Miracle-dz/UniFAR-FTUs huggingface dataset:
Stripe patterns formed on a glass surface during droplet evaporation

When a suspension droplet dries on a glass surface, particles collect near the edge of the droplet boundary (contact line) and often leave a striped pattern as the droplet evaporates. During drying, the motion of the droplet contact line resembles stick-slip motion and it shrinks toward the center with an oscillatory motion. To explain the oscillatory motion and the mechanism of the stripe formation, we formulated a mathematical model that includes a friction force which the contact line feels when particles flow from the inside of the droplet to the droplet boundary. As a result of competition between this friction force and surface tensions at the contact line, the droplet oscillates as it dries and generates a striped film composed of particles
Pareto Explorer for Solving Real World Applications

An important characteristic of the Multi-objective Optimization Problems (MOPs) is that their solution sets typically form a ( k − 1)- dimensional object where k is the number of objectives involved in the MOP. Thus, it is only possible to approximate the entire set of interest for a relatively few numbers of objectives (say, k = 3 or 4). In this work, we address the numerical treatment of MOPs with more than four objectives which are termed as Many Objective Optimization Problems (MaOPs). Such problems have recently caught the interest in the industry as the decision-making processes are getting more and more complex. The recently proposed Pareto Explorer (PE) method raises as a solution for the MaOPs, it is conceived as a global/local exploration tool which consists of two principal phases: obtaining a global optimal solution for a given MaOP, and the local exploration of optimal solutions based on the preferences of a decision-maker. In this work, we demonstrate the eﬀectiveness of PE for solving real-world applications.
Design and Implementation a Novel System for Estimation Precise Transfer Function of DC Motor

Article history: Received: 30 June, 2020 Accepted: 04 October, 2020 Online: 20 October, 2020 A precise modelling plant system is substantial to improve the design of the DC motor controller, where a low accurate model may cause an unacceptable controller system. This study presents a hardware-in-the-loop (HIL) system for design a high speed motor data acquisition system (HSMDAQS) and injected collected data (ICD) Simulink model to estimate accurately the transfer function (TF) of a DC motor, without needing motor’s specification, providing high accuracy estimation tool that can be used to develop the design of a DC motor controller. The proposed system generates synching data to be imported into system identification (Sys Ident) application through a serial port. To show the performance design, a comparative study has been conducted between the experimental realization and simulation results in terms of dead time(td), rise time(tr), and settling time(ts), using a scope simulator. It was used three different DC motors to demonstrate the effectiveness of our approach in terms of average error step responses (AE-SR). The estimation results show that the best FIT between the response of the estimated TF and the collected data augmented by 95.03 % and stabilized despite using different motor’s speed. A comparison step response between experimental and simulation shows a very low deviation and minimized AE-SR below 10% for all tested motors. The developed system could be applied in a wide range of industrial applications, offering faster with accurately capturing data, high precision stabilized platform, a simpler implementation for dynamic systems, lower computational cost design, and flexibility.
ABATe: Automatic Behavioral Abstraction Technique to Detect Anomalies in Smart Cyber-Physical Systems

Detecting anomalies and attacks in smart cyber-physical systems are of paramount importance owing to their growing prominence in controlling critical systems. However, this is a challenging task due to the heterogeneity and variety of components of a CPS, and the complex relationships between sensed values and potential attacks or anomalies. Such complex relationships are results of physical constraints and domain norms which exist in many CPS domains. In this article, we propose ABATe, an Automatic Behavioral Abstraction Technique based on neural networks for detecting anomalies in smart cyber-physical systems. Unlike traditional techniques which abstract the statistical properties of different sensor values, ABATe learns complex relationships between event vectors from normal operational data available in abundance with smart CPS and uses this abstracted model to detect anomalies. ABATe detected more than 88 percent of attacks in the publicly available SWaT dataset featuring data from a scaled down sewage water treatment plant with a very low false positive rate of 1 percent. We also evaluated our technique's ability to capture domain semantics and multi-domain adaptability using a real-world automotive dataset, as well as a synthetic dataset.
One-step synthesis of polyethyleneimine-coated magnetite nanoparticles and their structural, magnetic and power absorption study

