Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification and Identification of Spectral Pixels with Low Maritime Occupancy Using Unsupervised Machine Learning

For marine accidents, prompt actions to minimize the casualties and loss of property are crucial. Remote sensing using satellites or aircrafts enables effective monitoring over a large area. Hyperspectral remote sensing allows the acquisition of high-resolution spectral information. This technology detects target objects by analyzing the spectrum for each pixel. We present a clustering method of seawater and floating objects by analyzing aerial hyperspectral images. For clustering, unsupervised learning algorithms of K-means, Gaussian Mixture, and DBSCAN are used. The detection performance of those algorithms is expressed as the precision, recall, and F1 Score. In addition, this study presents a color mapping method that analyzes the detected small object using cosine similarity. This technology can minimize future casualties and property loss by enabling rapid aircraft and maritime search, ocean monitoring, and preparations against marine accidents.
Integrating Rolling Stock Circulation into the Delay Management Problem

In this paper, we consider the situation of a disturbed railway network. In case of disturbances, many decisions have to be made to find a disposition timetable which is feasible and minimizes the inconvenience for the passengers. In the delay management models discussed in the literature, the rolling stock circulations are always assumed to be fixed. We relax this assumption and allow changes in the vehicle schedules if they lead to a better disposition timetable. We present an integer programming model for the delay management problem integrating the rolling-stock-circulation decisions, investigate its complexity and suggest bounds and first solution approaches.
Brain Magnetic Resonance Imaging-Based Evaluation of Pediatric Patients With Developmental Delay: A Cross-Sectional Study

Background Developmental delay refers to the insufficient acquisition of age-appropriate developmental milestones. According to World Health Organization, approximately 5% of all children under the age of 14 years display some developmental disability. Aim and objective Our objective was to investigate the prevalence of abnormal magnetic resonance imaging (MRI) brain findings in pediatric patients with non-syndromic developmental delay and to establish the utility of MRI for the same. Material and Method This cross-sectional study prospectively enrolled 60 pediatric patients (three months to 12 years) and data were analyzed using SPSS software. Result Abnormalities on MRI were seen in 80% of cases, with findings indicating perinatal hypoxic insult (36.67%) being the most common, followed by structural abnormalities of the brain (20%). There was no significant difference in the prevalence of abnormal findings when classified by gender or age, or between global developmental delay (GDD) alone and GDD with epilepsy. However, perinatal hypoxic insult was significantly associated with GDD with epilepsy rather than GDD alone (p < 0.01). Conclusion In this study, brain MRI provides a high yield of abnormal findings and helps calculate the relative prevalence of various common etiologies in non-syndromic developmental delay. This study supports several international guidelines that include MRI as the first-line investigation for non-syndromic developmental delay.
Algorithms for Controlling a Nonholonomic Differential Drive Wheeled Mobile Robot

This paper discusses different algorithms for controlling an autonomous nonholonomic differential drive wheeled mobile robot (WMR) on the horizontal X-Y plane. The presented algorithms are used for controlling the WMR to perform several useful tasks like the following: moving to a goal point, moving to specific pose, line following and path following. Each algorithm designs the necessary input velocities for the robot kinematic model such that the WMR can accomplish the corresponding task efficiently. The delicate task here for the WMR is to follow any given reference path, hence a fuzzy PD controller is proposed in this paper to improve the effectiveness of the path following controller. The fuzzy PD controller is designed based on the fuzzy logic approach. The presented techniques are simple and efficient therefore they can be used in real time applications like control and navigation of mobile robots. Finally, Matlab simulations are given to test the different algorithms.
Agile Modeling and Design of Service-Oriented Component Architecture

Component-Based Development (CBD) and Web Services (WS) have been proposed as ways of building high quality and flexible enterprisescale e-business solutions that fulfill business goals within a short time-tomarket. However, current achievements in these areas at the level of modeling and design are much behind the technology ones. This paper presents how component-based modeling and design principles can be used as a basis for modeling a Service-Oriented Architecture (SOA). Proposed design approach is basically model-driven, but incorporates several agile development principles and practices that provide its flexibility and agility in today’s ever-changing business and IT environments.
Precipitation Scaling With Temperature in the Northeast US: Variations by Weather Regime, Season, and Precipitation Intensity

We present a novel hierarchical Bayesian quantile regression model to estimate how precipitation scales with temperature depending on season, weather regime (WR; i.e., large‐scale patterns of atmospheric circulation), and precipitation percentile. The approach develops regional scaling estimates by partially pooling data across sites, accounting for uncertainty stemming from variable record lengths. Results using long‐term records of daily and hourly precipitation and both dry‐bulb and dew point temperature across the Northeast US suggest that regional precipitation scaling rates vary from 0% to 8% per °C. Scaling rate variability is driven most by season and the percentile of precipitation, with only modest variations across WRs. Daily scaling rates are highest in the winter and summer, while hourly rates at the highest percentiles are greatest in summer. Lower scaling rates for more extreme precipitation quantiles are driven by a handful of storms occurring at cooler temperatures but with strong vertical uplift and heavy precipitation.
Blockchain enabled joint trust (MF‐WWO‐WO) algorithm for clustered‐based energy efficient routing protocol in wireless sensor network

