Miracle-dz/UniFAR-FTUs huggingface dataset:
Lateralization of autonomic activity in response to limb-specific threat

In times of stress or danger, the autonomic nervous system (ANS) signals the fight or flight response. A canonical function of ANS activity is to globally mobilize metabolic resources, preparing the organism to respond to threat. Yet a body of research has demonstrated that, rather than displaying a homogenous pattern across the body, autonomic responses to arousing events — as measured through changes in electrodermal activity (EDA) — can differ between right and left body locations. Surprisingly, the metabolic function of such ANS asymmetry has not been investigated. In the current study, we investigated whether asymmetric autonomic responses could be induced through limb-specific aversive stimulation. Participants were given mild electric stimulation to either the left or right arm while EDA was monitored bilaterally. Across participants, a strong ipsilateral EDA response bias was observed, with increased EDA response in the hand adjacent to the stimulation. This effect was observable in over 50% of individual subjects. These results demonstrate that autonomic output is more complex than canonical interpretations suggest. We suggest that, in stressful situations, autonomic outputs can prepare either the whole-body fight or flight response, or a simply a limb-localized flick, which can effectively neutralize the threat while minimizing global resource consumption. These findings provide insight into the evolutionary pathway of neural systems processing general arousal by linking observed asymmetry in the peripheral arousal response to a historical leveraging of neural structures organized to mediate responses to localized threat.
Achieving MTO's High Effective Response Rates: Strategies and Tradeoffs

The Institute for Social Research (ISR) at the University of Michigan successfully led an intensive, long-term, in-person survey for the Moving to Opportunity (MTO) for Fair Housing demonstration final impacts evaluation (Sanbonmatsu et al., 2011), achieving final effective response rates (ERRs) of 89.6 percent among MTO adults and 88.7 percent among youth, well above what response rates of surveys with comparable low-income populations have accomplished. A variety of survey field strategies ISR employed— careful staff selection, strategic use of financial incentives, and close collaboration between ISR and the National Bureau of Economic Research—all contributed to these high ERRs. The high costs associated with achieving high ERRs for in-person surveys like that employed in MTO raises questions about added value. Costs per survey interview nearly quadrupled during the last 4 fielding months. This extra investment increased the MTO adult survey ERR by only about 3.2 percentage points. A reanalysis of intention-to-treat estimates on selected outcomes suggests the merits of such an investment. If survey field ing had stopped at an 81-percent ERR for adults, we would have falsely concluded that MTO had no effect on two of four key health outcomes, that MTO had no effect on female youth mental health, and that MTO increased female youth idleness.
The Predictive Model of Oral Squamous Cell Survival Carcinoma: A Methodology of Validation

Background Cancer is primarily caused by smoking, alcohol, betel quit, a series of genetic alterations, and epigenetic abnormalities in signaling pathways, which result in a variety of phenotypes that favor the development of OSCC. Oral squamous cell carcinoma (OSCC) is the most common type of oral cancer, accounting for 80–90% of all oral malignant neoplasms. Oral cancer is relatively common, and it is frequently curable when detected and treated early enough. The tumor-node-metastasis (TNM) staging system is used to determine patient prognosis; however, geographical inaccuracies frequently occur, affecting management. Objective To determine the additional relationship between factors discovered by searching for sociodemographic and metastasis factors, as well as treatment outcomes, which could help improve the prediction of the survival rate in cancer patients. Material and Methods. A total of 56 patients were recruited from the ambulatory clinic at the Hospital Universiti Sains Malaysia (USM). In this retrospective study, advanced computational statistical modeling techniques were used to evaluate data descriptions of several variables such as treatment, age, and distant metastasis. The R-Studio software and syntax were used to implement and test the hazard ratio. The statistics for each sample were calculated using a combination model that included methods such as bootstrap and multiple linear regression (MLR). Results The statistical strategy showed R demonstrates that regression modeling outperforms an R-squared. It demonstrated that when data is partitioned into a training and testing dataset, the hybrid model technique performs better at predicting the outcome. The variable validation was determined using the well-established bootstrap-integrated MLR technique. In this case, three variables are considered: age, treatment, and distant metastases. It is important to note that three things affect the hazard ratio: age (β1: -0.006423; p < 2e − 16), treatment (β2: -0.355389; p < 2e − 16), and distant metastasis (β3: -0.355389; p < 2e − 16). There is a 0.003469102 MSE for the linear model in this scenario. Conclusion In this study, a hybrid approach combining bootstrapping and multiple linear regression will be developed and extensively tested. The R syntax for this methodology was designed to ensure that the researcher completely understood the illustration. In this case, a hybrid model demonstrates how this critical conclusion enables us to better understand the utility and relative contribution of the hybrid method to the outcome. The statistical technique used in this study, R, demonstrates that regression modeling outperforms R-squared values of 0.9014 and 0.00882 for the predicted mean squared error, respectively. The conclusion of the study establishes the superiority of the hybrid model technique used in the study.
Total quality management: literature review and an agenda for future research