Magnetic nanoparticles (NPs) are especially interesting for several biomedical applications due to their chemical surface, especially for targeted cancer imaging and therapeutics. In order to realize these applications, it is important to know their magnetic properties among other complementary properties that help to improve the understanding of the synthesis process. In this work, we report the magnetic properties of polyethyleneimine-coated magnetite (PEI-Fe3O4) NPs synthesized by a one-step method via the co-precipitation method and using PEI as a stabilizer. Transmission electron microscopy (TEM) images revealed agglomerated magnetic nanoparticles with an average size of ∼10 nm; meanwhile, the X-ray diffraction (DRX) analysis confirmed a pure magnetite phase. The study of magnetic properties shows a superparamagnetic system with coexistence of non-interacting single NPs with a low blocking temperature (∼35 K) and interacting NPs in the aggregates with a higher blocking temperature (>150 K), in which the interparticle interactions of magnetic cores dominate over surface spin disorder. The interaction between the surface spin-disorder layer and NP core was found to be weak, related to a weak exchange bias effect. A maximum specific loss power (SLP) value of 70 W g−1 was obtained (f = 571 kHz and H = 23.87 kA m−1) indicating that the magnetic response plays a crucial role in determining the heating efficiency for future applications.
A Tangled Web: The Dynamics of Endosymbiotic Infections in a Linyphiid Spider

OF THESIS A Tangled Web: The Dynamics of Endosymbiotic Infections in a Linyphiid Spider Many arthropods are infected with bacterial endosymbionts that manipulate host reproduction, but few bacterial taxa have been shown to cause such manipulations. Mermessus fradeorum (Linyphiidae) is a sheet-weaving spider that displays both feminization and cytoplasmic incompatibility (CI). To correlate reproductive manipulations to endosymbionts, I surveyed the bacterial community of M. fradeorum using high throughput sequencing and found that individuals can be infected with up to five different strains of bacteria from the genera Wolbachia, Rickettsia, and Rickettsiella. Rickettsiella was found in all 23 tested spider matrilines. I used antibiotic curing to generate uninfected matrilines that I reciprocally crossed with individuals infected with Rickettsiella. Only 13% of eggs hatched when uninfected females were mated with Rickettsiella-infected males, while at least 83% of eggs hatched in the other cross types. This is the first documentation of Rickettsiella, or any Gammaproteobacteria, causing CI. I then characterized symbiotypes of M. fradeorum in central Kentucky to determine the variation in endosymbiotic community composition among host populations. Overall, regional populations of M. fradeorum share endosymbiont strains, but the frequency of infection varied among populations. These results suggest that endosymbiotic infections of M. fradeorum are dynamic and that populations are composed of a mixture of symbiont-induced phenotypes.
Exploring the Impacts of an Open Door Policy and a Mindfulness Room at the Intercollegiate Speech (Individual Events) Tournament

Two distinct tournament features were offered at a regional intercollegiate individual events swing: 1. ) an open door policy for all competition rounds and 2. ) a mindfulness room for students. A 16-item survey (with both qualitative and quantitative prompts) was administered at the conclusion of the swing to gain a sense of participants’ perceptions of past tournament experiences and experiences with the newly implemented features. Seventy-one (n=71) respondents participated (competitors, coaches, tournament staff, and hired judges). Analysis of the data revealed: 40% of participants had felt the need to leave a round in the past (a disproportionate 80% of which were women, nonbinary, or genderqueer), a clear quantitative increase in perceived confidence that competitors felt to leave the room as needed after the reading of the open door policy, judges and students had divergent perceptions on the effectiveness of the open door policy, and while the mindfulness room concept was praised, the main criticisms were the size and levels of accessibility to the room. The authors offer suggestions for administering an open door policy and a mindfulness room in a forensics context.
Phenolic compound derived from microwave-assisted pyrolysis of coconut shell: Isolation and antibacterial activity testing

Indonesia is rich in natural resources, coconut plantation being one of them. The coconut processing industry produces coconut shell (CS) waste. The most effective technique to increase the value of this waste is to convert CS biomass through pyrolysis process. This research focuses on intensification of conversion process of CS by Microwave-Assisted Pyrolysis (MAP) to obtain PA. PA contains phenolic compounds which have antibacterial properties so they can be formulated as an antibacterial agent. CS has moisture and ash content of 8.89% and 0.21%, respectively. PA was produced from the MAP of CS at 600W at 450℃ and 500oC for 10, 20, and 30 minutes. The PA was extracted using ethyl acetate to obtain phenolic contents. Optimum pyrolysis condition was found at 400oC for 30 minutes and yield of PA was determined at 32.20 g with total phenolic content (TPC) of 112.13 mg GAE/g. The inhibition zone of phenolic extract from coconut shell (PECS) using E. Coli was determined within 22-25 mm that quantitatively PECS can effectively kill bacteria. PECS by MAP and its aplication as an antibacterial agent has never been performed, so this work is an important contribution in the intensification of pyrolysis and in medical field.
Differentiate the Game Maker in Any Soccer Match Based on Social Network Approach

