Miracle-dz/UniFAR-FTUs huggingface dataset:
Short-Term Load Forecasting Based on Improved TCN and DenseNet

With the grid-connected application of renewable energy sources such as wind and photovoltaic power, the nonlinearity and fluctuation of load data makes load forecasting more difficult than ever before. In order to extract the implicit relationship between multiple features and power load to construct a long-term sequence dependency, this paper proposes a short-term load forecasting based on improved temporal convolutional network (TCN) and densely connected convolutional network (DenseNet). Firstly, multiple features are reconstructed by using a fixed-length sliding window, and then the high-dimensional features reflecting the complex and non-stationary characteristics of power load are extracted by the DenseNet to construct a feature matrix. Secondly, we innovatively improve the TCN and introduce a parallel pooling into the traditional TCN to mine the features of time sequences. Finally, the self-attention mechanism (SAM) is used to further enhance the weight of key features to eliminate the influences of interference signals. Experiments were performed on Southern China and ISO-NE (New England) public datasets to verify the effectiveness and generalization of the proposed model. Compared with the traditional TCN, the mean average percentage error (MAPE) of the improved TCN on the two datasets decreases by 23.38% and 8.14%, respectively. Furthermore, when compared to the TCN-SAM hybrid model, the MAPE of the proposed model is significantly reduced by 42.41% and 26.89%, respectively.
Arabic Twitter Conversation Dataset about the COVID-19 Vaccine

The development and rollout of COVID-19 vaccination around the world offers hope for controlling the pandemic. People turned to social media such as Twitter seeking information or to voice their opinion. Therefore, mining such conversation can provide a rich source of data for different applications related to the COVID-19 vaccine. In this data article, we developed an Arabic Twitter dataset of 1.1 M Arabic posts regarding the COVID-19 vaccine. The dataset was streamed over one year, covering the period from January to December 2021. We considered a set of crawling keywords in the Arabic language related to the conversation about the vaccine. The dataset consists of seven databases that can be analyzed separately or merged for further analysis. The initial analysis depicts the embedded features within the posts, including hashtags, media, and the dynamic of replies and retweets. Further, the textual analysis reveals the most frequent words that can capture the trends of the discussions. The dataset was designed to facilitate research across different fields, such as social network analysis, information retrieval, health informatics, and social science.
Finite Searches, Chowla's Cosine Problem, and Large Newman Polynomials

A length $n$ cosine sum is an expression of the form $\cos a_1\theta + \cdots + \cos a_n\theta$ where $a_1 < \cdots < a_n$ are positive integers, and a length $n$ Newman polynomial is an expression of the form $z^{a_1} + \cdots + z^{a_n}$ where $a_1 < \cdots < a_n$ are nonnegative integers. We define $-\lambda(n)$ to be the largest minimum of a length $n$ cosine sum as $\{a_1,\ldots,a_n\}$ ranges over all sets of $n$ positive integers, and we define $\mu(n)$ to be the largest minimum modulus on the unit circle of a length $n$ Newman polynomial as $\{a_1,\ldots,a_n\}$ ranges over all sets of $n$ nonnegative integers. Since there are infinitely many possibilities for the $a_j$, it is not obvious how to compute $\lambda(n)$ or $\mu(n)$ for a given $n$ in finitely many steps. Campbell et al. found the value of $\mu(3)$ in 1983, and Goddard found the value of $\mu(4)$ in 1992. In this paper, we find the values of $\lambda(2)$ and $\lambda(3)$ and nontrivial bounds on $\mu(5)$. We also include further remarks on the seemingly difficult general task of reducing the computation of $\lambda(n)$ or $\mu(n)$ to a finite problem.
Exotic $\mathbb{R}^4$'s and positive isotropic curvature

We show that no exotic $\mathbb{R}^4$ admits a complete Riemannian metric with uniformly positive isotropic curvature and with bounded geometry. This is essentially a corollary of the main result in [Hu1], and was stated in [Hu2] without proof. In the process of the proof we also show that the diffeomorphism type of an infinite connected sum of some connected smooth $n$-manifolds ($n\geq 2$) according to a locally finite graph does not depend on the gluing maps used.
Numerical Modeling of Branching-Streamer Propagation in Ester-Based Insulating Oil Under Positive Lightning Impulse Voltage: Effects From Needle Curvature Radius

