Miracle-dz/UniFAR-FTUs huggingface dataset:
ENVIRONMENTAL MONITORING MANAGEMENT OF WASTE FROM LARGE EXCAVATIONS DUE TO INFRASTRUCTURE BUILDINGS

Abstract. Large infrastructure building like the Florence Railway Station designed for high-speed rails requires a proper management of the huge quantity of waste originating from excavation activities. Such waste amounts require large areas for disposals, making abandoned areas or exhausted quarries and mines ideal sites for hosting the excavated wastes.A rectangular area of 500×70m delimiting the railway station has been excavated in two steps causing the removal of a 10m-thick soil layer per step: excavated earth and rocks would then be used for the environmental restoration of an area of 400×350m located near a former exhausted lignite quarry) in the proximity of the Santa Barbara village near Cavriglia (Arezzo). The Tuscan Regional Environmental Agency (ARPAT) have been involved in monitoring both the terrain transportation and disposals’ operations according to the approved management plan: the Environmental Regional Information System Office (SIRA) was asked to evaluate volume balancing between all the waste management cycle, with included: (a) waste extraction from railway station site building, and (b) waste disposal final destination (exhausted Santa Barbara lignite quarry). Terrestrial Laser Scanner (TLS), Simultaneous Localization and Mapping System (SLAM) systems and Remotely Piloted Aircraft Systems (RPAS) surveys have been used to track earth and rocks excavation and disposal activities in the aforementioned sites: while RPAS systems cannot be used in underground site surveys, their usage must be recommended in open space surveys due to the ese of use if sub-centimetric precisions are not required.Multiple TLS scans alignment can result in a quite challenging task if automatic alignment software is not available, requiring manual rough alignment’s operations that can be very time consuming: two open-source solutions based on different algorithms have been evaluated.The selected survey technologies – RPAS, TLS, SLAM – have shown a great potential in earth and rocks monitoring: each technology has its own strengths and weakness, which can vary on the basis of both hardware and software technical progresses.
P2SIM: Privacy-Preserving and Source-Reliable Incentive Mechanism for Mobile Crowdsensing

In mobile crowdsensing (MCS), providing appropriate rewards is a common and efficient way to motivate participants to participate in sensing tasks. However, the privacy of task participants is not protected well in most quality-aware incentive schemes. Moreover, these schemes are designed for general MCS application scenarios where data are collected by internal sensors embedded in participants’ smartphones, and not suitable for scenarios where additional sensors (ASs) except internal sensors are to collect data (e.g., household medical devices). In scenarios with ASs, malicious participants can fabricate sensing data instead of collecting data from ASs, i.e., the source reliability of sensing data cannot be ensured. To address these issues, we propose P2SIM, a privacy-preserving and the source-reliable incentive mechanism scheme for MCS with ASs. We combine redactable signature with private hash function to achieve the source reliability verification of sensing data without revealing the privacy of participants. Moreover, rewards are divided into two parts: 1) fixed rewards and 2) floating rewards, to enhance the flexibility of rewards distribution. Both formal theoretical analysis and extensive experimental evaluations on a real data set show that the proposed P2SIM is secure and efficient.
Battery-Supercapacitor Energy Storage Systems for Electrical Vehicles: A Review

The current worldwide energy directives are oriented toward reducing energy consumption and lowering greenhouse gas emissions. The exponential increase in the production of electrified vehicles in the last decade are an important part of meeting global goals on the climate change. However, while no greenhouse gas emissions directly come from the operations of the electrical vehicles, the electrical vehicle production process results in much higher energy consumption and greenhouse gas emissions than in the case of a classical internal combustion vehicle; thus, to reduce the environment impact of electrified vehicles, they should be used for as long as possible. Using only batteries for electric vehicles can lead to a shorter battery life for certain applications, such as in the case of those with many stops and starts but not only in these cases. To increase the lifespan of the batteries, couplings between the batteries and the supercapacitors for the new electrical vehicles in the form of the hybrid energy storage systems seems to be the most appropriate way. For this, there are four different types of converters, including rectifiers, inverters, AC-AC converters, and DC-DC converters. For a hybrid energy storage system to operate consistently, effectively, and safely, an appropriate realistic controller technique must be used; at the moment, a few techniques are being used on the market.
Consonant-vowel Interactions Inform Paradigm Organization in Egyptian Arabic

