A semi-structured interview (SSI) is one of the essential tools in conduction qualitative research. This essay draws upon the pros and cons of applying semi-structured interviews (SSI) in the qualitative research method. Moreover, the challenges of SSI during the coronavirus pandemic are critically discussed to provide plausible recommendations.

The recurrent coronavirus outbreaks in China (SARS-CoV and its relative, SARS-CoV-2) have raised speculations that perhaps Asians are somehow more susceptible to these coronaviruses. Here, we test this possibility based on an analysis of the lung-specific expression of ACE2, which encodes the known cell-entry receptor of both SARS-CoV and SARS-CoV-2. We show that ACE2 expression is not affected during tumorigenesis, supporting that the abundant transcriptomes in cancer genomic studies can be informatively used to study ACE2 expression among diverse individuals without cancer. We find that ACE2 expression in the lung increases with age, but is not associated with sex. Further, Asians do not differ from other populations for ACE2 expression and do not harbor unique genetic polymorphisms in the ACE2 locus. Thus, beyond illustrating an innovative method for assessing the potential impacts of demographic factors for non-cancer diseases from large-scale cancer sample datasets, our statistically robust findings emphasize that individuals of all races require the same level of personal protection against SARS-CoV-2.

Electric vehicles (EV) are getting more commonplace in the transportation sector in recent times. As the present trend suggests, this mode of transport is likely to replace the internal combustion engine (ICE) vehicles in near future. Each of the main EV components has a number of technologies that are currently in use or can become prominent in the future. EVs can cause significant impacts on the environment, power system, and other related sectors. The present power system can face huge instabilities with enough EV penetration; but with proper management and coordination, EVs can be turned into a major contributor to the successful implementation of smart grid. There are possibilities of immense environmental benefits as well, as the EVs can extensively reduce the greenhouse gas emission from the transportation sector. However, there are some major obstacles for EVs to overcome before replacing the ICE vehicles totally. This paper is focused on reviewing all the useful data available on EV configurations, energy sources, motors, charging techniques, optimization techniques, impacts, trends, and possible directions of future developments. Its objective is to provide an overall picture of the current EV technology and ways of future development to assist in future researches in this sector.

In this paper, we discuss major issues of mathematics teaching and learning in Nepal. The issues coming from theories such as social and radical constructivism suggest that teachers are not trained to use such approach in teaching mathematics, and there is a lack of teaching aids and materials and technological tools. The issues related to social aspects are gender issues, language issues, social justice issues, and issues related to the achievement gap. The cultural issues are related to the diversity of language and ethnicity. The issues related to political aspects are equity and access, economic status, pedagogical choice, and professional organizations and unions. The issues related to technology include the technological skills, use of technology, and affordance. Finally, we suggest that all the stakeholders should pay attention to resolving these issues by improving the curriculum, training teachers, resourcing the classroom with locally made and new technological tools.

Deep learning (DL) algorithms have recently emerged from machine learning and soft computing techniques. Since then, several deep learning (DL) algorithms have been recently introduced to scientific communities and are applied in various application domains. Today the usage of DL has become essential due to their intelligence, efficient learning, accuracy and robustness in model building. However, in the scientific literature, a comprehensive list of DL algorithms has not been introduced yet. This paper provides a list of the most popular DL algorithms, along with their applications domains.

Background & Objectives: The global pandemic caused by novel coronavirus SARS-CoV-2 has claimed several lives worldwide. With the virus gathering rapid spread, the world has witnessed increasing number of confirmed cases and mortality rate, India is not far behind with approximately 37,000 affected individuals as on May 2, 2020. The ongoing pandemic has raised several questions which need to be answered by analysis of transmission of the infection. The data has been collected on daily basis from WHO and other sites. We have represented the data collated graphically using statistical packages, R and other online softwares. The present study provides a holistic overview of the spread of COVID-19 infection in India. Methods: Real-time data query was done based on daily observations using publicly available data from reference websites for COVID-19 and other government official reports for the period (15^th February, 2020 to April 28^th, 2020). Statistical analysis was performed to draw important inferences regarding COVID-19 trend in India. Results: A decrease in growth rate of cases due to COVID-19 in India post lockdown and improvement in recovery rate during the month of April was identified. The case fatality rate was estimated to be 3.22% of the total reported cases. State-wise analysis revealed a deteriorating situation in states of Maharashtra and Gujarat among others as cases continued to increase rapidly there. A positive linear correlation between the number of deaths and total cases and exponential relation between population density and number of cases reported per square km was established. Interpretation & Conclusions: Despite early preventive measures taken up by the Government of India, the increasing number of cases in India is a concern. This study compiles state-wise and district-wise data to report the daily confirmed cases, case fatalities and strategies adopted in the form of case studies. Understanding the transmission spread of SARS-CoV-2 in a diverse and populated country like India will be crucial in assessing the effectiveness of control policies towards the spread of COVID-19 infection.

The inhibition of alpha-glucosidase and alpha-amylase is one of clinic strategies for remedy the type II diabetes. Herbal medicines are reported to alleviate hyperglycemia. However, the constituents from those sources whether are targeted to the alpha-glucosidase and alpha-amylase still unexplored. This study attempted to select the compounds for efficacy of hypoglycemia via cellular and mouse levels. The results illustrated that the cytotoxicity in all tested compounds at various concentrations except the concentration of 16-hydroxy-cleroda-3,13-dine-16,15-olide (HCD) at 30 µM were not significant difference (p > 0.05) when compared with the untreated control. Acarbose (reference drug), Antroquinonol, Catechin, Quercetin, Actinodaphnine, Curcumin, HCD, Docosanol, Tetracosanol, Berberine, and Rutin could effectively inhibit the alpha-glucosidase activity of Caco-2 cells when compared with the control (maltose). The compounds (Curcumin, HCD, Tetracosanol, Antroquinonol, Berberine, Catechin, Actinodaphnine, and Rutin) could reduce blood sugar level at 30 min in tested mice. The effects of tested compounds on area under curve (AUC) were significant (p < 0.05) among Acarbose, Tetracosanol, Antroquinonol, Catechin, Actinodaphnine, and Rutin along with Berberine and Quercetin. In in vitro (alpha-glucosidase) with in vivo (alpha-amylase) experiments suggest that bioactive compounds can be a potential inhibitor candidate of alpha-glucosidase and alpha-amylase for the alleviation of type II diabetes.

The aim of this study is to explore the extent of English language teaching in Higher Institutions of Malaysia and investigate the current changes, trends and challenges in this niche. A sample of 100 English learners from public and private institutions participated in this study. Analysis of the responses indicated that English language is remaining to be difficult to master, due to speaking environment, proficiency of the teachers and other factors. However, the Government is on the right direction to improve this situation by following Common European Framework of Reference of Languages. As any other system, it takes time to put into realization and start up the mechanism. This observation carries a pedagogical perspective and includes the overview of the general picture based on Private, Public and Stand Alone English educational institutions. This study has highlighted the practical importance of British Framework of English learning and suggests to focus on emphasis of the learning process instead of a result.

In this paper analyses the characteristic of EM waves propagation in structured environment to identify the signal interference by the structure, and suggests the EM waves attenuation model considering the distance and penetration loss by the structure. The range sensor based on electromagnetic(EM) waves attenuation along to the distance showed the precise distance estimation with high resolution depending on the distance. However, it is hard to use in structured environments due to the lack of consideration of the EM waves attenuation characteristics in the structured underwater environment. In this paper, EM waves propagation characteristic and signal interference effects by the structures were analyzed, and the EM waves distance-attenuation model in structured environment was suggested with sensor installation guideline. The EM waves propagation characteristics and proposed sensor model were verified by the several experiments, and the localization result in structured environment showed the more reliable performance.

We suggest that despite McLuhan’s claim not to have a theory of communication that in fact the body of his work does indeed constitute a theory of media and their effects which I have called his General Theory of Media (GToM) that also includes his Laws of Media (LoM). Both McLuhan’s GToM and his LoM are described. A comparison is made of three notions of law: i. McLuhan’s notion of law as used in his Laws of Media; ii. the notions of the Law in the legal sense and iii. the notion of law as formulated in scientific laws. McLuhan’s understanding of media is used to analyze some of the negative effects of social media suggesting that laws need to be formulated to prevent the misuse of social media that are antithetical to democracy and the invasion of the privacy of the individual users of these apps. McLuhan’s Laws of Media are then used to provide insights into the nature of scientific laws, the Law in the legal sense and his own Laws of Media.

Pipelines are widely used for transportation of hydrocarbon fluids over millions of miles over the world. The structures of the pipelines are designed to withstand several environmental loading conditions to ensure safe and reliable distribution from point of production to the shore or distributions deport. However, leaks in pipeline networks are one of the major causes of innumerable losses in pipeline operators and nature. Incidents of pipeline failure can result in serious ecological disasters, human casualties and financial loss. In order to avoid such menace and maintain safe and reliable pipeline infrastructure, substantial research efforts have been devoted to implementing pipeline leak detection and localisation using different approaches. This paper discusses on pipelines leakage detection technologies and summarises the state-of-the-art achievements. Different leakage detection and localisation in pipeline systems are reviewed and their strengths and weaknesses are highlighted. Comparative performance analysis is performed to provide a guide in determining which leak detection method is appropriate for particular operating settings. In addition, research gaps and open issues for development of reliable pipeline leakage detection systems are discussed.

Lean is one of the systematic approach to achieve higher value for organizations through eliminate non-value-added activities. It is an integrated set of tools, techniques, and principles designed to optimize cost, quality and delivery while improving safety. In Vietnam, industry waste management and treatment has become serious issue. The aim of this research is to present the effective of Lean application for industrial wastes collecting and delivery improvement. Through a case study, this paper showed the way of Lean tools and principles applied for wastes management and treatment such as Value Stream Mapping, Pull system, Visual Control, and Andon.... to get benefit on both economic and environment. In addition, the results introduced a good experience for Vietnamese enterprises in cost saving and sustainable development in waste management.

Background: Currently, Indonesia is entering an era that is all digital and uses technology in all fields of activity. The internet has a lot to do with their behavior or character. Millennials are the nation's next generation. The emergence of the digital era caused by globalization has made the millennial generation less appreciative and practicing the values ​​of Pancasila. In this case, character education is something that must be applied to the millennial generation. Purpose: This study aims to analyze the characteristics of the millennial generation, the role of character education in realizing the values ​​of Pancasila in the daily life of the millennial generation, how to cultivate an attitude of patriotism and nationalism towards the nation by practicing Pancasila, and provide motivation for the millennial generation to realize these values. Pancasila values. Methods: This study uses a literature review method. The search for journals was carried out using the google scholar database with the keywords “Character Education”, “millenial generation”, and “Pancasila”. The journals selected are journals from 2019 to 2020. Results: By applying character education to the millennial generation, it will make it easier for them to practice the values ​​of Pancasila. Pancasila should be the way of life of the millennial generation. Recommendation and limitation: As millennials, we must protect the country from values ​​that are contrary to Pancasila. Character education must be applied following the nature of the millennial generation itself. Of course, the applied character education must prioritize and be based on the values ​​of Pancasila as well.

