Miracle-dz/UniFAR-FTUs huggingface dataset:
Theoretical Model and Design of Highly Sensitive Reflective Fiber Optic Fabry-Pérot Cavity Accelerometer Independent of Fiber Stiffness

The sensitivity of an accelerometer-based on fiber Bragg grating (FBG) is limited by the stiffness of the encapsulated fiber, and this article is inspired to research the highly sensitive accelerometer of the Fabry-Pérot (F-P) cavity with wavelength demodulation which is not affected by fiber stiffness. The mechanism of a new type of sensor based on the F-P cavity is researched, and the constraints of sensitivity and resonant frequency are researched systematically. The figure of merit is introduced to evaluate the comprehensive performance of the accelerometer. Theoretical analysis indicates that the F-P cavity accelerometer does have a good advantage, its sensitivity is two orders of magnitude higher than that of the FBG accelerometer. The experimental results show that the bandwidth of the sensor ranges from 10 to 350 Hz, a corresponding sensitivity range is from 5.95 to 10.12 nm/G, and the figure of merit is 6278.4 nm $\cdot $ Hz/G. Thus, it can be sufficiently demonstrated that the model has the potential advantages of ultrahigh sensitivity and miniaturization, which have potential theoretical significance and practical application value in the field of vibration signal detection.
Accounting the blue planet in tourism: Undersea and the opportunity for inclusive approaches to knowledge production

Oceanic estates are increasingly involved in the development of undersea tourism and leisure. Encountering undersea for pleasurable experiences is becoming big business as tourism and blue economies combine in these novel ways. As this size-able territory is opened up and transformed into diverse undersea experiences, equally important theoretical opportunities begin to emerge for tourism scholarship. This paper begins to explore the dimensions of this industry through some the most innovative undersea attractions to reveal the theoretical promises of blue tourism. The benefits and challenges of these encounters do not only accrue to tourists and the tourism industry but also to the development of tourism knowledge. While understanding the production and consumption of blue tourism is valuable for the sustainable management of oceanic estates, this paper advocates the latent possibilities of undersea to counter the territorial bias that dominates tourism theory, limiting an appreciation of the role of all kinds of actors.
Motiv för inflyttning till Dalen och Östbergahöjden samt inflyttades värdering av områdena : Arbetsrapport nr 5 i projektet Grannskapseffekter på områdesnivå- en fördjupad studie av bostadsrättsombildning i allmännyttan

Huvudsyftet med denna studie ar att fa kunskaper om varfor man flyttar till Ostbergahojden och Dalen samt vilka kvaliteter och eventuella problem de nyinflyttade upplever i respektive omrade. Metod .
Análisis de los factores que influyen en la intención de compra online

El tema del comercio online presenta un rápido crecimiento se ha evidenciado como una tendencia emergente entre diferentes consumidores. La popularidad del comercio online ha sido de interés para expertos en marketing e investigadores a enfocarse en esta área. Esta investigación tiene como objetivo analizar la literatura relacionada con factores como: percepciones del consumidor en el proceso de compra online, el perfil sociodemográfico del consumidor online y la adopción a la innovación tecnológica del consumidor online. Se realizó un análisis exploratorio y descriptivo para identificar las investigaciones en los factores de interés. La literatura reconoce una variedad de factores asociados a la intención de compra online y con un énfasis especial en los factores que aquí se proponen.
An Autonomous Feature Detection Method of Slow Small Targets on Sea Surface Based on Contextual Bandit

Under the background of slow small target detection on sea surface, it is a serious problem that the detection performance of existing feature detection methods decreases when the number of coherent pulses is less. In this letter, we first model the slow small target detection on sea surface as a contextual bandit (CB) problem. On this basis, we propose an autonomous feature detection method by modifying the classical feature detection process. The method can autonomously choose the detectors with better performance under the current sea scene from the constructed 18 feature detectors and obtain the fine detection performance by fusing their detection results. The performance superiority and the real-time capability of the proposed method are verified by the experiments on seven CSIR datasets.
A Method to Calculate Complex Cramér-Rao Bound for Line Spectrum Estimation After Compression with Multiple Measurement Vectors

