Miracle-dz/UniFAR-FTUs huggingface dataset:
TEXT SUMMARIZATION EVALUATION BASED ON SENTENCE SCORING AND CLUSTERING

A summary system comprises a subtraction of text document contents to generate a new form that delivers the essentials contents of the text documents. Due to the hassle of documents overload, getting the right information and effectively-developed summaries are essential in retrieving information. Reduction of information allows users to find the information needed quickly without the need to read the full document collection. The purpose of this paper is to evaluate the performance of sentence scoring and clustering in the process of generating text summaries. Adaptive Neuro-Fuzzy Inference System (ANFIS) has been used to score the sentences and clustering were performed using K-Means and Hierarchical Clustering (HC) approaches. From the experimental findings, it was found that no improvements in the quality of the generated summaries obtained by simply performing clustering. This paper proposes some recommendations to improve text summarization.
Do Lower Caseloads Improve the Effectiveness of Active Labor Market Policies? New Evidence from German Employment Offices

We study how the caseworker to client ratio affects the success of active labor market policies that aim to bring job-seekers into employment. Although existing evidence is limited, caseload is a potentially important policy parameter that affects both the quality and the administrative costs of employment services. Exploiting a unique pilot project by Germany's federal public employment agency that hired additional caseworkers in 14 of its 779 local employment offices, we find that lower caseloads resulted in a decrease in the rate and duration of local unemployment and a higher reemployment rate. Offices with lowered caseloads became more proactive and imposed more sanctions on clients with low search efforts and registered more new vacancies. Cost-benefit computations suggest that the costs from hiring additional caseworkers was offset by the savings from decreased benefit expenditures after a period of about ten months. Author note We thank Michael Rosholm and Julia Schneider, and participants at the ASB/IAB workshop, at JSM, and EALE for helpful comments on previous versions of this study. We are grateful to Frank Sowa and Stefan Theuer for sharing information about the implementation of the pilot project. The usual disclaimer applies.
Binding Pattern of cTAP Binding Epitopes of S-27 Strain with the Common HLA Alleles for the Chikungunya Vaccine Development: An In silico Study

Chikungunya is a reemerging disease caused by the CHIK virus of Togaviridae family. Aedes aegypti and Aedes albopictous are the carrier mosquitoes of this disease. The disease is spreading globally with the increasing number of cases every day, the first outbreak of which was noticed in the year 1952 in Tanzania, while the latest outbreak found in 2016 in India. The symptoms may be chronic if disease persists more than 2-3 weeks and cause severe joint pain, probably leading to arthritis. There is no medicine or vaccine available for the treatment of this disease. In this study, authors collected the African genotype of CHIK virus and predicted T cell epitopes. The predicted epitopes were tested for the sharing with B cell, TAP binding activity. The selected epitopes tertiary structure was modeled and then docked with the cTAP1 (1JJ7) protein. Those epitopes showed the interaction with the cTAP1, further docked with the respective HLA allele. The epitope-HLA complex was tested for stability using NAMD-VMD molecular dynamics simulation method. 128 FLARNYPTV 136 were found as the promiscuous epitopes that function as the vaccine candidate for the designing of vaccine of chikungunya. Data obtained from the present study provide new insights into development of novel process of vaccine research of chikungunya and ultimately shedding off the burden from the human society.
Integral Equation Modelling of Reverberation Chambers using Higher-Order Basis Functions

Reverberation chambers (RCs) are important measurement facilities, and thus it is often required to simulate their behaviour numerically. However, due to their special characteristics, especially for high Q factors, they are often considered too challenging for application of standard numerical software. In particular, a recent publication [1] listed the perceived stateof-the-art in integral equation modelling of RCs, and identified numerous open problems. The present paper illustrates that computational analysis of large RCs can be performed with limited computer resources. This can be achieved by using Higher-Order (HO) basis functions in the integral equation discretization and, if necessary, further applying the Multi-Level Fast Multipole Method. After a discussion and brief review of existing methods for RC modelling, we will turn to a description of the key features of HO basis functions and their related MLFMM implementation, focusing on how they allow surpassing some of the challenges faced by lower-order discretizations. Then, several RC test cases are analyzed, drawing comparisons to other results from the relevant literature. The conclusion is that, using HO basis functions and a thorough MLFMM implementation, some of the challenges identified in [1] can be overcome.
A Comparison of Armington Elasticity Estimates in the Trade Literature

