Miracle-dz/UniFAR-FTUs huggingface dataset:
Research and Application of Best Practices for Water Saving in Industry

Water is a crucial resource for the earth and therefore for all living beings on earth such human. This article is focused on how to optimize water usage (saving) in industrial environment. This sector has a huge impact on water: usage, pollution, etc. The first step was to define and apply a water management and the second step to make research on each opportunity identified and to implement it. All those actions have been carried out in a pharmaceutical manufacturing site. Water saving have been done on different application: washing machine, heat pump on chiller system, osmosis inverses system on purified water and continuous measurement device of water quality. The site’s water consumption has been reduced by 40% in less than 6 years.
Les couches diffusantes du golfe de Gascogne : caractérisation acoustique, composition spécifique et distribution spatiale

Des donnees acoustiques sont collectees en continu lors de campagnes ecosystemiques pour detecter les bancs de poissons d’especes commerciales et en quantifier l’abondance. Ces donnees multifrequences contiennent egalement des informations sur des agregations de cibles plus petites qui se presentent sous forme de couches diffusantes. Il existe une grande diversite de couches diffusantes dont l’aspect sur les echogrammes, la reponse frequentielle et la composition specifique varient. L'objectif de cette these est de definir les types de couches diffusantes rencontrees lors de la campagne PELGAS, de decrire leurs distributions spatiales a meso-echelle, de les comparer a celles des autres compartiments de l'ecosysteme, et d'examiner la composition taxonomique des couches diffusantes resonantes a fine echelle. Une methode de classification non supervisee des echos appliquee aux donnees PELGAS permet de definir des « paysages acoustiques » structures spatialement. Ces paysages acoustiques sont domines par des reflecteurs porteurs de bulles de gaz resonnant aux frequences halieutiques et ne sont correles a aucun compartiment de l'ecosysteme pelagique issus de PELGAS2013. La composition biologique de couches diffusantes denses est etudiee a fine echelle en combinant par des approches directe et inverse les resultats de leur echantillonnage acoustique et biologique. Les resultats montrent que la reponse acoustique des couches diffusantes denses est dominee par celle de bulles de gaz incluses dans des larves de poissons (e.g. Sardina pilchardus}), et dans des organismes micronectoniques, qui sont peu ou pas echantillonnes avec les outils de collecte biologique.
Automatic Music Transcription Using Fourier Transform for Monophonic and Polyphonic Audio File

Musical sheet is an important tool for musicians that enables musicians to communicate with each other and help musicians to learn a composition of a song. Sometimes, musicians face an obstacle when they cannot find the musical sheet to learn a new song or it may require payment to get the sheet. The solution for this problem is to learn the song by figuring out the composition of a song using music transcription. Music Transcription is the process of music information retrieval to produce musical notation. Music Transcription using a computational method often called Automatic Music Transcription by upload the audio file as an input and generate musical sheet. The proposed method is solved using Note Value Detection to separate windows by the detected note values and Fourier Transform to recognize the frequency from each window. This study is evaluating the system using three variables; note value, pitch accuracy, and extra notes. The study shows that note value and pitch detection gives a relatively small percentage error. Meanwhile, extra note detection gives a relatively moderate percentage error in every polyphonic file.
Deep-Learning-Assisted Sound Source Localization From a Flying Drone

Sound source localization from a flying drone is a challenging task due to the strong ego-noise from rotating motors and propellers as well as the movement of the drone and the sound sources. To address this challenge, we propose a deep-learning-based framework that integrates single-channel noise reduction and multichannel source localization. In this framework, we suppress the ego-noise and estimate a time–frequency soft ratio mask with a single-channel deep neural network (DNN). Then, we design two downstream multichannel source localization algorithms, based on steered response power (SRP-DNN) and time–frequency spatial filtering (TFS-DNN). The main novelty lies in the proposed TFS-DNN approach, which estimates the presence probability of the target sound at the individual time–frequency bins by combining the DNN-inferred soft ratio mask and the instantaneous direction of arrival (DOA) of the sound received by the microphone array. The time–frequency presence probability of the target sound is then used to design a set of spatial filters to construct a spatial likelihood map for source localization. By jointly exploiting spectral and spatial information, TFS-DNN robustly processes signals in short segments (e.g., 0.5 s) in dynamic and low signal-to-noise-ratio (SNR) scenarios (e.g., SNR −20 dB). Results on real and simulated data in a variety of scenarios (static sources, moving sources, and moving drones) indicate the advantage of TFS-DNN over competing methods, including SRP-DNN and the state-of-the-art TFS.
Glycolytic Inhibitors Potentiated the Activity of Paclitaxel and Their Nanoencapsulation Increased Their Delivery in a Lung Cancer Model