As the number of infections and deaths caused by the recent COVID-19 pandemic is increasing dramatically day-by-day, scientists are rushing towards developing possible counter-measures to fight the deadly virus, SARS-CoV-2. Although many efforts have already been put forward for designing and developing potential vaccines, however, most of them are proved to possess negative consequences. Therefore, in this study, the methods of immunoinformatics were exploited to design novel epitope-based subunit vaccine against the SARS-CoV-2, targeting four essential proteins of the virus i.e., spike glycoprotein, nucleocapsid phosphoprotein, membrane glycoprotein, and envelope protein. The highly antigenic, non-allergenic, non-toxic, non-human homolog and 100% conserved (across other isolates from different regions of the world) epitopes were used for constructing the vaccine. In total, fourteen CTL epitopes and eighteen HTL epitopes were used to construct the vaccine. Thereafter, several in silico validations i.e., the molecular docking, molecular dynamics simulation (including the RMSF and RMSD studies), and immune simulation studies were also performed which predicted that the designed vaccine should be quite safe, effective, and stable within the biological environment. Finally, in silico cloning and codon adaptation studies were also conducted to design an effective mass production strategy of the vaccine. However, more in vivo and in vitro studies are required on the predicted vaccine to finally validate its safety and efficacy.

Understanding how the coronaviruses invade our body is an essential point, and the expression profile of coronaviruses receptor may help us to find where the coronavirus infects our body. We found that the coronavirus receptors, including angiotensin-converting enzyme 2 (ACE2) for SARS-CoV and SARS-Cov-2, are digestion-related enzymes in human enterocytes. Coronaviruses are continually altering the binding receptor and binding modes during their evolution, but the potential target cell in the small intestine is constant when in the lung is inconstant. Enterocytes may act as a conserved cell reservoir for coronaviruses, which may be partially explained by the Red Queen hypothesis. We also found that coronaviruses receptors could be elevated in the presence of both invasive bacteria and their counterpart, probiotics. We demonstrated here that enterocytes act as a conserved cell reservoir for coronaviruses during their evolutions, which should not be ignored in the investigation of coronavirus diagnosis and treatment strategies.

When the distance between an obstacle and a power line is less than the discharge distance, a discharge arc can be generated, resulting in interruption of power supplies. Therefore, regular safety inspections are necessary to ensure safe operations of power grids. Tall vegetation and buildings are the key factors threatening the safe operation of extra high voltage transmission lines within a power line corridor. Manual or LiDAR based-inspections are time consuming and expensive. To make safety inspections more efficient and flexible, a low-altitude unmanned aerial vehicle remote-sensing platform equipped with optical digital camera was used to inspect power line corridors. We propose a semi-patch matching algorithm based on epipolar constraints using both correlation coefficient and the shape of its curve to extract three dimensional (3D) point clouds for a power line corridor. Virtual photography was used to transform the power line direction from approximately parallel to the epipolar line to approximately perpendicular to epipolar line to improve power line measurement accuracy. The distance between the power lines and the 3D point cloud is taken as a criterion for locating obstacles within the power line corridor automatically. Experimental results show that our proposed method is a reliable, cost effective and applicable way for practical power line inspection, and can locate obstacles within the power line corridor with measurement accuracies better than ±0.5 m.

In recent years, demand has been increasing for target detection and tracking from aerial imagery via drones using onboard powered sensors and devices. We propose a very effective method for this application based on a deep learning framework. A state-of-art embedded hardware system empowers small flying robots to carry out the real-time onboard computation necessary for object tracking. Two types of embedded modules were developed: one is designed using a Jetson TX or AGX Xavier, and the other is based on an Intel Neural Compute Stick. These are suitable for real-time onboard computing power on small flying drones with limited space. A comparative analysis of current state-of-art deep-learning-based multi-object detection algorithms was carried out utilizing the designated GPU-based embedded computing modules to obtain detailed metric data about frame rates as well as the computation power. We also introduce an effective target tracking approach for moving objects. The algorithm for tracking moving objects is based on the extension of simple online and real-time tracking. It was developed by integrating a deep-learning-based association metric approach (Deep SORT), which uses a hypothesis tracking methodology with Kalman filtering and a deep-learning-based association metric. In addition, a guidance system that tracks the target position using a GPU-based algorithm is introduced. Finally, we demonstrate the effectiveness of the proposed algorithms by real-time experiments with a small multi-rotor drone.

The financial inclusion, including all the people with the finance, is very concerned issue all over the world where Bangladesh is also trying to include all the people with the finance. Bangladesh lies in such a group of countries where only 17.6% - 38.6% adults are presently under the reach of the formal financial services. This is because the present banks and other formal financial modes consider the outcome and profitability in a way that, the rural and non-developed areas are always out of the consideration. But these areas consist of the most population of Bangladesh. And only then financial inclusiveness will be successful in Bangladesh when people from these regions will be under formal financial consideration. The paper seeks for a solution to the issue and presents the Unit Banking System as a probable way towards financial inclusion. For implementing the system in Bangladesh, the system needs a slight modification to cope in Bangladeshi economic condition and address the specific needs without hampering the surroundings. Considering all these, the paper shows the status, problems and key points of financial scenario of inclusion in Bangladesh and shows policy for a Modified Unit banking System.

This paper presents a methodology to design sensor fusion parameters using real performance indicators of navigation in UAVs based on PixHawk flight controller and peripherals. This methodology and the selected performance indicators allows to find the best parameters for the fusion system of a determined configuration of sensors and a predefined real mission. The selected real platform is described with stress on available sensors and data processing software, and the experimental methodology is proposed to characterize sensor data fusion output and determine the best choice of parameters using quality measurements of tracking output with performance metrics not requiring ground truth.

The market for autonomous vehicles (AV) is expected to experience significant growth over the coming decades and to revolutionize the future of transportation and mobility. The AV is a vehicle that is capable of perceiving its environment and perform driving tasks safely and efficiently with little or no human intervention and is anticipated to eventually replace conventional vehicles. Self-driving vehicles employ various sensors to sense and perceive their surroundings and, also rely on advances in 5G communication technology to achieve this objective. Sensors are fundamental to the perception of surroundings and the development of sensor technologies associated with AVs has advanced at a significant pace in recent years. Despite remarkable advancements, sensors can still fail to operate as required, due to for example, hardware defects, noise and environment conditions. Hence, it is not desirable to rely on a single sensor for any autonomous driving task. The practical approaches shown in recent research is to incorporate multiple, complementary sensors to overcome the shortcomings of individual sensors operating independently. This article reviews the technical performance and capabilities of sensors applicable to autonomous vehicles, mainly focusing on vision cameras, LiDAR and Radar sensors. The review also considers the compatibility of sensors with various software systems enabling the multi-sensor fusion approach for obstacle detection. This review article concludes by highlighting some of the challenges and possible future research directions.

Phenotyping is the task of measuring plant attributes for analyzing the current state of the plant. In agriculture, phenotyping can be used to make decisions concerning the management of crops, such as the watering policy, or whether to spray for a certain pest. Currently, large scale phenotyping in fields is typically done using manual labor, which is a costly, low throughput process. Researchers often advocate the use of automated systems for phenotyping, relying on the use of sensors for making measurements. The recent rise of low cost, yet reasonably accurate, RGB-D sensors has opened the way for using these sensors in field phenotyping applications. In this paper, we investigate the applicability of 4 different RGB-D sensors for this task. We conduct an outdoor experiment, measuring plant attribute in various distances and light conditions. Our results show that modern RGB-D sensors, in particular, the Intel D435 sensor, provides a viable tool for close range phenotyping tasks in fields.

For multi-sensor integrated systems, such as a mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, though the latter is more reliable.

The Bayes filters, such as Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of the unknowns. Efficient integration of multiple sensors requires deep knowledge of their error sources and it is not trivial for complicated sensors, such as Inertial Measurement Unit (IMU). Therefore, IMU error modelling and efficient integration of IMU and Global Navigation Satellite System (GNSS) observations has remained a challenge. In this paper, we develop deep Kalman filter to model and remove IMU errors and consequently, improve the accuracy of IMU positioning. In other words, we add modelling step to the prediction and update steps of Kalman filter and the IMU error model is learned during integration. Therefore, our deep Kalman filter outperforms Kalman filter and reaches higher accuracy.

High electricity demand for consumption at current supply level in Indonesia led to the rising cost of electricity bills. This factor is compounded by the fact that many electric generators in Indonesia still use fossil fuels, which contributes to the high basic generation cost. UBL is one of the universities that aim to be a green campus. Our research explores the possibility of installing motion sensor to contribute on the energy efficiency. Although mostly common in developed countries, the use of motion sensor for energy efficiency is still rare, especially in Indonesia. despite rising cost and supply shortages, Indonesian buildings are still of high energy consumption. our experiment shows that simple installation of commercially available motion sensors can contribute to reduce the electricity bill from the increase of energy efficiency. One of the efforts to lower energy demand in consumer side is to use the electricity efficiently, such as turning off lights in a room when it's not in use. This method can be simply done by turning the light switches for office and classrooms, but difficult to do in public spaces such as toilets and corridors. Our experiment shows that simple installation of commercially available motion sensors can contribute to reduce the electricity bill from the increase of energy efficiency. Automatic light switches experimentally installed in sample toilet room prove that electricity consumption from the lamps can contribute to the reduction of total weekly energy that translates into Green House Gas emission reduction.

An adequate representation of the water infiltration process in the soil allows improving the efficiency in application and the uniformity in surface irrigation. The Green and Ampt model has shown a good representation of the process, and researchers from the United States Department of Agriculture (USDA) determined the values of their parameters for soils of that country, which are shown in tables or through functional relationships and this information is used as reference in several parts of the world, although there is no certainty that they are representative of the soils in Mexico. In this study, the parameters of the Green & Ampt equation were determined and evaluated in some soils of agricultural importance in Mexico. The parameters were obtained in four ways: one of them applied a methodology adapted from Brooks and Corey to quantify the wetting front capillary pressure head and used an permeameter under constant hydraulic head to determine the saturated hydraulic conductivity, and the other three consisted in taking them from three studies reported by the USDA. The values of the parameters suggested in Mexico drastically underestimated the results with relative errors (RE) in a range of -49.0 to -94.0% and the most representative were those obtained with the methodology proposed in this research with RE of -15.0 to 6.0%.

In this paper, a method is developed for presenting a novel virtual torque sensor based on precise model and position measurements avoids the need of traditional strain gauges and amplifiers. More specifically, the harmonic drive compliance model and the Gaussian process regression (GPR) technique are used together to achieve virtual torque sensor measurement. While the harmonic drive compliance model provides the analytic part, the Gaussian process regression method is used to reconstruct the unmolded part based on motor-side and link-side joint angles as well as motor current. After an automatic offline calibration, the method allows for a lean online implementation. The virtual torque sensor measurement is compared with measurements of a commercial torque sensor, and the results have attested the effectiveness of the proposed method.

An existing power grid is going through a massive transformation. Smart grid technology is a radical approach for improvisation in prevailing power grid. Integration of electrical and communication infrastructure is inevitable for the deployment of Smart grid network. Smart grid technology is characterized by full duplex communication, automatic metering infrastructure, renewable energy integration, distribution automation and complete monitoring and control of entire power grid. Wireless sensor networks (WSNs) are small micro electrical mechanical systems which are accomplished to collect and communicate the data from surroundings. WSNs can be used for monitoring and control of smart grid assets. Security of wireless sensor based communication network is a major concern for researchers and developers. The limited processing capabilities of wireless sensor networks make them more vulnerable to cyber-attacks. The countermeasures against cyber-attacks must be less complex with an ability to offer confidentiality, data readiness and integrity. The address oriented design and development approach for usual communication network requires a paradigm shift to design data oriented WSN architecture. WSN security is an inevitable part of smart grid cyber security. This paper is expected to serve as a comprehensive assessment and analysis of communication standards, cyber security issues and solutions for WSN based smart grid infrastructure.

