Miracle-dz/UniFAR-FTUs huggingface dataset:
Intensive and extensive rice farm adaptations in salinity-prone areas of the Mekong Delta

ABSTRACT Sea-level rise and resulting salinity inundation are making many coastal areas increasingly unfavorable for rice production. This paper examines intensive and extensive adaptations to rice production in salinity-prone areas of the Mekong River Delta (MKD) of Vietnam using a two-year panel dataset of 788 rice-growing households. In terms of intensive adaptations, we estimate a fixed-effect regression model and find that salinity tolerant rice varieties (STVs) increase rice yields on fields that are not protected by salinity barriers, but overall economic benefits from STVs are limited by lower market prices compared to other varieties. In terms of extensive adaptations, farmers stop growing rice on 15% of survey fields. Probit and IV-probit model results reveal that falling rice profitability plays a significant role in these observed exits from rice production, while salinity barrier infrastructure, large rice field holdings, and community commitment to rice farming are associated with continued rice production. Development initiatives that support household adaptation to sea-level rise need to blend currently polarized policy options of investment in large rice sector infrastructure projects that lock farmers into intensive rice cultivation and of support farmer efforts to find alternative land uses in response to evolving market and environmental conditions.
Conception of a Mixed Reality Eyesight Training System Based on the Parallel Robot

Diseases of the human visual system occupy a significant part of the total number of illnesses. Exercising the motor muscles of the eyes is one of the most effective methods of combating certain diseases of the human visual system. The paper considers the concept of a mixed reality training system using a parallel mechanism for vision training tasks. The block diagram of the system is given, its main components are described (including input unit, control unit, reprojection unit, sensor unit), as well as the principle of its operation. The full-scale assembling of the parallel manipulator has been accomplished. Other mechanisms can also be used as a manipulator. The elements of such a system were tested, namely, the registration of depth information, segmentation of the significant planes, etc. Based on this, environmental modeling was carried out. The proposed concept of a mixed reality simulator can be widely applied in various medical institutions.
ASC-J9 Blocks Cell Proliferation and Extracellular Matrix Production of Keloid Fibroblasts through Inhibiting STAT3 Signaling

Keloids are a fibrotic skin disorder caused by abnormal wound healing and featuring the activation and expansion of fibroblasts beyond the original wound margin. Signal transducer and activator of transcription 3 (STAT3) has been found to mediate the biological functions of keloid fibroblasts (KFs). Therefore, we aimed to demonstrate whether ASC-J9, an inhibitor of STAT3 phosphorylation, can suppress the activation of KFs. Western blotting results showed that ASC-J9 inhibited the levels of COL1A1 and FN1 proteins, which were upregulated in KFs, by decreasing the expression of pSTAT3 and STAT3. RNA sequencing and in vitro studies further demonstrated that ASC-J9 treatment of KFs reduced cell division, inflammation, and ROS generation, as well as extracellular matrix (ECM) synthesis. ELISA assays verified that ASC-J9 treatment significantly mitigated IL-6 protein secretion in KFs. Transmission electron microscopy images revealed that ASC-J9 induced the formation of multilamellar bodies in KFs, which is associated with autophagy-related signaling. These results suggested that inhibiting a vicious cycle of the ROS/STAT3/IL-6 axis by ASC-J9 may represent a potential therapeutic approach to suppress cell proliferation and ECM production in KFs.
Developing high performance Q‐band planar filters using the multilayered substrate integrated waveguide technique

In this article, a novel planar multilayer Q‐band band‐pass filter is presented by cascading a low‐pass filter (LPF)and a high‐pass filter (HPF). The HPF is designed by utilizing the high‐pass behavior of the substrate integrated waveguide, and the LPF is realized by using millimeter‐wave lump‐element resonators. Since the insertion loss resulted by the millimeter‐wave planar resonators, which resonate in‐band and have a limited quality factor, is avoided by using the cascaded high‐/low‐pass architecture, the proposed filter has a small insertion loss. Moreover, a flexible bandwidth can be achieved by properly adjusting the cutoff frequencies of the HPF and LPF. As a demonstration, a band‐pass filter having a center frequency of 42.5 GHz and a fractional bandwidth of 11.76% is designed, fabricated, and measured. Good agreement is obtained between simulated and measured results. © 2017 Wiley Periodicals, Inc. Microwave Opt Technol Lett 59:698–703, 2017
Dysmaturational Longitudinal Epigenetic Aging During Transition To Psychosis

