Miracle-dz/UniFAR-FTUs huggingface dataset:
Explaining social insurance participation: the importance of the social construction of target groups in China

ABSTRACT The extension of welfare coverage to immigrants and their participation in welfare programmes has been a subject of concern in many countries. By applying the theory of social construction of target groups and a framework of stakeholder analysis, this article attempts to explain why migrants in the construction sector of China fail to participate despite the urban pension scheme aiming to expand its coverage. By analysing social construction and the interaction among the government, enterprises and migrants, this study suggests that migrants in the construction sector are considered a necessity for urban economic development but most migrants are low-skilled with limited education; thus, the policy is characterized by selectivity and inflexibility, which has feed-forward effects on both enterprises and individuals. On the one hand, enterprises select skilled technicians and management personnel to participate in urban pension schemes while compromising with most other construction workers to avoid contribution to the social insurance pool; on the other hand, most individual migrants also believe the unlikelihood of truly benefiting from the urban pension extension. This article suggests that local governments should change their stereotypes and negative attitudes toward construction workers to ensure that the objective of equity could be realized in policy design and implementation.
Design and Synthesis of New Curcuminoid Compounds and their Derivatives as Antioxidant Agents

A series of new curcumin analogues and their derivatives were synthesized by reacting curcumin analogues with various substituted hydrazine compounds to afford new pyrazol derivatives. The preparation of ether and ester derivatives was also carried out. All synthesized compounds were characterized using FT-IR, 1HNMR, 13CNMR, and MS-ESI. The evaluations of these compounds have shown a good inhibition activity as antioxidant agents against the stable radical of diphenylpicrylhydrazyl (DPPH). Findings from this work demonstrated a high inhibition activity in compounds substituted with hydroxyl phenol groups in comparison with compounds with other groups.
A Novel Approach towards Rating Free-Text Responses in Job Recruitment

The use of chatbots has become mainstream in the ﬁeld of stafﬁng and recruitment. It has been observed that candidates tend to be much more at ease when interacting with chatbots. The responses provided by the candidates to the questions posed to them via chat-bots are evaluated on the basis of various parameters by human evaluators who may have a subjective bias towards what deﬁnes a good response. This is especially the case, when it comes to evaluating free-text responses to open-ended questions that have little to no domain constraints. To overcome this hurdle involving human bias, we propose an alternate approach that utilizes modern techniques in the ﬁelds of Natural Language Processing and Deep Learning to develop an algorithm that rates free text responses in an impartial manner on the basis of the mood/sentiment expressed by the candidate, the grammatical accuracy of the answer and the relevance of the response w.r. t. the question asked while penalizing it for the presence of any negation or grammatical error, thus acting as a baseline model that aims to achieve the stated task. This algo-rithm thus sets a common standard towards what can be considered a good response thereby overcoming the hurdle arising from human perspective and establishing a criterion for evaluating free text responses.
A HYBRID APPROACH FOR CROP YIELD PREDICTION USING MACHINE LEARNING AND DEEP LEARNING ALGORITHMS

Agriculture is defined as the science and art of cultivating the flora and fauna. Farming in India is ranked as second around the globe and occupies 60.45% of Indian land. The Indian economy, dominatingly, depends upon farming along with agro-industry things. The soil ingredients (like Nitrogen, Phosphorous, Potassium), crop rotation, soil clamminess, atmospheric and surface temperature, precipitation, etc, play an efficient role in cultivation. The present evidence related to this field includes a model which is incorporated with ML algorithms (Random Forest, Decision Tree, Artificial Neural Network) to determine best crop. In this paper, the proposed model is enhanced by applying deep learning techniques and along with the prediction of crop, a clear information is achieved regarding the amounts of soil ingredients needed with their expenses separately. It provides a better accuracy than the existing model. It analyzes the given data and help the farmers in predicting a crop which in return help in gaining profits. The climatic and soil conditions of land are taken into consideration to predict a proper yield. The objective is to present a python based system that uses strategies smartly to anticipate the most productive reap in given conditions with less expenses. In this paper, SVM is executed as Machine Learning algorithm while LSTM and RNN are used as Deep Learning algorithms.
Dynamic value iteration networks for the planning of rapidly changing UAV swarms

In an unmanned aerial vehicle ad-hoc network (UANET), sparse and rapidly mobile unmanned aerial vehicles (UAVs)/nodes can dynamically change the UANET topology. This may lead to UANET service performance issues. In this study, for planning rapidly changing UAV swarms, we propose a dynamic value iteration network (DVIN) model trained using the episodic Q-learning method with the connection information of UANETs to generate a state value spread function, which enables UAVs/nodes to adapt to novel physical locations. We then evaluate the performance of the DVIN model and compare it with the non-dominated sorting genetic algorithm II and the exhaustive method. Simulation results demonstrate that the proposed model significantly reduces the decision-making time for UAV/node path planning with a high average success rate.
Hydroxypropyl lignins and model compounds: synthesis and characterization by electron-impact mass spectrometry