The Armington elasticity is one of the key parameters in quantitative trade models as it determines the level of substitutability between domestic and imported varieties of a good in a country. Estimates of this key parameter have been provided by several empirical studies using different methods and data sources. Our goal in this paper is to summarize and compare Armington elasticity estimates at the sector level that are found in this trade literature. We first discuss some of the most commonly used methodologies for estimating Armington elasticities as well the main advantages and challenges associated with each method. Using a common concordance, we then compare these Armington elasticity estimates at the sector level and assess if different levels of aggregation are driving the observed differences across studies. We find that the different estimation strategies, in combination with different levels of sectoral aggregation, has contributed to a wide range of estimates in the literature.
Towards Possible Cure of Cancer by Immunotherapy of Minimal Residual Disease Using Intentionally Mismatched Donor Lymphocytes

Cancer continues to be a leading cause of death worldwide. Considering lack of information about the causes of malignant transformation, except when viral agents seem to be involved, the universal dogma for treatment of cancer is based on ‘the more the better’ using available anti-cancer agents, attempting to eradicate the primary tumor by optimal resection, followed by chemotherapy or radiation therapy when indicated, considering additional treatment only as soon as secondary metastases become visible, usually focusing on aggressive chemotherapy as the standard of care. For patients with cancer not expected to respond adequately to conventional treatment, especially for treatment of hematological malignancies, myeloablative chemoradiotherapy followed by rescue with stem cell transplantation may be considered in an attempt to eradicate otherwise resistant malignant cells. Over the years it became apparent that in patients with primary resistant cancer or with metastatic disease, cure is unlikely to be accomplished. Indeed, relapse continues to be the single major obstacle in treatment of hematologic malignancies and many solid tumors as well, even following initial complete remission [1,2]. On the other hand, as the intensity of the regimen used for treatment of cancer or using high dose chemotherapy supported by stem cell transplantation (SCT) is escalated, the risks of procedure-related toxicity and mortality increase and recurrent disease may not be preventable [3]. In addition, increased incidence of late complications in patients treated with repeated courses of chemotherapy that may or may not increase survival are likely to impair the quality of life of longterm survivors and their supporting family. It became apparent that newer modalities must be introduced in order to improve the cure rate of patients with hematological malignancies and solid tumors as well as to improve the quality of life of successfully treated patients. For patients resistant to available chemotherapy, immunotherapy became in recent years an acceptable treatment as it was confirmed that activating patient’s immune system could be effective even against otherwise resistant disease. Unfortunately, in the absence of tumor-specific antigens and the unresponsiveness that develops between the immune system and the rapidly developing cancer cells, immunotherapy based on an attempt to immunize patients against cancer or using anti-cancer vaccines is far from being effective [4]. Clearly, the goal of effective immunotherapy should be based on an attempt to break the existing tolerance of the immune system against cancer cells, or Introduction Abstract
122597 AJLE Vol 22 No 2 2019 text.indd

This paper assesses the persistence of unemployment rates across Australian regions to see if there is evidence of sustained disadvantage for some Australian regions. Using Australian labour market data for statistical area level 4 regions over 1999–2018, the paper finds that lagged regional unemployment rates have substantial explanatory power for current regional unemployment rates. This effect lasts at least 19 years, even after controlling for factors such as average income levels and the industry structure of each region. There is strong persistence in the male unemployment rate across regions, a weaker effect for the female unemployment rate, and no observable effect for the youth unemployment rate. Lock-in effects are even stronger for participation rates. The results suggest that there is a potential role for well-designed place-based policies to combat persistent labour market disadvantages in some regions. JEL Codes: E24, J60, R10, R38
Reconstruction of Slowness Distribution of a Medium between Two Boreholes from First Arrival Traveltime Data