Psychosis frequently occurs during adolescence and young adulthood, possibly as a result of gene-environment interactions, mediated by epigenetic mechanisms such as DNA methylation. Methylation patterns can be leveraged to predict epigenetic age in order to identify anomalies in aging trajectories that may be associated with the emergence of psychosis. Thus, epigenetic age may provide a measurable surrogate of psychotic risk or psychosis’ emergence, and shed light on the neurodevelopmental model of psychosis. In this study, we present the first longitudinal analysis of epigenetic age trajectory during conversion to psychosis in a population at ultra-high-risk, with available genome-wide methylation DNA at two time points, at baseline and after one year of follow-up (N = 38 x 2). After predicting epigenetic age, we computed epigenetic age gap as the cross-sectional difference between real age and predicted age, and (longitudinal) epigenetic age acceleration as the derivative of predicted age with respect to time. At baseline, future converters were 2.7 years younger than non-converters and this difference disappeared at follow-up, when some converted to psychosis. This is because during conversion to psychosis, the epigenetic age of converters accelerated by 2.8 years/year compared to non-converters. This acceleration was robust with a strictly positive 95% confidence interval, and held its significance after adjustment for age, sex, and cannabis intake. The methylation sites most associated with aging were on genes also linked with schizophrenia and neurodevelopmental disorders. This accelerated age trajectory, following a previous deceleration, may therefore reflect dysmaturational processes.
The Influence of Wearables on Health Care Outcomes in Chronic Disease: Systematic Review

Background Chronic diseases contribute to high rates of disability and mortality. Patient engagement in chronic disease self-management is an essential component of chronic disease models of health care. Wearables provide patient-centered health data in real time, which can help inform self-management decision-making. Despite the perceived benefits of wearables in improving chronic disease self-management, their influence on health care outcomes remains poorly understood. Objective This review aimed to examine the influence of wearables on health care outcomes in individuals with chronic diseases through a systematic review of the literature. Methods A narrative systematic review was conducted by searching 6 databases for randomized and observational studies published between January 1, 2016, and July 1, 2021, that included the use of a wearable intervention in a chronic disease group to assess its impact on a predefined outcome measure. These outcomes were defined as any influence on the patient or clinician experience, cost-effectiveness, or health care outcomes as a result of the wearable intervention. Data from the included studies were extracted based on 6 key themes, which formed the basis for a narrative qualitative synthesis. All outcomes were mapped against each component of the Quadruple Aim of health care. The guidelines of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement were followed in this study. Results A total of 30 articles were included; studies reported 2446 participants (mean age: range 10.1-74.4 years), and the influence of 14 types of wearables on 18 chronic diseases was presented. The most studied chronic diseases were type 2 diabetes (4/30, 13%), Parkinson disease (3/30, 10%), and chronic lower back pain (3/30, 10%). The results were mixed when assessing the impact on a predefined primary outcome, with 50% (15/30) of studies finding a positive influence on the studied outcome and 50% (15/30) demonstrating a nil effect. There was a positive effect of 3D virtual reality systems on chronic pain in 7% (2/30) of studies that evaluated 2 distinct chronic pain syndromes. Mixed results were observed in influencing exercise capacity; weight; and biomarkers of disease, such as hemoglobin A1c, in diabetes. In total, 155 outcomes were studied. Most (139/155, 89.7%) addressed the health care outcomes component. This included pain (11/155, 7.5%), quality of life (7/155, 4.8%), and physical function (5/155, 3.4%). Approximately 7.7% (12/155) of outcome measures represented the patient experience component, with 1.3% (2/155) addressing the clinician experience and cost. Conclusions Given their popularity and capability, wearables may play an integral role in chronic disease management. However, further research is required to generate a strong evidence base for safe and effective implementation. Trial Registration PROSPERO International Prospective Register of Systematic Reviews CRD42021244562; https://www.crd. york.ac. uk/prospero/display_record. php? RecordID=244562
An Approach for Recognizing Two-Human Interactions Using Channel State Information

A new channel state information (CSI)-based approach for recognizing two-human interactions, which are ac-tivities that involve two humans, is presented in this paper. The proposed approach consists of three phases. Specifically, in the first phase, we utilize the principle component analysis transformation to reduce the dimensionality of the CSI data and produce a set of principal components that can explain the variance within the CSI data. In the second phase, we extract 17 time- and frequency-domain features from the computed principal components obtained from the first phase. Furthermore, the minimum redundancy maximum relevance algorithm is applied to select a subset of the extracted features. Finally, in the third phase, we use the selected features to build a set of support vector machine classifiers to recognize the performed two-human interactions. A publicly available CSI dataset, which includes CSI signals that were acquired from 40 pairs of subjects while executing 13 two-human interactions, was used to assess the performance of our proposed approach. The average accuracy achieved by our proposed approach was 86.21%. Moreover, the reported results illustrate the efficacy of our proposed approach to accurately recognize various two-human interactions.
Energy Capture Optimization for an Adaptive Wave Energy Converter

