Miracle-dz/UniFAR-FTUs huggingface dataset:
Advertisement Interval to Minimize Discovery Time of Whole BLE Advertisers

As the Internet of Things is expected to become pervasive in everyday life, it is also expected that numerous applications and services with a large number of bluetooth low energy (BLE) devices will be developed for areas such as sports arenas, subways, shopping malls, and many other busy public places. The fast discovery of all BLE advertisers is one of the most challenging tasks in supporting such a large number of BLE-enabled services successfully. However, there has been no research published so far that presents a method of setting parameters that provide the best performance in the BLE neighbor discovery process. In this paper, we propose a method to determine an optimal value for the BLE advertisement interval to minimize the time in which all surrounding BLE advertisers are discovered by a scanner. To obtain the optimal advertisement interval, we derive a new analytical model to characterize the BLE discovery time with all possible parameters. We also analyze the effect of the optimal advertisement interval on energy consumption. The analytical model is validated by comparing the analysis results with the simulations. The simulation results show that the optimal advertisement interval for a given number of BLE advertisers can minimize the discovery time, and the energy consumption also is reduced significantly.
Reliability of Oculometrics During a Mentally Demanding Task in Young and Old Adults

The sensitivity of oculometrics to the changes in mental load has already been investigated in several studies. However, the reliability of oculometrics remains unexplored, particularly under concurrent mental demands. To address this, we recruited 20 young and 18 elderly healthy adults to perform a functional computer task with three levels of mental load (i.e., low, medium, and high) on two days interspaced by at least seven days. We tracked the participants’ eye movements and pupil size during the task and computed the characterizing features of saccades, fixations, blinks, pupillary responses as well as nonlinear dynamics of pupillary responses and gaze trajectories. In addition, we recorded the trace of the computer mouse for performance measurement and acquired subjective ratings of the perceived task load. Among the investigated oculometrics, saccadic peak velocity (SPV) and its rate of changes across saccade amplitude (SVA) were influenced by the level of the task load in both the young and elderly adults, and the effects remained consistent across days. Reliability assessments revealed good to excellent test-retest reliability and acceptable absolute reliability in SPV, SVA, and the duration of fixations and saccades. The perceived load and task performance were monotonically altered with the task load levels. These findings may provide practical implications on mental load quantification in occupational fields.
Bicomponent nanofibrous scaffolds with dual release of anticancer drugs and biomacromolecules

Multifunctional scaffolds with dual release of small molecular drugs and biomacromolecules have potential in many applications such as cancer postoperative care, which require appropriate administration of anticancer drugs and biomacromolecules in a spatiotemporal manner. Herein, a systematic investigation into the dual release of anticancer drugs and biomacromolecules from the bicomponent nanofibrous scaffolds is performed. Their release behavior is affected by different fabrication techniques and different polymers used. We show that the bicomponent scaffold fabricated by dual-source dual-power emulsion electrospinning enables dual release of anticancer drugs and biomacromolecules in a controlled manner, holding promise for combinational cancer postoperative care.
A method for calculating the resonant frequency of meander line dipole antenna by using antenna's geometrical parameters

This paper presents the method for calculating the resonant frequency of Meander Line Dipole Antenna (MLDA) in the UHF frequency range. Two types of meander line antennas have been designed for passive RFID tag antennas. The design, analysis and characterization of the two proposed antennas are performed using simulation software FEKO. Two methods have been proposed to calculate the resonant frequency of a meander line dipole antenna by calculating its inductance. One method proposed by T. Endo and another method has been proposed in this paper and the proposed method contributes 90% as closely as desired. For example in MLDA-2 antenna the resonant frequency are 1.16 GHz and 1.01 GHz calculated by T. Endo and proposed method respectively when the no. of meander is 8. According to this method the resonant frequency and other antenna characteristics mainly depend upon the number of meander line, horizontal and vertical length, the separation of the twist arms, wire radius, total physical length and wire length of the antenna structure. The capacitance and inductance are introduced after squeezing the dipole antenna. The capacitance and inductance of the antenna are also a function of the antenna's shape and dimension. The resonant characteristics have been found by calculating their inductances and compared to the result from simulation software FEKO. The result showed a good agreement with the simulation.
Modeling the gate driver IC for GaN transistor: A black-box approach

