Miracle-dz/UniFAR-FTUs huggingface dataset:
Cold-Start Satellite Signal Acquisition Aided by an Antenna Array in the Presence of Outliers

In the cold-start mode, this work addresses the issue of signal acquisition for a satellite navigation receiver aided by an antenna array in the presence of outliers. First, the satellite signals acquisition is formulated as a problem of sparse matrix recovery in terms of <inline-formula><tex-math notation="LaTeX">$\ell _{2,1}$</tex-math></inline-formula>-norms minimization which encourages row sparsity of signal matrix and effectively suppresses outliers simultaneously. Then, an iterative reweighted framework and the Lagrange multipliers method with complex-valued conjugate gradient descent are employed to find a suitable solution. After that, to accelerate the convergence rate of the mean square error (MSE), an improved <inline-formula><tex-math notation="LaTeX">$\ell _{2,1}$</tex-math></inline-formula>-norms cost function with composite regularizers is devised, where several conjugate gradients of <inline-formula><tex-math notation="LaTeX">$\ell _{2,1}$</tex-math></inline-formula>-norms are derived in detail and convex optimization theory is employed to find the global minimum. At last, actual satellite almanac is downloaded to provide the information of the visible satellites and then numerical results are presented to demonstrate the effectiveness of the proposed methods.
Ecotourism Development in Small Cities: Insights from Macao

ABSTRACT Small cities with fewer natural resources are relatively hesitant in developing ecotourism. However, ecotourism can be in any form anywhere, whenever all stakeholders involved in such businesses are ecologically, economically, and ethically responsible. This study therefore tries to identify challenges for small cities in developing ecotourism, by using the four criteria (i.e. ecotourism based in nature; learning opportunities; sustainably managed sites; and ethical and responsible activities). It also explains reasons discouraging small cities from ecotourism development based on the perspectives of involved stakeholders in nature-based tourism. Macao, with its small size, few natural resources, and the need to diversify tourism products to ease overcrowding issues in the urban touristic areas, was chosen as a case study to fill this research gap. The detailed evaluation of each criterion on ecotourism development and management presented a clear view of what has been done and not done properly in the city. This finding offers potential solutions for different public and nonpublic sectors who are attempting to embrace ecotourism.
Introduction to Matrix Analysis

Foreword Preface to the Second Edition Preface 1. Maximization, Minimization, and Motivation 2. Vectors and Matrices 3. Diagonalization and Canonical Forms for Symmetric Matrices 4. Reduction of General Symmetric Matrices to Diagonal Form 5. Constrained Maxima 6. Functions of Matrices 7. Variational Description of Characteristic Roots 8. Inequalities 9. Dynamic Programming 10. Matrices and Differential Equations 11. Explicit Solutions and Canonical Forms 12. Symmetric Function, Kronecker Products and Circulants 13. Stability Theory 14. Markoff Matrices and Probability Theory 15. Stochastic Matrices 16. Positive Matrices, Perron's Theorem, and Mathematical Economics 17. Control Processes 18. Invariant Imbedding 19. Numerical Inversion of the Laplace Transform and Tychonov Regularization Appendix A. Linear Equations and Rank Appendix B. The Quadratic Form of Selberg Appendix C. A Method of Hermite Appendix D. Moments and Quadratic Forms Index.
A Cumulus Parameterization with State-Dependent Entrainment Rate. Part II: Impact on Climatology in a General Circulation Model

Abstract The impact of a new cumulus parameterization developed in Part I of this paper on climatology in an atmospheric general circulation model (AGCM) is compared with that of the Arakawa–Schubert scheme. The parameterization is characterized by a vertically variable entrainment rate depending on the surrounding environment. Two kinds of formulations on entrainment rate are tested and produce similar results in the AGCM. The results show reduction of precipitation over land and increase over the sea, weakening of the southern side of the double intertropical convergence zone (ITCZ) over the southeastern Pacific, and better representation of the South Pacific convergence zone (SPCZ), all of which are consistent with observations. The population of cumulus congestus is significantly increased, thereby inducing additional heating in the lower troposphere. The diurnal variation over land shows that deep convection tends to be suppressed earlier because of the reduction of convective available potential ene.
A Novel Composition Forecasting Model Based on Choquet Integral with Respect to L-Measure and O-Density

