Miracle-dz/UniFAR-FTUs huggingface dataset:
Configuration Optimization and Distributed Formation Control for Tethered Multirotor UAS

This article improves the robustness of tethered multirotor unmanned aircraft systems (UASs) through configuration optimization and controller design. Capacity margin and stiffness matrix are defined to measure the robustness of the system. The relationship between capacity margin and system configuration is analyzed based on a new optimization method. Moreover, the mathematical expression of system stiffness matrix argument with configuration is derived. Based on these two relations, the optimal configuration is determined to strengthen the robustness of the system. Under composite disturbances, it is not trivial to maintain the designed optimal configuration. Thus, a disturbance observer (DO) is developed to eliminate the disturbance generated by the tension force, which is a constant or harmonic signal. In addition, a fixed-time extended state observer (FTESO) is designed to mitigate the external aerodynamic force acting on the UAS. Accordingly, a distributed formation control algorithm based on the designed DO and FTESO is constructed for formation tracking control. Finally, the indoor experiments are demonstrated to validate the proposed strategy.
Increasing synchrony opposes stabilizing effects of species richness on terrestrial communities

Ecological theory has predicted that species richness should stabilize communities, with mechanisms including species synchrony and population variability determining the net impacts. While these theories have been supported empirically, results can be sensitive to taxonomic bias as studies are often focussed on plants. Trophic differences between consumers and primary producers can lead to varying stabilizing effects of species richness. Here, we compared the impact of species richness on community variability in four taxonomic groups: terrestrial birds, mammals, invertebrates and plants.
White racial ignorance and refusing culpability: how the emotionalities of whiteness ignore race in teacher education

ABSTRACT This article builds on Charles W. Mills’ foundational concept of white racial ignorance to expand his work by exploring the inner dynamics and practices of teacher education (its rationales, student teaching, practicums, pedagogies, curriculum) and explaining how the emotionalities of whiteness play a significant role in the ways that whiteness persists perniciously in teacher education. In order to hold whiteness accountable and culpable, it is argued that teacher education needs to stop emotionally deflecting anti-racist critiques by over pontificating their lackluster commitments to race, a practice which only ignores, and diverts attention away from the hegemonic presence of whiteness. It suggests that teacher educators need to help pre-service and in-service teachers be attentive to how racial politics are felt, acted upon, and reproduced, and how emotionalities of whiteness become ‘ordinary’ in everyday life in schools. The article concludes by outlining some implications for research and theory in critical whiteness studies.
Analytic Methods in Applied Probability: In Memory of Fridrikh Karpelevich

Karpelevich's contribution to applied probability by A. Ya. Kreinin and Y. Suhov A note on an $M/G/1$ queue with a waiting server, timer, and vacations by O. J. Boxma, S. Schlegel, and U. Yechiali Asymptotics for the maximum of a modulated random walk with heavy-tailed increments by S. Foss and S. Zachary Stochastic networks and activity analysis by J. M. Harrison Stability bounds for queueing models in terms of weighted metrics by V. Kalashnikov Context-free evolution of words by F. I. Karpelevich, V. A. Malyshev, A. I. Petrov, S. A. Pirogov, and A. N. Rybko The maximum of a tree-indexed random process, with applications by M. Kelbert, S. Rachev, and Y. Suhov Stochastic bounds for fast Jackson networks by J. Martin Markov chains in a wedge with excitable boundaries by M. Menshikov and D. Petritis Selecting the shortest of two queues, improved by M. Mitzenmacher and B. Vocking Stability of global LIFO networks by A. N. Rybko, A. L. Stolyar, and Y. M. Suhov Scheduling for multiple flows sharing a time-varying channel: The exponential rule by S. Shakkottai and A. L. Stolyar New ratio limit theorems for Markov chains by M. G. Shur Stability of patchwork-JSQ feedback networks by E. J. Thomas.
The effect of central sensitization on disease activity measures, quality of life and clinical parameters in axial spondyloarthritis: a cross-sectional study

