Miracle-dz/UniFAR-FTUs huggingface dataset:
Realization of acoustic wave directivity at low frequencies with a subwavelength Mie resonant structure

We realized high-efficiency acoustic directivity at low frequencies based on monopolar Mie resonance. This is caused by micro structures that have a high refractive index relative to the background medium. The structures can strongly control the radiation pattern though the acoustic wavelength is much larger than its dimensions. We herein discuss how to enhance the directivity through modifying the structure's parameters. Furthermore, our structure is proposed for use in obtaining an acoustic collimated beam without sidelobes. The structure characteristics and applications are demonstrated both theoretically and experimentally. Potential applications of our structures include acoustic device miniaturization, noise control, and medical ultrasonics.
Impact of Cigarette Smoking and Exercise on Arterial Stiffness: A Narrative Literature Review

PURPOSE: Smoking often causes acute and chronic cardiovascular disorders. Cigarette smoking increases oxidative stress, reduces nitric oxide bioavailability, and changes the extracellular matrix, impairing arterial stiffness. However, regular physical activity and smoking cessation significantly and rapidly reverse the detrimental effects. This narrative review summarizes the relevant research that describes the impacts of cigarette smoking on the cardiovascular system and demonstrates the therapeutic or preventative roles of exercise and smoking cessation in smoking-associated arterial stiffness.METHODS: We used scientific search engines, including PubMed, Web of Science, Google Scholar, and Wiley Online Library, to identify previous studies exploring the effects of smoking, exercise, and smoking cessation on arterial stiffness.RESULTS: We discussed the most important therapeutic and/or preventive roles of exercise and smoking cessation in decreasing arterial stiffness. Most studies have demonstrated that acute and chronic smoking increase arterial stiffness. Smoking and physical activity were negatively associated. However, this relationship was often attenuated or reversed during adult exercise interventions. In addition, smoking cessation reversed the effects of smoking on arterial stiffness.CONCLUSIONS: Smoking increases the risk of acute and chronic cardiovascular disease. Cigarette smoking deteriorates arterial stiffness by altering the vascular walls. However, regular exercise and smoking cessation can improve or prevent impaired arterial stiffness.
CONCEPT PATTERN FORMATION IN SEMANTIC SEARCH PROBLEMS

In accordance of information flow, the importance of semantic search rises as well. In the article the method of concept pattern formation is presented. Our method in fact represents the Analytic Heuristic method that might be used in semantic search problems successfully. We also have to note that the application of the given method in combination of other conceptual searching methods is encouraged.
Kinematic Wave Based Hydrologic Models with Different Solution Methods

The hydrologic simulation models RUNOFF and HEC-1 are applied to a 3212-ha watershed in New Jersey, and performances of the two models in predicting historical stromwater hydrographs from the watershed are compared. RUNOFF uses an analytical and a shockfitting solutions of the kinematic wave equations, whereas HEC-1 uses a finite difference scheme which has received criticisms in recent times due to its inherent computational error, numerical diffusion and instability. The current study shows that RUNOFF produces similar results as HEC-1 without having these numerical problems, and therefore provides an efficient alternative.
Gauss-Mapping Black Widow Optimization With Deep Extreme Learning Machine for Android Malware Classification Model

Nowadays, the malware on the Android platform is found to be increasing. With the prevalent use of code obfuscation technology, the precision of antivirus software and classical detection techniques is low. Classical detection techniques of signature matching and manual analysis have exposed issues like low accuracy and slow detection speed. Several authors have overcome the issue of Android malware detection utilizing machine learning (ML) techniques and had more research outcomes. With the growth of deep learning (DL), many researchers started to use DL methods for detecting Android malware. This article introduces a Gauss-Mapping Black Widow Optimization with Deep Learning Enabled Android Malware Classification (GBWODL-AMC) model. The major intention of the GBWODL-AMC technique lies in the automated classification of Android malware. To accomplish this, the GBWODL-AMC technique involves the design of GBWO based feature selection approach to enhance the classification performance. For Android malware classification purposes, the GBWODL-AMC technique employs a deep extreme learning machine (DELM) model and its parameter are optimally selected by the ant lion optimization (ALO) algorithm. The simulation analysis of the GBWODL-AMC technique is tested on CICAndMal2017 dataset. Extensive experimental results signify the better performance of the GBWODL-AMC technique over other malware detectors with maximum accuracy of 98.95%.
A Review of Research on the Function of Red Literature and Art in Ideological and Political Education during the Liberation War