During the switching performance evaluation for Si-based power devices, the gate driver IC's are commonly neglected because of Si device's slow switching speed. GaN transistors, with much smaller intrinsic capacitances, would enable faster switching speed and higher switching frequency. Consequently, the gate driver would largely impact the switching performance as well as the dead-time of the GaN transistor. In previous works, however, the gate driver IC used to drive GaN transistor have been ignored in circuit simulation, leading to lower modeling accuracy. In consideration of the lack of gate driver IC's critical design parameters, along with less familiarity of power electronics engineer/researcher with the semiconductor technologies, the gate driver IC could be regarded as a “black-box”. Despite the difficulty in directly performing measurements inside the driver chip package, a black-box modeling method could be proposed. Based on the measured terminal current/voltage signals in a typical gate drive scheme, the I-V characteristics of the PMOS in the totem-pole topology could be extracted. With respect to the C-V curves, the characteristics of a discrete Si MOSFET with comparable voltage/current rating could be introduced. Taking into account the operating principle of the totem-pole topology, a circuit-level model could be established. Consequently, the simulated waveforms are in reasonable agreements with the testing results. Taking advantages of the proposed black-box modeling method, the switching transient waveforms as well as the dead-time of GaN transistor could be more accurately evaluated.
2.20 Tbps hybrid O-OFDM WDM PON using direct detection technique

In this paper, 4-QAM architecture was developed where Optical-OFDM (O-OFDM) technique was used along with the incorporation of WDM, through which up to 40 channels were multiplexed each with 55 Gbps data speed. This paper investigates the system by evaluating the effect on OSNR, Error vector magnitude (EVM) and Power Loss in the network. It has been found from this architecture that sufficient power is received at the receiver side maintaining a low Bit error rate (BER), less than 10−3 according to IEEE standard. Through this endeavor, a PON with unprecedented capacity of 2.2 Tbps was created with a maximum transmission distance of 120km which is a very exceptional and noteworthy result for O-OFDM WDM PON, regarding both capacity and transmission distance.
Population Aging and Migrant Workers: Bottlenecks in Tuberculosis Control in Rural China

Background Tuberculosis is a serious global health problem. Its paradigms are shifting through time, especially in rapidly developing countries such as China. Health providers in China are at the forefront of the battle against tuberculosis; however, there are few empirical studies on health providers' perspectives on the challenges they face in tuberculosis control at the county level in China. This study was conducted among health providers to explore their experiences with tuberculosis control in order to identify bottlenecks and emerging challenges in controlling tuberculosis in rural China. Methods A qualitative approach was used. Semi-structured, in-depth interviews were conducted with 17 health providers working in various positions within the health system of one rural county (ZJG) of China. Data were analyzed based on thematic content analysis using MAXQDA 10 qualitative data analysis software. Results Health providers reported several problems in tuberculosis control in ZJG county. Migrant workers and the elderly were repeatedly documented as the main obstacles in effective tuberculosis control in the county. At a personal level, doctors showed their frustration with the lack of new drugs for treating tuberculosis patients, and their opinions varied regarding incentives for referring patients. Conclusion The results suggest that several problems still remain for controlling tuberculosis in rural China. Tuberculosis control efforts need to make reaching the most vulnerable populations a priority and encourage local health providers to adopt innovative practices in the local context based on national guidelines to achieve the best results. Considerable changes in China's National Tuberculosis Control Program are needed to tackle these emerging challenges faced by health workers at the county level.
Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation

Abstract. With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset.
Anomaly Detection Amidst Constant Anomalies: Training IDS On Constantly Attacked Data (CMU-CyLab-08-006)

Automated attack tools and the presence of a large number of untrained script kiddies has led to popular protocols such as SSH being constantly attacked by clumsy high-failure scans and bot harvesting attempts. These constant attacks result in a dearth of clean, attack-free network traffic logs, making training anomaly detectors for these protocols prohibitively difficult. We introduce a new filtering technique that we term attack reduction; attack reduction reduces the impact of these high-failure attacks on the traffic logs and can be used to extract a statistical model of normal activity without relying on prior assumptions about the volume of normal traffic. We demonstrate that a simple anomaly detection system (counting the number of hosts using SSH) trained on unfiltered data from our monitored network would fail to detect an attack involving 91,000 hosts; in contrast, it can be calibrated to detect attacks involving as few as 370 hosts using our attack reduction methodology. In addition, by using the same statistical model we use for filtering attacks, we estimate the required training time for an IDS and demonstrate that the system will be viable in as little as five hours.
Motivation to quit smoking and acceptability of shocking warnings on cigarette packages in Lebanon

