Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrable systems and combinatorial theory

T he goal of this article is twofold: • to describe the recent solution [BDJ1] of a problem in combinatorics using methods from the theory of integrable systems; • to illustrate, en route, various developments that have taken place in the general area of integrable systems over the years. The modern era in the theory of integrable systems began with the discovery in 1967 by Gardner, Greene, Kruskal, and Miura [GGKM] of a method for integrating the Korteweg de Vries equation. Initially this discovery was regarded as providing a method of solution restricted exclusively to the (rather thin) set of “integrable evolutionary systems”, but by the early 1980s it started to become clear that the discovery of [GGKM] was just the first glimpse of a far more general integrable methodthat would eventually have applications across the broad spectrum of problems in pure and applied mathematics. In the narrowest sense an integrable system is a Hamiltonian dynamical system—finite or infinite dimensional—with “enough” integrals of the motion, all of whose Poisson brackets are zero, to solve the system in some “explicit” form. It has been a broad and unifying experience in the field over the last thirty years that many systems that are of great mathematical and physical interest, which may not be Hamiltonian, and which may not even be dynamical, can be solved “explicitly” using techniques that have some direct link back to the method of solution for the Korteweg de Vries equation discovered in [GGKM]. This article, however, is not intended as a comprehensive bibliographical survey in the field. Descriptions of developments in integrable systems from the late 1960s to the early 1990s, together with the contributions of many different authors, can be found, for example, in [AS] and [FZ]. The problem at hand is the following. Let SN be the group of permutations π of the numbers 1, . ,N . For 1 ≤ i1 < · · · < ik ≤ N we say that π (i1), . , π (ik) is an increasing subsequence of π of length k if π (i1) < · · · < π (ik). Let ̀ N (π ) be the length of the longest increasing subsequence of π . For example, if N = 5 and π is the permutation with π (1) = 5 , π (2) = 1 , π (3) = 3 , π (4) = 2 , and π (5) = 4 , then 134 and 124 are both longest increasing subsequences of π and `5(π ) = 3. Equip SN with the uniform distribution, and define
DETECTION OF THE 3.3 μm AROMATIC FEATURE IN THE SUPERNOVA REMNANT N49 WITH AKARI

We present an infrared (IR) study of the supernova remnant (SNR) N49 in the Large Magellanic Cloud with the near-IR (NIR; 2.5–5 μm) spectroscopic observations performed by AKARI. The observations were performed as a coarse spectral mapping to cover most of the bright region in the east, which enables us to compare the distribution of various line emissions and to examine their correlation. We detect the 3.3 μm aromatic feature in the remnant, which is the first time the presence of the 3.3 μm aromatic feature related to an SNR has been reported. In the line maps of the H2 1–0 O(3), the 3.3 μm feature, and the Brα, the distribution of the aromatic feature shows overall correlation with those of other emissions together with regional differences that reflect the local physical conditions. By comparing other archival imaging data at different wavelengths, the association of the aromatic emission with other ionic/molecular emissions is clarified. We examine the archival Spitzer Infrared Spectrograph data of N49 and find signatures of other polycyclic aromatic hydrocarbon (PAH) features at 6.2, 7.7, and 11.3 μm corresponding to the 3.3 μm aromatic feature. Based on the band ratios of the PAHs, we find that the PAHs in N49 are not only dominantly neutral, but they are also small in size. We discuss the origin of the PAH emission in N49 and conclude that the emission is either from the PAHs that have survived the shock or from the PAHs in the preshock gas that was heated by the radiative precursor.
Inclusion of Digital Literacy Skills in Transition Planning for Students With Intellectual Disabilities

