bluuebunny/crossref_metadata_2025 huggingface dataset:
Microstructural Evolution of Cold-Rolled AA7075 Sheet during Solution Treatment
Authors: Wang Lu , Yang Xiaofang , Robson Joseph D. , Sanders Robert E. , Liu Qing
Published: June 2020

The influence of heating rate on the microstructural evolution of a cold-rolled AA7075 alloy sheet during solution heat treatment was examined using electrical conductivity, scanning electron microscopy, X-ray diffraction, transmission electron microscopy and electron backscatter diffraction. The results indicate that the dissolution of soluble phases takes place during the heating process. The heating rates affect the dissolution process of soluble phases, and these phases completely dissolve into matrix after solution treatment. Recrystallized and elongated grains are produced after solution treatment by both fast and slow heating rates, while the grains of the rapidly heated sample are much finer. The elongated grains are attributed to the difference in the pinning pressure of boundary migration between the rolling and normal directions. The {111}<110> texture, as well as typical recrystallization textures, were found in both fast and slowly heated samples after solution treatment, but the textures, especially the {111}<110> component in the slow-heated sample, are much stronger, leading to an anisotropy in the tensile properties after artificial aging.
Measuring Heat Production from Burning Al/Zr and Al/Mg/Zr Composite Particles in a Custom Micro-Bomb Calorimeter
Authors: Wainwright Elliot R. , Mueller Madeline A. , Overdeep Kyle R. , Vummidi Lakshman Shashank , Weihs Timothy P.
Published: June 2020

Al:Zr, Al-8Mg:Zr, and Al-38Mg:Zr nanocomposite particles fabricated by physical vapor deposition (PVD) and ball milling were reacted in 1 atm of pure O2 within a custom, highly-sensitive micro-bomb calorimeter. The heats of combustion were compared to examine the effect of particle size and composition on combustion efficiency under room temperature and in a fixed volume. All particles yielded ~60–70% of their theoretical maximum heat of combustion and exhibited an increase in heat over composite thin films of similar compositions, which is attributed to an increase in the surface area to volume ratio. The effect of particle size and geometry are mitigated owing to the sintering of the particles within the crucible, implying the importance of particle dispersion for enhanced performance. Vaporization of the metal species may transition between two diffusion flame species (Mg to Al). As Mg content is increased, more vaporization may occur at lower temperatures, leading to an additional stage of sintering. Physically intermixed Al and Mg oxides have been observed coating the surface of the particles, which implies a continuous transition of these vaporization processes. Such nano-oxides imply high vapor-flame combustion temperatures (>2700 K) and suggest viability for agent defeat applications.
A p-Ideal in BCI-Algebras Based on Multipolar Intuitionistic Fuzzy Sets
Authors: Lee Jeong-Gon , Fozouni Mohammad , Hur Kul , Jun Young Bae
Published: June 2020

In 2020, Kang, Song and Jun introduced the notion of multipolar intuitionistic fuzzy set with finite degree, which is a generalization of intuitionistic fuzzy set, and they applied it to BCK/BCI-algebras. In this paper, we used this notion to study p-ideals of BCI-algebras. The notion of k-polar intuitionistic fuzzy p-ideals in BCI-algebras is introduced, and several properties were investigated. An example to illustrate the k-polar intuitionistic fuzzy p-ideal is given. The relationship between k-polar intuitionistic fuzzy ideal and k-polar intuitionistic fuzzy p-ideal is displayed. A k-polar intuitionistic fuzzy p-ideal is found to be k-polar intuitionistic fuzzy ideal, and an example to show that the converse is not true is provided. The notions of p-ideals and k-polar ( ∈ , ∈ ) -fuzzy p-ideal in BCI-algebras are used to study the characterization of k-polar intuitionistic p-ideal. The concept of normal k-polar intuitionistic fuzzy p-ideal is introduced, and its characterization is discussed. The process of eliciting normal k-polar intuitionistic fuzzy p-ideal using k-polar intuitionistic fuzzy p-ideal is provided.
A Multistage Formulation Based on Full-Length CSP and AMA-1 Ectodomain of Plasmodium vivax Induces High Antibody Titers and T-cells and Partially Protects Mice Challenged with a Transgenic Plasmodium berghei Parasite
Authors: Lima Luciana C. , Marques Rodolfo F. , Gimenez Alba Marina , Françoso Katia S. , Aliprandini Eduardo , Camargo Tarsila M. , Aguiar Anna Caroline C. , Pereira Dhelio B. , Renia Laurent , Amino Rogerio , Soares Irene S.
Published: June 2020

