Miracle-dz/UniFAR-FTUs huggingface dataset:
Landscape structure is a major driver of plant and arthropod diversity in natural European forest fragments

Disentangling the effects of different landscape and local attributes on the biota of habitat patches is often challenging. In Central European forest-steppe ecosystems the high number of forest fragments and the relatively homogenous matrix between them offer the opportunity to disentangle the effects of habitat size and landscape structure (both landscape composition and landscape configuration) on plant and arthropod biodiversity. We selected 40 forest fragments: 20 forest fragments in extensive, dry, sandy forest-steppe region and 20 fragments in a mesic forest-steppe region of Hungary. We classified the detected plant and arthropod species according to their habitat association as forest specialist species or open habitat species. We then tested the effect of fragment size, landscape composition, and landscape configuration on their species richness and abundances. We found that increasing forest fragment size, forest habitat amount, and forest edge length had in general positive effects on forest spider abundance, but negative on open-habitat arthropod abundances and
The Effect of Educational Intervention on Health Literacy, Self-e�cacy and Quality of Life in Suburban Women of Mashhad

Background Health literacy is one of the important factors to improve menopausal quality of life that Proper and timely education and tailored to the needs of individuals, caused to improve quality of life. This study aimed to investigate the effect of educational intervention on health literacy, self-e�cacy, and quality of life in women. This quasi-experimental study with the control group was performed on 107 suburban women aged 40-60 years during 2021-2022. Participants were randomly selected by substituting and selected avenue number 3 as the experimental group and 6 as the control group. instruments of this study were Iranian Health Literacy and Scherer Self-E�cacy and Menopausal Quality of Life Questionnaires. The educational intervention was performed in 4 training sessions of 95 minutes once a week.Questionnaires were completed before training, immediately after training, and 3 months later. Data were analyzed by SPSS21 and independent t-test, Kruscalovalis, and linear regression tests.
Pheromone Incentivized Intelligent Multipath Traffic Scheduling Approach for LEO Satellite Networks

Low Earth Orbit (LEO) satellite networking has been an indispensable and promising concept for extending the Internet coverage of future space-air-ground integrated networks to oceanic and remote airspace. However, the topology dynamics of the LEO Satellite Network (LEO-SN) for network state perception [1] and the intermittent nature of the Inter-Satellite Links (ISLs) for multipath routing discovery [2], [3] both induce new complicated challenges to multipath traffic scheduling for the sake of improving the utility of the LEO-SN facility [4]-[6]. Motivated by these challenges, this paper aims to develop an AI aided intelligent multipath traffic scheduling approach for bolstering autonomous and efficient communications of LEO-SN. To achieve this, we formulate the multipath traffic scheduling problem into a pheromone incentivized Markov Decision Process (MDP) by considering ant routing protocol and adapting pheromone to LEO-SN. Employing enhanced pheromone characterizing network state, we propose ant-inspired multipath routing discovery, which is capable of promptly discovering routing paths available in the dynamic topology. To improve the utility of these discovered routing paths, we employ deep deterministic policy gradient into the pheromone-incentivized MDP-based scheduling problem to derive an intelligent multipath traffic scheduling strategy. The experimental results are further presented to show the achievable performance improvement.
Industrial Adoption of Model-Based Systems Engineering: Challenges and Strategies