Ester-based insulating oil provides the possibilities for controlling pollutant emissions and enhancing transformer safeties. A 2-D needle-plate electrode branching-streamer model has been established to numerically investigate the propagation characteristics of initial streamer branches and the effects from needle radius in ester-based insulating oil under lightning impulse (LI) voltage. The results indicate that by adding the source term that affects charge carrier density variation to the current continuity equation, the revised model could better capture the branching-streamer morphology in the experiment than the existing model. The accumulation of positive ions in the streamer branches promotes the electric field distortion, introducing the maximum electric field at the head of the streamer branches, which causes the appearance of the branching streamer due to the localized charge carrier surge (CCS). The electric field at the needle zone is affected by the curvature radius, and the smaller curvature radius enhances the electric field, allowing more space charge to be generated, which leads to easier distortion of the electric field at the head of the streamer branches and promotes forward propagation of the streamer branches. In addition, the smaller curvature radius contributes to the generation of the secondary streamer.
Poincaré polynomials of character varieties, Macdonald polynomials and affine Springer fibers

We prove an explicit formula for the Poincar\'e polynomials of parabolic character varieties of Riemann surfaces with semisimple local monodromies, which was conjectured by Hausel, Letellier and Rodriguez-Villegas. Using an approach of Mozgovoy and Schiffmann the problem is reduced to counting pairs of a parabolic vector bundles and a nilpotent endomorphism of prescribed generic type. The generating function counting these pairs is shown to be a product of Macdonald polynomials and the function counting pairs without parabolic structure. The modified Macdonald polynomial $\tilde H_\lambda[X;q,t]$ is interpreted as a weighted count of points of the affine Springer fiber over the constant nilpotent matrix of type $\lambda$.
Remarks on an elliptic problem arising in weighted energy estimates for wave equations with space-dependent damping term in an exterior domain

This paper is concerned with weighted energy estimates and di usion phenomena for the initial-boundary problem of the wave equation with space-dependent damping term in an exterior domain. In this analysis, an elliptic problem was introduced by Todorova and Yordanov. This attempt was quite useful when the coeffcient of the damping term is radially symmetric. In this paper, by modifying their elliptic problem, we establish weighted energy estimates and di usion phenomena even when the coeffcient of the damping term is not radially symmetric.
Registered Nurses’ Experiences of End-of-Life Care in Nursing Homes of South Korea: A Qualitative Study

This study aimed to qualitatively describe how registered nurses (RNs) experienced and perceived end-of-life (EOL) care for older residents in South Korean nursing homes. The participants included 11 nurses with experience of providing EOL care for older residents in six nursing homes. Data were collected through one-on-one in-depth interviews using semi-structured questions from 27 December 2019 to 22 October 2020. Around 1–2 interviews were conducted for each participant, and each interview lasted between 40 min and two hours. The interview data were analyzed using qualitative content analysis. Eight sub-themes were identified and abstracted under three themes: (a) “feeling fulfilled for doing my best until the last day,” (b) “defensive coping due to legal and institutional limitations,” and (c) “requirements for effective EOL care. ” This study suggests that there are many challenges and issues regarding EOL care at nursing homes. In order to provide effective EOL care to older residents, the foundation of the EOL care system, as well as skills training, should be strengthened. Furthermore, securing qualified nursing manpower and achieving institutional improvement by reducing obstacles are warranted.
Moderate deviations for the range of a transient random walk: path concentration

We study downward deviations of the boundary of the range of a transient walk on the Euclidean lattice. We describe the optimal strategy adopted by the walk in order to shrink the boundary of its range. The technics we develop apply equally well to the range, and provide pathwise statements for the {\it Swiss cheese} picture of Bolthausen, van den Berg and den Hollander \cite{BBH}.
INVESTIGATING LOCAL ITEM INDEPENDENCE IN CIVIC EDUCATION MULTIPLE-CHOICE ITEMS OF JOINT MOCK EXAMINATION

