Miracle-dz/UniFAR-FTUs huggingface dataset:
1 GIS Litigation Support Applications in the Courtroom

GIS as a technology has proven to have many different applications in various fields of study. One tangible application of GIS is in the courtroom, as support in either the defense or prosecution of parties under the law. Two case studies in this paper will be examined to demonstrate the applicability of GIS applications as litigation support. One study focuses on the use of three-dimensional GIS tools to quantify illegal dumping amounts on a property and prosecuting the responsible offending party. The second case study shows an approach to integrating a soil erosion and transport model into GIS to assist in the defense of a county government from a litigation suit filed by residents impacted by excessive sedimentation. Development of GIS tools for litigation support, as examined in this study, display how GIS technology can be successfully implemented to assist parties in litigation, ultimately enabling them to determine the truth. INTRODUCTION With the advent of newer GIS technologies, tools have been developed to help model and quantify changes in the environment. These changes, when quantified, can be very powerful evidence in a court of law. In this paper two cases are examined in this paper that employed GIS technology to quantify environmental impacts to assist in identifying responsible parties, and in effect allocate responsibility. The first case involved a county government that was alleged by a group of residents to have caused adverse impacts to surface water due to land disturbing activities. Residents claimed the County was the primary source of excessive sedimentation in trout streams and lakes located on and near their properties, and demanded that the County fix the problem to restore natural conditions. In this case study, GIS techniques in conjunction with satellite imagery and aerial photography were applied to determine the County’s relative contribution to sedimentation in a small North Georgia watershed. The second case involved a small business owner that was charged by a real estate company for illegal waste disposal on their undeveloped property. Brown and Caldwell provided litigation support to the real estate company and used GIS methods to substantiate criminal charges against the small business owner, and further to file suit against the waste owners to recoup the cost of cleanup. A CASE OF DEFENSE: GIS USED TO IDENTIFY SEDIMENT SOURCES IN THE BLUE RIDGE MOUNTAINS
Face Anti-Spoofing: Model Matters, so Does Data

Face anti-spoofing is an important task in full-stack face applications including face detection, verification, and recognition. Previous approaches build models on datasets which do not simulate the real-world data well (e.g., small scale, insignificant variance, etc.). Existing models may rely on auxiliary information, which prevents these anti-spoofing solutions from generalizing well in practice. In this paper, we present a data collection solution along with a data synthesis technique to simulate digital medium-based face spoofing attacks, which can easily help us obtain a large amount of training data well reflecting the real-world scenarios. Through exploiting a novel Spatio-Temporal Anti-Spoof Network (STASN), we are able to push the performance on public face anti-spoofing datasets over state-of-the-art methods by a large margin. Since the proposed model can automatically attend to discriminative regions, it makes analyzing the behaviors of the network possible.We conduct extensive experiments and show that the proposed model can distinguish spoof faces by extracting features from a variety of regions to seek out subtle evidences such as borders, moire patterns, reflection artifacts, etc.
Cybersecurity - Software Engineering, 2003. Proceedings. 25th International Conference on

As more business activities are being automated and an increasing number of computers are being used to store sensitive information, the need for secure computer systems becomes more apparent. This need is even more apparent as systems and applications are being distributed and accessed via an insecure network, such as the Internet. The Internet itself has become critical for governments, companies, financial institutions, and millions of everyday users. Networks of computers support a multitude of activities whose loss would all but cripple these organizations. As a consequence, cybersecurity issues have become national security issues. Protecting the Internet is a difficult task. Cybersecurity can be obtained only through systematic development; it can not be achieved through haphazard seat-of-the-pants methods. Applying software engineering techniques to the problem is a step in the right direction. However, software engineers need to be aware of the risks and security issues associated with the design, development, and deployment of network-based software. This paper introduces some known threats to cybersecurity, categorizes the threats, and analyzes protection mechanisms and techniques for countering the threats. Approaches to prevent, detect, and respond to cyber attacks
Medical Image Enhancement using Fuzzy and Regression based Neural Network Approach

