Miracle-dz/UniFAR-FTUs huggingface dataset:
NBER WORKING PAPER SERIES THE INTERGENERATIONAL MORTALITY TRADEOFF OF COVID-19 LOCKDOWN POLICIES

In lower-income countries, the economic contractions that accompany lockdowns to contain the spread of COVID-19 can increase child mortality, counteracting the mortality reductions achieved by the lockdown. To formalize and quantify this effect, we build a macro-susceptible-infectedrecovered model that features heterogeneous agents and a country-group-specific relationship between economic downturns and child mortality, and calibrate it to data for 85 countries across all income levels. We find that in low-income countries, a lockdown can potentially lead to 1.76 children's lives lost due to the economic contraction per COVID-19 fatality averted. The ratio stands at 0.59 and 0.06 in lower-middle and upper-middle income countries, respectively. As a result, in some countries lockdowns can actually produce net increases in mortality. In contrast, the optimal lockdown that maximizes the present value of aggregate social welfare is shorter and milder in poorer countries than in rich ones, and never produces a net mortality increase. Lin Ma AS2 #05-19 National University of Singapore Singapore ecsml@nus.edu. sg Gil Shapira The World Bank 1818 H street, NW Washington, DC 20433 gshapira@worldbank.org Damien de Walque The World Bank Development Research Group 1818 H Street, NW Washington, DC 20433 ddewalque@worldbank.org Quy-Toan Do The World Bank 1818 H Street NW Washington, DC 20433 qdo@worldbank.org Jed Friedman The World Bank 1818 H Street NW Washington, DC 20433 jfriedman@worldbank.org Andrei A. Levchenko Department of Economics University of Michigan 611 Tappan Street Ann Arbor, MI 48109 and CEPR and also NBER alev@umich.edu
A Novel Quantum Machine Learning Algorithm Based on Kronecker Reed-Muller Forms

Machine learning is being broadly applied in many areas to process large quantities of data, establish prediction models and predict the complex system behavior. In today’s ever-growing big data era, the total store of digital data already amounts to 487 billion gigabytes and this figure is expected to double in size every 18 months. In fact, it would take a classical computer enormous amount of time to manipulate big data and recommend the desired behavior for complex systems in machine learning. In contrast, quantum machine learning can accelerate the learning process significantly with its power of parallel quantum computing, especially when handling exponentially growing data sets for machine learning. In my research, a novel quantum machine learning algorithm was invented to execute complex machine learning predictive analysis where many variables, patterns and test models are possible. The machine learning problem in this research is modeled as finding the simplest Kronecker Reed-Muller (KRO) forms for incomplete Boolean functions with multiple “don’t know” values. An innovative implementation of Grover’s search algorithm was developed to enable quadratic accelerations for machine learning. A MATLAB simulator was developed to simulate quantum computer calculations to find the exact minimum KRO expression which yields the simplified machine learning prediction function compared against FPRM (Fixed Polarity Reed-Muller) forms. This research also integrated the simulator with a HROS1 humanoid robot to validate functionality. Over 65,000 MATLAB simulation runs were completed to validate KRO form minimization results and 600 machine learning simulation runs were tested, spanning different design permutations for variety of input variables. The machine learning prediction function complexity was reduced by up to ~33% in experiments. The HR-OS1 humanoid robot and MATLAB simulator integration validated the correctness of the algorithm.
Fuzzy based random valued Impulse noise suppression using optimal direction method

This paper proposed new techniques based on fuzzy logic in optimal direction for suppression of random valued impulse noise in digital images. The deviation of the test pixel from its neighboring pixels present in the optimal direction shows its corruption level. According to how much a pixel is impulse-like, a fuzzy index is assigned to each and every pixel in the image. After the detection of impulsivity of each pixel, a non-local mean filter is employed for noise suppression. Extensive simulations are performed to prove that the proposed techniques give better visual quality and quantitative measurement than recent impulse noise suppression techniques. © 2014 Elixir All rights reserved ARTICLE INF O Articl e h istory: Received: 24 April 2014; Received in revised form: 24 May 2014; Accepted: 4 June 2014;
Music Structure Analysis Based on an LSTM-HSMM Hybrid Model

