Miracle-dz/UniFAR-FTUs huggingface dataset:
Rapid Land Cover Classiﬁcation Using a 36-Year Time Series of Multi-Source Remote Sensing Data

: Long time series land cover classiﬁcation information is the basis for scientiﬁc research on urban sprawls, vegetation change, and the carbon cycle. The rapid development of cloud computing platforms such as the Google Earth Engine (GEE) and access to multi-source satellite imagery from Landsat and Sentinel-2 enables the application of machine learning algorithms for image classiﬁcation. Here, we used the random forest algorithm to quickly achieve a time series land cover classiﬁcation at different scales based on the ﬁxed land classiﬁcation sample points selected from images acquired in 2022, and the year-by-year spectral differences of the sample points. The classiﬁcation accuracy was enhanced by using multi-source remote sensing data, such as synthetic aperture radar (SAR) and digital elevation model (DEM) data. The results showed that: (i) the maximum difference (threshold) of the sample points without land class change, determined by counting the sample points of each band of the Landsat time series from 1986 to 2022, was 0.25; (ii) the kappa coefﬁcient and observed accuracy of the same sensor from Landsat 8 are higher than the results of the TM and ETM+ sensor data from 2013 to 2022; and (iii) the addition of a mining land cover type increases the kappa coefﬁcient and overall accuracy mean values of the Sentinel 2 image classiﬁcation for a complex mining and forest area. Among the land classiﬁcations via multi-source remote sensing, the combined variables of Spectral band + Index + Terrain + SAR result in the highest accuracy, but the overall improvement is limited. The method proposed is applicable to remotely sensed images at different scales and the use of sensors under complex terrain conditions. The use of the GEE cloud computing platform enabled the rapid analysis of remotely sensed data to produce land cover maps with high accuracy and a long time series.
International Journal of Research

While situating Andrographispaniculata (Kalmegh) in the cultural and ecological setting of Jharkhand, India, this work offers a thorough ethnopharmacological assessment. Traditional knowledge of Kalmegh's medicinal applications and its importance in indigenous healthcare practices is the focus of this study. The ethnomedicinal applications of Andrographispaniculata may be better understood via fieldwork that includes conversations with local populations, traditional healers, and practitioners. Among the many topics covered by the survey are the following: plant components, methods of manufacture, dosage, and delivery routes. Furthermore, the research delves into any cultural or ceremonial importance linked to the traditional medicinal use of Kalmegh. An evaluation of the phytochemical components found in Andrographispaniculata supplements the ethnobotanical data that has been gathered. Finding bioactive chemicals that might be responsible for the reported therapeutic effects is the primary goal of the study. For the local pharmacopoeia to fully grasp Kalmegh's medicinal potential, this knowledge is essential.The research sheds light on the traditional medical knowledge surrounding Andrographispaniculata in Jharkhand via its ethnopharmacological survey. The results help keep indigenous knowledge alive and pave the way for future pharmacological studies, which will help bring together traditional medicine and contemporary science to develop long-term solutions for this plant's therapeutic uses.
Experimental validation of an LSTM-based solar irradiance forecasting model

Establishing a foundation for the application of a new predictive model in small-and medium-sized buildings, where it is difficult to install measurement equipment, is associated with several challenges. In recent years, for the predictive control of buildings, research has been conducted on the development of a solar irradiance forecasting model that is capable of predicting solar irradiance at local sites using simple weather information and global data based on the LSTM machine-learning algorithm; however, in this previous study, tests were performed using simulation data only. Therefore, in this study, the solar irradiance on a target building was measured, and the effectiveness of this previously proposed model was examined using real-world data. The model was verified and categorized into three cases based on the type of data used for the LSTM learning. Cases 1 and 2 involved the prediction of the solar irradiance on a local building based on the use of global data corresponding to five and nine regions, respectively, and Case 3 involved the prediction of solar irradiance based on the learning of local solar irradiance data only. It was observed that Case 3 showed the best performance with an RSME of 32 W/m 2 , followed by Case 2, which showed a similar predictive performance, with a RMSE of 39 W/m 2 . These results can be used for the predictive control of buildings, and it is expected that the error will improve further as more global data becomes available for learning in future.
preda-Active defense mechanisms of thorny cat ﬁ sh