We consider a problem of reconstruction of seismic wave speed distribution from a set of measured first arrival traveltimes in presence of strong velocity contrasts, which cause the problem to be highly non-linear. In this context, a stable iterative reconstruction algorithm, proposed by Berryman (1990) is studied. An attempt is therefore made to improve and also used it for a simple synthetic borehole test after writing its algorithm in a C++ code. The simulations results support the effectiveness of the method.
Towards Rectifying the Effect on Image Registration of Pointing Inaccuracies in Nanosatellites Using Deep Convolutional Neural Networks

With the advent of satellite imaging with the use of nanosatellites, there is also huge potential to create a large volume of remote sensing images acquired over the same region in different periods of time by different satellites. Usually, remote sensing image datasets are geo-referenced. However, slight displacement is often seen with images from different sensors, or even within the same sensor due to pointing inaccuracies because of problems in attitude control systems. Here, we demonstrate a deep learning framework to solve such problems relating to identifying the location of satellite images by maintaining a separate repository of images from known reference satellites. Our idea is to detect the geographical location of remote sensing images using deep convolutional neural networks (CNN). We trained the VGGNet-16 model using Fully-Connected2 (FC2) features based on a reference Worldview-2 dataset to predict the geographical location based on the closest match found; in addition, it can be used to perform image registration. Performance evaluation of our proposed model is performed on different satellite images using a reference WorldView-2 satellite acquired in 2014, along with DubaiSat-2, image tiles from Google Earth, images from Sentinel-2 and Landsat-8 images acquired over an area of Abu Dhabi, United Arab Emirates (UAE).
Security Challenges in Fog and IoT, Blockchain Technology and Cell Tree Solutions: A Review

As the IoT is moving out of its early stages, it is emerging as an area of future internet. The evolving communication paradigm among cloud servers, Fog nodes and IoT devices are establishing a multilevel communication infrastructure. Fog provides a platform for IoT along with other services like networking, storage and computing. With the tremendous expansion of IoT, security threats also arise. These security hazards cannot be addressed by mere dependence on cloud model. In this paper we present an overview of security landscape of Fog computing, challenges, and, existing solutions. We outline major authentication issues in IoT, map their existing solutions and further tabulate Fog and IoT security loopholes. Furthermore this paper presents Blockchain, a decentralized distributed technology as one of the solutions for authentication issues in IoT. We tried to discuss the strength of Blockchain technology, work done in this field, its adoption in COVID-19 fight and tabulate various challenges in Blockchain technology. At last we present the Cell Tree architecture as another solution to address some of the security issues in IoT, outlined its advantages over Blockchain technology and tabulated some future course to stir some attempts in this area.
A REVIEW OF FIXED STRUCTURE MULTIPLE MODEL APPROACH TO MANEUVERING TARGET TRACKING

Almost all modern tracking systems utilize the Kalman filter as the central tool for state estimation. When a target is maneuvering, the success of the standard Kalman filter can be limited. The comparison and optimal choice of the one of basic multiple model single-target tracking techniques with fixed number of models (FSMM), are described in this paper. Brief overview and performance analysis by means of root mean square error of basic fixed structure multiple model (GPB1, GPB2 and IMM) are shown. The state estimate for all described multiple model methods based on all measurement up to time k and the mean square tracking error at time k , are computed. Simulations presented in paper, are performed in order to compare FSMM techniques with standard Kalman filter. It has been shown that the IMM approach is significantly better than GPB1 algorithm and almost similar to GPB2 algorithm, regard as practical purpose.
Morphology, 18S rDNA sequence and rbcL phylogeny of Navicula veneta (Bacillariophyceae) from thermal muds in Italy

