Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy-Efficient Service-Aware Multi-Connectivity Scheduler for Uplink Multi-Layer Non-Terrestrial Networks

This paper introduces the concept of energy efficiency (EE) in the uplink with the capability of multi-connectivity (MC) in a multi-orbit non-terrestrial network (NTN), where user terminals (UTs) can be simultaneously served by more than one satellite to achieve higher peak throughput at reduced energy consumption. This concept also considers the service classification of the users, so that network dimensioning is performed in order to satisfy the quality of service (QoS) requirement of users. MC can increase throughput, but this entails increased power consumption at user terminal for uplink transmissions. To this end, an energy-efficient service-aware multi-connectivity (EE-SAMC) scheduling algorithm is developed in this paper to improve the EE of uplink communications. EE-SAMC uses available radio resources and propagation information to intelligently define a dynamic resource allocation pattern, that optimally routes traffic so as to reduce the energy consumption at the UT while ensuring QoS is maximized. EE-SAMC is designed based on the formulation of a non-convex combinatorial problem, it is solved in two ways involving firstly an optimization solution and secondly a heuristic approach. The effectiveness of EE-SAMC is compared with random allocation, round robin and heuristic schedulers in terms of EE, throughput and delay; EE-SAMC outperforms all schedulers.
An Acoustic Study on The Effects Intonation Imposes on Sentence-final Particles in Nanjing Dialect

To investigate the interaction between tone and intonation on the production of the sentence-final syllables and the effects of a specific type of characters, i.e. sentence-final particles (SFPs) in Nanjing dialect, acoustic analyses were carried out in the current study. Participants were asked to produce sentences under four conditions: (1) SFPs in interrogative sentences; (2) SFPs in declarative sentences; (3) homophones of the SFPs in interrogative sentences; (4) homophones of the SFPs in declarative sentences. The acoustic productions were analyzed in order to compare the same SFPs in different intonation patterns, i.e., interrogatives and declaratives, and SFPs and their homophones in the carrier sentences. Results showed that the influence of intonation on tones within sentence-final syllables indeed exists, but SFPs mitigate the extent to which intonation functions. These results suggest that intonation is present in tonal languages as well, whereas SFPs influence the realization of intonation by reducing the extent of global rising.
Machine Learning Predicts the Oxidative Stress Subtypes Provide an Innovative Insight into Colorectal Cancer

So far, it has been reached the academic consensus that the molecular subtypes are via genomic heterogeneity and immune infiltration patterns. Considering that oxidative stress (OS) is involved in tumorigenesis and prognosis prediction, we propose an innovative classification of colorectal cancer- (CRC-) OS subtypes. We obtain three datasets from The Cancer Genome Atlas Program (TCGA) and Gene Expression Omnibus (GEO) online databases. 1399 OS-related genes were selected from the GeneCards database. We remove the batch effect before conducting differentially expressed genes (DEGs) analyses between normal and tumor samples. Nonnegative matrix factorization (NMF) was used to perform an unsupervised cluster. Lasso regression and Cox regression were used to construct the signature model. DEGs, robust rank aggregation, and protein-protein interaction networks were used to select hub genes, and then use hub genes to predict OS subtypes by random forest algorithms. NMF identifies two OS-related subtypes of CRC patients. Eight OS-related gene signatures were built to predict the outcome of patients, based on the DEGs between two subtypes. A total of 61 DEGs overlap each dataset, and the RRA analysis shows that 17 genes are important in these three datasets, and 15 genes are shared genes between the two methods. PPI network suggests that five hub genes are confirmed, they are SPP1, SERPINE1, CAV1, PDGFRB, and PLAU. These five hub genes could predict the OS-related subtype of CRC accurately with AUC equal to 0.771. In our study, we identify two OS-related subtypes, which will provide an innovative insight into colorectal cancer.
Reciprocity for electromagnetic–acoustic fields in compressible magnetoplasmas with anisotropic pressure