This paper describes a statistical music structure analysis method that splits an audio signal of popular music into musically meaningful sections at the beat level and classifies them into predefined categories such as intro, verse, and chorus, where beat times are assumed to be estimated in advance. A basic approach to this task is to train a recurrent neural network (e.g., long short-term memory (LSTM) network) that directly predicts section labels from acoustic features. This approach, however, suffers from frequent musically unnatural label switching because the homogeneity, repetitiveness, and duration regularity of musical sections are hard to represent explicitly in the network architecture. To solve this problem, we formulate a unified hidden semi-Markov model (HSMM) that represents the generative process of homogeneous mel-frequency cepstrum coefficients, repetitive chroma features, and mel spectra from section labels, where the emission probabilities of mel spectra are computed from the posterior probabilities of section labels predicted by an LSTM. Given these acoustic features, the most likely label sequence can be estimated with Viterbi decoding. The experimental results show that the proposed LSTM-HSMM hybrid model outperformed a conventional HSMM.
Effect of variations of CuIIX2/L, surface area of Cu0, solvent, and temperature on atom transfer radical polyaddition of 4-vinylbenzyl 2-bromo-2-isobutyrate inimers

An asymmetrical AB type inimer (4-vinylbenzyl 2-bromo-2-isobutyrate (VBBiB)) was synthesized and a variety of conditions for atom transfer radical polyaddition (ATRPA) of VBBiB was investigated regarding a CuX2/Cu0/ligand catalytic system (where, X = Br or Cl; ligand = 4,4′-dinonyl-2,2′-bipyridine (dNBpy), N,N,N′,N′′,N′′-pentamethyl diethylenetriamine (PMDETA) or 1,1,4,7,10,10-hexamethyltriethylenetetramine (HMTETA)). We focused on investigation of the effect of four reaction factors, i.e. type of ligand, Cu0 surface area, solvent and temperature on the final structure and molecular characteristics of the polyesters. The VBBiB/CuBr2/Cu0(wire)/PMDETA system showed formation of branched polymers due to very high activity of the catalyst complex. Replacing Cu0 wire with Cu0 powder, possessing higher surface area, resulted in only slight increase of the rate of inimer consumption. The polyaddition was more significantly affected by reaction temperature. Decreasing reaction temperature down to 0 °C increased significantly self-degradation by-products formation as a result of longer reaction times. Optimization of reaction conditions using commercially available catalytic systems allowed obtaining control over the polyester architecture and functionality, as well as ready achievement of functional linear polyesters with high molecular weight (Mw = 16 200).
Simulation of Localization for Indoor Mobile Robot using Extended Kalman Filter

1Dept. of Electronics and Telecommunication TSSM’s Padmabhushan Vasantdada Patil Institute of Technology, Bavdhan Pune, India maneakshay555@gmail.com 2Dept. of Electronics and Telecommunication TSSM’s Padmabhushan Vasantdada Patil Institute of Technology, Bavdhan Pune, India Swati.gandhi25@gmail.com ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Simultaneous localization and mapping (SLAM) is a key component in self-driving vehicles and other autonomous robots enabling awareness of where they are and the best routes to where they are going. By creating its own maps, SLAM enables quicker, more autonomous and adaptable response than pre-programmed routes. The main major problems with SLAM are localization errors accumulate which causes substantial deviation from actual values and in some cases localization fails. In this paper, a novel methodology is proposed to solve the SLAM problem of mobile robot with extended Kalman filter (EKF) algorithm. The robot used for this purpose is a differential drive robot which uses various types of cameras and sensors such as Kinect sensor, ultrasonic sensor and other technologies to understand its environment so that it can more effectively map, navigate, avoid obstacles and adjust to changes. The accuracy of these measurements and the performance of the corresponding SLAM algorithm directly affect the overall success of the system. The results of simulation indicate that EKF SLAM algorithm can localize the robot and landmarks precisely and the error of landmark’s estimation confluences better than general SLAM.
Image Classification using Deep Learning Neural Networks for Brain Tumor

