Search results for: school based support program

Authors: Mina Iskander, Mina Melad, Mourad Yasser, Waleed Abdel Rahim, Amr Mosa, Mohamed El Lahamy, Ezzeldin Sayed-Ahmed, Mohamed Abou-Zeid

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Strengthening of reinforced concrete beams in flexure using externally bonded composite laminate of high tensile strength is easy and of the minimum cost compared to traditional methods such as increasing the concrete section depth or reinforcement that requires formwork and curing which affect the structure usability. One of the main limitations of this technique is debonding of the externally bonded laminate, either by end delamination or by mid-span flexural crack-induced debonding. ACI 440.2-08 suggests that using side-bonded FRP laminate in the flexural strengthening of RC beams may serve to limit the extent and width of flexural cracks. Consequently, this technique may decrease the effect of flexural cracks on initiating the mid-span debonding; i.e. delays the flexural crack-induced debonding. Furthermore, bonding the FRP strips to the side of the beam may offer an attractive, practical solution when the soffit of this beam is not accessible. This paper presents an experimental programme designed to investigate the effect of using externally bonded CFRP laminate on the sides of reinforced concrete beams and compares the results to those of bonding the CFRP laminate to the soffit of the beams. In addition, the paper discusses the effect of using end anchorage by U-wrapping the CFRP strips at their end zones with CFRP sheets for beams strengthened with soffit-bonded and side-bonded CFRP strips. Thus, ten rectangular reinforced concrete beams were tested to failure in order to study the effect of changing the location of the externally bonded laminate on the flexural capacity and ductility of the strengthened beams. Pultruded CFRP strips were bonded to the soffit of the beams or their sides to check the possibility of limiting the flexural cracking in mid-span region, which is the main reason for mid-span debonding. Pre-peg CFRP sheets were used near the support as U-wrap for the beam to act as an end-anchorage for the externally bonded strips in order to delay/prevent the end delamination. Strength gains of 38% and 43% were recorded for the soffit-bonded and the side-bonded composite strips with end U-wrapped sheets, respectively. Furthermore, beams with end sheets applied as an end anchorage showed higher ductility than those without these sheets.

Keywords: flexural strengthening, externally bonded CFRP, side-bonded CFRP, CFRP laminates

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Authors: Nuno Da Camara, Victor Dulewicz, Malcolm Higgs

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Factors on employee engagement: In particular, although theorists have described the critical role of emotional cognition of the workplace environment as antecedents to employee engagement, empirical research on the impact of emotional cognition on employee engagement is limited. However, previous researchers have typically provided evidence of the link between emotional cognition of the workplace environment and workplace attitudes such as job satisfaction and organisational commitment. This study therefore aims to investigate the impact of emotional cognition of job, role, leader and organisation domains of the work environment – as represented by measures of psychological climate and organizational emotional intelligence (OEI) - on employee engagement. The research is based on a quantitative cross-sectional survey of employees in a UK charity organization (n=174). The research instruments applied include the psychological climate scale, the organisational emotional intelligence questionnaire (OEIQ) and the Utrecht Work Engagement Scale (UWES). The data were analysed using hierarchical regression and partial least squares (PLS) analytical techniques. The results of the study show that both psychological climate and OEI, which represent emotional cognition of job, role, leader and organisation domains in the workplace are significant drivers of employee engagement. In particular, the study found that a sense of contribution and challenge at work are the strongest drivers of vigour, dedication and absorption and highlights the importance of emotionally relevant approaches in furthering our understanding of workplace engagement.

Keywords: employee engagement, organisational emotional intelligence, psychological climate, workplace attitudes

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Authors: Soebowo Musa

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Mining industries are known to be very volatile due to their sensitive nature toward changes in the environment, particularly coal mining. Heavy equipment distributors and coal mining contractors are among heavily affected by such volatility. They are facing more uncertainty on the sustainability of the coal mining industry. Strategic alliances and organizational capabilities such as innovation capability have long been seen as ways to stay competitive with a focus more on the strategic alliances partner-to-partner in serving their customers. In today’s rapid change in the environment, a shift in consumer behaviors, and the human-centric business approach, this study looks at the strategic alliance partner-to-customer relationship in both the industrial organization and resource-based theories. This study was conducted based on 250 respondents from the strategic alliances partner-to-customer between heavy equipment distributors and coal mining contractors in Indonesia. This study finds strategic alliances have the highest association toward cost reduction, a proxy of operational efficiency followed by its association toward innovation capability. Further, strategic alliances and innovation capability have a positive relationship with customer loyalty, while innovation capability and customer loyalty have no significant relationships toward the firm’s competitive advantage. This study also indicates that cost reduction is not a condition to develop customer loyalty in the strategic alliance partner-to-customer relationship. It confirms strategic alliances are a strategy that creates a firm’s operational efficiency, innovation capability that develops customer loyalty, and competitive advantage.

Keywords: strategic alliance, innovation capability, cost reduction, customer loyalty, competitive advantage

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Authors: Theresa K., Shanmugasundaram R., Kennedy J. S.