Infections with Plasmodium vivax are predominant in the Americas, representing 75% of malaria cases. Previously perceived as benign, malaria vivax is, in fact, a highly debilitating and economically important disease. Considering the high complexity of the malaria parasite life cycle, it has been hypothesized that an effective vaccine formulation against Plasmodium should contain multiple antigens expressed in different parasite stages. Based on that, we analyzed a recombinant P. vivax vaccine formulation mixing the apical membrane antigen 1 ectodomain (PvAMA-1) and a full-length circumsporozoite protein (PvCSP-AllFL) previously studied by our group, which elicits a potent antibody response in mice. Genetically distinct strains of mice (C57BL/6 and BALB/c) were immunized with the proteins, alone or in combination, in the presence of poly(I:C) adjuvant, a TLR3 agonist. In C57BL/6, high-antibody titers were induced against PvAMA-1 and the three PvCSP variants (VK210, VK247, and P. vivax-like). Meanwhile, mixing PvAMA-1 with PvCSP-AllFL had no impact on total IgG antibody titers, which were long-lasting. Moreover, antibodies from immunized mice recognized VK210 sporozoites and blood-stage parasites by immunofluorescence assay. However, in the BALB/c model, the antibody response against PvCSP-AllFL was relatively low. PvAMA-1-specific CD3+CD4+ and CD3+CD8+ T-cell responses were observed in C57BL/6 mice, and the cellular response was impaired by PvCSP-AllFL combination. More relevant, the multistage vaccine formulation provided partial protection in mice challenged with a transgenic Plasmodium berghei sporozoite expressing the homologous PvCSP protein.
Novel Therapeutic Approach for the Management of Mood Disorders: In Vivo and In Vitro Effect of a Combination of L-Theanine, Melissa officinalis L. and Magnolia officinalis Rehder & E.H. Wilson
Authors: Borgonetti Vittoria , Governa Paolo , Biagi Marco , Galeotti Nicoletta
Published: June 2020

Mood disorders represent one of the most prevalent and costly psychiatric diseases worldwide. The current therapies are generally characterized by several well-known side effects which limit their prolonged use. The use of herbal medicine for the management of several psychiatric conditions is becoming more established, as it is considered a safer support to conventional pharmacotherapy. The aim of this study was to investigate the possible anxiolytic and antidepressant activity of a fixed combination of L-theanine, Magnolia officinalis, and Melissa officinalis (TMM) in an attempt to evaluate how the multiple modulations of different physiological systems may contribute to reducing mood disorders. TMM showed an anxiolytic-like and antidepressant-like activity in vivo, which was related to a neuroprotective effect in an in vitro model of excitotoxicity. The effect of TMM was not altered by the presence of flumazenil, thus suggesting a non-benzodiazepine-like mechanism of action. On the contrary, a significant reduction in the effect was observed in animals and neuronal cells co-treated with AM251, a cannabinoid receptor type 1 (CB1) antagonist, suggesting that the endocannabinoid system may be involved in the TMM mechanism of action. In conclusion, TMM may represent a useful and safe candidate for the management of mood disorders with an innovative mechanism of action, particularly as an adjuvant to conventional therapies.
The Impact of Protein Supplementation on Exercise-Induced Muscle Damage, Soreness and Fatigue Following Prolonged Walking Exercise in Vital Older Adults: A Randomized Double-Blind Placebo-Controlled Trial
Authors: ten Haaf Dominique S. M. , Bongers Coen C. W. G. , Hulshof Hugo G. , Eijsvogels Thijs M. H. , Hopman Maria T. E.
Published: June 2020

Background: It is unknown whether protein supplementation can enhance recovery of exercise-induced muscle damage in older adults who have a disturbed muscle protein synthetic response. We assessed whether protein supplementation could attenuate exercise-induced muscle damage and soreness after prolonged moderate-intensity walking exercise in older adults. Methods: In a double-blind, placebo-controlled intervention study, 104 subjects (81% male, ≥65 years) used either a protein (n = 50) or placebo supplement (n = 54) during breakfast and directly after exercise. Within a walking event, study subjects walked 30/40/50 km per day on three consecutive days. Muscle soreness and fatigue were determined with a numeric rating scale, and creatine kinase (CK) concentrations and serum inflammation markers were obtained. Results: Habitual protein intake was comparable between the protein (0.92 ± 0.27 g/kg/d) and placebo group (0.97 ± 0.23 g/kg/d, p = 0.31). At baseline, comparable CK concentrations were found between the protein and the placebo group (110 (IQR: 84–160 U/L) and 115 (IQR: 91–186 U/L), respectively, p = 0.84). Prolonged walking (protein: 32 ± 9 km/d, placebo: 33 ± 6 km/d) resulted in a cumulative increase of CK in both the protein (∆283 (IQR: 182–662 U/L)) and placebo group (∆456 (IQR: 209–885 U/L)) after three days. CK elevations were not significantly different between groups (p = 0.43). Similarly, no differences in inflammation markers, muscle soreness and fatigue were found between groups. Conclusions: Protein supplementation does not attenuate exercise-induced muscle damage, muscle soreness or fatigue in older adults performing prolonged moderate-intensity walking exercise.
Sequential In-Situ Carbonation Process for the Preparation of Hand Sheets with Waste Lime Mud
Authors: Chilakala Ramakrishna , Thenepalli Thriveni , Lee Seongho , Vu Hong Ha Thi , Quang Tuan Lai , Kim Jeongyun , Ahn Ji Whan
Published: June 2020

