Miracle-dz/UniFAR-FTUs huggingface dataset:
Combination of catalytic ozonation and fungal bioremediation for treatment from effluent from the laminate production industry

This study characterized and evaluated the potential of a combination of treatment strategies for the removal of phenolic compounds, color, and ecotoxicity of an effluent generated by a laminated wood industry. The characterization of a sample of the effluent generated by the pine lamination process collected in an industry in the Southwest region of the state of Paraná confirmed the potential impact of the effluent, with emphasis on the high content of phenolic compounds (1,530 ±50 mg/L), color (2,159 ±30 units), significant acute toxicity (63% mortality of microcrustaceans Artemia salina) and low biodegradability (BOD/COD=0.53), which, if eventually released into receiving bodies, can cause irreversible and harmful effects to the aquatic microbiota. The treatment processes studied in this work involved catalytic ozonation mediated by ferrous catalytic material based on steel scale and biological process with Pleurotus Florida fungi, evaluated in an individual way and sequentially integrated as follows: Catalytic ozonation>>biological process and vice-versa. The best results were obtained by applying the sequence "catalytic ozonation>>biological process", which resulted in reductions of 96.2% in soluble lignin concentrations, 93.3% in color units and more than 99% reduction in total phenols, in addition to a low mortality rate of A. salina (≈10%). In the integrated process, the application of catalytic ozonation before the biological process presents greater advantages because of the pre-decomposition process of recalcitrant compounds by the chemical action of catalytic ozonation, which can convert these compounds into biodegradable, facilitating the action of the biological process for the remediation of the effluent. Keywords: fungi, ozonation, phenols, wood lamination.
An Efficient Sensor Selection Algorithm for TDOA Localization with Estimated Source Position

This paper focuses on improving the sensor selection performance in the time difference of arrival (TDOA)-based localization scenario with the presence of source estimation error. In existing schemes, a coarse source position is first estimated and regarded as the actual counterpart for selecting optimal sensors. However, if the estimated position deviates from the actual position, the localization accuracy determined by the selected sensor subset will severely degrade. To solve the issue, we devise a distance-related weighted average Cramér Rao lower bound (WA-CRLB) to include the spatial information of the actual position by scattering sampling points around the estimated source position according to its distribution. Then, we formulate a Boolean vector-based sensor selection optimization problem to minimize WA-CRLB and propose a modified iterative swapping greedy (MISG) algorithm. Simulation results show that the proposed MISG algorithm achieves higher localization robustness with the increase of TDOA measurement error strength, and has lower computational complexity compared with the previous semi-definite relaxation (SDR)-based algorithms.
Ultra-Lightweight and Secure Intrusion Detection System for Massive-IoT Networks

The Internet of Things (IoT) is starting to integrate deeply into our daily lives thanks to the different services it provides. This technology has already made us more closely linked to the external environment through ubiquitous communication devices. However, even though this proximity has numerous benefits, it also has a significant security impact, where the cyber-attack surface has grown dramatically. In this regard, we present, in this paper, our results toward the development of a decision tree-based machine learning model for intrusion detection in Massive-IoT networks. The principal objective of this work is to provide a highly accurate detection model, while preserving resource consumption by developing a real prototype of the intrusion detection system. To this end, we first propose and apply our pre-processing methodology on the well-known Avast IoT-23 dataset, allowing us to reach a high detection rate with 99.99% of accuracy and just 1804KB of the model’s size. Then, we propose a new machine learning model based on the decision tree classifier and deploy it in a real environment with malicious attack traffic. Obtained results show that our proposed model allows 88% of real-traffic-based precision rate and up to 90% of specificity.
Design of a Nonintrusive Current Sensor with Large Dynamic Range Based on Tunneling Magnetoresistive Devices

