Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of chlorophyll-a concentration in waters over the continental shelf of the Bay of Biscay: a comparison of remote sensing algorithms

Ocean colour imagery is used increasingly as a tool to assess water quality via chlorophyll-a concentration (chl-a) estimations in European waters. The Bay of Biscay is affected by major river discharges, which alter the constituents of the marine waters. Chlorophyll-a algorithms, designed for use at global scales, are less accurate due to the variability of optically active in-water constituents. Hence, regionally parameterized empirical algorithms are necessary. The main objective of the present study was to develop a regional algorithm to retrieve chl-a in surface water using in situ R rs, for a subsequent application to Medium Resolution Imaging Spectrometer (MERIS) satellite images. To address this objective, a platform was developed initially and a measurement procedure adapted for the field HR4000CG Spectrometer. Subsequently, the procedure was tested during a survey over the south-eastern Bay of Biscay (North-East Atlantic Ocean), to establish a MERIS chl-a algorithm for the area, by comparing different global remote sensing chl-a algorithms, with band ratios. Results validated with the jackknife resampling procedure show a satisfactory relationship between the R rs(510)/R r s(560) and chl-a (R 2 jac = 0.681). This ratio is better correlated to chl-a than those obtained with established chl-a remote sensing algorithms. High content in coloured dissolved organic matter (CDOM > 0.4 m−1) and suspended particulate matter (SPM > 2.8 mg l−1) influenced this relationship, with yellow substances having a stronger effect.
Variability in Measured Space Temperatures in 60 Homes

This report discusses the observed variability in indoor space temperature in a set of 60 homes located in Florida, New York, Oregon, and Washington. Temperature data were collected at 15-minute intervals for an entire year, including living room, master bedroom, and outdoor air temperature (Arena, et. al). The data were examined to establish the average living room temperature for the set of homes for the heating and cooling seasons, the variability of living room temperature depending on climate, and the variability of indoor space temperature within the homes. The accuracy of software-based energy analysis depends on the accuracy of input values. Thermostat set point is one of the most influential inputs for building energy simulation. Several industry standards exist that recommend differing default thermostat settings for heating and cooling seasons. These standards were compared to the values calculated for this analysis. The data examined for this report show that there is a definite difference between the climates and that the data do not agree well with any particular standard.
The feasibility of using center frequency spectra in photoacoustic imaging for tissue characterization

In photoacoustic imaging, the amplitude of the photoacoustic signal is used for mapping the spatial distribution of a chromophore in the body and few studies have focused on the potential of using frequency content of the photoacoustic data. This study investigates the feasibility of using the photoacoustic center frequency spectrum in differentiating microspheres of various sizes and colors in phantoms. The microspheres with colors of green and blue, and the same size showed different center frequency spectrum shapes while keeping the offset (mean frequency) approximately the same. In addition, smaller microspheres showed higher center frequency offset, while larger microspheres showed smaller offset, suggesting the potential to use the center frequency spectrum for differentiating chromophores of various optical properties in the body.
A Needle is an Outlier in a Haystack: Hunting Malicious PyPI Packages with Code Clustering

As the most popular Python software repository, PyPI has become an indispensable part of the Python ecosystem. Regrettably, the open nature of PyPI exposes end-users to substantial security risks stemming from malicious packages. Consequently, the timely and effective identification of malware within the vast number of newly-uploaded PyPI packages has emerged as a pressing concern. Existing detection methods are dependent on difficult-to-obtain explicit knowledge, such as taint sources, sinks, and malicious code patterns, rendering them susceptible to overlooking emergent malicious packages. In this paper, we present a lightweight and effective method, namely MPHunter, to detect malicious packages without requiring any explicit prior knowledge. MPHunter is founded upon two fundamental and insightful observations. First, malicious packages are considerably rarer than benign ones, and second, the functionality of installation scripts for malicious packages diverges significantly from those of benign packages, with the latter frequently forming clusters. Consequently, MPHunter utilizes clustering techniques to group the installation scripts of PyPI packages and identifies outliers. Subsequently, MPHunter ranks the outliers according to their outlierness and the distance between them and known malicious instances, thereby effectively highlighting potential evil packages. With MPHunter, we successfully identified 60 previously unknown malicious packages from a pool of 31,329 newly-uploaded packages over a two-month period. All of them have been confirmed by the PyPI official. Moreover, a manual analysis shows that MPHunter recognizes all potentially malicious installation scripts with a recall of 100% across all analyzed packages. We assert that MPHunter offers a valuable and advantageous supplement to existing detection techniques, augmenting the arsenal of software supply chain security analysis.
Using Radar and Seismic Methods for the Determination of Ice Column Properties and Basal Conditions at Jakobshavn Isbræ and the NEEM Drill Site