In this manuscript, a blockchain enabled joint trust (MF‐WWO‐WO) algorithm for clustered based energy efficient routing protocol in wireless sensor network (WSN) is proposed for secure data transmission by finding the optimum cluster head (CH) in the network. Here, MayflyWater Wave Optimization (MF‐WWO) algorithm is used for CH selection accurately. After the selection of CH, the malicious node occurs in the cluster. Hence, the multi objective whale optimization algorithm is proposed to find the trust path from the several paths. At last, the optimized selected trust paths are given to the blockchain for communications in the network that is safe and more trustworthy. The simulation is done in MATLAB. The proposed MF‐WWO‐WO achieves high throughput, high efficiency, high network life time, high packet delivery ratio, low delay, low energy consumption, and low packet loss ratio. The outcomes shows the better performance of the proposed approach when compared to the existing approaches, like blockchain and clustered based secured data aware energy efficient using fitness averaged rider optimization algorithm FA‐ROA blockchain and clustered based secured data aware energy efficient using trusted moth flame optimization and genetic optimization algorithm TMFO‐GOA. Finally, the proposed approach attains better energy efficiency and security.
An Analysis of Selected Technological Parameters’ Influences on the Tribological Properties of Products Manufactured Using the FFF Technique

This study investigates how layer deposition in printing 3D models made of polyetherimide (PEI) using the fused filament fabrication (FFF) technique affects resistance of these models to abrasive wear. Samples made by additive manufacturing with different setting of build orientation and path generation strategy of extruded fibers were used in the experiment. The experiments were conducted on a tribometer according to the ASTM G65-16 standard. The friction force, normal force, and temperature in the contact area during the tribometer operation were measured using a strain gauge sensor. The tribometer allowed us to perform the tribological experiments using a rubber-coated or a metal disc without a lubricant in the so-called “dry” operation. Following the ASTM G65-16 standard, a rubber-coated disc and Fe3Al2 (SiO4)3 garnet abrasive were used for the wear resistance tests. The analysis of experimental data showed correlations among orientation selection, the strategy of layer deposition by the FFF technique, and the surface life in terms of abrasive wear. The results of this research also showed the suitability of the chosen building orientation and deposition strategy for part production by additive manufacturing, depending on the required tribological properties, such as the coefficient of friction (yield path) and wear behavior. Based on the results of the study, it is concluded that continuity of wear and friction force depends on the path traveled under the model production orientation. The size of wear (material loss) ranged from 0.451–0.809%. It was shown that the weight loss of the sample under loading was greater, on average, with the chosen fiber orientation strategy in the Z direction than in the X direction.
A New Approach for Industrial Cluster Performance and Human Resources Management: Based on Survey

Industrial clusters (IC) are groups of inter-related industries which drive wealth creation in a region, primarily through the production and export of goods and services. The use of clusters as a descriptive tool for regional economic relationships provides a richer, more meaningful representation of local industry drivers and regional dynamics than do traditional methods. On the other hand, one of the fundamental part of every industry such as IC is human resources managements (HRM). Manpower are key capital of organizations and can improve performance too. Although recent researches have been developed the concept of IC but they have not considered aspect of human resources (HR) on clusters performance. So, the purpose of this article is to examine the effect of special aspect of human resource management on IC. Data were collected based on interview and questionnaire with clusters development agent (CDA), managers of industrial clusters and labors. We used correlation matrix to test hypothesis. Results indicated that it is necessary for firms to develop the skill and training of human resources and labors of industrial clusters and it can affect total performance of IC.
DYNAMIC MASS MEASUREMENT AND APPROPRIATE FILTER ANALYSIS

The output signal of the load cells used in weighing systems always has an oscillating response and a certain amount of time is needed for this signal to settle to its real value. On the other hand, the output signal of the load cell in conveyor belt type checkweighers is significantly noisy due to the system's own vibrations and the fact that the object is moving. It is necessary to use effective filters in order to eliminate the effect of these noises and to improve the response of the load cell. Increasing the effect of the filter improves the accuracy of the measurement; however, it leads to an increase in measurement time as well. Therefore, it is necessary to use effective and quick-response filters in applications where measurement speed and accuracy are important. In this study, an electronic and mechanical system that can weigh moving products was designed and appropriate filters were tested and analyzed to reach the desired weighing speeds.
Error Bounds for Localization in mmWave MIMO Systems: Effects of Hardware Impairments Considering Perfect and Imperfect Clock Synchronization