This paper presents a two-stage ADC based on pseudo-differential operational transconductance amplifier (OTA), which is designed for the readout circuit of X-ray linear array sensor. This hybrid ADC employs an incremental sigma-delta ADC and a cyclic ADC, achieving a good trade-off between accuracy and conversion speed. The two stages share the same hardware to reduce power consumption and die area. A common-mood feedback module is used to suppress the influence of charge injection, and the effectiveness is demonstrated by detailed theoretical analysis. A test chip of 14-bit ADC is fabricated in 0.35μm CMOS technology. The measured root mean square (RMS) value of DNL is 0.254 LSB, and the maximum value of INL is -0.776/+1.56 LSB. The measured effective number of bits (ENOB) is 13.43 bits.

The issue of being pro-gender is still a controversial topic to be debated in Indonesian society. However, in the 21st Century, many women have been able to break through barriers and participate in the public sphere. It is a form of self-existence as proposed by Simone de Beauvoir on existentialist feminism. Based on these problems, this study aims to find out and answer questions about how Indonesian women exist in the public sphere in the 21st Century and find out how Indonesian women exist in the public sphere through Simone de Beauvoir's existentialist feminism paradigm. The research method used is descriptive-qualitative through a literature review of 23 journal articles, websites, and data reports with a range of 2019-2021. This study found that based on Simone de Beauvoir's feminist paradigm, Indonesian women in the 21st Century are no longer a figure other than complete. Furthermore, the data collected by the researcher shows that several gender indicators have shown that Indonesian women have been able to occupy public spaces in various aspects. Based on these results, it is hoped that it can provide information about Simone de Beauvoir's existentialist feminism thought and its relevance to the existence of Indonesian women in the public sphere in the 21st Century. However, this research has limitations, those are only about women in Indonesia, and the paradigm of feminism is limited to Simone de Beauvoir's existentialist feminism.

All cancer registries constantly show striking differences in cancer incidence by age and among tissues. For example, lung cancer is diagnosed hundreds of times more often at age 70 than at age 20, and this cancer in nonsmokers occurs thousands of times more frequently than heart cancer in smokers. An analysis of these differences using basic concepts in cell biology indicates that cancer is the end-result of the accumulation of cell divisions in stem cells. In other words, the main determinant of carcinogenesis is the number of cell divisions that the DNA of a stem cell has accumulated in any type of cell from the zygote. Cell division, process by which a cell copies and separates its cellular components to finally split into two cells, is necessary to produce the large number of cells required for living. However, cell division can lead to a variety of cancer-promoting errors, such as mutations occurring during DNA replication, chromosome aberrations arising during mitosis, errors in the distribution of cell-fate determinants between the daughter cells, and failures to restore physical interactions with other tissue components. Some of these errors are spontaneous, others are promoted by endogenous DNA damage occurring during quiescence, and others are influenced by pathological and environmental factors. The cell divisions required for carcinogenesis are primarily caused by multiple local and systemic physiological signals rather than by errors in the DNA of the cells. As carcinogenesis progresses, the accumulation of DNA errors promotes cell division and eventually triggers cell division under permissive extracellular environments. The accumulation of cell divisions in stem cells drives not only the accumulation of the DNA alterations required for carcinogenesis, but also the formation and growth of the abnormal cell populations that characterize the disease. This model of carcinogenesis provides a new framework for understanding the disease and has important implications for cancer prevention and therapy.

Indoor navigation systems must deal with absence of GPS signals, since they are only available in outdoor environments. Therefore, indoor systems have to rely upon other techniques for positioning users. Recently various indoor navigation systems have been designed and developed to help visually impaired people. In this paper an overview of some existing indoor navigation systems for visually impaired people are presented and they are compared from different perspectives. The evaluated techniques are ultrasonic systems, RFID-based solutions, computer vision aided navigation systems, ans smartphone-based applications.

In the paper we show that the general relativity in recent Einstein-Palatini formulation is equivalent to a gauge field. We begin with a bit of information of the Einstein-Palatini formulation and derive Einstein field equations from it. In the next section, we consider general relativity with a positive cosmological constant in terms of the corrected curvature. We show that in terms of the corrected curvature general relativity takes the form typical for a gauge field. Finally, we give a geometrical interpretation of the corrected curvature.

This paper investigates the impact of price and real exchange rate volatility on Foreign Direct Investment (FDI) inflows in a panel of 10 Latin American and Caribbean countries, observed between 1990 and 2012. Both price and exchange rate volatility series are estimated through the Generalized Autoregressive Conditional Heteroscedasticity model (GARCH). Our results, obtained employing the Fixed Effects estimator, confirm the theory of hysteresis and option value, in so far it is found a statistically significant negative effect of exchange rate volatility on FDI. Price volatility, instead, turns out to be positive but insignificant. Moreover, we show that human capital and trade openness are key for attracting foreign capital. From the policy perspective, our analysis suggests the importance of stabilization policies as well as the one of government credibility in promoting trade openness and human capital formation.

The abundant mechanical vibration energy in bridge road environment can be converted into electric energy by using the piezoelectric energy harvest technology, which could be an efficient way to provide energy required by the wireless sensor network in the bridge condition monitoring system. An autonomous energy harvesting system has been designed based on cantilever beams for sensing and acquiring the bridge vibration energy. After the analysis of the dynamic properties of the piezoelectric cantilever beam in the energy conversion, three kinds of interface circuits were compared through simulation and experimental results. It was shown that the VD interface circuit has less power loss. Furthermore, the proposed closed loop control method based on the VD circuit was simple, adaptive, and self-powered, which is suitable for the road energy harvesting application. Finally, the energy harvesting system based on VD circuit was realized with harvested power of around 0.8mW.

Arabic was the language of philosophy, logic, Islamic sciences and rhetorical linguistic sciences. It was used in the writing of all sciences generally and became the language of world culture. Although the other languages of the Islamic world had a little share, but all peoples of Islamic countries; Arabs and non-Arabs, Muslims and non-Muslims attributed to that movement appreciated. Hence, Arab sciences flourished in their bright ages. Arabic language was a cultural container of the ancient Greek and Latin intellectual heritage. As the ancient Greek and Latin sciences and literatures were translated into Arabic in the bright ages of Islam. Arab language was a strong bond for them, as a common human heritage for the centuries to save it from being lost, as Muslims used it to develop their sciences and arts, as Muslims in the East used the Western sciences and literatures in the modern age, because they are not Eastern or Western, but the common efforts of all humanity. Arabic language opened for the dictionaries ​​and other tongues of cross-fertilization, civil friction and simulation. Arabic had become the language of sciences: mathematics, astronomy, engineering, logic, philosophy, mysticism, agriculture, industry and economics by the continuous efforts of scientists in their scientific research, invention, experimentation, knowledge collection and classification in various fields, where orientalists recognized the Arab leadership. That scientific and literary civilization moved to Europe through Italy, Andalusia, Crusades and the Ottoman Caliphate. Europeans learned Arabic language, literature and sciences in the centers of Toledo, Fez and cities of Maghreb.

A compact Mach-zehnder interferometer with a novel design of directional couplers and a phase shifter has been presented as a thermo-optical sensor. With the aim of reducing device size to micro and nano dimension silicon-on-insulator technology was employed. That allowed miniaturization of device size through the reduction of its cross sectional area to 0.066 µm² and the radius of curvature of both the arms of the directional coupler and S-bends of the phase shifter to 5 µm and C-bends to 3 µm. These nano size device dimensions made it possible to reduce the coupling gap to 0.2 µm, which resulted in a significant reduction in the coupling length. The device geometry and its performance characteristics were analyzed and optimized using coupled mode analysis and finite difference time domain simulation tools, respectively. The wavelength dependent transmission loss of the device was measured at different temperature to verify and validate its performance characteristics. Tested devices showed a remarkable temperature dependent transmission characteristic offering significant changes in transmission loss band – with as low as 0.45 ⁰C change in substrate temperature. The extinction ratio and the free spectral range of the device were 26 dB and 0.26 nm respectively in the wavelength range of 1549.5 nm – 1550.5 nm. These results imply that the devices presented here can be used as compact and highly sensitive thermal sensors and optical switches.

This paper presents a piezoresistive pressure sensor with a shield layer for improved stability. Compared with the conventional piezoresistive pressure sensors, p-type piezoresistors are covered by an n-type shield layer, which is formed by ion implantation. The proposed pressure sensors have been successfully fabricated by bulk micromachining techniques. The impact of electrical field on piezoresistors is studied by simulation. The temperature drift of the pressure sensor has been investigated by both simulation and experimental measurement. Characteristics of developed pressure sensors are tested from -40 C to 125 C. A sensitivity of 0.022 mV/V/KPa and a maximum non-linearity of 0.085% FS are measured for the fabricated sensor in a pressure range of 1 MPa. The temperature coefficients of resistance of shielded piezoresistors are found to be smaller than those of un-shielded ones. It is demonstrated that the shield layer is able to reduce the drift caused by electrical field and ambient temperature variation.

The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a series of experimental results generated using a through-the-wall (TTW) Frequency Modulated Continuous Wave (FMCW) C-Band radar system named Soprano. The objective of this analysis was to classify whether an individual was carrying an item in both hands or not using micro-Doppler information from a FMCW sensor. The radar was deployed at a standoff distance, of approximately 0.5 m, outside a residential building and used to detect multiple people walking within a room. Through the application of digital filtering, it was shown that significant suppression of the primary wall reflection is possible, significantly enhancing the target signal to clutter ratio. Singular Value Decomposition (SVD) signal processing techniques were then applied to the micro-Doppler signatures from different individuals. Features from the SVD information have been used to classify whether the person was carrying an item or walking free handed. Excellent performance of the classifier was achieved in this challenging scenario with accuracies up to 94%, suggesting that future through wall radar sensors may have the ability to reliably recognize many different types of activities in TTW scenarios using these techniques.

The static formation temperature (SFT) is required to determine the thermophysical properties and production parameters in geothermal and oil reservoirs. However, the SFT is not easy to be obtained by both experimental and physical methods. In this paper, a mathematical approach to predicting SFT based on a new model describing the relationship between bottom hole temperature (BHT) and shut-in time was proposed. The unknown coefficients of the model were derived from least squares fit by Particle Swarm Optimization (PSO) algorithm. Besides, the ability to predict SFT based on a few BHT data (such as first 3, 4, or 5 ones of a data set) was evaluated. The accuracy of the proposed method to predict SFT was testified with a deviation percentage less than ±4% and high values of regression coefficient R² (>0.98). The proposed method could be used as a practical tool to predict SFT in both geothermal and oil wells.