Maxwell's curl equations and the linearized balance equations for momentum and pressure tensor for a plasma in an external magnetic field are combined in a system of first-order partial differential equations for the field quantities. With the corresponding adjoint system, the Lagrange identity is established, leading to a symmetry relation between the Green functions for the original and the adjoint fields. With temporal mapping the adjoint field can be transformed into a ‘Lorentz-adjoint’ (physical) field, leading to a reciprocity relation between the Green functions for the original and for the Lorentz-adjoint fields.
Source use in research articles in second language writing: A state-of-the-art review

Abstract This review aims to outline topics of interest and methodological approaches of empirical studies on source-use research from 2000 to 2020. The following research foci are identified: (1) the source misuse from the perspective of concept dimension; (2) the rhetorical strategy; (3) the source-use skill; and (4) the assessment from the perspective of the sentence and discourse dimension, indicating that studies on source use are from the rhetorical perspective of texts to interpersonal functions of texts and then cognitive processes of writers. Then, the frequently used research methodologies were the qualitative approach and mixed methods. Our review further discussed three central themes for future research: (1) the comparative and longitudinal study; (2) the assessment; and (3) the local development of source use, e.g. the continuation task in China. Methodological directions were also pointed out for future source-use studies.
Multiphysics Modeling of Liver Tumor Ablation by High Intensity Focused Ultrasound

High intensity focused ultrasound is a rapidly developing technology for the ablation of tumors. Liver cancer is one of the most common malignancies worldwide. Since liver has a large number of blood vessels, blood flow cooling can reduce the necrosed volume and may cause regeneration of the tumor to occur. All cancer cells should be ablated without damaging of the critical tissues. Today, treatment planning tools consider liver as a homogeneous organ. This paper is a step towards the development of surgical planning platform for a non-invasive HIFU tumor ablative therapy in a real liver geometry based on CT/MRI image. This task requires coupling of different physical fields: acoustic, thermal and hydrodynamic. These physical fields can influence each other. In this paper we illustrate how a computational model can be used to improve the treatment efficiency. In large blood vessel both convective cooling and acoustic streaming can change the temperature considerably near blood vessel. The whole tumor ablation took only 30 seconds in the considered simulation case, which is very small comparing with the current treatment time of several hours. Through this study we are convinced that high ultrasound power and nonlinear propagation effects with appropriate treatment planning can sufficiently reduce the treatment time.
MRI Characteristics and Alterations in Patellar Height in Patients with Patellar Tendinopathy—A Retrospective Study

(1) Background: Patellar tendinopathy (PT) is an overuse condition of the knee extensor mechanism characterized by ventral knee pain at the lower pole of the patella and limited functionality. (2) Methods: In this retrospective study, a group of patients with PT (n = 41) was compared with a control group (n = 50) in terms of patient-related data and magnetic resonance imaging (MRI) characteristics. (3) Results: Patellar height was higher in the PT patient group and there was a significant difference in Caton–Deschamps index (CD) compared to the control group (p = 0.021). Patients with PT showed a lower patella–patellar tendon angle (PPTA) (p = 0.011). The patellar tendon thickness (PTT) in the proximal (PTTprox), middle (PTTmid) and distal (PTTdistal) part of the tendon was significantly thickened (p < 0.001). Increased signal intensity in MRI was detected in symptomatic tendons over 6 months compared to a duration of less than 6 months (p = 0.025). A significant relationship between the PTTprox and an increased signal intensity was observed (p < 0.001). (4) Conclusions: Patients with PT showed a significant difference in the patellar height and PPTA. With persistence of symptoms over 6 months, MRI seems suitable to detect the morphologic tendon changes and further identify patients suitable for surgical procedures.
Rapid stress-testing vs. long-term aging: a case study of 980-nm emitting single-spatial mode lasers