Localization demands high-accuracy positioning, and this rings especially true in the context of fifth-generation (5G) millimeter-wave (mmWave) systems. However, it is easier said than done. mmWave systems require a large number of antennas to be deployed at the transceiver, so having ideal hardware components at each antenna is unrealistic. Degradation in the received signal, caused by hardware impairments (HWIs), affects the spectral efficiency, which in turn influences user positioning. Moreover, a high level of clock synchronization between the base station (BS) and the user equipment (UE) is rarely achieved. In this article, we investigate the effect of HWIs on UE localization under synchronous and asynchronous conditions. In order to minimize imperfect synchronization, two anchors or two-way localization protocols, a round-trip (RLP) as well as a collaborative localization protocol (CLP) are used. Conducting the localization process using the BS, we find the position and orientation bounds. We then study the effect of HWIs on the error bounds under the mentioned scenarios. Our numerical results show that HWIs have a significant impact on localization in all conditions, localization using two anchors and the CLP being more robust, however, against HWIs. Based on our outcome, compensating for imperfect synchronization using RLP does not increase the resilience of the system against HWIs.
DspA/E-Triggered Non-Host Resistance against E. amylovora Depends on the Arabidopsis GLYCOLATE OXIDASE 2 Gene

DspA/E is a type three effector injected by the pathogenic bacterium Erwinia amylovora inside plant cells. In non-host Arabidopsis thaliana, DspA/E inhibits seed germination, root growth, de novo protein synthesis and triggers localized cell death. To better understand the mechanisms involved, we performed EMS mutagenesis on a transgenic line, 13-1-2, containing an inducible dspA/E gene. We identified three suppressor mutants, two of which belonged to the same complementation group. Both were resistant to the toxic effects of DspA/E. Metabolome analysis showed that the 13-1-2 line was depleted in metabolites of the TCA cycle and accumulated metabolites associated with cell death and defense. TCA cycle and cell-death associated metabolite levels were respectively increased and reduced in both suppressor mutants compared to the 13-1-2 line. Whole genome sequencing indicated that both suppressor mutants displayed missense mutations in conserved residues of Glycolate oxidase 2 (GOX2), a photorespiratory enzyme that we confirmed to be localized in the peroxisome. Leaf GOX activity increased in leaves infected with E. amylovora in a DspA/E-dependent manner. Moreover, the gox2-2 KO mutant was more sensitive to E. amylovora infection and displayed reduced JA-signaling. Our results point to a role for glycolate oxidase in type II non-host resistance and to the importance of central metabolic functions in controlling growth/defense balance.
Combined plasma-enhanced-atomic-layer-deposition gate dielectric and in situ SiN cap layer for reduced threshold voltage shift and dynamic ON-resistance dispersion of AlGaN/GaN high electron mobility transistors on 200 mm Si substrates

In this work we will present the experimental path followed to optimize the dynamic ON-resistance (RDS-ON) dispersion and to reduce the threshold voltage shift of AlGaN/GaN transistors grown on 200 mm Si wafers. Firstly, it will be demonstrated that a SiN gate dielectric grown by means of plasma enhanced atomic layer deposition (PEALD) instead of rapid thermal chemical vapor deposition (RTCVD) reduces threshold voltage (Vth) shift induced by negative gate bias and the gate leakage. Secondly, the dynamic RDS-ON dispersion of two wafers with same gate dielectric (PEALD SiN) but different in situ metal organic chemical vapor deposition (MOCVD) capping layer, GaN or SiN, is compared. Results will show that the traps at the surface causing the RDS-ON dispersion can drastically be reduced by using in situ MOCVD SiN.
Utilização de portefólios digitais na formação inicial de professores, como estratégia de aprendizagem e avaliação: perspetivas das estudantes

Neste artigo apresentamos os resultados de um estudo desenvolvido na formação inicial de professores sobre a utilização de portefólios digitais como estratégia de aprendizagem e avaliação. No estudo, com características de estudo de caso interpretativo, foram entrevistadas estudantes que vivenciaram experiências de utilização de portefólios digitais em diferentes momentos da sua vida acadêmica, onde se pretendeu perceber a relação entre estas experiências, o processo de aprendizagem e a avaliação. Os resultados evidenciam os contributos positivos do portefólio digital para a aprendizagem e a avaliação das estudantes, bem como as principais dificuldades que revelam.
Sand Flies and Their Microbiota