A new culture strain of Navicula veneta Kützing (Bacillariophyceae) was isolated from brown mats covering thermal muds in the SPA town of Abano Terme, Padova, Italy. The morphology, 18S rDNA and rbcL gene sequences of this strain were analysed. The results do not support an existing taxonomic proposal to lower the taxonomic rank of Navicula veneta to a variety of Navicula cryptocephala Kützing. Therefore, we consider Navicula veneta as a good species in its own right. We also hypothesize that the species Navicula veneta, as defined morphologically, contains a number of cryptic species yet to be discovered and analysed genetically. Bacillariophyceae / morphology / Navicula / rbcL / thermal muds / ultrastructure / 18S rDNA Résumé – Morphologie, séquençes de l’ADNr 18S et phylogénie du rbcL du Navicula veneta (Bacillariophyceae) provenant de boues thermales en Italie. Une nouvelle souche du Navicula veneta Kützing (Bacillariophyceae) a été isolée à partir de couches brunes recouvrant des boues thermales dans la ville thermale de Abano Terme, Padue, Italie. La morphologie et les séquences de l’ADNr 18S et du gène rbcL de cette souche ont eté étudiées. Les résultats ne s’accordent pas avec les données de la littérature, dans laquelle l’espèce Navicula veneta a été réduit à une variété du Navicula cryptocephala Kützing. Par conséquent, nous considérons le Navicula veneta comme une bonne espèce à tous égards. Nous formulons aussi l’hypothèse que l’espèce Navicula veneta définie morphologiquement contient des espèces cryptiques qui sont encore à découvrir et à analyser du point de vue génétique. ADNr 18S / Bacillariophyceae / boues thermales / morphologie / Navicula / rbcL / ultrastructure 1. Both authors contributed equally to this paper. * Correspondence and reprints: carlo.andreoli@unipd.it Communicating editor: Gianfranco Novarino 210 I. Moro, S. Maistro, L. Cassaro, N. Rascio & C. Andreoli
DIFFERENT IRRIGATION SYSTEMS AFFECT THE YIELD AND WATER USE EFFICIENCYOF KINNOW MANDARIN (CITRUS RETICULATA BLANCO.)

Considering the scarce water resources, low average yield of citrus fruits, and haphazard irrigation system adopted in Pakistan; a study was conducted on 25 year old Kinnow mandarin plants grafted onto Rough lemon (Citrus jambhiri Lush.) during 2011–2015. In this study four modes of irrigation that includes drip irrigation (DI), full cover sprinkler (FCS), strip cover sprinkler (SCS) and traditional flood irrigation (TFI) were used. The yield, quality and water use efficiency (WUE) were evaluated. This study was conducted at Citrus Research Institute (CRI), Sargodha, Pakistan. To monitor the moisture level in the soil, tensiometers were installed in each block at the depth of 30, 60 and 90 cm in the root zone. A flume meter was used to measure the total quantity of water applied under flood irrigation system. The Kinnow plants growing under TFI system produced a fruit yield of 26.12 t ha (687 fruits tree and 104.55 kgtree) and WUE was only 2.29 kg m, however 40.46% higher yield (1288 fruitstree and 181kgtree) was obtained from plants grown under DI system compared with TFI and WUE was 4.85 kgm. The 55% water saving was attained using DI compared with TFI. Similarly, significantly higher yield of 28.45% (1029 fruit tree and 151kgtree) and 27.19% (1045 fruit tree and 147.92 kgtreewas obtained by using FCS and SCS, respectively compared with TFI, and WUE in FCS and SCS system was 3.03 kg mand 3.35 kg m, respectively as compared with TFI (2.29 kg m). It is concluded that DI is superior in terms of higher yield and WUE therefore for Kinnow growers DI is recommended to get higher yield and enhance the WUE.
Majority rule or dictatorship? The role of collective-choice rules in self-governance through institutional design

