Miracle-dz/UniFAR-FTUs huggingface dataset:
New sustainable and insulating building material made of cattail

SUMMARY: Due to the special structural properties of cattail (typha) building materials can be produced offering a combination of insulation and strength, which is unique on the market. The leaf mass of typha is especially suited due the structure of the plant. The leaves have a fiber-reinforced supporting tissue filled with soft open-cell spongy tissue providing for amazing statics and an excellent insulating effect. In the past few years, the Fraunhofer Institute for Building Physics investigated various product developments in cooperation with the inventor Dipl. -Ing. Werner Theuerkorn. The newly developed magnesite-bound typha board has an extremely high strength and dynamic stability despite a low thermal conductivity of about 0.055 W/mK and can solve energetic as well as static problems. This innovative building material possesses a lot of positive properties. With the typha board as infill of the timber frames and as an additional inside insulation layer an extremely slender exterior wall construction with wall heating is realized. Due to the simple processability and inherent stiffness the material could be adjusted to the irregular inclined walls. The suitability of the wall structure has been investigated over a measuring period of 1.5 years. The U-value of the whole building (infill and timber construction) is about 0.35 W/m²K. The low level of moisture applied by the mortar and plaster dried out fast to a constant moisture contents in the wooden supports of below 20 M. -%.
Different Concentrations of Potassium Silicate in Nutrient Solution Affects Selected Growth Characteristics and Mineral Composition of Barley (Hordeum vulgare L.)

This study was undertaken to determine the effect of potassium silicate (K2SiO3) on the physiological and growth characteristics and elemental composition of barley plants. Hydroponically grown barley (Hordeum vulgare L.) var. Wilma was exposed to four different levels of Si in the form of K2SiO3 at concentrations of 0 (Si0), 0.5 (Si0.5), 1 (Si1) or 1.5 (Si1.5) mM Si. Plants were analyzed for root length, number of dry leaves, number of trichomes, electron transport system activity in mitochondria (ETS), leaf pigment content and elemental composition of roots and leaves. Treatment with Si0.5 significantly increased the concentration of total chlorophylls, root length and ETS activity in barley. Plants with no Si added to the nutrient solution had significantly more dry leaves than plants from all Si-treated groups. Necrosis was observed in Si0 plants, while leaf damage was not visible in treated plants. According to the results of the study, we evidenced that plants were stressed due to Si deficiency. The addition of K2SiO3 significantly affected the concentration of Si, K, Ca, Cl, S, Mn, Fe and Zn in roots and leaves of barley. In barley treated with Si0.5, plants showed the best performance in terms of their physiological characteristics and growth.
Improving Data Quality in Health Care

The increasingly information intensive nature of health care demands a proactive and strategic approach to data quality to ensure the right information is available to the right person at the right time in the right format. The approach must also encompass the rights of the patient to have their health data protected and used in an ethical way. This article describes the principles to establish good practice and overcome practical
Electromagnetic Characterization of Thin Films by Using Non-contacting Waveguides

Surface impedance represents a crucial parameter for the characterization of thin films. Indeed, materials with a sheet impedance varying as a function of their elongation could be employed in radio frequency piezoresistive sensors. In order to estimate this quantity while having the possibility of stretching the sample under test, a waveguide-based non-contact approach is proposed. The absence of contact between the sample under test and the waveguides determines an electromagnetic field leakage, which is prevented by adopting an electromagnetic band-gap (EBG) structure. The surface impedance of the sample is retrieved through an inversion procedure exploiting the scattering parameters measured by using the proposed setup. The inversion procedure is based on a circuit representation of the waveguide-air-waveguide section as a π- junction. The reliability of the proposed measurement method has been experimentally assessed by using a WR137 waveguide. The proposed method allows to accurately determine the real part of the surface impedance (the sheet resistance) while higher uncertainty is achieved in the estimation of the imaginary part.
Modified Zeroing Neurodynamics Models for Range-Based WSN Localization From AOA and TDOA Measurements

With the rise of the internet of things, wireless sensor network (WSN) technology has gained unprecedented development and has attracted increasing attention from researchers. Due to the inherent characteristics of WSN, such as interaction with the environment, WSN localization becomes an essential and attractive topic in academia and industry. In this paper, the range-based localization problem in a mobile WSN application scenario is considered to be time-varying and modeled as a dynamic matrix equation by introducing the time parameter. Two modified zeroing neurodynamics (ZND) models are proposed and investigated to deal with range-based WSN localization problems from angle of arrival (AOA) measurement and time difference of arrival (TDOA) measurement. In addition, the convergence of the proposed models is theoretically analyzed. Furthermore, computer simulations on WSN localization are carried out to prove the effectiveness of the proposed models in terms of accuracy and robustness to the dynamic environment. Additionally, the application to underwater sensor node localization of underwater acoustic network (UAN) testbed is provided to illustrate the feasibilities of the proposed models for solving UAN localization problem.
An Optimized SWCSP Technique for Feature Extraction in EEG-based BCI System