Presentation d'une methode de synthese iterative de derives hydroxypropyles de phenols substitues permettant le controle du degre d'allongement de la chaine, methode appliquee a la preparation de composes modeles de la lignine. L'analyse par MS a impact electronique de ces composes permet de determiner le degre d'allongement de la chaine hydroxypropyl. L'hydrogenolyse suivie de la CPV et de la MS de l'hydroxypropyl lignine permet la determination des sites et du degre d'hydroxypropylation des fractions volatiles
A finite element method for degenerate two-phase flow in porous media. Part II: Convergence

Abstract Convergence of a finite element method with mass-lumping and flux upwinding is formulated for solving the immiscible two-phase flow problem in porous media. The method approximates directly the wetting phase pressure and saturation, which are the primary unknowns. Well-posedness is obtained in [J. Numer. Math., 29(2), 2021]. Theoretical convergence is proved via a compactness argument. The numerical phase saturation converges strongly to a weak solution in L2 in space and in time whereas the numerical phase pressures converge strongly to weak solutions in L2 in space almost everywhere in time. The proof is not straightforward because of the degeneracy of the phase mobilities and the unboundedness of the derivative of the capillary pressure.
Formulation and evaluation of ketoirolac tromethamire-Eudragit solid dispersions of potential sustained-release properties

Le ketorolac tromethamine (KT) est un anti-inflammatoire non steroidien qui presente une demi-vie d'environ six heures. L'objectif de cette etude est de preparer des formes de KT a liberation prolongee en realisant une dispersion solide dans des matrices de polymeres Eudragit (Eud) par la technique de co-evaporation. Deux polymeres Eud, Eud RS 100 et Eud RL 100, ont ete utilises pour preparer les coprecipites de KT dans differents rapports medicament:polymere. Les coprecipites KT-Eud prepares ont ete caracterises en termes de rendement, de teneur en medicament et de profils de liberation du medicament in vitro. De plus, les proprietes physicochimiques de certains coprecipites ont ete caracterisees par analyse calorimetrique differentielle (ACD) et spectroscopie infrarouge afin d'etudier l'eventuelle interaction KT-Eud a l'etat solide. L'interaction du KT avec les polymeres Eud testes a egalement ete etudiee en solution dans du tampon PBS de pH 7,4 sur vingt jours. Enfin, l'activite analgesique du coprecipite KT-Eud RS 100 (1 :5) a ete evaluee par la methode du « tail-flich » et comparee au KT non modifie. La liberation du medicament in vitro est plus lente pour les dispersions faites a partir d'Eud RS pur que pour celles preparees a partir d'un melange d'Eud RS/RL. Les courbes ACD des systemes KT-Eud RS 100 (1:5) ont montre une disparition totale des pics de fusion du medicament, ce qui laisse penser que la dissolution du medicament dans la matrice de polymere est homogene. Eud RL 100 presentait une meilleure capacite d'adsorption que le polymere Eud RS 100 en raison du plus grand nombre de fonctions ammonium quaternaires presentes a sa surface. L'activite analgesique maximum du coprecipite KT-Eud RS 100 (1:5) a ete observee entre 5 et 6 h, et s'etendait jusqu'a 10 h, tandis que l'activite analgesique maximum du ketorolac non modifie etait comprise entre 2 et 2,5 h.
Nonsmooth Adaptive Control for Uncertain Nonlinear Systems: A Non-recursive Design Approach

In this letter, a one-step nonsmooth adaptive controller design framework is proposed the first time for a class of nonlinear systems with general non-parametric uncertainties. By virtue of a novel non-recursive synthesis philosophy, a nonsmooth adaptive stabilizer can be constructed straightforwardly from the system in a possible simplest form, which facilitates practical implementations. In reference to well-acknowledged recursive design based approaches, direct improvements with this new non-recursive methodology include largely reduced synthesis complexity along with an essential detachment of control law design and stability analysis. A numerical example is provided to demonstrate both the simplicity and effectiveness of the proposed algorithm.
Phishing Website Detection using Machine Learning

