Miracle-dz/UniFAR-FTUs huggingface dataset:
Modern Design Education: Nurture in Technological Innovation and Social Responsibility

There is a strong interactive relationship between the education and the development of modern design. Every essential progress in design education had most probably encouraged a further development of modern design. The encouragement came not only from the educational practice, but also from the educational theory study which inevitably referred to the cultivating of design idea. As the establishment or the change of ideas could deeply influence the practice as well as the academic researching in modern design, the training of good thinking is revealing its importance in modern design education implementation. Here under a historical background of the evolution of modern design movements, it gives a general interpretation on the idea and practice of modern design education in the method of technological and ethical sociology, in which the application of technology to innovation and the sense of social responsibility draw a central attention comparatively, so as to present and clarify the meanings of the relationship between technology, society and design with the main objective of exhibiting the importance of technological innovation and social responsibility in the principles of modern design education.
Assisting Elders with Dementia in Residential Settings through Music Therapy: A Literature Review

Dementia is one of the most prevalent diagnoses for elders causing strain and debilitation of their social, mental, physical, emotional, behavioral and psychological faculties. Due to the nature of this condition, treatments for dementia have been structured to aid and improve the well-being and quality of life for those afflicted. Some of the goals that assisted-living services establish include reducing anxiety, increasing levels of comfort, improving mood, memory care and bettering verbal processing. Music therapy has been an intervention that assists with establishing these goals and implementing strategies resulting in short-term and long-term effects for those receiving treatment for dementia. This paper explored how the literature based on music therapy for elders with dementia has been defined and evolved over time and what could be done to explore more social aspects of the work within an assisted-living setting on many levels (i.e. peer to peer, client to therapist, client to assisted living staff). The literature detailed the results from studies that have explored short-term and long-term effects of music therapy and the varying theoretical approaches developed and implemented. Additionally, the literature presented describe how music therapy treatments are introduced to programs seeking out non-pharmacological measures to treat elders with dementia. In so doing, music therapy is presented as assisting elders to be individually empowered through use and acknowledgement of their personal narratives as well as socially empowered through efforts of clients working and interacting with one another in the same setting along with staff and caregivers who work to improve their lives. ASSISTING ELDERS WITH DEMENTIA 3
Developing an Accurate MADM Model Based on Fuzzy Certainty Factor

Multi-Attribute Decision Making (MADM) models are applied to solve decision making problems with multiple mutually exclusive attributes. The involved uncertainties on models are usually derived from incompleteness and inconsistencies. The traditional MADM models so far have tried to compensate uncertainties by focusing on the occurrence of final decision maker judgments. The center of new attention is on fuzzy MADM, which zooms on ambiguities in describing events rather the uncertainty about the occurrence of those events. The proposed approach applies another factor which is well known in the expert systems as Certainty Factor (CF). Applying this factor to fuzzy MADM problems, the reliability or assurance of judgments by using the degree of belief and disbelief on decision maker judgments will be improved. The experiments conducted have shown that using this approach could increase the precision of decisions.
Role of Image Processing and Machine Learning Techniques in Disease Recognition, Diagnosis and Yield Prediction of Crops: A Review

Agriculture planning plays a significant growth and food security of agro-based country like India. In this Review we present a comprehensive and critical survey on current challenges and methodologies applied for various image processing and Machine learning approaches on variety of crops in their productivity increase, considering the following measures: Early detection/recognition of crop diseases, diagnosing methods and crop selection method in yield prediction. This paper presents an overview of existing reported techniques useful in detection of diseases in variety of crops. Finally we identify the challenges and some opportunities for future developments in this area.
The Influence of Marketing Mix on Customers ’ Decision-Making for Small and Medium-Sized Chinese Language Schools ( SMEs ) in Thailand

The study investigates the relationship between marketing mix factors (4Ps) and customers’ decision-making in choosing small and medium-sized Chinese Language Schools (SMEs) in the Bangkok Metropolitan Region of Thailand. The proposition of the study will look at whether or not there are some factors that influence customers’ decision-making in making their choice. The study also examines the direction of those relationships. A quantitative approach was used to collect data at Chinese language schools located in shopping malls in Bangkok Metropolitan using a self-administered questionnaire as research instrument. The outcomes suggest that entrepreneurs should be concerned with a convenient location as major priority as well as sales promotion to match with Thai people’s culture and lifestyle. The study also recommends entrepreneurs or marketers to allocate their marketing mix resources with respect to traditional and/or modern marketing media to meet the challenges of severe rivalry in the shifting era of the digital age.
Application of Semiparametric Non-Linear Model on Panel Data with Very Small Time Point