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Nutrient supplements are indispensable for raising crops and to reap determining productivity. The nutrient imbalance between replenishment and crop uptake is attempted through the input of inorganic fertilizers. Excessive dumping of inorganic nutrients in soil cause stagnant and decline in yield. Imbalanced N-P-K ratio in the soil exacerbates and agitates the soil ecosystems. The study evaluated the fertilization practices of conventional (CFs), organic and Integrated Nutrient Management system (INM) on soil quality using key indicators and soil quality indices. Twelve rice farming fields of which, ten fields were having conventional cultivation practices, one field each was organic farming based and INM based cultivated under monocropping sequence in the Thondamuthur block of Coimbatore district were fixed and properties viz., physical, chemical and biological were studied for four cropping seasons to determine soil quality index (SQI). SQI was computed for conventional, organic and INM fields. Comparing conventional farming (CF) with organic and INM, CF was recorded with a lower soil quality index. While in organic and INM fields, the higher SQI value of 0.99 and 0.88 respectively were registered. CF₄ received with a super-optimal dose of N (250%) showed a lesser SQI value (0.573) as well as the yield (3.20 t ha⁻¹) and the CF6 which received 125 % N recorded the highest SQI (0.715) and yield (6.20 t ha⁻¹). Likewise, most of the CFs received higher N beyond the level of 125 % except CF₃ and CF₉, which recorded lower yields. CFs which received super-optimal P in the order of CF₆&CF₇>CF₁&CF₁₀ recorded lesser yields except for CF₆. Super-optimal K application also recorded lesser yield in CF₄, CF₇ and CF₉.

Keywords: rice cropping system, soil quality indicators, imbalanced fertilization, yield

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Authors: Farhad Salek, Shahaboddin Resalati

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The production of electric vehicles (EVs) featuring lithium-ion battery technology has substantially escalated over the past decade, demonstrating a steady and persistent upward trajectory. The imminent retirement of electric vehicle (EV) batteries after approximately eight years underscores the critical need for their redirection towards recycling, a task complicated by the current inadequacy of recycling infrastructures globally. A potential solution for such concerns involves extending the operational lifespan of electric vehicle (EV) batteries through their utilization in stationary energy storage systems during secondary applications. Such adoptions, however, require addressing the safety concerns associated with batteries’ knee points and thermal runaways. This paper develops an accurate mathematical model representative of the second-life battery packs from a cell-to-pack scale using an equivalent circuit model (ECM) methodology. Neural network algorithms are employed to forecast the degradation parameters based on the EV batteries' aging history to develop a degradation model. The degradation model is integrated with the ECM to reflect the impacts of the cycle aging mechanism on battery parameters during operation. The developed model is tested under real-life load profiles to evaluate the life span of the batteries in various operating conditions. The methodology and the algorithms introduced in this paper can be considered the basis for Battery Management System (BMS) design and techno-economic analysis of such technologies.

Keywords: second life battery, electric vehicles, degradation, neural network

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Authors: Hung Hing Chan, Tai-Shan Hu

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Kaohsiung has been an industrial city of Taiwan for over a hundred year. Consequently, there are several abandoned industrial lands left when the process of deindustrialization has started, resulting in the decay of the adjacent urban communities. These industrial lands, which are brownfields that are potentially or already contaminated by hazardous substances, have created social injustice to the surrounding communities. The redevelopments of industrial lands bring a sustainable development to the communities, while the redevelopments can be in different forms, depending on the natural conditions. This research studies the possible approaches to facilitate social sustainability of urban regeneration resulted from the industrial land redevelopment projects, which has always been ignored. The aim of the research is to find out the best western practices of brownfield redevelopment to facilitate social aspect of sustainable urban regeneration and make a contribution to the industrial land redevelopment of Taiwan. The research is conducted via literature review and case study. Industrial land redevelopment has been a social focus in the blighted communities to promote urban regeneration after the post-industrial age. The tendency of this kind of redevelopment is towards constructing the built environment, as a result the environmental and economic aspect of sustainability of the redeveloped industrial land will be boosted, while the social aspect will not be necessarily better since the local communities affected are rarely engaged in the decision-making process and inadequate resource allocation to the projects is not guaranteed. To ensure the improvement of social sustainability is reached, the recommendations of this research, such as civic engagement, a formation of dedicated brownfield regeneration agency and resource allocation to employ brownfield process manager and to strategic communication, should be incorporated into the real practices of industrial land-led urban regeneration. Besides, the case study also shows that the social sustainability of industrial land-led urban regeneration can be promoted by (1) upholding the local feature and public participation in the regeneration process, (2) allocating resources and enforcing responsibility system, and (3) assuring financial resource for the urban regeneration projects and residents. Subsequent research will involve in-depth interviews with the chiefs of the village of related communities in Kaohsiung and questionnaire with the community members to comprehend their opinions regarding social sustainability, aiming at evaluating the social sustainability and finding out which kind of redevelopment project tends to support the social dimension of sustainable development more.

