Miracle-dz/UniFAR-FTUs huggingface dataset:
129.RS and GIS Aided Study on Tempo-spatial Differences of EcologicalWater Requirement at Landscape Scale in Weihe Sub-watershed

At present, the related studies mainly target single ecosystem, but the further studies on the critical thresholds of ecological water requirement for composite ecosystem are needed. Therefore, we select the plant-soil combined system in Weihe sub-watershed as a research object. Firstly, we obtain the spatial distribution maps of plant and soil types based on the TM remote sensing images and the soil texture data. Also, we use the corresponding mathematical models to evaluate the ecological water requirement of the plant-soil composite system at landscape scale and analyse the tempo-spatial distribution characteristics based on RS and GIS technologies. Then, we get the following results: 1) According to the spectral and texture characteristics of TM remote sensing images, we divide the land cover into woodland, arable land, grassland, waters, construction land and unused land. From 2000 to 2010, the areas of woodland and construction land increased obviously while the areas of arable land and unused land decreased. These changes indicate the ecological improvement and economic development. 2) At the temporal scale, with the increase of plant areas year by year, the amount of minimum ecological water requirement in Weihe sub-watershed increased accordingly. Therein, the amount of minimum ecological water requirement of woodland-clay loam changed most obviously, with an increase of 656.215×10m; while the amount of minimum ecological water requirement of woodland-gravel loam decreased a little with the value of 7.966× 10m. 3) At the spatial scale, the amounts of minimum ecological water requirement are different significantly among the plant-soil landscapes in Weihe sub-watershed. Therein, the landscape types of higher ecological water requirement per unit area are woodland-clay loam, woodlandloam, woodland-sandy loam and woodland-gravel loam, and the water requirements ranged from 0.4621 to 0.5023 m/m. The landscape types of lower ecological water requirement per unit area are grassland-clay loam, grassland-loam, grassland-sandy loam and grass-gravel loam, and the water requirements ranged from 0.2813 to 0.3216 m/m. In general, because of the higher evapotranspiration from woodlands, the ecological water requirements of woodlands are higher than that of grasslands. The study offers scientific references for making the target of the regional hydrological ecological environment protection and plays a positive role in rational allocation of water resources.
Realizability , Covers , and Sheaves II . Applications to the Second-Order Lambda-Calculus

We present a general method for proving properties of typed λ-terms. This method is obtained by introducing a semantic notion of realizability which uses the notion of a cover algebra (as in abstract sheaf theory, a cover algebra being a Grothendieck topology in the case of a preorder). For this, we introduce a new class of semantic structures equipped with preorders, called pre-applicative structures. These structures need not be extensional. In this framework, a general realizability theorem can be shown. Applying this theorem to the special case of the term model, yields a general theorem for proving properties of typed λ-terms, in particular, strong normalization and confluence. This approach clarifies the reducibility method by showing that the closure conditions on candidates of reducibility can be viewed as sheaf conditions. Part II of this paper applies the above approach to the second-order (polymorphic) λ-calculus λ→,∀2 (with types → and ∀). Comments University of Pennsylvania Department of Computer and Information Science Technical Report No. MSCIS-93-47. This technical report is available at ScholarlyCommons: http://repository.upenn. edu/cis_reports/281 Realizability, Covers, and Sheaves. 11. Applications to the Second-Order Typed A-Calculus
UvA-DARE (Digital Academic Repository) Something interacting and solvable in 1D

We present a two-parameter family of exactly solvable quantum many-body systems in one spatial dimension containing the Lieb – Liniger model of interacting bosons as a particular case. The principal building block of this construction is the previously-introduced (Stouten et al 2018 arXiv:1712.09375) family of two-particle scattering matrices. We discuss an SL ( 2 ) transformation connecting the models within this family and make a correspondence with generalized point interactions. The Bethe equations for the ground state are discussed with a special emphasis on ‘ non-interacting modes ’ connected by the modular subgroup of SL ( 2 ) . The bound state solutions are discussed and are conjectured to follow some correlated version of the string hypothesis. The excitation spectrum of the new models in this family is derived in analogy to the Lieb – Liniger model and we show that for certain choices of parameters a spectrum inversion occurs such that the Umklapp solutions become the new ground state.
Experimental Observations of the Visibility Threshold of Illusory effects in Hermann Grid, Sinusoidal and Square Gratings and their Possible Implications