The basic purpose of the image enhancement is digitally manipulating the image to improve the quality of the image. It is found to be the simplest division of the medical image processing and is used to extract the required portion of the image. This proposed paper presents a neural based fuzzy enhancement technique. The pre-processing of the images is performed by the wiener filter and the contrast enhancement is obtained by the local transform histogram (LTH). The enhanced image obtained is given to neural based fuzzy enhancement which performs the process in three steps such as fuzzification, membership function and defuzzification. The evaluated parameters such as PSNR (peak signal to noise ratio) and CNR (Contrast to noise ratio) of the proposed technique are compared with different types of result images of different methods and it is found that the proposed method has highest PSNR value.
Application of Metal-Free Click Chemistry in Biological Studies

Abstract: The first reported click reaction, copper(I)-catalyzed azide-alkyne 1,3-dipolar cycloaddition had limited biocompatibility due to the high toxicity of copper. Since alternative bioorthogonal click reactions have been developed, they have strongly influenced the field of chemical biology. Here are summarized three main metal-free click methodologies based on cycloaddition, Staudinger and thioene reactions. This review contains the basic principles, some mechanistic considerations and a collection of reagents that can be used in each method. Firstly, Diels-Alder and strain promoted inverse electron demand Diels-Alder cycloadditions are outlined together with triazole and isoxazole formation by 1,3-dipolar cycloadditions. Secondly, Staudinger-Bertozzi ligation, a chemoselective reaction of azides and engineered triarylphosphines, is discussed. Finally, thio-click chemistries including thiol-ene, thiol-yne, thio-Michael and fluoro-thioclick reactions are reviewed. Among the most important bioapplications of these click methodologies is the labeling of glycans, proteins, lipids and DNA. Additionally, synthetic methods and surface immobilization of biomolecules and biologically useful polymeric materials are also reviewed.
Mechanical pulping

A series of chipping experiments were performed under both dynamic and quasi-static conditions in a laboratory wood chipper (dynamic) and in a MTSservohydraulic testing machine (quasi-static). One aim with the experiments was to investigate the rate dependency of the energy consumption during chipping. Another aim was to try to determine the load per unit knife edge length required to initiate cutting. The experiments were carried out using different combinations of spout and edge angles. It was found that for large edge angles (keeping the spout angle constant at 30°) there was a slight rate dependency such that the energy consumption was larger at higher cutting rates which is quite in opposite of what is expected if wood is assumed to be a viscoelastic material. It was also found that to determine the force at initiation of cutting, is not a trivial task. Both Acoustic Emission monitoring andvisual inspectionwasused to this end. The wood species used in this study was pine (Pinus silvestris).
EXPONENTIAL STABILITY ANALYSIS OF FUNCTIONAL OBSERVER FOR NONLINEAR SYSTEM WITH INTERVAL TIME-VARYING MIXED DELAYS

This paper investigates exponential stability of functional observer for a class of nonlinear systems with interval time-varying mixed delays. We first address the problem of functional observer design for nonlinear systems with interval time-varying mixed delays and establish the sufficient conditions of exponential stability of functional observer for this class of systems. Second, by utilizing Lyapunov-Krasovskii approach and some well-known inequalities, we convert the stability analysis problem into the feasible problem of several linear matrix inequalities (LMIs). We proposed sufficient conditions of the exponential stability of functional observer for nonlinear systems with interval time-varying mixed delays. Furthermore, the parameters of the delay-dependent observer are also designed using the Lyapunov-Krasovskii approach. Finally, we give two numerical examples and some simulation results to illustrate the effectiveness of the obtained method.
TO SPACE ENVIRONMENT MODELS AND DATABASES

Quantifying the space environment requires retrieval of spacecraft or ground based data and access to empirical or physical models. Many data providers are operational world wide, but they employ various methods and forms of data delivery and it is often a daunting task to locate, retrieve, extract and re-format the relevant data. Services providing remote access to space environment models are not so numerous (the SPENVIS [1] system is one example of such a service). In the framework of a prototyping activity, part of an ESA space weather programme study [2], an integrated system has been developed to access in a uniform way both models and databases [3]. Results of this prototype activity are presented as well as some suggestions to standardize remote access to space environment data and models.
Extensions for a surface-volume reaction model with application to optical biosensors

