Miracle-dz/UniFAR-FTUs huggingface dataset:
Knowledge, attitude and practice on leptospirosis among undergraduate students in University Putra Malaysia

Introduction: Leptospirosis is an infectious and zoonotic disease caused by pathogenic bacteria called leptospires which can be transmitted through the exposure to the urine or excretion of infected animals, and also water or soil that being contaminated with secretion of the infected animals. Leptospirosis remains a concern in Malaysia, as the number of cases had steadily increased. This study aims to determine the knowledge, attitude and practice (KAP) among final year students of selected programmes in Universiti Putra Malaysia (UPM). Methods: A cross sectional study was conducted among students of Environmental and Occupational Health (ENVOCH) (57 students), Nursing (22 students) and Veterinary Medicine (97 students). Thus, the total sample sizes were 170, however the response rate were 81.76%. Questionnaire was used as the study instrumentation. Results: There was a significant association between race and knowledge, also gender and attitude with p<0.05, (p=0.008) and (p=0.001) respectively. Furthermore, there was also an association between attitude and practice (p<0.05). Meanwhile, there was a significant difference on the knowledge between students of ENVOCH with Veterinary Medicine and Nursing with Veterinary Medicine (p<0.05). Conclusion: Most of the final year students in this study had moderate level of KAP towards Leptospirosis disease. Thus, improvement in education and training must be done to face this issue.
New Far Eastern Policy: Institutions and Investments

Trends and possibilities for implementing the state economic policy of the Russian Far East's development are discussed. A historical overview is given with the identification of stages of regional development, characterizing by the different sources and scales of economic resources, in particular investments, and the types and degree of localization of specific economic institutions for the regional development. It is shown that the solution of of the region's economic development problem, uncompetitive from the point of view of standard market procedures but highly appreciated by utility from the point of view of national geostrategic and geoeconomic goals, is possible only if an effective combination of scales and sources of investment resources is found for the development of a region with adequate tasks type of institutional regime and with an optimal level of localization of institutions. Keywords— Far East, investments, economic development, institutions, integration, priorities.
A Novel Hybrid Five-Level Voltage-Source Converter Based on T-Type Topology for High-Efficiency Applications

A novel hybrid five-level voltage-source converter for high-efficiency applications is investigated in this paper. Compared with traditional multilevel converters, this hybrid multilevel converter generates desired staircase voltage levels with a reduced number of power devices and isolated drivers at higher voltage levels. It has redundant switching state combinations in hybrid multilevel converter, which makes it easy to balance flying capacitor voltages and realize fault-tolerant operation. A voltage-balancing control strategy based on switching state redundancies is presented for the hybrid multilevel converter to generate desired levels and also keep voltage balance of flying capacitors at the same time. The performance of the hybrid multilevel converter under various operating conditions is investigated in MATLAB/Simulink. The effectiveness of the proposed hybrid multilevel converter is validated by experiment results.
Nanonewton Force Sensing and Control in Microrobotic Cell Manipulation

Cellular force sensing and control techniques are capable of enhancing the dexterity and reliability of microrobotic cell manipulation systems. In this paper we present two experimental techniques for nanonewton force sensing and control in microrobotic cell manipulation. A vision-based cellular force sensing approach, including a microfabricated elastic cell holding device and a sub-pixel visual tracking algorithm, was developed for resolving forces down to 3.7 nN during microrobotic mouse embryo injection. The technique also experimentally demonstrated that the measured mechanical difference could be useful for in situ differentiation of healthy mouse embryos from those with compromised developmental competence without requiring a separate mechanical characterization process. Centered upon force-controlled microrobotic cell manipulation, this paper also presents nanonewton force-controlled micrograsping of interstitial cells using a microelectromechanical systems (MEMS)-based microgripper with integrated two-axis force feedback. On-chip force sensors are used for detecting contact between the microgripper and cells to be manipulated (resolution: 38.5 nN at 15Hz) and sensing gripping forces (resolution: 19.9 nN at 15Hz) during force-controlled grasping. The experimental results demonstrate that the microgripper and the control system are capable of rapid contact detection and reliable force-controlled micrograsping to accommodate variations in size and stiffness of cells with a high degree of reproducibility.
MLACE-MLFMA Combined With Reduced Basis Method for Efficient Wideband Electromagnetic Scattering From Metallic Targets

