Miracle-dz/UniFAR-FTUs huggingface dataset:
Work Engagement of Nursery School Nurses and Its Related Factors in Japan

Purpose: This study aimed to clarify nursery school nurses’ work engagement and their pertinent related factors. Method: We conducted a survey of 136 nursery school nurses using an anonymous, self-administered questionnaire. Questionnaires were distributed to 186 people at licensed daycare centers in Ibaraki Prefecture. The following conclusions were obtained by analyzing 136 participants, excluding deficiencies: A multiple regression analysis (forced entry method) was performed. Results: The survey results show that most of the nurses in the nursery school were female, about 90% were married, and about 70% had children. Work engagement was generally high compared with other occupations. Moreover, it was influenced by their work-self balance (positive), the meaning of their work, and the leadership of bosses. It was suggested that there is a need for an environment where nurses can maintain a work-life balance, a place where childcare health activities can be carried out, and opportunities to participate in training and liaison meetings for nursery nurses to further enhance work engagement. Conclusion: It was influenced by work self-balance (positive), the meaning of their work, and boss leadership. It is suggested that nursery nurses further enhance their work engagement, and they need an environment where they can maintain a work-life balance, a place where they can engage in health activities in childcare, and opportunities for training and liaison meetings.
In Search of a Model for Effective Group Projects: From the MPA Student Perspective

Abstract Group or team work has become a staple element of workplace environments, and research has indicated that groupwork imparts many benefits to employers and students/employees alike. In response, public affairs programs have increasingly incorporated group projects into the MPA learning experience, but insight into how students perceive team activities is limited.This article addresses that knowledge gap with an analysis of the experience of more than 100 students in diverse team class activities in a variety of courses at the University of Nebraska at Omaha.The analysis identifies the characteristics that make the team project experience more satisfying to students and therefore more effective and useful in future groupwork.
A Compact Ultra-Wideband Multimode Bandpass Filter With Sharp-Rejection Using Stepped Impedance Open Stub and Series Transformers

This brief presents the analysis and design of an ultra-wideband bandpass filter (UWBPF) with four transmission zeros and seven poles. The UWBPF model consists of series transformers, coupled lines, and a shunt-stepped impedance open stub. The even-odd mode analysis method and scattering parameters theory are used to extract the closed-form equations for transmission zeros and poles of the proposed UWBPF. For validation, a prototype with a center frequency of 2.49 GHz is designed, simulated, and tested. The measured 3 dB fractional bandwidth is 103.2%, and the fabricated prototype occupies an area of $0.165\lambda _{g}^{2}$ . The circuit, full-wave simulated, and experimental results are in a good match.
THRESHOLD EFFECT IN THE RELATIONSHIP BETWEEN INFLATION RATE AND ECONOMIC GROWTH IN INDONESIA

This paper investigated the linear and nonlinear relationships between inflation and economic growth in Indonesia using provincial data from 1994 to 2019. The linear model revealed that inflation has a significant negative effect on economic growth, while the nonlinear model revealed that inflation would negatively affect economic growth only after exceeding a threshold value of 9.59 percent. Excluding a high inflationarystructural break, we found an inflation threshold of 5.22 percent. Furthermore, we found that the threshold of inflation rate in the eastern regions of Indonesia was higher than that of the western regions, namely 9.64 percent and 5.75 percent, respectively. These findings have significant implications for inflation targeting and management both at the national and regional levels.
Joint-Space CPG for Safe Foothold Planning and Body Pose Control During Locomotion and Climbing