Inclusive post-secondary education (PSE) for students with intellectual disabilities (IDs) is becoming increasingly common in colleges and universities. A majority of these inclusive PSE programs focus on academic enrichment, socialization, independent living skills, integrated work experiences, and career skills. Thus, in inclusive PSE programs, it is important for students with ID to be able to use technology for academic, employment, independent living, and communication functions. It is also beneficial if these students are able to use different technology devices (e.g., computers, smart phones, and tablets) for multiple purposes in order to complete academic, social, recreational, and vocational tasks. Although students with ID can be taught these skills in college, students who begin PSE programs already having these technology skills are better prepared for college and adulthood. Including digital literacy skills, technology strategies, and assistive technology use and application goals in Individualized Education Program (IEP) transition plans may be very helpful in preparing high school students for multiple adult outcomes. This paper describes some of the assistive technology and digital literacy skills, strategies, tools, and goals that secondary level special education teachers should include in students’ IEPs and transition plans. It also suggests how special education teachers can teach these technology skills.
Gambling and Gambling Problem Perception Questionnaire as a tool to evaluate professionals’ attitudes towards problem gamblers and training programmes in Japan

Aim: To develop and measure the psychometric properties of the Gambling and Gambling Problem Perception Questionnaire (GGPPQ); a scale to evaluate professionals’ attitudes towards people with problem gambling in the Japanese context. Data collection: We held 12 workshops in Japan targeted at mental health professionals who consult people with gambling problems. Participants completed the survey before the workshop. Some were also asked to complete the survey after the workshop to measure workshop influence. Setting: Public and private healthcare facilities in all 47 prefectures of Japan. Participants: Medical doctors, nurses, social workers, clinical psychologists, and other professionals working in the aforementioned facilities (n = 653, response rate = 98.5%). Measurements: licence; knowledge about gambling and gambling problems (questionnaire); self-rating of knowledge and general confidence for helping problem gamblers; years of practice; frequency of working with clients; experience in attending workshops; overall satisfaction with the workshop. Results: A five-factor structure extracted by exploratory factor analysis showed a good fit by confirmatory factor analysis (CFI = .973, TLI = .967, RMSEA = .060, AIC = 28913.6, BIC = 29110.8). The GGPPQ showed good internal consistency and good concurrent validity with participants’ self-rating of their knowledge, general confidence, frequency of working with clients who have gambling problems, and experience in attending workshops. The workshop had a positive influence on participants’ attitudes. Japan's unique gambling industry and lack of training opportunities on problem gambling were assumed to have influenced the psychometric properties of the measurement tool. Conclusion: The GGPPQ is a valid tool to measure the attitudes of healthcare professionals towards people with gambling problems, as well as workshop effectiveness in Japan.
Variation in Anti-Mullerian Hormone Levels with Age in Women Accessing In Vitro Fertilization Services in Ghana

The emergence of AMH as a reliable biomarker for assessing ovarian reserve and optimization of assisted reproductive technology (ART) remains a promising tool for the evaluation and prediction of controlled ovarian stimulation (COS) outcomes. This study assessed the association between serum AMH levels and maternal age in females receiving in vitro fertilization (IVF) treatment in Ghana. Methods: We conducted a prospective cohort study at a specialized fertility center in Ghana. Descriptive analysis was performed, and the differences between maternal age and AMH categories were assessed by the Kruskal–Wallis test. Results: We included 426 women with mean (±SD) age and AMH levels of 35.25 ± 6.33 years and 2.80 ± 2.60 ng/mL, respectively. Women with very-low AMH levels (0.94 ± 73 ng/mL) were older (>40 years), whereas the younger (20–25 years) group had higher levels (4.85 ± 3.34 ng/mL). There was a significant negative correlation between women’s age and serum AMH levels (R = −0.46; p < 0.001). None of the younger women had AMH levels <0.30 ng/mL, while 70% of women who had AMH levels of <0.30 ng/mL were older women (>40years). In addition, none of the older women had AMH levels >4 ng/mL with only 5% having AMH levels between 2.20 and 4.0 ng/mL. Conclusions: AMH levels ≤0.3 ng/mL are archetypal of 70% of Ghanaian women >40 years old receiving fertility treatment. A combined assessment of AMH levels and age supports clinical decisions in predicting ovarian response to controlled ovarian stimulation (COS) and may be valuable in predicting of IVF success. Further research to evaluate the combined use of age, AMH, and other ovarian reserve markers in assessing ovarian response to COS is recommended.
Solution of Combined Heat and Power Economic Dispatch Problem Using Genetic Algorithm