The past decade has seen many firms focusing on total quality management (TQM) as a means of improving profits, market share, and competitiveness. In this paper, an attempt is made to review the status of literature on TQM. The literature classification is done according to content and process issues of the article. Total of 153 articles from 55 refereed journals and international conferences are classified according to content (instrument, model, literature review, trans-national comparison, best practices, and economics) and process related issues of the articles. The methodology used in the literature is categorised into conceptual, descriptive, empirical, exploratory cross sectional, and exploratory longitudinal approaches. Considering all these aspects, some possible research issues are also identified.
Thick frequency selective surfaces

As an additional means of controlling bandwidth, the use of periodic screens in free space with thick metallization was investigated for single-square loop and double-concentric-square loop elements. These loops elements were chosen because the passbands of such screens, with tight lattice spacing, display a remarkable insensitivity to incident polarization and angle of incidence. The effect of thick metallization on passband width was investigated for both transmitted and reflected radiation. All results obtained are from a method of moments solution of the electric field integral equation. For FSS (frequency selective surface) screens with thick metallization, triangular patch basis functions were utilized to represent electric current on the surface of the three-dimensional unit cell structure. <<ETX>>
Evaluation of google translate in rendering English COVID-19 texts into Arabic

Machine Translation (MT) has the potential to provide instant translation in times of crisis. MT provides real solutions that can remove borders between people and COVID-19 information. The widespread of MT system makes it worthy of scrutinizing the capacity of the most prominent MT system, Google Translate, to deal with COVID-19 texts into Arabic. The study adopted (Costa et al., 2015a) framework in analysing the output of Google Translate output service in terms of orography, grammar, lexis, and semantics. The study's corpus was extracted from World Health Organization (WHO), United Nations Children's Emergency Fund (UNICEF), U.S. Food and Drug Administration (FDA), the Foreign, Commonwealth & Development Office (FCDO), and European Centre for Disease Prevention and Control (ECDC). The paper reveals that Google Translate committed a set of errors: Semantic, grammatical, lexical, and punctuation. Such errors inhibit the intelligibility of the translated texts. It also indicates that MT might work as an aid to translate general information about COVID-19, but it is still incapable of dealing with critical information about COVID-19. The paper concludes that MT can be an effective tool, but it can never replace human translators. © 2021 Selcuk University. All right reserved.
Building Change Detection for VHR Remote Sensing Images via Local–Global Pyramid Network and Cross-Task Transfer Learning Strategy

Building change detection (BCD) for very-high-spatial-resolution (VHR) remote sensing images is very important and challenging in the field of remote sensing, as the building is one of the most significant and valuable man-made ground targets. This article proposes a local–global pyramid network (LGPNet) that combines a local feature pyramid module (LFPM) and a global spatial pyramid module (GSPM) for various building feature extraction. The LFPM is constructed using the convolutional kernel with three different pyramid scales, and then, the local pyramid features are obtained by adding features of each scale. In the GSPM, the global spatial pyramid features are extracted by adaptive average pooling to acquire global contextual information from different fields of view on deep features. The LFPM and the GSPM work in a parallel and complementary manner to capture discriminative features of various buildings. In addition to the LFPM and the GSPM, the proposed LGPNet also employs two general attention mechanisms, i.e., the position attention module and the channel attention module, which can select and emphasize adaptively some building features with high semantic responses. Besides, in order to mitigate the influence of other ground targets to a certain extent, a cross-task transfer learning strategy is introduced to make the LGPNet focus on the building, which significantly improves the performance of our method. Extensive experiments on two public available BCD datasets show that the proposed LGPNet can achieve significant improvement compared with eight other state-of-the-art methods. The source code and the pretrained model will be released at https://github.com/TongfeiLiu/LGPNet.
Visual servoing for underwater docking of an autonomous underwater vehicle with one camera

