments for maritime administrations in European Union (EU) Member States to ensure that the ships docked in their ports comply with all maritime safety requirements. This paper focuses on the analysis of all inspections made between 2013 and 2018 in the top ten EU ports incorporated in the Paris MoU (17,880 inspections). The methodology consists of a multivariate statistical information system (STATIS) analysis using the inspected ship’s characteristics as explanatory variables. The variables used describe both the inspected ships (classification society, flag, age and gross tonnage) and the inspection (type of inspection and number of deficiencies), yielding a dataset with more than 600,000 elements in the data matrix. The most important results are that the classifications obtained match the performance lists published annually by the Paris MoU and the classification societies. Therefore, the approach is a potentially valid classification method and would then be useful to maritime authorities as an additional indicator of a ship’s risk profile to decide inspection priorities and as a tool to measure the evolution in the risk profile of flag over time.

Estimation of core and surface temperature is one of the crucial functionalities of the lithium-ion Battery Management System (BMS) towards providing effective thermal management, fault detection and operational safety. While, it is impractical to measure core temperature using physical sensors, implementing a complex estimation strategy in on-board low-cost BMS is challenging due to high computational cost and the cost of implementation. Typically, a temperature estimation scheme consists of a heat generation model and a heat transfer model. Several researchers have already proposed ranges of thermal models having different levels of accuracy and complexity. Broadly, there are first-order and second-order heat capacitor-resistor-based thermal models of lithium-ion batteries (LIBs) for core and surface temperature estimation. This paper deals with a detailed comparative study between these two models using extensive laboratory test data and simulation study to access suitability in online prediction and onboard BMS. The aim is to guide whether it’s worth investing towards developing a second-order model instead of a first-order model with respect to prediction accuracy considering modelling complexity, experiments required and the computational cost. Both the thermal models along with the parameter estimation scheme are modelled and simulated using MATLAB/Simulink environment. Models are validated using laboratory test data of a cylindrical 18650 LIB cell. Further, a Kalman Filter with appropriate process and measurement noise levels are used to estimate the core temperature in terms of measured surface and ambient temperatures. Results from the first-order model and second-order models are analyzed for comparison purposes.

Ensuring a protection scheme in DC distribution is more difficult to achieve against pole-to-ground fault than in AC distribution system because of the absence of zero crossing points and low line impedance. To complement the major obstacle of limiting the fault current, several compositions have been proposed related to mechanical switching and solid-state switching. Among them, solid-state circuit breakers(SSCBs) are considered a possible solution to limit fast fault current. However, they may cause problems in circuit complexity, reliability and cost-related troubles due to the use of multiple power semiconductor devices and additional circuit configuration to commutate current. This paper proposes the SSCB with a coupled inductor(SSCB-CI) which has symmetrical configuration. The circuit is comprised of passive components like commutation capacitors, a CI and damping resistors. Thus, proposed SSCB-CI offers the advantages of simple circuit configuration and fewer utilized power semiconductor devices than another typical SSCBs in LVDC microgrid. For analysis, six operation states are described for the voltage across main switches and fault current. The effectiveness of the SSCB-CI against a short-circuit fault is proved via simulation and experimental results in a lab-scale prototype.

“Money has always been something of an embarrassment to economic theory. Everyone agrees that it is important; indeed, much of macroeconomic policy discussion makes no sense without reference to money. Yet, for the most part theory fails to provide a good account for it.” (Banerjee and Maskin, 1996, p. 955)The debate about whether or not a growth imperative exists in debt based, interest bearing mone- tary systems has not yet been settled. It is the goal of this paper to introduce a new perspective in this discussion.For that purpose an SFC computational model is constructed which simulates a post Keynesian Endogenous Money system without including economic parameters such as production, wages, consumption and savings. A case is made that isolating the monetary system allows for better analysis of the inherent properties of such a system.Loan demands, which are assumed to happen, are the driving force of the model. Simulations can be run in two modes, each based on a different assumption. Either the growth rate of the money stock is assumed to be constant or the loan rate, expressed as a percentage of the money stock, is assumed to be constant.Simulations with varying parameters are run in order to determine the conditions under which the model converges to stability, which is defined as converging to a bounded debt rate.The analysis shows that stability of the model is dependent on net bank profit ratios, expressed relative to their debt assets, remaining below the growth rate of the money stock. Based on these findings it is argued that the question about the existence of a growth imperative in debt based, interest bearing monetary systems needs to be reframed. The question becomes whether a steady state economy can realistically support such a system without destabilising it. In order to answer this question real world behavior of economic actors must be included in the model.It is concluded that there are indications that it might not be feasible for a steady state economy to support a stable debt based, interest bearing monetary system without strong interventions. However, more research is necessary for a definite answer. Real world observable data should be analysed through the lens of the presented model to bring more clarity.

Recent progress in deep learning has led to accurate and efficient generic object detection networks. Training of highly reliable models depends on large datasets with highly textured and rich images. However, in real-world scenarios, the performance of the generic object detection system decreases when (i) occlusions hide the objects, (ii) objects are present in low-light images, or (iii) they are merged with background information. In this paper, we refer to all these situations as challenging environments. With the recent rapid development in generic object detection algorithms, notable progress has been observed in the field of object detection in challenging environments. However, there is no consolidated reference to cover state-of-the-art in this domain. To the best of our knowledge, this paper presents the first comprehensive overview, covering recent approaches that have tackled the problem of object detection in challenging environments. Furthermore, we present the quantitative and qualitative performance analysis of these approaches and discuss the currently available challenging datasets. Moreover, this paper investigates the performance of current state-of-the-art generic object detection algorithms by benchmarking results on the three well-known challenging datasets. Finally, we highlight several current shortcomings and outline future directions.

The space gravitational wave detection and drag free control requires the micro-thruster to have very low thrust noise within 0.1mHz~100mHz, which poses a great challenge to the ground thrust test. The evaluation and decoupling of thermal noise are the difficulties in the application of torsion balance for most thrusters dissipate heat in the experiment. The research has adopted a calibration scheme of micro-Newton thrust torsion balance. On the basis of Lisa Pathfinder's former research and using ideas inspired from PID control and multi time scale (MTS) for reference, the paper proposes to expand the state space of temperature to be applied on thrust prediction based on fine tree regression (FTR), to subtract the thermal noise filtered by transfer function fitted with z-domain vector fitting (ZDVF). The results show that the thrust amplitude thrust density in diurnal temperature fluctuation is decoupled from 24μN/Hz1/2 to 4.9μN/Hz1/2 at 0.11mHz. And the 1μN square wave modulations of electrostatic fins (ESF) is extracted from the simultaneously ambiguous background of temperature for PTC's heating and cooling. The FTR method is well demonstrated in thermal noise decoupling and can guide the design of thermal control and be extended to other physical quantities for noise decoupling.

