Miracle-dz/UniFAR-FTUs huggingface dataset:
An Optimized Pairing-Based Cryptography Library for Android

There are numerous pairing-based cryptography (PBC) libraries available for desktop-based applications. However, these libraries are mostly not compatible or not optimized for mobile phone operating systems (OS) such as Android. In this paper, we show the inconsistency on benchmarking result for Java-based PBC libraries between Java Virtual Machine (JVM) and Dalvik Virtual Machine (DVM). Identifying the root cause, we present a new PBC library for Android, namely, mobile-PBC (mPBC) which combines the strengths of several Java PBC libraries and optimized for Android’s DVM. The mPBC library out-performs the existing Java-based PBC libraries in DVM, yet as efﬁ-cient as the fastest PBC library to date in the JVM. In particular, the pre-processed Tate pairing operation in mPBC uses 426.11ms in DVM (Samsung GT-N7000) and 4.50ms in JVM (Sager NP5160).
Identification, Sorting and Characterization of Plastics from WEEE

The plastics components of a random sample of waste electrical and electronic equipment (WEEE) from small household appliances were identified and sorted. Moreover, by taking into account the practical needs for applications demanding medium to less severe restrictions from the standpoint of end-use characteristics, the mechanical and thermal properties are investigated for the four most used plastics in the EU, including acrylonitrile-butadiene-styrene (ABS), styrene-acrylonitrile (SAN), polystyrene (PS) and polypropylene (PP), as well as for a mixture resulting on the basis of corresponding EEE market evaluations. The obtained results show that in the case of these materials, separated prior to processing, even if a minor decrease arises from the standpoint of thermal properties due to inherent degradation induced by processing, the problem is the decline of different mechanical properties. In fact, this appears to be the net result of different morphologies of components – the essentially amorphous-like nature of ABS, SAN and PS, and the semi-crystalline component (PP). Accordingly, the loss in mechanical properties was lower for the elastic modulus, higher in case of impact strength and intermediate for the tensile strength, when the components and the resulting blend properties are compared.
( N O ) COMPETITION BETWEEN DEVERBAL NOUNS AND NOMINALIZED INFINITIVES IN S PANISH

This paper explores the distribution of deverbal nouns and nominalized infinitives that are built on transitive verbs and occur in eventive interpretations. The study is empirically oriented and based on an acceptability judgment experiment in which argument realization and interpretational possibilities are manipulated as the independent variables. The results show that deverbal nouns prefer but are not limited to realizing the lower argument of the base, whereas nominalized infinitives are mostly restricted to realizing the higher argument. Furthermore, deverbal nouns turn out to be insensitive with regard to the distinction between episodic and generic event readings, while nominalized infinitives are shown to be specialized on generic interpretations. Deverbal nouns and nominalized infinitives are, thus, mostly neither paradigmatically interchangeable nor complementarily distributed as nominalized infinitives reach the same degree of acceptability as deverbal nouns only under very specific conditions. With regard to the ecological validity of the experimental approach, a comparison to corpus data indicates that high frequency clearly correlates with acceptability, but that the same does not hold for low frequency and unacceptability, that is forms that are not (sufficiently) attested in the corpus do not necessarily receive low ratings within the judgment task. The study, thus, also addresses a number of methodological issues in the study of event nominals.
Transactions of the Korean Nuclear Society Virtual Autumn Meeting December 17-18 Development of system dynamics model for estimating DPRK’s fissile material stockpile

The DPRK's denuclearization is essential for establishing a stable peace regime on the Korean Peninsula. Therefore, substantial actions for denuclearization are necessary regardless of the political and diplomatic situation around the Korean Peninsula. The meaning of denuclearization is the complete disablement of nuclear weapons. In practice, it does not stop at the disposal of nuclear weapons but includes the removal of all facilities and technologies, human capabilities about developing nuclear weapons. This study excludes technological and human capabilities related to nuclear weapons development because it requires an institutional and political approach. Generally, a nuclear weapon is an explosive bomb using nuclear fission energy. Currently, it is known that the DPRK can produce HEU (high enriched uranium) and Pu (plutonium). Therefore, it must be verified the amount of fissile material to achieve denuclearization. In the verification stage, it is necessary to estimate the exact amount of fissile material based on the actual operating history of the facilities related to the nuclear fuel cycle. To attain this goal, we develop a simulation model for estimating the nuclear fuel cycle and flow about fissile material, which can be meaningful information in decision-making.
Investigating the Academic Performance and Disciplinary Consequences of School District Internet Access Spending