In this paper, based on L-measure and O-density, a novel composition forecasting model is proposed. For evaluating this new composition forecasting model, a real data experiment by using the sequential mean square error was conducted. Based on O-density, the performances of Choquet integral composition forecasting model with the L-measure, Lambda-measure and P-measure, respectively, a ridge regression composition forecasting model and a multiple linear regression composition forecasting model and the traditional linear weighted composition forecasting model were compared. Experimental results show that the Choquet integral composition forecasting model with respect to the L-measure outperforms other 5 composition forecasting models.
Acrobatic Low-cost Portable Hybrid AUV (ALPHA): System Design and Preliminary Results

This paper reports the progress towards the development of a highly maneuverable affordable portable AUV, called ALPHA. The ALPHA has a diameter of 10-inch, an overall length of 1.5 m, and a total weight of about 30 kg with flooded areas for wet sensors. The research aims to provide an accessible under-water vehicle platform that is highly customizable to lower the barrier-of-entry to conduct research and education in underwater robotics. In this paper, the details in AUV system design will be presented. Field tests have conducted in Narragansett Bay to validate the performance of the guidance, navigation and control system with preliminary results shown and discussed in the paper. A suite of science sensors (an CTD, an optical dissolved oxygen sensor, and an optical chlorophyll sensor) is also integrated on the ALPHA for water property assessment during the field trials.
A topological abstraction for implementing recursive subdivision surface computations

AbstractWe present a new abstraction, association space, in the context of recursive subdivision surfaces. An association space relates elements in a recursive subdivision surface at a given refinement level to the elements of the surface at the previous refinement level. These associations allow a programmer to easily implement recursive subdivision algorithms and augment them with computations, such as multigrid techniques, that require inter-level traversals of the hierarchy of refined meshes. These associations also extend to distributed recursive subdivision surfaces. They underlie the mechanism for stitching the refined partitions of a mesh into a single refined mesh.
STRATEGI PENGEMBANGAN DESA WISATA AAN KECAMATAN BANJARANGKAN KLUNGKUNG

A tourism village is a community consisting of residents of a limited area who can interact directly with each other under management and have awareness and awareness to play a role together by adapting different individual skills. Tourism villages are formed to realize the community so that they can act as direct actors in an effort to increase readiness and awareness in responding to tourism potential or tourist attractions in the area of each village. This study aims to formulate a development strategy for the tourism village of Aan as a tourism destination in Klungkung. Aan Village has enormous potential but faces a number of obstacles in its development. This is indicated by the diversity of tourism potentials originating from nature, culture and man-made tourist attractions. The research was conducted through a qualitative descriptive analysis using SWOT analysis to find strategies for developing the potential of the Aan tourism village and tourism area life cycle analysis. Data collection techniques through observation, in-depth interviews, documentation and literature study. Retrieval of informants was done by purposive sampling. The results of the study show that to maximize the development of the attractiveness of Aan Village as a tourist destination, it is necessary to develop strategies and programs such as community empowerment, development of supporting infrastructure, and collaboration with stakeholders and the private sector in creating sustainable programs
The Projective Synchronization of Drive-Reponse Complex Dynamical Networks

This paper investigates the projective synchronization of drive-response complex dynamical networks. Based on the stability theory for fractional-order differential equations, controllers are designed torealize the projective synchronization for complex dynamical networks. Morover, some simple synchronization conditions are proposed. Numerical simulations are presented to show the effectiveness of the proposed method.
Stochastic theory of diffusion-controlled reaction

A stochastic theory of a diffusion-controlled reaction is developed with the emphasis on the many-body aspects which rigorous stochastic theories inevitably encounter. The field operator method developed in the previous paper (see ibid., vol.9, no.9, p.1465 (1976)) is extensively used in the analysis. The classical Smoluchowski theory is shown to be strictly valid in the long-time scale, and its relation to the Boltzmann equation is discussed.
Next-Generation Sequencing of a Large Gene Panel for Outcome Prediction of Bariatric Surgery in Patients with Severe Obesity

