Miracle-dz/UniFAR-FTUs huggingface dataset:
An exponential method to solve linear Fredholm–Volterra integro-differential equations and residual improvement

Abstract: In this paper, a collocation approach based on exponential polynomials is introduced to solve linear Fredholm– Volterra integro-differential equations under the initial boundary conditions. First, by constructing the matrix forms of the exponential polynomials and their derivatives, the desired exponential solution and its derivatives are written in matrix forms. Second, the differential and integral parts of the problem are converted into matrix forms based on exponential polynomials. Later, the main problem is reduced to a system of linear algebraic equations by aid of the collocation points, the matrix operations, and the matrix forms of the conditions. The solutions of this system give the coefficients of the desired exponential solution. An error estimation method is also presented by using the residual function and the exponential solutions are improved by the estimated error function. Numerical examples are solved to show the applicability and the effectiveness of the method. In addition, the results are compared with the results of other methods.
Reconstructing the star formation history of the Solar neighbourhood with Gaia

Abstract Taking advantage of the Gaia DR1, we combined TGAS parallaxes with the Tycho-2 and APASS photometry to calculate the star formation history (SFH) of the solar neighbourhood within 250 pc using the colour-magnitude diagram fitting technique. Our dynamically-evolved SFH is in excellent agreement with that calculated from the Hipparcos catalogue within 80 pc of the Sun, showing an enhanced star formation rate (SFR) in the past ~4 Gyr. We then correct the SFR for the disc thickening with age to obtain a SFR that is representative of the whole solar cylinder, and show that even with an extreme correction our results are not consistent with an exponentially decreasing SFR as found by recent studies. Finally, we discuss how this technique can be applied out to ~5 kpc thanks to the next Gaia data releases, which will allow us to quantify the SFH of the thin disc, thick disc and halo in situ.
Optimal Thrust Programming Along the Brachistochronic Trajectory with Non-linear Drag

Abstract The problem of maximization of the horizontal coordinate of a mass-point moving in the vertical plane driven by gravity, non-linear viscous drag, and thrust is considered. The slope angle and the thrust are considered as a control variables. The problem is related to the modified brachistochrone problem. Principle maximum procedure allows to reduce the optimal control problem to the boundary value problem for a set of systems of two non-linear differential equations. The qualitative analysis of the trajectories of these systems is performed, and the characteristic features of the optimal solutions are determined. Thrust control depending on the velocity and slope angle is designed. Results obtained allow to construct quasi-optimal solutions for the more complex systems, where phase plane method is not applicable.
Experimental and Numerical Analysis of Wooden Sonic Crystals Applied as Noise Barriers

Recent research has been developed by different groups towards the development of sonic crystals as noise barriers. The present paper aims to contribute to this research, focusing on the possible application of this technology in practice, and exploring some aspects that may be useful for its further development. One of the objectives of this work is to explore the differences between experimental results obtained under laboratory conditions and numerical results computed with the finite element method (FEM), in 2D and 3D, understanding if different types of simplified models can be of use in the practical analysis of sonic crystals. Through this comparison, a validation of the prediction numerical models is performed, giving confidence for their use in the development and study of sonic crystal configurations. In this context, different geometric arrangements of the sonic crystals’ scatterers (the individual elements that make up the barriers) have been analyzed with the help of the numerical method, evaluating their behavior in different arrangements of numbers of elements, shape and size. A number of parametric studies are also performed introducing some randomness in the structure (in scatterer size and spacing), and analyzing its effect on the insertion loss provided by the sonic crystal. These contributions can be significantly useful for the development of new solutions, giving important hints about the sensitivity of these structures to possible defects or limitations in their production.
Discrete event system framework for fault diagnosis with measurement inconsistency: case study of rogue DHCP attack