Public school districts not only make strategic investments in internet access as a means to attract and retain students but also communicate the value of these investments with parents as part of their marketing programs. While it helps attract more customers, how does school district internet access spending (SDIAS) affect academic performance and disciplinary problems among students? Using a longitudinal data set that combines SDIAS of 1,243 school districts with academic performance and disciplinary records of more than 9,000 Texas public schools between 2000 and 2014, the authors find that a one-standard-deviation increase in SDIAS (an average increase of $.6 million) is associated with an improvement in eight academic performance indicators, with effect sizes ranging from 2% to 5% of a standard deviation, amounting to a $. 8 million to $1.8 million increase in cumulative income for the current students of a school district. Furthermore, a one-standard-deviation increase in SDIAS is associated with a 5% increase in Part II offense–related school disciplinary problems, amounting to a yearly cost of $25,800 to $53,440 for a school district. The positive and negative consequences of SDIAS are more pronounced among schools in regions with a higher level of household internet access.
Why keep the old dead around| Bringing together theory and method in the study of human remains from Balkan (E)Neolithic settlements

The aim of this article is to focus on the ways in which communities imagined their relationship with the dead throughout the Balkan area during the Neolithic and Eneolithic (6200– 3800 cal BC). My claim is that we should go beyond seeing the human remains discovered in settlements as unusual/atypical/non-funerary discoveries. Instead, they can be read as traces of complex funerary practices, which contributed to the creation and manipulation of collective identities. The dead became part of a place-making strategy, they fixed time and become central to certain kinds of assemblages, which in turn were meant to create more powerful ancestors who could intervene in the present. IZVLE∞EK – V ≠lanku se osredoto≠am na na≠ine, kako so si skupnosti predstavljale svoj odnos do mrtvih na obmo≠ju Balkana v ≠asu neolitika in eneolitika (6200–3800 pr. n. ∏t.). Trdim, da bi morali ≠love∏ke ostanke, odkrite v naseljih, obravnavati izven obi≠ajnega stali∏≠a o nenavadnih/netipi≠nih/ ne-pogrebnih odkritjih. Namesto tega jih lahko razlagamo kot sledi zapletenih pogrebnih navad, ki so pripevale k ustvarjanju in manipulaciji kolektivnih identitet. Mrtvi so tako postali del strategije o oblikovanju prostora, dolo≠ali so ≠as in postali osrednji del nekaterih zbirov, ti pa naj bi ustvarili mo≠nej∏e prednike, ki bi lahko posegali v sedanjost.
Instrument-Free Demand Estimation: Methodology and an Application to Consumer Products∗

We consider identification and estimation of demand systems in models of imperfect competition. When the standard assumption of profit maximization is imposed, the resulting supply-side restrictions allow us to correct for price endogeneity bias without the use of instruments. We show that the biased coefficient from an ordinary least squares regression of (transformed) quantity on price can be expressed as function of demand parameters. When combined with minimal assumptions about the correlations among unobservable shocks, the profit-maximization conditions are sufficient to identify the key parameters of several models commonly used in demand estimation. We illustrate the methodology with applications to the cement industry and the airline industry. ∗We thank Chuck Romeo, Gloria Sheu, Matthew Weinberg, and Karl Schurter for helpful comments. †Harvard University, Harvard Business School. Email: amackay@hbs.edu. ‡Georgetown University, McDonough School of Business. Email: nathan.miller@georgetown.edu
Description and evaluation of the process-based forest model 4C v2.2 at four European forest sites