This research work investigated the behaviour of a new semiparametric non-linear (SPNL) model on a set of panel data with very small time point (T = 1). The SPNL model incorporates the relationship between individual independent variable and unobserved heterogeneity variable. Five different estimation techniques namely; Least Square (LS), Generalized Method of Moments (GMM), Continuously Updating (CU), Empirical Likelihood (EL) and Exponential Tilting (ET) Estimators were employed for the estimation; for the purpose of modelling the metrical response variable non-linearly on a set of independent variables. The performances of these estimators on the SPNL model were examined for different parameters in the model using the Least Square Error (LSE), Mean Absolute Error (MAE) and Median Absolute Error (MedAE) criteria at the lowest time point (T = 1). The results showed that the ET estimator which provided the least errors of estimation is relatively more efficient for the proposed model than any of the other estimators considered. It is therefore recommended that the ET estimator should be employed to estimate the SPNL model for panel data with very small time point.
Synthesis of Gold Colloid using Zingiber officinale : Catalytic Study

Aqueous extract of the root of ginger (Zingiber officinale) has been used to prepare gold nanoparticles. Almost spherical gold nanoparticles having diameter 3.22  1.13nm have been revealed from transmission electron microscope image. Evidence of the existence of such small nanopartilces has been also demonstrated by their UV-Vis spectra. FT-IR study was performed to know the interaction of the ingredients present in extract with the surface of nanoparticles. Catalytic efficiency of the gold nanoparticles was evaluated and reported in terms of catalytic activity parameter (), against the remediation of common environmental pollutants 4nitro phenol and few organic dyes.
Cognitive Web Application Firewall to Critical Infrastructures Protection from Phishing Attacks

Phishing scams and attacks attempt to trick people into providing sensitive personal information such as account login credentials, credit card numbers, banking details and other identifying data. This is done for malicious reasons, by disguising as a trustworthy entity in an electronic communication. It is an example of social engineering techniques used to deceive users and to exploit weaknesses in current web security. It is very popular with cybercriminals, as it is far easier to trick someone into clicking a malicious link in a seemingly legitimate URL than trying to break through a computer’s defenses. Nowadays, phishing scammers continually target many critical infrastructures and major financial institutions, companies, government departments, and online service providers around the world. For those infrastructures specifically, skilled phishers use advanced techniques to target both vigilant and naive employees, with destructive often zero-day attacks, including ransomware, malware, bots, spam, spoofing and
Towards Metamodel Integration Using Reference

The complexity of modern software engineering projects increases with growing numbers of artefacts, domain specific languages, and stakeholders with their concerns. To overcome these demands, different viewpoints are used to describe different languages specifying different artefacts, specific concerns of stakeholders, and domain specific languages. Therefore, the use of different viewpoints together in one software engineering project increases and requires technical support for automatic synchronization of the used viewpoints. This paper gives an overview about use cases for viewpoint synchronization and compares their fulfillment by existing approaches. As result, this vision paper proposes a new approach for synchronization of viewpoints to overcome the presented use cases with focus on reduction in synchronization and integration effort, on reuse of integration knowledge, and on viewpoint evolution.
Marfan 1 Marfan Syndrome

Marfan's syndrome is an autosomal dominant chromosomal disorder of connective tissue which may cause major abnormalities in the musculoskeletal, ocular (pertaining to the eye), and cardiovascular systems of the body. A description of this disorder is presented in this paper. It affects approximately . 03 to . 05% of the population; approximately 40,000 persons in the United States are currently diagnosed with Marfan's syndrome. Although little research has been conducted exploring the educational and psychological features of the co-presence of other disorders, such as learning disabilities or attention deficit hyperactivity disorder, one study identified 13% of Marfan syndrome sufferers as having a learning disability and 17% as having attention deficit disorders. Although these results may suggest a higher incidence of learning disabilities and attention deficit disorders among individuals with Marfan Syndrome compared to the general population, the author recommended caution in generalizing the results of the entire Marfan population given the small size of their sample and the uncertainty of the incidence of learning disabilities among the general population. Developmental impacts of the syndrome are also poorly understood, although some tentative conclusions can be advanced. Some of the psychoeducational implications are explored here, including school behavior and what steps school psychologists can take to help these children. (RJM) ******************************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. ********************************************************************************
Control of sensorless electrical drives operating in a hybrid flying platform