Keywords: brownfield, industrial land, redevelopment, social sustainability, urban regeneration

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Authors: Alireza Naseri, Susan L. Holdt, Charlotte Jacobsen

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In 2014, the global amount of carrageenan production was 60,000 ton with a value of US$ 626 million. From this number, it can be estimated that the total dried seaweed consumption for this production was at least 300,000 ton/year. The protein content of these types of seaweed is 5 – 25%. If just half of this total amount of protein could be extracted, 18,000 ton/year of a high-value protein product would be obtained. The overall aim of this study was to develop a technology that will ensure further utilization of the seaweed that is used only as raw materials for carrageenan production as single extraction at present. More specifically, proteins should be extracted from the seaweed either before or after extraction of carrageenan with focus on maintaining the quality of carrageenan as a main product. Different mechanical, chemical and enzymatic technologies were evaluated. The optimized process was implemented in lab scale and based on its results; the new experiments were done a pilot and larger scale. In order to calculate the efficiency of the new upstream multi-extraction process, protein content was tested before and after extraction. After this step, the extraction of carrageenan was done and carrageenan content and the effect of extraction on yield were evaluated. The functionality and quality of carrageenan were measured based on rheological parameters. The results showed that by using the new multi-extraction process (submitted patent); it is possible to extract almost 50% of total protein without any negative impact on the carrageenan quality. Moreover, compared to the routine carrageenan extraction process, the new multi-extraction process could increase the yield of carrageenan and the rheological properties such as gel strength in the final carrageenan had a promising improvement. The extracted protein has initially been screened as a plant protein source in typical food applications. Further work will be carried out in order to improve properties such as color, solubility, and taste.

Keywords: carrageenan, extraction, protein, seaweed

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Authors: Julia R. Beulig, Stefan Ohla, Detlev Belder

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In contrast to off-line analytical methods, lab-on-a-chip technology delivers direct information about the observed reaction. Therefore, microfluidic devices make an important scientific contribution, e.g. in the field of synthetic chemistry. Herein, the rapid generation of analytical data can be applied for the optimization of chemical reactions. These microfluidic devices enable a fast change of reaction conditions as well as a resource saving method of operation. In the presented work, we focus on the investigation of multiphase regimes, more specifically on a biphasic microfluidic droplet systems. Here, every single droplet is a reaction container with customized conditions. The biggest challenge is the rapid qualitative and quantitative readout of information as most detection techniques for droplet systems are non-specific, time-consuming or too slow. An exception is the electrospray mass spectrometry (ESI-MS). The combination of a reaction screening platform with a rapid and specific detection method is an important step in droplet-based microfluidics. In this work, we present a novel approach for synthesis optimization on the nanoliter scale with direct ESI-MS detection. The development of a droplet-based microfluidic device, which enables the modification of different parameters while simultaneously monitoring the effect on the reaction within a single run, is shown. By common soft- and photolithographic techniques a polydimethylsiloxane (PDMS) microfluidic chip with different functionalities is developed. As an interface for the MS detection, we use a steel capillary for ESI and improve the spray stability with a Teflon siphon tubing, which is inserted underneath the steel capillary. By optimizing the flow rates, it is possible to screen parameters of various reactions, this is exemplarity shown by a Domino Knoevenagel Hetero-Diels-Alder reaction. Different starting materials, catalyst concentrations and solvent compositions are investigated. Due to the high repetition rate of the droplet production, each set of reaction condition is examined hundreds of times. As a result, of the investigation, we receive possible reagents, the ideal water-methanol ratio of the solvent and the most effective catalyst concentration. The developed system can help to determine important information about the optimal parameters of a reaction within a short time. With this novel tool, we make an important step on the field of combining droplet-based microfluidics with organic reaction screening.

Keywords: droplet, mass spectrometry, microfluidics, organic reaction, screening

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Authors: Hao Wang, Shuguo Pan

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The Global Navigation Satellite System (GNSS) signal received by the dynamic vehicle in the harsh environment will be frequently interfered with and blocked, which generates gross error affecting the positioning accuracy of the GNSS/Inertial Navigation System (INS) integrated navigation. Therefore, this paper put forward an improved robust Cubature Kalman filter (CKF) algorithm for single-frequency GNSS/INS tightly coupled system ambiguity resolution. Firstly, the dynamic model and measurement model of a single-frequency GNSS/INS tightly coupled system was established, and the method for GNSS integer ambiguity resolution with INS aided is studied. Then, we analyzed the influence of pseudo-range observation with gross error on GNSS/INS integrated positioning accuracy. To reduce the influence of outliers, this paper improved the CKF algorithm and realized an intelligent selection of robust strategies by judging the ill-conditioned matrix. Finally, a field navigation test was performed to demonstrate the effectiveness of the proposed algorithm based on the double-differenced solution mode. The experiment has proved the improved robust algorithm can greatly weaken the influence of separate, continuous, and hybrid observation anomalies for enhancing the reliability and accuracy of GNSS/INS tightly coupled navigation solutions.

