Reviewerly/exHarmony huggingface dataset:
Short-Term Wind Energy Resource Prediction Using Weather Research Forecasting Model for a Location in Indonesia

This study presents the performance of the Weather Research and Forecasting (WRF) with the 5-km horizontal grid as a tool for wind energy forecasting within and along the Indonesian coast for the next 72 hours.The modeled data is then validated using wind measurements from the meteorological mast in East Sumba at several heights.Global Forecast System (GFS) operational forecasting data with a resolution of 0.25 degrees are used as the initial and boundary conditions (IC/BC) model.The findings demonstrate that wind speed and wind power density are much higher above ground level (50 m) than at ground level (10 m) and are significantly higher towards the shore than inland.The model slightly overpredicts low-level wind speeds.The results suggest that the WRF model is feasible for forecasting Indonesia's wind flow and wind energy.
Research Review under the Framework of Inquiry Community Theory

The framework of inquiry community theory provides a unique perspective, method and tool for online learning and blended learning research.Based on this, this paper first introduces the origin and connotation of inquiry community theory, then reviews the researches under the framework of inquiry community theory at home and abroad in recent years, and divides the researches under the framework into four categories, which are the researches focusing on the framework itself and the three components of the framework, aiming to provide reference for the researches under the framework.It is concluded that since the research under the framework of inquiry community was put forward at the beginning of the 21st century, more and more scholars have paid attention to this field, but there are still some problems such as insufficient research depth and insufficient local verification methods of domestic research.
Dynamic displacement monitoring by integrating high-rate GNSS and accelerometer: on the possibility of downsampling GNSS data at reference stations

Abstract We combine accelerometer and asynchronous high-rate GNSS data to retrieve dynamic displacements. The method adopts relative GNSS positioning with observations of different sampling rates at rover and reference stations. The objective is to examine the feasibility of downsampling GNSS data at reference stations and thus, verify whether permanent GNSS networks collecting low-rate observations can serve as reference sites. The performance is assessed using a shake table to induce displacement waveforms. We show that the combined GNSS and accelerometer solution improves displacement accuracy by half compared to the GNSS-only one. Further accuracy improvement is obtained by applying the Rauch Tung Striebel (RTS) smoother. Consequently, it is reasonable to downsample high-rate GNSS data at the reference station even to a 2 s interval and preserve the displacement error below 1 mm. The results also reveal that a fusion of GNSS with accelerometer and RTS smoothing helps to mitigate the ephemeris error. With the assessment in the time–frequency domain, we show that the combined solution better recovers displacement waveforms than GNSS-only. For the former solution, the detected peak frequencies agree very well with those of the Linear Variable Differential Transformer responsible for providing the ground truth displacements, and the amplitude error does not exceed 0.5 mm. We conclude that the proposed approach based on asynchronous GNSS observations provides millimeter-level precision results and is better for reconciling dynamic displacements than a GNSS-only solution or simply integrating accelerometer data.
Edukasi Kesehatan Mental Siswa Melalui Program Literasi Di Sekolah Kota Palopo

Have a sense of every student wants to be a teenager growing flowers complain to note whether it is at home, schools and had become friends environment, many factors of the problems they experience provided growth from the teenagers become adults both in attitudes and think, mental health education literacy through the school aims to assist students find talent writing them to develop itself through writing to be work they have passed at the school recalls when either junior high schools, and senior high school. The methodology conducted using descriptive by approach cross sectional study in two schools SMP 2 and SMA 6.The strength and weakness of (questionnaire-SDQ) used to detect 12-17 teen age years. In the 50 follow every classroom is a representative from OSIS and the head of the teacher. The results of the assistance that was carried out for 1 month showed that students' interests and talents could be elicited by involving collaboration with private parties who were holding a national book writing competition for the Nyalanesia team which then facilitated schools and students in the field of literacy so that they could explain in detail the results of students' writing to be published in the form of a book with an ISBN
Acquisition and annotation in high resolution in vivo digital biopsy by confocal microscopy for diagnosis in oral precancer and cancer