In this paper, a fast interpolation algorithm [multilevel accelerated Cartesian expansion (MLACE)-multilevel fast multipole algorithm (MLFMA)-reduced basis method (RBM)] is proposed for the first time by leveraging the benefits of the MLACE, the classical MLFMA, and the RBM; furthermore, a novel nonblind sampling method (NBSM) is proposed to approximate an orthogonal subspace for the MLACE-MLFMA-RBM. By integrating the empirical interpolation method (EIM) and the error-based compensation method (EBCM) into the NBSM, we first efficiently establish a robust and precision-controllable orthogonal subspace. Next, with the accurate orthogonal subspace, the MLACE-MLFMA-RBM can simplify the iterative solution process of the MLACE-MLFMA or the MLFMA into <inline-formula> <tex-math notation="LaTeX">$N_{\text {g}}$ </tex-math></inline-formula> matrix–vector multiplications (MVMs) and the solution of a reduced <inline-formula> <tex-math notation="LaTeX">$N_{\text {g}}$ </tex-math></inline-formula>-dimensional linear equation (<inline-formula> <tex-math notation="LaTeX">$N_{\text {g}}$ </tex-math></inline-formula> is the number of orthonormal vectors). Note that only the MVMs between the far-region impedance matrix and the orthogonal vector bases are calculated. In comparison with the classical MLACE-MLFMA and the MLACE-MLFMA-RBM based on different sampling methods for wideband electromagnetic (EM) responses, our proposed algorithms require less memory and CPU time and integrate higher flexibility. The numerical results are provided to demonstrate the accuracy, efficiency, and flexibility.
Avances en la búsqueda y desarrollo de quimioprofilácticos causales para malaria

La malaria es una enfermedad infecciosa de importancia epidemiologica mundial, producida por diferentes especies del genero Plasmodium. La quimioprofilaxis causal (QC) evita la infeccion y/o el desarrollo de las formas hepaticas de Plasmodium spp. Considerando recientemente la QC como una estrategia para reducir la carga de morbimortalidad en regiones endemicas para malaria, en el marco de programas para el control, la eliminacion o la posible erradicacion de la enfermedad, se hizo una revision no sistematica de la literatura para conocer el estado del avance de las investigaciones sobre quimioprofilacticos causales en modelos in vivo para malaria, para aportar al conocimiento, presentando un panorama actualizado sobre el tema, y llamar la atencion acerca de la importancia y la necesidad de nuevos medicamentos con efecto quimioprofilactico. Para ello, se consultaron las bases de datos: PubMed, ScienceDirect, Google Scholar y la pagina oficial de la Organizacion Mundial de la Salud (OMS), combinando los descriptores o palabras clave: chemoprophylaxis, quimioprofilaxis, malaria, Plasmodium e in vivo. Luego de revisar 33 articulos de la literatura mundial y 4 informes de la OMS, publicados entre los anos 1995 y 2015, se concluye que la molecula semisintetica NCP-tazopsina y las moleculas sinteticas: KAF156 (imidazolpiperazina) y tafenoquina (8 aminoquinolina), son los agentes QC mas promisorios en el momento. Estas moleculas pueden convertirse en una alternativa para el control de la malaria en un futuro cercano.
External Pressure, Corporate Governance, and Voluntary Carbon Disclosure: Evidence from China

This paper uses manually collected data of carbon information disclosure for listed companies, from 2009 to 2015 in China, to measure corporate carbon information disclosure, and it explores the impact of external pressure and internal governance on carbon information disclosure through text analysis and a hierarchy analysis process. The results show that, firstly, the greater the external pressure is, the higher the level of carbon information disclosure will be; that is, when listed companies are state-owned enterprises or in heavy pollution industries, the level of carbon information disclosure is higher. Secondly, the higher the level of corporate governance is, the higher the level of carbon information disclosure will be; that is, when the board of directors is larger, the proportion of independent directors is higher, and the chairman and general manager positions are differentiated, the level of carbon information disclosure is higher. Furthermore, when listed companies are state-owned and in heavy pollution industries, the level of carbon information disclosure is higher; when the chairman and general manager are in the same position (lower governance level), the positive impact of government pressure on carbon disclosure is less significant, the positive impact of external pressure on carbon disclosure is less significant, and the positive interactive impact of government pressure and external pressure on carbon disclosure is less significant. The conclusions of this paper are still robust after Heckman two-stage regression, propensity score matching (PSM) analysis, sub-sample regression, and double clustering analysis.
A feasibility study for a straightforward decoration of a 3D printing filament with graphene oxide

Abstract The modification of 3D printing filaments with specific compounds, especially nanomaterials, can be regarded as an effective approach for the fabrication of novel composite structures. For this aim, the interest for potential applications of graphene oxide is continuously growing thanks to its versatility in several technological fields ranging, e.g., from mechanical engineering and sensors development to bioengineering. The intrinsic properties of this 2D carbon nanomaterial joined to the potential of 3D printing can pave the way to different approaches for designing and manufacturing ad hoc components. The present study shows a straightforward method to cover a commercial polymeric filament with graphene oxide to be subsequently processed into a testing structure by fused deposition modeling. The experimental characterization was carried out to assess the reliability of the process with the aim to evaluate the presence, the role and the distribution of the graphene oxide on the polymeric surface.
Cost matters to small and medium enterprises: a study of Malaysia food and beverage manufacturing