A method to calculate the complex Fisher information matrix (FIM) and the Cramer-Rao bound (CRB) is proposed for line spectrum estimation (LSE) problem after compression with multiple measurement vectors (MMVs). The detailed theoretic calculation process is presented in the text. Finally, numerical results are conducted to demonstrate the accuracy of CRB as the performance criterion.
Very Thin Layer Method for Solving High Schmidt Number Flow on Unstructured Hybrid Mesh

A CFD code based on unstructured mesh consisting of tetrahedrons and triangular prisms has been developed. The prisms are generated along body boundaries to resolute momentum boundary layers. A cell-centered finite volume discretization, the fractional step algorithm, third order compact scheme for convection term, a central difference for the diffusion term are adopted. In high Schmidt number problems, mass boundary layer is much thinner than that of momentum so that very thin layers (VTL) are generated in one layer of prisms attached to the interface only for solving mass transfer. It is noted that the explicit time integration is used for momentum, while mass is solved implicitly in time for reducing computational time. The Sherwood numbers of a solid sphere are obtained in our numerical experiments and are in good agreement with some typical empirical equations.
Real-Time Face Recognition Attendance System Based on Video Processing

The advent of big data and the commercial value of facial recognition technology have created a bright future for the technology, with a large market potential. This article proposes a face recognition participation framework based on continuous video processing. The article explores four aspects of the framework: the accuracy of facial recognition in offline recordings, the accuracy of facial recognition in continuous video processing, the dropout rate of the face recognition participation framework with continuous video processing, and the interface settings of the face recognition participation framework with continuous video processing. By analyzing these aspects, the article proposes a framework for participation based on facial recognition technology and conducts research on the framework with continuous video processing. Experimental results show that the accuracy of the video facial recognition framework can reach 82%. Compared with the traditional registration method, the face recognition participation framework can reduce the dropout rate by more than 60%. The dropout rate of missing classes has also been significantly reduced, which can effectively address the problems of students missing classes and leaving classes early.
The effect of cerebellar TMS on error processing: A combined single-pulse TMS and ERP study

Abstract The present study investigated temporal aspects of cerebellar contributions to the processing of performance errors as indexed by the error-related negativity (ERN) in the response-locked event-related potential (ERP). We co-registered EEG and applied single-pulse transcranial magnetic stimulation (spTMS) to the left posterolateral cerebellum and an extra-cerebellar control region (vertex) while healthy adult volunteers performed a Go/Nogo Flanker Task. In Go trials, TMS pulses were applied at four different time points, with temporal shifts of -100 ms, -50 ms, 0 ms, or +50 ms relative to the individual error latency (IEL, i.e., individual ERN peak latency + median error response time). These stimulation timings were aggregated into early (-100 ms, -50 ms) and late (0 ms, +50 ms) stimulation for the analysis. In Nogo trials, TMS pulses occurred 0 ms, 100 ms, or 300 ms after stimulus onset. Mixed linear model analyses revealed that cerebellar stimulation did not affect error rates overall. No effects were found for response times. As hypothesized, ERN amplitudes were decreased for cerebellar stimulation. No significant differences were found for the error positivity (Pe). Similar to TMS application to probe cerebellar-brain inhibition in the motor domain, the inhibitory tone of the cerebellar cortex may have been disrupted by the pulses. Reduced inhibitory output of the cerebellar cortex may have facilitated the processing of error information for response selection, which is reflected in a decreased ERN.
PEMODELAN SISTEM INFORMASI GEOGRAFIS (SIG) PADA DISTRIBUSI PENYAKIT DEMAM BERDARAH DENGUE (DBD) DI KECAMATAN KARANGMALANG KABUPATEN SRAGEN