In preparation for external examinations, Senior Secondary School II students write joint mock examinations in core subjects including civic education. The study examined into the authenticity of civic education test multiple-choice items. A post-hoc research design was used. The population included all public school senior secondary I, II, and III students, whereas the target population included 2020/21 SSS II students. The Kwara State Ministry of Education and Human Capital Development created a 50-item multiple-choice item for the research. At different stages of selection, stratified, proportionate, and simple random sampling techniques were used. Using tetrachoric correlation statistics, one research question was posed and answered. Based on the thumb rule of 0.3, 41 of 50 items favoured local item independence. Local item dependency should be taught as part of psychometric properties in undergraduate and postgraduate progra
Improvement of AMSR2 Soil Moisture Retrieval Using a Soil-Vegetation Temperature Decomposition Algorithm

It is well documented that soil moisture can be retrieved from passive microwave (PMW) observations. A basic assumption of most PMW-based SM retrieval algorithms is that vegetation temperatures (<inline-formula> <tex-math notation="LaTeX">$T_{v}$ </tex-math></inline-formula>) and soil temperatures (<inline-formula> <tex-math notation="LaTeX">$T_{s}$ </tex-math></inline-formula>) are equal (i.e., <inline-formula> <tex-math notation="LaTeX">$T_{v} = T_{s}$ </tex-math></inline-formula>), which however is not well satisfied in some cases, especially during daytime. In this study, we proposed a soil-vegetation temperature decomposition (SVTD) approach to avoid such an assumption, which can improve the accuracy of SM retrievals from the Advanced Microwave Scanning Radiometer 2 (AMSR2) data. First, the SVTD was used to decompose the vegetation and soil temperatures of the soil-vegetation mixed pixels in the Tibetan Plateau (TP). Subsequently, the decomposed temperature was integrated into the SM retrieval algorithm to correct the effects of soil and vegetation temperatures, and SM is then retrieved following the same strategy adopted in the land parameter retrieval model (LPRM). Finally, the algorithm was validated against densely instrumented SM networks (Maqu, Naqu, and Ngari) built in the TP and was also compared with the LPRM AMSR2 SM product. Results indicate that the proposed algorithm performs much better than the original LPRM in soil-vegetation mixed areas. The proposed SVTD method is promising for SM retrieval from PMW satellites, especially in the daytime when the difference between soil and vegetation temperatures is relatively large.
Minkowski Measurability Criteria for Compact Sets and Relative Fractal Drums in Euclidean Spaces

We establish a Minkowski measurability criterion for a large class of relative fractal drums (or, in short, RFDs), in Euclidean spaces of arbitrary dimension in terms of their complex dimensions, which are defined as the poles of their associated fractal zeta functions. Relative fractal drums represent a far-reaching generalization of bounded subsets of Euclidean spaces as well as of fractal strings studied extensively by the first author and his collaborators. In fact, the Minkowski measurability criterion established here is a generalization of the corresponding one obtained for fractal strings by the first author and M. \ van Frankenhuijsen. Similarly as in the case of fractal strings, the criterion established here is formulated in terms of the locations of the principal complex dimensions associated with the relative drum under consideration. These complex dimensions are defined as poles or, more generally, singularities of the corresponding distance (or tube) zeta function. We also reflect on the notion of gauge-Minkowski measurability of RFDs and establish several results connecting it to the nature and location of the complex dimensions. (This is especially useful when the underlying scaling does not follow a classic power law.) We illustrate our results and their applications by means of a number of interesting examples.
Multisite surveillance for influenza and other respiratory viruses in India: 2016–2018