Current sensors are widely used in power grid for power metering, automation and power equipment monitoring. Since the tradeoff between the sensitivity and the measurement range needs to be made to design a current sensor, it is difficult to deploy one sensor to measure both the small-magnitude and the large-magnitude current. In this research, we design a surface-mount current sensor by using the tunneling magneto-resistance (TMR) devices and show that the tradeoff between the sensitivity and the detection range can be broken. Two TMR devices of different sensitivity degrees were integrated into one current sensor module, and a signal processing algorithm was implemented to fusion the outputs of the two TMR devices. Then, a platform was setup to test the performance of the surface-mount current sensor. The results showed that the designed current sensor could measure the current from 2 mA to 100 A with an approximate 93 dB dynamic range. Besides, the nonintrusive feature of the surface-mount current sensor could make it convenient to be deployed on-site.
Molecular characterization of blue-green algae (Anabaena constricta) and comparative studies of biodiesel production from other species

Biodiesel can substitute fossil fuels adequately and thus, considered ‘future fuel’. Thus, identifying a promising algal strain for efficient biodiesel production is a very important endeavor. In the present investigation, the blue green algae, Anabaena constricta could be grown aseptically attaining exponential phase, 3 days post inoculation, responds to phototropism and amenable to both autotrophic and heterotrophic mode. Phylogenetic analysis reveal that Anabaena constricta grouped separately from other algal strains used in the study, making it unique in nature. Further, comparative studies of selected algal and blue green algal strains based on the oil percentage and fatty acid profile indicate potential biodiesel properties. The total lipid content of Anabaena constricta is estimated to 14% of the dry weight, and fatty acids profiling indicate presence of 11 fatty acid methyl esters (FAMEs), principally palmitic acid (16:0), oleic acids (18:1), linoleic acid (18:2), palmitoleic acid (16:1). The algal species, Hydrodictyon registered highest percentage of unsaturated fatty acids (59.5%), while highest content of saturated fatty acid was found in Anabaena constricta (51.5%). Cetane Number of seven algal and blue green algal biodiesel varied from 54.77 to 58.2 and Saponification Value varied from 205.6 to 211.39. PROMETHEE & GAIA analyses indicate both the Rhizoclonium and Tolypothrix species outranked while Hydrodictyon and Anabaena constricta are the least suitable species in seven algal and blue-green algal species studied for biodiesel production. Well-characterized strains offer promise for biodiesel production at a cost-effective level. The present study focus on the renewable fuel, which is useful for reducing the carbon footprint with potential to impact self-sustainability in fuel sector, without modification in current infrastructure.
An Anatomical and Histochemical Study of Abscission in Maturing Sweet Cherry Fruit

Abscission of maturing sweet cherry fruit (Prunus avium L. cv. Windsor) occurred at 2 different abscission zones, depending on the stage of fruit development. Immature fruit abscised at the upper zone between the pedicel and peduncle; mature fruit abscised at the lower zone between the fruit and receptacle. Separation in the abscission layer began directly above the stony pericarp and resulted in the formation of a cavity. Later separation occurred at the fruit : pedicel indentation and extended through the abscission layer toward the vascular bundles. Abscission involved the fracturing of cell walls as well as wall separation. There was no evidence of change in pectins, cellulose or other polysaccharides in the cell walls of the abscission layer prior to or during fruit separation. No starch accumulation in the abscission zone or lignification of tissue adjacent to the abscission layer was observed through fruit maturity.
Clinical and Molecular Implications of Osteopontin in Heart Failure