Brain-computer interface (BCI) is an evolving technology having huge potential for rehabilitation of patients suffering from disorders of the nervous system, besides many other nonmedical applications. Multichannel electroencephalography (EEG) is widely used to provide input signals to a BCI system. Significant research in methodology employed to implement different stages of BCI system, has led to discovery of new issues and challenges. The raw EEG data includes artifacts from environmental and physiological sources, which is eliminated in preprocessing phase of BCI system. It is then followed by a feature extraction stage to isolate a few relevant features for further classification to a particular motor imagery (MI) activity. A feature extraction approach based on spectrally weighted common spatial pattern (SWCSP) is proposed in this paper to improve overall accuracy of a BCI system. The reported literature uses SWCSP for feature extraction, as it has outperformed other techniques. The proposed approach enhances its performance by optimizing its parameters. The independent component analysis (ICA) method is used for detection and removal of irrelevant data, while linear discriminant analysis (LDA) is used as a classifier. The proposed approach is executed on benchmark data-set 2a of BCI competition IV. It yielded classification accuracy of 70.6% across nine subjects, which is higher than all the reported approaches.
Using Crowdsourcing to Prioritize Bicycle Network Improvements

Effort to improve the bicycle route network using crowdsourced data is a powerful means of incorporating citizens in infrastructure improvement decisions, which will improve livability by maximizing the benefit of the bicycle infrastructure funding and empowering citizens to be more active in transportation decisions. This research developed a free, GPS-enabled smartphone application to collect socio-demographic and route data of cyclists in Atlanta. The crowdsourced data were then used to model the factors influencing bicycle route choices of different types of cyclists as defined by their perceived safety and comfort with a facility. Finally, this research refined a quality-of-service measure for bicyclists based on the perceived level of traffic stress (LTS) that the users attach to the facility. The developed quality-of-service measure can be used by transportation professionals to compare alternative roadway and bikeway designs using quantifiable variables such as speed limit, traffic volume, and number of through lanes.
System theoretic descriptions of physical systems

Twee vragen dienen zich aan. Waardoor wordt een Hamiltoniaans systeem (uitwendig of in toestandsvorm) gekarakteriseerd, en wat kunnen we zeggen over de eigenschappen van een Hamiltoniaans systeem? Deze twee vragen worden bestudeerd in Hoofdstuk 3, het centrale hoofdstuk van dit proefschrift. Zie: Samenvatting
‘All hands on deck’ or separate lifeboats? Public support for European economic solidarity during the Covid-19 pandemic

ABSTRACT What are the sources of public support for international aid in times of crises? This paper investigates the determinants of public support for the EU Covid-19 aid package (‘NextGenerationEU’, NGEU), the largest aid package in EU history. Using what is to the best of our knowledge the first EU-wide study of public opinion on the Covid-19 rescue package, we first establish that public support for within-EU redistribution is influenced by long-standing factors such as ideology and citizen identities, corroborating previous literature. Next, our vignette survey experiment shows that short-term shifts in support for the rescue package are driven mostly by elite endorsement cues rather than information about the precise terms of aid or amount. We also find that the role of elite endorsement cues varies across different subsets of the population depending on their level of political sophistication, national level attachment and country context. Conversely, the effects of policy details about the aid package are more mixed. Thus, in the face of multidimensional decision-making in times of crises, national institutions are a key catalyst of moving short-term support for policies of international solidarity. We discuss how our findings have implications for democratic governance and accountability in the EU.
Pemanfaatan Metode Klasifikasi Naïve Bayes Untuk Pendeteksi Berita Hoax Pada Artikel Berbahasa Indonesia

– Hoax news has been widely spread on the internet. Ease of creating and sharing is one factor. Hoax news is a threat and concentration of many parties, problems arise in identifying or classifying them because there is no identifiable pattern, and the writing style is free and not rigid. The lack of accuracy of the existing hoax detection system found the methods and attributes used to classify hoax news with high accuracy. On this basis, this research was carried out, as in most classifications of hoax news used as reference in this study, preprocessing was carried out (case folding, tokenization, stemming, and stopword removal), feature extraction and adding attributes other than preprocessing articles. done like the website where the article is posted. publication and site status. The results of this study obtained an accuracy of 72% which turned out to be a decrease of 6.6% compared to previous research, namely 78.6% because one site only publishes one hoax article and allows the site's domain to expire thereby reducing the weight of the classification value.
Real Time Data Monitoring Using LoRaWAN in Different Cloud Platforms