Keywords: GNSS/INS integrated navigation, ambiguity resolution, Cubature Kalman filter, Robust algorithm

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Authors: Said Alshukri, Mazhar Hussain Malik

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Green hydrogen is hydrogen produced using renewable energy sources. In the last few years, Oman aimed to reduce its dependency on fossil fuels. Recently, the hydrogen economy has become a global trend, and many countries have started to investigate the feasibility of implementing this sector. Oman created an alliance to establish the policy and rules for this sector. With motivation coming from both global and local interest in green hydrogen, this paper investigates the potential of producing hydrogen from wind and solar energies in three different locations in Oman, namely Duqm, Salalah, and Sohar. By using machine learning-based software “WEKA” and local metrological data, the project was designed to figure out which location has the highest wind and solar energy potential. First, various supervised models were tested to obtain their prediction accuracy, and it was found that the Random Forest (RF) model has the best prediction performance. The RF model was applied to 2021 metrological data for each location, and the results indicated that Duqm has the highest wind and solar energy potential. The system of one wind turbine in Duqm can produce 8335 MWh/year, which could be utilized in the water electrolysis process to produce 88847 kg of hydrogen mass, while a solar system consisting of 2820 solar cells is estimated to produce 1666.223 MWh/ year which is capable of producing 177591 kg of hydrogen mass.

Keywords: green hydrogen, machine learning, wind and solar energies, WEKA, supervised models, random forest

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Authors: Kseniia Zviagintseva, Brett Buttliere

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Science is fundamentally a problem-solving enterprise, and scientists pay more attention to the negative things, that cause them dissonance and negative affective state of uncertainty or contradiction. While this is agreed upon by philosophers of science, there are few empirical demonstrations. Here we examine the keywords from those papers published by PLoS in 2014 and show with several sentiment analyzers that negative keywords are studied more than positive keywords. Our dataset is the 927,406 keywords of 32,870 scientific articles in all fields published in 2014 by the journal PLOS ONE (collected from Altmetric.com). Counting how often the 47,415 unique keywords are used, we can examine whether those negative topics are studied more than positive. In order to find the sentiment of the keywords, we utilized two sentiment analysis tools, Hu and Liu (2004) and SentiStrength (2014). The results below are for Hu and Liu as these are the less convincing results. The average keyword was utilized 19.56 times, with half of the keywords being utilized only 1 time and the maximum number of uses being 18,589 times. The keywords identified as negative were utilized 37.39 times, on average, with the positive keywords being utilized 14.72 times and the neutral keywords - 19.29, on average. This difference is only marginally significant, with an F value of 2.82, with a p of .05, but one must keep in mind that more than half of the keywords are utilized only 1 time, artificially increasing the variance and driving the effect size down. To examine more closely, we looked at those top 25 most utilized keywords that have a sentiment. Among the top 25, there are only two positive words, ‘care’ and ‘dynamics’, in position numbers 5 and 13 respectively, with all the rest being identified as negative. ‘Diseases’ is the most studied keyword with 8,790 uses, with ‘cancer’ and ‘infectious’ being the second and fourth most utilized sentiment-laden keywords. The sentiment analysis is not perfect though, as the words ‘diseases’ and ‘disease’ are split by taking 1st and 3rd positions. Combining them, they remain as the most common sentiment-laden keyword, being utilized 13,236 times. More than just splitting the words, the sentiment analyzer logs ‘regression’ and ‘rat’ as negative, and these should probably be considered false positives. Despite these potential problems, the effect is apparent, as even the positive keywords like ‘care’ could or should be considered negative, since this word is most commonly utilized as a part of ‘health care’, ‘critical care’ or ‘quality of care’ and generally associated with how to improve it. All in all, the results suggest that negative concepts are studied more, also providing support for the notion that science is most generally a problem-solving enterprise. The results also provide evidence that negativity and contradiction are related to greater productivity and positive outcomes.

Keywords: bibliometrics, keywords analysis, negativity bias, positive and negative words, scientific papers, scientometrics

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Authors: Emmanuel Abban Sagoe

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A proper functioning of the Central Nervous System ensures that we are able to accomplish just about everything we do as human beings such as walking, breathing, running, etc. Myelinated neurons throughout the body which transmit signals at high speeds facilitate these actions. In the case of MS, the body’s immune system attacks the myelin sheath surrounding the neurons and overtime destroys the myelin sheaths. Depending upon where the destruction occurs in the brain symptoms can vary from person to person. Fatigue is, however, the biggest problem encountered by an MS sufferer. It is very often described as the bedrock upon which other symptoms of MS such challenges in balance and coordination, dizziness, slurred speech, etc. may occur. Classifying and distinguishing between perceptions based fatigue and performance based fatigability is key to identifying appropriate treatment options for patients. Objective methods for assessing motor fatigability is also key to providing clinicians and physiotherapist with critical information on the progression of the symptom. This study tested if the Fatigue Index Kliniken Schmieder assessment tool can detect fatigability as seen in MS patients when healthy subjects with no known history of neurological pathology mimic abnormal gaits. Thirty three healthy adults between ages 18-58years volunteered as subjects for the study. The subjects, strapped with RehaWatch sensors on both feet, completed 6 gait protocols of normal and mimicked fatigable gaits for 60 seconds per each gait and at 1.38889m/s treadmill speed following clear instructions given.