The matricellular protein osteopontin modulates cell–matrix interactions during tissue injury and healing. A complex multidomain structure of osteopontin enables it not only to bind diverse cell receptors but also to interact with various partners, including other extracellular matrix proteins, cytokines, and growth factors. Numerous studies have implicated osteopontin in the development and progression of myocardial remodeling in diverse cardiac diseases. Osteopontin influences myocardial remodeling by regulating extracellular matrix production, the activity of matrix metalloproteinases and various growth factors, inflammatory cell recruitment, myofibroblast differentiation, cardiomyocyte apoptosis, and myocardial vascularization. The exploitation of osteopontin loss- and gain-of-function approaches in rodent models provided an opportunity for assessment of the cell- and disease-specific contribution of osteopontin to myocardial remodeling. In this review, we summarize the recent knowledge on osteopontin regulation and its impact on various cardiac diseases, as well as delineate complex disease- and cell-specific roles of osteopontin in cardiac pathologies. We also discuss the current progress of therapeutics targeting osteopontin that may facilitate the development of a novel strategy for heart failure treatment.
IoT Based Targeting System - Airsoft Use-Case

With the wide adoption of Internet of Things (IoT) devices, controller modules have become increasingly smaller and cheaper, allowing their use for a broader range of applications. This paper approaches the design and demonstration of a Targeting system commonly implemented with the help of cabling systems (reading sensors nearby), here replaced by an IoT solution. To fulfill the proposed objective, a Wemos D1 Mini module integrated with a smartphone that gives control of the network to the user is combined to create an airsoft target system that is easily controlled via a smartphone in a dynamic environment. When the target is hit, it communicates the event back to the smartphone to give it back to the user. In turn, the smartphone will control different game modes and send commands back to the targets. The microcontroller on the target’s side will acquire information from sensors and transmit these readings back to the smartphone. The solution approach is wireless and includes batteries that provide sufficient energy for the game’s duration.
Use of Natural Cytokinins to Extend the Storage Life of Broccoli (Brassica oleracea, Italica Group)1

Two natural cytokinins, zeatin and dihydrozeatin, were effective in preserving broccoli appearance and chlorophyll content. Single treatments with 100 ppm aqueous solutions of the 2 compounds, followed by storage at 13°C, permitted storage life of 5 days for zeatin- and 4 days for dihydrozeatin-treated samples of broccoli. Repeated treatments with these compounds increased broccoli storage life to 6 days at 13°C, approaching the apparently limiting value of 7 days conferred by the synthetic cytokinin, 6-benzylamino purine (25 ppm). Broccoli without cytokinin treatment remained salable for only 2 days at 13°C. Visual scores for color were linearly related to chlorophyll concentration.
Drone enabled Smart Air-Agent for 6G Network

The future ubiquitous network, which is mainly characterized by full coverage communication, air-ground integration, multidimensional fusion, network reconfiguration and sensing-communication-computing integration, has become the development trend of 6G technology. The realization of ubiquitous coverage and perceptive fusion of IoT-UAV-Edge is an urgent problem to be solved for complex fusion services. Therefore, this paper proposes a drone-enabled smart air agent in 6G edge fusion system. Firstly, the energy efficient dynamic routing strategy based on joint air-ground control optimization is designed to improve the fusion sensing performance and prolong the service time of drone swarm. Then, the system integration of user-IoT-UAV-Edge is realized to achieve the functionalities of perception, transmission, computing and analysis. Finally, an airborne data fusion mechanism based on multi-source sensing is designed to solve the associated cognitive optimization problem for multi-modal information. The experimental results invalidate the effectiveness and practicability of our system on autonomous path planning, effective computing offloading and accurate airborne fusion.
Power-On Reset Circuit in 180-nm CMOS With Brownout Detection, Stable Switching Points, Long Reset Pulse Duration, and Resilience to Switching Noise