Introduction Scanned fibre endomicroscopes are full point-scanning confocal microscopes with submicron lateral resolution with an optical slice thickness thin enough to isolate individual cell layers, allow active positioning of the optical slice in the z-axis and collection of megapixel images. Here we present descriptive findings and a brief atlas of an acquisition and annotation protocol high resolution in vivo capture of oral mucosal pathology including oral squamous cell carcinoma and dysplasia using a fluorescence scanned fibre endomicroscope with 3 topical fluorescent imaging agents: fluorescein, acriflavine and PARPi-FL. Methods Digital biopsy was successfully performed via an acquisition protocol in seventy-one patients presenting for investigation of oral mucosal abnormalities using a miniaturized, handheld scanned fibre endoscope. Multiple imaging agents were utilized and multiple time points sampled. Fifty-nine patients had a matched histopathology correlating in location with imaging. The images were annotated back to macrographic location using a purpose-built software, MouthMap™. Results Acquisition and annotation of cellular level resolved images was demonstrated with all 3 topical agents. Descriptive observations between clinically or histologically normal oral mucosa showed regular intranuclear distance, a regular nuclear profile and fluorescent homogeneity. This was dependent on the intraoral location and type of epithelium being observed. Key features of malignancy were a loss of intranuclear distance, disordered nuclear clustering and irregular nuclear fluorescence intensity and size. Perinuclear fluorescent granules were seen in the absence of irregular nuclear features in lichenoid inflammation. Discussion High resolution oral biopsy allows for painless and rapid capture of multiple mucosal sites, resulting in more data points to increase diagnostic precision. High resolution digital micrographs can be easily compared serially across multiple time points utilizing an annotation software. In the present study we have demonstrated realization of a high-resolution digital biopsy protocol of the oral mucosa for utility in the diagnosis of oral cancer and precancer..
PHRkNN: Efficient and Privacy-Preserving Reverse kNN Query Over High-Dimensional Data in Cloud

Big data and bursting cloud computing technologies have facilitated an increasing trend of outsourcing data-driven services to the cloud, where the reverse kNN (RkNN) query is a popularly outsourced query service. The RkNN query aims to retrieve objects having the query object as kNN and widely applied in the product recommendation. Considering privacy concerns, the outsourced query services are demanded to protect data privacy, and consequently a series of privacy-preserving query solutions have been put forth. Nevertheless, RkNN query over high-dimensional data has not been studied to date. In this work, we design the first efficient and privacy-preserving RkNN query scheme over encrypted high-dimensional data, named PHRkNN. Specifically, we first introduce a pivot filter condition for the RkNN query and utilize it to deliberately design a pivot filter R-tree (PFR-tree) to organize the high-dimensional dataset such that the RkNN query has sublinear query efficiency. Then, we propose our PHRkNN scheme by designing some homomorphic encryption based private algorithms and applying them to privately achieve PFR-tree based RkNN query. After that, we propose an oblivious PHRkNN scheme on the basis of the PHRkNN scheme by designing a private random tree permutation (PRTP) algorithm to protect the access pattern privacy. The security of our PHRkNN scheme and oblivious PHRkNN scheme is proved by the simulation-based security analysis. The performance is verified through computational costs and communication overheads evaluation.
Research on the Training of College Physical Education Teachers from the Perspective of Career Development

The 21st century is a new era of human development.In the current context of the "knowledge economy", "teachers" have become the focus of global attention.In this new era, education will take on the historical mission of revitalizing China's economy, nation, and country, with the most important being teachers.From the perspective of career development, the quality and quantity of teachers play a decisive role in the education process of a nation, and university physical education teachers are an indispensable part of higher education.The improvement of their personal abilities and the enrichment of their professional knowledge will hinder the development of university physical education.Therefore, the cultivation of university physical education teachers is also receiving increasing attention.
WindowSHAP: An efficient framework for explaining time-series classifiers based on Shapley values

Unpacking and comprehending how black-box machine learning algorithms (such as deep learning models) make decisions has been a persistent challenge for researchers and end-users. Explaining time-series predictive models is useful for clinical applications with high stakes to understand the behavior of prediction models, e.g., to determine how different variables and time points influence the clinical outcome. However, existing approaches to explain such models are frequently unique to architectures and data where the features do not have a time-varying component. In this paper, we introduce WindowSHAP, a model-agnostic framework for explaining time-series classifiers using Shapley values. We intend for WindowSHAP to mitigate the computational complexity of calculating Shapley values for long time-series data as well as improve the quality of explanations. WindowSHAP is based on partitioning a sequence into time windows. Under this framework, we present three distinct algorithms of Stationary, Sliding and Dynamic WindowSHAP, each evaluated against baseline approaches, KernelSHAP and TimeSHAP, using perturbation and sequence analyses metrics. We applied our framework to clinical time-series data from both a specialized clinical domain (Traumatic Brain Injury - TBI) as well as a broad clinical domain (critical care medicine). The experimental results demonstrate that, based on the two quantitative metrics, our framework is superior at explaining clinical time-series classifiers, while also reducing the complexity of computations. We show that for time-series data with 120 time steps (hours), merging 10 adjacent time points can reduce the CPU time of WindowSHAP by 80 % compared to KernelSHAP. We also show that our Dynamic WindowSHAP algorithm focuses more on the most important time steps and provides more understandable explanations. As a result, WindowSHAP not only accelerates the calculation of Shapley values for time-series data, but also delivers more understandable explanations with higher quality.
Study on process mineralogical evaluation index system of hard rock lithium-beryllium-niobium-tantalum mineral resources