Keywords: attractor attributes, fatigue index Kliniken Schmieder, gait variability, movement pattern

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Authors: Bercem Kiran-Yildirim, Volker Gaukel

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Ice recrystallization (IR) which occurs especially during frozen storage is an undesired process due to the possible influence on the quality of products. As a result of recrystallization, the total volume of ice remains constant, but the size, number, and shape of ice crystals change. For instance, as indicated in the literature, the size of ice crystals in ice cream increases due to recrystallization. This results in texture deterioration. Therefore, the inhibition of ice recrystallization is of great importance, not only for food industry but also for several other areas where sensitive products are stored frozen, like pharmaceutical products or organs and blood in medicine. Ice-binding proteins (IBPs) have the unique ability to inhibit ice growth and in consequence inhibit recrystallization. This effect is based on their ice binding affinity. In the presence of IBP in a solution, ice crystal growth is inhibited during temperature decrease until a certain temperature is reached. The melting during temperature increase is not influenced. The gap between melting and freezing points is known as thermal hysteresis (TH). In literature, the TH activity is usually investigated under laboratory conditions in IBP buffer solutions. In product applications (e.g., food) there are many other solutes present which may influence the TH activity. In this study, a subset of IBPs, so-called antifreeze proteins (AFPs), is used for the investigation of the influence of sucrose solution concentration on the TH activity. For the investigation, a polarization microscope (Nikon Eclipse LV100ND) equipped with a digital camera (Nikon DS-Ri1) and a cold stage (Linkam LTS420) was used. In a first step, the equipment was established and validated concerning the accuracy of TH measurements based on literature data.

Keywords: ice binding proteins, ice crystals, sucrose solution, thermal hysteresis

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Authors: Seyed Hossein Hosseini, Seyed Majid Hashemzadeh

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Solar energy is one of the remarkable renewable energy sources that have particular characteristics such as unlimited, no environmental pollution, and free access. Generally, solar energy can be used in thermal and photovoltaic (PV) types. The cost of installation of the PV system is very high. Additionally, due to dependence on environmental situations such as solar radiation and ambient temperature, electrical power generation of this system is unpredictable and without power electronics devices, there is no guarantee to maximum power delivery at the output of this system. Maximum power point tracking (MPPT) should be used to achieve the maximum power of a PV string. MPPT is one of the essential parts of the PV system which without this section, it would be impossible to reach the maximum amount of the PV string power and high losses are caused in the PV system. One of the noticeable challenges in the problem of MPPT is the partial shading conditions (PSC). In PSC, the output photocurrent of the PV module under the shadow is less than the PV string current. The difference between the mentioned currents passes from the module's internal parallel resistance and creates a large negative voltage across shaded modules. This significant negative voltage damages the PV module under the shadow. This condition is called hot-spot phenomenon. An anti-paralleled diode is inserted across the PV module to prevent the happening of this phenomenon. This diode is known as the bypass diode. Due to the performance of the bypass diode under PSC, the P-V curve of the PV string has several peaks. One of the P-V curve peaks that makes the maximum available power is the global peak. Model-based Global MPPT (GMPPT) methods can estimate the optimal point with higher speed than other GMPPT approaches. Centralized, modular, and interleaved DC-DC converter topologies are the significant structures that can be used for GMPPT at a PV string. there are some problems in the centralized structure such as current mismatch losses at PV sting, loss of power of the shaded modules because of bypassing by bypass diodes under PSC, needing to series connection of many PV modules to reach the desired voltage level. In the modular structure, each PV module is connected to a DC-DC converter. In this structure, by increasing the amount of demanded power from the PV string, the number of DC-DC converters that are used at the PV system will increase. As a result, the cost of the modular structure is very high. We can implement the model-based GMPPT through the multi-input interleaved boost DC-DC converter to increase the power extraction from the PV string and reduce hot-spot and current mismatch error in a PV string under different environmental condition and variable load circumstances. The interleaved boost DC-DC converter has many privileges than other mentioned structures, such as high reliability and efficiency, better regulation of DC voltage at DC link, overcome the notable errors such as module's current mismatch and hot spot phenomenon, and power switches voltage stress reduction.