In the pulp and paper industry, the white liquor obtained from the causticizing green liquor in the smelting process mostly contains NaOH and Na2S. These chemicals are returned to the digester for reuse in the pulping process. The lime mud (LM) material is obtained from the reaction of the causticization process in paper industries. It is mainly composed of CaCO3; it appears with a green color with a high moisture content; and it has a small proportion of impurities such as non-process elements, for example Fe, Na, Mg, Al, Si, P, and S oxides and other toxic metals. This lime mud has poor whiteness with less efficiency due to its contaminated with impurities. The recycling or reutilizing process for lime mud and solid wastes are minimizing its toxic effect on the environment. The present study proposed to improve the whiteness of the waste lime mud by the calcination and hydration process at high temperatures and reutilizing it for hand sheets, making the process improve the paper brightness. In this study, we used a lime mud sample for calcination at 1000 °C and 1200 °C for 2 h and hydration at different times (3–24 h) with different temperatures (30–80 °C) and measured the powder whiteness and hand sheet brightness. The results indicated that after the calcination and hydration process, the lime mud sample whiteness was improved and that re-utilization with pulp for making hand sheets also can improve the paper brightness. It can be concluded that waste lime mud sample purification and the re-utilization process are more advantageous in paper industries.
Buddhist Modernism Underway in Bhutan: Gross National Happiness and Buddhist Political Theory
Authors: Locke Jessica
Published: June 2020

This article synthesizes and clarifies the significance of the last half-century’s developments in Bhutan’s politics within the frame of Buddhist political thought. During this time, Bhutan has held a curious position in the international community, both celebrated as a Buddhist Shangri-La defending its culture in the face of globalized modernity, and at times, criticized for defending its heritage too conservatively at the expense of ethnic minorities’ human rights. In other words, Bhutan is praised for being anti-modern and illiberal and denounced for being anti-modern and illiberal. As an alternative to understanding Bhutan vis-à-vis this unhelpful schema, and in order to better grasp what exactly is underway in Bhutan’s political developments, I read Bhutan’s politics from within the tradition of Buddhist political literature. I argue that the theory of governance driving Bhutan’s politics is an example of Buddhist modernism—both ancient and modern, deeply Buddhist and yet manifestly inflected by western liberalism. To elucidate Bhutan’s contiguity with (and occasional departures from) the tradition of Buddhist political thought, I read two politically-themed Buddhist texts, Nāgārjuna’s Precious Garland and Mipham’s Treatise on Ethics for Kings, drawing out their most relevant points on Buddhist governance. I then use these themes as a lens for analyzing three significant political developments in Bhutan: its recent transition to constitutional monarchy, its signature policy of Gross National Happiness, and its fraught ethnic politics. Reading Bhutan’s politics in this manner reveals the extent to which Buddhist political thought is underway in this moment. Bhutan’s Buddhist-modernist theory of governance is a hybrid political tradition that evinces a lasting commitment to the core values of Buddhist political thought while at the same time being responsive to modern geopolitical and intellectual influences.
Learning Sequential Force Interaction Skills
Authors: Manschitz Simon , Gienger Michael , Kober Jens , Peters Jan
Published: June 2020

Learning skills from kinesthetic demonstrations is a promising way of minimizing the gap between human manipulation abilities and those of robots. We propose an approach to learn sequential force interaction skills from such demonstrations. The demonstrations are decomposed into a set of movement primitives by inferring the underlying sequential structure of the task. The decomposition is based on a novel probability distribution which we call Directional Normal Distribution. The distribution allows infering the movement primitive’s composition, i.e., its coordinate frames, control variables and target coordinates from the demonstrations. In addition, it permits determining an appropriate number of movement primitives for a task via model selection. After finding the task’s composition, the system learns to sequence the resulting movement primitives in order to be able to reproduce the task on a real robot. We evaluate the approach on three different tasks, unscrewing a light bulb, box stacking and box flipping. All tasks are kinesthetically demonstrated and then reproduced on a Barrett WAM robot.
Multiplatform-SfM and TLS Data Fusion for Monitoring Agricultural Terraces in Complex Topographic and Landcover Conditions
Authors: Cucchiaro Sara , Fallu Daniel J. , Zhang He , Walsh Kevin , Van Oost Kristof , Brown Antony G. , Tarolli Paolo
Published: June 2020