Wave energy has great potential as a renewable energy source, and can therefore contribute significantly to the proportion of renewable energy in the global energy mix. This is especially important since energy mixes with high renewable penetration have become a worldwide priority. One solution to facilitate such goals is to harvest the latent untapped energy of the ocean waves and convert it into electrical energy. A device performing such a task is known as a wave energy converter (WEC). In the present work, we focus on a specific type of WEC, which has the advantages of both significant energy storage capabilities, and adaptability to extract energy from the whole spectrum of ocean waves. This WEC consists of an array of point absorber devices, comprising adaptable piston-type hydraulic pumps powered by interconnected floaters, whose target is to extract optimally the energy from waves of varying heights and periods. Two different cases are considered in this paper; namely, the analysis of the energy extraction in a simplified floater blanket, and a model predictive control strategy to maximize the extracted energy of the WEC.
Usage of E-Technologies for Development Financial and Economic Potential of United Territorial Communities

The current directions of development of financial and economic potential on the example of united territorial communities of one region through the introduction of electronic technologies to select a promising area of development and create favorable conditions for modern business communications. The criteria for this selection are proposed and an expert evaluation is conducted to obtain the results of the study in Decision Making Helper©. The priority of small business in the financial and economic development of the region has been established on the example of four united territorial communities. The problems of small business development are identified and the introduction of the newest approaches to the organization of activity of united territorial communities in the system of infocommunication «community-business-power» with establishment of their priority is offered. Relevant recommendations for the application of algorithms for the development of small business to determine the priority area in various fields, which allowed to form the author's vision of solving problems based on the software used to acquire new competencies by potential users.
Codebook Design and Beam Training for Intelligent Omni-Surface Aided Communications

Recently, the intelligent omni-surface (IOS) has been proposed as a novel instance of metasurface to achieve full-dimensional communications by jointly engineering its reflective and refractive properties. However, optimal beamforming scheme for the IOS is hard to obtain due to the difficulty in acquiring perfect channel state information (CSI). To address this issue, in this paper, we consider an IOS aided system where the beamforming scheme is designed via beam training with codebooks at the base station (BS), the IOS, and users. Given that the refractive/reflective signals are closely related to both incident signals from the BS and phase shifts of IOS elements, the codebooks at the BS and the IOS are designed jointly. Based on the joint BS-IOS codebook, a multi-lobe beam training mechanism is proposed to perform beam training for multiple users simultaneously, thereby reducing the training overhead. Simulation results indicate that our proposed scheme achieves a higher sum rate than the state-of-the-art beam training schemes and performs close to the perfect CSI case.
Slicing Wi-Fi Networks for Differentiated IoT Service Provisioning

Network slicing is among the most wanted features of the 5G to address the diverse requirements of different classes of services, such as IoT applications. However, bringing the slicing to Wi-Fi networks is very challenging due to the lack of wireless virtualization supports in hardware. This paper proposes a new approach to achieve network slicing in Enterprise WiFi without virtualization techniques. Our approach is based on the dynamic association of user equipment to Wi-Fi access points to meet the requirements of differentiated IoT services. We model this technique as an optimization problem with the objective of maximizing the total throughput of the network while meeting the differentiated IoT service requirements. A heuristic algorithm based on the stable matching mechanism has been proposed to solve the optimization problem in near real-time. Furthermore, to enable a practical implementation, we advocate an online algorithm based on Reinforcement Learning which can mitigate the calculation in each time slot as done by the matching algorithm. Simulation results show that our solutions achieve the total throughput approximately to the optimum one and outperform the traditional RSSI method while guaranteeing the IoT slicing service requirements.
Determination of the uncertainty of the measurements performed by coordinate measuring machines

Abstract Today many different systems are working in accordance with the idea of coordinate measuring techniques. It is possible to use the same measuring software with optical or contact coordinate systems as well as with a 3D scanners. This gives the opportunity to use different measuring systems for the same tasks. Consequently, it is possible to build faster and more efficient techniques for controlling the production. For example: a fast check of car body production with 3D scanner systems and once per shift accurate measurement of the same element with reference Coordinate Measuring Machines. The main purpose of measurements in industry is the assessment of the conformity or nonconformity of the production with the specification. The specification can be written in classical paper documentation or saved in CAD-file. Never-mind how specification is written or saved, the uncertainty of the measurement should be taken into consideration, according to the ISO 14253-1 guideline. In the case of a supplier – to his benefit, by extending the area of conformity and in the case of production control – by reducing the area of conformity. Evaluation of the coordinate measurement accuracy is very complicated task, especially elaborating of one method for all Coordinate Measuring Systems. Until now, majority of methods focus only on the Coordinate Measuring Machines. ISO 15530 family of standards can be noticed in this area, however, many problems still remain unsolved.
Incorporating business process reengineering (bpr) into information system (is) development: case study at Universiti Teknologi Malaysia (UTM)