Today internet or websites plays a major role in every person life. Almost Every sector using the website services like banking sector using some apps for payment, passport sector is using for registration and renewal of passport, government sector for application of PAN cards, Adhar cards etc. This makes the human life simpler. But this provides an opportunity to make phishing websites. The phishing websites is same as legitimate or real websites. The purpose of the phishers is to stole their personal information, account ID, Passwords from individuals and organizations. They even add some tricks by asking security questions like pet name, city name to gain user’s trust. Although legitimate and phishing looks like same there are some features that make difference between those two things. That features such as IP address, URL length, having @ symbol, double slash redirection, Prefi and suffix, having subdomain, domain registration link, HTTPS tokens, Request URL, URL of anchor, disabling right click, using pop-up window and some more. Already many approaches are proposed for detecting phishing websites machine learning is most appropriate one. This is because there are some common features which can be identified by machine learning. In this paper we used random forest algorithm to detect phishing websites based on feature that make difference between both of the websites.
Facial imaging and landmark detection technique for objective assessment of unilateral peripheral facial paralysis

ABSTRACT In this paper, we propose a hypothesis that the facial landmark detection methods constructed by a private UPFP facial dataset can perform better than the model on a healthy facial dataset in the task of UPFP facial landmark detection. For proving this hypothesis, a customized UPFP facial dataset with 68 facial landmark annotations was built. A state-of-the-art facial landmark detection method was employed on the three evaluation datasets to exploit and prove the hypothesis. The mean error of validation dataset is 3.15, 56% lower than 7.42 that of the healthy dataset, which proves the hypothesis is true.
Premium estimation in the fire insurance through semiparametric bootstrap

Along with the development of information, science and technology, there is a quite popular developing resampling method, namely bootstrapping. Bootstrap estimates asymptotically against its original value (observation). Thus, the greater bootstrap replication, the resample distribution will be normally distributed. It indicates that the bootstrap estimator gives better results. Based on the goodness-of-fit test by using Kolmogorov-Smirnov test, the severity on fire insurance data follow Weibull 2 parameter distribution. A case study is conducted on reinsurance company’s data for shopping centre’s fire. It is a big data. Since it is a reinsurance company’s data, the data completeness may be inadequate. It causes the severity claim to be processed using semiparametric bootstrap.
Compact Continuous Time Common-Mode Feedback Circuit for Low-Power, Area-Constrained Neural Recording Amplifiers

A continuous-time common-mode feedback (CMFB) circuit for low-power, area-constrained neural recording amplifiers is proposed. The proposed CMFB circuit is compact; it can be realized by simply replacing passive components with transistors in a low-noise folded cascode operational transconductance amplifier (FC-OTA) that is one of the most widely adopted OTAs for neural recording amplifiers. The proposed CMFB also consumes no additional power, i.e., no separate CMFB amplifier is required, thus, it fits well to low-power, area-constrained multichannel neural recording amplifiers. The proposed CMFB is analyzed in the implementation of a fully differential AC-coupled neural recording amplifier and compared with that of an identical neural recording amplifier using a conventional differential difference amplifier-based CMFB in 0.18 μm CMOS technology post-layout simulations. The AC-coupled neural recording amplifier with the proposed CMFB occupies ~37% less area and consumes ~11% smaller power, providing 2.67× larger output common mode (CM) range without CM bandwidth sacrifice in the comparison.
Self-Regenerating Crime: The Resilient Network of a Sector of Rio de Janeiro’s Drug Trafficking in the 1970s

O crime que se regenera: A resiliente rede de um segmento do narcotrafico fluminense em 1970 traca uma analise de rede social (ARS) do narcotrafico fluminense no inicio dos anos 1970. Depois de revisar a teoria do crime organizado e onde a ARS se posiciona, mostramos como a rede foi construida. As partes restantes exploram o social embeddedness da rede, sua topologia e como ela se comporta diante de estrategias de ataque. Os resultados mostram que a rede se organizava em uma topologia comunitaria de alta modularidade com efeito de pequeno-mundo e pequena a moderada acoplagem social, potencialmente resiliente contra estrategias de ataque. Na conclusao, tracamos algumas implicacoes para a teoria sociologica mais geral.
An application of adaptive synchronization of uncertain chaotic system in secure communication systems

ABSTRACT Chaotic secure communication via synchronization of chaotic systems has attracted increasing attention in recent years. This note aims to introduce the function projective synchronization (FPS) of coupled fractional-order (FO) complex chaotic Lü system in the master-slave system formalism up to the desired scaling function matrix in the presence of bounded model uncertainties. An efficient chaotic secure communication scheme is proposed using the chaotic masking approach. In order to increase the unpredictability of the information signal, the transmitted signals to the channel are considered as the FO derivative of the product of the information signal and the states of the chaotic system. At the receiver side, by employing the Lyapunov stability theorem, an appropriate adaptive FO control law is derived to synchronize the master and slave systems. After the robust synchronization is achieved, the information signal can be recovered accurately with high speed in the transient response. Finally, to verify the effectiveness of the theoretical results, two numerical simulations are performed and some comparisons based on the adaptation parameter of the control law are provided.
Long Term Efficacy and Safety of Herring Roe Oil in the Treatment of Psoriasis, a 39-week Open-label Extension Study