Agricultural terraced landscapes, which are important historical heritage sites (e.g., UNESCO or Globally Important Agricultural Heritage Systems (GIAHS) sites) are under threat from increased soil degradation due to climate change and land abandonment. Remote sensing can assist in the assessment and monitoring of such cultural ecosystem services. However, due to the limitations imposed by rugged topography and the occurrence of vegetation, the application of a single high-resolution topography (HRT) technique is challenging in these particular agricultural environments. Therefore, data fusion of HRT techniques (terrestrial laser scanning (TLS) and aerial/terrestrial structure from motion (SfM)) was tested for the first time in this context (terraces), to the best of our knowledge, to overcome specific detection problems such as the complex topographic and landcover conditions of the terrace systems. SfM–TLS data fusion methodology was trialed in order to produce very high-resolution digital terrain models (DTMs) of two agricultural terrace areas, both characterized by the presence of vegetation that covers parts of the subvertical surfaces, complex morphology, and inaccessible areas. In the unreachable areas, it was necessary to find effective solutions to carry out HRT surveys; therefore, we tested the direct georeferencing (DG) method, exploiting onboard multifrequency GNSS receivers for unmanned aerial vehicles (UAVs) and postprocessing kinematic (PPK) data. The results showed that the fusion of data based on different methods and acquisition platforms is required to obtain accurate DTMs that reflect the real surface roughness of terrace systems without gaps in data. Moreover, in inaccessible or hazardous terrains, a combination of direct and indirect georeferencing was a useful solution to reduce the substantial inconvenience and cost of ground control point (GCP) placement. We show that in order to obtain a precise data fusion in these complex conditions, it is essential to utilize a complete and specific workflow. This workflow must incorporate all data merging issues and landcover condition problems, encompassing the survey planning step, the coregistration process, and the error analysis of the outputs. The high-resolution DTMs realized can provide a starting point for land degradation process assessment of these agriculture environments and supplies useful information to stakeholders for better management and protection of such important heritage landscapes.
An Airborne Offner Imaging Hyperspectrometer with Radially-Fastened Primary Elements
Authors: Kazanskiy Nikolay , Ivliev Nikolay , Podlipnov Vladimir , Skidanov Roman
Published: June 2020

We propose a new layout for the Offner imaging hyperspectrometer that is utilized onboard small space vehicles. The layout is based on a method of adjusting the adaptive temperature-dependent optical scheme by moving just two coaxial optical components located inside the hyperspectrometer. We present the results of modeling for a temperature range of −40 to +45 °C and an optical experiment using a heat and cold chamber for the range of 12 to 40 °C, proving the basic functionality of the proposed layout. Based on simulation results, the new layout is supposed to allow the hyperspectrometer to operate in a temperature range of −40 to +45 °C without its optical characteristics deteriorating, thus making it suitable for work onboard space or stratospheric vehicles.
Image-Based Somatotype as a Biometric Trait for Non-Collaborative Person Recognition at a Distance and On-The-Move
Authors: Danelakis Antonios , Theoharis Theoharis
Published: June 2020

It has recently been shown in Re-Identification (Re-ID) work that full-body images of people reveal their somatotype, even after change in apparel. A significant advantage of this biometric trait is that it can easily be captured, even at a distance, as a full-body image of a person, taken by a standard 2D camera. In this work, full-body image-based somatotype is investigated as a novel soft biometric feature for person recognition at a distance and on-the-move. The two common scenarios of (i) identification and (ii) verification are both studied and evaluated. To this end, two different deep networks have been recruited, one for the identification and one for the verification scenario. Experiments have been conducted on popular, publicly available datasets and the results indicate that somatotype can indeed be a valuable biometric trait for identity recognition at a distance and on-the-move (and hence also suitable for non-collaborative individuals) due to the ease of obtaining the required images. This soft biometric trait can be especially useful under a wider biometric fusion scheme.
Multi-Mode Love-Wave SAW Magnetic-Field Sensors
Authors: Schmalz Julius , Kittmann Anne , Durdaut Phillip , Spetzler Benjamin , Faupel Franz , Höft Michael , Quandt Eckhard , Gerken Martina
Published: June 2020

A surface-acoustic-wave (SAW) magnetic-field sensor utilizing fundamental, first- and second-order Love-wave modes is investigated. A 4.5   μ m SiO2 guiding layer on an ST-cut quartz substrate is coated with a 200 n m (Fe90Co10)78Si12B10 magnetostrictive layer in a delay-line configuration. Love-waves are excited and detected by two interdigital transducers (IDT). The delta-E effect in the magnetostrictive layer causes a phase change with applied magnetic field. A sensitivity of 1250 ° / m T is measured for the fundamental Love mode at 263 M Hz . For the first-order Love mode a value of 45 ° / m T is obtained at 352 M Hz . This result is compared to finite-element-method (FEM) simulations using one-dimensional (1D) and two-and-a-half-dimensional (2.5 D) models. The FEM simulations confirm the large drop in sensitivity as the first-order mode is close to cut-off. For multi-mode operation, we identify as a suitable geometry a guiding layer to wavelength ratio of h GL / λ ≈ 1.5 for an IDT pitch of p = 12   μ m . For this layer configuration, the first three modes are sufficiently far away from cut-off and show good sensitivity.
Deep Learning Method on Target Echo Signal Recognition for Obscurant Penetrating Lidar Detection in Degraded Visual Environments
Authors: Liang Xujia , Huang Zhonghua , Lu Liping , Tao Zhigang , Yang Bing , Li Yinlin
Published: June 2020

With the rapid development of autonomous vehicles and mobile robotics, the desire to advance robust light detection and ranging (Lidar) detection methods for real world applications is increasing. However, this task still suffers in degraded visual environments (DVE), including smoke, dust, fog, and rain, as the aerosols lead to false alarm and dysfunction. Therefore, a novel Lidar target echo signal recognition method, based on a multi-distance measurement and deep learning algorithm is presented in this paper; neither the backscatter suppression nor the denoise functions are required. The 2-D spectrogram images are constructed by using the frequency-distance relation derived from the 1-D echo signals of the Lidar sensor individual cell in the course of approaching target. The characteristics of the target echo signal and noise in the spectrogram images are analyzed and determined; thus, the target recognition criterion is established accordingly. A customized deep learning algorithm is subsequently developed to perform the recognition. The simulation and experimental results demonstrate that the proposed method can significantly improve the Lidar detection performance in DVE.
An Artificial Neural Network Assisted Dynamic Light Scattering Procedure for Assessing Living Cells Size in Suspension
Authors: Chicea Dan
Published: June 2020