This research proposes a synergistic meta-heuristic algorithm for solving the extreme operational complications of combined heat and power economic dispatch problem towards the advantageous economic outcomes on the cost of generation. The combined heat and power (CHP) is a system that provides electricity and thermal energy concurrently. For its extraordinary efficiency and significant emission reduction, it is considered a promising energy pros-pect. The broad application of combined heat and power units requires the joint dispatch of power and heating systems, in which the modelling of combined heat and power units plays a vital role. The present research employs the genetic optimization algorithm to evaluate the cost function, heat and power dispatch values encountered in a system with simple cycle cogeneration unit and quadratic cost function. The system was first modeled to determine the various parameters of combined heat and power units towards solving its economic dispatch problem directly. In order for modelling to be done, a general structure of combined heat and power must be defined. The test system considered consists of four units: two conventional power units, one combined heat and power unit and one heat-only unit. The algorithm was applied to test system while taking into account the power and heat units, bounds of the units and feasible operation region of cogeneration unit. Output decision variables of 4-unit test systems plus cost function from Genetic Algorithm (GA), was determined using appropriate codes. The proposed algorithm obtained compared favourably with that obtained with the direct solution algorithm discussed in a previous paper. We conclude that the genetic algorithm is quite efficient in dealing with non-convex and constrained combined heat and power economic dispatch problem.
POLA PENGELOLAAN MEDIA KOMUNIKASI PUBLIK PERGURUAN TINGGI DALAM MEMBENTUK ONLINE REPUTATION

Perguruan tinggi baik negeri maupun swasta harus mampu untuk meningkatkan kualitas membentuk reputasi yang kedepannya akan membantu meningkatkan kepentingan masyarakat dan calon mahasiswa agar dapat bersaing mempertahankan eksistensi masing – masing. Penelitian ini menggunakan pendekatan kualitatif dengan jenis penelitian studi kasus. Teori yang digunakan adalah Konstruksi Teknologi Sosial (SCOT). Pada penelitian ini ditemukan bahwa komunikator mengalami konflik peran, hal ini terjadi ketika komunikator mengalami tekanan peran ganda dan/atau ambiguitas peran, karena pembatasan tugas dan pekerjaan yang kurang tertata rapi dan tidak jelas. Peneliti mengidentifikasi efisiensi pola pengelolaan media komunikasi publik sangat didukung oleh tujuan spesifik dari strategi media sosial yang dirancang secara strategis dan oleh tingkat respons pemangku kepentingan terkait terhadap pesan media sosial. Perguruan tinggi harus melibatkan pekerja humas yang memiliki pengetahuan, pemahaman, dan keterampilan khusus untuk membentuk reputasi lembaga ekosistem media digital. Kata Kunci: Media Komunikasi Publik, Online Reputation, Perguruan Tinggi
Cynanoside F Controls Skin Inflammation by Suppressing Mitogen-Activated Protein Kinase Activation

Atopic dermatitis (AD) is a chronic inflammatory skin disease accompanied by severe itching and dry skin. Currently, the incidence of AD due to excessive activation of immune cells by various environmental factors is increasing worldwide, and research on inflammatory response inhibitors with fewer side effects is continuously needed. Cynanoside F (CF) is one of the pregnane-type compounds in the root of Cynanchum atratum, an oriental medicinal herb that has been shown to have antioxidant, antitumor, and anti-inflammatory effects. Although CF has been isolated as a component in Cynanchum atratum, the scientific role of CF has not yet been explored. In this study, we evaluated the effect of CF on AD and revealed the mechanism using in vitro and in vivo experimental models. CF significantly reduced lipopolysaccharide (LPS)-induced protein expression levels of interleukin-1β (IL-1β), interleukin-6 (IL-6), and cyclooxygenase-2 (COX-2), which are important proinflammatory mediators in the RAW264.7 macrophage cell line. CF did not inhibit the nuclear factor-kappa B (NF-κB) signaling activated by LPS but significantly reduced the phosphorylation of mitogen-activated protein kinases (MAPKs), such as p38 MAPK, JNK, and ERK. CF consistently inhibited the activity of the activator protein-1 (AP-1) transcription factor, a downstream molecule of MAPK signaling. In addition, in an experiment using an oxazolone-induced AD mouse model, the CF-treated group showed a marked decrease in epidermal thickness, the number of infiltrated mast cells, and the amount of histamine. The mRNA levels of IL-1β, interleukin-4 (IL-4), and thymic stromal lymphopoietin (TSLP) were consistently lowered in the group treated with CF. Moreover, the phosphorylation of c-Jun and c-Fos protein levels, which are the AP-1 components, were lowered in the skin tissues of CF-treated mice. These results provide the first evidence that CF has an inhibitory effect on AD and suggest the possibility of CF being developed as a potential therapeutic agent for AD.
The Epidemics of Corruption