Antiglycolytic agents inhibit cell metabolism and modify the tumor’s microenvironment, affecting chemotherapy resistance mechanisms. In this work, we studied the effect of the glycolytic inhibitors 3-bromopyruvate (3BP), dichloroacetate (DCA) and 2-deoxyglucose (2DG) on cancer cell properties and on the multidrug resistance phenotype, using lung cancer cells as a model. All compounds led to the loss of cell viability, with different effects on the cell metabolism, migration and proliferation, depending on the drug and cell line assayed. DCA was the most promising compound, presenting the highest inhibitory effect on cell metabolism and proliferation. DCA treatment led to decreased glucose consumption and ATP and lactate production in both A549 and NCI-H460 cell lines. Furthermore, the DCA pretreatment sensitized the cancer cells to Paclitaxel (PTX), a conventional chemotherapeutic drug, with a 2.7-fold and a 10-fold decrease in PTX IC50 values in A549 and NCI-H460 cell lines, respectively. To increase the intracellular concentration of DCA, thereby potentiating its effect, DCA-loaded poly(lactic-co-glycolic acid) nanoparticles were produced. At higher DCA concentrations, encapsulation was found to increase its toxicity. These results may help find a new treatment strategy through combined therapy, which could open doors to new treatment approaches.
Antimicrobial and cytotoxic effects of marine sponge extracts Agelas clathrodes, Desmapsamma anchorata and Verongula rigida from a Caribbean Island

Although marine sponges are known for their antimicrobial, antifungal and cytotoxic activity, very few studies have been carried out on endemic species of Martinique. Martinique is part of the Agoa Sanctuary, a marine protected area that includes the exclusive economic zones (EEZ) of the French Caribbean islands, making it an abundant source of marine species. To highlight the potential of this area for the discovery of marine biomolecules with antipathogenic and antitumor activities, we tested the aqueous and ethanolic extracts of sponge species Agelas clathrodes, Desmapsamma anchorata and Verongula rigida. Five bacterial strains: Bacillus cereus (CIP 78.3), Escherichia coli (CIP 54.127), Pseudomonas aeruginosa (CIP A22), Staphylococcus aureus (CIP 67.8) and Staphylococcus saprophyticus (CIP 76125) were evaluated, as well as four tumor cell lines: breast cancer (MDA-MB231), glioblastoma (RES259) and leukemia (MOLM14 and HL-60). Antimicrobial activity was evaluated using the disc diffusion technique by determining the minimum inhibitory and minimum bactericidal concentrations. Tumor cytotoxic activity was determined in vitro by defining the minimum concentration of extracts that would inhibit cell growth. Ethanolic extracts of Agelas clathrodes were bactericidal for Staphylococcus aureus and Staphylococcus saprophyticus strains, as well as strongly cytotoxic (IC50 < 20 µg/mL) on all cancer cell lines. Verongula rigida also showed strong cytotoxic activity on cell lines but no antimicrobial activity. These results are innovative for this species on these bacterial lines, highlighting the potential of sponge extracts from this area as bioactive compounds sources.
First Steps in Random Walks: From Tools to Applications

1. Characteristic Functions 2. Generating Functions and Applications 3. Continuous Time Random Walks 4. CTRW and Aging Phenomena 5. Master Equations 6. Fractional Diffusion and Fokker-Planck Equations for Subdiffusion 7. Levy Flights 8. Coupled CTRW and Levy Walks 9. Simple Reactions: A+B->B 10. Random Walks on Percolation Structures
How much do we know and how much do we care about genetic diversity of threatened plants ? A case study from the French flora