Based on a review of presented power-on reset (POR) integrated circuit (IC) module designs for different environments and aims, an example of high-speed POR module with the supply voltage brownout detection and resilience to glitch supply noise (GSN) has been designed in a 0.18-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS technology. The module has dimensions of <inline-formula> <tex-math notation="LaTeX">$176 ~\mu \text{m}$ </tex-math></inline-formula> per <inline-formula> <tex-math notation="LaTeX">$102 ~\mu \text{m}$ </tex-math></inline-formula> and the static current consumption of <inline-formula> <tex-math notation="LaTeX">$14 ~\mu \text{A}$ </tex-math></inline-formula>. The basic features are stable detection thresholds of 1.52 and 1.42 V, the reset time pulse duration of more than 0.3 ms, independence from temperature, technological process, and the supply voltage value and slew rate. The unique feature is resilience to the supply voltage glitches down to 70% of the rated voltage, which is sometimes below any thresholds, with a duration of fewer than <inline-formula> <tex-math notation="LaTeX">$10 ~\mu \text{s}$ </tex-math></inline-formula>.
Textural and sensory characterization of carbomeric gels with panthenol

Introduction. The aim of this study was to evaluate the influence of the carbomer concentration (used as the gelling agent, in the range 0.5 - 2.0%) on textural and sensory characteristics of gels with 3% panthenol using sensory analysis as subjective and texture analysis as an objective assessment method. An active substance in the gels was panthenol, which also acted as a neutralizing agent of the carbomer. Participants and methods. Twenty female panelists, aged between 20 and 36, participated in the sensory study and had to fulfill a questionnaire regarding product attributes before, during and after application on the skin. Texture analysis was performed on CT3 Texture Analyzer, after each week for a month, and the following parameters were calculated: hardness cycle 1, hardness cycle 2, cohesiveness, adhesiveness, resilience and springiness. Results. The results showed that gels were stable over time and the structure of the gels was preserved regardless of compression. An increase in hardness and resilience was followed by an increase in the concentration of carbomer, while adhesiveness, cohesiveness and springiness did not differ much among different gels. The same trend was noticed when gels were compared during time. Sensory analysis confirmed findings of texture analysis and showed that with the increment of carbomer concentration, stickiness and density also enhanced, while absorption rate and spreadability decreased. Gel with 1% carbomer was chosen by the majority of panelists as favorite and as a gel they would regularly use. Conclusion. The methods of textural and sensory analysis represent valuable approaches in drug/cosmetic product design because they offer insight in the compliance of patients/consumers.
Time evolution of a non-singular primordial black hole

There is growing notion that black holes may not contain curvature singularities (and that indeed nature in general may abhor such spacetime defects). This notion could have implications on our understanding of the evolution of primordial black holes (PBHs) and possibly on their contribution to cosmic energy. This paper discusses the evolution of a non-singular black hole (NSBH) based on a recent model [1]. We begin with a study of the thermodynamic process of the black hole in this model, and demonstrate the existence of a maximum horizon temperature T_{max}, corresponding to a unique mass value. At this mass value the specific heat capacity C changes signs to positive and the body begins to lose its black hole characteristics. With no loss of generality, the model is used to discuss the time evolution of a primordial black hole (PBH), through the early radiation era of the universe to present, under the assumption that PBHs are non-singular. In particular, we track the evolution of two benchmark PBHs, namely the one radiating up to the end of the cosmic radiation domination era, and the one stopping to radiate currently, and in each case determine some useful features including the initial mass m_{f} and the corresponding time of formation t_{f}. It is found that along the evolutionary history of the universe the distribution of PBH remnant masses (PBH-RM) PBH-RMs follows a power law. We believe such a result can be a useful step in a study to establish current abundance of PBH-MRs.
Can stellar dynamos be modelled in less than three dimensions

Les equations de base et les definitions associees aux dynamos αω axisymetriques sont presentees. Les resultats de plusieurs modeles axisymetriques de geometries differentes sont compares afin de determiner les consequences de la negligence de la structure radiale et de la courbure. Un modele non-axisymetrique 2D, ne tenant pas compte de la structure radiale, est developpe. Les resultats lineaires et non lineaires de ce modele sont analyses
Safe sonet: A framework for building trustworthy relationships