Introduction Health warnings on tobacco packages have been considered an essential pillar in filling the gap of knowledge and communicating the health risks of tobacco use to consumers. Our primary objective was to report the perception of smokers on the textual health warnings already appearing on tobacco packages in Lebanon versus shocking pictures about the health-related smoking consequences and to evaluate their impact on smoking behaviors and motivation. Methods A pilot cross-sectional study was undertaken between 2013 and 2015 in five hospitals in Lebanon. Participants answered a questionnaire inquiring about sociodemographic characteristics, chronic respiratory symptoms, smoking behavior and motivation to quit smoking. Only-text warning versus shocking pictures was shown to the smokers during the interview. Results Exactly 66% of the participants reported that they thought shocking pictorial warnings would hypothetically be more effective tools to reduce/quit tobacco consumption compared to only textual warnings. Also, 31.9% of the smokers who were motivated to stop smoking reported that they actually had stopped smoking for at least 1 month secondary to the textual warnings effects. A higher motivation to quit cigarette smoking was seen among the following groups of smokers: males (odds ratio [OR] =1.8, P=0.02), who had stopped smoking for at least 1 month during the last year due to textual warning (OR =2.79, P<0.001), who considered it very important to report health warning on cigarette packs (OR =1.92, P=0.01), who had chronic expectoration (OR =1.81, P=0.06) and who would change their favorite cigarette pack if they found shocking images on the pack (OR =1.95, P=0.004). Conclusion Low-dependent smokers and highly motivated to quit smokers appeared to be more hypothetically susceptible to shocking pictorial warnings. Motivation to quit was associated with sensitivity to warnings, but not with the presence of all chronic respiratory symptoms.
Tweeting and Eating: The Effect of Links and Likes on Food-Hypersensitive Consumers’ Perceptions of Tweets

Moving on from literature that focuses on how consumers use social media and the benefits of organizations utilizing platforms for health and risk communication, this study explores how specific characteristics of tweets affect the way in which they are perceived. An online survey with 251 participants with self-reported food hypersensitivity (FH) took part in an online experiment to consider the impact of tweet characteristics on perceptions of source credibility, message credibility, persuasiveness, and intention to act upon the presented information. Positioning the research hypotheses within the framework of the Elaboration Likelihood Model and Uses and Gratifications Theory, the study explored motivations for using social media and tested the impact of the affordances of Twitter—(1) the inclusion of links and (2) the number of social validation indicators (likes and retweets). Having links accompanying tweets significantly increased ratings of the tweets’ message credibility, as well as persuasiveness of their content. Socially validated tweets had no effect on these same variables. Parents of FH children were found to utilize social media for social reasons more than hypersensitive adults; concern level surrounding a reaction did not appear to alter the level of use. Links were considered valuable in obtaining social media users to attend to useful or essential food health and risk information. Future research in this area can usefully consider the nature and the effects of social validation in relation to other social media platforms and with other groups.
Asymmetric Spatial Processing Under Cognitive Load

Spatial attention allows us to selectively process information within a certain location in space. Despite the vast literature on spatial attention, the effect of cognitive load on spatial processing is still not fully understood. In this study we added cognitive load to a spatial processing task, so as to see whether it would differentially impact upon the processing of visual information in the left versus the right hemispace. The main paradigm consisted of a detection task that was performed during the maintenance interval of a verbal working memory task. We found that increasing cognitive working memory load had a more negative impact on detecting targets presented on the left side compared to those on the right side. The strength of the load effect correlated with the strength of the interaction on an individual level. The implications of an asymmetric attentional bias with a relative disadvantage for the left (vs the right) hemispace under high verbal working memory (WM) load are discussed.
Overcoming the Loss of Performance in Unmanned Ground Vehicles Due to the Terrain Variability

Performance in autonomous driven vehicles is susceptible of degradation when traversing different terrains, thus needing motion controllers to be tuned for different terrain profiles. Such tuning stage is a time consuming process for the programmer or operator, and it is often based on intuition or heuristic approaches, and once tuned, the performance of the vehicle varies according to the terrain nature. In this context, we provide a visual based approach to identify terrain variability and its transitions, while observing and learning the performance of the vehicle using machine learning techniques. Based on the identified terrain and the knowledge regarding the performance of the vehicle, our system self-tunes the motion controller, in real time, to enhance its performance. In particular, the trajectory tracking errors are reduced, the control input effort is decreased, and the effects of the wheel-terrain interaction are mitigated preserving the system robustness. The tests were carried out by simulation and experimentation using a robotized commercial platform. Finally, implementation details and results are included in this paper, showing an enhancement in the motion performance up to 92.4% when the highest accuracy of the terrain classifier was 84.3%.
Evaluation of Annual Energy Loss Reduction Based on Reconfiguration Scheduling