Keywords: solar energy, photovoltaic systems, interleaved boost converter, maximum power point tracking, model-based method, partial shading conditions

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Authors: Pauline Cuenin, Marcelo Leles Romarco Oliveira

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Based on their localities and following their ecological rationality, family-based farmers have experimented, adapted and innovated to improve their production systems continuously for millennia. With the technological package transfer processes of the so-called Green Revolution for agricultural holdings, farmers have become increasingly dependent on ready-made "recipes" built from so-called "universal" and global knowledge to face the problems that emerge in the management of local agroecosystems, thus reducing their creative and experiential capacities. However, the production of novelties within farms is fundamental to the transition to more sustainable agro food systems. In fact, as the fruits of local knowledge and / or the contextualization of exogenous knowledge, novelties are seen as seeds of transition. By presenting new techniques, new organizational forms and epistemological approaches, agroecology was pointed out as a way to encourage and promote the creative capacity of farmers. From this perspective, this theoretical work aims to analyze how agroecology encourages the innovative capacity of farmers, and in general, the production of novelties. For this, an analysis was made of the theoretical and methodological bases of agroecology through a literature review, specifically looking for the way in which it articulates the local with the global, complemented by an analysis of agro ecological Brazilian experiences. It was emphasized that, based on the peasant way of doing agriculture, that is, on ecological / social co-evolution or still called co-production (interaction between human beings and living nature), agroecology recognizes and revalues peasant involves the deep interactions of the farmer with his site (bio-physical and social). As a "place science," practice and movement, it specifically takes into consideration the local and empirical knowledge of farmers, which allows questioning and modifying the paradigms that underpin the current agriculture that have disintegrated farmers' creative processes. In addition to upgrade the local, agroecology allows the dialogue of local knowledge with global knowledge, essential in the process of changes to get out of the dominant logic of thought and give shape to new experiences. In order to reach this articulation, agroecology involves new methodological focuses seeking participatory methods of study and intervention that express themselves in the form of horizontal spaces of socialization and collective learning that involve several actors with different knowledge. These processes promoted by agroecology favor the production of novelties at local levels for expansion at other levels, such as the global, through trans local agro ecological networks.

Keywords: agroecology, creativity, global, local, novelty

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Authors: Carin Chuang, Kuan-Chou Chen

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An Enterprise Resource Planning (ERP) system is an integrated information system that supports the seamless integration of all the business processes of a company. Implementing an ERP system can increase efficiencies and decrease the costs while helping improve productivity. Many organizations including large, medium and small-sized companies have already adopted an ERP system for decades. Although ERP system can bring competitive advantages to organizations, the lack of proper training approach in ERP implementation is still a major concern. Organizations understand the importance of ERP training to adequately prepare managers and users. The low return on investment, however, for the ERP training makes the training difficult for knowledgeable workers to transfer what is learned in training to the jobs at workplace. Inadequate and inefficient ERP training limits the value realization and success of an ERP system. That is the need to call for a profound change and innovation for ERP training in both workplace at industry and the Information Systems (IS) education in academia. The innovated ERP training approach can improve the users’ knowledge in business processes and hands-on skills in mastering ERP system. It also can be instructed as educational material for IS students in universities. The purpose of the study is to examine the use of ERP simulation games via the ERPsim system to train the IS students in learning ERP implementation. The ERPsim is the business simulation game developed by ERPsim Lab at HEC Montréal, and the game is a real-life SAP (Systems Applications and Products) ERP system. The training uses the ERPsim system as the tool for the Internet-based simulation games and is designed as online student competitions during the class. The competitions involve student teams with the facilitation of instructor and put the students’ business skills to the test via intensive simulation games on a real-world SAP ERP system. The teams run the full business cycle of a manufacturing company while interacting with suppliers, vendors, and customers through sending and receiving orders, delivering products and completing the entire cash-to-cash cycle. To learn a range of business skills, student needs to adopt individual business role and make business decisions around the products and business processes. Based on the training experiences learned from rounds of business simulations, the findings show that learners have reduced risk in making mistakes that help learners build self-confidence in problem-solving. In addition, the learners’ reflections from their mistakes can speculate the root causes of the problems and further improve the efficiency of the training. ERP instructors teaching with the innovative approach report significant improvements in student evaluation, learner motivation, attendance, engagement as well as increased learner technology competency. The findings of the study can provide ERP instructors with guidelines to create an effective learning environment and can be transferred to a variety of other educational fields in which trainers are migrating towards a more active learning approach.

Keywords: business simulations, ERP implementation training, ERPsim, game-based learning, instructional strategy, training innovation

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Authors: N. N. Pandey, Raghvendra Singh, Biju S. Kamlam, Bipin K. Vishwakarma, Preetam Kala