AbstractIn the paper, the results of an investigation on the electrical drive of a hybrid flying platform (BAL) are presented. Due to restrictions on flying platforms it is necessary to use solutions with a limited number of sensors. For that purpose an investigation of two versions of electrical drives with a BLDC motor without a speed feedback has been conducted. The obtained results have been compared and conclusions regarding the practical use of the motor drive have been made. The investigations discussed in the paper concern only the proposed methods of speed estimation based on current measurement.
Surface-Enhanced Raman Scattering as an Emerging Characterization and Detection Technique

While surface-enhanced Raman spectroscopy (SERS) has been attracting a continuously increasing interest of scientific community since its discovery, it has enjoyed a particularly rapid growth in the last decade. Most notable recent advances in SERS include novel technological approaches to SERS substrates and innovative applications of SERS in medicine and molecular biology. While a number of excellent reviews devoted to SERS appeared in the literature over the last two decades, we will focus this paper more specifically on several promising trends that have been highlighted less frequently. In particular, we will briefly overview strategies in designing and fabricating SERS substrates using deterministic patterning and then cover most recent biological applications of SERS.
he avoidance of farmyards by European badgers Meles meles n a medium density population nda

Mycobacterium bovis (TB) in cattle is a disease with far-reaching economic effects throughout Europe but especially in Great Britain and Ireland. Wildlife reservoirs, in particular the European badger Meles meles, continue to play an important role in the transmission of the disease, although the pathways of transmission are still poorly understood. The badger is an opportunistic feeder that takes advantage of seasonally abundant foods, such as fruits and insect larvae. Badgers might therefore be expected to enter farmyards to exploit grain stores or feed concentrates. This would bring them into close proximity with livestock present in those yards, potentially increasing the likelihood of disease transmission. This Irish study is the first to have looked at the use of a variety of farmyard types by free-ranging, GPS collared badgers from a medium-density population over a 3 years period. We found that badgers in our study area avoided all types of farmyards but particularly those where cattle were present. We investigated the influences of seasonality, social group members and badger gender on these preferences and found that they had no impact on this behaviour. As our results differ from the findings of studies carried out in high-density badger populations in Great Britain it is probable that different farming practices as well as differences in badger behaviour and ecology must be taken into account when designing measures to control this disease. Increasing our knowledge of the interactions between badgers and cattle in a variety of ecological situations will assist in proactive and general control of the disease in both species. © 2015 Elsevier B.V. All rights reserved.
Too Spineless to Rebel? New Labour's Women MPs

The 1997 British general election saw a record 120 women returned to the House of Commons, 101 of them Labour. Yet if the most striking feature of the 1997 intake into the House of Commons was the number of newly elected women, then the most striking feature of the backbench rebellions in that parliament was the lack of these women amongst the ranks of the rebels. They were less than half as likely to rebel against the party whip as the rest of the Parliamentary Labour Party; even those who did, did so around half as often. Attempts to explain this difference fall into two broad groups: (i) those that attempt to explain the difference away, as resulting from other characteristics of the women, and (ii) those that attempt to explain it – indeed, celebrate it – as evidence of a different, women's, style of political behaviour. Attempts at (i) are largely unconvincing: most of the supposed explanations for the difference do not stand up to empirical verification. Although difficult to prove, a belief in (ii) is dominant amongst the new women themselves.
Effects of Tillage on Some Selected Soil Physical Properties and Soil Organic Carbon Stocks in Northern Guinea Savanna Alfisol of Nigeria *Manasseh, E. A and **Yau S.L

Study on the effect of selected tillage practices on some soil physical properties and organic carbon stock in various dry aggregate size fractions was conducted at the Institute for Agricultural Research farm, Samaru, Zaria, Nigeria in the year 2010 and 2011. The treatments included no-tillage (NT) and conventional tillage (CT). Disturbed soil samples were collected at 0-5, 5-15 and 15-30 cm depths after harvest for dry aggregate stability and soil organic carbon stock determination in the various aggregates while undisturbed soil samples were collected at the same depths for bulk density determination. Tillage treatment effects on bulk density value occurred at 15-30 cm depths in both years, where NT exhibits significantly higher value by measure of 0.01 and 0.03Mgm -3 in the respective years. Both the MWD and GMD increases as the depths of sampling increases, with NT having greater value of MWD and GMD at their respective depths in the two years of the study. At 0-5 cm depth, NT management enabled enhancement of carbon stock in 2-5 mm aggregates size class by 21.8 and 27.6% in 2010 and 2011, at 5-15 cm depth, significant difference occur only in <0.05 mm size class in 2011, while in 15-30 cm depth, only 0.25-0.5mm aggregate size class sequestered 11.9% greater carbon stock in NT compared to CT treatment. No-till practices seem to favor increasing aggregate stability and carbon stock accumulation in various dry aggregate.
CRAb-COMPUTER GRAPHICS , VIRTUAL REALITY AND ANIMATION