Abstract. The process-based model 4C (FORESEE) has been developed over the past 20 years to study climate impacts on forests and is now freely available as an open-source tool. The objective of this paper is to provide a comprehensive description of this 4C version (v2.2) for scientific users of the model and to present an evaluation of 4C at four different forest sites across Europe. The evaluation focuses on forest growth as well as carbon (net ecosystem exchange, gross primary production), water (actual evapotranspiration, soil water content), and heat fluxes (soil temperature) using data from the PROFOUND database. We applied different evaluation metrics and compared the daily, monthly, and annual variability of observed and simulated values. The ability to reproduce forest growth (stem diameter and biomass) differs from site to site and is best for a pine stand in Germany (Peitz, model efficiency ME=0.98). 4C is able to reproduce soil temperature at different depths in Sorø and Hyytiälä with good accuracy (for all soil depths ME > 0.8). The dynamics in simulating carbon and water fluxes are well captured on daily and monthly timescales (0.51 < ME < 0.983) but less so on an annual timescale (ME < 0). This model–data mismatch is possibly due to the accumulation of errors because of processes that are missing or represented in a very general way in 4C but not with enough specific detail to cover strong, site-specific dependencies such as ground vegetation growth. These processes need to be further elaborated to improve the projections of climate change on forests. We conclude that, despite shortcomings, 4C is widely applicable, reliable, and therefore ready to be released to the scientific community to use and further develop the model.
Model-Based Testing in Agile Projects: An Approach Based on Domain-Specific Languages

Model-Based Testing (MBT) can bring several beneﬁts to software quality. However, generally, MBT is applied in traditional software development lifecycle models, with few studies exploring its application in agile software development context. Hence, usually, agile development teams (AT) do not beneﬁt from the advantages that the MBT technique provides, for example, reuse of artifacts and traceability between requirements and test artifacts. Thus, this article presents an approach for applying MBT in agile software development teams. This approach is based on the use of a semi-natural language to write scenarios for the automatic generation of models and test scripts. To exemplify the application of this approach, we also present a Domain-Speciﬁc Language (DSL) called Aquila, in which new functional test related keywords are added to the Gherkin DSL. We also present, based on a literature review, the majors challenges and diﬃculties of applying MBT in AT. To validate the proposed approach a Focus Group study was used.
Endodontic management of c-shaped canal system in mandibular second molar: A case series

An in depth understanding of root canal anatomy and its variations is an important parameter for determining the clinical success of an endodontic treatment. ‘C’shaped canal system is a peculiar anatomic variation depicting an ethnic predilection with high incidence in Asian population. This characteristic feature of root canal anatomy has been reported to occur in various teeth but most frequently observed in mandibular second molars. These canal systems are named for the cross-sectional morphology of root and root canal. Characteristic feature like presence of a fin or web connecting the individual mesial and distal canals makes the canal cross sectional and 3D shape variable along the root. Their diagnosis with routine radiographic techniques and management with respect to debridement and obturation frequently pose a challenge in front of dental clinicians. This paper presents successful endodontic management of three mandibular molar teeth with C-shaped canal system in two cases. *Correspondence to: Ashish Kalra, Classified Specialist Prosthodontics, Military Dental Centre, India, Tel: 8109423588, E-mail: doc_ashish47@ rediffmail.com
On Protecting Microdata in Open Data Settings from a Data Utility Perspective

—In modern societies, opening data is playing a crucial role in innovations and economic growth. Public organizations and private enterprises constantly are collecting data. To support the growth of societies, these organizations and enterprises intend to be more active in data opening. However, disclosure of personal data is one of the main threats for data opening. Data transformation techniques for Statistical Disclosure Control (SDC) aim at removing personal data while maintaining the utility of the data at an acceptable level. Applying SDC methods always faces the struggle of maintaining a balance between data utility and personal disclosure risk. In this research, we investigate different options for a common set of transformations for protecting microdata. We study a set of common scenarios which target (or specify) two types of data environments (i.e., those with and without the original microdata sets) and two approaches for privacy protection (i.e., those based on normative heuristics and a formal approach). Employing ARX, we run a series of experiments to observe the behaviours of various measurement factors. At the end, we discuss the consequences of choosing each of the options that can be used by policymakers for opening privacy-sensitive microdata sets.
Plant Regeneration and Enhanced Tuberization in Dioscorea Bulbifera L. Meristem Explants