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The rainbow trout (Oncorhynchus mykiss) is an exotic salmonid fish, well known for its fast growth, tremendous ability to thrive in diverse conditions, delicious flesh and hard fighting nature in Europe and other countries. Rainbow trout farming has a great potential for its contribution to the mainstream economy of Himalayan states in India and other temperate countries. These characteristics establish them as one of the most widely introduced and cultured fish across the globe, and its farming is also prominent in the cold water regions of India. Nevertheless, genetic fatigue, slow growth, early maturity, and low productivity are limiting the expansion of trout production. Moreover, farms adjacent to natural streams or other water sources are subject to escape of domesticated rainbow trout into the wild, which is a serious environmental concern as the escaped fish is subject to contaminate and disrupt the receiving ecosystem. A decline in production traits due to early maturity prolongs the culture duration and affects the profit margin of rainbow trout farms in India. A viable strategy that could overcome these farming constraints in large scale operation is the production of triploid fish that are sterile and more heterozygous. For better triploidy induction rate (TR), heat shock at 28°C for 10 minutes and pressure shock 9500 psi pressure for 5 minutes is applied to green eggs with 90-100% of triploidy success and 72-80% survival upto swim-up fry stage. There is 20% better growth in aquaculture with triploids rainbow trout over diploids. As compared to wild diploid fish, larger sized and fitter triploid rainbow trout in natural waters attract to trout anglers, and support the development of recreational fisheries by state fisheries departments without the risk of contaminating existing gene pools and disrupting local fish diversity. Overall, enhancement of productivity in rainbow trout farms and trout production in coldwater regions, development of lucrative trout angling and better ecological management is feasible with triploid rainbow trout.

Keywords: rainbow trout, triploids fish, heat shock, pressure shock, trout angling

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Authors: Jacintha Menezes, Ramalingam Dharmalingam, Palaiahnakote Shivakumara

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In the recent years, Omani acid lime cultivation and production has been affected by Citrus greening or Huanglongbing (HLB) disease. HLB disease is one of the most destructive diseases for citrus, with no remedies or countermeasures to stop the disease. Currently used Polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) HLB detection tests require lengthy and labor-intensive laboratory procedures. Furthermore, the equipment and staff needed to carry out the laboratory procedures are frequently specialized hence making them a less optimal solution for the detection of the disease. The current research uses hyperspectral imaging technology for automatic detection of citrus trees with HLB disease. Omani citrus tree leaf images were captured through portable Specim IQ hyperspectral camera. The research considered healthy, nutrition deficient, and HLB infected leaf samples based on the Polymerase chain reaction (PCR) test. The highresolution image samples were sliced to into sub cubes. The sub cubes were further processed to obtain RGB images with spatial features. Similarly, RGB spectral slices were obtained through a moving window on the wavelength. The resized spectral-Spatial RGB images were given to Convolution Neural Networks for deep features extraction. The current research was able to classify a given sample to the appropriate class with 92.86% accuracy indicating the effectiveness of the proposed techniques. The significant bands with a difference in three types of leaves are found to be 560nm, 678nm, 726 nm and 750nm.

Keywords: huanglongbing (HLB), hyperspectral imaging (HSI), · omani citrus, CNN

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Authors: Paolino Di Felice

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The background and significance of this study come from papers already appeared in the literature which measured the impact of public services (e.g., hospitals, schools, ...) on the citizens’ needs satisfaction (one of the dimensions of QOL studies) by calculating the distance between the place where they live and the location on the territory of the services. Those studies assume that the citizens' dwelling coincides with the centroid of the polygon that expresses the boundary of the administrative district, within the city, they belong to. Such an assumption “introduces a maximum measurement error equal to the greatest distance between the centroid and the border of the administrative district.”. The case study, this abstract reports about, investigates the implications descending from the adoption of such an approach but at geographical scales greater than the urban one, namely at the three levels of nesting of the Italian administrative units: the (20) regions, the (110) provinces, and the 8,094 municipalities. To carry out this study, it needs to be decided: a) how to store the huge amount of (spatial and descriptive) input data and b) how to process them. The latter aspect involves: b.1) the design of algorithms to investigate the geometry of the boundary of the Italian administrative units; b.2) their coding in a programming language; b.3) their execution and, eventually, b.4) archiving the results in a permanent support. The IT solution we implemented is centered around a (PostgreSQL/PostGIS) Geo DataBase structured in terms of three tables that fit well to the hierarchy of nesting of the Italian administrative units: municipality(id, name, provinceId, istatCode, regionId, geometry) province(id, name, regionId, geometry) region(id, name, geometry). The adoption of the DBMS technology allows us to implement the steps "a)" and "b)" easily. In particular, step "b)" is simplified dramatically by calling spatial operators and spatial built-in User Defined Functions within SQL queries against the Geo DB. The major findings coming from our experiments can be summarized as follows. The approximation that, on the average, descends from assimilating the residence of the citizens with the centroid of the administrative unit of reference is of few kilometers (4.9) at the municipalities level, while it becomes conspicuous at the other two levels (28.9 and 36.1, respectively). Therefore, studies such as those mentioned above can be extended up to the municipal level without affecting the correctness of the interpretation of the results, but not further. The IT framework implemented to carry out the experiments can be replicated for studies referring to the territory of other countries all over the world.