The purpose of this paper is to build a new bridge between category theory and a generalized probability theory known as noncommutative probability or quantum probability, which was originated as a mathematical framework for quantum theory, in terms of states as linear functional defined on category algebras. We clarify that category algebras can be considered as generalized matrix algebras and that the notions of state on category as linear functional defined on category algebra turns out to be a conceptual generalization of probability measures on sets as discrete categories. Moreover, by establishing a generalization of famous GNS (Gelfand-Naimark-Segal) construction, we obtain a representation of category algebras of †-categories on certain generalized Hilbert spaces which we call semi-Hilbert modules over rigs.

The change in the value of the breaking energy is discussed here for selected steel grades used in building structures after subjecting the samples made of them to episodes of heating in the steady-state heating regime and then cooling in a simulated fire conditions. These changes were recorded based on the instrumented Charpy impact tests, in relation to the material initial state. The S355J2+N, 1H18N9T steels and also X2CrNiMoN22-5-3 duplex steel were selected for detailed analysis. The fire conditions were modelled experimentally by heating the samples and then keeping them for a specified time at a constant temperature of: 600°C (first series) and 800°C (second series), respectively. Two alternative cooling variants were investigated in the experiment: slow cooling of the samples in the furnace, simulating the natural fire progress, without any external extinguishing action, and cooling them in water mist simulating an extinguishing action by a fire brigade. The temperature of the tested samples was set at the level -20oC and alternatively at the level + 20oC. The conducted analysis is aimed at assessing the risk of sudden, catastrophic fracture of load-bearing structure made of steel degraded as a result of a fire previously occurred with different development scenarios.

We present a new analytical method to find the asymptotic stable equilibria states based on the Markov chain technique. We reveal this method on the SIR-type epidemiological model that we developed for viral diseases with long-term immunity memory pandemic. This is a large-scale model containing 15 nonlinear ODE equations, and classical methods have failed to analytically obtain its equilibria. The proposed method is used to conduct a comprehensive analysis by a stochastic representation of the dynamics of the model, followed by finding all asymptotic stable equilibrium states of the model for any values of parameters and initial conditions.

The fact that quantum gravity does not admit a co-variant vacuum state has far-reaching consequences for all physics. It points out that space could not be empty, and we return to the notion of an ether . Such a concept requires a preferred reference frame for, e.g., universe expansion and black holes. Here, we intend to discuss vacuum and quantum gravity from three essential viewpoints: universe expansion, black holes existence, and quantum decoherence.

Recent brain imaging findings by using different methods (e.g., fMRI and PET) have suggested that social anxiety disorder (SAD) is correlated with alterations in regional or network-level brain function. However, due to many limitations associated with these methods, such as poor temporal resolution and limited number of samples per second, neuroscientists could not quantify the fast dynamic connectivity of causal information networks in SAD. In this study, SAD-related changes in brain connections within the default mode network (DMN) were investigated using eight electroencephalographic (EEG) regions of interest. Partial directed coherence (PDC) was used to assess the causal influences of DMN regions on each other and indicate the changes in the DMN effective network related to SAD severity. The DMN is a large-scale brain network basically composed of the mesial prefrontal cortex (mPFC), posterior cingulate cortex (PCC)/precuneus, and lateral parietal cortex (LPC). The EEG data were collected from 88 subjects (22 control, 22 mild, 22 moderate, 22 severe) and used to estimate the effective connectivity between DMN regions at different frequency bands: delta (1–3 Hz), theta (4–8 Hz), alpha (8–12 Hz), low beta (13–21 Hz), and high beta (22–30 Hz). Among the healthy control (HC) and the three considered levels of severity of SAD, the results indicated a higher level of causal interactions for the mild and moderate SAD groups than for the severe and HC groups. Between the control and the severe SAD groups, the results indicated a higher level of causal connections for the control throughout all the DMN regions. We found significant increases in the mean PDC in the delta (p = 0.009) and alpha (p = 0.001) bands between the SAD groups. Among the DMN regions, the precuneus exhibited a higher level of causal influence than other regions. Therefore, it was suggested to be a major source hub that contributes to the mental exploration and emotional content of SAD. In contrast to the severe group, HC exhibited higher resting-state connectivity at the mPFC, providing evidence for mPFC dysfunction in the severe SAD group. Furthermore, the total Social Interaction Anxiety Scale (SIAS) was positively correlated with the mean values of the PDC of the severe SAD group, r (22) = 0.576, p = 0.006 and negatively correlated with those of the HC group, r (22) = −0.689, p = 0.001. The reported results may facilitate greater comprehension of the underlying potential SAD neural biomarkers and can be used to characterize possible targets for further medication.

The redefined vacuum approach, which is frequently employed in the many-body perturbation theory, proved to be a powerful tool for formula derivation. Here, we elaborate this approach within the bound-state QED perturbation theory. In addition to general formulation, we consider the particular example of a single particle (electron or vacancy) excitation with respect to the redefined vacuum. Starting with simple one-electron QED diagrams, we deduce first- and second-order many-electron contributions: screened self-energy, screened vacuum polarization, one-photon exchange, and two-photon exchange. The redefined vacuum approach provides a straightforward and streamlined derivation and facilitates its application to any electronic configuration. Moreover, based on the gauge invariance of the one-electron diagrams, we can identify various gauge-invariant subsets within derived many-electron QED contributions.

Covid-19 has become a non-natural national disaster that affects the national resilience of the Indonesian state. In maintaining national resilience, the implementation of state defense is needed. This research aims to describe the awareness of defending the state of millennials during the current situation of the Covid-19 pandemic in Indonesia by using a quantitative approach with descriptive analysis methods with survey techniques. The results of this study indicate that most millennials are aware of the obligation to defend the state amid the current Covid-19 pandemic, namely by implementing health protocols such as preparing cleaning equipment, conducting social distancing, and working from home. However, there are still millennials who cannot run it for some reason. Based on the results of this study, it concluded that most millennials are aware of the obligation to defend the state during a pandemic by complying with health protocols as a form of state defense character.