This study examines the costs faced by small and medium enterprises (SMEs) involved in food and beverage manufacturing. It investigates the relationship between product value and the costs of producing packaging and related branding. The majority of SMEs in Malaysia have limited funds for product related expenditure. The results from the partial least squares structural equation model (PLS-SEM) show a strong mediation between packaging and branding expenditure towards product value. The food and beverage industries are highly competitive and need to be focused on in more depth. This study is potentially useful for future research directions on both theoretical and practical point of view.
Barriers Missouri's Farmers Face Regarding Beginning Farmer Government Programs

Federal and state governments have responded to the hardships beginning farmers and ranchers face by creating programs to mediate the identified challenges for new producers. However, hardships still exist for these producers and there is a lack of research on if the programs are providing the needed assistance to beginning farmers and ranchers. This research explores the perceived barriers to beginning farmer federal and state government programs for Missouri producers. Through the utilization of focus groups, the research identified major barriers such as: time, program awareness, program resources, and program requirements and eligibility. Aside from the barriers, the research also identified results in program positives and benefits. Altogether, the results of this research illustrate areas which could be improved and potential ways to improve the government programs, thus providing more and better opportunities for beginning farmers and ranchers.
Data Fusion in Sensor Networks

There is a growing excitement about the potential application of large scale sensor networks in diverse applications such as precision agriculture, geophysical and environment monitoring, remote health care, and security. Rapid progress in sensing hardware, communications and low-power computing has resulted in a profusion of commercially available sensor nodes. The big challenge now is to develop effective methods for the automatic fusion and interpretation of the information generated by large-scale sensor networks. The success of future applications is predicated on finding solutions to this data fusion challenge. This talk will focus on probabilistic models and Bayesian data fusion methods appropriate to describing and solving sensor network data fusion problems. Over a number of years, we have used such methods to develop decentralised algorithms for point-target estimation in sensor networks. More recently, other researchers have developed distributed Bayesian algorithms for sensor networks to estimate field properties, such as temperature or humidity over an area. The prospect of developing holistic Bayesian methods for fusion in sensor networks now looks to be a real and exciting possibility. This talk will describe these potential developments. Notions of divergence and information appear naturally in probabilistic fusion algorithms. In turn these provide a handle on two other sensor network data fusion problems; how to model and manage sensor node performance and how to learn patterns in or interpret sensor network information. These ideas will also be developed in this talk. Interspersed amongst these developments we will describe some real sensor network applications, some solved, some currently being addressed, and some that remain as a challenge to network data fusion methods.
INNOVACIÓN TECNOLÓGICA Y PRODUCTIVIDAD SECTORIAL EN LA ECONOMÍA MEXICANA: EVIDENCIA REGIONAL

This paper analyzes the effects to incorporate qualified manual labor in the productive processes, as well as the returns to the investment in the formation of manual labor qualified in the sectors of manufactures, commerce and services. For such effect, statistical data of the economic census of INEGI of years 1999 and 2004 are used. The use of data of cross section for a total of two thousand 438 municipalities allows to have a great number of observations, besides to this the disaggregation of the statistical information by economic sectors. Starting off of the estimation of a production function, the paper determines the elasticity of the product with respect to the factors of capital production and labor, as well as of the technological factor and the factor innovation. In one first approach to the data, the descriptive ones for the variables previously mentioned have been analyzed habitual statistical. Later, the estimation of a econometric model with data of cross section has taken place, for it, has been applied the method of weigthed square minimums. The reached empirical results are coherent with the theoretical expectations. They indicates that the investment in the capital human formation, the investment in the technological change and the own technological innovation, in the case of the three analyzed economic sectors, has a positive effect on productive process and in the greater one of the cases statistically significant.
ScriptProtect: Mitigating Unsafe Third-Party JavaScript Practices

The direct client-side inclusion of cross-origin JavaScript resources in Web applications is a pervasive practice to consume third-party services and to utilize externally provided libraries. The downside of this practice is that such external code runs in the same context and with the same privileges as the first-party code. Thus, all potential security problems in the code directly affect the including site. To explore this problem, we present an empirical study which shows that more than 25% of all sites affected by Client-Side Cross-Site Scripting are only vulnerable due to a flaw in the included third-party code. Motivated by this finding, we propose ScriptProtect, a non-intrusive transparent protective measure to address security issues introduced by external script resources. ScriptProtect automatically strips third-party code from the ability to conduct unsafe string-to-code conversions. Thus, it effectively removes the root-cause of Client-Side XSS without affecting first-party code in this respective. As ScriptProtect is realized through a light-weight JavaScript instrumentation, it does not require changes to the browser and only incurs a low runtime overhead of about 6%. We tested its compatibility on the Alexa Top 5,000 and found that 30% of these sites could benefit from ScriptProtect's protection today without changes to their application code.
Effective Approaches to Extract Features and Classify Echoes in Long Ultrasound Signals from Metal Shafts