Abstract: Modeling Of Geographic Information System (GIS) In Distribution of Dengue Haemorrhagic Fever (DHF) In The District Karangmalang Sragen. This study aims to provide an overview of the spatial distribution of Dengue Hemorrhagic Fever (DHF), aware of any clustering of dengue cases and analyze the risk factors associated with the incidence of dengue disease in the district Karangmalang Sragen with modeling of Geographic Information Systems (GIS) with SpatialAnalysis. The results of this study indicate that the pattern of distribution of cases of Dengue Hemorrhagic Fever (DHF) in the district Karangmalang Sragen toward clustered (Clustering) and There is a relationship between the distribution of cases of Dengue Hemorrhagic Fever (DHF) with Population Density, Figures Status Free Larva (ABJ) and the percentage of large settlements in districts Karangmalang Sragen. Keywords : Geographic Information Systems (GIS), Dengue Hemorrhagic Fever Abstrak: Pemodelan Sistem Informasi Geografis (SIG) pada Distribusi Penyakit Demam Berdarah Dengue (DBD) di Kecamatan Karangmalang Kabupaten Sragen. Penelitian ini bertujuan untuk memberikan gambaran distribusi spasial penyakit Demam Berdarah Dengue (DBD), mengetahui adanya clustering pada kasus DBD dan menganalisis faktor-faktor resiko yang berhubungan dengan kejadian penyakit DBD di kecamatan Karangmalang kabupaten Sragen dengan pemodelan Sistem Informasi Geografis (SIG). Hasil penelitian ini menunjukkan bahwa Pola distribusi kasus Demam Berdarah Dengue (DBD) di kecamatan Karangmalang ke arah mengelompok (Clustering) dan Terdapat hubungan antara Distribusi kasus Demam Berdarah Dengue (DBD) dengan Kepadatan Penduduk, Status Angka Bebas Jentik (ABJ) dan prosentase luas permukiman di kecamatan Karangmalangjiwa. Kata kunci: Sistem Informasi Geografis (SIG), Demam Berdarah Dengue.
Power Improvement of Partial Shaded Photovoltaic System Using Water Swirl Arrangement Method

The phenomenon of the partial shading is major cause which affects the operation of the PV system. The non uniform irradiation mainly caused due to towers, passing of clouds, falling of trees, etc. This becomes the reason to power reduction and mismatch loss. In this developed arrangement method, a new reconfiguration method is developed to enhance the power of the PV system which follows the Water Swirl (WS) pattern. The operation of PV system with minimum mismatch loss of PV array using shaded dispersion method is allowed. For array formation of developed method, the equations with constraints are expressed. Simulation of $\mathbf{9}\times \mathbf{9}$ Photovoltaic arrays is simulated in MATLAB/Simulink and output analysis has been validated. The comparison is made between mismatch loss generation under non-uniform pattern and power improvement with various arrangement methods. The developed arrangement method is good and well than total cross tied and series-parallel patterns methods. For assumed system mismatch losses are minimal and power output is improved using shade dispersion.
Spatial Ecology and Captive Behavior of Rehabilitated Black Bears in Utah

Fitness for animals is governed by the ability with which individuals are able to utilize the components of their habitat; thus, wildlife ecology and management necessitates a thorough understanding movement, space use, and resource needs for organisms. The study of animal space and resource use is particularly salient for the reintroduction of rehabilitated carnivores, given their wide-ranging nature, their release into habitats that are assumed to meet their needs, and human-safety which is reliant upon the expression of natural behaviors by those animals. Rehabilitated animals, however, are rarely monitored after release. I utilized GPS technology, resource selection functions, and generalized linear mixed models, to investigate the immediate post-release movements, denning chronology, release-site fidelity, and season-delineated movements, home ranges, and resource use for orphaned and rehabilitated black bears (Ursus americanus). Results indicate species-typical behaviors, with bears denning shortly after their releases, exhibiting elevated movement rates and dispersals during late-summer, preferential selection for certain habitat types based on season, and no utilization of anthropogenic-resources. The survival and behavior of the rehabilitated bears in this study suggest that captive care of orphaned wildlife can be a safe and effective practice with no apparent deleterious effects on fitness.
The anatomy of a long­lived fault system—structural and thermochronologic evidence for Laramide to Quaternary activity on the Tijeras fault, New Mexico