LoRa and its upper layers definition LoRaWAN is one of the most promising LPWAN technologies for implementing the Internet of Things (IoT). Although being a popular technology, several works in the literature have revealed various weaknesses regarding the security of LoRaWAN v1.0 (the official 1st draft). By using all these recommendations from the academia and industry, the LoRa-Alliance has worked on the v1.0 to develop an enhanced version and provide more secure and trustable architecture. The result of these efforts ended-up with LoRaWAN v1.1, which was released on Oct 11, 2017. This manuscript aims at demystifying the security aspects and provide a comprehensive Security Risk Analysis related to latest version of LoRaWAN. Besides, it provides several remedies to the recognized vulnerabilities. To the best of authors’ knowledge, this work is one of its first kind by providing a detailed security analysis related to latest version of LoRaWAN. According to our analysis, end-device physical capture, rogue gateway and replay attacks are found to be threating for safety operation of the network. Eventually, v1.1 of LoRaWAN is found to be less vulnerable to attacks compared to v1.0, yet possesses several security implications that need to be addressed and fixed for the upcoming releases.

Reactive NO_x is one of the major air pollutants, which also plays a key role as greenhouse gas. Many research efforts have been devoted to not only detection of NO_x in air but also abatement of NO_x emission. The aim of this mini review is to provide a panoramic snapshot of the electrochemical analysis methods for the emission and detection of NO_x in atmosphere, with special emphasis on NO_x sensor. The electrochemical detecting mechanism and materials for fabricating electrochemical gas sensors are discussed and the prospects and challenges in this area are also evaluated. This work will serve as a useful source to inform the interested audience of the latest developments and applications in the field of NO_x emission and electrochemical detection.

This research aims to identify the role of the Dyson model for strategic development in achieving strategic success, and the starting point of the research was the following main question: What is the role of the Dyson model in achieving success?The research was applied in the field in the departments of the Baghdad Municipality, where the examination list was relied upon, which included a set of questions that the senior and middle leaders in the Baghdad Municipality answered, and it was the main means by which the information related to the field of research was collected, and the checklist included two variables and three dimensions From each variable, as each dimension included four questions that express indicators that revolve around one of the research hypotheses, and the case study methodology was used, which defined its path and steps, collected and analyzed field data, and linked it to its theoretical framework, in order to reach To achieve the goal of completing this research, and through analyzing, interpreting and discussing the results, the most important results were drawn up: It was found that the principle of motivation within the departments of Baghdad Municipality does not exist and this affects the employees who do not receive it from the higher leaders in their departments, and this shows that the leaderships in The Municipality of Baghdad do not have the skills and experience. Baghdad Municipality seeks to work alone and not to involve employees who have experiences and skills and strive to achieve development in their departments, and this is what the community members expressed. Among them and poor business completion in their departments.

Since the first description of bisphosphonate-related osteonecrosis of the jaw (BRONJ) numerous research groups have focused on possible pathological mechanisms including the suppression of the bone turnover of the jaw, antiangiogenic effects and soft tissue toxicity. In our review we focused on summarizing the role of the soft tissues in the development and progression of BRONJ. The biological behavior of fibroblasts can be significantly influenced by bisphosphonates (BP) such as a concentration dependent reduction of cell viability. High concentrations of BP can induce apoptosis and necrosis of the cells. Comparable effects could be detected for keratinocytes. Compared to non-nitrogen containing bisphosphonates nitrogen-containing BP have worse effects on cell biology by blocking the mevalonate pathway. Next to this the cell architecture and the expression levels of several genes and proteins are significantly disturbed by BP. These inhibitory effects of BP are in accordance with BP related reduced angiogenesis and neovascularization and could underline the hypothesis that inhibition of fibroblasts and keratinocytes results in delayed wound healing and can induce and trigger BRONJ.

Vehicle windshield wiper system increases the driving safety by contributing a clear shot viewing to the driver. In this paper, modelling, designing and simulation of a vehicle windshield wiper system with robust control theory is done successfully. H∞ loop shaping and robust pole placement controllers are used to improve the wiping speed by tracking a reference speed signals. The reference speed signals used in this paper are step and sine wave signals. Comparison of the H∞ loop shaping and robust pole placement controllers based on the two reference signals is done and convincing results have been obtained. Finally the comparative results prove the effectiveness of the proposed H∞ Loop Shaping controller to improve the wiping mechanism for the given two reference signals.

Urbanization is considered as a main indicator of regional economic development due to its positive effect on promoting industrial development; however, many regions, especially developing countries, are troubled by its negative effect — the aggravating environmental pollution. Many researchers have indicated that rapid urbanization stimulated the expansion of industrial production scale and increased industrial pollutant emissions. However, this judgement contains a grave deficiency in that urbanization not only expands industrial production scales but can also increase industrial labour productivity and change the industrial structure. To modify this deficiency, we first decompose the influence which urbanization impacts on industrial pollutant emissions into the scale effect, the intensive effect and the structure effect by using the Kaya Identity and the LMDI Method; second, we perform an empirical study of the three effects’ impacts by applying the spatial panel model with data from 282 Chinese cities between 2003 and 2013. Our results indicate that (1) there are significant reverse U-shapes between Chinese urbanization rate and its industrial pollutant emissions; (2) the scale effect and the structure effect have aggravated Chinese industrial waste water discharge, sulphur dioxide emissions and soot (dust) emissions, while the intensive effect has generated a decreasing and ameliorative impact on that aggravated trend. The definite relationship between urbanization and industrial pollutant emissions depends on the combined influence of the scale effect, the intensive effect and the structure effect; (3) there are significant spatial autocorrelations of industrial pollutant emissions between Chinese cities, but the spatial spillover effect from other cities does not aggravate local urban industrial pollutant emissions, we offer an explanation to this contradiction that the vast rural areas surrounding Chinese cities have served as sponge belts and have absorbed the spatial spillover of cities’ industrial pollutant emissions. According to the results, we argue that this type of decomposition of the influence into three effects is necessary and meaningful, it establishes a solid foundation for understanding the relationship between urbanization and industrial pollutant emissions, and effectively helps to meet relative policy making.

In the study of relativistic jets one of the key open questions is their interaction with the environment on the microscopic level. Here, we study the initial evolution of both electron–proton (e^- - p⁺) and electron–positron (e^±) relativistic jets containing helical magnetic fields, focusing on their interaction with an ambient plasma. We have performed simulations of "global" jets containing helical magnetic fields in order to examine how helical magnetic fields affect kinetic instabilities such as the Weibel instability, the kinetic Kelvin-Helmholtz instability (kKHI) and the Mushroom instability (MI). In our initial simulation study these kinetic instabilities are suppressed and new types of instabilities can grow. In the e^- - p⁺ jet simulation recollimation-like instability occurs and jet electrons are strongly perturbed. In the e^± jet simulation a recollimation-like instability occurs at early times followed by a kinetic instability and the general structure is similar to a simulation without helical magnetic field. Simulations using much larger systems are required in order to thoroughly follow the evolution of global jets containing helical magnetic fields.

In the era when the market segment of Internet of Things (IoT) tops the chart in various business reports, it is apparently envisioned that the field of medicine expects to gain a large benefit from the explosion of wearables and internet-connected sensors that surround us to acquire and communicate unprecedented data on symptoms, medication, food intake, and daily-life activities impacting one’s health and wellness. However, IoT-driven healthcare would have to overcome many barriers, such as: 1) There is an increasing demand for data storage on cloud servers where the analysis of the medical big data becomes increasingly complex; 2) The data, when communicated, are vulnerable to security and privacy issues; 3) The communication of the continuously collected data is not only costly but also energy hungry; 4) Operating and maintaining the sensors directly from the cloud servers are non-trial tasks.This book chapter defined Fog Computing in the context of medical IoT. Conceptually, Fog Computing is a serviceoriented intermediate layer in IoT, providing the interfaces between the sensors and cloud servers for facilitating connectivity, data transfer, and queryable local database. The centerpiece of Fog computing is a low-power, intelligent, wireless, embedded computing node that carries out signal conditioning and data analytics on raw data collected from wearables or other medical sensors and offers efficient means to serve telehealth interventions. We implemented and tested an fog computing system using the Intel Edison and Raspberry Pi that allows acquisition, computing, storage and communication of the various medical data such as pathological speech data of individuals with speech disorders, Phonocardiogram (PCG) signal for heart rate estimation, and Electrocardiogram (ECG)-based Q, R, S detection. The book chapter ends with experiments and results showing how fog computing could lessen the obstacles of existing cloud-driven medical IoT solutions and enhance the overall performance of the system in terms of computing intelligence, transmission, storage, configurable, and security. The case studies on various types of physiological data shows that the proposed Fog architecture could be used for signal enhancement, processing and analysis of various types of bio-signals.

A wide variety of pump and treat methods like chemical precipitation, adsorption, ion exchange and reverse osmosis have been trialled for many decades for fluoride removal from groundwater, but the problem of fluoride contaminated water remains in many parts of the world largely because these processes require constant monitoring, are expensive to implement and maintain at decentralised scale due to lack of reticulation infrastructure, and possess sludge disposal problem. This paper presents an overview of various fluoride removal processes and the limitations associated with each process and the application of in-situ permeable reactive barrier for remediating fluoride contaminated groundwater is explored, which displays the potential to be a cost effective, low maintenance and energy intensive technology.

Understanding the vulnerability of areas and the likelihood of specific disasters, particularly earthquakes, is one of the most important issues in Iran. One of the major concerns in Iran is the resilience of rural communities. The present study is devoted to spatial analysis of risk in rural areas and the evaluation of preparedness in the rural districts of the city of Abhar. In particular, this study evaluates the resilience to earthquakes. The research was conducted in two parts in which the first part has used the VIKOR Multiple criteria decision making model as well as the employment of this model in the ArcGis. The second part of the study used field studies, in the form of questionnaires, to evaluate the readiness of the local population against the risks of earthquakes. Four indicators, individual, physical, economic abilities and access, were assessed. The population included rural districts, where statistical samples were villagers. Results of the spatial analysis indicated that 15 villages are in the high-risk areas, 24 villages were in the medium-risk areas and all other villages were in low-risk areas. In terms of readiness of the locals, the results indicated a lack of planning with regards to the four mentioned indicators.

Functional Near Infrared Spectroscopy (fNIRS) systems for e-health applications usually suffer of poor signal detection mainly due to a low end-to-end signal to noise ratio of the electronics chain. Lock-In Amplifiers (LIA) historically represent a powerful technique helping to improve performances in such circumstances. In this work it has been designed and implemented a digital LIA system, based on a Zynq® Field Programmable Gate Array (FPGA), trying to explore if this technique might improve fNIRS system performances. More broadly, FPGA based solution flexibility has been investigated, with particular emphasis applied to digital filter parameters, needed in the digital LIA, and it has been evaluated its impact on the final signal detection and noise rejection capability. The realized architecture was a mixed solution between VHDL hardware modules and software ones, running within a softcore microprocessor. Experimental results have shown the goodness of the proposed solutions and comparative details among different implementation will be detailed. Finally a key aspect taken into account throughout the design was its modularity, allowing an ease increase of the input channels while avoiding the growth of the design cost of the electronics system.