The degradation behaviors of 980-nm emitting nominally identical single-spatial mode lasers are studied during continuous wave long-term operation and during single-pulse stress tests. Both tests activate internal catastrophic optical damage as sudden degradation mechanism limiting the device lifetime. In case of high power stress-testing, the mechanism that initializes this effect is a spatial widening of the optical mode, resulting in increased absorption outside the waveguide. A similar disturbance to the optical mode is caused by defects that are generated during long-term operation. Thus two very different aging regimes eventually result in the same degradation scenario. We find that single-pulse stress-testing allows for activation of several degradation mechanisms in a device one after the other. Moreover, it becomes possible to distinguish between effects induced by gradual degradation and such that are independent on operation time. Thus stress-testing is considered a complementary tool, which might pave the way towards more economic device testing.
Genetic algorithms in seismic waveform inversion

SUMMARY Recently a new class of methods, to solve non-linear optimization problems, has generated considerable interest in the field of Artificial Intelligence. These methods, known as genetic algorithms, are able to solve highly non-linear and non-local optimization problems and belong to the class of global optimization techniques, which includes Monte Carlo and Simulated Annealing methods. Unlike local techniques, such as damped least squares or conjugate gradients, genetic algorithms avoid all use of curvature information on the objective function. This means that they do not require any derivative information and therefore one can use any type of misfit function equally well. Most iterative methods work with a single model and find improvements by perturbing it in some fashion. Genetic algorithms, however, work with a group of models simultaneously and use stochastic processes to guide the search for an optimal solution. Both Simulated Annealing and genetic algorithms are modelled on natural optimization systems. Simulated Annealing uses an analogy with thermodynamics; genetic algorithms have an analogy with biological evolution. This evolution leads to an efficient exchange of information between all models encountered, and allows the algorithm to rapidly assimilate and exploit the information gained to find better data fitting models. To illustrate the power of genetic algorithms compared to Monte Carlo, we consider a simple multidimensional quadratic optimization problem and show that its relative efficiency increases dramatically as the number of unknowns is increased. As an example of their use in a geophysical problem with real data we consider the non-linear inversion of marine seismic refraction waveforms. The results show that genetic algorithms are inherently superior to random search techniques and can also perform better than iterative matrix inversion which requires a good starting model. This is primarily because genetic algorithms are able to combine both local and global search mechanisms into a single efficient method. Since many forward and inverse problems involve solving an optimization problem, we expect that the genetic approach will find applications in many other geophysical problems; these include seismic ray tracing, earthquake location, non-linear data fitting and, possibly seismic tomography.
Identification of ischemia-causing lesions using coronary plaque quantification and changes in fractional flow reserve derived from computed tomography across the lesion

Background This study sought to evaluate the association between coronary plaque characteristics, changes in the fractional flow reserve (FFR) derived from computed tomography across the lesion (ΔFFRCT), and lesion-specific ischemia using the FFR in patients with suspected or known coronary artery disease. Methods The study assessed coronary computed tomography (CT) angiography stenosis, plaque characteristics, ΔFFRCT, and FFR in 164 vessels of 144 patients. Obstructive stenosis was defined as stenosis ≥50%. An area under the receiver -operating characteristics curve (AUC) analysis was conducted to define the optimal thresholds for ΔFFRCT and the plaque variables. Ischemia was defined as a FFR of ≤0.80. Results The optimal cut-off value of ΔFFRCT was 0.14. Low-attenuation plaque (LAP) ≥76.23 mm3 and a percentage aggregate plaque volume (%APV) ≥28.91% can be used to predict ischemia independent of other plaque characteristics. The addition of LAP ≥76.23 mm3 and %APV ≥28.91% improved the discrimination (AUC, 0.742 vs. 0.649, P=0.001) and reclassification abilities [category-free net reclassification index (NRI), 0.339, P=0.027; relative integrated discrimination improvement (IDI) index, 0.093, P<0.001] of the assessments compared to the stenosis evaluation alone, and the addition of information about ΔFFRCT ≥0.14 further increased the discrimination (AUC, 0.828 vs. 0.742, P=0.004) and reclassification abilities (NRI, 1.029, P<0.001; relative IDI, 0.140, P<0.001) of the assessments. Conclusions The addition of the plaque assessment and ΔFFRCT to the stenosis assessments improved the identification of ischemia compared to the stenosis assessment alone.
Smart Diet Diary: Real-Time Mobile Application for Food Recognition