The birth of red literature and art is closely related to the revolution, construction and reform led by the CPC. The function of ideological and political education of red literature and art has helped the Party to achieve great achievements in various periods. In the final stage of the Chinese Revolutionary War - the Liberation War period, it is even more necessary for red literature and art to play a role in ideological and political education. At present, the academic community has conducted extensive research on the theoretical issues related to the ideological and political education function of red literature and art during the War of Liberation, and has achieved certain results, but still needs to be deepened.
The role of information in consciousness.

This paper comprehensively examines how information processing relates to attention and consciousness. We argue that no current theoretical framework investigating consciousness has a satisfactory and holistic account of their informational relationship. Our key theoretical contribution is showing how the dissociation between consciousness and attention must be understood in informational terms in order to make the debate scientifically sound. No current theories clarify the difference between attention and consciousness in terms of information. We conclude with two proposals to advance the debate. First, neurobiological homeostatic processes need to be more explicitly associated with conscious information processing, since information processed through attention is algorithmic, rather than being homeostatic. Second, to understand subjectivity in informational terms, we must define information uniqueness in consciousness (e.g., irreproducible information, biologically encrypted information). These approaches could help cognitive scientists better understand conflicting accounts of the neural correlates of consciousness and work towards a more unified theoretical framework.
Dual-Polarized Wideband Low-Sidelobe Slot Array Antenna for V-Band Wireless Communications

A dual-polarized wideband low-sidelobe slot array antenna for wireless communication systems in the V-band is proposed in this work. The Taylor distribution is applied with each radiating slot as a tapering unit in both polarizations. A compact <inline-formula> <tex-math notation="LaTeX">$2\times2$ </tex-math></inline-formula> element subarray is designed to achieve stable amplitude and phase distribution among elements with two sets of integrated compact wideband unequal power dividers for the E- and H-planes inside the subarray. Then, two layers of orthogonally polarized feeding networks with unequal E-plane T-junction power dividers are used to connect the subarrays to two standard waveguides WR-15 as input ports. The prototype of <inline-formula> <tex-math notation="LaTeX">$8\times8$ </tex-math></inline-formula> elements is fabricated and measured in an anechoic chamber. The maximum measured gain is 25.3 and 25.4 dBi for V- and H-polarization, respectively. The overlapped impedance bandwidth is from 57 to 66.4 GHz with reflection coefficiencies below −10 dB, and the isolation between two input ports is around 35 dB. Sidelobe levels of both polarizations are below −22 dB with good agreement with the simulations.
Diver-Robot Communication Glove Using Sensor-Based Gesture Recognition

Despite the popularity of the buddy system, where a pair of divers look out for each other, scuba diving still poses significant risks with 15–30 deaths per 100 000 divers per year. In the 2015 edition of “Diving Medicine for Scuba Divers,” it is reported that 86% of diving fatalities involve a lone diver, yet divers still elect to dive alone for a variety of reasons including buddy unavailability. A solution to this may lie in a dedicated autonomous dive-buddy robot, which could also operate as an assistant. The challenge is how would the diver interact and communicate with the robot in underwater conditions often involving low visibility. In this article, we detail and demonstrate a technological solution that involves the direct motion capture of fingers and hand using a smart dive glove with integrated stretch sensors alongside an inertial measurement unit. The hardware and gesture recognition protocol were initially evaluated in a lab-based study where 10 users participated in a virtual reality environment setup and interacted with a virtual robot using gestures. In total, 140 out of 175 gestures were correctly recognized, resulting in diver-robot commands. A full sea demonstration of the underwater motion-capture system followed with the underwater dive glove used to send gesture-based acoustic commands to a dedicated dive buddy, a modified autonomous underwater vehicle. The diver was able to command the robot to move in six directions with a total delay of 6 s or less between the beginning of the gesture and the initiation of the action by the robot.
Photometric stereo via random sampling and tensor robust principal component analysis