Dynamic light scattering (DLS) is an essential technique used for assessing the size of the particles in suspension, covering the range from nanometers to microns. Although it has been very well established for quite some time, improvement can still be brought in simplifying the experimental setup and in employing an easier to use data processing procedure for the acquired time-series. A DLS time series processing procedure based on an artificial neural network is presented with details regarding the design, training procedure and error analysis, working over an extended particle size range. The procedure proved to be much faster regarding time-series processing and easier to use than fitting a function to the experimental data using a minimization algorithm. Results of monitoring the long-time variation of the size of the Saccharomyces cerevisiae during fermentation are presented, including the 10 h between dissolving from the solid form and the start of multiplication, as an application of the proposed procedure. The results indicate that the procedure can be used to identify the presence of bigger particles and to assess their size, in aqueous suspensions used in the food industry.
A Microservices e-Health System for Ecological Frailty Assessment Using Wearables
Authors: Garcia-Moreno Francisco M. , Bermudez-Edo Maria , Garrido José Luis , Rodríguez-García Estefanía , Pérez-Mármol José Manuel , Rodríguez-Fórtiz María José
Published: June 2020

The population in developed countries is aging and this fact results in high elderly health costs, as well as a decrease in the number of active working members to support these costs. This could lead to a collapse of the current systems. One of the first insights of the decline in elderly people is frailty, which could be decelerated if it is detected at an early stage. Nowadays, health professionals measure frailty manually through questionnaires and tests of strength or gait focused on the physical dimension. Sensors are increasingly used to measure and monitor different e-health indicators while the user is performing Basic Activities of Daily Life (BADL). In this paper, we present a system based on microservices architecture, which collects sensory data while the older adults perform Instrumental ADLs (IADLs) in combination with BADLs. IADLs involve physical dimension, but also cognitive and social dimensions. With the sensory data we built a machine learning model to assess frailty status which outperforms the previous works that only used BADLs. Our model is accurate, ecological, non-intrusive, flexible and can help health professionals to automatically detect frailty.
Vibration-Response-Only Structural Health Monitoring for Offshore Wind Turbine Jacket Foundations via Convolutional Neural Networks
Authors: Puruncajas Bryan , Vidal Yolanda , Tutivén Christian
Published: June 2020

This work deals with structural health monitoring for jacket-type foundations of offshore wind turbines. In particular, a vibration-response-only methodology is proposed based on accelerometer data and deep convolutional neural networks. The main contribution of this article is twofold: (i) a signal-to-image conversion of the accelerometer data into gray scale multichannel images with as many channels as the number of sensors in the condition monitoring system, and (ii) a data augmentation strategy to diminish the test set error of the deep convolutional neural network used to classify the images. The performance of the proposed method is analyzed using real measurements from a steel jacket-type offshore wind turbine laboratory experiment undergoing different damage scenarios. The results, with a classification accuracy over 99%, demonstrate that the stated methodology is promising to be utilized for damage detection and identification in jacket-type support structures.
Reliable UHF Long-Range Textile-Integrated RFID Tag Based on a Compact Flexible Antenna Filament
Authors: Wagih Mahmoud , Wei Yang , Komolafe Abiodun , Torah Russel , Beeby Steve
Published: June 2020

This paper details the design, fabrication and testing of flexible textile-concealed Radio Frequency Identification (RFID) tags for wearable applications in a smart city/smart building environment. The proposed tag designs aim to reduce the overall footprint, enabling textile integration whilst maintaining the read range. The proposed RFID filament is less than 3.5 mm in width and 100 mm in length. The tag is based on an electrically small (0.0033 λ 2 ) high-impedance planar dipole antenna with a tuning loop, maintaining a reflection coefficient less than −21 dB at 915 MHz, when matched to a commercial RFID chip mounted alongside the antenna. The antenna strip and the RFID chip are then encapsulated and integrated in a standard woven textile for wearable applications. The flexible antenna filament demonstrates a 1.8 dBi gain which shows a close agreement with the analytically calculated and numerically simulated gains. The range of the fabricated tags has been measured and a maximum read range of 8.2 m was recorded at 868 MHz Moreover, the tag’s maximum calculated range at 915 MHz is 18 m, which is much longer than the commercially available laundry tags of larger length and width, such as Invengo RFID tags. The reliability of the proposed RFID tags has been investigated using a series of tests replicating textile-based use case scenarios which demonstrates its suitability for practical deployment. Washing tests have shown that the textile-integrated encapsulated tags can be read after over 32 washing cycles, and that multiple tags can be read simultaneously while being washed.
The Relationship between School Age Children’s Academic Performance and Innovative Physical Education Programs
Authors: Kliziene Irina , Cizauskas Ginas , Augustiniene Aldona , Sipaviciene Saule , Aleksandraviciene Roma
Published: June 2020