The advent of easy to use services and the ability to bridge boundaries in space and time has increasingly changed our social lives and com-munication habits. Being unaware of their audience people on social networks inconsiderately share many personal items. Generally Social Networking Sites (SNS) users depend on the SNS platform for managing their social identities. Although SNS providers have introduced privacy settings to protect users against threats, these are insufficient and the access control models are difficult to be understood by novice users [1]. Unexpectedly, even those who are aware of the security and privacy threats and the preventive tools that combat those threats, lack the motivation to utilize security features to protect themselves. The paper discusses a frame-work (Safe SoNet) that aims to provide a plat-form for secure sharing of posts. The objective of this framework is twofold. Firstly, to analyze user behavior by retrieving user information from various social networking sites, addressing transliteration issues. Secondly, apply the user behavior to quantify the trust score of a connect, which would in turn form a decision making parameter to decide on the peer with whom the information can be securely shared.
Effects of Bogies on the Wake Flow of a High-Speed Train

The wake region of high-speed trains is an area of complex turbulent flow characterized by the periodic generation and shedding of vortices, which causes discomfort to passengers and affects the stability and safety of the train. In this study, the unsteady characteristics of the wake flows of three 1:1 scale China Railway High-Speed 380A (CRH380A) high-speed train models with different degrees of simplification were numerically investigated using the improved delayed detached eddy simulation (IDDES) method. Analyses of the aerodynamic forces, train-induced slipstream, and turbulent kinetic energy (TKE) were conducted to determine the effects of the bogies on the wake flow of the high-speed train. It was found that the existence of bogies on the bottom of the train, especially the last bogie, not only enhanced the wake flow but also introduced large perturbances into the wake flow. Moreover, the generation and evolution of the vortices in the wake flows were determined by analyzing the instantaneous flow fields and coherent flow structures that were obtained by the dynamic mode decomposition (DMD) method. The results showed that a pair of large, counter-rotating streamwise vortices in the real model of the high-speed train was generated by the cowcatcher and their intensity was significantly enhanced by perturbances that were introduced by the bogies on the bottom of the train.
COVID-19 Diagnosis by Wavelet Entropy and Extreme Learning Machine

In recent years, COVID-19 has spread rapidly among humans. Chest CT is an effective means of diagnosing COVID-19. However, the diagnosis of CT images still depends on the doctor's visual judgment and medical experience. This takes a certain amount of time and may lead to misjudgment. In this paper, a new algorithm for automatic diagnosis of COVID-19 based on chest CT image data was proposed. The algorithm comprehensively uses WE to extract image features, uses ELM for training, and finally passes k-fold CV validation. After evaluating and detecting performance on 296 chest CT images, our proposed method is superior to state-of-the-art approaches in terms of sensitivity, specificity, precision, accuracy, F1, MCC and FMI.
Population genetic diversity and structure of Rhinogobius candidianus (Gobiidae) in Taiwan: Translocation and release

Abstract Rhinogobius candidianus is a freshwater goby distributed in north, northwest, west, and south Taiwan, but this species has been introduced to east Taiwan and became dominant. To investigate its native population genetic diversity and structure and evaluate the sources and diversity of translocated populations, the mitochondrial DNA control region and cytochrome b gene (1981 bp) from 220 specimens were analyzed. These results indicated that (1) the east populations originated from two sources in west Taiwan; (2) translocated populations exist in east Taiwan and south Taiwan; (3) many populations have likely been moved secondarily by human intervention; (4) the effective size of the populations had declined greatly; (5) within the native populations, the ancestral populations colonized Taiwan during the land bridge phase in the Pleistocene through north Taiwan; (6) the landform changes in Taiwan shaped the population structure; and (7) the landforms of the coastline during glaciation also shaped the native range. The low‐level genetic diversity, high population differentiation, and population decline greatly suggest the need for resource management and conservation interventions. Four clades (α–δ) should be managed as four distinct evolutionarily significant units, while the translocated populations should be managed as separate management units. Moreover, the translocated populations in east Taiwan should be evaluated and monitored carefully.