A game maker controls the game by passing the ball among the teammates and is considered the most influential player in any ball-passing multiplayer team game. In the current approach, we have represented the players and the ball passing among themselves using a dynamic social network structure. Now, the challenging task is to differentiate the game maker from any match where the performance of any individual player is not directly involved with the cumulative effect of the scoring mechanism. Different temporal graph centrality metrics, such as degree, closeness, betweenness, and clustering coefficient, have differentiated the game maker in the ball-passing network. We have analyzed some random games of FIFA men’s world cup 2018, to distinguish the game makers from the matches as a case study. Another challenging problem is to locate the tactical position of the influential passes. We have investigated the games and identified those areas in different time frames. The accuracy of our method is tested over the real-life benchmark data set. The analytical results exhibit notable improvement over the existing methods. Our study opens up a new framework for the strategic analysis not only for soccer but also for similar ball-passing multiplayer team games, such as basketball and hockey.
Multi-Camera Color Correction via Hybrid Histogram Matching

With the explosive popularity of multi-camera systems, a challenging problem is how to guarantee the inter-camera color consistency. In this paper, we have developed a hybrid histogram matching (HHM) algorithm that leverages the cumulative color histogram to fulfill this purpose, in which it mainly includes the global color mapping, and local color straightening for uniform color presentation across cameras. Our approach is applicable to any camera pair with sufficient viewing angle overlap, and can be easily extended to support multi-camera setup by pairwisely color map transfer. This HHM method has provided the superior efficiency for color correction when compared with the state-of-the-art algorithms, both objectively and subjectively, via extensive validations on different multi-camera systems. Additional ablation studies have been performed to further examine the capacity of our algorithm in practical applications. We would like to make all materials publicly accessible at https://njuvision.github. io/HHM/ for reproducible research.
Estimation of certain blood metabolites between normal, delayed sexual maturity and low growth rate Karan fries crossbred heifers in different seasons

The present study reports the seasonal variation of certain plasma metabolites in normal and delayed sexual maturity Karen Fries crossbred heifers at Livestock Research Center, ICAR-National Dairy Research Institute, Karnal, Haryana over a period of one year. Total 160 heifers; eight healthy heifers in each month [24, 16, 32, 24 healthy heifers in rainy, autumn, winter and summer, respectively and 8 heifers from each group (delayed sexual maturity and low growth rate) per season were selected for the study. Plasma metabolite like glucose, urea nitrogen, cholesterol and non-esterified fatty acid (NEFA) was estimated. There was significant (P< 0.05) seasonal variation of plasma metabolites like glucose, urea nitrogen, cholesterol and NEFA was observed. In delayed sexual maturity and low growth rate heifers mean plasma glucose, cholesterol and NEFA concentration differed significantly (P< 0.05) from healthy heifers and and also did not follow a similar pattern. It might be due to change or variation in the fodder other management effects. Herd status regarding metabolic parameters need to be evaluated regularly in different seasons to achieve set targets in terms of growth performance of heifers by adjusting feeding management.
Inclusion of Battery SoH Estimation in Smart Distribution Planning With Energy Storage Systems

Energy storage systems (ESSs) can improve energy management in distribution grids, especially with the increasing penetration of home energy management systems (HEMSs) that schedule household appliances and render them as smart loads. A large number of uncoordinated HEMSs can result in significant changes to the aggregated load profile of the distribution system. This paper proposes a framework and mathematical model for integrating ESS in the distribution grid to minimize the operation cost of the local distribution company (LDC) and alleviate the impact of uncoordinated HEMS operation on the distribution grid. A novel neural network (NN) based state of health (SoH) estimator for a lithium-ion (Li-ion) battery based ESS is proposed, which is incorporated within the LDC's planning problem. The results show that the proposed estimation model is an accurate estimation of the SoH of the ESS. The LDC's planning decisions are also compared, considering SoH of the ESS vis-á-vis linear degradation and no-degradation models.
Static vs. Dynamic Modelling of Acoustic Speech Features for Detection of Dementia

Dementia is a chronic neurological disease that causes cognitive disabilities and significantly impacts daily ac-tivities of affected individuals. It is known that early detection of dementia can improve the quality of life of patients through a specialized care program. Recently, there has been a growing interest in speech-based screening of neurological diseases such as dementia. The focus is on continuous monitoring of changes in speech of dementia patients, aiming to identify the early onset of the disease which could facilitate development of preventative treatment care. In this work, we propose a dynamic (temporal) modeling of acoustic speech characteristics aiming at identifying the signs of dementia. The classification performance of the proposed framework is compared with a baseline static modeling of acoustic speech features. Experimental results show that the proposed dynamic approach outperforms the static method. It achieves the classification accuracy of 74.55% compared to 66.92% obtained using the static models.
A Comprehensive Study of Blockchain Services: Future of Cryptography

