Miracle-dz/UniFAR-FTUs huggingface dataset:
Contrasting ambient fine particles hygroscopicity derived by HTDMA and HR-AMS measurements between summer and winter in urban Beijing

Abstract. The effects of aerosols on visibility through scattering and absorption of light and on climate through altering cloud droplet concentration are closely associated with their hygroscopic properties. Here, based on field campaigns in winter and summer in Beijing, we compare the size-resolved hygroscopic parameter (κgf) of ambient fine particles derived by an HTDMA (Hygroscopic Tandem Differential Mobility Analyzer) to that (denoted as κchem) of calculated by an HR-ToF-AMS (High-resolution Time-of-Flight Aerosol Mass Spectrometer) measurements using a simple rule with a uniform internal mixing hypothesis. We mainly focus on contrasting the disparity of κgf and κchem between summer and winter to reveal the impact of atmospheric processes/sources on aerosols hygroscopicity and to evaluate the uncertainty in estimating particles hygroscopicity with the hypothesis. We show that, in summer, the κchem for 110, 150 and 200 nm particles was averagely ~ 10 %–12 % lower than κgf, with the greatest difference between the values observed around noontime when aerosols experience rapid photochemical aging. In winter, no apparent disparity between κchem and κgf is observed for those > 100 nm particles around noontime, but the κchem is much higher than κgf in the late afternoon when ambient aerosols are greatly influenced by local traffic and cooking sources. By comparing with the observation from other two sites (Xingtai, Hebei and Xinzhou, Shanxi) of north China, we verify that atmospheric photochemical aging of aerosols enhances their hygroscopicity and may induce a coating effect which thereby leads to 10 %–20 % underestimation of the hygroscopic parameter if using the uniform internal mixing assumption. The coating effect is found more significant for these >100 nm particles observed in remote or clean regions. However, local primary sources, which result in an externally mixture of the fine particles with a large number of POA (Primary Organic Aerosol) in urban Beijing, makes the particle much less hygroscopic and cause 20–40 % overestimation of the hygroscopic parameter by the mixing rule assumption. In addition, we also note lower κchem than κgf for 80, 110 and 150 nm particles during the nighttime of winter, particularly in polluted days, probably due to a nighttime coating effect driven by condensation of secondary hygroscopic species on pre-existing aerosols in cold season. Our results suggest that it is critical to parameterize the impacts in model simulations to improve the evaluation of the aerosols indirect effect.
HaptiSculptVR: Virtual Reality Open Source 3D-Design with Haptic Feedback

In this thesis, an application is presented for deforming the surface of a 3D model (Sculpting) with haptic feedback in virtual reality (VR). The HTC Vive VR set and the Touch 3D stylus from 3D Systems is the hardware used for this project. The software base for the sculpting is the open source tool SculptGL [1], which was modi ed to implement VR and a haptic interface. The haptic feedback of the Touch does not only naturally increase the immersion into the VR even further, it also enables people with visual impairments to use the application by feeling the surface structure. At the end of the work, a user study was conducted on the usability with and without haptic feedback during Maker Faire Hannover 2018. This study showed that sculpting in VR is much more intuitive and practical than working on a screen and that the use of haptic feedback accelerates this experience.
MOELS: Multiobjective Evolutionary List Scheduling for Cloud Workflows

Cloud computing has nowadays become a dominant technology to reduce the computation cost by elastically providing resources to users on a pay-per-use basis. More and more scientific and business applications represented by workflows have been moved or are in active transition to cloud platforms. Therefore, efficient cloud workflow scheduling methods are in high demand. This paper investigates how to simultaneously optimize makespan and economical cost for workflow scheduling in clouds and proposes a multiobjective evolutionary list scheduling (MOELS) algorithm to address it. It embeds the classic list scheduling into a powerful multiobjective evolutionary algorithm (MOEA): a genome is represented by a scheduling sequence and a preference weight and is interpreted to a scheduling solution via a specifically designed list scheduling heuristic, and the genomes in the population are evolved through tailored genetic operators. The simulation experiments with the real-world data show that MOELS outperforms some state-of-the-art methods as it can always achieve a higher hypervolume (HV) value. Note to Practitioners—This paper describes a novel method called MOELS for minimizing both costs and makespan when deploying a workflow into a cloud datacenter. MOELS seamlessly combines a list scheduling heuristic and an evolutionary algorithm to have complementary advantages. It is compared with two state-of-the-art algorithms MOHEFT (multiobjective heterogeneous earliest finish time) and EMS-C (evolutionary multiobjective scheduling for cloud) in the simulation experiments. The results show that the average hypervolume value from MOELS is 3.42% higher than that of MOHEFT, and 2.27% higher than that of EMS-C. The runtime that MOELS requires rises moderately as a workflow size increases.
Comparison of Software Design Models