Objective Despite biological drug therapy, pain remains a persistent complaint in patients with axial spondyloarthritis (axSpA). We aimed to investigate the effect of central sensitization (CS) on disease activity measures, quality of life, and clinical parameters in axSpA patients. Methods We consecutively recruited axSpA patients who were followed up at our rheumatology outpatient clinic, and age- and sex-matched controls in this cross-sectional study. The central sensitization inventory, douleur neuropathique 4 (DN4) questions, and 2010 American College of Rheumatology fibromyalgia (FM) diagnostic criteria were applied to all individuals. The patients’ clinical parameters were recorded. The data of the patient and control groups were compared. Results Of the 116 axSpA patients (57 female) and 95 controls (46 female) who participated in this study, CS was determined in 46.6% of axSpA patients and 13.7% of controls (p<0.001). Patients with CS exhibited high disease activity, and poor quality of life and functionality than without it (all p<0.001). The median CS, frequency of FM and frequency of neuropathic pain were higher in patients than in the controls (all p<0.001). CS-related conditions, including anxiety and depression, were higher in axSpA patients than in controls (both p<0.05). Conclusion The results showed that CS was common in axSpA patients, and patients with CS had higher disease activity, worse quality of life, and worse functional status than those without CS.
Modified invariant colour model for shadow detection

High-resolution satellite images usually contain a significant amount of shadow cast by elevated objects. Image information is affected by such shadows. Shadows obscure image information partially and/or totally, which leads to interpretation errors. This article aims to develop a complete shadow detection approach using all available bands of a multispectral image. Therefore, the near-infrared band is employed in addition to visible bands while generating a C1C2C3 colour model to achieve a modified C3 index. A comparative study is then applied to the original C1C2C3, hue, saturation, and value colour model and the modified model, to validate the developed index. The results show the superiority of the proposed approach in shadow detection, with overall accuracy around 94%.
Buckled graphene-like materials in ultrashort and strong optical fields

This paper investigates the interaction of buckled Dirac materials (silicene and germanene) with ultrashort and ultrastrong optical pulses. Highly intensive few-cycle pulses strongly modify the electronic and optical properties of these two dimensional materials. Electron dynamics in such a short optical pulse is coherent and can be robustly controlled by altering the propagation direction, as well as the polarization angle of the pulse. The strong nonlinearity of the system for fields applied (~ V/Å) causes the violation of the charge (C) and parity (P) symmetries, effectively reducing the system’s symmetry from hexagonal to triangular. Such symmetry violations are related to the electron transfer between the sublattices caused by the normal field component and result in nonreciprocity, optical rectification and the appearance of a cross current.
A divide-and-conquer machine learning approach for modeling turbulent flows

In this paper, a novel zonal machine learning (ML) approach for Reynolds-averaged Navier–Stokes (RANS) turbulence modeling based on the divide-and-conquer technique is introduced. This approach involves partitioning the flow domain into regions of flow physics called zones, training one ML model in each zone, then validating and testing them on their respective zones. The approach was demonstrated with the tensor basis neural network (TBNN) and another neural net called the turbulent kinetic energy neural network (TKENN). These were used to predict Reynolds stress anisotropy and turbulent kinetic energy, respectively, in test cases of flow over a solid block, which contain regions of different flow physics including separated flows. The results show that the combined predictions given by the zonal TBNNs and TKENNs were significantly more accurate than their corresponding standard non-zonal models. Most notably, shear anisotropy component in the test cases was predicted at least 20% and 55% more accurately on average by the zonal TBNNs compared to the non-zonal TBNN and RANS, respectively. The Reynolds stress constructed with the zonal predictions was also found to be at least 23% more accurate than those obtained with the non-zonal approach and 30% more accurate than the Reynolds stress predicted by RANS on average. These improvements were attributed to the shape of the zones enabling the zonal models to become highly locally optimized at predicting the output.
Improved Embedding for Prediction-Based