Cryptography is the process of protecting information from intruders and letting only the intended users’ access and understand it. It is a technique originated in 2000 BC where simple methods were used in earlier times to keep the information in a way that is not understandable by everyone. Only the intended receiver knows how to decode the information. Later, as technology advances, many sophisticated techniques were used to protect the message so that no intrusion can invade the information. Many mathematically complex algorithms like AES, RSA are used to encrypt and decrypt the data. Due to the advancements in the computer science field, recently, cryptography is used in the development of cryptographic currencies of cryptocurrencies. Blockchain technology, a distributed ledger technology identified to be the foundation of Bitcoin cryptocurrency, implements a high-level cryptographic technique like public-key cryptography, Hash Functions, Merkle Trees, Digital signatures like Elliptic curve digital signatures, etc. These advanced cryptographic techniques are used to provide security to blockchain data and for the secure transmission of information, thereby making Blockchain more popular and demandable. Blockchain applies cryptography in various phases, and some of the techniques used in Blockchain are advanced in cryptographic sciences. This paper intends to provide a brief introduction to cryptography and Blockchain Technology and discusses how both technologies can be integrated to provide the best of the security to the data. This paper reviews the various cryptographic attacks in Blockchain and the various security services offered in Blockchain. The challenges of blockchain security are also analyzed and presented briefly in this paper.
Biomimetic Realization of a Robotic Penguin Wing: Design and Thrust Characteristics

Flapping flippers or fins are widely employed in biomimetic and bioinspired aquatic robots that imitate natural swimmers, such as fish and dolphins. This article involves robotic biomimetics of the penguin, which is often overlooked as an excellent swimmer benefiting from agile wings. To achieve equivalent swimming skills in an aquatic robot, the wing motion of a real penguin was investigated. Based on the findings, we developed a three-DOF robotic penguin wing that is able to implement the same flapping, feathering, and pitch motions as in natural penguins. A kinematic analysis is presented, and the generation of swimming motions is demonstrated. We designed experiments to study the thrust characteristics of the motion of each joint. The results suggest that the flapping motion generates the main thrust during locomotion and the pitch angle can effectively change the thrust direction while the feathering motion enables active control of the angle of attack (AoA). According to the results, stalling of the wing occurs near an AoA of 10$^{\circ }$ in the steady state; however, the feathering motion can avoid the stall and boost the net thrust by a factor of up to 7 relative to the net thrust without active feathering. Furthermore, the introduction of the feathering motion reduces the torque required to actuate the flapping motion. The hydrodynamics of the wing in different flow states are also discussed.
Historical reconstruction of the Puget Sound (USA) groundfish community

We examined historical and contemporary trends for a suite of groundfish species in Puget Sound, Washington, USA, to ask how the groundfish community has responded following shifts in fishing regulations, climate, food web, and a growing human population in the surrounding watershed. We used contemporary data (1990−2017) from a standardized annual bottom trawl survey with historical logbook information (1948−1977) from a research vessel. We standardized data to account for spatial and temporal effects on catch rate by first fitting a Bayesian model to the contemporary data, and then using the posterior distributions of the covariates as prior distributions when fitting models to the historical data. We found that most of the 15 species chosen for analysis had highly variable population dynamics within both time periods, and that patterns of variability were similar in the contemporary and historical time period. Surprisingly, there was little evidence of community-wide recovery following regulations that first limited and then banned commercial bottom trawling in the late 1980s to mid-1990s. Spotted ratfish and English sole dominated catches in both time periods, and species that were common in the historical time period were also common in the contemporary time period. The absence of coherent community changes in response to fisheries regulations and other major social and ecological changes may signal the complex dynamics of an urban estuary that is subject to multiple external drivers, and speaks to the need to consider long-term dynamic behavior of populations and communities when establishing ecological indicators.
An Offloading Strategy for Multi-User Energy Consumption Optimization in Multi-MEC Scene

Mobile edge computing (MEC) is capable of providing services to smart devices nearby through radio access networks and thus improving service experience of users. In this paper, an offloading strategy for the joint optimization of computing and communication resources in multi-user and multi-MEC overlapping scene was proposed. In addition, under the condition that wireless transmission resources and MEC computing resources were limited and task completion delay was within the maximum tolerance time, the optimization problem of minimizing energy consumption of all users was created, which was then further divided into two subproblems, i
Cooperative Learning and Enhanced Communication: Effects on Student Performance, Retention, and Attitudes in General Chemistry.

This report discusses the retention and performance of three sections of general chemistry that utilized different levels of cooperative learning and enhanced communication. The structured cooperative section (S-coop) required that students belonged to study groups, had group homework and group quizzes and had course credit driven electronic mail. The unstructured cooperative section (U-coop) encouraged students to form optional informal groups and provided for optional enhanced communication by paper mail. The control section used a standard lecture format without any cooperative learning or enhanced communication options. The student retention (C or better) was S-coop 85 %, U-coop 76 %, and Control 59 % (all differences were statistically significant). On the final exam the percent correct for common questions was S-coop 58%, U-coop 60%, and Control 55%. Adjusted for the difference in retention there was no significant difference between the two cooperative sections. The results of the Student Instructi.