We study corruption as a generalized epidemic process on the graph of social relationships. The main difference to classical epidemic processes is the strong nonlinear dependence of the transmission probability on the local density of corruption and the mean field influence of the overall corruption in the society. Network clustering and the degree-degree correlation play an essential role in corruption dynamics. We discuss phase transitions, the influence of the graph structure and the implications for epidemic control. Structural and dynamical arguments are given why strongly hierarchically organized societies like systems with dictatorial tendency are more vulnerable to corruption than democracies. A similar type of modelling can be applied to other social contagion spreading processes like opinion formation, doping usage, social disorders or innovation dynamics.
A New Detection Method Based on Magnetic Leakage Theory and BP Neural Network for Broken Steel Strands in ACSR Conductor

Aluminum conductor steel-reinforced (ACSR) conductor is characterized by inner tensile body of steel core and outer twisted aluminum wire strands, which is obviously different from common steel wire ropes (SWRs) or cables. However, the existing studies are mainly focused on the magnetic flux leakage (MFL) testing of the SWR defects, few or not related to broken steel strands in ACSR conductors. Thus, the leakage magnetic field distributions of SWR and ACSR defects are compared and analyzed by the theoretical and numerical calculations. By considering the nonconductivity characteristics of aluminum wire strands, the steel-air model is established to calculate the effects of fracture width and the number of broken steel strands on the MFL signal for ACSR conductors. Based on the spatial distribution characteristics of ACSR leakage field with low intensity, weak lifting-off effect, and weak circumferential correlation, a single-channel signal processing method with time–frequency domain coupling is proposed. Multiple sets of characteristic values of MFL signal both in time and time–frequency domains are extracted to construct a back propagation (BP) neural network for broken steel strand identification. The results have shown that the improved single-channel time–frequency analysis method has higher accuracy in identifying the ACSR fracture width and the number of broken steel strands compared to the image processing method with multichannel leakage data fusion. With the improved method, the detection error of the fracture width is less than 2 mm, and the accuracy of the number of broken strands can reach 91.67%.
Do mergers and acquisitions improve bank efficiency? Evidence from North Macedonia

This article focuses on the efficiency of commercial banks in North Macedonia in the period from 2007 to 2020. The main goal is to assess the relative efficiency of the banking sector as a whole, and more importantly, to evaluate and analyse the impact of mergers and acquisition (M&A) transactions on banks’ efficiency. For this reason, the leading nonparametric methodology Data Envelopment Analysis (DEA) has been employed, i.e., the window DEA model with two input and two output variables on a sample of 13 commercial banks. Based on balanced panel data from the banking sector of North Macedonia, the obtained results show a constant fall of efficiency of the whole banking sector, from 83.33% in 2007 to 70.06% in 2011 and 66.36% in 2020. The results of the M&A transactions case study analysis show that, in general, M&A transactions decrease banks' efficiency, i.e., they do not result in an efficiency increase. The contribution of the study is that it comprises the first study analysing the effects of banks' M&A on bank efficiency in the region of South-Eastern Europe with the application of DEA and thus, it provides valuable information for investors, bank management, M&A analysts, academic members and regulatory bodies.
Reuse in Contemporary Software Engineering Practices - An Exploratory Case Study in A Medium-sized Company