Fault detection and diagnosis ( FDD ) facilitates reliable operation of systems. Various approaches have been proposed for FDD like Analytical redundancy ( AR ), Principal component analysis ( PCA ), Discrete event system ( DES ) model etc., in the literature. Performance of FDD schemes greatly depends on accuracy of the sensors which measure the system parameters. Due to various reasons like faults, communication errors etc., sensors may occasionally miss or report erroneous values of some system parameters to FDD engine, resulting in measurement inconsistency of these parameters. Schemes like AR, PCA etc., have mechanisms to handle measurement inconsistency, however, they are computationally heavy. DES based FDD techniques are widely used because of computational simplicity, but they cannot handle measurement inconsistency efficiently. Existing DES based schemes do not use Measurement inconsistent ( MI ) parameters for FDD. These parameters are not permanently unmeasurable or erroneous, so ignoring them may lead to weak diagnosis. To address this issue, we propose a Measurement inconsistent discrete event system ( MIDES ) framework, which uses MI parameters for FDD at the instances they are measured by the sensors. Otherwise, when they are unmeasurable or erroneously reported, the MIDES invokes an estimator diagnoser that predicts the state( s ) the system is expected to be in, using the subsequent parameters measured by the other sensors. The efficacy of the proposed method is illustrated using a pump-valve system. In addition, an MIDES based intrusion detection system has been developed for detection of rogue dynamic host configuration protocol ( DHCP) server attack by mapping the attack to a fault in the DES framework.
An Accelerating Universe with No Dark Energy

The original application of general relativity to the universe showed that the universe is expanding, albeit at a decreasing rate. Supernova data have established that although early in its history the universe was expanding at a decreasing rate, the rate of expansion has been increasing for the past several billion years. Einstein’s equations were modified by adding the cosmological constant to make the expansion of the universe accelerate and fit the data, giving birth to the notion of dark energy. However, there is to date no good explanation of dark energy. This paper proposes that Einstein’s original equations be left alone and that instead, the model assumed for the expanding universe be changed: from a single uniformly isotropic expanding space universe of constant mass to a similarly expanding universe surrounded by an isotropic, uniform shell. The overall mass of the structure remains constant. This new geometry produces the observed expansion behavior of the universe and is simply a result of different initial conditions.
Internalization of Islamic Moderation Value in Mathematics Problem Solving

Several studies have discussed the internalization of Islamic values in mathematics, including Islam and mathematics, internalization of Islamic values in mathematics learning with analogy strategies, mathematical analysis of the philosophy of the Quran, the secret of numbers in the Qur’an. However it has never been discused abaout the internalization of Islamic moderation values in mathematical problem solving. So this research is needed. Moreover, the phenomenon of Islam in Indonesia is currently shifting away from the image of moderate Islam and into a harsher conservative ideology. This is more worrying because it has entered the realm of education. For that it is necessary to internalize the value of Ilamic moderation in mathematical problem solving. One of the strategies that can be done to instill religious moderation values in mathematical problem solving is the analogy strategy. Facts, concepts, and principles in mathematics can be used a analogy to instill religious moderation values. In this study, describe some examples of the application of analogy strategies for internalizing Islamic value. This study uses the library method. The data obtained were publications of research artcles in scientific journals. The analyed articles include three stages, organizing, synthesizing and identifying. The results of data analysis show that the value of tasamuh in mathematics learning can be done through open ended problem solving. The characteristics of open ended problem is problem that have more than one solution and answer tolerance, so each student may have different and equally correct solutions and answers. This is in accordance with the principle of tasamuh value in Islamic moderation. Therefore, on classroom learning, the values of tasamuh can be implemented through open ended problem.
Role of Intestinal Ultrasonography in Assessment of Disease Activity in Ulcerative Colitis Patients

Background: Intestinal ultrasound [IUS] has been reported to be accurate in the diagnosis of ulcerative colitis and can also be applied to determine the extent, severity and location of inflammation. The aim of this study was to evaluate the usefulness of bowel US in comparison to colonoscopy for assessing disease extent and activity of ulcerative Colitis. Methods: This cross sectional study included 60 patients with ulcerative colitis who attended Gastroenterology outpatient clinics and IBD unit of National Hepatology and Tropical Medicine Research Institute. Participants were divided into 2 groups of patients according to Truelove and Witt’s criteria for classification of severity of ulcerative colitis. Group I (n= 30) active ulcerative colitis patients. Group II (n= 30) inactive ulcerative colitis patients (in remission). Selected patients were subjected to laboratory investigations, colonoscopic and intestinal ultrasound examination (IUS). Results: In the present study, bowel wall thickness can be used to discriminate between active and inactive ulcerative colitis patients at a cut off level of > 3.5(P<0.001). The mean BWT was significantly thicker in active group of patients (5.2±0.7 mm, P<0.001) than of inactive (2.6±0.2 mm, P<0.001) while fat creeping and reactive lymph nodes (LNs) has no role in discrimination of ulcerative colitis patient’s activity (P=0.150). Doppler signal increased (P=0.057), while wall layer stratification was disturbed in patients with active ulcerative colitis (P=0.002). Conclusion: IUS may represent a useful first-line, non-invasive tool for assessing activity, severity and extent of ulcerative colitis.
The Effect of Change Perceptions in Price, Service Quality and Brand Image on Consumer Shopping Behavior During the COVID-19 Pandemic