Maheshwari, Apoorv M.S.A.A. , Purdue University, December 2015. Industrial Adoption of Model-Based Systems Engineering: Challenges and Strategies. Major Professor: Daniel A. DeLaurentis. As design teams are becoming more globally integrated, one of the biggest challenges is to efficiently communicate across the team. The increasing complexity and multi-disciplinary nature of the products are also making it difficult to keep track of all the information generated during the design process by these global team members. System engineers have identified Model-based Systems Engineering (MBSE) as a possible solution where emphasis is placed on the application of visual modeling methods and best practices to systems engineering (SE) activities right from the beginning of the conceptual design phases through to the end of the product lifecycle. Despite several advantages, there are multiple challenges restricting the adoption of MBSE by industry. We mainly consider the following two challenges: a) Industry perceives MBSE just as a diagramming tool and does not see too much value in MBSE; b) Industrial adopters are skeptical if the products developed using MBSE approach will be accepted by the regulatory bodies. To provide counter evidence to the former challenge, we developed a generic framework for translation from an MBSE tool (Systems Modeling Language, SysML) to an analysis tool (Agent-Based Modeling, ABM). The translation is demonstrated using a simplified air traffic management problem and provides an example of a potential quite significant value: the ability to use MBSE representations directly in an analysis setting. For the latter challenge, we are developing a reference model that uses SysML to represent a generic infusion pump and SE process for planning, developing, and obtaining regulatory approval of a medical device. This reference model demonstrates how regulatory requirements can be captured effectively through model-based representations. We will present
Municipal-to-Industrial Water Reuse via Multi-Stage and Multi-Pass Reverse Osmosis Systems: A Step from Water Scarcity towards Sustainable Development

Wastewater reclamation is a promising solution to growing pressure on limited water resources. In this study we evaluated the efficiency of boron removal from effluent at a water resource recovery facility (WRRF) using a two-stage/two-pass RO membrane system. We propose using measurements of electrical conductivity (EC) as a proxy for boron concentration. We tested our approach to boron estimation and the proposed split partial second pass (SPSP) system at an established WRRF and a pilot plant we constructed at the same location. Results showed that boron in the effluent was directly related to the concentration of EC. The proposed regression equation (y = 4.959 × 10-5x + 0.138) represents a rule of thumb for wastewater plant operators. The proposed SPSP system was optimized through manipulation of operating conditions, achieving a promising total water recovery of 64% at maximum boron rejection (over 85% removal) in a manner that was both cost-effective and flexible. This study demonstrates that two-stage/two-pass split-partial permeate treatment with a high pH for boron removal offers a sustainable freshwater supply option suitable for use by the semiconductor industry.
Tiefenscannende Weißlichtinterferometrie in maschinennaher Umgebung

Zusammenfassung Weißlichtinterferometer sind hochauflösende optische Messgeräte zum dreidimensionalen Messen von Mikrostrukturen. Der Einsatz solcher Messgeräte in maschinennaher Umgebung abseits schwingungsgedämpfter Labore wird durch Umgebungsschwingungen erschwert oder sogar unmöglich gemacht. Daher wird nach Algorithmen oder modifizierten Anordnungen gesucht, um den Einfluss der Störschwingungen zu kompensieren bzw. aus den Ergebnissen herauszurechnen. In diesem Beitrag wird ein passives Kompensationsverfahren vorgestellt, mit dem der Einfluss einer monofrequenten Störschwingung kompensiert werden kann. Dazu wird ein punktförmig messendes Laserinterferometer verwendet, das in das Weißlichtinterferometer (WLI) integriert ist und parallel zur Weißlichtmessung mit höherer zeitlicher Auflösung das Interferenzsignal des Lasers aufzeichnet. Die Bestimmung des jeweiligen Abstands zwischen WLI und Messobjekt erfolgt nachträglich durch Fourieranalyse, wobei die erforderlichen Parameter wie Frequenz, Amplitude und Phasenlage der Störschwingung aus dem Amplituden- bzw. Phasenspektrum des Interferenzsignals ermittelt werden. Diese Information wird genutzt, um die gestörten WLI-Korrelogramme zu korrigieren. Anschließend kann die Oberflächentopographie auf konventionelle Weise mit Hilfe der Hüllkurven- und der Phasenauswertung bestimmt werden.
Sparser Ordinal Regression Models Based on Parametric and Additive Location‐Shift Approaches