ABSTRACT Small demographic size and reduced genetic diversity increase the extinction probability of a population. Genetic diversity within populations for neutral markers is an heuristic parameter, as it reflects past and ongoing processes acting on populations, and informs on possible futures. This study presents a synthesis of the knowledge on neutral genetic diversity for threatened plants in metropolitan France and the use of such data in management actions. Pairing threatened species with the closest non-threatened species for which we could find appropriate genetic data, we collected information on genetic diversity for 25 threatened species and non-threatened controls. We found that threatened species in France have on average a lower within-population genetic diversity than non-threatened controls and thus are exposed to risks linked to genetic erosion. Combining an analysis of recovery plans and a survey addressed to practitioners, we concluded that genetic diversity is rarely integrated in management actions. The integration of such information into applied conservation remains a challenge. We provide some guidelines to collect biological traits impacting within-population genetic diversity and some specific recommendations for a better incorporation of population genetics concepts into conservations actions.
Solar Cycle Variability in Coronal Holes and Their Effects on Solar Wind Sources

Various upstream spacecraft have now observed the solar wind conditions affecting the Earth since the 1970s, covering over four solar activity cycles. These measurements provide a long term picture of the related patterns in large scale incident plasma and magnetic field parameters of interest for both interpreting cycles in geospace effects, and understanding how the Sun controls our space environment. This paper focuses on the latter, in part to provide context at the start of the new solar cycle 25, and toward establishing connections between the 1 AU ecliptic solar wind behavior and the unprecedented near‐Sun measurements of heliospheric features on Parker Solar Probe and Solar Orbiter. Magnetograph data‐based potential field source surface models provide a basic picture of how the solar wind sources, including those that give rise to corotating high speed streams in the ecliptic, have changed since the beginning of the record of regular solar wind measurements. In particular, they suggest the contributions from low to mid latitude coronal holes dominate the observed cycles (21–24), especially the weaker cycles (23 and 24), impacting upstream measurement interpretations, modeling, and forecasting considerations. For example, recurring features are affected by differential rotation of the Sun's surface field, which through its effects on the corona, can produce solar wind streams reappearing at ∼25–30 days intervals instead of at the canonical 27.3 days Carrington rotation rate. In addition, the conditions that lead to the corotating stream structure that can dominate periods of low solar activity are seen to be more complicated than suggested by the simple concepts of early studies. The overall results illustrate where in the cycles well‐defined, long‐lived large scale structures can be expected, and the advantages of synoptic displays of 1 AU solar wind parameters for anticipating timings of recurring features.
Rotating Single-Antenna Spoofing Signal Detection Method Based on IPNN

The traditional carrier-phase differential detection technology mainly relies on the spatial processing method, which uses antenna arrays or moving antennas to detect spoofing signals, but it cannot be applied to static single-antenna receivers. Aiming at this problem, this paper proposes a rotating single-antenna spoofing signal detection method based on the improved probabilistic neural network (IPNN). When the receiver antenna rotates at a constant speed, the carrier-phase double difference of the real signal will change with the incident angle of the satellite. According to this feature, the classification and detection of spoofing signals can be realized. Firstly, the rotating single-antenna receiver collects carrier-phase values and performs double-difference processing. Then, we construct an IPNN model, whose smoothing factor can be adaptively adjusted according to the type of failure mode. Finally, we use the IPNN model to realize the classification and processing of the carrier-phase double-difference observations and obtain the deception detection results. In addition, in order to reflect that the method has a certain practical value, we simulate the spoofing scenario of satellite signals and effectively identify abnormal satellite signals according to the detection results of the inter-satellite differential combination. Actual experiments indicate that the detection accuracy of the proposed method for spoofing signals reaches 98.84%, which is significantly better than the classical probabilistic neural network (PNN) and back-propagation neural network (BPNN), and the method can be implemented in fixed base station receivers for the real-time detection of forwarding spoofing.
Diagnosis and Management of Adrenal Crisis in 46XX Congenital Adrenal Hyperplasia Infant