The COVID-19 pandemic is forcing the world community to adopt new habits, one of the new habits at once The solution is Gojek as an online delivery service. This research aims to understand the effect of changes in consumer perceptions in terms of price, quality and brand image on consumer shopping behavior during the COVID-19 pandemic. The type of research used is explanatory research, with a quantitative approach. The research subjects are Go-food customers in Yogyakarta during the COVID-19 pandemic and the objects of research are consumer perceptions, prices, service quality, brand image and consumer shopping behavior. and customer satisfaction. Data collection techniques were carried out through questionnaires and documentation which were analyzed using multiple linear regression. The results showed that consumer perceptions in terms of price, service quality, and brand image had a significant positive effect on consumer shopping behavior during the COVID-19 pandemic.
High‐Resolution Land Surface Modeling of Hydrological Changes Over the Sanjiangyuan Region in the Eastern Tibetan Plateau: 1. Model Development and Evaluation

High‐resolution modeling became popular in recent years due to the availability of multisource observations, advances in understanding fine‐scale processes, and improvements in computing facilities. However, modeling of hydrological changes over mountainous regions is still a great challenge due to the sensitivity of highland water cycle to global warming, tightly coupled hydrothermal processes, and limited observations. Here we show a successful high‐resolution (3 km) land surface modeling over the Sanjiangyuan region located in the eastern Tibetan plateau, which is the headwater of three major Asian rivers. By developing a new version of a Conjunctive Surface‐Subsurface Process model named as CSSPv2, we increased Nash‐Sutcliffe efficiency by 62–130% for streamflow simulations due to the introduction of a storage‐based runoff generation scheme, reduced errors by up to 31% for soil moisture modeling after considering the effect of soil organic matter on porosity and hydraulic conductivity. Compared with ERA‐Interim and Global Land Data Assimilation System version 1.0 reanalysis products, CSSPv2 reduced errors by up to 30%, 69%, 92%, and 40% for soil moisture, soil temperature, evapotranspiration, and terrestrial water storage change, respectively, as evaluated against in situ and satellite observations. Moreover, CSSPv2 well captured the elevation‐dependent ground temperature warming trends and the decreased frozen dates during 1979–2014, and significant increasing trends (p < 0.05) in evapotranspiration and terrestrial water storage during 1982–2011 and 2003–2014 respectively, while ERA‐Interim and Global Land Data Assimilation System version 1.0 showed no trends or even negative trends. This study implies the necessity of developing high‐resolution land surface models in realistically representing hydrological changes over highland areas that are sentinels to climate change.
A Compressed Multivariate Macromodeling Framework for Fast Transient Verification of System-Level Power Delivery Networks

This article discusses a reduced-order modeling and simulation approach for fast transient power integrity verification at full system level. The reference structure is a complete power distribution network (PDN) from platform voltage regulator module (VRM) to multiple cores, including board, package, decoupling capacitors, and per-core fully integrated voltage regulators (FIVRs). All blocks are characterized and known through high-fidelity models derived from first-principle solvers (full-wave electromagnetic and circuit-level extractions). The complexity of such detailed characterization grows very large and becomes intractable, especially for power integrity verification of massive multicore platforms subjected to real workload scenarios. We approach this problem by exploiting a multistage macromodeling and compression process, leading to a compact representation of the system dynamics in terms of a linearized state-space structure with multiple feedback loops from the FIVR controllers. The PDN macromodel is obtained through a data-driven approach starting from reference small-signal frequency responses, obtaining a sparse and structured representation specifically designed to match the behavior of the reference system. The resulting compact model is then solved in time-domain very efficiently. Results on Mobile and enterprise Server benchmarks demonstrate a speedup in runtime up to $50\times $ with respect to HSPICE, with negligible loss of accuracy.
Automated inter-device 3D OCT image registration using deep learning and retinal layer segmentation

Optical coherence tomography (OCT) is the most widely used imaging modality in ophthalmology. There are multiple variations of OCT imaging capable of producing complementary information. Thus, registering these complementary volumes is desirable in order to combine their information. In this work, we propose a novel automated pipeline to register OCT images produced by different devices. This pipeline is based on two steps: a multi-modal 2D en-face registration based on deep learning, and a Z-axis (axial axis) registration based on the retinal layer segmentation. We evaluate our method using data from a Heidelberg Spectralis and an experimental PS-OCT device. The empirical results demonstrated high-quality registrations, with mean errors of approximately 46 µm for the 2D registration and 9.59 µm for the Z-axis registration. These registrations may help in multiple clinical applications such as the validation of layer segmentations among others.
The Influence of Digital Technologies on Knowledge Management in Engineering: A Systematic Literature Review