iii ACKNOWLEDGMENTS . v 1.0 INTRODUCTION . 1 2.0 CHAPTER I: COMPARISON OF PREFERRED ICE CRYSTAL ORIENTATION DATA AT THE NEEM ICE-CORE SITE WITH MULTI-POLARIZATION RADAR MEASUREMENTS. 4 2.1 CHAPTER I: INTRODUCTION . 4 2.2 AREA OF STUDY . 7 2.3 DATA ACQUISITION . 10 2.3. 1 GROUND BASED DATA . 10 2.3. 2 AIRBORNE DATA ACQUISITION . 13 2.4 GROUND-BASED AND AIRBORNE DATA PROCESSING . 13 2.5 MULTI-POLARIZATION PLANE TECHNIQUE . 14 2.6 RESULTS AND INTERPRETATION . 18 2.6. 1 CIRCULAR DATA RESULTS . 18 2.6. 2 INTERPRETATION OF CIRCULAR DATA . 21 2.6. 3 GROUND-BASED GRID DATA RESULTS . 22 2.6. 4 INTERPRETATION OF GROUND-BASED GRID DATA SET . 31 2.6. 5 AIRBORNE DATA SET RESULTS . 35 2.6. 6 INTERPRETATION OF AIRBORNE DATA SET . 38 2.7 COMPARISON BETWEEN GROUND-BASED RADAR DATA SET AND ICE CORE MEASUREMENTS . 39 2.8 CHAPTER I: CONCLUSIONS . 42
UAV Bioacoustic Monitoring for Bird Survey

Bioacoustic monitoring using UAV mounted recorders is fast being adopted as a new technique for monitoring songbirds within the natural environment. With this in mind, microphone placement techniques can improve the audio capture performance on drones. We present a low cost sound acquisition system with a shotgun microphone that is capable of reducing UAV noise on larger sized drones and acquiring bird call data. We disclose the technical details of the hardware and the bird call data that is successfully obtained during flight. Two setups are implemented that place the microphone system at different locations on the drone. We present experimental results obtained by the microphone system during flight. It is shown that the ego-noise reduction performance achieved by the microphone system varies depending on the microphone placement and type of windshield applied. This observation provides valuable insights into hardware development for drone audition related to acquiring bird call data for bird survey.
Generative Model-Based Testing on Decision-Making Policies

The reliability of decision-making policies is urgently important today as they have established the fundamentals of many critical applications, such as autonomous driving and robotics. To ensure reliability, there have been a number of research efforts on testing decision-making policies that solve Markov decision processes (MDPs). However, due to the deep neural network (DNN)-based inherit and infinite state space, developing scalable and effective testing frameworks for decision-making policies still remains open and challenging. In this paper, we present an effective testing framework for decision-making policies. The framework adopts a generative diffusion model-based test case generator that can easily adapt to different search spaces, ensuring the practicality and validity of test cases. Then, we propose a termination state novelty-based guidance to diversify agent behaviors and improve the test effectiveness. Finally, we evaluate the framework on five widely used benchmarks, including autonomous driving, aircraft collision avoidance, and gaming scenarios. The results demonstrate that our approach identifies more diverse and influential failure-triggering test cases compared to current state-of-the-art techniques. Moreover, we employ the detected failure cases to repair the evaluated models, achieving better robustness enhancement compared to the baseline method.
Experiences With the Integration of MOOCs Into Online Courses Through E-tivity