The food system, the most important driver of planetary transformation, is in a deep crisis. Therefore, seeking a sustainable and socially-fair transition pathway becomes an issue of utmost priority for our own survival. The consideration of food as a commodity, a social construct that played a central role in driving this crisis, remains the uncontested narrative to lead the different transition pathways what seems rather contradictory. By exploring the normative values in the transition landscape, this paper seeks to understand how relevant is the hegemonic narrative of “food as commodity” and its alternative of “food as commons” to determine transition trajectories and food policy beliefs. Applying the Multi-level Perspective framework and developing the ill-studied “agency in transition”, this research enquired food-related professionals that belong to an online community of practice (N=95) on valuation of food dimensions and agency in food transitions to check whether the valuation of food is relevant to explain personal stances in transition. Results suggest the socially-constructed view of food as commodity is positively correlated to the gradual reforming attitude, whereas food as commons is positively correlated to the counter-hegemonic transformers regardless the self-defined position in the transition landscape (regime or niches). At personal level, there are multiple loci of resistance with counter-hegemonic attitudes in varied institutions of the regime and the innovative niches, many of them holding this discourse of food as commons. Conversely, alter-hegemonic attitudes are not positively correlated to this alternative discourse and they may inadvertently or purportedly reinforce the ‘‘neoliberal narrative’’. Food as commons, a different narrative whose rationale is explained in the paper, seems to be a relevant framework that could enrich the multiple transformative constituencies that challenge the industrial food system and therefore facilitate the convergence of movements that reject the commodification of food.

This paper proposed three-dimensional numerical simulation method by coupling of electrostatic and fluid fields to evaluating the performance of electrical sensor in the concentration measurement of gas/solid two-phase flow. Compared with the static numerical simulation, this real-time dynamic 3-D simulation method can research on a designed capacitance sensor combining the dynamic characteristics of the two-phase flows for concentration measurement. Several fluid-electrostatic models of transmission pipes with different sensor structures are built. Under different test positions and different particle concentrations, the flow characteristics and the corresponding electric signals can be obtained, and the correlation coefficient between the concentration values and the capacitance values are used for performance evaluation of the sensors. The effects of flow regimes on concentration measurement are also been investigated in this paper. To validate the results of simulation, an experimental platform with horizontal straight pipe for phase volume concentration measurement of solid/air two-phase flow is built, and the experimental results agree well with simulation conclusions. The simulation and test results show that the coupling models can give constructive reference opinions for the sensor design and collection of installation position in different transmission pipelines, which are very important for the practical process of pneumatic conveying system.

This paper investigates the influence of magnetic field for a two dimensional deformations on a two temperature problem at the free surface of a semi-infinite semiconducting medium under the effect of mechanical force during a photothermal theory and the effect of hydrostatic initial stress on the medium. The Harmonic Wave Method (Normal Mode Analysis) has been used to obtain the equations of elastic waves, heat conduction equation, quasi-static electric field, carrier density, two temperature coefficient, ratios, and constitutive relationships for the thermo-magnetic-electric medium. The effects of several parameters as thermoelastic and thermoelectric coupling parameters and two temperature parameter of this force on the displacement component, force stress, carrier density and temperature distribution has been depicted graphically.

Visual inertial odometry (VIO) has recently received much attention for efficient and accurate ego-motion estimation of unmanned aerial vehicle systems (UAVs). Recent studies have shown that optimization-based algorithms achieve typically high accuracy when given enough amount of information, but occasionally suffer from divergence when solving highly non-linear problems. Further, their performance significantly depends on the accuracy of the initialization of inertial measurement unit (IMU) parameters. In this paper, we propose a novel VIO algorithm of estimating the motional state of UAVs with high accuracy. The main technical contributions are the fusion of visual information and pre-integrated inertial measurements in a joint optimization framework, and the stable initialization of scale and gravity using relative pose constraints. To count for ambiguity and uncertainty of VIO initialization, a local scale parameter is adopted in the online optimization. Quantitative comparisons with the state-of-the-art algorithms on the EuRoC dataset verify the efficacy and accuracy of the proposed method.

The measurement of discrimination in employment is a key variable in understanding dynamics in the nature of and change in ‘race relations’. Measuring such discrimination using ‘situation’ and ‘correspondence’ tests was influenced by John Rex’s sociological analyses, begun in in England in the 1960s, and replicated in Europe and America in later decades. This literature is reviewed, and the methodologies of testing for employment discrimination are discussed. Recent work in Britain and The Netherlands is considered in detail in the light of changing social structures, and the rise of Islamophobia. Manchester, apparently the city manifesting the most discrimination in Britain, is considered for a special case study, with a focus on one individual, a Muslim woman seeking intermediate level accountancy employment. Her vita was matched with that of a manifestly indigenous, white Briton. Submitted vitas (to 1,043 potential employers) indicated significant discrimination against the Muslim woman candidate. Results are discussed within the context of Manchester’s micro-sociology, and Muslim women’s employment progress in broader contexts, drawing on our work in Jordan and Palestine. We conclude with the critical realist comment that the “hidden racism” of employment discrimination shows that capitalist societies continue to be institutionally racist, and the failure to reward legitimate aspirations of minorities pushes ethnic minorities into a permanent precariat, with implications for social justice and social control, which denies minority efforts to “integrate” in society’s employment systems.

Carotid atherosclerotic lesions are a major cause of cerebrovascular disease (CVD). Identification and quantification of carotid plaques are important for categorizing the vulnerability of plaques for rupture and assessing the impact of treatments. The irregularity of plaque surface is associated with previous plaque rupture and plays an important role in the risk of stroke. Thus, the aim of this study is to develop and validate novel vulnerability biomarkers from three-dimensional ultrasound (3DUS) images by analyzing the surface morphological characterization of carotid plaque using fractal geometry features. 3D box-counting and 3D blanket are the two types of 3D fractal dimension that were employed to describe the smoothness of plaques. This fractal dimension analysis tool was used to evaluate the effect of atorvastatin using 3DUS carotid images, which were acquired from 6 patients treated with atorvastatin with 80 mg daily and 5 patients with placebo. The Student's T Test results showed that those two fractal features were effective for detecting the statin-related changes in carotid atherosclerosis with p<0.0068 and p<0.015 respectively, suggesting that 3D fractal dimension measurements can be used effectively to analyze the surface characteristics of carotid plaques, especially for evaluating the impact of the treatment.

The technological development of piezoelectric materials is crucial for developing wearable and flexible electromechanical devices. There are many inorganic materials with piezoelectric effects, such as piezoelectric ceramics, aluminum nitride, and zinc oxide. They all have very high piezoelectric coefficients and large piezoelectric response ranges. The characteristics of high hardness and low tenacity make inorganic piezoelectric materials unsuitable for flexible devices that require frequent bending. Polyvinylidene fluoride (PVDF) and its derivatives are the most popular materials used in flexible electromechanical devices in recent years and have high flexibility, high sensitivity, high ductility, and a certain piezoelectric coefficient. Owing to increasing the piezoelectric coefficient of PVDF, researchers are committed to optimizing PVDF materials and enhancing their polarity by a series of means to further improve their mechanical–electrical conversion efficiency. This paper reviews the latest PVDF-related optimization materials, related processing and polarization methods, and the applications of these materials such as those in wearable functional devices, chemical sensors, biosensors, and flexible actuator devices for flexible micro-electromechanical devices. We also discuss the challenges of wearable devices based on flexible piezoelectric polymer, consider where further practical applications could be.

This work deals with a numerical implementation of a fifth order CENTRAL WENO-TVD (\textit{Weighted Essentially Non-Oscillatory-Total Variation Dimimishing}) of Haschem (2006) scheme applied to the convective terms of some hyperbolic conservation laws problems, in a volume finite framework. The WENO-TVD scheme is used to solve the 1D advection and Burgers equations. For this case is implemented two different numerical fluxes: The Lax-Friedrichs and TVD fluxes. In the TVD fluxes the schemes applied are in flux-limiter form. The schemes implemented for this flux are: Van Albada-1 (van Albada et al.,1982), van Albada-2 (Kermani et al., 2003), van Leer (Hassanzadeh, 2009) and MINMOD (Hirsch, 2007). The WENO type schemes are characterized for their high order approximation, and do not produce spurious oscilations near discontinuities, shocks and higher gradients. A third order Runge-Kutta TVD for the temporal variable is used. Qualitative and quantitative comparison are presented. The numerical solutions are computed with an in-house computer code developed in MATLAB software. In future works, it will develope a paralelization of computer code for solving systems of conservation laws, e.g. Euler equations of gas dynamics.

This paper introduces a sliding mode control (SMC) based equivalent control method to a novel high output gain Cuk converter. An additional inductor and capacitor improves the efficiency and output gain of the classical Cuk converter. Classical PI controllers are widely used in DC-DC converters. However, it is a very challenging task to design a single PI controller operating in different load and disturbances. SMC based equivalent control method which achieves a robust operation in a wide operation range is also proposed. Switching frequency is kept constant in appropriate interval in different loading and disturbance conditions by implementing a dynamic hysteresis control method. Numerical simulations conducted on Matlab/Simulink confirm the accuracy of analytical analysis of high output gain modified Cuk converter. In addition, proposed equivalent control method is validated in different perturbations to demonstrate the robust operation in wide operation range.

Wearable technology has been proposed as a potential tool to change the way of human life, such as the smart bracelet and the Google Glass. In the wearable technology, the inertial sensor has great significance in tracking the object movements. The paper focused on detecting the movements of user’s finger based on the inertial sensor to give the control signals. Firstly, the attitude matrix, which represented the transformation relation of carrier coordinate system and the navigation coordinate system, was obtained. Secondly, the attitude matrix was expressed based on the quaternions. Thirdly, the finger gesture was processed by the attitude matrix to get the attitude angle. Finally, the robot was controlled by attitude angle to make the moving action. The experimental results showed the detection of the finger movement is effective.

Multiple sensor nodes known as detection stations make the sensor networks; each node is light and portable. Every sensor node contains power source, microcomputer, transducer and transceiver. Power source provides power to each node. Micro-computer is used for storing and processing the output coming from the sensors. The transducer is used to generate the signals and the transceiver is used to receive and transmit data to the central computer. Eavesdropping gets facilitated with wireless communication, and it has many useful applications in military, homeland, hostile and uncontrolled environments. So it is prone to the high level of security. The process in which information is gathered to form a summarized type for analysis is known as data aggregation, as it is used to reduce the energy consumption in wireless sensor networks. The security issues have become crucial in data aggregation, especially when gets deployed in hostile and remote environment. In wireless sensor networks many secure aggregations have been proposed. It still faces some resource constrained that’s why new techniques are needed. In our survey we will discuss those approaches and their pros and cons.

Recycling waste products is an environmental-friendly activity that can bring benefits to accompany, saving manufacturing costs and improving economic efficiency. For the beer industry, recycling bottles can reduce manufacturing costs and reduce the industry's carbon footprint. This paper presents a model for a multi-objective collection-distribution center location and allocation problem in a closed loop supply chain for the beer industry, in which the objective is to minimize total costs and transportation pollution. Uncertainties in the form of randomness and fuzziness are jointly handled in this paper to ensure a more practical problem solution, for which returned bottle sand unusable bottles are considered fuzzy random variables. A heuristic algorithm based on priority-based global-local-neighbor particle swarm optimization (pb-glnPSO) is applied to ensure reliable solutions for this NP-hard problem. A case study on a beer operation company is conducted to illustrate the application of the proposed model and demonstrate the priority-based global-local-neighbor particle swarm optimization.