Obesity is a chronic disease in which abnormal deposition of fat threatens health, leading to diabetes, cardiovascular diseases, cancer, and other chronic illnesses. According to the WHO, 19.8% of the adult population in Italy is obese, and the prevalence is higher among men. It is important to know the predisposition of an individual to become obese and to respond to bariatric surgery, the most up-to-date treatment for severe obesity. To this purpose, we developed an NGS gene panel, comprising 72 diagnostic genes and 244 candidate genes, and we sequenced 247 adult obese Italian patients. Eleven deleterious variants in 9 diagnostic genes and 17 deleterious variants in 11 candidate genes were identified. Interestingly, mutations were found in several genes correlated to the Bardet–Biedl syndrome. Then, 25 patients were clinically followed to evaluate their response to bariatric surgery. After a 12-month follow-up, the patients that carried deleterious variants in diagnostic or candidate genes had a reduced weight loss, as compared to the other patients. The NGS-based panel, including diagnostic and candidate genes used in this study, could play a role in evaluating, diagnosing, and managing obese individuals, and may help in predicting the outcome of bariatric surgery.
Bioactive Compounds and Antioxidant Properties of Wild Rocket (Diplotaxis Tenuifolia L.) Grown under Different Plastic Films and with Different UV-B Radiation Postharvest Treatments

Rocket species are rich in nutrients with well-known bioactive activity, but their content depends on several factors, such as plant–UV radiation interaction. In this work, we measured the production of nutritional elements in wild rocket (Diplotaxis tenuifolia L.) leaves as a function of exposure to UV-B radiation by adopting a combined approach. The wild rocket plants were grown under three greenhouse cover films (A, B, and C) having different transmittivity to UV-B and the fresh-cut leaves were exposed to UV-B in postharvest for 45, 150, 330, and 660 s. The content of chlorophyll, carotenoids, phenolic compounds, ascorbic acid, and the antioxidant activity were determined. Chlorophyll, carotenoids, and total phenolic content were significantly increased by the combination of Film C and treatment with UV-B for 45 s. The predominant phenolic compounds were kaempferol, isorhamnetin, and quercetin. Film C also elicited an increase in ascorbic acid (the most abundant antioxidant compound in the range 374–1199 per 100 g of dry matter) and antioxidant activity. These findings highlighted an increase in bioactive compound content in the wild rocket when it was cultivated under Film C (diffused light film with a tailored UV-B transmission dose) and treated with UV-B radiation for 45 s postharvest, corresponding to an energy dose of 0.2 KJ m−2.
NeuroAI - A strategic opportunity for Norway and Europe

At an energy consumption of merely 20 watts, the brain is able to learn, perceive its surroundings, analyze solutions, predict the future and choose actions in a much more general way than any computer algorithm and infrastructure. NeuroAI, an emerging field at the intersection of brain sciences and artificial intelligence, is expected to become a large research field in the years to come. The main promise of NeuroAI is that by understanding how the brain and biological neural networks compute, it will be possible to identify the key components of human intelligence in order to drive the development of a more energy-efficient and flexible artificial intelligence (AI) that will match, perhaps even surpass, human intelligence. NeuroAI is a truly multidisciplinary effort, spanning across several disciplines such as computer science, neuroscience, psychology, philosophy, linguistics, law and ethics. Norway has unique world-class expertise in brain sciences, and a fast growing, well-organized AI community at the highest international level. In this opinion article, we argue that Norway has competitive advantages within NeuroAI, and that Norway has the ideal ecosystem to take a leading role in NeuroAI initiatives in Europe. Norwegian investments in NeuroAI may be a strategic initiative to position Norway in the forefront of AI research worldwide.
Nanomaterial-Based Sensors for Exhaled Breath Analysis: A Review