Internet of Things (IoT) is rapidly expanding, and a wide range of technologies are being developed for IoT solutions. The majority of studies on these solutions focus on a specific communication standard, which contradicts the IoT system’s overall architecture. This paper presents the methodology of a fully functioning LoRaWAN based IoT system that is connected to various cloud platforms and how each platform process the data collected. Finally, when the data value increases in a catastrophic situation, a user notification will be delivered. Presently, the described IoT structure serves the European region and its surrounding area. The system has been demonstrated as a service that is capable of serving a wide range of IoT-based applications across many cloud platforms.
Innovative outreach programs to attract and retain women in undergraduate engineering programs

Statistics Canada figures for 1998 show that women comprise two-thirds of graduates with degrees in fine arts, humanities and social sciences, yet only 12% of graduates in the science and technology fields are women. For the engineering profession alone, the figures are even more daunting - only 5% of registered Professional Engineers in Canada in 1998 were women. We can no longer afford to exclude the vast pool of talent represented by women, therefore effective recruitment and retention programs are necessary to encourage more women to consider a career in the field of engineering. This paper describes several projects undertaken at Ryerson Polytechnic University to increase the participation of women in engineering. These projects include the 'Discover Engineering' Summer Camp, in-class high school workshop program, one day engineering career conference, on-line mentoring program, student 'drop-in' hours and an incoming student welcoming reception. The paper discusses the impact of these initiatives, as measured by follow-up surveys and other evaluation tools. Figure 2, showing data broken down by gender, reveals an interesting snapshot of the state of engineering profession in Canada (Ontario data is representative of national statistics). While reasons for declining interest in engineering as a career are a focus of intense discussion within the profession and academia and are based on larger societal issues, it is clear that more women than ever are interested in pursuing engineering.
Tissue Adhesive, Conductive, and Injectable Cellulose Hydrogel Ink for On-Skin Direct Writing of Electronics

Flexible and soft bioelectronics used on skin tissue have attracted attention for the monitoring of human health. In addition to typical metal-based rigid electronics, soft polymeric materials, particularly conductive hydrogels, have been actively developed to fabricate biocompatible electrical circuits with a mechanical modulus similar to biological tissues. Although such conductive hydrogels can be wearable or implantable in vivo without any tissue damage, there are still challenges to directly writing complex circuits on the skin due to its low tissue adhesion and heterogeneous mechanical properties. Herein, we report cellulose-based conductive hydrogel inks exhibiting strong tissue adhesion and injectability for further on-skin direct printing. The hydrogels consisting of carboxymethyl cellulose, tannic acid, and metal ions (e.g., HAuCl4) were crosslinked via multiple hydrogen bonds between the cellulose backbone and tannic acid and metal-phenol coordinate network. Owing to this reversible non-covalent crosslinking, the hydrogels showed self-healing properties and reversible conductivity under cyclic strain from 0 to 400%, as well as printability on the skin tissue. In particular, the on-skin electronic circuit printed using the hydrogel ink maintained a continuous electrical flow under skin deformation, such as bending and twisting, and at high relative humidity of 90%. These printable and conductive hydrogels are promising for implementing structurally complicated bioelectronics and wearable textiles.
Methodology for assessment of area and properties of farmlands suitable for establishment of shelter belts

The aim of the study is to develop a methodology for assessment of the area and properties of buffer zones around drainage ditches and areas surrounding protective belts around natural streams, for transformation into “biomass factories”. In Latvia and neighboring countries, these buffer zones have significant biofuel production, as well as climate change mitigation and nutrient retention potential. A GIS based algorithm using various data sources to obtain information about conditions and land use in buffer zones has been created. Spatial data about drainage diches and surrounding areas are obtained from the Latvian Rural Support Service, Corine land cover, State Forest Service and Latvian Geospatial Information Agency. In this study 15-meter buffers are defined for soil scarification, planting, tending, harvesting and biomass production for energy and other appliances. Using the methodology elaborated within this study, 706797 features of buffer polygons (buffer sides) were identified, each labelled with a unique number. Each polygon is labelled with a number that determines from which ditch line the buffer is derived. Total area of the generated buffers – 167532 ha. The data obtained can make a significant contribution to assessing the potential of buffer zones suitable for establishment of shelter belts.
Portraying Cendekia Leadership in the Perspective of Ki Hajar Dewantara’s Trilogy