This paper aims at reducing the embedding distortion of prediction error expansion reversible watermarking. Instead of embedding the entire expanded difference into the current pixel, the difference is split between the current pixel and its prediction context. The modification of the context generates an increase of the following prediction errors. Global optimization is obtained by tuning the amount of data embedded into context pixels. Predic- tion error expansion reversible watermarking schemes based on median edge detector (MED), gradient-adjusted predictor (GAP), and a simplified GAP version, SGAP, are investigated. Improve- ments are obtained for all the predictors. Notably good results are obtained for SGAP-based schemes. The improved SGAP appears to outperform GAP-based reversible watermarking. Index Terms—Gradient-adjusted predictor (GAP), improved embedding, median edge detector (MED), prediction error expan- sion, reversible watermarking, simplified GAP (SGAP).
Strongly order continuity and pseudo-S-property of generalized fuzzy valued Choquet integrals

In general fuzzy measure spaces,aimed at giving generalized fuzzy valued Choquet integrals,these kind of integrals were completely regarded as a set function taken fuzzy numbers in measurable spaces.Then,when the fuzzy measure satisfied the strongly order continuity and pseudo-S-property,the heredity of the fuzzy valued Choquet integrals was researched.
AN IMPROVED MAPPING METHOD OF MULTISATELLITE ALTIMETER DATA

Abstract Objective analysis of altimetric data (sea level anomaly) usually assumes that measurement errors are well represented by a white noise, though there are long-wavelength errors that are correlated over thousands of kilometers along the satellite tracks. These errors are typically 3 cm rms for TOPEX/Poseidon (T/P), which is not negligible in low-energy regions. Analyzing maps produced by conventional objective analysis thus reveals residual long-wavelength errors in the form of tracks on the maps. These errors induce sea level gradients perpendicular to the track and, therefore, high geostrophic velocities that can obscure ocean features. To overcome this problem, an improved objective analysis method that takes into account along-track correlated errors is developed. A specific data selection is used to allow an efficient correction of long-wavelength errors while estimating the oceanic signal. The influence of data selection is analyzed, and the method is first tested with simulated data. The me.
What Do We Know About Balanced Scorecard and Its Benefit? A Systematic Literature Review

This study aims to systematize articles on Balanced Scorecard (BSC) and the benefit of its adoption in various organizations and business entities. Using a systematic literature review, this study reviews 60 articles published in international reputable journals between 2003 and 2022. The articles were found using keywords such as ‘balanced scorecard’, ‘BSC’, and ‘BSC implementation’ in the Emerald, Elsevier, Sage Journals, and Scopus databases. The search was restricted by the language and scope of the research. The results show that BSC facilitates the improvement of organization performance, the achievement of organizational goals and vision, the outlining of strategies into action, the measurement of performance, the management of risk and the decision-making process.
TransCP: A Transformer Pointer Network for Generic Entity Description Generation With Explicit Content-Planning

We study neural data-to-text generation to generate a sentence to describe a target entity based on its attributes. Specifically, we address two problems of the encoder-decoder framework for data-to-text generation: i) how to encode a non-linear input (e.g., a set of attributes); and ii) how to order the attributes in the generated description. Existing studies focus on the encoding problem but do not address the ordering problem, i.e., they learn the content-planning implicitly. The other approaches focus on two-stage models but overlook the encoding problem. To address the two problems at once, we propose a model named TransCP to explicitly learn content-planning and integrate them into a description generation model in an end-to-end fashion. We propose a novel Transformer-based Pointer Network with gated residual attention and importance masking to learn a content-plan. To integrate the content-plan with a description generator, we propose a tracking mechanism to trace the extent to which the content-plan is exposed in the previous decoding time-step. This helps the description generator select the attributes to be mentioned in proper order. Experimental results show that our model consistently outperforms state-of-the-art baselines by up to 2% and 3% in terms of BLEU score on two real-world datasets.
Behavioral Patterns of Sugary Drink Consumption among African American Adolescents: A Pilot and Feasibility Study Using Ecological Momentary Assessment