In this paper, we propose a method for accurate 3D reconstruction based on Photometric Stereo. Instead of applying the global least square solution on the entire over-determined system, we randomly sample the images to form a set of overlapping groups and recover the surface normal for each group using the least square method. We then employ fourdimensional Tensor Robust Principal Component Analysis (TenRPCA) to obtain the accurate 3D reconstruction. Our method outperforms global least square in handling sparse noises such as shadows and specular highlights. Experiments demonstrate the reconstruction accuracy of our approach.
A Note on the New Activation Function of Gompertz Type

In this note we construct a family of parametric Gompertz activation function (PGAF) based on hyperbolic tangent function. We prove upper and lower estimates for the Hausdorff approximation of the sign function by means of this family. Some comparisons between the hyperbolic tangent activation function and the new parametric Gompertz activation function are reported. Numerical examples, illustrating our results are given.
CHEMICAL FRACTION ANALYSIS AND ASSESSMENT OF ASERNIC IN SOILS SAMPLED IN A Pb/Zn MINING AT HICH VILLAGE IN THAI NGUYEN PROVINCE

Tình trạng ô nhiễm các kim loại nặng ở các khu vực khai thác quặng là rất nghiêm trọng hiện nay ở Việt Nam cũng như trên thế giới. Đánh giá mức độ và nguy cơ ô nhiễm của asen (As) trong đất ở khu vực khai thác quặng là rất cần thiết đối với việc quản lý môi trường. Phân tích hàm lượng tổng số và dạng hóa học của As trong các mẫu đất được thực hiện theo quy trình chiết Tessier và thiết bị ICP-MS. Nồng độ trung bình của As trong 5 mẫu đất bãi thải là 10,14 ÷ 44,68 mg/Kg và trong 7 mẫu đất nông nghiệp là 5,66 ÷ 7,65 mg/Kg. As trong 12 mẫu đất phân tích đều tồn tại chủ yếu trong các mẫu đất ở dạng cặn dư (F5) > dạng cacbonat (F2) > dạng oxit Fe/Mn (F3) > dạng hữu cơ (F4) > dạng trao đổi (F1). Theo tiêu chuẩn Việt Nam, nồng độ của As trong các mẫu đất nông nghiệp đều thấp hơn giới hạn cho phép, và 3/5 mẫu đất bãi thải có nồng độ As thấp hơn giới hạn cho phép trong đất nông nghiệp và 2 mẫu đất bãi thải có nồng độ As cao hơn giới hạn cho phép. Theo chỉ số Igeo, hầu hết các mẫu đất đều có giá trị Igeo ở mức ô nhiễm nhẹ. Theo mã đánh giá mức độ rủi ro (RAC) thì 10/12 mẫu đất phân tích nằm ở mức rủi ro trung bình.
Searches for new physics in lepton plus jet final states in ATLAS and CMS : arXiv

The most recent results on searches in lepton plus jet final states motivated by different models beyond the standard model are presented, using pp collision data collected by the ATLAS and CMS detectors during Run I and Run II at the CERN LHC. Leptoquarks and heavy Majorana neutrinos that arise in the left-right model are looked for in the final states with two leptons and two jets (ll + jj; l = e; mu; tau ). Heavy Majorana neutrinos are further investigated by relying on a composite-fermion scenario, considering two leptons and one large-radius jet (ll + J; l = e, mu), and in the context of a model with Type-1 seesaw mechanism, requiring two same-sign leptons plus dijet (ll' + jj; l,l' = e, mu). Finally, models of microscopic black holes with two to six extra dimensions are tested by analysing the channels with at least one lepton and two additional jets (l + jj; l = e, mu). In all the searches, the observed data are in good agreement with the standard model prediction and 95% confidence level upper limits are set on the parameters of difierent models.
Prediction Intervals for Functional Data