MOOCs have many benefits for higher education, which is why many universities are incorporating them into their curricula. The University of Rijeka, Croatia, has joined the Coursera for Campus program to provide students and teachers with the opportunity to gain skills, competencies, and certificates for completed courses. There are several models of how a MOOC can be integrated into an online or hybrid course. This paper proposes the integration of MOOCs into online courses through an e-tivity approach, that requires students to collaborate in an online environment to complete a specific task and achieve learning outcomes. A didactic model for the course “E-Learning for Education and Business” is presented that uses MOOC courses in the context of e-tivity. To become familiar with MOOCs and prepare to design their own courses, students first enroll in a Coursera course, keep an individual learning diary of their participation, and are then expected to collaborate on course analysis. Evaluation of the model has shown that students are positive about this approach. The e-activity involving MOOCs was found to be interesting, and useful for creating their own online courses. This e-activity also encouraged students to enroll in a Coursera course and learn about the possibilities of MOOC courses, which they found useful for their studies and future work.
TIME-DEPENDENT BEHAVIOR OF CRUSHABLE MATERIALS IN ONE-DIMENSIONAL COMPRESSION TESTS

Particle crushing is a progressive phenomenon. This study examines time-dependent behavior due to particle crushing. A review of the literature was made to find evidence of time-dependent behavior due to particle crushing. Single particle crushing tests and one-dimensional compression tests were carried out on four crushable materials with careful visual observations. The mechanism of time-dependent compression was discussed. The following observations were made : (1) The time-dependent behavior under one-dimensional compression stems mainly from a repetitive cycle of crushing, rearrangement of particles and redistribution of contact stresses. (2) Crushing patterns and rearrangement in one-dimensional compression tests are different depending on the characteristics observed in single particle crushing tests.
Structural and geochemical features of the Sabina strike-slip fault (Central Apennines)

Within the western part of the Sabina area, 50 km north of Rome, a N10E strike-slip fault (Sabina Fault), which outcrops continuously from the village of Casperia to Stroncone, is recognized. The Sabina Fault appears to continue northward across the tectonic basin of Terni and along the Umbrian Apennines toward Spoleto, whereas southward it is covered by Plio-Pleistocene marine deposits, alluvial fans of the Tiber river, and Alban Hills volcanites. The role of strike-slip faulting is generally inferred in several models of Apennine structural evolution, but has not yet been recognized in a continuous and clear structure in the field element. The aim of this paper is to introduce this tectonic feature and the related strain pattern which is probably connected with the recent geodinamical evolution of Central Italy. The Sabina strike-slip fault has been active since the late Miocene to the latest Pleistocene in a number of different pulses. It shows a dextral movement with a recognizable elongation of almost 40 km, accompanied by a swarm of splays with differential dips from 90 degrees to 30 degrees developed up to hundreds of meters away from the main fault scarp. A set of open folds whose axial planes generally dip towards the east are also present, the results of the changing strike of the main fault producing small compressive volumes. The frequency of stylolitic cleavage systems increases toward the main fault surface with a production of redeposited calcites sigmoidal bodies, which create a peculiar petrofabric texture within the "Scaglia rossa" beds. These structures produce a peculiar and unique lithological type that was used in the development of Roman and Baroque historical monuments as the, so called, "Marmo di Cottanello". The vertical displacement of the base of Pleistocene sediments and coastlines is 100 m. An en-echelon system of fractures was recognized in Pliocene marine units which outcrop in the Campagna Romana. They are associated to strike-slip faulting that could represent the southermost extension of the Sabina Fault. 13 C and 18 O data show a differential role of fluids within extensive fracture swarms in Mesozoic Scaglia and in Lower Pliocene clays to that found in sigmoidal recrystallized calcite bodies. This result confirms the polyphase tectonic activity of the Sabina Fault.
Detection of Diabetes Using 1D Convolutional Neural Network from Short Time PPG Signal