Background: Sugary drinks (SDs) are the predominant contributors to added sugar intake among adolescents, with the highest intakes reported among African American adolescents. The objective of this pilot study was to examine the feasibility of using mobile phone-based ecological momentary assessment (EMA) to investigate, in real time, behavioral patterns of SD consumption among African American adolescents from low-income households. Methods: Adolescents (n = 39, ages 12–17) attended a virtual meeting with a trained research assistant, which involved completion of surveys and training on responding to EMA prompts using a mobile phone application. On the seven subsequent days, adolescents were instructed to respond to researcher-initiated prompts three times daily, which queried their SD intake, location, social context, activities, stress, and mood. They were also asked to complete an analogous self-initiated survey each time they consumed SDs. Results: SD consumption was reported on 219 of 582 (38%) researcher-initiated surveys and on 135 self-initiated SD consumption surveys, for a total of 354 instances of SD intake over the 7-day assessment period. The majority (69%) of the surveys were completed while at home. SD consumption was reported on 37%, 35%, and 41% of researcher-initiated surveys completed at their home, at the home of a friend or family member, or while in transit, respectively. Conclusions: These preliminary data indicate that mobile phone-based EMA is feasible for investigating SD intake behaviors among African American youth from low-income households and support the promise of EMA for investigating SD consumption in this population in larger samples of youth.
The COVID-19 pandemic and the exchange rate: a lesson learned from Indonesia

This paper aims to capture the relationship between the COVID-19 pandemic and the exchange rate. We utilized high-frequency data by utilizing daily data from January 21st, 2020, through June 29th, 2022. In contrast to the vast majority of research that disregards the incubation period of COVID-19 in the number of daily transmission cases, we use the growth of COVID-19 as a 14-day moving average of confirmed cases as the main independent variables. Findings indicate that the devaluation of the rupiah exchange rate is long-term associated with the increase in COVID-19 cases and deaths. According to the efficient market hypothesis, the rupiah depreciates due to the increase of COVID-19 transmission, which is publicized by the media. In the midst of the debate over the impact of the pandemic on the exchange rate and using Indonesia as a lesson learned for emerging market economies, our research is a recent study that examines this topic with completed data-generating processes – when the pandemic entered its last wave phase. In regard to exchange rate behavior, the disease outbreak channel exists. The government must restrict widespread media coverage of data on the spread of COVID-19 while focusing on accelerating measures to control the pandemic. A low-interest rate imposed by the monetary authorities as an effort to stimulate economic recovery can also exert pressure on the exchange rate, necessitating the optimization of other instruments, such as foreign exchange intervention.
Experience With J-Plasma Device in Achieving Complete Cytoreduction in Patients With Ovarian Cancer.

BACKGROUND/AIM Ovarian cancer remains one of the most lethal malignancies in women. Optimal surgical cytoreduction is the most important prognostic factor of survival in patients with advanced ovarian cancer. The helium gas plasma device (J-Plasma) has recently been introduced into surgical treatment of these patients with some promising results. The aim of this study was to evaluate the utility of J-Plasma in the debulking surgery of patients with ovarian cancer. PATIENTS AND METHODS A single center retrospective analysis of the characteristics of patients with ovarian cancer who had cytoreductive surgery with the use of J-Plasma device from January of 2020 until July of 2022 was conducted. RESULTS A total of 13 patients were included in our study. Six patients were treated with primary debulking surgery, whereas seven underwent interval debulking surgery after neoadjuvant chemotherapy. Complete cytoreduction was achieved in nine patients (64%), and CC-1 in four patients. Most of the patients did not face any major complications; only 1 patient suffered from small bowel fistula that needed relaparotomy. CONCLUSION J-Plasma can safely be used in ovarian cancer debulking surgeries performed by gynecologic oncologists in tertiary centres. This technology can safely increase the complete cytoreduction rates.
Spectropolarimetric Inversions of the Ca II 8498 and 8542 Å Lines in the Quiet Sun

We study non-LTE inversions of the Ca II infrared triplet lines as a tool for inferring physical properties of the quiet Sun. The inversion code is successful in recovering the temperature, velocity, and longitudinal magnetic flux density in the photosphere and chromosphere, but the height range where the inversions are sensitive is limited, especially in the chromosphere. We present results of inverting spectropolarimetric observations of the lines in a quiet-Sun region. We find three distinct ranges in chromospheric temperature: low temperatures in the internetwork, high temperatures in the enhanced magnetic network, and intermediate temperatures associated with low magnetic flux regions in the network. The differences between these regions become more pronounced with height as the plasma-β decreases. These inversions support the picture of the chromosphere, especially close to the magnetic network, being highly inhomogeneous in both the vertical and horizontal directions.
Relation between body condition score and conception rate of Japanese Black cows