Digital technologies are gaining widespread acceptance in engineering and offer opportunities for collating and curating knowledge during and beyond the life cycle of engineering products. Knowledge is central to strategy and operations in most engineering organizations and digital technologies have been employed in attempts to improve current knowledge management practices. A systematic literature review was undertaken to address the question: how do digital technologies influence knowledge management in the engineering sector? Twenty-seven primary studies were identified from 3097 papers on these topics within the engineering literature published between 2010 and 2022. Four knowledge management processes supported by digital technologies were recognized: knowledge creation, storage and retrieval, sharing and application. In supporting knowledge management, digital technologies were found to have been acting in five roles: repositories, transactive memory systems, communication spaces, boundary objects and non-human actors. However, the ability of digital technologies to perform these roles simultaneously had not been considered and similarly knowledge management had not been addressed as a holistic process. Hence, it was concluded that a holistic approach to knowledge management combined with the deployment of digital technologies in multiple roles simultaneously would likely yield significant competitive advantage and organizational value for organizations in the engineering sector.
The Relationship between Environmental Innovation, Sustainable Supply Chain Management, and Financial Performance: The Moderating Role of Environmental, Social and Corporate Governance

Academics and professionals frequently relate the success of environmental, social, and corporate governance (ESG) performance to a company's financial performance. Due to their potential to reduce a company's sustainability challenges, environmental innovation and ESG have attracted considerable attention in the business environment and academia. This study aims to investigate the relationship between environmental innovation, ESG, sustainable supply chain management
Early Onset Metastatic Colorectal Cancer: Current Insights and Clinical Management of a Rising Condition

Simple Summary In this review, the authors will discuss the highlights of early onset colon cancer (EOCRC), an increasing but still unclear phenomenon. Indeed, the risk factors are largely similar to classic colon cancer (CRC), but it is still unclear what causes an increased risk of CRC at an early age. In addition, the issue of screening, which allows early diagnosis of the disease, is also important; the younger segment of the population is not included in such programs except if they belong to the highest-risk groups. If the phenomenon of EOCRC becomes more prominent, screening programs will have to be reviewed but with consideration of the consequences for health economics. In this review, we will focus on the epidemiological, prognostic, clinico-pathological, molecular, and therapeutic features of EOCRC; in particular, we will try to highlight the characteristics of the metastatic stage and the differences with CRC in older segments of the population. Abstract Despite a recent overall decrease in colorectal cancer (CRC) incidence and mortality, there has been a significant rise in CRC diagnoses in young adults. Early onset colorectal cancer (EOCRC) is defined as CRC diagnosed before the age of 50. Possible predisposing conditions include not only genetic syndromes but also other risk factors, such as microbiome alteration, antibiotic exposure, obesity, diabetes mellitus, and inflammatory bowel disease. EOCRC tends to be diagnosed later than in the older counterpart because of a lack of awareness and the fact that screening for CRC usually starts at the age of 50. Furthermore, CRC in young adults seems to be related to unique molecular features and more aggressive clinical behavior. This paper aims to provide an in-depth review of this poorly understood subject, with a comprehensive review of the state of the art and considerations for future perspectives.
Capital gains overhang and irrelevant value characteristics of Brazilian companies

This study, based on Ahmed’s (2017) work for the US market, examines whether the prices of shares traded on the stock market of a developing country, such as Brazil, can also be influenced by noise traders who make their decisions based on irrelevant information. Using data from the Brazilian stock market between Jan/2003 and Sep/2018 we show that irrelevant firm characteristics are associated with variations in capital gains overhang (CGO), a proxy for the disposition effect bias. Our results are quite similar to those found by Ahmed (2017) for the US. However, the two markets show different results for the relationship between CGO and market liquidity and systematic risk for the entire sample period. Also, we find that there is an inverse relationship between investor sentiment and CGO at times of market upward movement. Overall, the influence of variables considered irrelevant was confirmed in robustness checks. These results may imply that noise traders evaluate stocks and companies based on their irrelevant characteristics, and this behavior, which is not compensated for by rational investors, temporarily influences the market by generating price distortions like the disposition effect.