We statistically investigate the Coronavirus Disease 19 (hereinafter Covid-19) epidemics, which is particularly invasive in Italy. We show that the high apparent mortality (or Case Fatality Ratio, CFR) observed in Italy, as compared with other countries, is likely biased by a strong underestimation of infected cases. To give a more realistic estimate of the mortality of Covid-19, we use the most recent estimates of the IFR (Infection Fatality Ratio) of epidemic, based on the minimum observed CFR, and furthermore analyse data obtained from the ship Diamond Princess, a good representation of a ‘laboratory’ case-study from an isolated system in which all the people have been tested. From such analyses we derive more realistic estimates of the real extension of the infection, as well as more accurate indicators of how fast the infection propagates. We then point out from the various explanations proposed, the dominant factors causing such an abnormal seriousness of the disease in Italy. Finally, we use the deceased data, the only ones estimated to be reliable enough, to predict the total number of infected people and the interval of time when the infection in Italy could stop.

Primate vision is an active process that constructs a stable internal representation of the 3D world based on 2D sensory inputs that are inherently unstable due to incessant eye movements. We present here a mathematical framework for processing visual information for a biologically-mediated active vision stereo system with asymmetric conformal cameras. This model utilizes the geometric analysis on the Riemann sphere developed in the group-theoretic framework of the conformal camera, thus far only applicable in modeling monocular vision. The asymmetric conformal camera model constructed here includes the fovea’s asymmetric displacement on the retina and the eye’s natural crystalline lens tilt and decentration, as observed in ophthalmological diagnostics. We extend the group-theoretic framework underlying the conformal camera to the stereo system with asymmetric conformal cameras. Our numerical simulation shows that the 1 theoretical horopter curves in this stereo system are conics that well approximate the empirical longitudinal horopters of the primate vision system.

Age-related diseases (ARDs) are the leading cause of death worldwide, and contribute to 90% of mortality in developed countries. Interestingly, the mortality rates of individual ARDs increase exponentially with age. Processes described by the exponential growth function typically involve a branching chain reaction or, more generally, a positive feedback loop. Here I propose that each ARD is mediated by one or several positive feedback loops (vicious cycles). I then identify critical vicious cycles in five major ARDs: atherosclerosis, hypertension, diabetes, Alzheimer’s and Parkinson’s. I also propose that the progression of ARDs can be halted by selectively interrupting the vicious cycles and suggest the most promising targets. An evolutionary perspective is also offered.

Although, Artificial intelligence (AI) helps experts with crime analysis, research, and understanding, it has a favourable influence on cyber security. It strengthens the tools that businesses use to safeguard their networks, clients, and workers against dangerous online behaviour. However, artificial intelligence is infamous for requiring a lot of resources. It may not, however, always be relevant. Additionally, it can provide hackers a new tool and advance their abilities. Actually, the VPN industry benefits from AI in the same way. The threat posed by machine learning in AI to user data privacy may be lessened by using a VPN on all of your devices. Because they use machine learning algorithms, VPNs are better equipped to shield their users from internet-based threats. Artificial intelligence (AI) has reportedly being investigated as a means of enhancing internet security for a considerable amount of time, according to Smart Data Collective. We anticipated that AI and machine learning will have a substantial impact on the future of cyber security around two years ago.

In an increasingly interconnected world, the internationalization of languages plays a pivotal role in shaping global linguistic landscapes. This qualitative study delves into the intriguing realm of Cebuano, a language with a rich cultural heritage and a vibrant community of speakers. Through a meticulous exploration of language variation, adaptation, and policy dynamics, the researcher unravels the complex interplay between Cebuano and the global linguistic tapestry. Drawing upon a comprehensive literature review and qualitative research, including in-depth interviews and focus group discussions, this paper illuminates the nuanced manifestations of Cebuano beyond its traditional borders and sheds light on its presence in diverse international settings. The findings reveal the intricate dance of language and identity, offering insights into the processes of language maintenance, shift, and revitalization. As the researcher navigates the multifaceted dimensions of Cebuano's internationalization, not only is its global significance unraveled, but also the intricate connections between language, culture, and human experience are investigated. This study not only contributes to the scholarly discourse on language dynamics but also raises compelling questions about the preservation of linguistic diversity, the power of language in shaping identities, and the role of language in fostering intercultural understanding. By embracing the kaleidoscope of Cebuano's global journey, this paper invites readers to contemplate the broader implications for language diversity, communication, and cultural preservation in an increasingly interconnected world.

That how to improve the sensitivity and the detection ability of the Large-caliber sensor is critical to satisfy the requirement of heavy vehicle wear condition monitoring. In this paper, we introduced the LC resonance principle to the design of sensor with large flow channel (7mm). The resonant exciting coil increases the impedance change of the exciting circuit caused by wear particles which magnify the current difference between the two exciting coils and improve the sensitivity of the sensor. The resonant induction coil greatly suppresses the interference signals and magnifies the weak induced electromotive force which is beneficial to enhance the detection ability. In order to boost the detectability for different materials particles, a phase controlled variable-frequency exciting system (PCVFES) was adopted to automatically switch the exciting frequency between 284kHz for ferromagnetic particles and 420KHz for non-ferromagnetic particles. For the weak signal detection, based on the essential characteristic of the signal, we apply a simpler method that modified lock-in amplifier (MLIA) rather than the conventional algorithms (Wavelet transform, EMD). Results show that using these methods the sensitivity and the detection ability of the sensor are significantly improved and the 75μm iron particles and 220μm copper particles were successfully detected which realizes the initial abnormal wear monitoring for the large flow project.

This paper proposes an innovative mechatronic piezo-actuated module to control vibrations in modern machine tools. Vibrations represent one of the main issues that compromise seriously the quality of the workpiece. The active vibration control (AVC) device is composed by a host part integrated with sensors and actuators synchronized by a regulator, able to make a self-assessment and adjust to the environmental alteration. This study presents the mechatronic model based on the kinematic and dynamic analysis of the AVC device. To ensure a real time performance, a H2-LQG controller has been developed and validated by simulations involving machine tool, PZT actuator and controller models. The Hardware-in-the-loop (HIL) architecture is adopted to control and attenuate the vibrations. A set of experimental tests has been performed to validate the AVC module on a commercial machine tool. The feasibility of the real time vibration damping is demonstrated and the simulation accuracy is evaluated.

Neurofibromatosis type1 (NF1) is an autosomal dominant disorder caused by mutations in the NF1gene. Although congenital pseudarthrosis of the tibia (CPT) has frequently been associated with NF1, the underlying molecular mechanism of CPT in these NF1 patients is yet ill-understood. The aim of the present study was to detect NF1 mutations from genomic DNA and to harbor variants associated with CPT in NF1 patients. Whole-exome sequencing was first carried out with samples from two patients with CPT in one NF1 family, and a novel mutation c.2324A>G (p.E775G) in NF1 gene was identified. Additionally, a missense variant c.455C>T (p.P152L) in BCOR gene completely co-segregated with the CPT phenotype within this family. Subsequently, NF1 and NF2 genes in four other unrelated patients with both NF1 and CPT were screened using targeted sequencing. Four mutations in NF1 gene, including two known mutations (c.2288T>C/p.L763P, c.574 C>T/p.R192*) and two novel mutations (c.768delT/p.F256Lfs*25, c.2229_2230delTG/ p.V744Qfs*23) were detected. Further study confirmed that CPT was present in NF1 families, and NF1 mutations were closely associated with these complex phenotypes. Moreover, the data from the current study indicated that male gender might be a susceptibility factor for CPT in NF1. Therefore, we speculated that BCOR variants might be related to CPT phenotype among male NF1 patients.

The main foundations of the standard $\Lambda $CDM model of cosmology are that: 1) The redshifts of the galaxies are due to the expansion of the Universe plus peculiar motions; 2) The cosmic microwave background radiation and its anisotropies derive from the high energy primordial Universe when matter and radiation became decoupled; 3) The abundance pattern of the light elements is explained in terms of primordial nucleosynthesis; and 4) The formation and evolution of galaxies can be explained only in terms of gravitation within a inflation+dark matter+dark energy scenario. Numerous tests have been carried out on these ideas and, although the standard model works pretty well in fitting many observations, there are also many data that present apparent caveats to be understood with it. In this paper, I offer a review of these tests and problems, as well as some examples of alternative models.

Depth-sensing technology has led to broad applications of inexpensive depth cameras that can capture human motion and scenes in 3D space. Background subtraction algorithms can be improved by fusing color and depth cues, thereby allowing many issues encountered in classical color segmentation to be solved. In this paper, we propose a new fusion method that combines depth and color information for foreground segmentation based on an advanced color-based algorithm. First, a background model and a depth model are developed. Then, based on these models, we propose a new updating strategy that can eliminate ghosting and black shadows almost completely. Extensive experiments have been performed to compare the proposed algorithm with other, conventional RGB-D algorithms. The experimental results suggest that our method extracts foregrounds with higher effectiveness and efficiency.

In this paper, an in-wheel vibration absorber for In-wheel-motor electric vehicle (IWM EV) is designed, and a comprehensive control strategy of in-wheel absorber and vehicle suspension is proposed to improve vehicle ride comfort. The proposed in-wheel vibration absorber, designed for suppressing the motor vibration, is composed of a spring and a controllable damper. The values of in-wheel spring stiffness and damper initial coefficient are determined by using the improved particle swarm optimization (IPSO) algorithm, which is carried on the typical driving condition. To deal with the negative interaction effects between vehicle suspension and in-wheel absorber, the linear quadratic regulator (LQR) algorithm is utilized to control suspension damper, and the fuzzy PID method is utilized to control in-wheel damper. Based on the four evaluation indexes including vehicle body vertical acceleration, suspension dynamic deflection, wheel dynamic load and motor wallop, the simulation results show that, the proposed LQR control of suspension effectively improves vehicle ride comfort, and the fuzzy PID control of in-wheel damper exhibits superior performance of motor vibration suppressing in comparison to conventional electric wheel.

This paper attempts to clarify an long-standing issue about the number of unknowns in the Reynolds-Averaged Navier-Stokes equations (RANS). This study shows that all perspectives regarding the numbers of unknowns in the RANS stem from the misinterpretation of the Reynolds stress tensor. The current literature consider that the Reynolds stress tensor has six unknown components; however, this study shows that the Reynolds stress tensor actually has only three unknown components, namely the three components of fluctuation velocity. This understanding might shed a light to understand the well-known closure problem of turbulence.

Recent developments in optical biosensors based on integrated photonic devices are reviewed with a special emphasis on silicon-on-insulator ring resonator. The review is mainly devoted to the following aspects: (1) Principles of sensing mechanism, (2) sensor design, (3) biofunctionalization procedures for specific molecule detection and (4) measurement set-ups and advances in chip-integration. The inherent challenges of implementing photonics-based biosensors to meet specific requirements of applications in medicine, food analysis, and environmental monitoring are discussed.