Many previous workers have recognized that the Tijeras–Canoncito fault system is a long­lived fault system. The number, timing, and kinematics of different deformation events, however, have been dif­ ficult to resolve due to a lack of piercing points and stratigraphic limitations. We propose a method for resolving the kinematics and minimum number of faulting events and use fission track and 40Ar/39Ar dating techniques together with geologic constraints to evaluate the timing of these events. Our approach is to use minor faults as a record of strain in the damage zone of the Tijeras fault and to assume that strain is compatible with fault slip. Thus, for example, the absence of evidence for crustal thickening in the damage zone is taken to indicate that the fault did not experience reverse motion. This work indicates that fault­zone structural elements largely record dextral strike­slip motion with a component of north­side­down normal motion. This is the earliest faulting event, which ther­ mochronologic and geologic constraints indicate initiated during the Laramide orogeny. The fault may have been reactivated during the transition in stress states between the Laramide orogeny and Rio Grande rifting and was definitely active during extension associated with the Rio Grande rift. Reactivation involved left­lateral strike­slip motion and, at least locally, further north­side­down nor­ mal movement.
On mining pixel based evolution classes in satellite image time series

The actual increase in size, in resolution, in spectral chan nel number and in acquisition frequency of remote sensing images makes possible for end-users to gather huge volumes of observation data for a same geographical area, at different dates. This kind of data is termed as Satellite Image Time Series (SITS) [1]. In this paper, we propose to process SITS data by exhibiting pixel based evolution classes. In this aim, we classify pixels according to their radiometric evolutions through each image of the time series by building up a trie [2]. Experiments on a SPOT image time series originating from ADAM (Data Assimilation for Agro-Modeling) [3] project are detailed.
Osmoregulation facilitated by leaf structural and functional traits in malabar nut (Justicia adhatoda L.) along elevation gradient

Elevations possess a specific set of biotic and abiotic factors that determine the vegetation type of the region. Abiotic factors along with biotic factors in a region can change the morphology, physiology and anatomy of vegetation. Justicia adhatoda (L.) was collected from different elevations in the northern areas of Pakistan. Morphology of lower elevations (200 m) showed healthy growth representing plenty of nutrients and water along with suitable abiotic climatic conditions. At moderate levels (800 m and 1250 m) total chlorophyll reduced, however lower (200 m) and higher (1550 m) elevations showed increased concentration of photosynthesis. Proline and glycine betaine concentrations were the lowest at 200 m and 800 m. Anatomical changes like increased cuticle thickness, epidermal thickness and number of cystoliths increased with elevations (1400 m) showing environmental variability. The presence of more adaptive features like trichomes and cystoliths at low and high elevations that were linked to tolerance against environmental adversaries. Such morpho-anatomical and physiological study of Justicia adhatoda is helpful to understand the elevational adaptation in different abiotic climatic conditions, such as temperature, wind velocity, UV and soil physio-chemistry.
Exploration of hydro-geomorphological indices for coastal floodplain characterization in Rivers State, Nigeria

Flood is a reoccurring natural hazard in many parts of Nigeria, and is likely to increase in severity and frequency. Characterization of recently flooded areas was carried out using hydro-morphological indices to identify flood prone areas. In flood risk quantification and identification, hydrodynamic models require vast amounts of data, while contour delineation fails to account for the upstream contribution and accumulation at downstream locations. Data on recently flooded areas and elevation data were collated. Hydro-geomorphometric indices were computed and compared using the Mann-Whitney U test. Across the indices, the terrain roughness indices – vertical roughness measure (VRM) and topographic roughness index (TRI) were found to be significant but weakly correlated (r = 0.455, P<0.05). There was a significantly positive but moderate correlation between topographic wetness index (TWI) and VRM (r=-0.673) and TWI vs TRI (r=0.572). Topographic position index (TPI) displayed a weak but significant relation to VRM, TWI and TRI. Of these four indices, TWI and TRI have standardized test statistics of -6.11 and 10.00 respectively and a significant test value < 0.05. Results show that flooded and non-flooded areas can be distinguished for the study area using these indices. It is recommended that hydro-geomorphometric indices should be used, adding another layer of confidence in the identification of flood prone areas for disaster risk management in data poor environments.
MS-Mapper: A LiDAR Mapping System by Switching Between Mobile and Stationary Configurations