1Professor, Dept. of Electronics and Telecommunication, Xavier Institute of Engineering, Mumbai, Maharashtra, India 2,3Student, Department of Electronics and Telecommunication, Xavier Institute of Engineering, Mumbai, Maharashtra, India. ---------------------------------------------------------------------------***-------------------------------------------------------------------Abstract -The brain tumors, are the most common disease, leading to a very short life span in their highest grade. Among the various types of brain tumors, gliomas are the most common type, leading to a very short life. The survival rates of patients are improved if early diagnosis of brain tumor ,Magnetic Resonance Imaging(MRI)is one of the non-invasive technique has emanated as a frontline diagnostic tool for brain tumor without ionizing radiation heir highest grade. In the clinical practice manual
I 74 t Processes and Mechanisms of Bilingual Control : Insights yiom

#$::11*:'J*J the. studv of bilinguaris. ta psvchoringuistic monorinsuar,**""r"o"tjit"l1t#T:? ,h:;:m:*1". **x them to do so' Models that account for thrs-betraviour assume subtle control processes that differentially activate and)or inhibit each of the two underlying language sub-systems'ano ,rr"i t"rrtrt, prior to articulation output of the non_t seep rhrough. tn" . "ffi'"frffi il",HIthat might ott". ri. " likelv to uJ"u"n'n-"-"o,npr"" due ro the rut;ffi;"iffTr'ifii#: behaviour demands that both of the interpii". ;, tunguug" sub_systems are activated, but possibly to a different'""i.rr. In this paper we will discuss a number of views "; ;lu*;;i language control in "monolingual" rasks and, especially, i,,i_ifr"", pre s umably i s th e c o gni ti ver y mo s r d";;-;dd": Jltir? llt'li;X_1tT monolingual rask (as we define it) ,. "r"rvn"r",l" theory, the (bilingual) participants only have to address on" ", *"r, i""*uage sub_systems and where' ideally, pure output is produced. a u'inguur ,usk is one where task performance requires that both ,"rr** . ri_lrrr"_. are implicated. A number of studies suggest that theloitrol exerted by bilinguals in monolingual and bilingual language "rO, ,, "*"tuated by a more general cognitive system that iakes "ur" oi rn" control of action in O Department ofTranslation, The Chinese University ofHong Kong, 2007. published by The Chinese University press, ISSN 1027-7978. Journal ofTranslation Studies 10(1) (2007) general. An attempt will be made to relate simultaneous interpreting to this more general theory of control.
A Novel Control Strategy for Reduce Voltage Unbalance in an Islanded Microgrid

1Student, M.Tech (Power Systems), PRIST University, Puducherry Campus, Puducherry, India 2A.P/ Head of Department, Power Systems, PRIST University, Puducherry campus, Puducherry, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Micro Grids (MG) provide advantages such as providing energy supply to areas far from the distribution grid, efficient use of resources by supporting demand management and having a more dynamic grid. However, if an advanced control system is not implemented in the islanded MG, problems of power quality may arise. One of these problems is the voltage unbalance. Increasing the number of single-phase roof-mounted PV plants and the number of electric vehicle charging stations in recent times may negatively affect voltage unbalance. One of the methods used to mitigate this problem is the Demand-Side Management (DSM). Here, a solution method based on DSM is presented for the voltage unbalance problem that may occur in an islanded MG. The proposed Direct power control algorithm reduces successfully both the voltage unbalance factor.
FISH STOCK ASSESMENT OF FISH RESOURCES COMMON PONYFISH (Leiognathus equulus) CAUGHT RAMPUS NET IN SUNDA STRAIT