Abstract: Ultrasonic vocalizations (USVs) are one of the evolutionarily oldest forms of animal communication. In order to study the communication architecture in an aversive social situation, we used a behavioral model in which one animal, the observer, is witnessing as his cagemate, the demonstrator, is experiencing a series of mild electrical foot-shocks (aversive stimuli). We studied the effect of foot-shocks experience in the observer and the influence of a warning sound (emit-ted shortly before the shock is applied) on USVs communication. These experiments revealed that such a warning seems to increase the arousal level, which differentiates the responses depending on previous experience. It can be identified by the emission of characteristic, short 22-kHz calls, of a duration below 100 ms. Furthermore, by analyzing temporally overlapping USVs, we found that in ‘Warned’ pairs with a naive observer, 22-kHz were mixed with 50-kHz calls. This fact, combined with a high fraction of very high-pitched 50-kHz calls (over 75-kHz), suggests the presence of the phenomenon of social buffering. On the other hand, in ‘Warned’ pairs with an experienced observer, pure 22-kHz overlaps were mostly found, signifying possible fear contagion with dis-tress sharing. Hence the importance of differentiating 22-kHz calls to long and short.

Considering the negative impacts of climate changes along with the rapid increase in population in Islamic dominated states, e.g., the Middle East, water tension among upstream and downstream states is increasing. Despite the importance of water management in Islamic culture, the role of religion has been under-valued and under-emphasized by the scholars. The paper has sought to compare and contrast Islamic water management principles (IWMP) with international water law principles (IWLP). The findings from this analysis show not only that IWMP are in conformity with IWLP, but that in many cases, IWMP can be more effective. For instance, where international water accords between riparian states of a shared river basin are poorly developed and lack enforcement mechanisms under IWLP, those upstream states can abuse their geographical locations depriving those downstream-ers. In contrast, IWMPs stress the equitable and reasonable use of water resources among upstream and downstream users of a shared watercourse. Moreover, although IWLPs emphasize the conservation and preservation of ecosystems and the environment at the basin level, the inter-basin states especially those upstream can pose significant harm to the ecosystems. On the other side, Islam as the religion of peace, has placed much emphasis on the preservation of nature. For example, the verse, “.... And waste not by excess, for Allah loves not the wasters” [Quran, 7:31], illustrates the importance of the sustainable use of water and the environment. It is argued that if Islamic Water Management Principles are incorporated into the management instrument of Islamic States, the issue of equitable and sustainable use of water among Muslim-dominated riparian states (e.g., Iran, Afghanistan, etc.) will be solved.

The induced draft (ID) fan is important auxiliary equipment in the thermal power plant. It is of great significance to monitor the operation of the ID fan for safe and efficient production. In this paper, an adaptive warning model is proposed to detect early faults of ID fans. First, a non-parametric monitoring model is constructed to describe the normal operation states with the multivariate state estimation technique (MSET). Then, an early warning approach is presented to identify abnormal behaviors based on the results of the MSET model. As the performance of the MSET model is heavily influenced by the normal operation data in the historic memory matrix, an adaptive strategy is proposed by using the samples with a high data quality index (DQI) to manage the memory matrix and update the model. The proposed method is applied to a 300 MW coal-fired power plant for early fault detection, and it is compared with the model without an update. Results show that the proposed method can detect the fault earlier and more accurately.

State legitimacy and effectiveness could be seen by the way to deliver welfare to citizens to mitigate social grievances, that could eventually lead to conflicts (Kivimäki, 2021). Social security systems in Maghreb countries are quite similar in their architecture and aims to provide social insurance to all the workers in the labor market. However, they suffer from the same main problem: the low rate of enrollment of workers. Many workers (employees and self-employed) work informally without any social security coverage. The issue of whether informal jobs are chosen voluntarily by workers or as a strategy of last resort is controversial. Many authors recognize that the informal sector is heterogeneous and it is made up of workers who voluntary choose it and others who are pushed inside because of entry barriers to the formal sector (Günther & Launov, 2012). Using the SAHWA survey and discrete choice models, this article confirms the heterogeneity of the informal labor market in three Maghreb countries: Algeria, Morocco, and Tunisia. Furthermore, this article highlights the profiles of workers who voluntarily choose informality, which is missing from previous studies. Finally, this article proposes policy recommendations in order to extend social security to informal workers and to include them in the formal labour market.

In this paper, we present some new models for anisotropic compact stars within the framework of 5-dimensional Einstein-Gauss-Bonnet (EGB) gravity with a linear and nonlinear equation of state considering a metric potential proposed for Thirukkanesh and Ragel (2012) and generalized for Malaver (2014). The new obtained models satisfy all physical requirements of a physically reasonable stellar object. Variables as energy density, radial pressure and the anisotropy are dependent of the values of the Gauss-Bonnet coupling constant

Communication, compression of information, transmission of information through noisy channels, interconnecting different information systems, cryptography, gate construction –– these areas all depend on classical information theory. We show that, in classical terms, semantic aspects of communication are not at all irrelevant to the engineering problem, contrary to Shannon, and affect the message intended to be transmitted. This is revisited and captured by an analogy to trust, in that they are essential to the channel (for proper use), but cannot be transferred (under risk of flaws) through that same channel. Information is also described by, at least, a tri-state system — not by binary logic. The trust analogy semantics can be coded as the Curry-Howard relationship, connecting computer code with structural logic, by way of different categories. Two-state and Boolean logic (aka Shannon semantics) was used classically before, with Shannon theory, but without trust analogy semantics – found to be a sine qua non condition. This is now familiar in classical gate construction with physical systems with, e.g., Verilog and SystemVerilog. The applications to computation and quantum theory are further explored. The most fundamental entity in today`s theory of information is proposed to use at least three logical states, not bits, in all applications, including: cyber-physical systems, devices, in computation, and in quantum theory.

This paper presents the current lexical, morphological, syntactic and rule-based machine translation work for Erzya and Moksha that can and should be used in the development of a roadmap for Mordvin linguistic research. We seek to illustrate and outline initial problem types to be encountered in the construction of an Apertium-based shallow-transfer machine translation system for the Mordvin language forms. We indicate reference points within Mordvin Studies and other parts of Uralic studies, as a point of departure for outlining a linguistic studies with a means for measuring its own progress and developing a roadmap for further studies.

The available magnetic field strength for high resolution NMR in persistent superconducting magnets has recently improved from 23.5 to 28 Tesla, increasing the proton resonance frequency from 1 to 1.2 GHz. For magic-angle spinning (MAS) NMR, this is expected to improve resolution, provided the sample preparation results in homogeneous broadening. We compare two-dimensional (2D) proton detected MAS NMR spectra of four membrane proteins at 950 and 1.2 GHz. We find a consistent improvement in resolution that scales superlinearly with the increase in magnetic field for three of the four examples. In 3D and 4D spectra, which are now routinely acquired, this improvement indicates the ability to resolve at least 2 and 2.5 times as many signals, respectively.