A rcliablc and fasl proloco1 is clescrihed for plant regeneration and enhanced tuberiiration in I)iotrorc.n bvlhfirn 1. a ~ncdicinally important ~) lanl of thc family L)ioscoreaceae. Shoot organogencsis was irlducctl i n temir~al and rdlary metistems within 28 days on MS. R5 and SI-1 basal mcdia supplemented with 0.1 I . O mgl ' benzyladcnitle. Rooling of shoots occurrcd spntancously within 21 days on MS rncdia i n the ahscncc ofrnixi~~s, hut was suhstanlinlly cnhancctl (within 14 days) in mcdia supplemented with 2-5 mg1.l indolcbulyric acid. Up to 93 per cent plantlet survival was achieved whcn rooted plantlets were hardened using top soil + coconut husk ( I : I ) as subswatc, prior to transfcr to potted soil in the greenhouse. Incorporation of abscisic acid at 0.02-0.20 mgl-' into the planting substrate rcsultccl in significant depression of root and shoot growth while enhancing early tuberiaation with consequcnt partitioning of assimilates in favour of tuber growth i n the later growth phase. Key Word%: Uioscorea bulbi/era, nlerislcn~ cxplants, c~~liancrcl lubcrizalion.
Clinical Characteristics & Observation of Hospitalized Cases of Dengue Fever: A Study in Tertiary Care Hospital, Dhaka, Bangladesh

Introduction: Incidence of dengue infection has increased around the world in recent decades and has become a major international public health concern. Early diagnosis is essential and clinical suspicion is based on the frequency of symptoms in the population. The exact clinical profile is important for management and prognosis. Objective: This study is an attempt to describe the Clinical Characteristics & Observation of Hospitalized Cases of Dengue Fever: A Study in Tertiary Care Hospital, Dhaka, Bangladesh. Materials and Methods: A hospital-based prospective study was undertaken in the Paediatrics Dept. in Tertiary Care Hospital, Dhaka, Bangladesh (July -October 2018). NS1 antigen and IgM dengue antibody-positive cases were included. These patients were admitted with fever, myalgia, headache, vomiting, abdominal pain or bleeding manifestations. NS1 antigen and IgM dengue antibody was estimated using capture ELISA. The diagnosis of dengue fever, dengue hemorrhagic fever and dengue shock syndrome was based on the WHO (World Health Organization) criteria. Results: The study enrolled 101 patients of suspected dengue fever of whom 51 (50.49%) were serologically confirmed to have dengue infection. 28 (55.0%) patients were males and 23 (45.0%) were females. 38 (37.62%) patients had classic dengue fever while 12 (11.88%) fulfilled the criteria of dengue hemorrhagic fever. Of those patients with dengue hemorrhagic fever, 6 patients had developed dengue shock syndrome. Conclusion: Dengue presents as a highly unspecific illness and is hardly recognized as a clinical entity by primary health care physicians. Dengue infection can have potentially fatal consequences, and to date, vector control methods to prevent the spread of the virus have been unsuccessful. Although there are promising vaccine candidates in development, further studies are required for a greater understanding of the humoral immune responses to Dengue infection and observation disease pathogenesis.
Graph To Coherent Text: Passage Generation from Knowledge Graphs by Exploiting Edge Representations in Sentential Contexts

In the present digital age, much information is organized as knowledge graphs, where numerous techniques have been developed to retrieve relevant subgraphs. As the information represented in such retrieved subgraphs is not readily suitable for human laymen users to understand, it is useful to develop approaches to represent such information in natu-ral language. In this work, we propose a neural modeling framework that jointly learns to (1) generate topically coherent and informative text by computing the representation of the input knowledge graph for each sentential context, and to (2) generate text in a sentence-by-sentence order to improve tractability for long sequence generation. Our proposed approach improves the accuracy of text generation using objec-tive metrics such as BLEU and METEOR in comparison to established baselines such as graph transformer networks on the AGENDA dataset. Human evaluations also show that our proposed model compares favorably with established base-lines on the dimensions of informativeness and coherence.
A Cost-Efficient IoT-Enabled Alerting and Prediction System for Rural People: Survey