Sand flies are a significant public health concern in many parts of the world where they are known to transmit agents of several zoonotic diseases to humans, such as leishmaniasis. Vector control remains a key component of many anti-leishmaniasis programs and probably will remain so until an effective vaccine becomes available. The sand fly gut microbiota has recently emerged as an encouraging field for the exploration of vector-based disease control. In particular, the gut microbiome was previously reported to either enhance or inhibit parasite activity depending on the species of bacteria and, thus, has the potential to alter vector competence. Here, we describe the technological advances that are currently expanding our understanding of microbiota composition in sand flies. The acquisition and composition of microbiomes are influenced by several abiotic and biotic factors, including host immunity, genetics, and the environment. Therefore, the microbiomes of sand flies can vary substantially between individuals, life stages, species, and over geographical space, and this variation likely contributes to differences in host phenotypes, highlighting opportunities for novel vector control strategies.
A Cross-Layer Design Approach to Strategic Cyber Defense and Robust Switching Control of Cyber-Physical Wind Energy Systems

Due to the increasing adoption of smart sensing and Internet of things (IoT) devices, wind energy system (WES) becomes more vulnerable to cyber and physical attacks. Therefore, designing a secure and resilient WES is critical. This paper first proposes a system-of-systems (SoS) framework for the cyber-physical WES. Specifically, on the one hand, we adopt a game-theoretic model to capture the interactions between the WES system defender and the adversary at the cyber layer. The outcome of this cyber defense game is reflected by control-aware Nash equilibria. On the other hand, we devise a cyber-aware robust and resilient switching controller based on a Markov jump linear system model for the physical WES. The performances of the WES cyber and physical layers are interdependent due to their natural couplings. We further investigate the SoS equilibrium of the integrated WES, which considers the system security, robustness, and resilience holistically. Finally, we use case studies to corroborate the developed cross-layer design principles for the cyber-physical WES. Note to Practitioners—Cybersecurity becomes a critical concern of wind energy system (WES) operators as an increasing amount of IoT devices are adopted for WES’s communication, monitoring, and operation support purposes. This cyber-physical integration in WES creates a much broader attack surface because adversaries can compromise the physical WES by attacking its dependent cyberspace. To mitigate the impact of attacks, the operator should not only design intelligent control strategies for WES but also strategically secure the WES’s cyber layer. These two goals are naturally coupled together. On the one hand, the WES operates under different compromised conditions depending on the attack actions at the cyber layer. Thus, the control design needs to be adversary-aware by taking the real-time cyber state into account. On the other hand, the adversary’s cyberattack strategy is influenced by the induced performance degradation of WES. Hence, the corresponding attack measures and countermeasures, in turn, should be physically control-aware. This paper establishes a holistic mathematical framework to simultaneously address these two challenging objectives. The obtained solution provides guidelines for the WES operator on the optimal security resource investment in defending against cyberattacks and the robust switching control design to mitigate the impacts of attacks further. This methodology creates a defense-in-depth paradigm for the WES operators to maintain the energy system efficiency in the adversarial environment. This cross-layer design approach is also efficient and user-friendly for online implementation with the developed iterative algorithm. The simulated-based case studies in this paper show the effectiveness of the proposed approach. However, a more thorough validation of the method in practice is necessary before its integration with the production standard.
Variability and Source Characterization of Regional PM of Two Urban Areas Dominated by Biomass Burning and Anthropogenic Emission

Identifying the sources and formation pathways of particulate matter (PM) and its components is important to determine the impact of atmospheric aerosols on human health and the warming of the global atmosphere. Here, we characterized the variability of the eleven-year concentration and the origin of PM 2.5 in two urban regions (Metro Manila and Boracay) in the Philippines, a country in South East Asia (SEA) with high local anthropogenic emissions and frequently impacted by transboundary pollution. The surface concentration of PM 2.5 was analyzed using simulated and reanalyzed satellite data (MERRAero), complemented, and validated with filter measurements for PM 2.5 and black carbon (BC). The PM 2.5 masses in Metro Manila (12.3 ± 2.4 µ g m – 3 ) and Boracay (12.9 ± 3.6 µ g m – 3 ) were comparable yet with varying concentrations of aerosol components Anthropogenic related components of PM (organic carbon, sulfate, and BC) were more enhanced in the metropolis region (4.9 µ g m – 3 ) than in the prime tourist spot (2.72 µ g m – 3 ). Sulfate formation impacted the aerosol mass in Metro Manila, with the photochemical oxidation of SO 2 as the predominant production pathway of sulfates. Analysis of regional organic matter (OM) and BC in Boracay revealed extensive transboundary transport of biomass burning (BB) plumes from equatorial SEA countries. Also, the ratio of OM and SO 4 was utilized as a quick proxy for source characterization. Metro Manila and Boracay reported 0.77 ± 0.20 and 1.06 ± 0.55, highlighting the evident impact of traffic emissions in the PM mass in the metropolis region. For Boracay, the mixed contributions of BB and vehicular activities influenced the formation of PM. Overall, the reanalysis of satellite data captured the long-term variability and origins of surface PM in two vital urban regions in the Philippines. The utilization of MERRAero will be an important procedure in making regulatory decisions on regional pollution control.