Diabetes is a prevalent and chronic condition requiring effective surveillance and categorization. In recent years, the analysis of physiological signals, such as photoplethysmography (PPG), has arisen as a promising detection and classification technique for diabetes. The main focus of this study is to analyze the detection of Diabetes using 1D Convolutional Neural Networks (CNN) applied to short-time PPG signals. Our experimental findings demonstrate that the proposed method is effective. Using 5-fold cross-validation to evaluate a dataset containing PPG signals from diabetic and non-diabetic subjects, we attain an average accuracy of 84.62%. In addition, we report precision, recall, and F1 scores to demonstrate the model's ability to correctly classify diabetic and non-diabetic. For the ‘diabetic’ class, our method achieves a precision of 0.864041, recall of 0.857135, and F1 score of 0.868085. For the ‘non-diabetic’ class, our precision is 0.83114, recall is 0.858586, and F1 score is 0.845771. These results demonstrate that our 1D CNN-based method accurately classifies Diabetes from PPG signals, allowing for early detection and intervention.
OSL‐based chronostratigraphy of river terraces in mountainous areas, Dunajec basin, West Carpathians: a revision of the climatostratigraphical approach

The technique of optically stimulated luminescence (OSL) dating applied to fluvial sediments provided a geochronological framework of river terrace formation in the middle part of the Dunajec River basin – a reference area for studies of evolution of river valleys in the northern part of the Carpathians (West Carpathians). Fluvial sediments at 18–90 m above valley bottoms were dated in the valleys of the Dunajec River and one of its tributaries. The resulting ages range from 158.9±8.3 to 12.2±1.3 ka. This indicates that some of the terrace sediments were deposited much later than previously assumed on the grounds of a combined morphostratigraphical and climatostratigraphical approach. The OSL‐based chronostratigraphy of terrace formation consists of seven separate phases of fluvial aggradation, separated by periods of incision and lateral erosion. Some of the ages determined correspond to warm stages of the Pleistocene – Marine Isotope Stage 3 (MIS 3) and MIS 5 – demonstrating that some terraces were formed during interstadial or interglacial periods. The results provide a key for evaluating rates of neotectonic uplift, allowing us to decipher the response of a fluvial system to climate change within the context of the glacial–interglacial scheme.
BEASY: Making EASY Backfilling Renewable-Only

Reducing greenhouse gas (GHG) emissions from Information and Communication Technology (ICT) has become a hot topic since the Paris Agreement. Data centers are one of the most impactful ICT energy consumers since they are built to run 24 hours / 7 days. An emerging discussion is switching their power supply from brown to green energy, using Renewable Energy Sources (RES). However, this change introduces uncertainties linked to production intermittence. This work is part of the Datazero2 project. This project designs a data center powered only by renewable production, adding storage elements to reduce the impact of the intermittence. A clean-by-design data center requires several decisions at different levels of management. To do so, it uses predictions to plan the actions for the next few days. However, it also needs to react to the actual events that can vary from the forecast. This work presents the BEASY heuristic. BEASY mixes power and scheduling decisions in a renewable-only data center, seeking to reduce the number of killed jobs and wasted energy. The results demonstrate that BEASY reduced wasted energy by up to 35.33% in critical cases. Considering the killed jobs, it also kills fewer jobs than the state of art algorithms in all executions.
Phantom-Based Evaluation of a Planar Microwave Sensor for Non-Invasive Intracranial Pressure Monitoring