Currently, there is great interest in the correlation between children’s physical activity and their academic performance. In this study, a pre-test/mid-test/post-test experimental strategy was used to avoid any disruption of educational activities, due to the random selection of children in each group. The experimental group was tested for eight months. We developed a methodology for innovative physical education classes and created a model of educational factors that encourage physical activity for children. The experimental group comprised 45 girls and 44 boys aged 6–7 years. The control group included 43 girls and 46 boys aged 6–7. Methods: Mathematical diagnostic progress tests were divided into two sections: tasks were allocated according to performance levels and the content as well as fields of activity and cognitive skills. The assessment of all areas of activity was based on student performance (unsatisfactory, satisfactory, basic, and advanced). Distribution of mathematical learning achievements by curriculum content: mathematical diagnosis was used to evaluate first-grade children’s mathematical knowledge and skills according to the five areas of the mathematics education curriculum: numbers and calculations; phenomena, equations, and inequalities; geometry, measures, and measurements; statistics and communication; and general problem-solving skills. The differences between the pre-test and mid-test results indicated that the number of children performing at a satisfactory level decreased (p = 0.035). The differences between the pre-test and post-test advanced (p = 0.038) and basic (p = 0.018) levels were found to be increased. Applying an innovative physical education program to first graders demonstrated a higher-level mathematics program in the areas of geometry, measures, and measurements; statistics; and communication and general problem-solving skills. Based on the interface between an innovative primary school physical education program and mathematics learning achievements, a research tool was developed that can be used in a quantitative research strategy.
New Policies and Evaluation System Needed to Address Environmental Concerns in China
Authors: Liu Zhe , MacDonald Bertrum
Published: June 2020

It is reported that the smog days in 2018 were much reduced compared to those in 2013 in China. The air environmental condition in China was much improved because of a number of comprehensive strategies adopted by the government such as phasing out backward production capacities and developing renewable energy industries. In addition, the Ministry of Ecology and Environment of the People’s Republic of China adopted a series of measurements to respond to the environmental events, including questioning the local highest official in serious air pollution areas. However, there are still lots of questions to be answered for a long term consideration. For instance, given the current situation of a gross domestic production (GDP) driven assessment system for officials’ credit, how long this high pressure pattern can respond to environmental events, such as air pollution, issue is a question. Therefore, unless this GDP driven assessment system is replaced by another assessment system it cannot last long. This paper also highlights the importance of developing low-carbon industries and circular economy as well as public involvement.
Model of Business Relations in Spa Tourism Enterprises and Their Business Environment
Authors: Szromek Adam R.
Published: June 2020

Sustainable tourism, carried out on spa tourism enterprises, is a key issue that requires the combination of the implementation of economic goals of business activity and, at the same time, the limitation of negative influences on the tourist areas, which are valuable from the point of nature. The main objective of this article and, at the same time, the objective of theoretical–cognitive and empirical research, is to find links and mutual relations between the entities carrying out tourist and therapeutic activity in health resorts in a model approach, taking into account sustainable tourism elements. The implementation of the goal will be carried out on the basis of empirical studies, covering business models of 17 of the largest health resorts in Poland. The article describes relations occurring in the health resort environment and defines a model of relations between health resort enterprises and other entities functioning within this sector. The network approach of the studied issue is analyzed from the point of view of relations found in the complementary cooperation of entities, among which one is ready to implement the benefit and others express their need for the said benefit and are willing to be its recipients. The network relation of the second type, where the entities combine their forces to meet a common goal, is presented in the form of exemplification of the health resort enterprise network in the Polish market.
Innovative Climate, a Determinant of Competitiveness and Business Performance in Chinese Law Firms: The Role of Firm Size and Age
Authors: Bibi Sughra , Khan Asif , Qian Hongdao , Garavelli Achille Claudio , Natalicchio Angelo , Capolupo Paolo
Published: June 2020

In the past few decades, a firm’s innovative climate has received much attention in the context of innovative behavior, competitiveness, and business performance. The existing literature has relied to a great extent on innovative climate as an interacting factor and overlooked its role as an antecedent of various organizational phenomena. Furthermore, the interaction effects of the firm’s size and age on the relationships between innovative climate and other organizational variables have gone unnoticed. This study adds to the literature by empirically assessing the effects of the firm’s innovative climate on organizational learning and employees’ innovative behavior as well as its consequences on the firm’s competitiveness and business performance. Additionally, it addresses the interaction impacts of firm size and age on the relationships between the abovementioned variables. This research achieves its goal by developing an integrative research design that analyzes complex relations using covariance-based structural equation modeling (SEM) and regression techniques on a dataset of 408 Chinese law firms. The results indicate that the firm’s innovative climate has a significant positive relationship with organizational learning and employees’ innovative behavior. It is also found that organizational learning has a significant positive influence on employees’ innovative behavior. Meanwhile, organizational learning and employees’ innovative behavior have a significant positive influence on firm competitiveness and business performance. Another important finding is that contextual factors, i.e., firm size and age, strengthen these relations. Theoretical and managerial implications, including links to firm size and age, are provided.
Diferença e educação: pensando essa composição
Authors: Novaes Marcus Pereira , Marques Davina
Published: June 2020