Title of Thesis: PREDICTION INTERVALS FOR FUNCTIONAL DATA Nicholas Rios, Master of Science, 2018 Thesis directed by: Dr. Andrada E. Ivanescu Department of Mathematical Sciences The prediction of functional data samples has been the focus of several functional data analysis endeavors. This work describes the use of dynamic function-on-function regression for dynamic prediction of the future trajectory as well as the construction of dynamic prediction intervals for functional data. The overall goals of this thesis are to assess the efficacy of Dynamic Penalized Function-on-Function Regression (DPFFR) and to compare DPFFR prediction intervals with those of other dynamic prediction methods. To make these comparisons, metrics are used that measure prediction error, prediction interval width, and prediction interval coverage. Simulations and applications to financial stock data from Microsoft and IBM illustrate the usefulness of the dynamic functional prediction methods. The analysis reveals that DPFFR prediction intervals perform well when compared to those of other dynamic prediction methods in terms of the metrics considered in this paper. PREDICTION INTERVALS FOR FUNCTIONAL DATA 3 PREDICTION INTERVALS FOR FUNCTIONAL DATA
AI-based performance optimization of MPTT algorithms for photovoltaic systems

ABSTRACT Solar models have been drawing much attention in the contemporary electricity environment. Solar energy installations employ various MPPT techniques that generate the most energy. Increasing a solar (PV) device's energy effectiveness has become a key concern for scientists. Multiple MPPT approaches that collect the most power possible using a PV array have been researched. Both primary and intermediate-type procedures will be used in most procedures. The performance and convergence velocity of such a PV device become significant depending on its practical deployment under various conditions. The energy attributes of unit sections collectively serve as the primary energy-extracting elements in specific systems, dependent upon all interior and exterior elements. Considering specific external dynamical circumstances, traditional maximal power point tracing systems will not have the required translation efficacy. For assessing the overall effectiveness of the proposed intelligent maximal power point outlining methodology in partially shaded situations having significant and dynamical variations within ambient parameters, that study contrasts its efficacy using traditional maximal power point tracing techniques.
Stellar populations in the Galactic bulge

AIMS:The aim of this paper is to study the characteristics of the stellar populations and the metallicity distribution in the Galactic bulge. We study the entire stellar population, but also retrieve information using only the red clump stars. METHODS: To study the characteristics of the stellar populations and the metallicity distribution in the Galactic bulge, we compared the output of the galaxy model TRILEGAL, which implements the Binney et al. (1997) bulge model, with observations from 2MASS and OGLE-II. A minimisation procedure has been set up to retrieve the best fitting model with different stellar populations and metallicity distributions. RESULTS: Using the TRILEGAL code we find that the best model resembling the characteristics of the Galactic bulge is a model with the distance to the Galactic centre $R_0 = 8.7\pm^{0.57}_{0.43}$ kpc, the major axis ratios of the bar $1:\eta:\zeta = 1 : 0.68\pm_{0.19}^{0.05} : 0.31\pm_{0.04}^{0.06}$, and the angle between the Sun-centre line and the bar $\phi = 15\deg\pm_{12.7}^{13.3}$. Using these parameters the best model is found for a burst of 8 Gyr, although it is almost indistinguishable from models with ages of 9 and 10 Gyr. The metallicity distribution found is consistent with metallicity distributions in the literature based on spectroscopic results.
Multiobjective navigation of external radiotherapy plans based on clinical criteria

This study considers a navigation method for finding the most preferable radiotherapy plan from a discrete set using planner-defined clinical criteria. The method is based on repeatedly solving an optimization model to identify a plan that best satisfies the aspiration values set by the planner. During navigation, the planner iteratively adjusts the aspiration values to match the preference information learned from previous plans until the most preferable plan is identified. The use of soft constraints to model aspiration values enables navigation amongst a discrete set and allows the planner to freely specify the aspiration values without producing an infeasible model. We demonstrate the use of the model by applying it to a prostate cancer case. This illustrates that improvements in optimization criteria do not necessarily lead to improvements in clinical criteria. Hence, the method obviates the need to simultaneously monitor both optimization and clinical criteria in current navigation systems. Instead, the direct use of clinical criteria for navigation aids the planner to quickly identify the most preferable plan.
Isolating the Effects of Moisture Entrainment on Convectively Coupled Equatorial Waves in an Aquaplanet GCM