Information System (IS)/Information Technology (IT) is playing crucial role in the business world. There is numerous success stories demonstrate that IS/IT have high potential Business Process Reengineering (BPR). BPR concept is used in the organization to stay and enhance competitiveness. It is said that IS/IT is the enabler to the BPR and cannot be integrated due to different perspective. However, BPR method and IS development lifecycle shared some elements that can incorporate the BPR method into IS development environment. Realizing the elements in BPR method can be incorporated into IS development, this article proposes the new framework model that will be implemented in the Study Leave System (SLS) in Universiti teknologi Malaysia (UTM). SLS is a progress report system for staff that further study to improve teaching skills. However, the system needs to improve due to some problems faced by the staff such as repetitive notification, misunderstand the flow of the system, lack of login page, lack of status of progress report page and lack of viewing the previous progress report. In order to solve the problem, the new framework will be used as the guideline to improve the SLS and to proof that some of the element in BPR method can be integrated into the IS development. This paper examines how BPR method can be incorporated into IS development environment through a review of relevant literature.
Autonomous Goal-Based Mapping and Navigation Using a Ground Robot

Autonomous Goal-Based Mapping and Navigation Using a Ground Robot Jeffrey L. Ferrin Department of Mechanical Engineering, BYU Doctor of Philosophy Ground robotic vehicles are used in many different applications. Many of these uses include tele-operation of the robot. This allows the robot to be deployed in locations that are too difficult or are unsafe for human access. The ability of a ground robot to autonomously navigate to a desired location without a-priori map information and without using GPS would allow robotic vehicles to be used in many of these situations and would free the operator to focus on other more important tasks. The purpose of this research is to develop algorithms that enable a ground robot to autonomously navigate to a user-selected location. The goal is selected from a video feed from the robot and the robot drives to the goal location while avoiding obstacles. The method uses a monocular camera for measuring the locations of the goal and landmarks. The method is validated in simulation and through experiments on an iRobot Packbot platform. A novel goal-based robocentric mapping algorithm is derived in Chapter 3. This map is created using an extended Kalman filter (EKF) by tracking the position of the goal along with other available landmarks surrounding the robot as it drives towards the goal. The mapping is robocentric, meaning that the map is a local map created in the robot-body frame. A unique state definition of the goal states and additional landmarks is presented that improves the estimate of the goal location. An improved 3D model is derived and used to allow the robot to drive on nonflat terrain while calculating the position of the goal and other landmarks. The observability and consistency of the proposed method are shown in Chapter 4. The visual tracking algorithm is explained in Chapter 5. This tracker is used with the EKF to improve tracking performance and to allow the objects to be tracked even after leaving the camera field of view for significant periods of time. This problem presents a difficult challenge for visual tracking because of the drastic change in size of the goal object as the robot approaches the goal. The tracking method is validated through experiments in real-world scenarios. The method of planning and control is derived in Chapter 6. A Model Predictive Control (MPC) formulation is designed that explicitly handles the sensor constraints of a monocular camera that is rigidly mounted to the vehicle. The MPC uses an observability-based cost function to drive the robot along a path that minimizes the position error of the goal in the robot-body frame. The MPC algorithm also avoids obstacles while driving to the goal. The conditions are explained that guarantee the robot will arrive within some specified distance of the goal. The entire system is implemented on an iRobot Packbot and experiments are conducted and presented in Chapter 7. The methods described in this work are shown to work on actual hardware allowing the robot to arrive at a user-selected goal in real-world scenarios.
SURVEY AND PROSPECTS OF ARDUINO NANO 3.0 PLATFORM USE IN HIGH SCHOOL

The article represents hardware opportunities, advantages and specification of Arduino platform. The author gives functional characteristics of the main accessory boards which are used for functional improving. The comparative analysis of the most popular Arduino platforms is made. The perspectives of this tool implementation are defined. The article points out functional description and engineering specification by the example of Arduino Nano 3.0 platform. The author describes the advantages of Arduino Nano 3.0 platform in comparison with other controllers. ArduinoIDE software is explored. The prospects of the use of microprocessor board in teaching and learning activities are evaluated.