-IoT is the main high end-technological evolutions of the day that assist the interconnection and communicationby speedup of a device to device, device to human and human to human. It uses smart devices that used in sensing, analyzing and predicting. Thisresearch paper proposes a cost-efficient IoT enabled system with sensing rain, alerting the user, analyzing data and predicting flood based on the measurements of the rain. It uses the rain parameters such as temperature, humidity, and raindrop with a specific location using Global Positioning System (GPS) module using Wi-Fi.The temperature and humidity parameters are sensed by the DHT22 sensor and the rain by Raindrop sensor. The sensor senses data from the environment and stores the senseddata to the local storage (computer’s hard-disk) and alerts the users when the rain values exceed its threshold limit with its exact location using GPS module installed within Arduino and Wi-Fi module (ESP8266 Module). The Wi-Fi helps in connecting to the network. The alerting service is sent to the Mobile Phone by using a Global System for Mobile Communication (GSM) module technology with an interconnection of Arduino. The rainfall data from the sensors may be graphed and analyzed using MATLAB to clearly provide flood prediction. The damages due to floods are increasing due to changes in the weather across the globe. Such a localized alerting system would help the users be aware of depending disasters.
Cyclodextrin-Based Hyperbranched Polymers: Molecule Design, Synthesis, and Characterization

The cyclodextrin (CD) molecule, a host for a variety of smaller molecular guests, and hyperbranched polymers both possess molecule cavities in their molecular architectures. If the hyperbranched poly(β-cyclodextrin)s are established using modified β-CD molecules as monomers, their molecular inclusion capabilities for smaller molecular guests may be enhanced due to the combination of two different molecule cavities from both their hyperbranched topography architecture and CD molecule chain segments. Herein, three types of hyperbranched poly(β-cyclodextrin)s, i.e., HBP-ABx from ABx-type β-CD monomers, HBP-(By + ABx) from By core molecules and ABx-type β-CD monomers, and water-soluble HBP-AB2 from AB2-type β-CD monomers, were synthesized via hydrosilylation reaction under the thermal or ultraviolet activated polymerization. The hyperbranched structures of resultant poly(β-cyclodextrin)s were characterized using 1H NMR, 13C NMR, 29Si NMR, 1H−29Si heteronuclear multiple bond correlation, and size exclusion chr.
Resilience, Hope, and Self-Efficacy in Mothers having Children Diagnosed with Autism Spectrum Disorder

This research aimed to investigate resilience and hope as correlates and predictors of self-efficacy in mothers of children diagnosed with Autism Spectrum Disorder (ASD). Correlational research design was employed. Using purposive sampling strategy, a sample of 60 mothers having children with ASD with age range of between 4-12 years was selected from Children Hospital, Lahore. Three self-reported questionnaires were used for data collection that includes State Trait Resilience Inventory (Hiew, Mori, Shimizu, & Tominga, 2000), The Adult Dispositional Hope Scale (Snyder et al., 1991) and General SelfEfficacy Scale (Schwarzer & Jerusalem, 1995). Results showed that a significant positive relationship existed between resilience and hope. However, resilience and hope didn‟t have any significant relationship with self-efficacy. Multiple hierarchical regression analysis showed that self-efficacy was not predicted by resilience and hope. Findings imply the importance of considering socio-demographic characteristics of mothers rearing a child with ASD to better understand their sense of self-efficacy.
A Review on Face Mask Detection using Convolutional Neural Network

- Corona virus disease 2019 has become a major health problem. It is spreading very widely due to its contact transparent behavior. So WHO declared to wear mask in crowded areas as a prevention method. Some of the areas the diseases become widely spread out due to improper wearing of facial mask. So to overcome this problem we required an efficient mask monitoring system. By the development of machine learning and image processing analysis introduce methods for mask detection. By using image processing analysis and machine learning method is used for find out mask detection. Face mask detection can be done through various methods. Mainly convolutional neural network method is used rapidly. The accuracy and decision making is very high in CNN compared to others. Here we are discussed about various deep learning techniques used for face mask detection.