Growing obesity has been a worldwide issue for several decades. This is the outcome of common nutritional disorders which results in obese individuals who are prone to many diseases. Managing diet while simultaneously dealing with the obligations of a working adult can be difficult. This paper presents the design and development of a smartphone-based diet-tracking application, Smart Diet Diary, to assist obese people as well as patients to manage their dietary intake for a healthier life. The proposed system uses deep learning to recognize a food item and calculate its nutritional value in terms of calorie count. The dataset used comprises 16,000 images of food items belonging to 14 different categories to train a multi-label classifier. We applied a pre-trained faster R-CNN model for classification and achieved an overall accuracy of approximately 80.1% and an average calorie computation within 10% of the real calorie value.
Detection of Copy-Move Forgery using Haar- like features

Copy-move forgery is a specific type of image tampering where a part of the image is copied and pasted on another part generally to conceal unwanted portions of the image. Hence, the goal in detection of copy-move forgeries is to detect image areas that are same or extremely similar. This paper describes a method for robust and accurate copy-move forgery detection by employing Haar-like features on the integral image. By applying Haar-like filters to n×n overlapping blocks of the integral image instead of input image, time needed for the detection process is reduced. Experimental results show that the proposed scheme accurately detects such specific image manipulations although the copied region are rotated and it’s complexity time is very small compared to approaches base on overlap blocking.
Impact of Pre-Storage Melatonin Application on the Standard, Sensory, and Bioactive Quality of Early Sweet Cherry

Melatonin (N-acetyl-5-methoxytryptamine) is involved in multiple functions in plants. However, its role in some metabolic pathways and exogenous application’s effect on fruits is still unclear. Furthermore, the effects of pre-storage melatonin treatment on sensory traits and consumer acceptance of cherries have yet to be studied. For this reason, the early sweet cherry cultivar ‘Samba’ harvested at the commercial ripening stage was treated with different melatonin concentrations (0.1, 0.3, and 0.5 mmol L−1) and stored for 21 days under controlled cold temperature and humidity. The standard quality, respiration rate, postharvest aptitude, sensory quality, phenols, and antioxidant systems (non-enzymatic and enzymatic) were analysed at 14 and 21 days of storage. Postharvest treatment with melatonin 0.5 mmol L−1 improved firmness and reduced weight loss and non-commercial fruit percentage while increasing respiration rate, lipophilic antioxidant activity, and ascorbate peroxidase enzyme activity. Furthermore, the treated cherries showed better sensory qualities, such as uniformity of colour and skin colour, as well as being sourer and showing better consumer acceptance and liking after 14 days of storage. Therefore, we conclude that the 0.5 mmol L−1 concentration is effective on the standard, sensory, and bioactive quality of early sweet cherries and can be considered an eco-friendly tool for maintaining the postharvest quality of early cherries.
Empathy or Counter-Empathy? The Victims’ Empathic Response Toward Offenders Depends on Their Relationships and Transgression Severity