Model comparison has been widely used to support many tasks in model-driven software development. For this reason, many techniques of comparing them have been proposed in the last few decades. However, academia and industry have overlooked a classification of currently available approaches to the comparison of design models. Hence, a thorough understanding of state-of-the-art techniques remains limited and inconclusive. This article, therefore, focuses on providing a classification and a thematic analysis of studies on the comparison of software design models. We carried out a systematic mapping study following well-established guidelines to answer nine research questions. In total, 56 primary studies (out of 4,132) were selected from 10 widely recognized electronic databases after a careful filtering process. The main results are that a majority of the primary studies (1) provide coarse-grained techniques of the comparison of general-purpose diagrams, (2) adopt graphs as principal data structure and compare software design models considering structural properties only, (3) pinpoint commonalities and differences between software design models rather than assess their similarity, and (4) propose new techniques while neglecting the production of empirical knowledge from experimental studies. Finally, this article highlights some challenges and directions that can be explored in upcoming studies.
MORINGA OLEIFERA GUM EXUDATE AS CORROSION INHIBITOR ON MILD STEEL IN ACIDIC MEDIUM

The present work focuses the study of corrosion inhibition efficiency of gum exudate obtained from the bark of Moringa oleifera (MO). The specimens used were mild steel coupons (MS) of specific dimensions and practical studies were carried out by using mass loss method in acidic medium . The results showed good trend in inhibition efficiency which indicated that as concentration of the inhibitor was raised percentage of inhibition efficiency too improved but declined with rise in temperature. The adsorption took place by physical adsorption of molecules on MS surface. Thermodynamic parameters were obtained and adsorption complies with Langmuir adsorption isotherm.
Antioxidant and Enzyme Inhibitory Properties of Mangifera indica leaf Extract

The foliar residues of Mangiferaindica tree are usually burned or used for soil amelioration except nominal uses as fodder.To add value to this agricultural waste, extracts of the leafy residues of M. indica were studied to analyze their potential as antioxidants and to inhibit the enzymes related to the management of diabetes, Alzheimer’s Disease (AD), hepatic disorders as well as to identify important phytochemicals present in the extracts.Results depicts that the leaves have notable bioactivities. The methanol extract (ME) showed much potential than ethyl acetate fraction after hydrolysis (HME) against α-amylase and α- glucosidase. The activity against the enzyme β-glucuronidase was also higher than that of the commercial β- glucuronidase inhibitor. The extract after hydrolysis showed better antioxidant and acetylcholinesterase inhibitory activities. Detection of important phytochemicals such as chrysin and myricetn, alizarin, arbutin, hydroquinone, tyrosol, taxifolin, kaempferol, mangiferin, and the vitamin alpha tocophereol, in addition to a number of organic acids, amino acids, fatty acids, sugars and polyols by GC-MS and HPTLC based analysis of the extract of M. indica leaf, also suggest the use of the leaves as sources of these important phytochemicals.More concisely HME with more number of detected metabolites found better to be used against oxidative stress as well as enzymes related to neural and liver disorders than that of ME.
Witness generation in existential CTL model checking

Hardware and software systems are widely used in applications where failure is prohibitively costly or even unacceptable. The main obstacle to make such systems more reliable and capable of more complex and sensitive tasks is our limited ability to design and implement them with sufficiently high degree of confidence in their correctness under all circumstances. As an automated technique that verifies the system early in the design phase, model checking explores the state space of the system exhaustively and rigorously to determine if the system satisfies the specifications and detect fatal errors that may be missed by simulation and testing. One essential advantage of model checking is the capability to generate witnesses and counterexamples. They are simple and straightforward forms to prove an existential specification or falsify a universal specification. Beside enhancing the credibility of the model checker’s conclusion, they either strengthen engineers’ confidence in the system or provide hints to reveal potential defects. In this dissertation, we focus on symbolic model checking with specifications expressed in computation tree logic (CTL), which describes branching-time behaviors of the system, and investigate the witness generation techniques for the existential fragment of CTL, i.e., ECTL, covering both decision-diagram-based and SAT-based. Since witnesses provide important debugging information and may be inspected by engineers, smaller ones are always preferable to ease their interpretation and understanding. To the best of our knowledge, no existing witness generation technique guarantees the minimality for a general ECTL formula with nested existential CTL operators. One contribution of this dissertation is to fill this gap with the minimality guarantee. With the help of the saturation algorithm, our approach computes the minimum witness size for the given ECTL formula in every state, stored as an additive edge-valued multiway decision diagrams (EV+MDD), a variant of the well-known binary decision
Towards an optimal thermal comfort and energy efficient workplace