In this paper, Hybrid Automata, which is a formal model for hybrid systems, has been introduced. A summary of its theory is presented and some of its special and important classes are listed and some properties that can be studied and checked for it are mentioned. Finally, the purposes of use, the most widely used areas, and the tools that provide H.A. Support are addressed.

Three low band gap copolymers based on isoindigo acceptor units were designed and successfully synthesized by direct arylation polycondensation method. Two of them were benzodithiophene(BDT)-isoindigo copolymers (PBDTI-OD and PBDTI-DT) with 2-octlydodecyl(OD) and 2-decyltetradecyl (DT) substituted isoindigo units, respectively. Thiophene donor and DT-substituted isoindigo acceptor units were copolymerized to synthesize PTI-DT. The copolymers have broad absorption range that extends to over 760 nm with a band gap ~ .5 eV. The photophysical property studies showed the BDT based copolymers have non-polar ground states. Their emission exhibited the population of intramolecular charge transfer (ICT) state in polar solvents and tightly bound excitonic state in non-polar solvents due to self-aggregation. On the contrary, the emission from the thiophene based copolymers was only from the tightly bound excitonic state. The thermal decomposition temperature of the copolymers was above 380 oC. The X-ray diffraction pattern of the three copolymers showed a halo due pi-pi stacking. A second sharper peak was observed in the BDT-based copolymer with longer side chain on the isoindigo unit (PBDTI-DT) and the thiophene based copolymers with PTI-DT exhibiting a better structural order.

The exact dynamics of emergence remains one of the most prominent outstanding questions for the field of complexity science. I first discuss various perspectives on emergence in various contexts, then offer a different perspective on understanding emergence in a graph-theoretic representation. From the discussion, an observer’s choice in state space seems to have an effect for that observer to detect emergent behavior. To test these ideas, I analyze the dynamics of all possible spatial state spaces near the critical temperature in an Ising model. As a result, state space topologies that appear more deterministic flip more bits than topologies that appear more random, which is contrary to our intuitions about randomness. In addition, the size of different state spaces constrain a system’s ability to explore various states within the same time frame. These results are important to understanding emergent phenomena in biological systems, which are layered with various state spaces and observational perspectives.

This article examines the impact of some system parameters on an industrial system composed of two dissimilar parallel units with one repairman. The active unit may fail due to essential factors like aging or deteriorating, or exterior phenomena such as Poisson shocks that occur at various time periods. Whenever the value of a shock is larger than the specified threshold of the active unit, the active unit will fail. The article assumes that the repairman has the right to take any of two decisions at the beginning of the system operation: either a takes a vacation if the two units work in a normal way, or stay in the system to monitor the system until the first system failure. In case of having a failure in any of the two units during the absence of the repairman, the failing unit will have to wait until the repairman is called back to work. We suppose that the value of every shock is assumed to be i.i.d. with some known distribution. The length of the repairman’s vacation, repair time, and recall time are arbitrary distributions. Various reliability measures have been calculated by the supplementary variable technique and the Markov’s vector process theory. At last, numerical computation and graphical analysis have been given for a particular case to validate the derived indices.

We refute a recently proposed thought experiment namely the Dead-Alive Physicist (DAP) whose authors claim it to be the falsification of the von Neumann interpretation in Quantum Mechanics. We discover major flaws in their model and our justification serves the purpose of disregarding further claims and assertions made in the paper at various stages. Thus, in a yet another situation, it is proven that the formalism advanced by von Neumann is non-trivial and non-falsifiable.

Bioenergetics, genetic coding, and catalysis are all difficult to imagine emerging without pre-existing historical context. That context is often posed as a “Chicken and Egg” problem; its resolution is concisely described by de Grasse Tyson: “the egg was laid by a bird that was not a chicken”. The concision and generality of that answer furnish no details—only an appropriate framework from which to examine detailed paradigms that might illuminate paradoxes underlying these three life-defining biomolecular processes. We examine experimental aspects here of five examples that all conform to the same paradigm. The paradox in each example is resolved by coupling if, and only if, conditions for two related transitions between levels. One drives, and each restricts fluxes through, or “gates” the other. That reciprocally-coupled gating, in which two gated processes constrain one another, maps onto the formal structure of “strange loops”. That mapping may help unite the axiomatic foundations of genetics, bioenergetics, and catalysis. As a physical analog for Gödel’s logic, biomolecular strange-loops provide a natural metaphor around which to organize these data, linking biology to the physics of information, free energy, and the second law of thermodynamics.

The Internet-of-Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state-of-the-art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture.

New pharmaceutically acceptable salts of trazodone for the treatment of central nervous system disorders are synthesized and described. Each salt (trazodone hydrogen bromide and trazodone 1-hydroxy-2-naphthoate) was obtained by two or three different methods leading to the same crystalline form. Although trazodone salts are poorly crystalline, single-crystal X-ray diffraction data for trazodone 1-hydroxy-2-naphthoate were collected and analyzed as well as compared to the previously described crystal structure of commercially available trazodone hydrochloride. The powder samples of all new salts were characterized by Fourier transform infrared spectroscopy and 13C solid-state nuclear magnetic resonance spectroscopy. Spectroscopic studies were supported by gauge including projector augmented wave (GIPAW) calculations of carbon chemical shielding constants. The main goal of our research was to find salts with better physicochemical properties and to make an attempt to associate them with both the anion structure and the most prominent interactions exhibited by the protonated trazodone cation. The dissolution profiles of trazodone from tablets prepared from various salts with lactose monohydrate were investigated. The studies revealed that salts with simple anions show a fast release of the drug while the presence of more complex anion, more strongly interacting with the cation, effects a slow-release profile of the active substance and can be used for the preparation of the tables with a delay or prolonged mode of action.

The general coupling between particle transport and ionization-recombination processes in hot plasma is considered on the key concept of equilibrium charge state (CS) transport. A theoretical interpretation of particle and CS transport is gained in terms of a two-dimensional (2D) Markovian stochastic (random) processes, a discrete 2D Fokker-Plank-Kolmogorov equation (in charge and space variables) and generalized 2D coronal equilibrium between atomic processes and particle transport. The basic tool for analysis of CS equilibrium and transport is the equilibrium cell (EC) (two states on charge and two on space), which presents (i) a unit phase volume, (ii) the characteristic scale of local equilibrium, (iii) a comprehensive solution for the simplest nonlinear relations between transport and atomic processes. The approach opens up new perspectives on transport studies: (i) the direct modelling of equilibrium and transport of impurity using the atomic data base, (ii) recovery of the complete recombination rate profile based on knowledge of density profiles and ionization rate profiles, (iii) the local transport analysis, based on the reduction of the equilibrium set to the single EC (in particular, central or edge), (iv) analysis of the reduced transport coefficients (diffusion and convection) on the density profile measurements.