The thorny cat ﬁ sh (Doradidae; order Siluriforme), has characteristic barbed pectoral ﬁ n spines and mid-lateral scutes that work in concert to provide an active mechanical defense mechanism. The pectoral spines can be locked into several ﬁ xed positions at angles between 0 (cid:1) and 90 (cid:1) to the longitudinal axis. Upon deployment they provide a formidable barrier to deglutition by a predator. Additionally, each spine contains two rows of sharp serrations which are inclined to its axis and can slice through tissue. We characterize the internal structure of the rotation joint of the pectoral spines and unravel the locking mechanism which is ensured by dual sources of friction generated from the dorsal and anterior components on the spine base. In addition to the lockable spines, thorny cat ﬁ sh also possess two arrays of mid-lateral dermal scutes with a sharp hook shape and gradient inner structure, which also have potential cutting capability and are part of the ﬁ sh ’ s active defense, since they can injure the predator through rapid motions of the cat ﬁ sh body. The structural design of these two weapons is very impressive, including a hollow structure, porous components, and gradient transitions, leading to outstanding performance by maintaining strength, toughness and light weight synergistically. These designs may provide inspiration for the development of novel structural materials or new armor materials.
Construction of Adaptive Portfolios using A Deep Reinforcement Learning for Risk Mitigation

Choosing authentic stocks is critical to both quantitative trading and investing, which are intricate fiscal processes. The sensitive and big-time stochastic stock forecasting challenge has seen substantial evolution due to deep literacy advances, yet current results have two major downsides. They disregard the rich signals between associated stocks' temporal price oscillations and don't incontinently optimize the investment end in terms of profit. expanding upon these restrictions. Investors generally prefer portfolios with minimum correlations among their means in order to reduce the threat associated with connected means. The" Mercury" frame, a fresh system of stock webbing, is introduced in this approach. Your plutocrat grows as a effect of its capability to observe the request, acclimate to changes, and choose a collection of stocks that will not all vanish at formerly. Choosing the right stocks is pivotal to both quantitative trading and investing, which are intricate fiscal processes. The delicate and largely stochastic stock vaticination problem has seen substantial development due to deep literacy advances, yet current results have two major downsides. They disregard the rich signals between associated stocks' temporal price oscillations and don't incontinently optimize the investment end in terms of profit. expanding upon these restrictions. Investors generally prefer portfolios with minimum correlations among their means in order to reduce the threat associated with connected means. The" Mercury" frame, a new system of stock webbing, is introduced in this passage. Your plutocrat grows as a result of its capability to observe the request, acclimate to changes, and elect a collection of stocks that will not all vanish at formerly.
Observing CAPTCHAS “in the Wild”

For nearly two decades, CAPTCHAS have been widely used as a means of protection against bots. As their use grew, techniques to defeat or bypass them continued to improve, while, CAPTCHAS evolved in terms of sophistication and diversity, becoming increasingly difficult to solve for both bots (machines) and humans. Given this long-standing and still-ongoing arms race, it is both timely and important to investigate the user burden of solving current CAPTCHAS , and how they are perceived by users. This work [27] explores CAPTCHAS in the wild by evaluating solving performance and user perceptions of unmodified currently-deployed CAPTCHAS . We obtain this data through manual inspection of popular websites and a large-scale user study wherein 1 , 400 participants collectively solved 14 , 000 CAPTCHAS . Results show significant differences between most popular types of CAPTCHAS : surprisingly, solving time and user perception are not always correlated. We performed a comparative analysis of effects of experimental context , focusing on the difference between solving CAPTCHAS directly as opposed to solving them as part of a more natural task, such as account creation. While there were several potential confounding factors, results show that experimental context might impact this task, and must be taken into account in future CAPTCHA studies. Finally, we investigated CAPTCHA - induced user task abandonment by analyzing sessions where participants began, and did not complete, the task.
Narrative Advertising and Implicit Persuasion: The Loss of Persuasive Potential

Building on transportation theory, consumer persuasion knowledge, and para-social interaction, this study explores a potentially limiting aspect of the persuasive potential of narrative advertisements. Given the indirect transfer of meaning of narrative advertisements, consumers might perceive this form of advertising as a form of implicit persuasion attempt. This activates consumer persuasion knowledge, and consumers feel that their personal freedom is threatened and counterarguing against the message is elicited. Interestingly, the results of the study suggest that narrative advertisements can be transporting but at the same time elicit counterarguing originating in a threat to freedom. This highlights the potential downside of narrative ads, and more importantly, it suggests that a reduction in counterarguing might not be a primary mechanism by which narrative ads persuade consumers. In spotlight of the results of this study, the persuasive potential and the associated negative aspects of implicit persuasion appeals in narrative ads should be subjected to further research.
Is rebound effect ‘a cost’ or ‘a benefit’? Evidence from China’s urban households

Rebound effect is recognized as a loss ratio of energy savings or environmental emission reductions. But, this research suggests a positive side of rebound effect to consumers – welfare effect. We define the welfare effect using a dual form to rebound effect, explain its mechanism in the same economic framework with rebound effect, and give its estimation formula using Taylor expansion. Four consumer types are classified according to the sizes of rebound effect and welfare effect, and the determinants of the classification are discussed. We then conduct empirical research on both rebound effect and welfare effect for urban residents in China. We find backfire and large welfare effect, revealing that the urban residents in China are likely to remain ‘ the insufficient in demand’ for a long period. Besides, rebound effect tends to decline and welfare effect to increase when energy efficiency measures are enhanced.
Age Estimation and Sex Determination Using Raman Spectra of Human Dentine