We, humans, spend 80-90% of our lives indoors. Thereby the building has two main functions, namely: protect their occupants and provide the occupants a comfortable indoor environment. However, the last one seems a big challenge, since every individual is different from each other, based on the factors as age, gender, clothing, activity, positioning within the building or body mass. At the current situation, building service systems in most buildings are maintained at a steady level based on fixed schedules and average values. As a result, the thermal comfort of building occupants are hardly met. In the meantime, the same building service systems account for up to 50% of the energy consumption in the commercial sector. A response to this challenge is started with the introduction of personal comfort systems, which focuses on the individual occupants instead of average values of a large group of people. However, we are not there yet. This thesis is contributing to the response by focusing on efficient usage of personal comfort systems and tries to close the loop between the building service system and building occupants by finding a proper balance between providing thermal comfort and reducing energy consumption.
Human Skin Detection from Image using Gaussian Algorithm

-This paper presents the procedures of Human skin detection. For this we propose preprocessing (RGB mean value) that combines a smoothed 2-D histogram [4] and GAUSSIAN approach, for automatic human skin detection in color images. The main objective of this paper is to provide the maximum prefect area of human skin to be detected. The experimental result has show that the performance of the Gaussian approach works well over the Human skin detection, eye detector .
Value of Serum Zinc, Magnesium and Copper in Obese and Normal Weight Children

Background: Childhood obesity is one of the most serious public health challenges of 21st century. The problem is global and is steadily affecting many low- and middle-income countries. The rising prevalence of childhood overweight and obesity represent a major health concern, as obesity is an important risk factor for a number of diseases. A strong evidence indicating that a disturbance of serum levels of zinc, copper and magnesium plays important role in the development of obesity and its related diseases. Our aim is to determine the mean zinc, magnesium and copper levels in obese and overweight children as compared to the levels in normal weight controls to study its relationship with overweight and obesity. Objective: We aimed to assess, evaluate and compare serum zinc, magnesium and copper in obese, overweight and normal-weight children. Patients and methods: The study was a case-control study conducted on 60 subjects 20 obese children, 20 overweight children and 20 normal weight children. All of them were subjected to full history taking, complete examination, and routine investigation including CBC, SGOT, SGPT, RBS, urea, Creatinine, TSH, lipid profile and specific laboratory investigation including serum zinc, magnesium and copper. Results: In obese and overweight children, there were increased serum copper levels together with reduced serum levels of zinc and magnesium regardless age and sex when compared to normal weight children. Conclusion: In obesity, there were increased serum copper levels together with reduced serum levels of zinc and magnesium regardless age and sex. Obese and overweight may be at a greater risk of developing imbalance (mainly deficiency) of trace elements, which may be playing an important role in the pathogenesis of obesity and related metabolic risk factors.
ANÁLISIS DE ESCENARIOS PARA EL MANTENIMIENTO INDUSTRIAL DE UN TALADRO UTILIZANDO VENSIM PLE (ANALYSIS OF SCENARIOS FOR THE INDUSTRIAL MAINTENANCE OF A DRILL USING VENSIM PLE)

Un aspecto importante dentro del mantenimiento industrial radica en que no se elaboran simulaciones, y se debe considerar que el mantenimiento es un modelo dinamico en donde esta latente el parametro del tiempo. El mantenimiento industrial tiene diversas vertientes, las cuales podemos identificar como mantenimiento predictivo, preventivo y correctivo, en donde se involucrar los elementos que logran satisfacer caracteristicas esenciales del mantenimiento mostrando escenarios en un entorno graficos de Vensim Ple. Los escenarios de analisis permiten evaluar los elementos necesarios para abordar al mantenimiento en sus diferentes fases en funcion al desempeno del proceso involucrado. Los resultados obtenidos mediante esta herramienta son una base de datos con cada uno de los casos de exito y aquellos que han generado una dificultad en analisis y resolucion, la base de datos sirve como fuente de informacion en variables que se definen dentro del modelo para su posterior simulacion y analisis de escenarios. An important aspect of industrial maintenance is that there are no simulations made, and it should be considered that maintenance is a dynamic model where the time parameter is latent. Industrial maintenance has different aspects, which we can identify as predictive, preventive and corrective maintenance, where the elements that manage to satisfy essential maintenance characteristics are involved, showing Scenarios in a graphical environment of Vensim Ple. The analysis scenarios allow to evaluate the elements necessary to approach the maintenance in its different phases according to the performance of the process involved.The results obtained through this tool are a database with each one of the success cases and those that have generated a difficulty in analysis and resolution, the database serves as a source of information in variables that are defined within the model for Its subsequent simulation and analysis of scenarios.
Formalizing the Metatheory of Metaprogramming in a Metalogical Framework