With a reduction in the mortality rate of burn patients, patient length of stay (LOS) is increasingly adopted as an outcome measure. Some studies have attempted to identify factors that explain a burn patient's expected LOS. However, few have investigated the association between LOS and a patient's mental and socioeconomic status. There is anecdotal evidence for links between these factors and uncovering these will aid in better addressing the specific physical and emotional needs of burn patients, and facilitate the planning of scarce hospital resources. Here, we employ machine learning (clustering) and statistical models (regression) to investigate whether a segmentation by socioeconomic/mental status can improve the performance and interpretability of an upstream predictive model, relative to a unitary model derived for the full adult population of patients. Although we found no significant difference in the performance of the unitary model and segment-specific models, the interpretation of the segment-specific models reveals a reduced impact of burn severity in LOS prediction with increasing adverse socioeconomic and mental status. Furthermore, the models for the socioeconomic segments highlight an increased influence of living circumstances and source of injury on LOS. These findings suggest that, in addition to ensuring that the physical needs of patients are met, management of their mental status is crucial for delivering an effective care plan.

The paper presents an analysis of the method of recording the magnetic component of the Earth’s natural pulse electromagnetic field in an urban environment. This method of recording has already proved itself to be a method that allocates the stressed sections of rock mass at mining and, therefore, authors suppose its effectiveness for allocating active tectonic disturbances and forecasting accidents at underground utilities, what will help reduce the potential environmental hazard of these objects.

In this paper, we found a new model for compact star with charged anisotropic matter distribution considering an extended version of the Chaplygin equation of state. We specify a particular form of the metric potential Z(x) that allows us to solve the Einstein-Maxwell field equations. The obtained model satisfies all physical properties expected in a realistic star such that the expressions for the radial pressure, energy density, metric coefficients, measure of anisotropy and the mass are fully well defined and are regular in the interior of star. The solution obtained in this work can have multiple applications in astrophysics and cosmology.

Tumorigenesis is a complex biological phenomenon that includes extensive genetic and phenotypic heterogeneities and complicated regulatory mechanisms. In the recent few years, our studies demonstrate that tumor-initiating cells are similar to neural stem/progenitor cells in regulatory networks, tumorigenicity and pluripotent differentiation potential. In the review, I will make further discussion on these observations and propose a rule of cell biology by integrating these findings with evidence from developmental biology, tumor biology and evolution, which suggests that neural stemness underlies two coupled cell properties, tumorigenicity and pluripotent differentiation potential. Tumorigenicity and phenotypic heterogeneity in tumor is a result of acquirement of neural stemness in cells. The neural stemness property of tumor-initiating cells can hopefully integrate different concepts/hypotheses underlying tumorigenesis. Neural stem cells/neural progenitors and tumor-initiating cells share regulatory networks; both exhibit neural stemness, tumorigenicity and differentiation potential; both are dependent on expression or activation of ancestral genes (the atavistic effect); both rely primarily on aerobic glycolytic metabolism; both can differentiate into various cells or tissues that are derived from three germ layers, resembling severely disorganized or more severely degenerated process of embryonic development; both are enriched in long genes with more splice variants that provide more plastic scaffolds for cell differentiation, etc. The property of neural stemness might be a key point to understand tumorigenesis and pluripotent differentiation potential, and possibly explain certain pathological observations in tumors that have been inexplicable. Therefore, behind the complexity of tumorigenesis might be a general rule of cell biology, i.e., neural stemness represents the ground state of cell tumorigenicity and pluripotent differentiation potential.

Routing quantum information among different nodes in a network is a fundamental prerequisite for a quantum internet. While single-qubit routing has been largely addressed, many-qubit routing protocols have not been intensively investigated so far. Building on the many-excitation transfer protocol in Ref. , we apply the perturbative transfer scheme to a two-excitation routing protocol on a network where multiple two-receivers block are coupled to a linear chain. We address both the case of switchable and permanent couplings between the receivers and the chain. We find that the protocol allows for efficient two-excitation routing on a fermionic network, although for a spin-12 network only a limited region of the network is suitable for high-quality routing.

SHANK3 encodes scaffold protein involved in postsynaptic receptor density in glutamatergic synapses, including those in the parvalbumin (PV)+inhibitory neurons – the key players in generation of sensory gamma oscillations, such as 40-Hz auditory steady-state response(ASSR). Here we describe a clinical and neurophysiological phenotype of a 15-years old girl (SH01) with microduplication of 16389 bp in 22q13.33, affecting the SHANK3 gene in comparison to typically developing children (n=32). EEG were recorded during the binaurally presentation of 40-Hz clicks’ trains lasting for 500 ms with inter-trial intervals 500-800 ms. SH01 was diagnosed with mild mental retardation and learning disabilities(F70.88) and had problems with reading and writing, as well as smaller vocabulary than TD peers. Her clinical phenotype generally resembled the phenotype of previously described patients with 22q13.33 microduplication. SH01 had mild autistic symptoms but below the threshold for ASD diagnosis. No seizures or MRI abnormalities were reported. While SH01 had relatively preserved auditory event-related potential(ERP) with slightly attenuated P1, her 40-Hz ASSR was totally absent significantly deviating from TD’s ASSR. Absence of 40-Hz ASSR in patient with microduplication, affected SHANK3 gene, indicates deficient temporal resolution of the auditory system, that might underlie language problems, and represent neurophysiological biomarker of SHANK3 abnormalities.

The use of natural stone has a historical and environmental value that makes it strategically valuable for landscape conservation in Europe. Marble, among others, is widely spread on Earth, and it offers high-performance features in architectural applications. However, the complexity of these formations and the rock variability in different ore bodies require detailed studies of the natural and induced stress state, the fracturing degree, and the influence of external factor (such as temperature and/or chemical agents) on the mechanical properties in order to optimize the exploitation processes by reducing extractive waste. This article shows a series of studies conducted by the authors over the last 20 years aimed at making the exploitation of marble blocks in the Carrara basin safer, more efficient, and, therefore, more sustainable. In particular, studies for increasing the knowledge on the natural and the induced stress state through on-site measurements and numerical modeling, studies to improve the quality of the exploited material through improvements of cutting technologies, studies to improve the knowledge of the mechanical behavior of the material under varying loads and temperature conditions and studies to improve the reuse of water materials and their reduction are reported.