We address the problem of sculpting and deforming shapes composed of small, randomly placed objects. Objets may be tightly packed such as pebbles, pills, seeds and grains, or may be sparsely distributed with an overarching shape such as flocks of birds or schools of fishes. Virtual sculpture has rapidly become a standard in the entertainment industry, as evidenced by the extensive use of software such as ZBrush Pixologic (2017b). Composites, though, are still usually created in a static way by individually placing each object or by sculpting a support surface and procedurally populating the final shape, which raises problems for the generalization of evolving shapes with visual continuity of the components. Large amounts of geometrical data are generated that must be maintained and processed, both by the CPU and by the GPU. Whenever the shape is stretched, pressed or deformed, one has to define how these compositing objects should turn, displace or disappear inside the volume, as well as how new instances should become visible to the outside. It is difficult to rely on a physical system to perform that task in real time. The system we suggest can be constructed upon any uniform mesh-based representation that can be deformed and whose connectivity can be updated by operations such as edge splits, collapses, and flips. We introduce the notion of CompEls as composing elements used to populate the mesh, with aperiodic distribution. These can be automatically updated under deformation. The idea is to sculpt the shape as if it were filled with little objects, without handling the complexity of manipulating volumetric objects. For this purpose, we suggest exploiting the properties of the uniform sampling of the surface with distances between vertices greatly exceeding the CompEls distances. Both the surface and the CompEls are immersed into deformation fields, such that the update of the uniform sampling can be used to track the movement of the CompEls, to identify those which should disappear inside the shape, and empty areas where further CompEls should be generated. This system uses GPU optimizations to efficiently perform the rendering of individual components. To our knowledge, no previous sculpting system allows the user to simultaneously see and sculpt agglomerates in such a fast and reliable fashion.
Structural adaptive smoothing for single-subject analysis in SPM: the aws4SPM-toolbox

There exists a variety of software tools for analyzing functional Magnetic Resonance Imaging data. A very popular one is the freely available SPM package by the Functional Imaging Laboratory at the Wellcome Department of Imaging Neuroscience. In order to enhance the signal-to-noise ratio it provides the possibility to smooth the data in a pre-processing step by a Gaussian filter. However, this comes at the cost of reducing the effective resolution. In a series of recent papers it has been shown, that using a structural adaptive smoothing algorithm based on the Propagation-Separation method allows for enhanced signal detection while preserving the shape and spatial extent of the activation areas. Here, we describe our implementation of this algorithm as a toolbox for SPM. 1 Theoretical background Functional Magnetic Resonance Imaging (fMRI) is a non-invasive tool for studying the functionality of the brain, searching for brain activation, and localizing cognitive functions. In the past decades, it has become increasingly important in neurosciences as well as for clinical applications such as presurgical planning. However, activation in brain is not subject to direct measurement. Second level characteristics are therefore used as indication of brain activity. One of them is the change in blood oxygenation (BOLD response) [6, 7] connected with some task the subject is to perform during the scan. A higher oxygenation level is associated with increased neuronal activity necessary to solve the task. In a typical block-design fMRI experiment the subject has to perform one or several tasks alternated by some period of rest. In the following we review the analysis of such fMRI data using a linear model for the expected BOLD response and show, how to include structural adaptive smoothing into this analysis. The original work has been published in [13]. In a series of papers the use of this smoothing algorithm in several applications [10, 12, 14] has been demonstrated. 1.1 fMRI analysis using linear modeling In fMRI, the BOLD effect can be used as a natural contrast employing the fact that voxels with increased neuronal activity are characterized by a higher oxygenation level [6, 7]. The expected BOLD response can be modeled by a convolution of the task indicator function with the hemodynamic response function. This function accounts for the fact that blood oxygenation is subject to some delay and shows a more complex structure than a simple indicator function [3]. For the rest of this paper we simply assume that we are able to model the expected BOLD-response as the specific model is not relevant for all considerations henceforth. Here, we adopt the common view [2, 15, 18], of a linear model Yi = Xβi + ei, (1) for the time series Yi = (Yit)t=1.T at each voxel i after reconstruction of the raw data, where X denotes the design matrix. The first q columns of X contain the expected BOLD response for the