There is limited surveillance and laboratory capacity for non-influenza respiratory viruses in India. We leveraged the influenza sentinel surveillance of India to detect other respiratory viruses among patients with acute respiratory infection. Six centers representing different geographic areas of India weekly enrolled a convenience sample of 5–10 patients with acute respiratory infection (ARI) and severe acute respiratory infection (SARI) between September 2016-December 2018. Staff collected nasal and throat specimens in viral transport medium and tested for influenza virus, respiratory syncytial virus (RSV), parainfluenza virus (PIV), human meta-pneumovirus (HMPV), adenovirus (AdV) and human rhinovirus (HRV) by reverse transcription polymerase chain reaction (RT-PCR). Phylogenetic analysis of influenza and RSV was done. We enrolled 16,338 including 8,947 ARI and 7,391 SARI cases during the study period. Median age was 14.6 years (IQR:4–32) in ARI cases and 13 years (IQR:1.3–55) in SARI cases. We detected respiratory viruses in 33.3% (2,981) of ARI and 33.4% (2,468) of SARI cases. Multiple viruses were co-detected in 2.8% (458/16,338) specimens. Among ARI cases influenza (15.4%) were the most frequently detected viruses followed by HRV (6.2%), RSV (5%), HMPV (3.4%), PIV (3.3%) and AdV (3.1%),. Similarly among SARI cases, influenza (12.7%) were most frequently detected followed by RSV (8.2%), HRV (6.1%), PIV (4%), HMPV (2.6%) and AdV (2.1%). Our study demonstrated the feasibility of expanding influenza surveillance systems for surveillance of other respiratory viruses in India. Influenza was the most detected virus among ARI and SARI cases.
Kähler metrics with constant weighted scalar curvature and weighted K‐stability

We introduce a notion of a Kähler metric with constant weighted scalar curvature on a compact Kähler manifold X , depending on a fixed real torus T in the reduced group of automorphisms of X , and two smooth (weight) functions v>0 and w , defined on the momentum image (with respect to a given Kähler class α on X ) of X in the dual Lie algebra of T .
“What a nasty girl!” incivility and gendered symbolic violence in news discussions

ABSTRACT This study examines conversations developed in the virtual public sphere to identify if a user’s gender affects the presence of incivility in news comment sections. By relying on a mixed-method analysis of 1,961 news comments published on a Chilean news website, we observed the extent to which uncivil speech and gendered symbolic violence traits are used to reinforce stereotypes against women. Our results show men are more likely to post uncivil comments, while women use fewer profanities, insulting language, and stereotypes. One of our most intriguing findings is that men tend to receive more uncivil replies that women, mostly because they are more likely to initiate uncivil conversations, which in turn triggers uncivil replies and increases the odds of uncivil comment threads. As such, news outlets looking for enhancing healthy discussions should encourage greater participation of female users in their comment sections. We also identified the presence of hegemonic masculinity discourses referring to women and their gender roles in society. These findings reveal that comment sections mirror a social hierarchy in which men have a position of power that allows them to be more uncivil. Consequently, the virtual public sphere replicates the dominant-subordinate relationships described by previous research.
STCN-Net: A Novel Multi-Feature Stream Fusion Visibility Estimation Approach

Low visibility always leads to serious traffic accidents worldwide, although extensive works are studied to deal with the estimation of visibility in meteorology areas, it is still a tough problem. Deep learning-based visibility estimation methods, it has low accuracy due to lacking “specific features” of the foggy images. Meanwhile, physical model-based visibility estimation methods are only applicable to some specific scenes due to its high requirements for extra auxiliary parameters. Therefore, This paper proposes a novel end-to-end framework named STCN-Net for visibility estimation, which combined the “engineered features” and “learned features” to achieve higher accuracy. Specifically, a novel 3D multi-feature stream Matrix, named DDT, is designed for visibility estimation, which is consisted of a transmittance matrix, a dark channel matrix, and a depth matrix. Unlike traditional deep learning methods which only use convolutional neural networks (CNN) to deal with the input data or images, our method combines CNN and Transformer to process the input data or images. In STCN-Net, Swin-Transformer(Swin-T) module takes the original image as input while the CNN module takes the DDT matrix as input. Moreover, in order to integrate different feature information from the CNN and Swin-T, we embed a Coordinate Attention (CA) module in STCN-Net. Finally, two visibility datasets: Visibility Image Dataset I (VID I) and Visibility Image Dataset II (VID II) were constructed for evaluation where VID I is a real scene visibility dataset and VID II is a synthetic visibility dataset. The experimental results show that our method has better performance than classical methods on the two datasets. And compared with the runner-up, it has 2.1% more accuracy in VID I and 0.5% in VID II.
A Survey on Output Feedback Control of Robot Manipulators with an Application to PHANToM 1.5A Haptic Device