In this paper, the stability control of the inverted pendulum on a cart with a disturbance forces has been done using observer based and full state feedback H2 controllers. The Lagrangian equation has been used to model the system equation of motions and linearized the system to the unstable upward position. Comparison of the system stability has been simulated by comparing the proposed controllers using Matlab/Scripts and a promising results has been analyzed successfully.

Nowadays, model checking is applied as an accurate technique to verify software systems. The main problem of model checking techniques is the state space explosion. This problem occurs due to the exponential memory usage by the model checker. In this situation, using meta-heuristic and evolutionary algorithms to search for a state in which a property is satisfied/violated is a promising solution. Recently, different evolutionary algorithms like GA, PSO, etc. are applied to find deadlock state. Even though useful, most of them are concentrated on finding deadlock. This paper proposes a fuzzy algorithm in order to analyze reachability properties in systems specified through GTS with enormous state space. To do so, we first extend the existing PSO algorithm (for checking deadlocks) to analyze reachability properties. Then, to increase the accuracy, we employ a Fuzzy adaptive PSO algorithm to determine which state and path should be explored in each step to find the corresponding reachable state. These two approaches are implemented in an open-source toolset for designing and model checking GTS called GROOVE. Moreover, the experimental results indicate that the hybrid fuzzy approach improves speed and accuracy in comparison with other techniques based on meta-heuristic algorithms such as GA and the hybrid of PSO-GSA in analyzing reachability properties.

Recently, there has been, on the one hand, an increase in the complexity of digital device designs and, on the other hand, an increase in the requirements for the development time and the reliability of the designs. One of the directions of solving this problem is developing new techniques for designing digital devices.This paper proposes a new technique for designing digital devices based on finite state machines with datapath (FSMD), when the functioning of the device is described in the form of an algorithm state machine with datapath (ASMD) charts. The new technique is called ASMD-FSMD. Different digital device design techniques are compared to each other using design examples of a synchronous multiplier on field programmable gate array (FPGA). The efficiency of the ASMD-FSMD technique compared to the traditional approach in terms of area and performance was investigated. The ASMD-FSMD technique, compared to the traditional one, reduces the area from 28.6% to 39.7% and increases the speed for some designs to 17.6%. In addition, using the ASMD-FSMD technique significantly reduces design time and increases design reliability. In conclusion, recommendations for using the ASMD-FSMD technique are made.

In this work, meshless methods are applied for the solution of two-dimensional steady-state heat conduction problems with nonlocal multi-point boundary conditions (NMBC). These meshless procedures are based on multiquadric radial basis function (MQ RBF) and its modified version (i.e. integrated MQ RBF). The proposed meshless methods which were recently published in \cite{Reutskiy2016} is compared with standard collocation method (i.e. Kansa's method). Three different sorts of solution domain are considered in which Dirichlet boundary condition is specified on some part of the boundary and is related to the unknown function values at a discrete set of interior points. The influence of NMBC on the accuracy and condition number of the system matrix associated to the proposed methods is investigated. The sensitivity of the shape parameter is also analyzed in the proposed methods. Performance of the proposed approaches in terms of accuracy and efficiency is confirmed on the benchmark problems.

This is a report on a dynamic autonomous magnetic interaction which does not depend on polarities resulting in short ranged repulsion involving one or more inertial bodies and a new class of bound state based on this interaction. Both effects are new to the literature, found so far. Experimental results are generalized and reported qualitatively. Working principles of these effects are provided within classical mechanics and found consistent with observations and simulations. The effects are based on the interaction of a rigid and finite inertial body (an object having mass and moment of inertia) endowed with a magnetic moment with a cyclic inhomogeneous magnetic field which does not require to have a local minimum. Such a body having some DoF involved in driven harmonic motion by this interaction can experience a net force in the direction of the weak field regardless of its position and orientation or can find stable equilibrium with the field itself autonomously. The former is called polarity free magnetic repulsion and the latter magnetic bound state. Experiments show that a bound state can be obtained between two free bodies having magnetic dipole moment. Various schemes of trapping bodies having magnetic moments by rotating fields are realized as well as rotating bodies trapped by a static dipole field in presence of gravity. Also, a special case of bound state called bipolar bound state between free dipole bodies is investigated.

The coordination polymer [Fe(NH₂trz)₃](2ns)₂ exhibits the rare phenomenon of spin crossover in an attractive temperature range, i.e., somewhat above room temperature. Spin crossover in [Fe(NH₂trz)₃](2ns)₂ is manifest by thermochromism, which is accompanied by a magnetic transition from diamagnetism to paramagnetism. However, [Fe(NH₂trz)₃](2ns)₂ is brittle and difficult to process, which limits its use. In this study, we show that [Fe(NH₂trz)₃](2ns)₂ can be co-processed with ultrahigh molecular weight polyethylene (UHMWPE), which possesses outstanding mechanical properties, particularly when tensile drawn. Therefore, [Fe(NH₂trz)₃](2ns)₂–UHMWPE blends were gel-processed by extrusion, employing a relatively poor solvent, which has recently been shown to offer advantages compared to good solvents. Uniform and flexible films, ribbons and fibers with [Fe(NH₂trz)₃](2ns)₂ fractions as high as 33.3% m/m were obtained that could be readily drawn. Spin crossover in the coordination polymer is retained in these materials, as evident from their thermochromism. The tensile strength and Young’s modulus of the blends exceed those of typical commodity polymers. Thus, the films, ribbons and fibers constitute a special class of multifunctional materials that combine the flexibility and excellent mechanical properties of drawn UHMWPE with the spin crossover behavior of [Fe(NH₂trz)₃](2ns)₂.

For crystal periodic structure prediction, a new and concise approach based on the principles of statistical physics was employed to derive a new form of the equation to determine their period vectors (cell edge vectors), under general external stress. Then the new form is applicable to both classical physics and quantum physics. It also turned out to be the equation of state and the mechanical equilibrium condition for crystals under external stress and temperature. It should be helpful in piezoelectric and piezomagnetic studies, as the period vectors were changed by the external stress. For linear elastic crystals, it is actually also the microscopic but temperature-dependent form of the generalized Hooke's law, then can be used to calculate the corresponding elastic constants of the law, for given temperatures.

In this paper a full state feedback control of a double inverted pendulum on a cart (DIPC) are designed and compared. Modeling is based on Euler-Lagrange equations derived by specifying a Lagrangian, difference between kinetic and potential energy of the DIPC system. A full state feedback control with H infinity and H 2 is addressed. Two approaches are tested: open loop impulse response and a double inverted pendulum on a cart with full state feedback H infinity and H 2 controllers. Simulations reveal superior performance of the double inverted pendulum on a cart with full state feedback H infinity controller.