Surface-volume reactions are an important area for continued mathematical analysis due to many biological and chemical applications, including increased use of optical biosensors such as the Flexchip. We extend a mathematical model for ligand concentration and bound ligand concentration in the reaction-limited case for unidirectional flow, with special attention for the application to optical biosensors. For a single reacting zone with uniform or nonuniform receptor concentration, we obtain an explicit expression for the average bound ligand concentration and compare results with numerical simulations. We also consider arrays of reacting zones having the same rate constants and generalize previous results for strips of reacting zones to more general zone geometries, with particular interest in the depletion effect for circular reacting zones. For reacting zones having different rate constants, we propose two models for average bound ligand concentration for individual reacting zones and discuss the applicability of each. We also consider two-dimensional flow within the Flexchip, relating this to the model for unidirectional flow using the Schwarz-Christoffel mapping, and compare ligand depletion within the device.
Cetacean Behavior Mechanisms And Functions

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Heterogeneity in Intangible Risk and Cross-Section Stock Return

With the rise of high technology producing companies, intangible capital becomes an important part of the capital of a modern economy. However, under current U.S. accounting standards, most of investment in intangible capital is expensed rather than capitalized, which complicates the valuation of corporate securities and the assessment of risk and return of investments. We find that it is crucial to recognize the heterogeneity in intangible capital and the risk and return differences in different types of intangible capital, and it is the key to dissect the “anomalies” in the stock market such as value premium and R&D anomaly. R&D expenses (developing intangible capital) to discover new technology and new products should be evaluated differently from the intangible investments to improve the existing process of production (embodied intangible capital). Embodied-intangible-capital intensive firms invest more aggressively in physical capital and have higher market value relative to book value of physical capital (lower B/M), and appear to be overvalued in an asset pricing model without intangible capital; while developing-intangible-capital intensive firms are riskier due to intensive R&D expenses are not yet embodied in the production process, appear to have weaker earnings and be undervalued in an asset pricing model with missing factor or intangible capital.
The Effect of PowerPoint Presentation on Grammar and Vocabulary Learning of Iranian Pre-University EFL Learners

The current study was an attempt to examine the effect of PowerPoint presentations on grammar and vocabulary learning of Iranian pre-university EFL learners. To meet the objectives of the present study, a mixed method research strategy was adopted. A multiple-choice test of grammar and vocabulary, the reliability of which was 0.79, was administered to a group of EFL students from which 54 students were selected and randomly divided into two groups of 27(a control group and an experimental group)as pretest – posttest design was used. Then, their pre and post test scores were compared using a paired-sample t -test. At the end of this period, the experimental participants were interviewed as to their idea of the impact of PowerPoint presentation on learning grammar and vocabulary. The findings of the study indicated that PowerPoint presentations can prove successful in enhancing the learners' grammar and vocabulary knowledge. It was also found tha the learners have a positive attitude towards the use of PowerPoint presentation. Results can have pedagogical implications for language teachers to use this technology as a useful way of teaching vocabulary and grammar.
Releasing Impact of the Predatory Gall Midge , Aphidoletes aphidimyza ( Rondani ) ( Diptera : Cecidomydae ) on Suppressing the Population of the Cotton Aphid , Aphis gossypii ( Golver . ) on Cucumber Plants

Efficacy of releasing the gall midge, Aphidoletes aphidimyza (Rondani) (Diptera: Cecidomydae) to suppress the population of the cotton aphid, Aphis gossypii (Glov.) infesting the protected cucumber plants was carried out in the experimental farm and laboratory of the Environmental Studies and Research Institute, Sadat City University, El Sadat district, Menofiya Governorate, Egypt during the two successive growing seasons, 2014 and 2015. Three release rates (3, 5 and 10 cocoons /m) of the predator for 3 releases at 14 days intervals were evaluated. Seedling of “Safa 62 F1” cucumber variety was planted under two high polytunnels. Randomized complete block design with 3 replicates was used. Results revealed significant potential efficacy of all releasing regimes against the pest population. The average lowest mean number of aphid (55.03 & 58.69 individuals/ leaf) was recorded at the rate of (10 predacious pupae/ m) in both seasons, respectively. In addition, this plot had the highest value of cucumber fruit yield (4.45 and 4.16 Kg/plant) in 2014 and 2015, respectively. Furthermore, moderate to relatively high suppression were also observed by releasing (3 and 5 cocoons/ m) as seasonal means of (284.24 and 69.55) and (314.05 and 74.81) individuals/ leaf were recorded and resulted to significant increases in fruit yield (3.13 and 3.9 Kg/plant) and (3.08 and 3.85 Kg/plant) in both seasons, respectively comparing to the control plot. Moreover, the results evidenced the vital role of the predator for suppressing the cotton aphid population in the protected cucumber.
ST 2104 attenuates neuronal injuries in Aβ 25-35-induced AD rats by inhibiting CRMP 2-NMDAR 2 B signaling pathways