Common Ponyfish is one of demersal fish have an important economic value and is one of dominant catch in Sunda Strait landed at Costal Fishing Port (PPP) Labuan, Banten. Common ponyfish fish caught with boat seine, danish seine, beach net, purse seine, rampus net, and bamboo platform liftnet. The purpose of this study was to analyze dynamic of common ponyyfish (Leiognathus equulus) in Sunda Strait. The research was conducted from April to August 2015 in PPP Labuan, Banten. Data taken in this study of biological data such as measurements of total length and height of the fish, weight, and gender. Total fish taken during this research reaching 1895 tail. The results showed that the growth coefficient (K) females and males respectively 0.47/year-1 and 0.79/year-1 with asymptotic length (L∞) of 258 mm for females and 210 mm for male. Values were first captured length (Lc) female (145.57 mm) and male (142.92 mm) is greater than value of the first mature gonads (Lm), which is for female and males respectively 116.54 mm and 146.162 mm. The rate of exploitation reached the optimal level between 0.53-0.74. The rate of exploitation of common ponyfish has exceeded the optimum exploitation rate, thus might common pony fish in Sunda Strait has overexploited. Keyword: common ponyfish, dynamic population, overexploited, Sunda Strait
EXAMINING THE EFFECTS OF SMARTPHONE USE AT WORK ON JOB PERFORMANCE AND WORK ATTITUDES

This study examines the effects of excessive smartphone use at work and examined its effects on job performance and work attitudes. Data were collected from a sample of 486 participants who work in IT and construction companies located in Ankara. In the analysis, smartphone addiction and daily duration of smartphone usage at work were found to be negatively associated with job performance. Meaningful differences were detected in terms of both gender and industry type. Female participants were found to have more daily smartphone use at work than male participants. Those who work for the IT company were also observed to have more daily duration of smartphone use at work than those from the construction company. Job satisfaction and organizational commitment had positively associated with each other and with job productivity. However, no meaningful relationship was detected between smartphone addiction and both job satisfaction and organizational commitment. It is concluded that the level of excessive smartphone use should be determined considering both gender and industry type in order to develop a balanced smartphone use arrangement, which would not harm the productivity at work.
Crystal structure of 2-(4-bromophenyl)-1,3-dimethyl-2,3-dihydro-1H-perimidine, C19H17BrN2

Abstract C19H17BrN2, orthorhombic, Pnma, a = 11.506(5) Å, b = 12.176(5) Å, c = 11.327(5) Å, V = 1586.8(11) Å3, Z = 4, Rgt(F) = 0.0409, wRref(F2) = 0.1051, T = 296(2) K.
STUDENTS SURVEILLANCE SYSTEM IN MASS GATHERING USING DEEP LEARNING

---------------------------------------------------------------------***--------------------------------------------------------------------Abstract ID cards of students in schools and colleges provide a quick visual way to determine if a student belongs to that particular college or not. Making sure the IDs are worn prominently will ensure people who don’t belong are spotted quickly. Thus, it is important to ensure that all the students wear ID cards inside the campus. The project proposes a system to monitor the wearing of ID cards using computer vision with object detection. To facilitate object detection in a college environment, the proposed work identifies the presence of a student wearing an ID card or not, by comparing it with the database containing pre-stored images. Once the absence of an ID card is detected, the student’s face will be recognized and compared with the faces that are stored in the database to find out the student who is not wearing an ID card. This is achieved using the face detection and face recognition concepts. Further, the image captured is mailed to the student and management through IMAP protocol.
STRUCTURAL HEALTH MONITORING USING HARALICK FEATURES

Crack detection in structural elements is pivotal for structural health monitoring. In this paper, an automatic machine vision-based crack detection method is proposed, which is efficient, computationally simple, and fast in contrast to the timeconsuming and highly subjective traditional visual inspection approach. Textural analysis of the concrete surface image is performed using Haralick features for crack detection. First, a combination of 8 suitable Haralick features in 4 different directions are extracted from the SDNET2018 image dataset. Then, different SVM classifiers are trained on the extracted features and tested using a 5-fold cross-validation scheme to distinguish between cracked and non-cracked images. The resulting best-trained classifier achieves an overall classification accuracy of 88%. Furthermore, the high classification accuracy for individual image categories indicates that the proposed method can effectively detect cracks in the images. Finally, crack orientation is localized based on the extracted feature values. KeywordsCrack detection, Haralick features, structural health monitoring, machine learning
Gold and cadmium selenide (CdSe) nanoparticles capped with oligothiophenes