The COVID-19 appears as a catastrophic health risk with psychological, emotional, social and relational implications. From the early stages of the virus spread, the elderly population was identified as the most vulnerable and the health authorities have rightly focused on such frailest population. Conversely, less attention was paid to emotional and psychological dimension of children and adolescents. Actually, they were less at risk quoad vitam or quoad valetudinem, nevertheless they had to face a reality of anxiety, fears and uncertainties. The current study investigated state anxiety and emotion awareness in a healthy sample of older adolescents, 84 females and 64 males, aged 17 to 19, during the pandemic lockdown, using Self-rating Anxiety Scale and the Italian Emotion Awareness Questionnaire. An unexpected anxious phenomenology, impacting the anxiety ideo-affective domain, was found, while the somatic symptomatology appeared to be less severe. The highest anxiety symptom were the breathing difficulties. These findings supported the hypothesis that the COVID-19 pandemic may be a risk condition for an increased state anxiety in older adolescents and suggest the need to provide 1. an effective, empathic communication system with the direct participation of older adolescents, 2. a psychological counseling service for stress management of adolescents.

In this paper, a 3 DOF gyrscope position control have been designed and controlled using optimal control theory. An input torque has been given to the first axis and the angular position of the second axis have been analyzed while the third axis are kept free from rotation. The system mathematical model is controllable and observable. Linear Quadratic Integral (LQI) and Linear Quadratic State Feedback Regulator (LQRY) controllers have been used to improve the performance of the system. Comparison of the system with the proposed controllers for tracking a desired step and random angular position have been done using Matlab/Simulink Toolbox and a promising results has been analyzed.

In this paper, the design of a low cost portable ventilator with performance analysis have been done to solve the scarcity of respiratory ventilators for COVID-19 patients. The materials used to build the system are: DC motor, rotating disc and pneumatic piston. The system input is the patient heart beat and the output is volume of air to the patient lung with adjusted breathing rate. This ventilator adjusts the breathing rate to the patient depending on his heart beat rate. The performance analysis of this system have been done using Proportional Integral Derivative (PID) and Full State Feedback H2 controllers. Comparison of the system with the proposed controllers have been done using a step change and a random change of the patient heart beat and a promising result have been analyzed successfully.

In this paper, a metal cutting machine position control have been designed and simulated using Matlab/Simulink Toolbox successfully. The open loop response of the system analysis shows that the system needs performance improvement. Static output feedback and full state feedback H₂ controllers have been used to increase the performance of the system. Comparison of the metal cutting machine position using static output feedback and full state feedback H₂ controllers have been done to track a set point position using step and sine wave input signals and a promising results have been analyzed.

Room-temperature phosphorescent (RTP) materials have been attracted tremendous interest owing to their unique material characteristics and potential applications for state-of-the-art optoelectronic devices. Recently, we have reported a synthesis and fundamental photophysical properties of new RTP materials based on benzil, i.e., fluorinated monobenzil derivative and fluorinated and non-fluorinated bisbenzil derivative analogues [Yamada, S. et al, Beilstein J. Org. Chem. 2020, 16, 1154–1162.]. To further understand their RTP properties, here we investigated the excited-state dynamics and photostability of the derivatives by means of time-resolved and steady-state photoluminescence spectroscopies. For these derivatives, clear RTP emissions with lifetimes on the microsecond timescale were identified. Among them, the monobenzil derivative was found to be the most efficient RTP material, showing both the longest lifetime and highest amplitude RTP emission. Time-resolved photoluminescence spectra measured at 77 K and density functional theory calculations revealed the existence of a second excited triplet state in the vicinity of the first excited singlet state for the monobenzil derivative, indicative of the presence of a fast intersystem crossing pathway. A discussion of the correlation between the excited state dynamics, emission properties, and conformational flexibility of the three derivatives is presented.

This research aims to study the ultimate limit state (ULS) behaviour of stiffened panel under longitudinal compression by non-linear finite element method (NLFEM). There are different types of stiffeners being used in shipbuilding i.e. T-bar, flat-bar and angle-bar. However, this research focuses on the ultimate compressive strength behaviour of flat-bar stiffened panel. A total of 420 of reliable scenarios of flat-bar stiffened panel are selected for numerical simulation by ANSYS NLFEM. The ultimate strength behaviours obtained were used as data for the development of closed form shape empirical formulation. Recently, Kim et al. [1] proposed for advanced empirical formulation for T-bar stiffened panel and the applicability of the proposed formulation to flat-bar stiffened panel will be confirmed by this study. The accuracy of the empirical formulation obtained for flat-bar stiffened panel has been validated by FE simulation results of statistical analysis (R2 = 0.9435). The outcome obtained will be useful for ship structural designers in predicting the ultimate strength performance of flat-bar type stiffened panel under longitudinal compression.

The purpose of this paper is to simulate a two-dimensional Rayleigh-Taylor instability problem using the classical method of Finite Element analysis of a multiphase model using ANSYS FLUENT 19.2. The governing equations consist of a system of coupled nonlinear partial differential equations for conservation of mass, momentum and phase transport equations. The study focuses on the transient state simulation of Rayleigh Taylor waves and subsequent turbulent mixing in the two phases incorporated in the model. The Rayleigh Taylor instability is an instability of an interface between two fluids of different densities which occurs when the lighter fluid is pushing the heavier fluid in a gravitational field. The problem was governed by the Navier-Stokes and Cahn-Hilliard equations in a primitive variable formulation. The Cahn- Hilliard equations were used to capture the interface between two fluids systems. The objective of this article is to perform grid dependency test on Rayleigh Taylor Instability for 2 different mesh size and compare the results for the variation in Atwood Number. The results were validated with the observations from previous published literatures.

Multipartite entanglement is a resource for application in disparate protocols, of computing, communication and cryptography. Nested entanglement provides resource-states for quantum information processing. In this paper, Matryoshka quantum resource-states, which contain nested entanglement patterns, has been studied. A novel scheme for the generation of such quantum states has been proposed using an anisotropic XY spin-spin interaction-based model. The application of the Matryoshka GHZ-Bell states for n-qubit teleportation is reviewed and an extension to more general Matryoshka ExhS-Bell states is posited. An example of Matryoshka ExhS-Bell states is given in the form of the genuinely entangled seven-qubit Xin-Wei Zha state. Generation, characterisation and application of this seven-qubit resource state in theoretical schemes for quantum teleportation of arbitrary one, two and three qubits states, bidirectional teleportation of arbitrary two qubit states and probabilistic circular controlled teleportation are presented.