This article introduces the design and implementation of MS-Mapper, a LiDAR mapping system incorporating a mechanical structure based on a step motor and steering gear. The hardware configuration of MS-Mapper allows for adjustable vertical and horizontal orientations of the LiDAR sensor. The MS-Mapper has two configurations during the mapping process: stationary mapping (S-mapping), which is dedicated to generating detailed point cloud maps and providing pose drift correction, mobile mapping (M-mapping), which is utilized for completing map cavities and ensuring comprehensive coverage mapping. This dual-configuration approach employed by MS-Mapper significantly enhances pose estimation accuracy, particularly in challenging environments such as lengthy corridors. To further improve pose estimation accuracy, we propose a residual selection-based bundle adjustment (BA) algorithm. Additionally, we propose a dynamic Gaussian mixture model (GMM) tree map representation, which is designed to accommodate dynamic growth. This representation effectively reduces the number of redundant Gaussian models and minimizes data association costs compared to utilizing a dense point cloud. Furthermore, a configuration selection algorithm is proposed to detect pose estimation degeneration and determine optimal opportunities for switching configurations. In summary, the MS-Mapper system amalgamates the strengths of the traditional terrestrial laser scanner (TLS) and LiDAR simultaneous localization and mapping (SLAM) approaches. MS-Mapper provides a robust solution for achieving accurate mapping results.
Stacked Layer Based Deep Learning Approach for Fake News Classification

The growth of the global population”s social. , economic. , and emotional spheres is impacted by fake news and misleading information. Several classification systems are available to help identify fake news. , but they needed to be quicker. , more secure. , and as trustworthy as was required at the time. Since manually confirming the integrity of news is difficult and expensive. , researchers have shown much interest in this area. Different techniques for spotting fake news. , including sentiment-based. , image-based. , content-based. , social context-based. , and hybrid context-based categorization. , were examined. In this paper. , we have developed a lightweight Deep Learning (DL) network for Fake News Classification (FNC). , a sentiment-based classification. The deep network consists of a stacked layer based feature extraction approach. Here stack layer first extracts the global features by the network of Bidirectional-Long Short Term Memory (Bi-LSTM) and Bidirectional-Gated Recurrent Unit (Bi-GRU). The results of the global features we have extracted the local features by the Convolutional Neural Network (CNN). The experiment findings show that the suggested lightweight DL network is more successful in producing superior results than the other methods.
Prospects for narrowing bounds on Earth's equilibrium climate sensitivity

The concept of Earth's Equilibrium Climate Sensitivity (ECS) is reviewed. A particular problem in quantifying plausible bounds for ECS has been how to account for all of the diverse lines of relevant scientific evidence. It is argued that developing and refuting physical storylines (hypotheses) for values outside any proposed range has the potential to better constrain these bounds and to help articulate the science needed to narrow the range further. A careful reassessment of all important lines of evidence supporting these storylines, their limitations, and the assumptions required to combine them is therefore required urgently.
Neural Networks in Recruitment: Trends and Future Directions

A thorough bibliometric analysis of 464 academic publications published between 1985 and 2023 is presented in this study to analyse current trends and potential future directions for neural networks in recruiting. It looks at publishing patterns, well-known publications, and notable contributors to this area-authors, institutions, and nations. The findings help researchers choose credible journals for publishing by offering insightful information on major research themes and illuminating developing areas within this domain. Researchers need to investigate the use of neural networks in new recruiting fields, such as prejudice reduction, diversity and inclusion, ethical considerations, and privacy issues. Future research might focus on using neural networks in group decision-making procedures and the fusion of neural networks with other cutting-edge technologies like machine learning and natural language processing.