The preparation and characterization of hybrid materials composed of oligothiophenecapped Au and CdSe nanoparticles with novel chemical, structural, electronic and optical properties are reported. a-Phosphino-oligothiophenes (12-15 and 23) and thiol-substituted oligothiophenes (26, 29, 32) were prepared by metal-catalyzed coupling reactions and studied using absorption and emission spectroscopy, and cyclic voltammetry. These functionalized oligothiophenes were used to passivate the surface of Au (16-19) and CdSe (CdSe-26, CdSe-29, CdSe-32) nanoparticles. Oligothiophene-capped Au nanoparticles were prepared directly by reducing a Au salt in the presence of the phosphino-oligothiophene. Attachment to the A u nanoparticles has little effect on the electronic structure of the oligothiophene as determined from the absorption spectra. On the other hand, the oligothiophenes appear to affect the electronic structure of the Au nanoparticle, as observed via a red-shift in the surface plasmon absorption. Electrochemical oxidation of the phosphino-terthiophene capped Au nanoparticles lead to crosslinking where the nanoparticles are linked both structurally and electronically by observed increases in conjugation, conductivity and plasmon coupling relative to the unlinked particles. The oligothiophene bridge linking the Au nanoparticles is shown to facilitate plasmon coupling between adjacent nanoparticles. The crosslinked material also demonstrates tunable conductivity where the conductivity in the material can be increased by oxidative doping of the 7r-conjugated bridge. Oligothiophene-capped CdSe nanoparticles were prepared through an exchange reaction between thiol-substituted oligothiophenes and trioctylphosphine oxide-capped CdSe nanoparticles. Attachment of the oligothiophenes to the CdSe nanoparticle has little effect on
Studies on Genetic Diversity and Population Structure of Tasar Silkworm, Antheraeamylitta.Drury

The populations of Indian tropical Tasar silkworm, Antheraeamylitta Drury, the semi-wild, sericigenous, lepidopteran insect are distributed in eco pockets of various States. These ecoraces vary in geography, topography, ecology, food plant flora and frequency of life cycle in latitudinal and altitudinal gradients. They exhibit diversity in phenotypic, behavioural, physiogenetic and commercial characters. In the present study, the SSR amplification of 7 silkworm strains/ecoraces (16 individuals in each, with seven primers which generated polymorphism) yielded a total of 887 bands, out of which 420 were (47.3 %) polymorphic. Most of the bands were observed within the range 130 to 500 base pairs which is in accordance with the allelic size of the primers taken for studies. The subsequent analysis of its population structure using these alleles revealed the formation of population clusters. The study suggests that these markers could be effectively utilized for identifying the genetic variability among tasar ecoraces.
Budgeting for gold or profit ? A case study on budget uses within a Swedish elite ice hockey organisation

This paper explores, through a single-case study, the budget uses and roles of budgeting within a professional ice hockey organisation that encompasses different and sometimes diverging logics. We identify a sport and a managerial logic to enable an exploration of how different logics affect budget uses and roles of budgeting within the case organisation. Drawing upon recent work by Amans et al. (2015), we find that sport and managerial logics shape the budget uses in various ways. Further, we find that budgeting plays certain roles during three different processes studied: budget setting, monitoring and revision. A particularly noteworthy role unfolds during the budget setting process, as a tension between the two logics arises when the size of the player budget is to be decided. By deploying the Guardian and Advocate terminology of Wildavsky (1975), we illustrate how different organisational actors help manage the co-existence of multiple logics during the budget setting process, which in turn plays the role of an arena for discussion allowing for compromise (cf. Chenhall et al. 2013). We use previous literature on roles of budgeting to discuss and substantiate our findings, which contribute to the growing field of budget research in organisations facing institutional complexity (Ezzamel et al., 2012; Amans et al., 2015).