Highlight: The diagnosis and therapy of Congenital Adrenal Hyperplasia (CAH) children with Adrenal crisis (AC) case report. Adrenal crisis (AC) is a life-threatening emergency that contributes to the high death rate of children with adrenal insufficiency. The early detection and prompt treatment can improve the outcomes of patients with CAH and AC. Abstract: Adrenal crisis is the acute complication of the patient with congenital adrenal hyperplasia. Congenital adrenal hyperplasia (CAH) is a rare condition. Children with CAH commonly come to the emergency room due to acute complications. The condition has high mortality and thus needs early recognition. Newborn screening for CAH in Indonesia is not routinely performed and has not been suggested yet. The purpose of this case report was to report a case of adrenal crisis in a congenital adrenal hyperplasia patient focused on diagnosis and therapy. A female, 10 months old infant, was admitted to the emergency department with a chief complaint of a decrease of consciousness for 3 hours before admission and frequent vomiting since born. On physical examination, there was clitoromegaly. Laboratory showed 17-OH progesterone: 173 ng/dL (7-77 ng/dL) and karyotyping: 46 XX. Management of adrenal crisis is a stress dose of hydrocortisone and rehydration. Education is the key to optimal outcomes and normal growth and development.
A Mobile Application to Help Self-Manage Pain Severity, Anxiety, and Depressive Symptoms in Patients with Fibromyalgia Syndrome: A Pilot Study

Treatment for individuals with fibromyalgia syndrome (FMS) is complex and is not always accessible to those who could benefit. The aim of this study was to conduct a preliminary evaluation of a mobile-app-delivered, cognitive behavioral treatment (CBT)-based intervention in helping adults self-manage fibromyalgia symptoms. A total of 100 adults with FMS (M [SD] age = 49.81, [9.99] years; 94% women) were given access to the digital treatment program and downloaded the app. Pain severity, anxiety symptoms, depression symptoms, fatigue, and sleep quality were assessed at pre-treatment, post-treatment, and 3-month follow-up. Fifty-three of the potential participants completed the 47-day treatment. Data showed significant improvements in pain severity (p = 0.007, d = 0.43), anxiety (p = 0.011, d = 0.40) and depressive symptoms (p = 0.001, d = 0.50) from pre-treatment to post-treatment. The effect sizes associated with app use are consistent with improvements seen in previously published clinical trials of CBT for FMS. Improvements were generally maintained, although there was some decrease in the outcomes from post-treatment to the 3-month follow-up. Most participants reported that they were very satisfied with the app. The use of the app was associated with similar levels of improvements found with in-person CBT treatment for FMS. Research to evaluate the effectiveness of the app in a controlled trial is warranted.
Determinants of students' perceived enjoyment towards online learning

PurposeThe study aims to seek the factors affecting perceived online learning enjoyment among university students across Viet Nam.Design/methodology/approachBased on the concept of the technology acceptance model (TAM), this research adopts structural equation modelling (SEM) to analyse data collected from 795 undergraduate students who have gained the experience of online courses in the period of the COVID-19 pandemic.FindingsThe results of this study indicate that both perceived ease of use and perceived usefulness are significant predictors of students' perceived enjoyment in online courses while perceived obstacles are not its direct antecedents. The correlation between perceived ease of use and perceived usefulness is also affirmed in this study. Besides, differences are found based on students' characteristics including gender, grade and academic major.Research limitations/implicationsAs online learning turns education to be learner-centred, it is crucial to have a better understanding of students' perceptions toward this advanced learning method. The insights found in this research may be of interest to educational administrators, aimed at achieving the digital transformation success in education which may adapt to the current trend of Industrial Revolution 4.0. Originality/valueAccording to the best of the knowledge, this research is the first to explore the effect of the group of three predictors including perceived ease of use, perceived usefulness and perceived obstacles on the students' learning enjoyment toward the online learning method, especially in the context of Viet Nam.
Miniaturized filtering trans‐directional coupler with enhanced input‐reflectionless feature using two types of coupled multi‐line sections