From insects to larger mammals, legged animals can be seen easily traversing a wide variety of challenging environments, by carefully selecting, reaching, and exploiting high-quality contacts with the terrain. In contrast, existing robotic foothold planning methods remain computationally expensive, often relying on exhaustive search and/or (often offline) optimization methods, thus limiting their adoption for real-life robotic deployments. In this work, we propose a low-cost, bio-inspired foothold planning method for legged robots, which replicates the mechanism of the central nervous system of legged mammals. We develop a low-level joint-space CPG model along with a high-level vision-based controller that can inexpensively predict future foothold locations and locally optimize them based on a potential field based approach. Specifically, by reasoning about the quality of ground contacts and the robot's stability through the high-level vision-based controller, our CPG model smoothly and iteratively updates relevant locomotion parameters to both optimize foothold locations and body pose, directly in the joint space of the robot for easier implementation. We experimentally validate our control model on a modular hexapod on various locomotion tasks in obstacle-rich environments as well as on stair climbing. Our results show that our method enables stabler and steadier locomotion than an open-loop CPG controller, yielding higher-quality feedback from onboard sensors by minimizing the effect of slippage and unexpected impacts.
Virtual/Augmented Reality for Rehabilitation Applications Using Electromyography as Control/Biofeedback: Systematic Literature Review

Virtual reality (VR) and augmented reality (AR) are engaging interfaces that can be of benefit for rehabilitation therapy. However, they are still not widely used, and the use of surface electromyography (sEMG) signals is not established for them. Our goal is to explore whether there is a standardized protocol towards therapeutic applications since there are not many methodological reviews that focus on sEMG control/feedback. A systematic literature review using the PRISMA (preferred reporting items for systematic reviews and meta-analyses) methodology is conducted. A Boolean search in databases was performed applying inclusion/exclusion criteria; articles older than 5 years and repeated were excluded. A total of 393 articles were selected for screening, of which 66.15% were excluded, 131 records were eligible, 69.46% use neither VR/AR interfaces nor sEMG control; 40 articles remained. Categories are, application: neurological motor rehabilitation (70%), prosthesis training (30%); processing algorithm: artificial intelligence (40%), direct control (20%); hardware: Myo Armband (22.5%), Delsys (10%), proprietary (17.5%); VR/AR interface: training scene model (25%), videogame (47.5%), first-person (20%). Finally, applications are focused on motor neurorehabilitation after stroke/amputation; however, there is no consensus regarding signal processing or classification criteria. Future work should deal with proposing guidelines to standardize these technologies for their adoption in clinical practice.
Analysis, Design, and Measurement of Directed-Beam Toroidal Waveguide-Based Leaky-Wave Antennas

Leaky-wave antennas (LWAs) have been widely investigated for wireless systems. Most LWAs reported to date are open-path based, i.e., their guided traveling waves follow a non-closed path. A substrate-integrated (SI) toroidal waveguide-based LWA is developed in this article. A coaxial-fed probe structure effectively excites traveling waves that propagate along a closed path in the toroidal waveguide. Inverted L- and planar helical-shaped radiators, whose pickup structures extract power from the waveguide through its top wall, are introduced to radiate, respectively, linearly-polarized (LP) and circularly-polarized (CP) directed beams. The dispersion properties of the closed waveguide’s traveling wave are determined and the associated propagation phase along circular paths with specific radii guides the placement of these radiators to achieve a directive beam at a specified angle. Prototypes of both the LP and CP toroidal LWA (TLWA) systems were fabricated and tested. Good agreement between the simulated and measured results was obtained. The measurements of the compact, low-cost LP and CP prototype systems confirm they radiate beams pointed in their distinctly different, specified directions with realized gains of 13.2 dBi and 13.9 dBic, respectively, at 9.75 GHz.
Isoperistaltic side-to-side anastomosis for the surgical treatment of Crohn disease