Background: Software practice is evolving with changing technologies and practices such as InnerSource, DevOps, and microservices. It is important to investigate the impact of contemporary software engineering (SE) practices on software reuse. Aim: This study aims to characterize software reuse in contemporary SE practices and investigate its implications in terms of costs, benefits, challenges, and potential improvements in a medium-sized company. Method: We performed an exploratory case study by conducting interviews, group discussions, and reviewing company documentation to investigate software reuse in the context of contemporary SE practices in the case company. Results: The results indicate that the development for reuse in contemporary SE practices incurs additional coordination, among other costs. Development with reuse led to relatively fewer additional costs and resulted in several benefits such as better product quality and less development and delivery time. Ownership of reusable assets is challenging in contemporary SE practice. InnerSource practices may help mitigate the top perceived challenges: discoverability and ownership of the reusable assets, knowledge sharing and reuse measurement. Conclusion: Reuse in contemporary SE practices is not without additional costs and challenges. However, the practitioners perceive costs as investments that benefit the company in the long run.
A Practical Lightweight Anonymous Authentication and Key Establishment Scheme for Resource-Asymmetric Smart Environments

With the rapid developments of Internet of Things (IoT) technologies, the security of sensitive data has attracted more and more attention for many resource-asymmetric smart environments, such as smart home, smart agriculture and so on. The resource-asymmetry environment refers to the uneven distribution of resources on different devices side, which is specifically manifested as gateway side is resource-rich, user side and device side are resource-restricted. Hence, a secure and practical authentication key establishment scheme for such smart environments is urgently needed. Recently many researchers have designed authentication and key establishment schemes for security purpose, however most of them cannot consider the excess of gateway resources and guarantee the anonymity of user, and further, they are not suitable for resource-asymmetric smart environments because they are not lightweight enough in user side and smart device side. Due to the fact that Rabin cryptosystem has the large difference in time-consuming between encryption and decryption, it is extremely suitable for constructing authentication and key establishment scheme for resource-asymmetric smart environments. So, a new practical authentication and key establishment scheme based on the Rabin cryptosystem for resource-asymmetric smart environments is proposed, which can make better use of the advantages of abundant gateway resources and realize the lightweight operations on device side and user side, and at the same time can provide user anonymity. With Proverif and BAN logic, we can prove that our solution not only provides anonymity, but also satisfies all defined security features. Simultaneously, compared with latest similar protocols in computation cost and communication overhead, the results show that our scheme is more effective. Hence, our design has more attraction for authentication and key establishment scheme in resource-asymmetric smart environments.
Semi-supervised Deep Learning via Transformation Consistency Regularization for Remote Sensing Image Semantic Segmentation

Deep convolutional neural networks have gotten a lot of press in the last several years, especially in domains like computer vision and remote sensing (RS). However, achieving superior performance with deep networks highly depends on a massive number of accurately labeled training samples. In real-world applications, gathering a large number of labeled samples is time consuming and labor intensive, especially for pixel-level data annotation. This dearth of labels in land-cover classification is especially pressing in the RS domain because high-precision high-quality labeled samples are extremely difficult to acquire, but unlabeled data are readily available. In this study, we offer a new semisupervised deep semantic labeling framework for the semantic segmentation of high-resolution RS images to take advantage of the limited amount of labeled examples and numerous unlabeled samples. Our model uses transformation consistency regularization to encourage consistent network predictions under different random transformations or perturbations. We try three different transforms to compute the consistency loss and analyze their performance. Then, we present a deep semisupervised semantic labeling technique by using a hybrid transformation consistency regularization. A weighted sum of losses, which contains a supervised term computed on labeled samples and an unsupervised regularization term computed on unlabeled data, may be used to update the network parameters in our technique. Our comprehensive experiments on two RS datasets confirmed that the suggested approach utilized latent information from unlabeled samples to obtain more precise predictions and outperformed existing semisupervised algorithms in terms of performance. Our experiments further demonstrated that our semisupervised semantic labeling strategy has the potential to partially tackle the problem of limited labeled samples for high-resolution RS image land-cover segmentation.