This paper presents a quantitative study on vowel alternation in Egyptian Arabic verbs. Specifically, the vowels in perfective verb forms (of the prosodic shape CVCVC) and imperfective verb forms (-CCVC) are hard to predict from each other. This study investigates how probabilistic phonological generalizations involving the root consonants and vowel correspondences help predict the idiosyncratic vowel choice by collecting lexicon statistics and fitting regression models. Following the line of works which has shown that speakers have the ability to internalize statistical patterns into their phonological grammars (e.g., Zuraw 2000, Ernestus & Baayen 2003), the models were used as a means to investigate organization of the perfective-imperfective paradigm. Moreover, by showing that consonant and vowel information play distinct roles in paradigm predictability, this study provides evidence for lexical representations that separate consonants and vowels in Semitic languages (e.g., McCarthy 1979).
Engineering Mechanics : Dynamics

General Principles. Kinematics of Particles. Kinematics of Rigid Bodies. Kinetics of Particles: Newton's Law. Kinetics of Rigid Bodies: Newton's Laws. Kinetics of Particles: Work and Energy Methods. Kinetics of Rigid Bodies: Work and Energy Methods. Kinetics of Particles: Impulse and Momentum. Kinetics of Rigid Bodies: Impulse and Momentum. Mechanical Vibrations. Appendices. Answers to Selected Problems. Index. Photo Credits.
Reliable Data Collection Methodology for Face Recognition in Preschool Children

Most face datasets target adults who can make their own decisions. In the case of children, consent from parents or guardians is necessary to collect biometric information, thus making it very difficult. As a result, the amount of data on children is quite small and inevitably private. In this work, we built a database by collecting face data of 74 children aged 2–7 years in daycare facilities. In addition, we conducted an experiment to determine the best location to perform face recognition on children by installing cameras in various locations. This study presents the points and methods to be considered to build a children’s face dataset and also studies the optimal camera installation setups for the face recognition of children.
SIW-Based -Band Leaky-Wave Antenna With Improved Beam Steering Performance

A high-scanning rate leaky-wave antenna (LWA) working at Ka-band with continuous backward-to-forward beam-scanning capability, good open stopband (OSB) suppression and wide scanning angle is exhibited. The proposed LWA is made by etching an array of cascaded high-Q resonators and open discontinuities on the substrate integrated waveguide (SIW). The resonator is designed by combining two symmetrically unbalance split ring resonators (USRRs) on the top surface of the SIW. The LWA's working mechanics were thoroughly investigated through band structure theory. An in-depth interpretation of the LWA's characteristics is provided by studying the surface current distribution and the equivalent circuit model of the resonator structure. The LWA's OSB is effectively alleviated by properly selecting the length of the radiation slot. Yet, the antenna scanning rate is directly improved by the oscillation quality of the resonators (i.e., USRRs), which is realized by tuning the split gap of the USRR. In the experiments, a prototype of the proposed LWA was fabricated and measured. The simulated and measured data show good agreement in terms of the antenna's scanning range and radiation gain. The measured results indicates that a continuous beam scanning from −56° to +48° is rendered over the frequency band from 32 to 36 GHz, which implies a spectral scanning rate of 8.84° per percentage. Finally, it is shown that the average gain can reach up to 9.1 dBi.
HOW TO GROW? - MODELING LAND USE CHANGE TO DEVELOP SUSTAINABLE PATHWAYS FOR SETTLEMENT GROWTH IN THE HINTERLAND OF COLOGNE, GERMANY