The quantification of gases in breath has gained significant attention as a modern diagnosis method due to its non-invasive nature, and as a painless and straightforward method for the early detection of physiological disorders. Several notable clinical applications have been established for disease diagnosis by correlating exhaled breath samples and specific diseases. In addition, diverse breath molecules represent a biomarker of specific illnesses and are precisely identified by the standard analytical method. However, because of the bulky equipment size, expensive cost, and complexity in measurement when using analytical methods, many researchers are focusing on developing highly selective, sensitive, stable, robust, and economical sensors for breath analysis. It is essential to optimize approaches such as breath sampling, biomarker sensing, data analysis, etc. However, the detection of ppb-level biomarkers in exhaled breath is too challenging to solve due to the abundance of interfering gases. We present a brief and comprehensive review of a recent diagnostic technique that employs nanomaterial (NM)-based sensors to identify the volatile organic compounds (VOCs) associated to diseases. Because they are easily fabricated, chemically versatile, and can be integrated with existing sensing platforms, NMs are ideal for such sensors. Initially, this review provides crucial details about certain representative biomarkers found in diseased patients’ exhaled breath and the demand for breath sensors. Subsequently, the review highlights diverse sensor technologies such as electrical, optical, and mass-sensitive gas sensors and describes their sensing capability for detecting the biomarkers’ concentrations and their primary endeavor of diagnosing disease. Finally, the pitfalls and challenges of sensor characteristics are discussed. This article lays the basis for developing high-performance gas sensors based on novel NMs.
The Spatiotemporal Variability of Snowpack and Snowmelt Water 18O and 2H Isotopes in a Subarctic Catchment

This study provides a detailed characterization of spatiotemporal variations of stable water 18O and 2H isotopes in both snowpack and meltwater in a subarctic catchment. We performed extensive sampling and analysis of snowpack and meltwater isotopic compositions at 11 locations in 2019 and 2020 across three different landscape features: (a) forest hillslope, (b) mixed forest, and (c) open mires. The vertical isotope profiles in the snowpack's layered stratigraphy presented a consistent pattern in all locations before snowmelt, and isotope profiles homogenized during the peak melt period; represented by a 1–2‰ higher δ $\delta $18O value than prior to melting. Our data indicated that the liquid‐ice fractionation was the prime reason that caused the depletion of heavy isotopes in initial meltwater samples prior to the peak melt period. The liquid‐ice fractionation was influenced by snowmelt rate, with higher fractionation during slow melt. The kinetic liquid‐ice fractionation was evident only in close examination of meltwater lc‐excess values, not δ $\delta $18O values alone. Meltwater was isotopically heavier and more variable than the depth‐integrated snowpack; the weighted mean of meltwater isotope values was higher by 0.62–1.33‰ δ $\delta $18O than the weighted mean of snowpack isotope values in forest hillslope and mixed forest areas, and 1.51–6.37‰ δ $\delta $18O in open mires. Our results reveal close to 3.1‰ δ $\delta $18O disparity between the meltwater and depth‐integrated snowpack isotope values prior to the peak melt period, suggesting that proper characterization of meltwater δ $\delta $18O and δ $\delta $2H values is vital for tracer‐based ecohydrological studies and models.
The Influence of Motive Attributions for Destination Social Responsibility on Residents’ Empowerment and Quality of Life

This research provides new insights into the link between destination social responsibility (DSR) and resident quality of life (QOL). A conceptual model is tested based on attribution theory and empowerment theory that investigates the impact that different DSR motive attributions can have on resident QOL, and the potential mediating role of empowerment. DSR actions attributable to intrinsic (extrinsic) motives by destination residents were found to demonstrate greater (lesser) empowerment and QOL. Empowerment was found to have a significant positive impact on QOL and to mediate the DSR motive attribution and resident QOL relationship. Examination of these initial findings suggest that intrinsic, relative to extrinsic, DSR motive attributions enhance resident empowerment through tourism and QOL under high involvement conditions. This relationship was not found to hold in low involvement tourism conditions. The paper concludes with a discussion of theoretical and managerial contributions, as well as study limitations and future research directions.
Velocities and rotational excitation of interstellar H2 toward Pi Scorpii