Purpose Increasing evidence has shown an association of surgical technique, particularly anastomotic configuration, with postoperative recurrence of CD. This pilot study aimed to evaluate short-term outcomes of isoperistaltic side-to-side anastomosis (ISSA) employed on Crohn disease (CD) patients. Methods Data were retrieved from a prospectively maintained database. Postoperatively, all patients were followed up with close endoscopic (ileocolonoscopy) surveillance. Results From January 2017 to May 2021, 30 patients diagnosed with CD who underwent ISSA were compared with 45 CD patients who underwent antiperistaltic side-to-side anastomosis (ASSA). The 2 groups were comparable in baseline demographics and clinical characteristics. No significant differences were observed between groups regarding postoperative safety issues, including anastomotic leak, abdominal/pelvic abscess, length of hospital stay, readmission rate within 30 days, etc. At postoperative 24th month, reduced endoscopic recurrence was observed in the ISSA group compared with that in the ASSA group (18 of 24, 75.0%, vs. 36 of 38, 94.7%; P = 0.024). Regarding surgical recurrence, there was 0% in the ISSA group vs. 4.4% (2 of 45) in the ASSA group (P = 0.510). Conclusion In this study, we aimed to explore the influence of ISSA on postoperative recurrence in CD patients, and the preliminary results show that ISSA was technically safe and feasible, and appears to be effective in reducing postoperative recurrence in CD patients. However, our conclusion was underpowered due to small sample size and inadequate follow-up. We proposed ISSA be considered as another alternative option in the toolbox of inflammatory bowel disease surgeons when performing anastomosis on CD patients.
POMDP Planning Under Object Composition Uncertainty: Application to Robotic Manipulation

Manipulating unknown objects in a cluttered environment is difficult because segmentation of the scene into objects, that is, object composition, is uncertain. Due to the uncertainty, prior work has either identified the “best” object composition and decided on manipulation actions accordingly or tried to greedily gather information about the “best” object composition. We instead, first, use different possible object compositions in planning, second, utilize object composition information provided by robot actions, third, consider the effect of competing object hypotheses on the desired task. We cast the manipulation planning problem as a partially observable Markov decision process (POMDP) that plans over possible object composition hypotheses. The POMDP chooses the action that maximizes long-term expected task-specific utility, and while doing so, considers informative actions and the effect of different object hypotheses on succeeding in the task. In simulation and physical robotic experiments, a probabilistic approach outperforms using the most likely object composition, and long term planning outperforms greedy decision making.
A sliding‐mode‐based active fault‐tolerant control for robust trajectory tracking in quad‐rotors under a rotor failure

In this article an active fault‐tolerant control (FTC) is developed for the tracking problem in a quad‐rotor under the effects of a rotor failure and external disturbances. Such a strategy is composed of a finite‐time sliding‐mode observer, which estimates the full state from the measurable output and identifies uniformly bounded and Lipschitz disturbances. The failure scenario is analyzed in order to identify how it affects the dynamics. It is assumed that the failure has been isolated. The FTC design is composed of PID and continuous high‐order sliding‐modes controllers that allow the yaw angular velocity to remain bounded and the position tracking to be achieved even in the presence of some external disturbances. The closed‐loop stability is formally proven. Numerical simulations show the performance of the proposed control strategy.
Deception Attack Detection and Resilient Control in Platoon of Smart Vehicles

Platooning of smart vehicles would be an important application of multi-agent systems. Each member of a multi-agent system is vulnerable to malicious attacks. Cyber attacks including deception attacks can inject false data into the information sent through the local feedback links of vehicles in the platoon. The attacked agents might deviate from the specified route in the group. Furthermore, due to the cooperation between agents, the effect of attack can snowball into other agents and destabilize the whole system. In this paper, a resilient vehicular control strategy is proposed against deception attack to retrieve the attacked agent to rejoin the platoon. Moreover, the detection of a vehicle under deception attack will be done by incorporating a high-gain observer. At the end, the case study demonstrates the capability of the proposed procedure.
Methane's Solar Radiative Forcing