Introduction Empathy facilitates prosocial behaviors, whereas counter-empathy harms others. The question that remains unanswered is: when and for whom do people show different empathic responses? This study aimed to explore the effects of transgression severity and interpersonal relationships on victims’ empathy or counter-empathy toward an offender. Methods Before and after experiencing a slight or serious transgression, 42 college students were asked to imagine that they had different relationships (ie, intimate, strange, or bad) with a person and then report their empathy or counter-empathy toward that person from cognitive and affective aspects. Results The results showed that, in the affective aspect, the participants’ empathy for the intimate friend decreased after a slight transgression and even disappeared after a serious transgression. For strangers, empathy transformed into counter-empathy after the transgression, and its intensity increased with the transgression’s severity. For a person in a bad relationship, the participants felt counter-empathy before the transgression, and its intensity increased with the transgression’s severity. In the cognitive aspect, participants’ counter-empathy toward the stranger and the person in a bad relationship increased with transgression severity. Discussion These results suggest that interpersonal relationships and transgression severity can change the type and degree of a victim’s empathy toward the offender. Our findings not only deepen our understanding of the cognitive aspect of counter-empathy but also provide insights for handling interpersonal conflict.
Research on Improving the Shielding Effect of Stacked Superconducting Bulks Based on Increasing the Gap Reluctance

Superconducting bulk has great advantages in shielding magnetic fields owing to its high critical current density. Since the shielded area is usually larger than the size of a single bulk, superconducting bulks need to be stacked together to form a shielding layer. However, bulks stacked together can cause the magnetic flux to concentrate at the gaps between bulks. In order to increase the shielding effect, multiple shielding layers are usually required. This increases the shielding cost. In this article, a shielding structure that makes an angle between gap and external field nonparallel is explored. This structure can increase the gap reluctance and reduce the magnetic flux leakage, which provides a method to get a uniform shielding area in a relatively economical way. The shielding effects are studied by experiment and finite element calculation. The established simulation model can be used to further explore and optimize new shielding structures.
Global robust output regulation of multivariable systems with nonlinear exosystem

It is well known that multi‐input, multi‐output nature of nonlinear system and generalized exosystem have posed some challenges to output regulation theory. Recently, the global robust output regulation problem for a class of multivariable nonlinear system subject to a linear neutrally stable exosystem has been studied. It has been shown that a linear internal model‐based state feedback control law can lead to the solution of previous problem. In this paper, we will further study the global robust output regulation problem of the system subject to a nonlinear exosystem. By utilizing nonlinear internal model design and decomposing the multi‐input control problem into several single‐input control problems, we will solve the problem by recursive control law design. The theoretical result is applied to the non‐harmonic load torque disturbance rejection problem of a surface‐mounted permanent magnet synchronous motor. Copyright © 2016 John Wiley & Sons, Ltd.
An Evaluation and Validation of the Discover Wellness Worksite Health Promotion Program Across Three Locations Web Appendix

Aligned with their mission and strategies, many organizations strive to make positive societal contributions, including employee behavior change strategies that promote wellness and stress management skills. Such programs are paramount among employees that experience extraordinary challenges due to COVID-19 and communities severely impacted by high rates of heart disease, stroke, and obesity. We therefore describe “ Discover Wellness '', a health promotion intervention to improve health behaviors in teachers and staff employees at three New York locations. The intervention, a collaborative effort between two academia and one community field location, aimed to promote healthy behaviors. A mixed methods approach was used to evaluate the program. Employees that participated in Discover Well-ness reported significant increases for all four areas of interest: managing stress, improved nutrition, more physical activity, and better sleep. Lessons learned and future research are addressed.
An Approach to Surface Region Decomposition for CAD Models

Surface region decomposition of 3D models is important for shape analysis,especially local shape analysis.Traditional region decomposition methods are mostly based on mesh models not general CAD models in mechanical engineering.So,a surface region decomposition method is proposed for CAD models with boundary representations,with which the surface boundary of a solid model is divided into local convex,concave and planar regions with the minimal number.To achieve high computation efficiency,a two-pass decomposition approach is used.First,based on the classification of faces according to their local convexity,a surface boundary is initially divided into convex,concave and planar regions.Then,the decomposed regions are recursively combined to form the optimal region decomposition.Experimental results show that this approach can effectively decompose the surface boundary of CAD models.