Diferença e educação: pensando essa composição
Klasifikasi Jenis Penyandang Masalah Kesejahteraan Sosial Menggunakan NaÃ¯ve Bayes
Authors: Nurhaeni Nurhaeni
Published: June 2020

Kebutuhan utama dalam merumuskan kebijakan, program, dan kegiatan pembangunan kesejahteraan sosial adalah ketersediaan data Penyandang Masalah Kesejahteraan Sosial (PMKS). Setiap individu dalam sebuah rumah tangga sangat miskin cenderung memiliki lebih dari satu kategori jenis PMKS. Hal ini akan mempengaruhi dalam penentuan jenis bantuan yang layak diterima, dimana sebaiknya setiap individu hanya dikategorikan ke dalam satu jenis PMKS. Dengan demikian setiap individu hanya akan menerima satu jenis bantuan.  Jenis PMKS dengan pendekatan keluarga ditentukan berdasarkan 12 kriteria yaitu umur, jenis kelamin, status perkawinan, pekerjaan, pendidikan, kecukupan ASI, imunisasi, makanan sehat, pengobatan, kondisi kecacatan, orang tua tunggal, dan perhatian dari keluarga. Sebagai upaya dalam mengoptimalkan klasifikasi jenis PMKS, digunakan metode NaÃ¯ve Bayes. Berdasarkan penelitian yang dilakukan, tingkat akurasi dari penggunaan metode naÃ¯ve bayes adalah sebesar 83,87%. Dengan demikian dapat disimpulkan bahwa metode klasifikasi NaÃ¯ve Bayes dapat digunakan untuk klasifikasi jenis PMKS.
Sistem Pendukung Keputusan Penentuan Calon Penerima Beasiswa Menggunakan Metode Simple Additive Weighting (SAW) Berbasis Web
Authors: Rohmatin Yuni , Kusrini Wiwik , Noor Agustian , Fathurrahmani Fathurrahmani
Published: June 2020

Politeknik Negeri Tanah Laut mengelola program beasiswa Bidikmisi dan PPA (Peningkatan Prestasi Akademik) untuk calon mahasiswa maupun mahasiswanya. Penentuan penerima beasiswa selama ini menggunakan microsoft excel dengan memasukkan data pendaftar beasiswa dan melakukan perhitungan berdasarkan kriteria penilaian pada masing-masing beasiswa. Proses penyeleksian tersebut memerlukan waktu serta ketelitian yang relatif lama karena setiap berkas yang dikumpulkan mahasiswa maupun calon mahasiswa akan dibandingkan dengan setiap kriteria beasiswa. Permasalahan tersebut dapat diatasi dengan membangun sistem pendukung keputusan berbasis web untuk memilih calon penerima beasiswa. Pengambilan keputusan penentuan calon penerima beasiswa mengguakan metode Simple Additive Weighting (SAW) dilakukan dengan memberikan nilai bobot pada setiap atribut dan dilanjutkan dengan proses perangkingan untuk menyeleksi alternatif yang ada. Pengembangan sistem dilakukan dengan bahasa pemrograman Hypertext Preprocessor (PHP) dengan framework CodeIgniter. Penelitian ini bertujuan untuk melakukan perangkingan terhadap nilai bobot setiap atribut yang menjadi persyaratan dalam penentuan beasiswa. Tingkat ketepatan antara jawaban yang diperoleh dari sistem dengan informasi yang diminta oleh pengguna dapat diketahui dengan melakukan pengujian perbandingan hasil perhitungan pada sistem dengan hasil perhitungan manual.
Baby Incubator Based on PID Control With Kangaroo Mode (Kangaroo Mode and Humidity)
Authors: Hidayati Nur Fildzah , Endro Yulianto  , Abd. Kholiq
Published: June 2020

Baby Incubator is one of the electromedical equipment used to provide protection to premature babies or low birth weight. Baby care in the baby incubator causes separation of mother and baby. A new innovation in the care of premature babies who bring their babies and mothers closer is Kangaroo Method Management (PMK). Kangaroo method treatment aims to create emotional attachment to the baby, so that the mother will confidently take care. The research and manufacture of this module uses a method of treating baby incubator by adding a reading of the room temperature when the kangaroo mode runs at a setting of 34 ° C - 37 ° C with the effect of room temperature at 18 ° C, 24 ° C, and 30 ° C and setting the humidity control automatically by measuring at a temperature of 32 ° C, then measuring the results immediately. Sensors used to detect temperature are LM35 sensors and sensors used to detect humidity using DHT22. Based on the measurement results obtained uncertainty values ​​on the measurement of humidity 2.1, the measurement of temperature stability can be seen from the results of the graph which shows that the room temperature is not too influential at the temperature of the baby incubator. This study has shown the development of baby incubators to help mothers who have babies born prematurely so that they can have a good bond with how to treat skin to skin. This study has proven that its accuracy is appropriate to be used to stabilize the condition of babies born prematurely and help to treat PMK in some hospitals. In the future, this research can be made and used in small clinics in villages at low costs.
DC SHOCK SIMULATOR
Authors: Amir Maruf Muhammad , Guruh Irianto Bambang , Bowo Indrato Tri
Published: June 2020