Objectives This study aimed to determine the sex and estimate the age of individuals by analysing Raman spectra obtained from extracted teeth dentine. Material and methods A total of 25 male and 26 female extracted teeth were collected, disinfected, and fixed in auto acrylate before being cut near the cervical margin. The inclusion criteria were non endodontically treated teeth with the cervical third of the tooth crown preserved. The exposed dentine was recorded using a Raman spectrometer, with 100 scans per dentine site in the spectral range of 3500 to 200 cm-1 and a resolution of 4 cm-1. Background-corrected, normalized, and decomposed spectra were subjected to principal component analysis using MATLAB 2010 (The MathWorks, Natick, MA, USA). To assess age differences, prominent vibrational bands were observed and statistically analyzed, while sex differentiation employed the T-test on acquired data, exploring vibrational bands with significant intensity differences. Results The obtained results revealed a segmentation of spectra in the male sample group based on the age of teeth at extraction, with an accuracy of age estimation at 7.0048 years. A similar segmentation was observed in the female sample group, with an accuracy of 9.3863 years. Conclusion The recorded spectra were organized into datasets and analyzed with principal component analysis, demonstrating the feasibility of sex determination and age estimation using Raman spectra of teeth. Differences in classification accuracy between sexes may be attributed to hormonally-mediated differences in the biochemical composition of dentine between males and females. The findings of this study can provide valuable insights into methods for forensic and anthropological applications.
Exploring the Relationship between CLPTM1L-MS2 Variants and Susceptibility to Bladder Cancer

CLPTM1L (Cleft Lip and Palate Transmembrane Protein 1-Like) has previously been implicated in tumorigenesis and drug resistance in cancer. However, the genetic link between CLPTM1L and bladder cancer remains uncertain. In this study, we investigated the genetic association of variable number of tandem repeats (VNTR; minisatellites, MS) regions within CLPTM1L with bladder cancer. We identified four CLPTM1L-MS regions (MS1~MS4) located in intron regions. To evaluate the VNTR polymorphic alleles, we analyzed 441 cancer-free controls and 181 bladder cancer patients. Our analysis revealed a higher frequency of specific repeat sizes within the MS2 region in bladder cancer cases compared to controls. Notably, 25 and 27 repeats were exclusively present in the bladder cancer group. Moreover, rare alleles within the medium-length repeat range (25–29 repeats) were associated with an elevated bladder cancer risk (odds ratio [OR] = 5.78, 95% confidence interval [CI]: 1.49–22.47, p = 0.004). We confirmed that all MS regions followed Mendelian inheritance, and demonstrated that MS2 alleles increased CLPTM1L promoter activity in the UM-UC3 bladder cancer cells through a luciferase assay. Our findings propose the utility of CLPTM1L-MS regions as DNA typing markers, particularly highlighting the potential of middle-length rare alleles within CLPTM1L-MS2 as predictive markers for bladder cancer risk.
Theoretical and observational aspects of the variation of fundamental constants of Nature

The fundamental constants of Nature play a crucial role in our understanding of the Universe. They represent the limits of our knowledge of the laws of Physics but at the same time encode new phenomena yet to be discovered. In recent years, an enormous observational effort has been devoted to study the possible variation in space and time of some of these fundamental constants. Such a discovery would have deep consequences in our current models for physical interactions, and in particular for the theoretical framework behind gravitation. Astrophysics and Cosmology provide us with a great window to look for any variation, with space and time scales ranging from the Solar System to the whole observable Universe and its origin. On the other side, theoretical models to accommodate variation of fundamental constants are also being actively explored. This thesis is divided into an observational analysis and a theoretical study. First, we present the most precise observational constraint to date for the cosmological variation of the fine structure constant using emission lines present in quasar spectra up to redshift z = 1. From the Sloan Digital Sky Survey Quasar Catalog (Data Release 12), we build a sample of 13 175 quasar spectra showing the [O iii] doublet ( 4960; 5008 A). Then, by measuring the separation between both lines we obtain the following relative constraint on the time variation of the fine structure constant = ¹0:9 1:8o 105. We also impose limits on its variation in redshift bins ( z 0:06) over the last 7.9 Gyr at the 104 level. Several sources of systematics are analyzed including sky contamination and line blendings. In the second part, we explore a theoretical mechanism producing expectations values of scalar fields to depend on the gravitational potential. To have varying expectation values is one of the usual ways to accommodate variation of fundamental constants. We develop a formalism that enables us to compute the complete one-loop quantum corrections to the effective potential and energy momentum tensor of scalar fields arising in the presence of gravity. This formalism provides the local part, usually computed with the well-known DeWitt-Schwinger expansion, but it would also allow to obtain the non-local contributions. Assuming weak and slowly varying gravitational fields, we obtain a complete set of mode solutions for the Klein-Gordon equation in perturbed Friedmann-Robertson-Walker geometries at leading order in the adiabatic approximation. Then, we compute the corresponding expectation values of a self-interacting scalar field as a mode summation in different quantum states and apply dimensional regularization to obtain the final contributions. Although there is no effect due to metric perturbation in vacuum states, there are thermal corrections that could modify the expectation value of scalar fields
Uttern i Västernorrland - resultat från inventeringar 1989-2005