Abstract. Urban sprawl, with its negative consequences for nature and agriculture, is one of the great challenges of the 21st century. A particular problem is the strong population growth in metropolitan regions and the associated need for new residential areas. For the study area presented in this article, the western part of the Cologne metropolitan region, an increase of up to 200,000 inhabitants (30% of the population in 2040) is expected by 2040. If planning practices remain unchanged, this would result in a need for up to 4,460 hectares of new residential areas by 2040. Much of this development would take place at the edge of existing residential areas which frequently are of high value for agricultural production. To simulate different scenarios for the allocation of the necessary residential areas in the study area, a land use model was developed based on an open software stack. To evaluate the results of the simulations, a set of 20 indicators covering aspects of agriculture, ecology, housing and economy was used to assess both the sustainability and quality of possible new residential areas. In this article, two scenarios were used to show the effects of different building densities and the protection of particularly high-quality agricultural land. While the increase in building density is expected to reduce the area needed for new residential areas, the protection of high value agricultural land has negative effects on species protection. Using two species as examples, the limitations of an indicator-based assessment of the model results are shown.
Classical Control System Analysis Over Lossy Networks: An Easy-to-Use Nyquist Plot Approach

This article presents an approach based on the Nyquist plot to analyze the mean-square stability of a networked control system in which data transmission is subject to the occurrence of packet losses. This result is obtained by translating well-known linear matrix inequality (LMI) conditions for mean-square stability to conditions that take the form of upper bounds on the $\mathcal {H}_{\infty }$ norms of the sensitivity and complementary sensitivity transfer matrices. Although the results obtained provide only sufficient conditions, the proposed approach allows us to inspect if the stochastic feedback system is mean-square stable by conveniently using classical Nyquist plots. A numerical example is given to illustrate the ease of use of the proposed tool.
A Flower Recognition System using Deep Neural Network Coupled with Visual Geometry Group 19 Architecture

Computer vision is one of the basic features to streamline processes like robotic process automation and digital asset management. Computer vision has come a long way in terms of its capabilities and what it can provide and do for different industries. Object detection and image detection are just some of the few applications provided by computer vision. However, this field is still relatively young and prone to challenges. The first is the lack of wellannotated images to train the algorithms to perform optimally, and the second being lack of accuracy when applied to real-world images different from the ones from the training dataset. As such, this paper aims to fine-tune pre-trained machine learning models, which are ResNet50 and VGG19 as well as training a new SqueezeNet inspired model from scratch to create a flower recognition model that can process and remember large amounts of flower species data. In conclusion, VGG19 was found to perform the best on both the 5 Categories and Flower-102 dataset, with an accuracy of 88% and 84% respectively. Keywords: VGG19, Transfer Learning, Deep Learning, Flower Recognition, Neural Network
Phenotyping and genetic analysis of the Caucasian grape resistance to Erysiphe necator

CREA Research Centre for Viticulture and Enology, viale XXVIII Aprile 26, 31015, Conegliano (TV), Italy INRAE, Université de Strasbourg, UMR 1131, 28 rue de Herrlisheim, 68000, Colmar, France Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle Scienze 206, 33100, Udine (UD), Italy ______________________________________________________________________________
Robust Weak Detectability Analysis of Boolean Networks Subject to Function Perturbation

As a class of state estimation issues, detectability is widely used in fault diagnosis, circuit design, and disease status detection. This brief analyzes the robust weak detectability of Boolean networks (BNs) under function perturbation. A simplified parallel system is constructed for BNs. Based on the transition of state pairs in the simplified parallel system, a new criterion is proposed for the weak detectability of BNs. Using the reachability from perturbed state pairs to attractors in indistinguishable pairs, the robust weak detectability of BNs subject to function perturbation is analyzed. A practical example of p53-MDM2 negative feedback regulatory loop is used to illustrate the obtained criteria.
Momentum Pseudo-Labeling: Semi-Supervised ASR With Continuously Improving Pseudo-Labels