Collision avoidance is an important feature in advanced driver-assistance systems, aiming at providing correct, timely and reliable warnings before an imminent collision (objects, vehicles, pedestrians, etc.). A co-simulation framework is proposed in this paper to address the design and evaluation of collision avoidances in a cyber-physical system. The co-simulation framework is supported on the interaction between SCANeR and Matlab/Simulink. From the best of authors’ knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip LIDAR sensors in a cyber-physical system (CPS) considering traffic scenarios is presented. The CPS is designed and implemented in SCANeR. Secondly, an obstacle recognition library with three specific Artificial Intelligence-based methods is also designed based on sensory information database provided by SCANeR. Three methods for collision avoidance detection are considered, i.e.; a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods for detecting obstacles before different weather conditions is done with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and fog conditions, the support vector machine in rainy and self-organized map in snowy conditions.

In recent experimental studies, we reported the aggravating effects of Asian sand dust (ASD) on male reproductive function in mice. However, the effects of fetal ASD exposure on male reproductive function have not been investigated. The present study investigated the effects of fetal ASD exposure on reproductive function in male offspring. Using pregnant CD-1 mice, ASD was administered intratracheally on days 7 and 14 of gestation, and the reproductive function of male offspring was determined at 5, 10, and 15 weeks after birth. The secondary sex ratio was significantly lower in the fetal ASD-exposed mice than in the controls. Histologic examination showed partial vacuolation of seminiferous tubules in immature mice. Moreover, daily sperm production (DSP) was significantly less in the fetal ASD-exposed mice than in the controls. DSP in the fetal ASD-exposed mice was approximately 10% less than the controls at both 5 and 10 weeks. However, both the histologic changes and the DSP decrease were reversed as the mice matured. These findings suggest that ASD exposure affects both the fetal development and the reproductive function of male offspring. In the future, it will be necessary to clarify the onset mechanisms of ASD-induced male fetus death and male reproductive disorders.

In this work, we designed a MEMS device which allows simultaneous direct measurement of mechanical properties during deformation under external stress and characterization of the evolution of microstructure of nanomaterials within a transmission electron microscope. This MEMS device makes it easy to establish the correlation between microstructure and mechanical properties of nanomaterials. The device uses piezoresistive sensors to qualitatively measure the force and displacement of nanomaterials, e.g., in wire and thin plate forms. The device has a theoretical displacement resolution of 0.19 nm and a force resolution of 2.1 μN. The device has a theoretical displacement range limit of 2.74 μm and a load range limit of 27.75 mN.

Academic entrepreneurship focuses on commercialization of research. Even though it is practiced worldwide for decades, Bangladesh is a newcomer in this segment. In Bangladesh only 2 Universities have Technology Transfer Offices or TTOs which are established with the sole focus of commercialization of researches of the students and the faculty members of the Universities. This article focuses on worldwide practices of technology transfer and academic entrepreneurial activities and also explores the opportunities and challenges of such entrepreneurs through detail investigation of the existing body of knowledge. Apart from exploring the problems and prospect of academic entrepreneurship in Bangladesh, this article also introduces the concept of Full-Service Knowledge Transfer Office (KTO), which existing literatures do not offer. The authors believe that by establishing such KTOs as a self-sustaining body, it is possible for an academic entrepreneur to stimulate, support and sustain their activities in Bangladesh. The concept of full service KTOs can also become models for other nations, specially the developing ones, to establish and nurture a culture of academic entrepreneurship.

Grid energy storage system for PV Applications is connected with three different power sources i.e. PV Array, Battery and the Grid. It is advisable to have Isolation between these three different sources to provide safety for the equipment. The configuration proposed in this paper provides the complete isolation between the three sources. A Power Balancing Control (PBC) for this configuration is proposed to operate the system in three different modes of operation. Control of a dual active bridge (DAB) based battery charger which provides a galvanic isolation between batteries and other sources is explained briefly. Various modes of operation of a Grid energy storage system are also presented in this paper. Hardware-In-Loop (HIL) Simulation is carried out to check the performance of the system and the PBC algorithm. Power circuit (comprises of inverter, dual active bridge based battery charger, grid, PV cell, batteries, contactors and switches) is simulated and the controller hardware and user interface panel are connected as HIL with the simulated power circuit through Real Time Digital Simulator (RTDS). HIL simulation results are presented to explain the control operation, steady state performance in different modes of operation and the dynamic response of the system.

According to the current understanding, the recently observed accelerated expansion of the universe is caused by the dark or the vacuum energy. Attempts to calculate the magnitude of this energy using the standard model of particle physics led to values which are 59 – 120 orders of magnitude larger than the experimentally estimated one. Even though the expanding space has positive internal energy, in a flat universe it is completely balanced by the negative energy of gravitational field making the net energy equal to zero. However, the current physical theories may breakdown for times less than or on the order of Planck time and one cannot assume that the above assertion concerning the balance of two energies is valid also in this time scale. In this note it is assumed that this balance of the two energies during the creation of new space as the universe expands takes place only for times larger than the Planck time. If this assumption is correct, the net energy of the newly created space remains positive for times on the order of Planck time and the positive vacuum energy has to be burrowed from empty space before it is being balanced by gravity. This can happen only within the restrictions of the time-energy uncertainty principle. In this note it is shown that such considerations lead to a vacuum energy density of about 0.3 Nanojoules per cubic meter which has to be compared with the measured value of 0.6 Nanojoules per cubic meter.

Since 1970s, a great deal of attention has been paid to the development of semiconductor–based biosensors because of the numerous advantages they offer, including high sensitivity, faster response time, miniaturization, and low–cost manufacturing for quick biospecific analysis with reusable features. Commercial biosensors have become highly desirable in the fields of medicine, food, environmental monitoring as well as military applications (e.g., Hoffmann–La Roche, Abbott Point of Care, Orion High technologies, etc.), whereas increasing concerns on the food safety and health issues have resulted in the introduction of novel legislative standards for these sensors. Numerous devices have been developed for monitoring of biological–processes such as nucleic–acid hybridization, protein–protein interaction, antigen–antibody bonds and substrate–enzyme reactions, just to name a few. Since 1980s scientific interest moved to the development of semiconductor–based devices which also include integrated front–end electronics, such as the extended–gate–field–effect–transistor biosensor which is one of the first miniaturized chemical sensors. This work is intended to be a review of the state of the art focused on the development of biosensors based extended–gate–field–effect–transistor within the field of bioanalytical applications, which will highlight the most recent research works reported in the literature. Moreover, a comparison among the diverse EGFET devices will be presented giving particular attention to the materials and technologies.

Plant leaf area index (LAI) is a key characteristic affecting field canopy microclimate. In addition to traditional professional measuring instruments, smartphone camera sensors have been used to measure plant LAI. However, when smartphone methods were used to measure conifer forest LAI, very different performances were obtained depending on whether the smartphone was held at the zenith angle or at a 57.5° angle. To validate further the potential of smartphone sensors for measuring conifer LAI and to find the limits of this method, this paper reports the results of a comparison of two smartphone methods with an LAI-2000 instrument. It is shown that both methods can be used to reveal the conifer leaf-growing trajectory. However, the method with the phone oriented vertically upwards always produced better consistency in magnitude with LAI-2000. The bias of the LAI between the smartphone method and the LAI-2000 instrument was explained with regard to four aspects that can affect LAI: gap fraction, leaf projection ratio, sensor field of view (FOV), and viewing zenith angle (VZA). It was concluded that large FOV and large VZA cause the 57.5° method to overestimate the gap fraction and hence underestimate conifer LAI, especially when tree height is greater than 2.0 m. For the vertically upward method, the bias caused by the overestimated gap fraction is compensated for by an underestimated leaf projection ratio.

Background: COVID-19 pandemic has pulled us all a few steps back, were we never shake hands or hug each other when we meet our friends and family after a gap, but instead we greet them by saying Namaste and joining our hands together. As we all know, COVID-19 spreads through air and the only way to shield ourselves is by maintaining a safe distance from one another. Methodology: In order to conduct a meta-analysis on the number of COVID-19 cases in Kerala and India, the data was retrieved from various sites hosted by the government bodies. The data for analysis was collected from May 2020 to July 2020. The average number of days required to reach every 5000 fresh cases were also calculated using this data. COVID-19 has affected all the economy holistically regardless of financial, behavioral, or societal aspects. Conclusion: Lifting of the lockdown in a step by step process keeping in mind the necessities for the nation was a thoughtful act, but the people who mistook this opportunity and did not remain in quarantine after coming from abroad was recognized as the reasons behind the sudden and uncontrolled rise in the number of COVID-19 cases in Kerala, India. The government authorities had no other option but to lift the restrictions to reduce the economic burdens that had already affected the daily wage worker and farmers prompting them to give up their lives.

Implementation of the German Climate change Strategy in the Federal State of Saxony-Anhalt is discussed in this paper. It shares the requirement and importance of sustainable development. An overview of strategy, The DAS Indicator System is provided with results of a portion of work being done for the ministry of agriculture by Deutscher Wetterdienst (DWD). Applicability of the indicator system is also shown by evaluation of results for specific indicators from 1961-2015.

In recent years, online social media information has been subject of study in several data science fields due to its impact on users as a communication and expression channel. Data~gathered from online platforms such as Twitter has the potential to facilitate research over social phenomena based on sentiment analysis, which usually employs Natural Language Processing and Machine Learning techniques to interpret sentimental tendencies related to users opinions and make predictions about real events. Cyber attacks are not isolated from opinion subjectivity on online social networks. Various security attacks are performed by hacker activists motivated by reactions from polemic social events. In this paper, a methodology for tracking social data that can trigger cyber attacks is developed. Our main contribution lies in the monthly prediction of tweets with content related to security attacks and the incidents detected based on ℓ1 regularization.

Smart sensors based on graphene field effect transistor and biologically receptors are regarded as a promising nanomaterial that could be the basis for future generations of selective real-time monitoring of target analytes and smaller electronics. So the purpose of this paper is to provide details a real-time and selective explosive sensor based on GFETs and PDA-based lipid membranes coupled with biologically inspired TNT peptide receptors. Following an introduction, this paper describes the way of fabrication of the GFETs device by investigation methods for transferring graphene sheet from Cu substrates to target substrates, which is functionalized by the TNT peptide receptors, in order to offer a system which has the capability of answering the presence of related target molecules. Field effet transistor was fabricated using graphene as a channel and monitored by the source-drain current and back-gate voltage curves in the measurement. The transport property changed compared to that of the FET made by intrinsic graphene, that is, the Dirac point position moved from positive Vg to negative Vg, indicating the transition of graphene from p-type to n-type after annealing in TNT, and GFET sensor show good sensitivity and selectivity response.

In this paper, quasi-static axial compression tests are performed on the nodal Moso bamboos to study the size effect on energy absorption of the bamboos and the damage pattern of the multiple bamboo columns. Experimental results show that under the same moisture content, growth age and growing environment, the specific energy absorption (SEA) of the test samples increases with the increase of the out-diameter and thickness of the bamboo columns, indicating that size effect exists for energy absorption of the Moso Bamboos. For the multiple bamboo columns, there are mainly three failure modes for the constituent single bamboo columns: splitting above the node, splitting below the node and splitting through the node. Also, the tensile tests are conducted on three kinds of dog-bone shaped bamboo samples to investigate the macroscopic tensile fracture mode in the longitudinal direction of Moso bamboos. Results show that there is no direct relationship between the fracture pattern and moisture content of the bamboos, as well as the growth age of the bamboos. However, the tensile loading rate and the shape of the dog-bone shaped bamboo sample could affect the macroscopic fracture pattern of the bamboos in some cases.