The potential of location‐shift models to find adequate models between the proportional odds model and the non‐proportional odds model is investigated. It is demonstrated that these models are very useful in ordinal modelling. While proportional odds models are often too simple, non‐proportional odds models are typically unnecessary complicated and seem widely dispensable. In addition, the class of location‐shift models is extended to allow for smooth effects. The additive location‐shift model contains two functions for each explanatory variable, one for the location and one for dispersion. It is much sparser than hard‐to‐handle additive models with category‐specific covariate functions but more flexible than common vector generalised additive models. An R package is provided that is able to fit parametric and additive location‐shift models.
key technologies of Wireless Optical Communication

Wireless Optical Communication combines the advantages of wireless communication and fiber communication. In Access Network, it is a very useful method to solve "the last mile" problem. In this paper, according to the Agile 155 system we developed and the next generation developing product with ATP part, several key technologies in the system are discussed.
Bioinspired Stretchable Transducer for Wearable Continuous Monitoring of Respiratory Patterns in Humans and Animals

We report a bio-inspired continuous wearable respiration sensor modeled after the lateral line system of fish which is used by the fish for detecting mechanical disturbances in the water. Despite the clinical importance of monitoring respiratory activity in humans and animals, continuous measurements of breathing patterns and rates are rarely performed in or outside of clinics. This is largely due to conventional sensors being too inconvenient or expensive for wearable sensing for most individuals and animals. The bio-inspired air-silicone composite transducer is placed on the chest and measures respiratory activity by continuously measuring the force applied to an air channel embedded inside a silicone-based elastomeric material. The force applied on the surface of the transducer during breathing changes the air pressure inside the channel which is measured using a commercial pressure sensor and mixed-signal wireless electronics. We extensively characterized the transducer produced in this work and tested it with humans, dogs, and laboratory rats. The bio-inspired air-silicone composite transducer may enable the early detection of a range of disorders that result in altered patterns of respiration. The technology reported can also be combined with artificial intelligence and cloud computing to algorithmically detect illness in humans and animals remotely, reducing unnecessary visits to clinics.
Spectroscopic Characterization of Wood Surface Treated by Low-Temperature Heating

1) As a study for the verification of heat treated wood according to ISPM No. 15, the spectroscopic characteristics of the heat treated wood surface were analyzed. Various functional groups were observed on the IR spectrum, but it was difficult to find any particular difference between wood species, heat treatment time and storage period. HBI (hydrogen-bonding intensity) shows the change of the heat treated wood according to the storage time, but the change of wood with the heat treatment time was hard to be observed. On the PCA score plot, however, it was possible to sort the wood according to the heat treatment time of 60 minutes or 90 minutes in the species. The standards for classification of heat-treated wood in PCA were aromatic rings in lignin and C-H bending in cellulose, and these components were able to classify heat-treated wood by ISPM No. 15.
Separation of ampicillin on polar-endcapped phase: Development of the HPLC method to achieve its correct dosage in cardiac surgery

The accurate, simple, and selective reversed phase high performance liquid chromatography (RP-HPLC) has been established and validated for the determination of an antibiotic ampicillin (AMP) in human blood plasma. The SPE extraction was used for the sample preparation. Chromatographic separation was accomplished by a mobile phase containing 15 mM monopotassium phosphate solution of pH 3.3 and methanol (75:25, v/v) in an isocratic mode at a flow rate of 1.4 mL min−1 at 30 °C. The separation was evaluated on a column with a new polar-endcapped C18 stationary phase Arion® Polar C18 or well-known phase Luna® Omega Polar C18. Excellent linearity (R 2 0.9998) was shown over range 10–300 mg L−1 with mean percentage recovery 90%. Peak shapes were symmetrical in both columns, Arion® Polar C18 and Luna® Omega Polar C18, with asymmetry factor of 1.0 and 1.4, tailing factor of 1.0 and 1.2, and retention factor of 4.6 and 5.6, respectively. The Arion® Polar C18 was almost 1.4-fold more effective than Luna® Omega Polar C18 phase. The LOQ for ampicillin was achieved 10 mg L−1 for Luna® Omega Polar C18 and 5 mg L−1 for Arion® Polar C18 using 20 µL of a solution containing 0.24 mg mL−1 of cephalexin as an internal standard. A number of articles dealing with the determination of ampicillin is limited, therefore, this study showed the HPLC method suitable for the determination of AMP in human blood plasma from patient who underwent elective cardiac surgical revascularization. In addition, the determination of AMP was also performed for the first time using an Arion® Polar C18 column, which effectively separated AMP from other compounds present in human blood plasma. This new polar-endcapped phase can help in separation of polar antibiotics or other polar compounds, which are unsuccessfully separated on conventional C18 column, and thus can help during method development.
Identification of Social and Economic Expectations: Contextual Reasons for the Transformation Process of Industry 4.0 into the Industry 5.0 Concept