This study aims to describe the Cendekia leadership from the personality perspective of Ki Hajar Dewantara, the father of education in Indonesia. This research is a qualitative study that uses literature study as the method. Seven articles published in the national journal were used as the data of this study and then analyzed using content analysis method. The results of the discussion of cendekia leadership in the perspective of Ki Hajar Dewantara's character from the first philosophy are (1) Ing Ngarso Sung Tuladha; good leadership must behave and speak well and become a role model, discipline, able to be role model for everyone, innovators, protector, educator, honest, wise, and serve wholeheartedly, (2) Ing Madya Mangun Karsa means always help other, motivating and encouraging to work hard, inspiring, have a sense of empathy and sympathy, as well as able to collaborate, (3) Tut Wuri Handayani means that a leader who can encourage his subordinates to be at the forefront of achievement and individuals who are strong in facing obstacles, smart, creative, have a sense of justice, giving freedom to express themselves, and encourage people to be independent, effective, and efficient at work.
Long Short-Term Memory Recurrent Neural Network for Predicting the Return of Rate Underframe the Fama-French 5 Factor

The multifactor approach helps determine the linear connection between a diversified portfolio’s return and risk; however, the efficacy of the model models is still limited in the experiment. Algorithms in machine learning have recently grown in popularity to compensate for some of the shortcomings of theoretical models. This study applied a machine learning technique to compare the performance of the Fama-French 5-factor model (FF5). Two approaches are employed in the Fama-French model: Long Short Term Memory Recurrent Neural Network (LSTM-RNN) and Maximum Likelihood Estimation (MLE). From January 1, 2010, through March 3, 2022, the stock market in Ho Chi Minh City was experimentally researched. The rolling window approach is used in combination with the Root Mean Square Error (RMSE), and the results of the FF5 model with the LSTM-RNN algorithm are more efficient in prediction error than the MLE methodology. This contribution encourages investors and hedge fund managers to use the LSTM-RNN algorithm to boost forecasting efficiency.
Optimal Motion Planning in Unknown Workspaces Using Integral Reinforcement Learning

A novel motion planning scheme for optimal navigation in unknown workspaces is proposed in this letter. Based upon the Artificial Harmonic Potential Fields (AHPFs) theory, a robust framework for provably correct (i.e., safe and globally convergent) navigation is enhanced through Integral Reinforcement Learning (IRL)<xref ref-type="fn" rid="fn1"><sup>1</sup></xref> to obtain a provably complete solution for optimal motion planning in unknown workspaces. Our method aims at bridging the gap between the control theoretic framework of mathematical rigor, with the data-driven Reinforcement Learning (RL) paradigm, while preserving the strong traits of each approach. Finally, it is compared against an RRT<inline-formula><tex-math notation="LaTeX">$^\star$</tex-math></inline-formula> method to asses the optimality of the final results in a multiply connected synthetic workspace.
Thirty Years’ History since the Discovery of Pax6: From Central Nervous System Development to Neurodevelopmental Disorders

Pax6 is a sequence-specific DNA binding transcription factor that positively and negatively regulates transcription and is expressed in multiple cell types in the developing and adult central nervous system (CNS). As indicated by the morphological and functional abnormalities in spontaneous Pax6 mutant rodents, Pax6 plays pivotal roles in various biological processes in the CNS. At the initial stage of CNS development, Pax6 is responsible for brain patterning along the anteroposterior and dorsoventral axes of the telencephalon. Regarding the anteroposterior axis, Pax6 is expressed inversely to Emx2 and Coup-TF1, and Pax6 mutant mice exhibit a rostral shift, resulting in an alteration of the size of certain cortical areas. Pax6 and its downstream genes play important roles in balancing the proliferation and differentiation of neural stem cells. The Pax6 gene was originally identified in mice and humans 30 years ago via genetic analyses of the eye phenotypes. The human PAX6 gene was discovered in patients who suffer from WAGR syndrome (i.e., Wilms tumor, aniridia, genital ridge defects, mental retardation). Mutations of the human PAX6 gene have also been reported to be associated with autism spectrum disorder (ASD) and intellectual disability. Rodents that lack the Pax6 gene exhibit diverse neural phenotypes, which might lead to a better understanding of human pathology and neurodevelopmental disorders. This review describes the expression and function of Pax6 during brain development, and their implications for neuropathology.