A spectrum of Pi Sco showing numerous atomic lines and 70 absorption features from the Lyman and Werner transitions of interstellar H2 in rotational level J from zero to five is presented. Their shapes of the composite column density profiles are very nearly Gaussian with a one-dimensional rms velocity dispersion of 3 km/s. The behavior of shifts in the inferred N(H2) as a function of velocity are consistent with the overall profiles being composed of nearly symmetrical, tightly paced assemblies of about seven unresolved components. The relative overall column densities in the higher J levels of H2 are consistent with a model where these states are populated by optical pumping through the Lyman and Werner transitions, powered by UV radiation from nearby stars. The slight narrowing of the high-J profiles may be due to small clumps of H2 at radial velocities some 5-8 km/s from the core of the profile are exposed to a pumping flux about 10 times lower than that for the material near the profile's center.
Resource allocation in 5G multi-tenancy network slicing for balancing distribution power systems

In recent years consumers of power have also started to generate power via renewable sources such as wind and solar. In smart grid distribution systems, controls are applied to regulate the consumption and distribution of energy to save energy and costs. These controls rely on monitoring of the power distribution systems. To monitor these systems sufficiently to optimize power flow can be costly. The advent of fifth-generation (5G) networks presents an opportunity to improve monitoring capabilities at low cost. In the 5th generation of mobile cellular networks, end-to-end network slicing is the critical enabler, such that an infrastructure provider creates various network slices for different Mobile Virtual Network Operators (MVNOs) to accommodate various services. This work assumes each MVNO is a power company while nodes are sensors and actuators in the power grid. Proper resource allocation for numerous coexisting network slices is vital. We address this issue by proposing a novel scheme in Radio Access Network (RAN) network slicing to maximize spectral efficiency, subject to guaranteeing each sensor and actuator in the power grid receives a minimum requirement of slices. We characterize the fundamental hardness of our problem and develop a greedy heuristic. Next, via simulations on the IEEE 13-, 34- and 37-node test feeders, we show that the proposed algorithm achieves superior performance in terms of served power after balancing the unbalanced distributed power system.
ARCoD: A Serious Gaming Approach to Measure Cognitive Distortions

Cognitive Distortion, defined as erroneous and in-accurate thoughts [4] can cause fatal mental impairment. Identifying the presence of cognitive distortions is the fundamental initiative to treat mental health disorders such as anxiety and depression. As a consequence of COVID-19 and the other changes in social aspects, there is an escalation in the number of patients with mental illness. Although there are abundant effective psychotherapy strategies available, a substantial number of people avoid them due to misconceptions and stigma. Serious games can be a feasible solution to purvey mental healthcare to a significant percentage of people. The availability of smartphones unveils the opportunity to provide therapeutic facilities via digital gaming. Technology like Augmented Reality with its interactive features, has unlocked numerous opportunities in the mental health domain. In this paper, we have remodeled our previously proposed game, ARCoD, accessible on smartphones to measure Cognitive Distortions. We hypothesized that, through this game, it is possible to assess the level of 5 different Cognitive Distortions (Arbitrary Inference, Catastrophizing, Black and White Thinking, Emotional Reasoning, and Labeling) in an individual playing the game. The experimental outcome demonstrates that the level of Cognitive Distortions assessed from the game is exceedingly similar to the measurement accumulated from an established scale-Cognitive Distortion Scale (CDS).
Photoluminescence of polycrystalline CuInSe2 thin films

The photoluminescence of CuInSe2 thin films grown by multisource physical vapor deposition is investigated over a wide composition range with a specially designed sample. Measurements as a function of excitation intensity, and temperature are correlated with the Cu/In ratio x of the films ranging from 1.47≤x≤0.46. All the Cu–rich samples (x≳1.0) show well‐defined peak positions independent of the composition. In the slightly In‐rich region (x=0.90) where the best absorber layers for high efficiency CuInSe2 solar cells are expected, two broad emission lines are ascribed to donor‐acceptor pair transitions. For very In‐rich samples (x<0.67), a blue shift of the dominant transition is observed.