Defibrillators are electronic devices that carry shock electrical signals (pulses) to the heart muscle to maintain myocardial depolarization that is undergoing cardiac fibrillation (ventricular fibrillation or atrial fibrillation) (Bronzino, 2000). There are several conditions that must be met for the occurrence of shock processes including shock time, energy to be provided, patient and operator safety. In this defibrillator the use of selectors / energy selection is linear in the range 1-30 Joules with the use of tools at 10, 15, 20, 25, 30 Joules. The energy will then be discarded or given to the patient via a paddle when pressed the Discharge / shock button. The result of the signal given to the patient is monophasic. This study used a pre-experimental type with a One Group post test design research design. Measurements were made 5 times the volt meter at the test points determined by the compiler.
Syringe Pump With Nearly Empty Based Microcontroller Atmega328
Authors: Putri Lely Erica , Muhammad Ridha Mak'ruf  , Abd. Kholiq
Published: June 2020

Syringe Pump is a tool used to give liquid medicine or food liquid into the patient's body in a certain amount and within a certain period of time on a regular basis. The purpose of this study is to facilitate monitoring of fluid in the syringe so that the hose is not installed continuously when the liquid has run out. The circuit consists of an Atmega328 microcontroller, a motor driver, and an optocoupler sensor. Setting the syringe, volume and flowrate is done at the beginning. To insert liquid, the motor must be run by the way the settings have been done and press the start button. Tools need supply from PLN grids. Calibration is done using IDA 4 Plus. This tool is equipped with the addition of alarms nearly empty and the bolus button. From the measurements taken, at the 20 ml syringe the biggest error occurred at the 5 ml volume point of 0.4% and at the 50 ml syringe the biggest error occurred at the 5 ml volume point of 0.280%.This module can be used according to its function, because the% error is still below the ± 5% standard.
Design of Respiration Rate Meter Using Flexible Sensor
Authors: Sarah Aghnia Miyagi  , Muhammad Ridha Mak’ruf  , Endang Dian Setioningsih  , Das Tark
Published: June 2020

Respiration rate is an important physiological parameter that helps to provide important information about the patient's health status, especially from the human respiratory system. So it is necessary to measure the human respiratory rate by calculating the number of respiratory frequencies within 1 minute. The respiratory rate meter is a tool used to calculate the respiratory rate by counting the number of breaths for 1 minute. The author makes a tool to detect human respiratory rate by using a sensor that detects the ascend and descend of the chest cavity based on a microcontroller so that the operator can measure the breathing rate more practically and accurately. Component tool contains analog signal conditioning circuit and microcontroller circuit accompanied by display in the form of LCD TFT. The results of measurement data on 10 respondents obtained an average error value, namely the position of the right chest cavity 6.6%, middle chest cavity 7.92%, and left chest cavity 6.85%. This value is still below the error tolerance limit of 10%. It can be concluded that to obtain the best measurement results, the sensor is placed in the position of the right chest cavity.
Effects of Feature Selection and Normalization on Network Intrusion Detection
Authors: Umar Mubarak Albarka , Zhanfang Chen , Shuaib Khaled , Liu Yan
Published: June 2020

The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using Machine Learning (ML) techniques to build more efficient and reliable Intrusion Detection Systems (IDSs). However, the advent of larger IDS datasets has negatively impacted the performance and computational complexity of ML-based IDSs. Many researchers used data preprocessing techniques such as feature selection and normalization to overcome such issues. While most of these researchers reported the success of these preprocessing techniques on a shallow level, very few studies have been performed on their effects on a wider scale. Furthermore, the performance of an IDS model is subject to not only the utilized preprocessing techniques but also the dataset and the ML algorithm used, which most of the existing studies give little emphasis on. Thus, this study provides an in-depth analysis of feature selection and normalization effects on various IDS models built using two IDS datasets namely, NSL-KDD and UNSW-NB15, and five different ML algorithms. The algorithms are support vector machine, k-nearest neighbor, random forest, naive bayes, and artificial neural network. For feature selection and normalization, the decision tree wrapper-based approach, which tends to give superior model performance, and min-max normalization methods were respectively used. A total of 30 unique IDS models were implemented using the full and feature-selected copy of the datasets. The models were evaluated using popular evaluation metrics in IDS modeling, intra- and inter-model comparisons were performed between models and with state-of-the-art works. Random forest achieved the best performance on both NSL-KDD and UNSW-NB15 datasets with prediction accuracies of 99.87% and 98.5%, as well as detection rates of 99.79% and 99.17% respectively, it also achieved an excellent performance in comparison with the recent works. The results show that both normalization and feature selection positively affect IDS modeling with normalization slightly more important. The study also found that the UNSW-NB15 dataset is more complex and more suitable for building and evaluating modern-day IDS than NSL-KDD.