Collapsin response mediator protein 2 (CRMP2), traditionally regarded as an axon/dendrite growth and guidance protein, plays an important role in the regulation of both postand pre-synaptic Ca2+ channels, such as N-methyl-d-aspartate receptors (NMDARs). The Ca2+ channel-binding domain 3 (CBD3) peptide derived from CRMP2 has recently emerged as a Ca2+ channel blocker, suppressing neuropathic pain in a spared nerve injury (SNI) model when linked to the transduction domain of HIV TAT protein and reduced neuronal death in a middle cerebral artery occlusion model and a traumatic brain injury (TBI) model. The present study aimed to examine the neuroprotective effects and biochemical mechanisms of ST2-104 (a non-arginine-conjugated CBD3 peptide) in an Aβ25-35-induced Alzheimer’s disease (AD) rat model. This study demonstrated that CRMP2 and NMDARs subunit NMDAR2B form a direct biochemical complex, which regulates NMDAR activity in a rat model. ST2-104 peptide given via tail vein injections significantly reduced spatial learning and memory impairment. ST2-104 relieved neuronal injuries by suppressing expression of NMDAR2B and p-CRMP2 and increasing expression of CRMP2 in the hippocampus. Remarkably, ST2-104 attenuated levels of intracellular Ca2+ by disrupting the interaction between p-CRMP2 and NMDAR2B. Taken together, these findings support ST2-104 as a novel neuroprotective agent, potentially representing a novel direction for a therapeutic targeting channel in AD.
Influences of Cost Factors Affecting Technical Performance of Local Government Projects in Nigeria : A Partial Least Square-Structural Equation Modeling ( PLS-SEM ) Approach

The technical performance requirements of projects posed a challenge to the sustainable development of small size local government projects particularly in developing countries. Studies in the past focused mainly on the performance of major foreign construction firms mostly owned and operated by expatriates. Very few researches however, have been conducted to assess the relationship between major cost factors affecting technical performance of small size local government projects. This study is aimed at assessing the relationship between major cost factors that affect technical performance of small size local government projects in Nigeria. Survey instruments were administered to major stakeholders in the construction industry comprising of project clients, contractors and consultants using proportionate stratified random sampling method. A Warp partial least square-structural equation modeling (PLS-SEM) software algorithm was used for the analysis of collected data. The software is one of the powerful software for data analysis and has an advantage of providing p values based on the structure of the research model. The study concluded that cash flow problem, fraudulent practice and nature of construction environment are the major factors affecting technical performance of local government projects in Nigeria and further recommended the use of mediator variables like pay for performance and advance payment policy to minimise such negative effects. Governments in developing countries should devise a good cash flow policy and impose stringent penalties against any party involved in fraudulent activity.
Logistic Regression for Spam Filtering

Unsolicited bulk emails, also known as spam emails, are a regular occurrence for anyone who uses email. Spam filtering is a way to distinguish between spam emails and regular emails. The goal with spam filtering is to determine whether an email is spam or not spam, then filtering out the spam emails, resulting in a spam-free in-box for the user. Logistic regression is a statistical method that can be utilized for spam filtering. It is sensible that spam emails typically share a certain type of characteristics. Words that recurrently show up in spam emails can be used as predictor variables in the logistic regression model. Other email characteristics, such as special formatting, tables, links, may also be used as predictor variables. More on this in section ? This report looks into what determines the probability of an email being a spam email by using logistic regression. We will examine if certain characteristics alter the probability of an email being a spam email or not. We will also test which model best predict the probability of an email being spam. The study initially contain 12 variables that potentially could alter the probability of an email being spam. After variable selection, the number of explanatory variables decrease to 5 in the chosen model. The variables shown to be insignificant are excluded from the model while all the significant variables are kept in the model. It appears that factors such as winner, mult sent, prior corr and sender spam have a significant effect on determining the probability of an email being spam, and thus should be used in a spam filter. ∗Postal address: Mathematical Statistics, Stockholm University, SE-106 91, Sweden. Email: niclas.englesson@gmail.com. Supervisor: Gudrun Brattström and Jan-Olov Persson. Bachelor Thesis in Mathematical Statistics Logistic Regression for Spam Filtering