Docking systems are required to increase the capability of autonomous underwater vehicles (AUVs) to recharge the batteries and to transmit data in real time in underwater. This paper presents a docking system for an AUV to dock into an underwater station with one camera installed at the nose center of the AUV. To make a visual servo controller, this paper presents an optimal control algorithm based on a state equation composed of the AUV dynamics and the optical flow equation. The control inputs of the AUV are generated with the projected target position on the CCD plane of the camera and with the AUVs motion. This paper introduces a test bed AUV for underwater docking developed in Korea Research Institute of Ships and Ocean Engineering (KRISO), KORDI of Korea. The AUV is propelled with one thruster and controlled with two horizontal planes and two vertical planes. Experiments will be performed in Ocean Engineering Basin of KRISO to demonstrate the effectiveness of the modeling and control law of the visual servoing AUV. The AUV identifies target position with processing the captured image of the lights mounted around the entrance of the dock. This paper also presents a strategy to identifier the target with lights arrays.
Débitmétrie : précision des stations de jaugeage

Les stations de jaugeage servent a elaborer les donnees de debits. Au cours de la chaine des operations qui aboutissent a l'edition d'un annuaire : mesure continue des hauteurs d'eau, mesure des debits instantanes a l'occasion de jaugeages intermittents, trace des courbes hauteur-debit, le dernier maillon est la source principale des incertitudes. On s'interroge sur la maniere de tracer la courbe et d'estimer la precision dans sa partie moyenne. Les problemes les plus consequents concernent les parties extremes et le suivi de la courbe face aux variations accidentelles ou saisonnieres des conditions d'ecoulement. Des jaugeages peu frequents peuvent conduire a des erreurs systematiques importantes temporaires sur la serie des debits.
3D small-scale object recognition network in cluttered point cloud scenes

This paper proposes a recognition network for small-scale objects in cluttered point clouds. The network consists of two components: improved semantic segmentation for large-scale 3D point clouds and an adaptive instantiation algorithm. In semantic segmentation, based on the backbone, we introduce the grid sampling module and the normal-angle feature to improve the efficiency and accuracy of segmentation respectively. Then the network outputs point-wise semantic labels. After that, we propose an adaptive instantiation algorithm to group points that are closely packed together and obtain the objects. In this way, our network completes the recognition of the small-scale objects. We conducted experiments on real aero-engine datasets and the results reveal that the proposed network can recognize a small-sized component in the cluttered point cloud scene of aero-engine.
Automated edge detection model for large irregular circular using a scanning approach

In this paper, an automated edge detection model is developed for large irregular circular using a laser scanning approach. Some key influencing factors, just like surface quality, surface orientation and scan depth, have been respectively considered in this model. By consider of the limited of field of view and corresponding optical constraints, only a small part of key region is effectively captured by laser scanner at a specific posture. In term of specified view angles of laser scanner, the position of laser scanner approximate to the stand-off distance with respect to edge area can be determined and then high-quality point clouds of large irregular circular edge feature can be effectively obtained. Finally, a series of experiments are performed on workpieces with different large irregular circular features. The experimental result shows our method features high automation and high efficiency. Those results are most promising for on-machine applications in dimensional measurement of large-scale workpiece.
Eliminating ghost images in high-range resolution profiles for stepped-frequency train of linear frequency modulation pulses

In modern radar systems, using stepped-frequency pulse train is an effective approach to achieve high-range resolution (HRR) with narrow instantaneous bandwidth and low system complexity. However, if the parameters of stepped-frequency (SF) radar (such as single pulse bandwidth, frequency step size and sampling instant) are not prudently designed, ‘ghost image’ phenomenon (also called range ambiguity in some literature) will corrupt the synthetic HRR profiles. The relationship between parameters of the SF radar and the ghost images is provided analytically. A new synthetic range profiling algorithm is developed to generate HRR profiles without ghost images by using the least-squares (LS) estimation. For targets with negligible radial velocities, the new LS profiling algorithm can eliminate the ghost images successfully, and introduces less signal-to-noise ratio loss. With this algorithm, the restriction on the frequency step size is less rigid than the traditional unambiguous criterion. Consequently, a higher range resolution could be obtained. Simulations and field experimental results are also presented.
Sensorless rotor position estimation of an interior permanent-magnet motor from initial states

This paper describes a torque, speed, or position control method at standstill and low speed in the interior permanent-magnet motor (IPMM) drive system without any rotational transducer. While IPMMs have originally magnetic saliency, it varies according to the load conditions and the control performance can be easily degraded. In this paper, the saliency or impedance difference is used as the conventional methods and, nevertheless, in order to amplify the difference containing the information of the rotor angle and to maintain a reasonable performance under any load condition a high-frequency injection scheme is proposed. A speed and position estimation scheme based on the characteristics of the high-frequency impedance is proposed. The scheme extracts the high-frequency impedance components related to the rotor position. An initial angle estimation scheme for starting from an arbitrary rotor position is also proposed. It can distinguish the north magnetic pole position from the south one in several decade milliseconds. The proposed scheme enables position control of a transducerless or position-sensorless IPMM. The experimental results clarify the satisfactory operation of the proposed position control algorithm under any load condition.
Self-oscillating electronic ballast analysis via relay systems approach