The rate of humidity entrainment in the convective parameterization scheme in a general circulation model affects the simulation of convectively coupled waves. However, it is unclear whether this is caused directly by the effects of entrainment on waves or indirectly through associated impacts such as on the basic state. Therefore, using an aquaplanet model, we employ a novel framework in which we entrain a weighted average of the resolved humidity field and a prescribed zonally symmetric field, with the weighting controlled by a decoupling parameter. Hence, we can vary the entrainment rate of basic-state humidity independently of the entrainment of humidity perturbations, simultaneously minimizing changes in the basic state. Thus, we isolate the effect of moisture entrainment on the waves. Enhancing the entrainment rate increases spectral power over all zonal wavenumbers and frequencies, with an increase in the ratio of eastward-to-westward power. The Kelvin wave speed decreases as entrainment increases, which can be partially accounted for by an associated change in basic-state humidity. Increasing the decoupling parameter reduces spectral power in Kelvin waves relative to the background, with only long waves still prominent when entrainment is almost fully decoupled from the resolved moisture field, suggesting the wave structure in humidity is required for convection to organize into short-wave structures. For long waves, the increase in the ratio of eastward-to-westward power as entrainment rate increases cannot be explained by the changes in the coupling with the wave structure in humidity but is consistent with the changes in the basic state.
OTFS Waveform Based on 3-D Signal Constellation for Time-Variant Channels

Orthogonal time frequency space (OTFS) is a new waveform modulated in the delay-Doppler domain that can achieve better communication performance than the conventional waveform, such as orthogonal frequency division multiplexing (OFDM), in high-mobility scenarios. In this letter, we introduce the three-dimensional (3-D) mapper into the conventional OTFS modulation scheme to further reduce the bit error rate (BER) at higher modulation orders. Moreover, the minimum Euclidean distance of the 3-D signal constellations and detector complexity analysis of the proposed 3D-OTFS are presented. The simulation results demonstrate that the proposed 3D-OTFS system outperforms the conventional OTFS system in terms of BER performance for higher modulation orders in time-variant channels, such as the Extended Vehicular A (EVA) channel and the Extended Pedestrian A (EPA) channel. Furthermore, performance comparisons between the proposed 3D-OTFS and 3D-OFDM in different time-variant channels show that the proposed 3D-OTFS is better suited for high-mobility communication scenarios.
Effectiveness of an education program for Caregivers Knowledge Related to Management of Children with Growth Hormone Deficiency in Outpatient Endocrine Clinics

Objectives: The study aims to assess and evaluate the caregivers knowledge about management of the children with growth hormone deficiency and to find out the relationship between caregivers kowledge and caregivers age, gender, number of individual in house hold, Date of treatment started ,Caregivers level education and economic status Methodology: Quazi expermental study design was carried out at (Child's Central Teaching Hospital, Medical City of Al Imamian Al Khadhmain Teaching Hospital, and National Centre for Treatment and Research of Diabetes,Specialized Center for Endocrine Diseases and Diabetes, and Department of Medical City Children Welfare Teaching Hospital started from novomber 6th , 2017 through july 1st , 2018 , accidental (non-probability) sample of (80) caregivers who were attending to outpatient endocrine clinics and centers.The data were collected through the use of constructed questionnaire , which consist of two parts (1) demographic characteristic (6 )items (2) caregivers knowledge which consist from 3 sections of (33 ) items . Validity of the study was determined through the panel of (16) experts and the reliability of the study questionnaire through the pilot study.Descriptive statistical and inferential analysis by using spss , version 23 Results: The findings of the study indicated that there is statistical significant difference between caregivers knowledge and their demographic characteristic except gender, level of education ,and economic status. The study recommended that: necessary for early detection of growth hormone deficiency for children, providing special nurse in endocrine clinics and center to give high quality care for children and education for children and their caregivers about signs and symptoms of growth hormone deficiency