Background. Increasing evidence demonstrate that concentration of protein in infant formula >1.9g/100Kcal with high levels of insulinogenic aminoacids is associated with accelerated weight gain, increased fat mass accumulation and risk of adiposity. Purpose of this study was to conduct a systematic review to determine the metabolic effects in infants feed with infant formula optimized in protein. Methods. Systematic review was conducted according PRISMA Statement. RCTs with one intervention group (infant formula with 1.6-1.9gr of protein/100Kcal) and at least one comparative control group (infant formula with >1.9gr of protein/100Kcal) were included. Standardized mean differences (SMD), through random model were calculated. Results. 15 RCT were included. Optimized protein in infant formula was associated with less gain of BMI at 24 months of follow-up (SMD -0.25, IC95% -0.36 to -0.13, p 0.01) and less fat mass accumulation (SMD -0.68, IC95% -0.98 to -0.37, p 0.01). Optimized protein was also associated to less gain of weight, weight/age Z-score, weight/length Z-score, BUN (mmol/dL) and IGF1 (ng/ml). No effect on length/age Z-score was observed. Conclusions. Robust evidence showed optimized protein (1.6gr/100Kcal to 1.9gr/100Kcal) in infant formula is associated with metabolic benefits in infants with less weight gain, BMI and fat mass accumulation.

When we talk about the Defence Industry (DI), arms transfers, and military expenditures we mostly refer to data accumulated by the Stockholm International Peace Research Institute (SIPRI). In the SIPRI Top 20 list of largest exporters of major arms for 2019, small states hold consecutive positions: Israel takes 8th place, Switzerland is 13th, and Sweden, Norway, and Belarus place 15th, 17th, and 20th respectively. The author analyses the Swiss DI case due to several reasons; its place in SIPRI Top, its sharp rise of Swiss arms exports in the recent year, its Swiss neutrality strategy, the country’s multilingual society, and its all-government approach to the arms industry, though still contributing to the limited scholarly studies on contemporary Swiss DI. This paper aims to explore Swiss DI and its strategies, to identify the country’s defence and security policy influence towards DI, and to discuss the Swiss DI stance and future perspectives in the context of the global arms trade. At the same time, this paper also highlights Swiss DI successes and failures that could be of significant use to other small states aiming to develop or enhance their relevant DIs.

Lack of shock absorption capability of conventional steel bollards causes significant vehicle damage and consequently high repair costs. This research studies a solution to reduce vehicle damage by inserting PLA honeycomb structures. A honeycomb-inserted bollard was designed based on numerical simulations using LS-DYNA, which yielded the bollard designed for actual vehicle-bollard collision experiments. Simulation efforts were focused on calculating the acceleration characteristics when a vehicle collides with steel and honeycomb-inserted bollards. Compared to the simulated steel bollards, 20 MPa yield-strength honeycomb-inserted bollard showed 0.017s delay in the maximum acceleration occurrence time, reduction of the maximum acceleration to 37.4% of that of steel bollards, and 13.1% reduction in the B-pillar maximum acceleration. Actual vehicle-bollard collision experiments, with a gyro-sensor installed at the test vehicle front bumper frame, also proved improved shock absorption characteristics of the honeycomb-inserted bollards. An experiment with honeycomb-inserted bollard showed 0.783s delay in the maximum acceleration occurrence time, a significant delay when compared to steel bollards. The maximum acceleration measured by the gyro-sensor was 0.35m/s2 when the simulation predicted it to be 0.388 m/s2, proving the similarity in the simulations and experiments. Thus, this study of shock absorption characteristics promised reduced damage to vehicles and lower repair cost.

The theory of the continuous two-dimensional (2D) Fourier Transform in polar coordinates has been recently developed but no discrete counterpart exists to date. In the first part of this two-paper series, we proposed and evaluated the theory of the 2D discrete Fourier Transform (DFT) in polar coordinates. The theory of the actual manipulated quantities was shown, including the standard set of shift, modulation, multiplication, and convolution rules. In this second part of the series, we address the computational aspects of the 2D DFT in polar coordinates. Specifically, we demonstrate how the decomposition of the 2D DFT as a DFT, Discrete Hankel Transform (DHT) and inverse DFT sequence can be exploited for efficient code. We also demonstrate how the proposed 2D DFT can be used to approximate the continuous forward and inverse Fourier transform in polar coordinates in the same manner that the 1D DFT can be used to approximate its continuous counterpart.

The way people innovate and create new ideas and bring them to the market is undergoing a fundamental change from closed innovation to open innovation. Why and how do firms perform open innovation? Firms’ open innovation is measured through the levels of firms’ joint patent applications. Next, we analyze network structures and characters of firms’ joint patent applications such as betweenness and degree centrality, structure hole, and closure. From this research, we drew conclusions as follows. First, the structure of collaboration networks has both direct and indirect effects on firms’ innovative performance. Second, in the process of joint patent applications, there is a long tail phenomenon in networks of joint patent applications. Third, the number of patents and International Patent Classification (IPC) subclasses together constitute a meaningful measure of the innovation performance of firms.

The widespread proliferation of sensor nodes in the era of Internet of Things (IoT) coupled with increasing usage of wireless spectrums especially the ISM band makes it difficult to deploy real-life IoT. Currently, the cognitive radio technology enables sensor nodes communicate with each other through the licensed spectrum bands as well as the free ISM bands. Cognitive radio networks (CRSNs) are considered as a promising solution to the problem of spectrum under utilization and artificial radio spectrum scarcity. The paradigm of dynamic spectrum access allows secondary users (SUs) to utilize wireless spectrum resources which belong to primary users (PUs) with minimal interference to PUs. Due to the dynamic spectrum availability and quality, routing for SUs in multi-hop CRSNs is a challenge. In this paper, we introduce novel routing metrics that estimate both the future spectrum availability and the average transmission time with the consideration of both the global statistical spectrum usage and local instant spectrum resources. In our novel routing metrics, one retransmission is allowed and considered to reduce the probability of rerouting upon PU's arrival. Then, we propose two routing algorithms for multi-hop CRSNs. Finally, we conduct simulations, whose results show that our proposed algorithms lead to a significant performance improvement over the reference algorithm.

Current therapeutic strategies targeting cancer cells within solid tumors have displayed limited success owing to the presence of non-cancer components referred to as the tumor stroma within the tumor microenvironment (TM). These stromal cells, extracellular matrix and blood vessels influence cancer cell response to therapy and play key roles in tumor relapse and resistance. Of the stromal cells present in the TM, a lot of attention has been given to cancer-associated fibroblasts (CAFs) as they are the most abundant and are important in cancer initiation, progression and therapy resistance. In this updated review I emphasize the role of CAFs in the regulation of tumor cell behaviour and reveal how CAF-derived factors and signaling influence tumor cell heterogeneity and development of novel strategies to combat cancer. To investigate the expression of CAF markers in tumor tissues versus normal tissues, transcriptomic data from The Cancer Genome Atlas (TCGA) and the Gene Expression Profiling Interactive Analysis (GEPIA) databases was used. Bioinformatic analysis reveals differential expression of CAF markers in several cancer types, underscoring the need for further multiomics and biochemical studies on CAFs, CAF subsets and markers. Differences in CAF markers’ expression could be due to different cellular origins as well as the effect of cancer-specific tumor microenvironmental effect on CAFs. Lastly, I present recent advances in therapeutic targeting of CAFs and the success of such endeavours or its lack thereof. It is recommended that for patients’ outcomes to improve, cancer treatment be combinatorial in nature, targeting both cancer cells and stromal cells and interactions.

The concept of economic self-reliance, widely known by Thai people as the philosophy of sufficiency economy, has been widely promoted in rural Thai societies. By practicing this philosophy, it is expected that the citizens’ quality of life and local environments could be sustainably improved. This study aims to explore the contribution of the community practices of the sufficiency economy philosophy to rural villagers’ quality of life improvement, and to investigate potential factors that determine the trust of villagers in the philosophy. With the purpose to propose strategies which could enhance trust and promote villagers’ practices of the philosophy, the study investigated influences of three relevant factors on trust towards the philosophy. Those factors included factors related to cognitive-based trust, factors related to emotional-based trust, and factors related to demographic characteristics. Questionnaire surveys and in-depth interviews with community leaders and local villagers were conducted in the Ban Jamrung community, in Thailand’s Rayong province. The results of the statistical analysis revealed that the residents who applied the sufficiency economy philosophy in their daily lives experienced a relatively better quality of life. Additionally, it was found that trust in the philosophy could be predicted more by rational factors than by emotional factors. These findings could be utilized to develop strategies to maintain and enhance the trust of the people in the philosophy of sufficiency economy.

Deformation of the surface of diamagnetic liquid by magnetic field is called the “Moses Effect”. Physics and applications of the direct and inverse Moses effects are reviewed. Experimental techniques enabling visualization of the effects are surveyed. Impact of magnetic field on micro- and macroscopic properties of liquids is addressed. Influence of the surface tension on the shape of the near-surface dip formed in a diamagnetic liquid by magnetic field is reported. Floating of diamagnetic bodies driven by the Moses effect is treated. The effect of the “magnetic memory of water” in its relation to the Moses Effect is discussed. The dynamics of self-healing of near-surface dips due to the Moses Effect is considered.

In this project, four of fibers Bragg gratings were fabricated by injecting different volumes of liquids (star line Glass Mechanix optical adhesive material, olive oil diluted with ethanol) into the hollow core fiber. The amplitude splitting interferometric technique with a high resolution specially designed translation stage was used for the fabrication process. The fabrication was done using ultraviolet laser operated at wavelength 405nm. The fabricated Bragg length of the four fibers is equal to 3.8 cm. The results presented fiber Bragg grating (FBG) with successful fabrication at 653.3 nm Bragg reflected wavelength.

Structural health monitoring has been studied by a number of researchers as well as various industries to keep up with the increasing demand for preventive maintenance routines. This work presents a novel method for reconstruct prompt, informed strain/stress responses at the hot spots of the structures based on strain measurements at remote locations. The structural responses measured from usage monitoring system at available locations are decomposed into modal responses using empirical mode decomposition. Transformation equations based on finite element modeling are derived to extrapolate the modal responses from the measured locations to critical locations where direct sensor measurements are not available. Then, two numerical examples (a two-span beam and a 19956-degree of freedom simplified airfoil) are used to demonstrate the overall reconstruction method. Finally, the present work investigates the effectiveness and accuracy of the method through a set of experiments conducted on an aluminium alloy cantilever beam commonly used in air vehicle and spacecraft. The experiments collect the vibration strain signals of the beam via optical fiber sensors. Reconstruction results are compared with theoretical solutions and a detailed error analysis is also provided.

The building envelope has the most significant contribution in the reduction of the building energy consumption. Application of new, alternative and improved materials and systems has an important impact on the buildings performances. This paper is focused on the thermal transmittance, as an indicator of the thermal conductance of the construction element. It includes comparisons of the U-values, calculated by software, with those measured in situ on three representative façade walls. The walls have been constructed with the new wall system Fragmat NZ-1, a new product in Macedonian buildings. This research provides basic information on the thermal transmittance of the system. The results of the analysis show that the in situ measuring is a useful tool in validation of the precision of analytically calculated values, since it was difficult to obtain precise results from the analytical calculations only, especially when the layers are with non-uniform thickness.