This paper is aimed at presenting a short survey of velocity-free control schemes for robot manipulators. A salient feature of this work is the implementation of this control schemes on a simulation model of the 3-DOF industrial PHANToM 1.5 A robot. For both the regulation and tracking problems, two classes of control algorithms without velocity measurements are considered, namely, those based on observer-controller combination and those based on approximate derivation through an n-order filter. The latter was shown to be more advantageous from different aspects. First the controllers based on approximate derivation are very intuitive and easy to implement in practice. Moreover, these algorithms are proved to be globally asymptotically stable, while the observer-based controllers have only local stability results. We have also considered some algorithms that are robust to load disturbances and to unmodeled dynamics. Simulation results have confirmed the theoretical advantages and drawbacks of each algorithm.
Higher-Order Total Directional Variation. Part I: Imaging Applications

We introduce a new class of higher-order total directional variation regularizers. These regularizers extend the directional total variation for a constant direction \cite{directionaltv} to accommodate spatially-adaptive directions and higher-order derivatives. For the numerical solution of the resulting variational regularisation approach, we propose a primal-dual hybrid gradient approach whose details we report in the paper. We demonstrate that the proposed regulariser is able to preserve and enhance intrinsic anisotropic features in images by showing results for different imaging applications: image denoising, wavelet-based image zooming and reconstruction of surfaces from scattered height measurements.
An Efficient and Light Weight Deep Learning Model for Accurate Retinal Vessels Segmentation

Detecting eye diseases early can make a difference when trying to treat them. Existing diagnostic systems are not only prone to inaccurate judgments, but are also difficult and require a longer time from experts. Artificial intelligence (AI) based on deep learning (DL) has attracted global interest recently because of its effectiveness and accuracy in detecting eye diseases. There are several challenges in diagnosing eye diseases based on retinal fundus imaging. Most of the previous models in the literature targeted these challenges and tried to improve the evaluation metrics, whereas very little attention has been given to reducing the computational complexity of the developed model. The reduced computational complexity is highly desired, as the aim of developing an AI-enabled automated diagnostic system is to use for population-scale screening programs. This observation motivated us, and this work aimed to use a lightweight DL model based on ColonSegNet for retinal vessel segmentation. The performance of the model was assessed using three open-access fundus image datasets: DRIVE, CHASE_DB1, and STARE, and it achieved sensitivity, specificity, accuracy, AUC, and MCC performance of (0.8491, 0.9774, 0.9659, 0.9850, and 0.7960), (0.8607, 0.9806,0.9731, 0.9869, and 0.8014), and (0.8573, 0.9813, 0.9719, 0.9873, and 0.8069) respectively. Furthermore, the proposed method has five M trainable parameters, making it lightweight and capable of deployment on low-end hardware devices. These results outperform several lightweight and computationally heavy methods. The reduced number of parameters, computational complexity, and improved segmentation performance support its use in automated diagnostic systems for retinal vessel segmentation.
Torsion Freeness of Schur Modules

Let $R$ be a Noetherian commutative ring and $M$ an $R$-module with $\operatorname{pd_R} M\le 1$ that has rank. Necessary and sufficient conditions were provided by Lebelt for an exterior power $\wedge^k M$ to be torsion free. When $M$ is an ideal of $R$ similar necessary and sufficient conditions were provided by Tchernev for a symmetric power $S_k M$ to be torsion free. We extend these results to a broad class of Schur modules $L_{\lambda/\mu} M$. En route, for any map of finite free $R$ modules $\phi\: F\rightarrow G$ we also study the general structure of the Schur complexes $L_{\lambda/\mu}\phi$, and provide necessary and sufficient conditions for the acyclicity of any given $L_{\lambda/\mu}\phi$ by computing explicitly the radicals of the ideals of maximal minors of all its differentials.