This paper presents a miniaturized filtering trans‐directional (TRD) coupler with enhanced input‐reflectionless feature. Coupled two‐line and three‐line sections are loaded at through and coupled ports of a basic TRD coupler to realize the filtering performance. The basic TRD coupler based on a periodically loaded coupled‐line (CL) can be independently designed to realize tight coupling degree and wideband bandwidth. Coupled three‐line structure has been applied to obtain a higher coupling factor and wider bandwidth in various components. Since the coupled multi‐line sections exhibit open‐circuit at f0, by selecting the appropriate coupling coefficient and type of coupled multi‐line sections, the filtering bandwidth and transmission zeros (TZs) can be independently controlled. Moreover, the input‐reflectionless feature can be realized by the signal‐interference of the reflected stop‐band signals of two output ports. Explicit equations and limitations of implementations are derived and discussed. Two 3‐dB prototypes are designed and built to verify the design theory.
Structure order, local potentials, and physical anomalies of water ice

Hydrogen-bond forms a pair of asymmetric, coupled, H-bridged oscillators with ultra-short-range interactions and memory. hydrogen bond cooperative relaxation and the associated binding electron entrapment and nonbonding electron polarization discriminate water and ice from other usual materials in the physical anomalies. As a strongly correlated fluctuating system, water prefers the statistically mean of tetrahedrally-coordinated structure with a supersolid skin that is elastic, polarized, ice like, hydrophobic, with 3/4 density.
Model Structure Determination and Identifiability Problems in System Identification.

Abstract : System identification has become one of the most active areas in system theory and its applications. In many engineering applications where the system to be identified or estimated is governed by differential or difference equations with known structure, the problem is mainly that of parameter estimation. As the authors extend the concept of system identification to those classes of problems where prior knowledge on structure is limited, some basic problems other than parameter estimation become important. System identification consists of three basic sub-problems: (1) pre-estimation, where one is concerned with structure specification, types of data to be collected, and experimental design, (2) estimation, where the main emphasis is on estimation algorithm development, and (3) post-estimation, where one has to test the validity of using the model for a specific objective. The program of studies reported here is on the basic problem in system identification, with more emphasis on pre-estimation and post-estimation problems.
Self-Correcting Algorithm for Estimated Time of Arrival of Emergency Responders on the Highway

Edge computing is one of the key features of the 5G technology-scape that is realizing new and enhanced automotive use cases for improving road safety and emergency response management. Back Situation Awareness (BSA) is such a use case that provides an advance notification to the vehicles of an arriving emergency vehicle (EmV). This paper presents an algorithm for enhancing the accuracy of the advanced Estimated Time of Arrival (ETA) notification of an approaching EmV towards the other vehicles on the highway. The notification is expected to ensure timely reaction by the vehicles to create a clear corridor for the EmV to pass through unhindered, thereby saving critical time to reach the emergency event in a safe manner. The main features of the presented solution are i) the self-correcting algorithm, ii) adaptive and dynamic dissemination areas size allocation, as a response to traffic changes, and iii) the evaluation of the ETA estimation accuracy. We have used the real travel time data measurements collected on the E313 highway (Antwerp, Belgium), to evaluate the performance of the algorithm. The performance is evaluated and compared in terms of accuracy and run-time complexity, using different methods such as Kalman filter, Filter-less method, Moving Average, and Exponential Moving Average filters. It is observed that the Kalman filter provides better accuracy on the ETA estimation, thereby reducing the estimation error by around 14% on average.
Main pulse−interpulse correlation and mode changing in PSR 1055−52

Les observations radio, a 645 MHz, du pulsar radio 1055-52 qui a une interpulsation forte sont presentees. Les profils de pulsation et la correlation pulsation-interpulsation sont analyses. Les proprietes physiques des pulsations sont etudiees et sont trouvees consistantes avec une geometrie d'emission dans laquelle l'axe de rotation et l'axe magnetique sont presque orthogonaux.