Measuring the status and trends of biodiversity is critical for making informed decisions about the conservation, management or restoration of species, habitats and ecosystems. Defining the reference state against which status and change are measured is essential. Typically, reference states describe historical conditions, yet historical conditions are challenging to quantify, may be difficult to falsify, and may no longer be an attainable target in a contemporary ecosystem. We have constructed a conceptual framework to help inform thinking and discussion around the philosophical underpinnings of reference states and guide their application. We characterise currently recognised historical reference states and describe them as Pre-Human, Indigenous Cultural, Pre-Intensification and Hybrid-Historical. We extend the conceptual framework to include contemporary reference states as an alternative theoretical perspective. The contemporary reference state framework is a major conceptual shift that focuses on current ecological patterns and identifies areas with higher biodiversity values, regardless of the disturbance history. The specific context for which we design the contemporary conceptual frame is underpinned by an overarching goal—to maximise biodiversity conservation and restoration outcomes in existing ecosystems. The contemporary reference state framework can account for the inherent differences in the diversity of biodiversity values (e.g., species richness, habitat complexity) across spatial scales, communities and ecosystems. In contrast to historical reference states, contemporary references states are measurable and falsifiable. This ‘road map of reference states’ offers perspective needed to define and assess the status and trends in biodiversity and habitats. Our framework for contemporary reference states provides a tractable way for policy-makers and practitioners to navigate biodiversity assessments to maximise conservation and restoration outcomes in contemporary ecosystems. We illustrate how to define a contemporary reference state using an example from south-eastern Australia.

In this paper, optimum parameters of Tuned Mass Dampers (TMD) are considered to control the responses of 10-story shear building under harmonic loading and 22 set of seismic records of FEMA-P695. The criterion used to obtain the optimum parameters is to select mass ratio, the frequency (tuning) and damping ratio that would result in smallest lateral displacements. State-space equations of motion are presented to compute the structural responses by developing a MATLAB file. A 10-story shear building is presented as a case study to assess the effects of TMDs on the multi-story structures. The results indicate that using TMD can reduce structural responses up to the average 20% under earthquake excitation and up to 90% under harmonic loadings. TMDs are not always effective under any type of ground motion; therefore, being aware of the given location is significant to design TMDs properly.

Multipartite entanglement is a resource for application in disparate protocols, of computing, communication and cryptography. In this paper, generation, characterisation and application of a genuine genuinely entangled seven-qubit resource state is studied. Theoretical schemes for quantum teleportation of arbitrary one, two and three qubits states, bidirectional teleportation of arbitrary two qubit states and probabilistic circular controlled teleportation as well as three schemes for undertaking tripartite quantum state sharing are presented.

Background: Social skills deficits are present in 43.3% of major depressed patients and significantly impact health-related quality of life. However, studies concerning social deficits as state-dependent markers of depression are limited. Objective: To delineate the effects of severity of depression, personality characteristics, family support satisfaction and self-esteem on social skills in clinical depression. Methods: We recruited 150 patients with major depressive disorder or persistent depressive disorder and assessed 1) Beck Depression Inventory-II (BDI-II), 2) Social Skill Inventory (SSI), 3) Family Adaptation, Partnership, Growth, Affection, Resolve (APGAR) Questionnaire 4) Rosenberg Self-Esteem Scale (RSES) and 5) Maudsley Personal Inventory (MPI). Results: Social skills deficits were significantly associated with female gender, age < 40 years, depression severity, introvert / neurotic personality, and lowered family support satisfaction and self-esteem. A large part of the variance (47.2%) in social skills deficits was predicted by satisfaction of family support, introvert personality, and low self-esteem. Exploratory Factor Analysis showed that a bifactorial model best fitted the data with a) a general factor loading highly on BDI-II, SSI emotional and social, APGAR, RSES, MPI_introvert and MPI_neurotic scores, and b) a single-group factor loading on both SSI, RSES, and MPI introvert scores. Conclusion: In clinical depression, social skills deficits covary with increasing severity of depression and thus constitute a state marker of depression, and independently from severity of depression covary with introvert personality features. As such, remission of social skills deficits may emerge as a novel objective for the treatment of depression and prevention of new episodes.

This paper studies the integrated design problems of control and guidance with parameter uncertainties, target disturbances, input constraints and actuator faults. Firstly, based on the integrated design idea of the missile guidance and control, the auxiliary variable is used to establish and transform it into a cascade system with input constraints, actuator faults and disturbances of unknown upper bounds. Secondly, the adaptive anti-saturation dynamic surface fault-tolerant controller is designed by using the back-stepping method, adaptive control, auxiliary system and tracking differentiator. By introducing the tracking differentiator and tangent barrier Lyapunov function, the computational explosion problem in the traditional back-stepping method is avoided and the angle of attack can be guaranteed in prospective range, respectively. Finally, the theoretical proof of the designed control strategy is given to ensure that the states of the closed-loop system are bounded. At the same time, the digital simulation of the maneuvering target of different maneuvering forms is carried out, which further illustrate the effectiveness and robustness of the designed control schemes.

Background & Objectives: The global pandemic caused by novel coronavirus SARS-CoV-2 has claimed several lives worldwide. With the virus gathering rapid spread, the world has witnessed increasing number of confirmed cases and mortality rate, India is not far behind with approximately 37,000 affected individuals as on May 2, 2020. The ongoing pandemic has raised several questions which need to be answered by analysis of transmission of the infection. The data has been collected on daily basis from WHO and other sites. We have represented the data collated graphically using statistical packages, R and other online softwares. The present study provides a holistic overview of the spread of COVID-19 infection in India. Methods: Real-time data query was done based on daily observations using publicly available data from reference websites for COVID-19 and other government official reports for the period (15^th February, 2020 to April 28^th, 2020). Statistical analysis was performed to draw important inferences regarding COVID-19 trend in India. Results: A decrease in growth rate of cases due to COVID-19 in India post lockdown and improvement in recovery rate during the month of April was identified. The case fatality rate was estimated to be 3.22% of the total reported cases. State-wise analysis revealed a deteriorating situation in states of Maharashtra and Gujarat among others as cases continued to increase rapidly there. A positive linear correlation between the number of deaths and total cases and exponential relation between population density and number of cases reported per square km was established. Interpretation & Conclusions: Despite early preventive measures taken up by the Government of India, the increasing number of cases in India is a concern. This study compiles state-wise and district-wise data to report the daily confirmed cases, case fatalities and strategies adopted in the form of case studies. Understanding the transmission spread of SARS-CoV-2 in a diverse and populated country like India will be crucial in assessing the effectiveness of control policies towards the spread of COVID-19 infection.