Objective This study analyzes interactions of body condition score (BCS) with other factors and the effect of BCS on estimates of genetic paremeters of conception rate (CR) in Japanese Black cows. Methods Factors affecting CR were analyzed through the linear mixed model, and genetic parameters of CR were estimated through the threshold animal model. Results The interactions between BCS and each season and the number of artificial inseminations (AI) was significant (p<0.05), but that between BCS and parity showed no significance for CR. High CR was observed with BCS 3 in autumn (0.56±0.01) and BCS 4 in summer (0.56±0.02). The highest CR with BCS 3 (0.56±0.02) and BCS 4 (0.55 ±0.01) was observed at first AI. With BCS 5, however, the highest CR (0.55±0.08) was observed at second AI. Conclusion The model with BCS was notably conducive to the estimation of genetic parameters because of a low deviance information criterion of heritability that, nevertheless, was slightly lower than the model without BCS.
ANFIS Modeling Based on T-S Model on Lithopone Calcination Process

In order to solve the difficult modeling problem of the lithopone calcination process, this paper proposes an adaptive neural fuzzy inference systems(ANFIS) modeling method based on T S model. Through the structure and parameter identification of fuzzy identification system, the system can converge to the required input output relationships independently and rapidly. The systems structure and its learning algorithm is discussed. Through simulation research, its practical application value is obtained.
Properties and algorithms of the (n, k)-arrangement graphs

The (n, k)-arrangement interconnection topology was first introduced in 1992. The (n, k )-arrangement graph is a class of generalized star graphs. Compared with the well known n-star, the (n, k )-arrangement graph is more flexible in degree and diameter. However, there are few algorithms designed for the (n, k)-arrangement graph up to present. In this thesis, we will focus on finding graph theoretical properties of the (n, k)arrangement graph and developing parallel algorithms that run on this network. The topological properties of the arrangement graph are first studied. They include the cyclic properties. We then study the problems of communication: broadcasting and routing. Embedding problems are also studied later on. These are very useful to develop efficient algorithms on this network. We then study the (n, k )-arrangement network from the algorithmic point of view. Specifically, we will investigate both fundamental and application algorithms such as prefix sums computation, sorting, merging and basic geometry computation: finding convex hull on the (n, k )-arrangement graph. A literature review of the state-of-the-art in relation to the (n, k)-arrangement network is also provided, as well as some open problems in this area.
Peran Komunikasi Dalam Proses Akulturasi Sistem Sosial Lokal

Budaya harus diteliti, diwariskan dari generasi ke generasi, berdasarkan simbol, dinamis, dan proses yang terintegrasi karena biasanya langsung mempengaruhi komunikasi. Akulturasi merupakan fenomena sosial yang terjadi secara alami. Jika sekelompok orang dari budaya tertentu dihadapkan pada unsur-unsur dari budaya yang berbeda sedemikian rupa sehingga mereka secara bertahap menerima dan memasukkan unsur-unsur asing ke dalam budaya mereka sendiri, tanpa kehilangan identitas budaya aslinya, dan jika kelompok budaya dari masyarakat hidup berdampingan. Tujuan dari penelitian ini adalah untuk mengidentifikasi perbedaan budaya dan filosofi komunikasi yang dapat menimbulkan masalah dalam komunikasi lintas budaya. Penelitian ini menggunakan metode studi literature review melalui pengalaman-pengalaman lintas budaya yang ditunjang dengan studi formal tentang konsep budaya. Hasil penelitian dapat memahami potensi akulturasi dan peran komunikasi dalam mempermudah akulturasi dari pihak-pihak yang berkomunikasi akan memudahkan berlangsungnya proses komunikasi dan dalam pencapaian makna di antara keduanya.