In distribution network management, switch reconfiguration is an important tool for reducing energy loss. Recently, a variety of annual reconfiguration planning methods considering energy loss have been studied. However, no conventional methods address the reconfiguration periods in fine granularity. Practically, switch durability does not support high-frequency switching. Therefore, this paper proposes a new optimization method for annual reconfiguration scheduling. This method determines switch configurations and their reconfiguration periods with a constraint on the permissible reconfiguration times. In addition, this paper reveals the annual energy loss reduction effect of this optimization. Our method is based on partial network optimization with exhaustive enumeration of all feasible configurations. Experiments were conducted using a standard Japanese distribution network model with 468 switches. The results show that optimizing the reconfiguration periods reduces energy loss by up to 2.1 times, relative to that in a simulated conventional operation, which considers reconfiguration at equal intervals. We believe that this is the first quantitative report to address the difference between optimal reconfiguration scheduling and conventional reconfiguration.
Trehaloseaccumulation inAzospirillum brasilense improves droughttoleranceandbiomass inmaizeplants

Bacteria of the genus Azospirillum increase the grain yield of several grass crops. In this work the effect of inoculating maize plants with genetically engineered Azospirillum brasilense for trehalose biosynthesis was determined. Transformed bacteria with a plasmid harboring a trehalose biosynthesis gene-fusion from Saccharomyces cerevisiae were able to grow up to 0.5 M NaCl and to accumulate trehalose, whereas wild-type A. brasilense did not tolerate osmotic stress or accumulate significant levels of the disaccharide. Moreover, 85% of maize plants inoculated with transformed A. brasilense survived drought stress, in contrast with only 55% of plants inoculated with the wild-type strain. A 73% increase in biomass of maize plants inoculated with transformed A. brasilense compared with inoculation with the wild-type strain was found. In addition, there was a significant increase of leaf and root length in maize plants inoculated with transformed A. brasilense. Therefore, inoculation of maize plants with A. brasilense containing higher levels of trehalose confers drought tolerance and a significant increase in leaf and root biomass. This work opens the possibility that A. brasilense modified with a chimeric trehalose biosynthetic gene from yeast could increase the biomass, grain yield and stress tolerance in other relevant crops.
Design and test of the bidirectional solid-state switch for an 160kV/9kA hybrid DC circuit breaker

Solid-state switch is one of the key components of hybrid DC circuit breaker (HDCCB). This paper proposed a bidirectional solid-state switch which is composed of series-connected IGBTs and diode bridges. The solid-state switch has the advantages of low cost, low stray inductance and high turn-off capability, which forms an 160kV/9kA HDCCB together with ultra-fast mechanical switches (MS) and a current commutation drive circuit (CCDC). In this paper, the characteristics of press-pack IGBT, IEGT and IGCT are compared. The turn-off tests of IGBT and IEGT at over 10kA are held. A novel switching module (SM) based on IGBT, diode bridge and external snubber circuits is proposed in order to achieve bidirectional switching with low costs. The series-connected SMs are mounted in a special clamp assembly with high accuracy and uniform pressure distribution. The stray inductance, mechanical property and thermal resistance of the assembly are analyzed. A prototype of the HDCCB demonstrated a successful current interruption within 3 ms at 68.5 kV and 7.2 kA, which verifies the performance of the HDCCB.
Wired to the roots

Often, plant-pathogenic microbe interactions are discussed in a host-microbe two-component system, however very little is known about how the diversity of rhizospheric microbes that associate with plants affect host performance against pathogens. There are various studies, which specially direct the importance of induced systemic defense (ISR) response in plants interacting with beneficial rhizobacteria, yet we don’t know how rhizobacterial associations modulate plant physiology. In here, we highlight the many dimensions within which plant roots associate with beneficial microbes by regulating aboveground physiology. We review approaches to study the causes and consequences of plant root association with beneficial microbes on aboveground plant-pathogen interactions. The review provides the foundations for future investigations into the impact of the root beneficial microbial associations on plant performance and innate defense responses.