Experimental studies have been conducted on the Sinusoidal Grating, Square Grating and Hermann Grid Illusions. Volunteers were presented with a range of input stimuli and asked to report the perceptibility of the illusory effect. We tried to find the thresholds for the parameters within which the illusion is visible. Some noteworthy observations were made from these experiments. We have observed that the length scale of the illusory effect changes with the typical length scale of the input stimulus, almost in proportion, wherefrom one can draw the conclusion that most spatial filters, possessing typical length scales of their own, would not respond to stimuli much smaller or much larger than that typical length scale. We have also found that even tiny changes to the pattern of the Hermann grid illusion is sufficient to wipe out the illusion completely, i.e. the illusion is very sensitive to tiny changes in the input stimulus. These observations indicate that simple linear models such as the DOG (Difference of Gaussians) model or even the highly successful ODOG (Oriented Difference of Gaussians) model of brightness perception are actually inadequate for explaining such effects. The present work thus bears implication for future efforts towards modeling the human visual system, by pointing out certain features that such models must exhibit.
Factors That Influence Women Entrepreneurs in Women-Headed Families: A Case Study of Ammachchi Canteens in the Jaffna District, Sri Lanka.

: In general, there are different types of pull and push factors that are encouraging both males and females to become entrepreneurs, but the authors of this article identified that the same push and pull factors are acting in different ways according to the different situations. Therefore, the main purpose of this article is to find out how push and pull factors are affecting women-headed families in Jaffna District in the Northern Province of Sri Lanka. The data were collected through semi-structured interviews with 10 randomly selected women entrepreneurs in the Ammachchi canteens in the Jaffna District, in the Northern Province of Sri Lanka, because most of the women entrepreneurs at Ammachchi are the heads of their families due to the loss of their husbands. Further, this study is a qualitative case study, and data analysis was done through both narrative and thematic analysis methods; moreover, in this article, the authors selected family support, opportunity, education, network, independence, competition, and capital as pull factors in order to find out what factors are affecting women to start their businesses at Ammachchi. As a result of this study, the authors found that family support and opportunity factors are positively affecting, and education is negatively affecting these women entrepreneurs at Ammachchi under the push factors; then, network is a neutral factor at Ammachchi, but independence and competition are negative factors, and capital is acting as a positive factor under the pull factors.
Effect of gravity on Non-Linear Modeling and Stability of a Pneumatic Levitation System

Pneumatic applications are currently focused on industrial force processes such as pistons and levers, but this resource can be used to generate other types of applications such as automatic transport of objects with high precision through the application of control techniques on the position of the mentioned objects, the present work shows a proposal of non-linear dynamic modeling of a pneumatic levitator with a different approach to previous works, considering the gravitational force as a constant input of the system.In common mechanical systems the gravitational force is omitted when considering part of elastic systems, in this case the object to levitate does not have an elastic component so it is essential to consider gravity and its effect on the position of the object obtained from the non-linear model, its output was checked before different stimuli and it was compared with a response curve of a real model, the results were suitable since the responses were very similar, in addition an attempt to linearize the two-input mode was madel in order to study its stability and controllability and identify a suitable linear or non-linear regulator in subsequent lines of work without the need for a physical model.
A Review of Challenges to Security in IoT

As smart devices are increasingly getting deployed in distinct scenarios it is important to examine how the various demands of these practical uses will affect the dynamics of protection. The Internet of Things (IoT) is a long-term technological vision in which items will be able to speak with one another and connect to the internet to create self-configuring, intelligent systems. The majority of IoT apps complete tasks without the involvement of humans or physical objects. Current and future gadgets must be smart, efficient, and capable of providing services to users in order to deploy such a new technology in a secure manner. As a result, researchers are investigating security concerns on a daily basis. As IoT devices are so small and light, they have a number of difficulties, including battery consumption, memory and as they operate over a wide range they have the issues of security also. We have discussed security attacks with reference to several types of IoT layers in this review paper.
Diversifying Domestic Tourism Products in the Context of the Covid-19 Epidemic: A Case of Vietnam

- The COVID-19 pandemic has caused borders to be closed, inbound and outbound tourism in Vietnam and other countries around the world completely frozen, and this is also considered the time when domestic tourism is fully utilized. But for domestic tourism to really become a lever for the entire tourism industry, which is struggling during the pandemic, is a rather difficult problem for managers and travel businesses. Many problems and solutions from the practice of managing over nearly two years of living with the COVID 19 pandemic have been proposed by managers, businesses, and travel associations. This article compares current and previous research results in order to find appropriate solutions to contribute to the sustainable development of the tourism economy. The results show that the diversification of tourism products is quite necessary. We need to be more proactive and gradually adapt to the pandemic. In addition to product diversification, advertising, linking regions as well as amending regulations is extremely urgent today.
Attributing Changing Rates of Temperature Record Breaking to Anthropogenic Influences