Methane (CH4) has significant absorption bands at wavelengths of 1.7, 2.3, 3.3 and 7.6 μm which absorb incoming solar ‘shortwave’ (SW) radiation and contribute to radiative forcing (RF). A comprehensive quantification of CH4 SW RF is presented using a narrow‐band radiative transfer model to calculate spatially and monthly resolved estimates of CH4 SW RF and its impact on longwave (LW) stratospheric temperature adjusted RF (SARF). These new calculations include satellite measurements of CH4 distribution and spectrally varying surface albedo, and include absorption of solar mid‐infrared radiation by methane's 7.6 μm band. These factors substantially influence methane's SW effect. For a 750–1,800 ppb perturbation, the all‐sky top‐of‐atmosphere SW instantaneous RF is 0.082 W m−2; at the tropopause it is 0.002 W m−2, considerably smaller than previous estimates. Including the impact of SW absorption on stratospheric temperature increases tropopause SARF by 0.039 W m−2 (or 7%) compared to the LW‐only SARF.
Algorithmic Interactions in Open Source Work

This study focuses on algorithmic interactions in open source work. Algorithms are essential in open source because they remedy concerns incompletely addressed by parallel development or modularity. Following algorithmic interactions in open source allows us to map the operational performance of algorithms to understand how algorithms work with multiple other algorithms to accomplish work. Studying algorithms working together shows us how residual interdependencies of modularity and problems not resolved by dependence on parallel development are worked around to perform open source work. We examine the Linux Kernel case that reveals how algorithmic interactions facilitate open source work through the three processes of managing, organizing, and supervising development work. Our qualitative study theorizes how algorithmic interactions intensify through these processes that work together to facilitate development. We make a theoretical contribution to open source scholarship by explaining how algorithmic interactions navigate across module rigidity and enhance parallel development. Our work also reveals how, in open source, developers work to automate most tasks and augmentation is a bidirectional relationship of algorithms augmenting the work of developers and of developers augmenting the work of algorithms.
Riemannian statistics geometry: A counterpart approach of inference geometry

Riemannian statistics geometry is proposed in this work as a counterpart approach of inference geometry. This geometry framework is inspired on the existence of a notable analogy between the general theorems of inference theory and the the general fluctuation theorems associated with a parametric family of distribution functions $dp(I|\theta)$, which describes the stochastic behavior of a set of continuous stochastic variables driven by a set of control parameters $\theta$. In this approach, statistical properties are rephrased as purely geometric notions derived from the Riemannian structure on the manifold $\mathcal{M}_{\theta}$ of stochastic variables $I$. Consequently, this theory arises as an alternative framework for applying the powerful methods of differential geometry for the statistical analysis.
A 108-nW 0.8-mm2 Analog Voice Activity Detector Featuring a Time-Domain CNN With Sparsity-Aware Computation and Sparsified Quantization in 28-nm CMOS

This article reports a passive analog feature extractor for realizing an area-and-power-efficient voice activity detector (VAD) for voice-control edge devices. It features a switched-capacitor circuit as the time-domain convolutional neural network (TD-CNN) that extracts the 1-bit features for the subsequent binarized neural network (BNN) classifier. TD-CNN also allows area savings and low latency by evaluating the features temporally. The applied sparsity-aware computation (SAC) and sparsified quantization (SQ) aid in enlarging the output swing and reducing the model size without sacrificing the classification accuracy. With these techniques, the diversified output also aids in desensitizing the 1-bit quantizer from the offset and noise. The TD-CNN and BNN are trained as a single network to improve the VAD reconfigurability. Benchmarking with the prior art, our VAD in 28-nm CMOS scores a 90% (94%) speech (non-speech) hit rate on the TIMIT dataset with small power (108 nW) and area (0.8 mm2). We can configure the TD-CNN as a feature extractor for keyword spotting (KWS). It achieves a 93.5% KWS accuracy with the Google speech command dataset (two keywords). With two TD-CNNs operating simultaneously to extract more features, the KWS accuracy is 94.3%.
The Influence Mechanism of Education on Health from the Sustainable Development Perspective