锂-铍-铌-钽是重要的关键金属矿产资源,其矿石矿物"稀"、"伴"和"细"的特征决定了一些锂、铍、铌、钽矿床在开采利用上有较大难度,需要加强工艺矿物学研究。除了品位和储量,还要考虑矿石的可选性指标,才能对矿床工业价值进行准确评价。本文在基于锂铍铌钽矿床成矿规律及典型矿床研究的基础上,尝试从工艺矿物学角度提出一套综合性评价锂-铍-铌-钽矿产资源的指标体系。具体内容包括矿床类型、矿石品位、主要工业矿物、主要矿物组成、主要目的组分的平衡配分、矿石结构构造,目的矿物工艺粒度、目的矿物嵌布特征、可综合利用矿物或伴生/共生组分、杂质元素/有害元素。通过矿床实例对不同类型锂-铍-铌-钽矿床的评价指标进行了简要评述,影响伟晶岩型、花岗岩锂矿和铍矿价值的主要矿物学指标是"主要工业矿物"和"主要目的组分的平衡配分"及"目的矿物工艺粒度",影响黏土型/沉积岩型锂矿价值的主要因素是锂的赋存状态,影响火山岩型铍矿价值的主要矿物学指标有"主要工业矿物"、"目的矿物的工艺粒度"和"目的矿物嵌布特征",影响碱性岩型和矽卡岩型铍矿价值的主要矿物学因素是"主要工业矿物"、"主要目的组分的平衡配分"和"目的矿物嵌布特征",影响伟晶岩型和花岗岩型铌钽矿的主要因素是"目的矿物工艺粒度",影响碳酸岩型和碱性岩型铌钽矿的主要因素是"主要工业矿物"和"目的矿物工艺粒度"。应用矿物学评价指标体系时应注意,对于不同类型的矿床,不同矿物学指标的权重有所不同,需要具体矿床具体分析。
Underwater Image Enhancement Based on Optimal Contrast and Attenuation Difference

The quality of underwater images is often marred by noticeable color casts and blurring, resulting from complex phenomena such as differential light attenuation based on wavelength, veiling light scattering, and light scattering by plankton and suspended particles in water. In this paper, we propose an effective underwater image enhancement method called Optimal Contrast and Attenuation Difference (OCAD) to tackle these issues. The OCAD method employs a two-step approach. First, it estimates a coarse transmission map by optimizing contrast and minimizing information loss during image mapping. This transmission map is then refined using a combination of dark channel prior and guided filter refining techniques to improve its accuracy. Second, OCAD estimates the veiling light by considering the differential attenuation of red, green, and blue light underwater. This estimated veiling light is utilized to partially mitigate the color cast caused by the attenuation effect, while also addressing the blurring based on an imaging model. To further enhance the image quality, we introduce the Gray World approach to correct the color and obtain a deblurred and color-corrected underwater image. To evaluate the performance of our proposed method, extensive experiments are conducted on well-established underwater image datasets, including the EUVP, UIEB, and RUIE datasets. Comparative analysis against state-of-the-art and classical underwater image enhancement methods reveals that our OCAD algorithm significantly enhances underwater images and outperforms other methods in terms of image quality improvement.
Measurement-device-independent nonlinear entanglement witnesses

Abstract Entanglement witnesses (EWs) are one of the most effective methods to detect entanglement. It is known that nonlinear EW provide better entanglement detection than their linear counterparts, in that the former detect a strictly larger subset of entangled states than the latter. Whether linear or nonlinear, the method is measurement-device dependent, so that imperfect measurements may cause false certification of entanglement in a shared state. Measurement-device-independent EW provide an escape from such measurement dependence of the entanglement detection for linear EW. Here we present measurement-device-independent nonlinear EW for non-positive partial transpose entangled states as well as for bound entangled states with positive partial transpose. Although the witness considered herein does not detect a larger set of entangled states than other nonlinear EW, it is more efficient in that it never leads to a false detection corresponding to wrong measurements. The constructed measurement-device-independent nonlinear EW certify the entanglement of the same sets of entangled states as their device-dependent parents do, and therefore are better than the linear EW, device-independent or otherwise.
Correlations and projective measurements in maximally entangled multipartite states

Multipartite quantum states constitute the key resource for quantum computation. The understanding of their internal structure is thus of great importance in the field of quantum information. This paper aims at examining the structure of multipartite maximally entangled pure states, using tools with a simple and intuitive physical meaning, namely, projective measurements and correlations. We first show how, in such states, a very simple relation arises between post-measurement expectation values and pre-measurement correlations. We then infer the consequences of this relation on the structure of the recently introduced entanglement metric, allowing us to provide an upper bound for the persistency of entanglement. The dependence of these features on the chosen measurement axis is underlined, and two simple optimization procedures are proposed, to find those maximizing the correlations. Finally, we apply our procedures onto some prototypical examples.
Information and communication technologies (ICT) access indicators in the LGBTQ+ population with a high risk of contagion by acquired immunodeficiency virus (HIV) in Honduras