Record‐breaking temperatures attract attention from the media, so understanding how and why the rate of record breaking is changing may be useful in communicating the effects of climate change. A simple methodology designed for estimating the anthropogenic influence on rates of record breaking in a given time series is proposed here. The frequency of hot and cold record‐breaking temperature occurrences is shown to be changing due to the anthropogenic influence on the climate. Using ensembles of model simulations with and without human‐induced forcings, it is demonstrated that the effect of climate change on global record‐breaking temperatures can be detected as far back as the 1930s. On local scales, a climate change signal is detected more recently at most locations. The anthropogenic influence on the increased occurrence of hot record‐breaking temperatures is clearer than it is for the decreased occurrence of cold records. The approach proposed here could be applied in rapid attribution studies of record extremes to quantify the influence of climate change on the rate of record breaking in addition to the climate anomaly being studied. This application is demonstrated for the global temperature record of 2016 and the Central England temperature record in 2014.
Acetylcholine decreases formation of

Acetylcholine (ACh) has been reported to play various physiological roles, including wound healing in the cornea. Here, we study the role of ACh in the transition of corneal fibroblasts into myofibroblasts, and in consequence its role in the onset of fibrosis, in an in vitro human corneal fibrosis model. Primary human keratocytes were obtained from healthy corneas. Vitamin C (VitC) and transforming growth factor-β 1 (TGF-β 1) were used to induce fibrosis in corneal fibroblasts. qRT-PCR and ELISA analyses showed that gene expression and production of collagen I, collagen III, collagen V, lumican, fibronectin (FN) and alpha-smooth muscle actin ( α -SMA) were reduced by ACh in quiescent keratocytes. ACh treatment furthermore decreased gene expression and production of collagen I, collagen III, collagen V, lumican, FN and α -SMA during the transition of corneal fibroblasts into myofibroblasts, after induction of fibrotic process. ACh inhibited corneal fibroblasts from developing contractile activity during the process of fibrosis, as assessed with collagen gel contraction assay. Moreover, the effect of ACh was dependent on activation of muscarinic ACh receptors. These results show that ACh has an anti-fibrotic effect in an in vitro human corneal fibrosis model, as it negatively affects the transition of corneal fibroblasts into myofibro-blasts. Therefore, ACh might play a role in the onset of fibrosis in the corneal stroma.
Performance Statistical Evaluation of Deep Learning Classifiers for Handwritten Character Recognition

Text classification is a well formed process using various measurable properties and computerized logical procedure to fetch a pattern from different classes. Since classification is important for the pattern recognition process, there are some issues with well-formed classification in this process, which is one of the important issues for proper development and improvement of productive data examinations. On behalf of the versatility of learning and the ability to deal with complex calculations, classifiers are consistently best suited for design pattern recognition issues. This paper aims to present a result based comparative study of different classifiers and the optimal recognition of results computation through the Devanagari Handwritten characters and numerical values. Different classifiers were used and evaluated in this investigation including k-Nearest Neighbor (k-NN), Support-Vector machine (SVM), Naïve Bayes, Decision Tree, Random Forest, and Convolution Neural Network (CNN). To accomplish the experiment purpose, this paper used an unbiased dataset with including 123 samples that consists of 123 characters and 123 numerical values. Python 3.0 with sciket learn machine learning open-source environment library have been used to evaluate the performance of the classifiers. The performances of the classifiers accessed by considering the different matrices including dataset volume with best split ratio among training, validation, and testing process, accuracy rate, Ture/False acceptance rate, True/False rejection rate and the area covered under the receiver operating characteristic curve. Similarly the paper shows the correlation of the accuracy of the experiments obtained by applying to chosen the classifier. On behalf of the exploratory results, the infallible classifiers considered in this test have free rewards and must be executed in a hybrid manner to meet the thigh precision rates. In the views of test work, their result compressions and the examination to be performed, it is argued that the Random Forest classifier is performing in a way that the current use of the classifier to recognize the Devanagari Handwritten character and the numerical values with the accuracy rate 87.9% for the considered 123 samples.
Creation of a novel usability test and conducting it on music streaming applications

In this thesis a usability test has been created and conducted on three prominent music streaming applications: Spotify, Apple Music and Deezer. The aim of the study is to evaluate the usability of these platforms through a comprehensive usability test, which applies eight usability principles. The thesis also aims to serve as a possible guide for creation of future usability tests. The research questions of this thesis focus on the creation of a tailored usability test, the performance of the applications under the test and the correspondence between the results of the usability test and global popularity of the applications. The usability test involved twelve carefully selected participants. Each participant completed a list of tasks and then rated their experience of using respective application in a retrospective interview. Descriptive statistics were applied to analyse the results, revealing Spo-tify and Apple Music as equally user-friendly with each showing the best results in four out of eight principles. There were minimal differences between the two, but both had significantly better scores than Deezer. The analysis of the correspondence with global popularity shows a match for the Deezer app. However, the difference in the popularity of the other two apps is not reflected in the results of the test. Limitations of the thesis include biases in selection of the participants.
Working Paper Series Satellites turn “concrete”: tracking cement with satellite data and neural networks