Collective-choice rules aggregate individual choices into a collective decision. This experimental study addresses the role of collective-choice rules in self-governance via institutional design in a social dilemma situation. Groups decide repeatedly on whether to establish any institution, and if so which institutions, to sustain cooperation in a public goods game. We hypothesize that collective-choice rules may directly affect cooperation, conditional on having the same institutions and indirectly affect cooperation through institutional choices. We implement three collective-choice rules: majority voting, dictatorship, and rotating dictatorship. Our main findings are: (1) Cooperation level is not higher with the institutions chosen via a democratic rule than with the same institutions chosen via a non-democratic rule. (2) Institutional choices made via majority voting or a fixed dictator are more stable over time than those chosen by rotating dictators. (3) The instability of institutions is associated with lower cooperation level. These results have implications for the organization of group decision-making in self-governance.
TDMA based BFNN Using Deep Learning for B5G Cellular Communication System

Beamforming neural network (BFNN) using deep learning (DL) is a key issue to optimize the beamformer to maximize the spectral efficiency and mitigate the challenge of imperfect channel state information. For beyond 5G (B5G) cellular communication system, a suitable BFNN technique using DL is proposed in this paper to enhance the cell center and cell edge user channel capacities and sum channel capacity by utilizing time division multiple access technique
WORKING PAPERS IN ECONOMICS & ECONOMETRICS FISCAL POLICY WITH INTERTEMPORALLY NON-SEPARABLE PREFERENCES

In this paper, we show that Ricardian equivalence does not hold in a representative agent framework if one considers goods whose current consumption affect future marginal utilities. We find that, when the intertemporal elasticity of substitution changes over time, the timing of lump sum taxation has an asymmetric effect on current and future consumption. This in turn induces distinctive welfare consequences even if the government and individual budget constraints are unchanged in present value terms.
Twitter’s Rumour Detection Using ID Based Clustering

— Social Networks like Twitter, Facebook, Instagram are playing very important role in our day –to –day life. They help us in exchanging information, establishing the social relationships and for sharing the large amount of content. When the information is being exchanged, it is not always possible to find out in which part of the real world, the information is being produced, from which the information is being shared to another place. This information can also be fake. This fake information also called rumours may create the panic in the society, heightens the bad effects on society, organizations, companies and individuals etc. Our paper introduces an algorithm that clusters the users of twitter based on their ids in to different communities and helps to detect how the rumour is spreading and helps to eliminate the rumours.
Facial Landmarks Detection with MobileNet Blocks

—Facial keypoint detection is a challenging problem in the ﬁeld of computer vision. The keypoint detection is done by predicting the coordinates of certain facial features. In this paper, facial keypoint detection is predicted using MobileNet techniques. The model is trained to predict facial key points using the webcam input data. The facial keypoints includes eyebrow corners, nose tip, eye corners and center, and lip points. The predicted keypoints are mapped onto the webcam input data and tested with various head poses. The adaptive wing loss is used to estimate the loss of the model.
An empirical investigation of definiteness

The debate between those who believe that uniqueness is the defining property of definite noun phrases (Russell, 1905; Loebner, 1987; Kadmon, 1987; Abbott, 1999; Roberts, 2001) and those who instead argue that the determining factor is familiarity (Christophersen, 1939; Heim, 1982; Prince, 1981, 1992) is still ongoing (see also (Birner and Ward, 1994; Abbott, 2000)). We report the results of a study in which this question was investigated by means of corpus analysis. Perhaps the most novel feature of this work is that for our study we used a large number of annotators together with statistical tests of reliability to ensure that our results could be replicated, whereas most previous studies were carried out by a single person on the basis of her own intuitions.
Note on quasi-polarized canonical Calabi–Yau threefolds

Let (X ,L) be a quasi-polarized canonical Calabi–Yau threefold. In this note, we show that |mL| is basepoint free for m ≥ 4. Moreover, if the morphism Φ|4L| is not birational onto its image and h0(X ,L) ≥ 2, then L3 = 1. As an application, if Y is an n-dimensional Fano manifold such that −KY = (n −3)H for some ample divisor H , then |mH | is basepoint free for m ≥ 4 and if the morphism Φ|4H | is not birational onto its image, then either Y is a weighted hypersurface of degree 10 in the weighted projective space P(1, . . . ,1,2,5) or h0(Y , H) = n −2.