Good health and quality education are two important goals of the Sustainable Development Goals (SDGs). More and more people pay attention to physical and mental health in a pandemic age. Previous studies have paid more attention to the relationship between socioeconomic status and health, and also scholars at home and abroad have not reached a consistent conclusion on how education affects health. In this study, we try to explore the relationship between education and health from the sustainable development perspective and its internal influence mechanism through the data of China General Social Survey (CGSS) in 2015 and 2017, according to Grossman's health demand model. The results indicated that from the junior high school education, physical health improved with the increase of the education level, but this effect was gradually weakened. The relationship between education and mental health is not a simple linear relationship but an inverted U-shaped change. After 16 years of education, mental health gradually decreases. Compared with women and rural population, men and urban population have better health. Education leads to labor market segmentation, which makes people with different education levels in different social structure positions, resulting in differentiation of lifestyles, psychology, and social interaction, and this ultimately leads to health inequality. Education indirectly improves people's health by changing healthy behaviors, cultivating healthy psychology, and strengthening social interactions.
Alternatives to external polarization source for dielectric elastomer generators: electrets versus piezoelectric materials

Among the different technologies for kinetic energy harvesting, dielectric elastomers generators (DEGs) may represent a promising solution for supplying power to wearable low power consumption sensors and devices. These electrostatic generators provide a low-cost and lightweight solution to harvest high electrical energy densities from the mechanical deformation of an elastomeric membrane. The main disadvantage of these structures is the need of an external high voltage supply to perform the energetic cycle. In order to overcome this limitation and have a completely autonomous energy scavenger, our research group has been working since 2012, on coupling dielectric elastomers with electret materials (i.e. insulator materials that can hold a permanent electric charge over a long period of time). In the present work, a new hybrid solution for wearable energy harvesters based on DEG will be presented. This new autonomous device is based on the combination of a DEG with a piezoelectric material, which is used as new polarization source for the DEG energetic cycle. The working principle and the first results obtained on this new prototype are presented and a comparison between the two polarization solutions (electret and piezoelectric materials) is discussed.
Detecting Impersonation Attacks in a Static WSN

The current state of security found in the IoT domain is highly ﬂawed, a major problem being that the cryptographic keys used for authentication can be easily extracted and thus enable a myriad of impersonation attacks. In this MSc thesis a study is done of an authentication mechanism called device ﬁngerprinting. It is a mechanism which can derive the identity of a device without relying on device identity credentials and thus detect credential-based impersonation attacks. A proof of concept has been produced to showcase how a ﬁngerprinting system can be designed to function in a resource constrained IoT environment. A novel approach has been taken where several ﬁngerprinting techniques have been combined through machine learning to improve the system’s ability to deduce the identity of a device. The proof of concept yields high performant results, indicating that ﬁngerprinting techniques are a viable approach to achieve security in an IoT system. (Less)
Novel High-Step-Up/Step-Down Three-Port Bidirectional DC/DC Converter for Photovoltaic Systems

This paper presents a novel three-port high-step-up/step-down bidirectional DC/DC converter with a coupled inductor for photovoltaic (PV) systems. The proposed converter combines a high-step-up converter, which is used to step-up the PV module to DC bus 200 V, and a battery charge/discharge bidirectional converter to form a three-port bidirectional converter. When sufficient energy is supplied from the PV modules, the converter can step-up the output of the PV modules and provide energy to the DC bus while charging the battery simultaneously. However, when no energy is supplied from the PV modules, the DC bus voltage is provided by the battery. Moreover, the energy stored in the leakage inductor is recycled to the DC-blocking capacitor, and synchronous rectification is conducted in the switch during the step-up mode to reduce switch loss and thereby increase the system’s overall efficiency. Finally, a 500 W three-port bidirectional converter is implemented to verify the feasibility and practicability of the proposed converter. The maximum efficiency of the proposed converter is 95.4%, 94.3%, and 94.7% when operated in the high-step-up mode, battery step-up mode, and step-down mode for the PV modules, respectively.