End-to-end automatic speech recognition (ASR) has become a popular alternative to traditional module-based systems, simplifying the model-building process with a single deep neural network architecture. However, the training of end-to-end ASR systems is generally data-hungry: a large amount of labeled data (speech-text pairs) is necessary to learn direct speech-to-text conversion effectively. To make the training less dependent on labeled data, pseudo-labeling, a semi-supervised learning approach, has been successfully introduced to end-to-end ASR, where a seed model is self-trained with pseudo-labels generated from unlabeled (speech-only) data. Here, we propose momentum pseudo-labeling (MPL), a simple yet effective strategy for semi-supervised ASR. MPL consists of a pair of online and offline models that interact and learn from each other, inspired by the mean teacher method. The online model is trained to predict pseudo-labels generated on the fly by the offline model. The offline model maintains an exponential moving average of the online model parameters. The interaction between the two models allows better ASR training on unlabeled data by continuously improving the quality of pseudo-labels. We apply MPL to a connectionist temporal classification-based model and evaluate it on various semi-supervised scenarios with varying amounts of data or domain mismatch. The results demonstrate that MPL significantly improves the seed model by stabilizing the training on unlabeled data. Moreover, we present additional techniques, e.g., the use of Conformer and an external language model, to further enhance MPL, which leads to better performance than other semi-supervised methods based on pseudo-labeling.
Real-Time Short-Term Pedestrian Trajectory Prediction Based on Gait Biomechanics

The short-term prediction of a person’s trajectory during normal walking becomes necessary in many environments shared by humans and robots. Physics-based approaches based on Newton’s laws of motion seem best suited for short-term predictions, but the intrinsic properties of human walking conflict with the foundations of the basic kinematical models compromising their performance. In this paper, we propose a short-time prediction method based on gait biomechanics for real-time applications. This method relays on a single biomechanical variable, and it has a low computational burden, turning it into a feasible solution to implement in low-cost portable devices. We evaluate its performance from an experimental benchmark where several subjects walked steadily over straight and curved paths. With this approach, the results indicate a performance good enough to be applicable to a wide range of human–robot interaction applications.
Magnetic Adhesion in Wall Climbing Robots using varied Electromagnet Arrangements

The improvements and innovations in the field of robotics have given a great opportunity to perform tasks that are hazardous for humans to perform. For example, robots can be used for working on high-storied buildings, inspection on ferromagnetic surfaces, painting and maintenance of buildings, surveillance purposes, etc., at the outset, to carry out any operation on vertical surfaces, which may be quite hazardous and time-consuming as well, wall climbing robots (WCRs) can be deployed. The method of adhesion determines the stability of the robot on the wall, be it smooth or coarse. Using magnets to bring about magnetic adhesion would be advantageous when the robot is maneuvered over iron or steel surfaces, typically, to clean boilers, etc., This paper presents the different ways of placements of the magnets, both permanent and electromagnets, in order to introduce adequate magnetic adhesion that would cease the robot from toppling down while encountering an obstacle. This work proposes two methods of arrangement of magnets: square and diamond. Four electromagnets when arranged in array formation with 5000 windings of thin copper coil, generated a magnetic field force of approximately 150 N when 50 A of current is passed. By and large, around 35 N to 40 N is the suction force that would be sufficient to stick the WCR of 2kg on the wall, while using a suction chamber instead of electromagnets. Other methods of placing the magnets such as square and diamond are studied and compared as well using FEMM. Hence arranging the 4 electromagnets in array formation gives an adhesion pressure sufficient to hold and move the WCR, over the vertical wall against gravity.
Design, Development and in vitro Assessment of Flurbiprofen Microemulsion Gel for Transdermal Drug Delivery

The aim of current research is to develop flurbiprofen microemulsion gel for transdermal delivery. To prepare a microemulsion oil, surfactant and co-surfactant selection is one of the important criteria. Selected to prepare different ratios of oil and surfactant mixture using ternary phase diagram. Based on results of physicochemical properties, we have optimized one formulation. The optimized microemulsion formulation incorporated into carbopol P 934 gel base. The In vitro diffusion of drug release shown maximum (98.6% in 12hrs) for prepared microemulsion gel than marketed gel (60.5% in 16 hrs).
The Relationship Between Hearing Status and Self-Efficacy in Adults