Intracranial pressure (ICP) measurements are essential to improve current clinical decision schemes in different scenarios: hospital, home, sports field, military field, etc. ICP is fundamental for understanding cerebrospinal fluid (CSF) mechanics and modelling better physiological conditions. Nowadays, several studies have focused on developing non-invasive ICP monitoring methods (nICP) based on different sensing modalities with advantages and disadvantages. Some works have focused on microwave-based sensing; among them is the application of NASA SansEC spectroscopy technology. This work extends previous results on this technology to nICP. Notably, in a simple phantom-based experiment and with a square spiral planar resonator sensor, pressure values up to 48 mmHg could be achievable. The phantom-based experiment consists of a large column tank gradually filled with a liquid that mimics the cerebrospinal fluid (CSF) based on data from the Italian database IFAC. Microwave-based methods for non-invasive intracranial pressure monitoring could be instrumental as tools that can be easily embedded and worn and give indications of brain health to trigger proper care in the future.
Resource Scheduling for NOMA-Based Mobile Phones and IoT Fusion Satellite Network

With the advent of 5G, wireless communication has greatly changed people's lifestyles. However, limited by the coverage of terrestrial cellular networks, the demand for communication services of mobile phones in remote areas is difficult to be met. In order to meet the large coverage and quality of service (QoS) requirements of mobile phones, we consider a non-orthogonal multiple access (NOMA)-based mobile phones and internet of things (IoT) fusion satellite network. In this network, low earth orbit (LEO) satellite can significantly enlarge the coverage while NOMA and IoT further improve the utilization efficiency of resources. Aiming at maximizing the QoS satisfaction rate of mobile phones and the sum rate of internet of things devices, we formulate a joint optimization problem considering NOMA user grouping, inter-group power allocation and intra-group power allocation. To tackle the problem, we design a QoS priority joint optimization algorithm based on proximal policy optimization (Q-PPO). The experimental results show that the proposed Q-PPO algorithm always has considerable performance in QoS satisfaction rate and sum rate of internet of things devices.
A New Adaptive POL Converter Controller Design to Improve Bus Voltage Stability for DC Microgrid Application

This article describes an adaptive resonance frequency extraction-based dc–dc converter controller to stabilize the dc microgrid (dc MG). The dc MG becomes prone to instability due to the excessive application of constant power loads (CPLs) and their variations. Under such conditions, the source-side control techniques for the stabilization of dc MG systems fail. Therefore, to stabilize dc MG systems, the load-side control methods are alternate approaches to improve the stability of dc MG. In this article, a new feed-forward control technique is proposed to improve the stability of the dc MG. In the proposed method, the input impedance of the load-side dc–dc converter is modified by the phase compensation method without realizing a total magnitude separation $(Z_{\text {os}}$ and $y_{\text {iL}}=1/Z_{\text {iL}}) $ to stabilize the dc MG system. The investigation analyzes the possibility of instability across the operational frequency spectrum. Based on that, a new feed-forward loop compensator is derived, which is a function of the center frequency to make it adaptive to load variations. After that, the derived compensator is realized for voltage mode control of the buck converter. It reduces the dc MG bus voltage oscillations without increasing system complexity and dissipation. The results of the MATLAB® simulation are compared with suggested and existing control methods. Moreover, it was discovered that the ripple in bus voltage decreased from 5.28% to 0.7%. And the settling durations of dc bus voltage and current were lowered from 0.5 and 0.25 s to 0.25 and 0.16 s, respectively.
Impact of FBAR Oscillator Stabilized to the CPT Resonance as Local Oscillator of Millimeter-Wave Communications

We verified the applicability of FBAR oscillators to local oscillators (LOs) in millimeter-wave communications (MMWc). Assuming the development of an oscillator chip that operates in the extra-high-frequency (EHF) band, which is a key component of an LO in an MMWc system, we investigated the phase noise degradation due to the frequency multiplication to achieve oscillation in the EHF band from an atomic-resonance-stabilized FBAR oscillator. Then, using system simulation, we evaluated the constellation images and bit error rate (BER) in MMW band quadrature amplitude modulation (QAM) communication. Additionally, for comparison, a similar methodology was applied to TCXO or OCXO. As a result, our FBAR oscillator was found to show excellent phase noise characteristics with a noise floor, clarifying its effectiveness in MMW band QAM communication.