The effect of omega-3 poly-unsaturated fatty acid supplements in patients with Psoriasis vulgaris has previously been investigated, but interventions varied in source, composition, dose, administration route and duration of treatment. The observed beneficial effects in patients with Psoriasis vulgaris using herring roe oil (HRO) as a dietary supplement prompted the conduct of this investigation. We monitored the longer-term efficacy and safety of as oral treatment for patients with plaque psoriasis originally included with a Psoriasis Area Severity Index (PASI) 4 points. The most commonly reported adverse events in both groups were gastrointestinal in nature. No serious adverse reactions were reported.
The perception concerning the COVID-19 pandemic: case of Turkey

Objectives: This study aims to evaluate the level of knowledge and perception of the Turkish society about the COVID-19 pandemic. Methods: This cross-sectional study whose sampling consists of 903 adults. Results: About half (49.6%) of the participants' information sources about COVID-19 composed of printed and visual media tools such as television, radio, newspaper, etc. 57.5% of the participants stated that their self-knowledge levels about COVID-19 were at a good level, whereas 19.7% of them at a very good level. 64.4% of the participants stated that their health would be seriously damaged if they get this virus; 58.9% of them thinks that this virus will severely damage their place of the resident; 50.9% of them stated that they trust that this crisis will be handled effectively by the health authorities of Turkey. Participants rated themselves an average of 8.7 points on compliance with COVID-19 measures. It was found that the participants had a 55% confidence in the Coronavirus Scientific Advisory Board (Turkey) and the World Health Organization (WHO) regarding COVID-19. Conclusions: Like all over the world, health authorities also in Turkey have taken several measures in the context of fighting against the pandemic and they expect society to comply with these measures. The fact that individuals in the society fulfill their individual responsibilities by confirming the accuracy of the information took place in printed/visual and social media from reliable sources is an important factor in reducing the effects of infectious diseases.
Developing a University Children’s Collection for Pre-Service Teachers Using PLACID

Abstract Not all academic librarians who oversee children’s collections for pre-service teachers have backgrounds in K-12 education. To develop a robust collection, the St. Cloud State University library reached out to an assistant professor in the Department of Teacher Development to help weed their children’s literature collection and recommend new titles because of their dual expertise with both libraries and schools. This commentary paper will outline the development of a children’s collection for pre-service teachers from the perspective of a faculty member with school library media expertise using an acronym they have deemed as PLACID: Pleasure, Levels, Awards, Curriculum, Illustrations, Diversity.
Review on the modeling of the laser sintering process for Polyamide 12

One of the most promising additive manufacturing techniques is selective laser sintering (SLS) of thermoplastic materials. However, the materials successfully applicable to laser sintering (LS) are very limited today. In this study the exceptional position of polyamide 12 powders is underlined. Several numerical and experimental studies have been carried out to make comparisons between the use of powdered materials for polyamide 12 and other types of polymers during the SLS process. The complexity of this process and the interaction between the different phenomena involved has not been fully understood. In this work we highlight the different models of the selective laser sintering of polyamide 12 as well as their different results in order to better understand the functioning of this process.
Selection and Micropropagation of an Elite Melatonin Rich Tulsi (Ocimum sanctum L.) Germplasm Line

Tulsi (Ocimum sanctum L.) is a sacred plant of medicinal and spiritual significance in many cultures. Medicinal properties of Tulsi are ascribed to its phytochemicals with antioxidant capabilities. The current study was undertaken to screen a large seed population of Tulsi to select germplasm lines with high antioxidant potential and to standardize protocols for micropropagation and biomass production to produce a phytochemically consistent crop. A total of 80 germplasm lines were established under in vitro conditions and screened for their antioxidant potential determined with the 2,2-diphenyl-1-picrylhydrazyl (DPPH) bioassay. The micropropagation of a selected line, named Vrinda, was established using nodal cultures grown on Murashige and Skoog medium containing benzylaminopurine (1.1 µM), gibberellic acid (0.3 µM), and activated charcoal (0.6%). The antioxidant phytohormones melatonin and serotonin were quantified in the field and greenhouse grown tissues of Vrinda and melatonin levels were found to be consistent in both conditions with higher serotonin levels under field conditions. This integrated approach combining the in vitro selection and propagation offers potential applications in the development of safe, effective, and novel natural health products of Tulsi, and many other medicinal plant species.