The dynamic development of the fourth industrial revolution, focused on the implementation of Industry 4.0 technologies, sparked fears of governments and society regarding the dehumanization of the industry in the future. Currently, there is a need to consider sustainable development and the crucial role of man in the assumptions of industry’s future development. Concerns about the implementation of the fourth industrial revolution’s technology became the basis for building the assumptions of Industry 5.0. The article aims to identify the social and economic expectations of the development of the fourth industrial revolution in the context of the development of the sustainability, humanization, and resilience of Industry 4.0. The article presents the results of research obtained based on a critical analysis of the literature and surveys conducted among representatives of Polish society. As a result of the research, key social expectations as to the directions of development of the Industry 4.0 concept were identified. Recommendations for industry development focused on three areas of development—human-centric, sustainable, and resilient—were established. The presented research results will allow the development of an investment strategy and a government policy to support the development of industry based on the human-centric digitization of the economy.
An Attempt to Optimize Supercritical CO2 Polyaniline-Polycaprolactone Foaming Processes to Produce Tissue Engineering Scaffolds

Conjugated polymers are biomaterials with high conductivity characteristics because of their molecular composition. However, they are too rigid and brittle for medical applications and therefore need to be combined with non-conductive polymers to overcome or lessen these drawbacks. This work has, consequently, focused on the development of three-dimensional scaffolds where conductive and non-conductive polymers have been produced by combining polycaprolactone (PCL) and polyaniline (PANI) by means of supercritical CO2 foaming techniques. To evaluate their therapeutic potential as implants, a series of experiments have been designed to determine the most influential variables in the production of the three-dimensional scaffolds, including temperature, pressure, polymer ratio and depressurization rate. Internal morphology, porosity, expansion factor, PANI loads, biodegradability, mechanical and electrical properties have been taken as the response variables. The results revealed a strong influence from all the input variables studied, as well as from their interactions. The best operating conditions tested were 70 °C, 100 bar, a ratio of 5:1 (PCL:PANI), a depressurization rate of 20 bar/min and a contact time of 1 h.
Instructional Leadership Practices Among Headmasters and The Correlation with Primary Schools’ Achievement in Sabah, Malaysia

This study aims to identify the correlation between the instructional leadership practices by the headmasters with the level of performance and achievement of schools in Malaysia. A total of 141 respondents comprised of senior assistants of primary schools were examined. Respondents' perceptions of instructional leadership practices by the headmasters were gained using a set of questionnaire that was modified from the Principal Instructional Management Rating Scale (PIMRS). Descriptive statistical analysis was used to obtain the mean score, percentage, and standard deviation of the instructional practices. At the same time, ANOVA test was applied to obtain the perceptions from demographic factors and Pearson Correlation to measure the relationship between the instructional leadership and the schools’ performance that is based on band measurement. The findings show that the level of instructional leadership practice is high, with a mean of 4.24. Band 1, 2, 3 and 4 schools each have min of 4.37 4.23, 4.23 and 4.05 respectively. Pearson correlation analysis shows that there is a weak negative correlation between the headmasters’ instructional leadership practices level and the performance of the schools (r = -0.210). Thus, findings conclude that the level of instructional leadership practices among headmasters in primary schools is high and has a weak negative relationship in-term of schools’ achievement.
Narrow-Band Screen-Space Fluid Rendering using Layered Neighborhood Method