A-scans from ultrasonic testing of long shafts are complex signals, thus the discrimination of different types of echoes is of importance for non-destructive testing and equipment maintenance. Research has focused on selecting features of physical significance or exploring classifier like Artificial Neural Networks and Support Vector Machines. This paper summarizes and reports on our comprehensive exploration on efficient feature extraction schemes and classifiers for shaft testing system and further on the diverse possibilities of heterogeneous and homogeneous ensembles.
A Novel L-Shaped RFID Tag Antenna

A novel RFID tag antenna is designed and its performance is verified with both simulated and experimental results. One of the limitations of the conventional RFID system is its orientation, which poses a technical challenge to its performance. We propose a dual-planar L-shaped RFID microstrip patch antenna, which is formed by folding a flat uni-planar rectangular microstrip patch with a 90deg bend. The proposed design is tested and is seen to remove the orientation sensitivity of the RFID tag antenna, giving a 3-dB beamwidth of 150 deg. The proposed design is chosen so that the antenna may be placed along any of the vertical edges of a pallet/box and there is no radiation back into the pallet/box on which it is fixed.
DC conduction and electrical breakdown of MgO/LDPE nanocomposite

To understand basic electric properties of nano-sized magnesium oxide (MgO)/low-density polyethylene (LDPE) nanocomposite under DC voltage application, the volume resistivity, the space charge distribution, the breakdown strength and the short circuit tree were investigated. By the addition of nano-sized MgO filler, both the DC breakdown strength and the volume resistivity of LDPE increased. At the average DC electric field of about 120 kV/mm, a positive packet-like space charge was observed in LDPE without MgO nano-filler, whereas a little homogeneous space charge was observed in MgO/LDPE nanocomposite material at the front of electrode. The initiation probability of short circuit tree is decreased by addition of MgO nano-filler. And also, the length of short-circuit tree in the film with MgO nano-filler is shorter than that without MgO nano-filler. From these results, it is confirmed that the addition of MgO nano-filler leads to the improvement of DC electrical insulating properties of LDPE.
Distributed match-making for processes in computer networks

In the very large multiprocessor systems and, on a grander scale, computer networks now emerging, processes are not tied to fixed processors but run on processors taken from a pool of processors. Processors are released when a process dies, migrates or when the process crashes. In distributed operating systems using the service concept, processes can be clients asking for a service, servers giving a service or both. Establishing communication between a process asking for a service and a process giving that service, without centralized control in a distributed environment with mobile processes, constitutes the problem of distributed match-making. Logically, such a match-making phase precedes routing in store-and-forward computer networks of this type. Algorithms for distributed match-making are developed and their complexity is investigated in terms of message passes and in terms of storage needed. The theoretical limitations of distributed match-making are established, and the techniques are applied to several network topologies.
Continuous robust fault‐tolerant control and vibration suppression for flexible spacecraft without angular velocity

The fault‐tolerant control and vibration suppression for flexible spacecraft without angular velocity measurement are investigated. External disturbances, actuator faults, unknown angular velocity, and flexible vibration are addressed simultaneously. Firstly, a model‐free adaptive supertwisting state observer and an angular velocity calculation algorithm in one step are developed by using attitude information only, which can estimate the angular velocity in finite time. Then, on the basis of angular velocity estimation, a novel continuous multivariable integral sliding mode (CMISM) is proposed for the first time, which is a combination of continuous nominal controller and a modified multivariable twisting controller to reject disturbances and faults. The CMISM can stabilize attitudes in finite time and attenuate chattering effectively. Furthermore, the input shaping technique is developed to achieve effective vibration suppression of the flexible appendages. Finally, the efficiency of the proposed method is illustrated by numerical simulations.
Optimal Configuration Analysis of AOA Localization and Optimal Heading Angles Generation Method for UAV Swarms

In this paper, the angle-of-arrival (AOA) measurements are adapted to locate a target using the UAV swarms equipped with passive receivers. The measurement noise is considered to be target-to-receiver distance dependent. The Cramer–Rao low bound (CRLB) of the AOA localization is calculated, and the optimal deployments are explored through changing angular separations and distances. Then, a distributed collaborative autonomous generation (DCAG) method is proposed based on the deep neural network (NN). The off-line training and on-line application rules are applied to generate the optimal heading angles for the UAV swarms in the AOA localization. The simulation results show that through the DCAG method, the generated heading angles for UAV swarms enhance the localization accuracy and stability.