Hearing loss is a disability that impedes people’s ability to access auditory information and communicate through listening and spoken language. Self-efficacy describes one’s confidence in their actions and behaviors. The study examined the relationship between hearing status of adults with and without hearing loss and self-efficacy. The participants answered a series of assessment questions: A hearing demographic information questionnaire, a self-efficacy scale assessment, and a measure of subjective sound quality in various situations. Findings revealed that poorer performance in various hearing situations was correlated with lower score of self-efficacy. Alternatively, the better participants can function and effortlessly hear in various hearing settings, the higher their self-efficacy. Self-efficacy is neither correlated with severity of hearing nor age. The study also found that the later the participant’s onset of hearing loss, the more likely they will have difficulty performing in hearing situations. Since the relationship between the degree of hearing loss and self-efficacy is insignificant, but the hearing performance is relevant to self-efficacy, better performance is reflected via appropriate hearing technology through rehabilitation. The study supports the notion that by undergoing hearing rehabilitation when necessary, regardless of the severity of the hearing loss, one will ideally be able to perform better in hearing situations, which will ultimately be a strong predictor of a higher sense of self-efficacy.
Didactics in School-Age Educare Centres – an Unexplored Field But with Distinctive Views

The background for this study is the lack of well-defined and distinct theories on didactics in school-age educare centres (SAECs). Therefore, in this study, we investigated and compared perceptions among nine professional groups employed in the field. The participants included 390 females and 102 males in Sweden, and their beliefs about didactics in SAECs were measured through a questionnaire consisting of 24 items on a 4-point Likert scale, which researchers and those related to the didactics in SAECs proposed. Descriptive statistics presented an overall picture of the various claims on a group level. The Mann – Whitney test investigated the distinctions between occupational categories. The results indicated that most of the items were relevant. Furthermore, the pupils ’ orientation was not taken into account enough. Didactics should be translated into SAEC practices but the transfer into practice remains unclear. Many respondents appeared to agree with all of the items to varying degrees, but least that SAEC didactics should not be related to school activities. An important result was that principals ’ perceptions diverged largely from those of other groups, especially regarding the relationship of didactics to the school ’ s activities. The results partly explain that different professions the SAECs affect see the role of didactics differently.
Effects of Combining Biofactors on Bioenergetic Parameters, Aβ Levels and Survival in Alzheimer Model Organisms

Increased amyloid beta (Aβ) levels and mitochondrial dysfunction (MD) in the human brain characterize Alzheimer disease (AD). Folic acid, magnesium and vitamin B6 are essential micro-nutrients that may provide neuroprotection. Bioenergetic parameters and amyloid precursor protein (APP) processing products were investigated in vitro in human neuroblastoma SH-SY5Y-APP695 cells, expressing neuronal APP, and in vivo, in the invertebrate Caenorhabditis elegans (CL2006 & GMC101) expressing muscular APP. Model organisms were incubated with either folic acid and magnesium-orotate (ID63) or folic acid, magnesium-orotate and vitamin B6 (ID64) in different concentrations. ID63 and ID64 reduced Aβ, soluble alpha APP (sAPPα), and lactate levels in SH-SY5Y-APP695 cells. The latter might be explained by enhanced expression of lactate dehydrogenase (LDHA). Micronutrient combinations had no effects on mitochondrial parameters in SH-SY5Y-APP695 cells. ID64 showed a significant life-prolonging effect in C. elegans CL2006. Incubation of GMC101 with ID63 significantly lowered Aβ aggregation. Both combinations significantly reduced paralysis and thus improved the phenotype in GMC101. Thus, the combinations of the tested biofactors are effective in pre-clinical models of AD by interfering with Aβ related pathways and glycolysis.