We investigate the feasibility of formalizing the syntaxes, type systems, operational semantics, and especially the metatheories of a collection of multi-stage programming languages within the metalogical framework Twelf, a framework usually employed when dealing with singlestage programming systems. More specifically, we consider three different modal-logical based systems for staged computation, and we succeed in adequately representing them all within Twelf. Compared to most applications of Twelf, proving correctness of the representations is here a non-trivial task. The problem of distinguishing variables from different stages is solved by combining standard higher-order abstract syntax with an intrinsic encoding of world-based-scopes inspired by Kripke semantics; we show that this approach does not prevent the representation of operational semantics and Twelf verifications of relevant metatheorems. One of the treated metaprogramming systems comprises two languages, and a key result is a successful Twelf formalization of a type preserving translation between these two languages by introducing an intermediate first-order representation of free variables. We also challenge our representation methodology by in one case formulating a small-step operational semantics of the language, proving it equivalent to the big-step one, and showing type soundness by the standard method of progress and preservation – all formalized within Twelf. The experience gained suggests that even though Twelf does not provide any explicit support for reasoning about metaprogramming features, its general facilities are powerful and flexible enough to allow multi-stage programming systems to be formalized within the framework, with effort mostly comparable to conventional single-stage cases.
Coevolvable hardware platform for automatic hardware design of neural networks

This paper proposes a system for the automatic hardware design of neural networks based on cooperative coevolutionary paradigms and multiple reconfigurable devices. The authors' system is composed of a logic synthesis tool, multiple reconfigurable devices and an embedded processor executing the coevolutionary algorithm. The partitioning of the engineering design process follows current practices in hardware/software codesign based on both information on arrival rate /spl lambda/ of requests and the service time /spl mu/ of the reconfigurable devices. The system is suitable under some conditions for industrial applications such as a reactive system but also because it can be connected to multiple systems in a totally networked industrial environment which allows download of the same hardware configuration on multiple on ine devices.
A Study of Personalized Learning Behavior Evaluation Method Based on Deep Neural Network

The development of computer technology has greatly changed and influenced human production and life style. With the development of computer technology, the intelligent algorithm of neural network has also been developing rapidly. Deep learning is a method that can learn the intrinsic characteristics of data, which interprets data by simulating human brain to construct multi-layer neural network. In this paper, the deep neural network algorithm was optimized, analyzed and applied to the research of personalized learning behavior evaluation method, and then the most specific application effect was analyzed and evaluated. The comparative analysis shows that this method is superior to other traditional algorithm methods, it has better applicability and learning effect and has certain promotion value and significance.
Soymida febrifuga aqueous root extract maneuvered silver nanoparticles as mercury nanosensor and potential microbicide

The present communication reports a rapid, uncomplicated, sustainable and facile method of ecofriendly synthesis of silver nanoparticles (AgNPs). The pressing need for the development of benign, profitable and eco-friendly alternative routes has inspired researchers to explore plant extracts as safer replacements to hazardous chemicals. In the present study, a benign method of synthesis of AgNPs using Soymida febrifuga aqueous root extract has been developed. The characterization studies of synthesized AgNPs revealed spherical morphology and crystalline nature of AgNPs. The average particle size was 21.81 nm. The synthesized AgNPs were employed as mercury nanosensor for the selective and sensitive detection of toxic mercury ions in water and soil samples. The AgNPs showed a marked visual color change and change in surface plasmon resonance band on interaction with mercury ions. The greater selectivity of AgNPs towards mercury ions was observed. The limit of detection of mercury by 100 μL of colloidal AgNPs was found to be 2×10 M visually and 1.332×10 M spectrophotometrically in water samples and × M visually and 22.3×10 M spectrophotometrically in soil samples. The method makes use of a small quantity of AgNPs for detection of mercury in water and soil samples. The method proposed in the present study provides a rapid, selective and sensitive method for detection of mercury ions in environmental water and soil samples. The synthesized AgNPs were also used as effective microbicidal agents. The microbicidal potential of the synthesized AgNPs was checked against two gram positive and gram negative bacterial strains. World Scientific News 114 (2018) 84-105 -85
Making the problem visible: project specific information in collaborative design

This paper describes our current work in the development of an interactive, collaborative design space. It attempts to anticipate a future in which complex design problems are undertaken by an interdisciplinary, collaborative group of contributors working within an electronic, networked environment. These networked working groups are made possible by the expanded use of high-speed digital networks and are expected to continue to grow within the design profession Using the design of an academic building as a case study, several new tools and techniques were used to develop an information place superimposed over the three-dimensional digital model of the site and proposed building. These tools allow the user to create a collection of data including site documentation and analysis; propose interventions; and access the data through three-dimensional icons in the model. Several new techniques related to collecting and accessing information within the collaborative space are discussed.