This paper exploits daily infrared images taken from satellites to track economic activity in advanced and emerging countries. We first develop a framework to read, clean, and exploit satellite images. Our algorithm uses the laws of physics (Planck’s law) and machine learning to detect the heat produced by cement plants in activity. This allows us to monitor in real-time whether a cement plant is working. Using this information on around 500 plants, we construct a satellite-based index tracking activity. We show that using this satellite index outperforms benchmark models and alternative indicators for nowcasting the production of the cement industry as well as the activity in the construction sector. Comparing across methods, we find neural networks yields significantly more accurate predictions as they allow to exploit the granularity of our daily and plant-level data. Overall, we show that combining satellite images and machine learning allows to track economic activity accurately.
Improving Pseudo Labels for Open-Vocabulary Object Detection

Recent studies show promising performance in open-vocabulary object detection (OVD) using pseudo labels (PLs) from pretrained vision and language models (VLMs). However, PLs generated by VLMs are extremely noisy due to the gap between the pretraining objective of VLMs and OVD, which blocks further advances on PLs. In this paper, we aim to reduce the noise in PLs and propose a method called online Self-training And a Split-and-fusion head for OVD (SAS-Det). First, the self-training finetunes VLMs to generate high quality PLs while prevents forgetting the knowledge learned in the pretraining. Second, a split-and-fusion (SAF) head is designed to remove the noise in localization of PLs, which is usually ignored in existing methods. It also fuses complementary knowledge learned from both precise ground truth and noisy pseudo labels to boost the performance. Extensive experiments demonstrate SAS-Det is both efficient and effective. Our pseudo labeling is 3 times faster than prior methods. SAS-Det outperforms prior state-of-the-art models of the same scale by a clear margin and achieves 37.4 AP 50 and 27.3 AP r on novel categories of the COCO and LVIS benchmarks, respectively.
Churn Prediction Model using Hierarchical clustering and Customer Retention using Probability Model

Database of telecom industries have unstructured data in today’s world. Researches to identify Data analysis tool which can format all these business data, have been undergoing. Another challenge that Telecom industries has is the churn prediction and problems in retaining customers. Recommended approach can overcome problems of unstructured data as it converts them to structured format with the help of prediction model and classification of customers. This approach makes use of the data preprocessing technique which can minimize the high dimensional data with the help of feature selection. The customer classification is performed with the help of the k-nearest neighbor to churn customer and non-churn customer. CLV (customer life time value) is found by using the probability model which is the second proposed method. The higher CLV value refers to the longer time retention of customer. Results: The proposed framework is implemented with MATLAB R 2014b software and its results are conferred. Conclusion: Considering current competitive telecom domain market, churn prediction becomes crucial issue in CRM. This actual issue in CRM is to sustain valuable customers in finding same set of customers and giving best services/offers which are competitive to associated groups. Hence, there are researches in progress to look for Churn’s key parameters to preserve customer and provide resolution to CRM problems and making company decisions. Data analytics and data validation which is derived through standard evaluation metrics, are provided with a customer churn model in this study. The identified results states that our recommended churn model worked better with the help of techniques in machine learning. K-nearest neighbor 90% and RNN generated better F-measure result which is almost 95%.
Protecting the proper Baltic harbour porpoise An evaluation of Sweden’s conservation plan

More than a third of the earths marine mammal species are threatened. This study aims to analyze and evaluate the conservation of the proper Baltic harbour porpoise in Sweden. The population is estimated to consist of only 500 individuals and are likely to be extinct if measures are not taken. A new Swedish conservation plan for harbour porpoises will be implemented in 2021 and will be the first since 2013. This study analyzes the suggested conservation plan and aims to identify strengths and weaknesses in the actions. Through a grounded theory approach, a qualitative content analysis is performed to identify the action strengths and weaknesses. A scoring matrix was developed to create indicators of the actions effort, delivery and conservation. The findings show that the short-term goals and the actions have a multidirectional approach which lack an alignment to the vision and the long-term goal of the plan. The study presents the action efficiency which shows the need for, and importance of prioritizing the actions with the most potential impact for conservation. Mainly, the study provides a framework for species conservation plan evaluation and by performing the plan evaluation prior to implementation, the study contributes to the field of environmental evaluations.