OLIVEIRA, F. O. Narrow-Band Screen-Space Fluid Rendering using Layered Neighborhood Method. 2021. 82 p. Dissertação (Mestrado em Ciências – Ciências de Computação e Matemática Computacional) – Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos – SP, 2021. This works introduces a new approach for screen-space fluid rendering. We built on top of classic methods and, with the use of fluid narrow-band, we heavily increase performance of those methods. We present a simple formulation for a narrow-band extraction the Layered Neighborhood Method that is compatible with the screen-space rendering pipeline and does not introduce complexity into the fluid solver. Together, extraction and rendering technique, are able to provide state-of-the-art quality rendering and achieve better performance than classic methods alone.
Self-portrait in the photo booth: self-representation in the selfie era, a Photo-based Educational Research Project

This visual essay is the result of an inquiry that analyses the selfie with students in the art teacher training programme in the Faculty of Education. These students are familiar with the selfie in a recreational context, in which the result and the aesthetics of the immediate prevail, overlooking elements of the photographic act. The visual experimentation triggered by the limitations of this strongly standardised and automated process is a challenge for young people. The results show a great capacity for visual reflection and denote a deep critical sense. The aim of this artistic research is to slow down the act of self-portraiture and to make it a more conscious process. The methodology of this Photo-based Educational Research is based on transforming the classroom into an artistic laboratory. For this purpose, a visual, experimental and theoretical research proposal is designed. The empirical part involves a photographic project that establishes the use of the photo booth as a technical condition. The theoretical dimension consist of the study of contemporary artistic references that consider the self-portrait and the selfie as a central theme.
Hessian Locally Linear Embedding of PMU Data for Efficient Fault Detection in Power Systems

This article develops a computationally efficient fault-detection method for power systems, by exploiting phasor measurement unit (PMU) data and Hessian locally linear embedding (HLLE) technique. First, via HLLE technique, high-dimensional PMU data are transformed into low-dimensional embedding coordinates, which effectively captures the fluctuations of PMU data. Next, based on the feature space of embedding coordinates, T-squared statistic is employed for online fault detection. The method is evaluated on IEEE 39-bus system and a real-world system, exhibiting decent fault-detection performance as well as a considerably lower computational complexity when compared with existent methods.
A SLR on Customer Dropout Prediction

Dropout prediction is a problem that is being addressed with machine learning algorithms; thus, appropriate approaches to address the dropout rate are needed. The selection of an algorithm to predict the dropout rate is only one problem to be addressed. Other aspects should also be considered, such as which features should be selected and how to measure accuracy while considering whether the features are appropriate according to the business context in which they are employed. To solve these questions, the goal of this paper is to develop a systematic literature review to evaluate the development of existing studies and to predict the dropout rate in contractual settings using machine learning to identify current trends and research opportunities. The results of this study identify trends in the use of machine learning algorithms in different business areas and in the adoption of machine learning algorithms, including which metrics are being adopted and what features are being applied. Finally, some research opportunities and gaps that could be explored in future research are presented.
Hybrid Continuous-Wave and Self-Injection-Locking Monopulse Radar for Posture and Fall Detection

This article presents a novel monopulse radar that combines high-sensitivity continuous-wave (CW) and self-injection-locking (SIL) receivers to detect and localize the movements in a human body. The proposed radar utilizes a CW sum pattern and an SIL difference pattern to process the echo signal from the target, so it can produce a monopulse ratio to estimate the angle of arrival (AoA) of the echo signal. With this capability, the radar can localize the movements on the target’s chest that are caused by vital signs such as respiration and heartbeat for posture classification. In addition, the radar can be used in a fall alarm as it can detect a change of posture during a fall. As a proof of concept, a 2.4-GHz prototype radar was experimentally implemented to validate the robustness of detecting falls regardless of their direction.