In all societies, some populations are prioritized to be served by civil organizations and governments; access to technologies is typically left aside, especially in developing countries. The sample was for intentional contributions through the snowball method to reach 107 study participants. A survey-type instrument has been carried out where access, the use, and knowledge about convergent devices have been measured in a sample of individuals belonging to the lesbian, gay, bisexual, transgender, queer, and more (LGBTQ+) community. Basic statistics have been carried out to describe the frequencies of the sociodemographic variables and access to information and communication technologies (ICT). The LGBTQ+ community has access to convergent technologies, with a regular quality of service, with a preference for mobile devices and high daily use of them; there's an incongruence between income and spending on telecommunications services since it was perceived that this is a prioritized expense for all of them, even for those with the lowest economic income. The results of this study indicate that the LGBTQ+ community has significantly greater access to information technology and telecommunications services than the general population that hosts them; this study gives us a vision of how to offer technological solutions to prevent HIV in this community with a high incidence of this disease. Keywords: ICT; Digital divide; LGBTQ+; Convergency
Content-Adaptive Auto-Occlusion Network for Occluded Person Re-Identification

The occluded person re-identification (ReID) aims to match person images captured in severely occluded environments. Current occluded ReID works mostly rely on auxiliary models or employ a part-to-part matching strategy. However, these methods may be sub-optimal since the auxiliary models are constrained by occlusion scenes and the matching strategy will deteriorate when both query and gallery set contain occlusion. Some methods attempt to solve this problem by applying image occlusion augmentation (OA) and have shown great superiority in their effectiveness and lightness. But there are two defects that existed in the previous OA-based method: 1) The occlusion policy is fixed throughout the entire training and cannot be dynamically adjusted based on the current training status of the ReID network. 2) The position and area of the applied OA are completely random, without reference to the image content to choose the most suitable policy. To address these challenges, we propose a novel Content-Adaptive Auto-Occlusion Network (CAAO), that is able to dynamically select the proper occlusion region of an image based on its content and the current training status. Specifically, CAAO consists of two parts: the ReID network and the Auto-Occlusion Controller (AOC) module. AOC automatically generates the optimal OA policy based on the feature map extracted from the ReID network and applies occlusion on the images for ReID network training. An on-policy reinforcement learning based alternating training paradigm is proposed to iteratively update the ReID network and AOC module. Comprehensive experiments on occluded and holistic person ReID benchmarks demonstrate the superiority of CAAO.
Pictographic Representation of the Toki Pona Language for Use in Augmentative and Alternative Communication Systems

This article presents an analysis of the association of pictograms with a minimal expression communication language. This analysis has the purpose of determining if it is possible to build a data set that allows expressions in natural language based on concepts for use in augmentative and alternative communication systems. To carry out this activity, it is necessary to verify the degree of link between the set of pictograms that express concepts and the chosen minimal expression language, in this case, Toki Pona. The degree of linkage is determined using questionnaires on a target population, which makes it possible to validate whether there is indeed a direct association between the vocabulary and the grammar of Toki Pona, with respect to the concepts of the pictograms. This analysis opens up the opportunity to use the resource as an expression mechanism when using certain types of technologies, such as electroencephalographic (EEG) reading devices, which could be used to infer whether a person is thinking about a certain concept.
Employer-university cooperation: 1C interfaculty laboratory of I. N. Ulyanov Chuvash State University

The modernization of the national education creates a clear need for revision of the existing educational trajectories and close interaction between the employer and the educational institution in order to train highly qualified specialists. With all the variety of specialties and educational institutions in Russia, there is a shortage of professional staff. This trend is also typical for the IT sphere. Therefore, educational institutions need to cooperate not only with state institutions, but also with employers. The triple alliance “student — university — employer” is a stable platform for the development of young professionals. Basic departments and laboratories are created on the basis of higher education institutions through cooperation with potential employers.On March 17, 2022, there was a Strategic Partnership Agreement signed between I. N. Ulyanov Chuvash State University (ChuvSU), 1C Company and LLC “Leader Soft — Implementation Center”. The subject of this agreement was cooperation with the purpose of special training of the university students in the field of development, implementation and operation of software on the platform “1C:Enterprise” and “1C” products. Within the framework of the agreement 1C interfaculty core laboratory was created.This article explores the activities of 1C interfaculty core laboratory at ChuvSU for the year 2022. The innovative experience of partnership between the employing company and the educational institution, which will be in demand in other regions of the country, is presented on the example of creating a basic laboratory in the Chuvash university.