Spillningsinventeringar av utter i Vasternorrlands lan utfordes forsta gangen hostarna 1989 och 1990. Den sodra delen av lanet inventerades 1989 och den norra 1990. Under inventeringen hittades sak .
Robust optimal identiﬁcation and scheduling of modernization measures for typical buildings

Optimization approaches for the modernization of buildings mostly consider one-time investments for the design decision. Also the uncertainty of boundary conditions is rarely taken into account. In this work, we propose a robust extension of a mixed-integer linear program that determines modernization schedules considering multiple points in time for the design decision. An initially conducted sensitivity analysis of the original model reveals high inﬂuences of user behavior, emission factors and economic parameters on the objectives and design decisions. By applying the method to a typical building, it is shown that robust diﬀer from nominal solutions. The shown investigation of diﬀerent degrees of robustness should facilitate the decision for a modernization path in the future.
JOURNAL OF LANGUAGE AND LINGUISTIC STUDIES

Machine Translation (MT) has the potential to provide instant translation in times of crisis. MT provides real solutions that can remove borders between people and COVID-19 information. The widespread of MT system makes it worthy of scrutinizing the capacity of the most prominent MT system, Google Translate, to deal with COVID-19 texts into Arabic. The study adopted (Costa et al., 2015a) framework in analysing the output of Google Translate output service in terms of orography, grammar, lexis, and semantics. The study’s corpus was extracted from World Health Organization (WHO), United Nations Children’s Emergency Fund (UNICEF), U.S. Food and Drug Administration (FDA), the Foreign, Commonwealth & Development Office (FCDO), and European Centre for Disease Prevention and Control (ECDC). The paper reveals that Google Translate committed a set of errors: semantic, grammatical, lexical, and punctuation. Such errors inhibit the intelligibility of the translated texts. It also indicates that MT might work as an aid to translate general information about COVID-19, but it is still incapable of dealing with critical information about COVID-19. The paper concludes that MT can be an effective tool, but it can never replace human translators.
Research on the Impact of Governance Structure on the Cost of Equity Capital of Food Businesses Listed on the Vietnam Stock Market

In this article, the author analyzes the relationship between corporate governance and the cost of equity capital at businesses. The study's data is based on a sample of 55 food businesses listed on the Vietnamese stock market in the period 2015-2022. In this study, the author focuses on the Vietnamese market with the expectation that differences in the economy and characteristics of market mechanisms in other countries will have different impacts on corporate governance. business and cost of equity capital. The author measures the characteristics of corporate governance through: the number of independent members of the board of directors, concurrent CEOs, the CEO's tenure, the number of board meetings and the presence of committees. nomination committee. The author focuses on food businesses because this is a conditional business that directly affects the health of consumers and is supervised by authorities. Research results have shown that management Corporate governance has a negative impact on the Cost of Equity (COE), which means that when the role of corporate governance is enhanced, businesses will enjoy a reduced COE level.
Tamoxifen blocks retrograde traf ﬁ cking of Shiga toxin 1 and 2 and protects against lethal toxicosis

Shiga toxin 1 (STx1) and 2 (STx2), produced by Shiga toxin – producing Escherichia coli , cause lethal untreatable disease. The toxins invade cells via retrograde traf ﬁ cking. Direct early endosome-to-Golgi transport allows the toxins to evade degradative late endosomes. Blocking toxin traf ﬁ cking, particularly at the early endosome-to-Golgi step, is appealing, but transport mechanisms of the more disease-relevant STx2 are unclear. Using data from a genome-wide siRNA screen, we discovered that disruption of the fusion of late endosomes, but not autophagosomes, with lysosomes blocked the early endosome-to-Golgi transport of STx2. A subsequent screen of clinically approved lysosome-targeting drugs identi ﬁ ed tamoxifen (TAM) to be a potent inhibitor of the traf ﬁ cking and toxicity of STx1 and STx2 in cells. The protective effect was independent of estrogen receptors but dependent on the weak base property of TAM, which allowed TAM to increase endolysosomal pH and alter endosomal dynamics. Importantly, TAM treatment enhanced survival of mice injected with a lethal dose of STx1 or STx2. Thus, it may be possible to repurpose TAM for treating Shiga toxin – producing E. coli infections.