In this paper, the authors analyze the self-oscillating LC parallel resonant inverter for electronic ballast applications from a system point of view. It is observed that the self-oscillating parallel resonant inverter with lamp loads can be naturally modeled as a relay system with negative hysteresis. Based on this formulation, the self-oscillating frequencies of the circuit are found via the time-domain based Hamel locus. Also, the predicted self-oscillating frequencies via the describing function approach and the Hamel locus approach are compared with the prototype measurement results. It turned out that the accuracy of the frequency prediction via Hamel locus is high, while the accuracy via the describing function is circuit Q dependent.
Long-term reliability of transmission loss in optical fiber cables

Increased optical-fiber cable losses due to hydrogen are discussed. A mathematical model is developed to predict the growth of hydrogen concentration in the cable, which is determined by the evolution from organic cable materials and permeation through the cable sheath. This cable model, together with the measured parameters for the cable materials, explains the measured results. Design criteria for the allowable hydrogen evolution from cable materials and for the cable sheath structure are established on the basis of the model. >
Feature-based fixturing analysis for machining parts represented with multiple sets of features

In a feature-based model, a typical approach is to represent a part with a single set of features. However, in a part with feature interactions, there may exist multiple sets of features to represent the same part. The multiple sets of features represent different ways of machining the part. It is necessary to analyse and evaluate the various sets of features to measure their performance when using different machining methods. In a machining process, different fixturing parameters are required when different sets of features are used for machining. The purpose of this research is to determine a 'good' set of features that is more suitable from the fixturing point of view. A feature-based fixturing analysis method is developed based on the 3-2-1 and the 4-2-1 fixture design principles to analyse the supporting, locating, and clamping parameters. First, a set of fixturing parameters is determined for machining one set of machining features. Next, multiple sets of fixturing parameters are determined for the .
The Limpopo Magma‐Rich Transform Margin, South Mozambique: 1. Insights From Deep‐Structure Seismic Imaging

A variety of structures results from the interplay of evolving far‐field forces, plate kinematics, and magmatic activity during continental break‐up. The east Limpopo transform margin, offshore northern Mozambique, formed as Africa and Antarctica separated during the mid‐Jurassic period break‐up of the Gondwana supercontinent. The nature of the crust onshore has been discussed for decades in an effort to resolve issues with plate kinematic models. Two seismic refraction profiles with coincident multichannel seismic reflection profiles allow us to interpret the seismic velocity structures across the margin, both onshore and offshore. These seismic profiles allow us to (a) delineate the major regional crustal domains; (b) identify widespread indications of magmatic activity; and (c) map crustal structure and geometry of this magma‐rich transform margin. Careful examination of the profiles allows us to make the following observations and interpretations: (a) on land, continental crust is overlain by a >10‐km thick volcano‐sedimentary wedge related to an early rifting stage, (b) offshore, thick oceanic crust formed due to intense magmatic activity, and between the two (c) a 50–60‐km wide transform zone where the crustal structures are affected by intense magmatic activity and faulting. The prominent presence of intrusive and extrusive igneous units may be attributed to the combination of a deep‐seated melting anomaly and a trans‐tensional fault zone running through thinned lithosphere that allowed melt to reach the surface. A comparison of the crustal thinning along other transform margins shows a probable dependence with the thermal and/or tectonic history of the lithosphere.
From electronic photography to seeing chips-the future of image sensing

Thanks to the advances of semiconductor technology, solid state image sensors with impressive properties can be realized today: CCDs with 26 million pixels are commercially available. Pixel size has been reduced to 5/spl times/5 /spl mu/m/sup 2/ and less. This enables one to integrate electronic circuitry with each pixel, providing added functionality for custom photo-ASICs and smart image sensors: single-chip cameras with on-chip analog-to-digital converters for less than $20 are advertised; image sensors have been developed including novel functionality such as real-time selectable pixel size and shape, the capability of performing arbitrary convolutions simultaneously with the exposure, as well as variable, programmable sensitivity of the pixels leading to image sensors with a dynamic range exceeding 100 dB. It is concluded that the possibilities offered with custom smart image sensors will influence the design and the performance of future imaging systems in many disciplines, reaching from optical metrology to machine vision on the factory floor and in robotics applications.