Keywords: quality of life, distance measurement error, Italian administrative units, spatial database

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Authors: Jasna Milošević Đorđević, Jelisaveta Blagojević, Jovana Timotijević, Alison Mckinley

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Young people in Serbia, have grown up in turbulent times during the Balkan wars, in a cultural and economic isolation without adequate education on (ethnic, gender, social,..) equality. They often have very strong patriarchal gender stereotypes. The perception of gender in Serbia is still heavily influenced by traditional worldview and young people have little opportunity in traditional educational system to challenge it, receiving no formal sex education. Educational policies have addressed achieving gender equality as one of the goals, supporting all young people to gain better educational opportunities, but there are obvious shortcomings of the official education system in implementation of those goals. Therefore new approaches should be implemented. We evaluate the impact of non traditional approach, such as participatory theatre performance with strong transformative potential, especially in relation to gender issues. Theatre based intervention (TBI) was created to provoke the young people to become aware of their gender constructs. Engaging young people in modern form of education such as transformative gender intervention through participatory theatre could have positive impact on their sex knowledge and understanding gender roles. The transformative process in TBI happens on two levels – the affective and the cognitive. The founding agency of the project and evaluation is IPPF. The most important aim of this survey is evaluation of the transformative TBI, as a new educational approach related to better understanding gender as social construct. To reach this goal, we have measured attitude change in three indicators: a) gender identity/ perception of feminine identity, perception of masculine identity, importance of gender for personal identity, b) gender roles on the labor market, c) Gender equality in partnership & sexual behavior. Our main hypothesis is that participatory theatre-based intervention can have a transformational potential in challenging traditional gender knowledge and attitudes among youth in Serbia. To evaluate the impact of TB intervention, we implement: online baseline and end-line survey with nonparticipants of the TBI on the representative sample in targeted towns (control group). Additionally we conducted testing the experimental group twice: pretest at the beginning of each TBI and post testing of participants after the play. A sample of 500 respondents aged 18-30 years, from 9 towns in Serbia responded to online questionnaire in September 2017, in a baseline research. Pre and post measurement of all tested variables among participants in nine towns would be performed. End-line survey with 500 respondents would be conducted at the end of the project (early year 2018). After the first TBI (60 participants) no impact was detected on measured indicators: perception of desirable characteristics of man F(1,59)= 1.291, p=.260; perception of desirable characteristics of women F(1,55)=1.386, p= .244; gender identity importance F(1,63)= .050, p=.824; sex related behavior F(1,61)=1,145, p=.289; gender equality on labor market F(1,63)=.076, p=.783; gender equality in partnership F(1,61)=.201, p=.656; However, we hope that following intervention would bring more data showing that participatory theatre intervention explaining gender as a social construct could have additional positive impact in traditional educational system.

Keywords: educational impact, gender identity, gender role, participatory theatre based intervention

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Authors: Carlos Roberto De Rolt, Julio da Silva Dias, Rafael Tezza, Luca Foschini, Matteo Mura

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The seasonal population fluctuation presents a challenge to touristic cities since the number of inhabitants can double according to the season. The aim of this work is to develop a model that correlates the waste collected with the population of the city and also allow cooperation between the inhabitants and the local government. The model allows public managers to evaluate the impact of the seasonal population fluctuation on waste generation and also to improve planning resource utilization throughout the year. The study uses data from the company that collects the garbage in Florianópolis, a Brazilian city that presents the profile of a city that attracts tourists due to numerous beaches and warm weather. The fluctuations are caused by the number of people that come to the city throughout the year for holidays, summer time vacations or business events. Crowdsensing will be accomplished through smartphones with access to an app for data collection, with voluntary participation of the population. Crowdsensing participants can access information collected in waves for this portal. Crowdsensing represents an innovative and participatory approach which involves the population in gathering information to improve the quality of life. The management of crowdsensing solutions plays an essential role given the complexity to foster collaboration, establish available sensors and collect and process the collected data. Practical implications of this tool described in this paper refer, for example, to the management of seasonal tourism in a large municipality, whose public services are impacted by the floating of the population. Crowdsensing and big data support managers in predicting the arrival, permanence, and movement of people in a given urban area. Also, by linking crowdsourced data to databases from other public service providers - e.g., water, garbage collection, electricity, public transport, telecommunications - it is possible to estimate the floating of the population of an urban area affected by seasonal tourism. This approach supports the municipality in increasing the effectiveness of resource allocation while, at the same time, increasing the quality of the service as perceived by citizens and tourists.

Keywords: big data, dashboards, floating population, smart city, urban management solutions

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Authors: Nane Giloyan

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The rapid development of social networks in the 21st century increases the interests towards the role and impact of social media on the success or failure of a revolution. Even though studies are investigating the role of social media on the outcome of a revolution, still, the conclusions on this matter are ambiguous so far. Hence, this research aims to investigate the role of social media in the success or failure of a revolution and make a contribution to the literature gap. The study aims to examine the research question whether the use of social media explains the success or failure of revolutions in 2008 and 2018 in Armenia. The research question is investigated through content analysis of two cases; failed revolution in 2008 and the successful revolution in 2018 in Armenia. The secondary data analysis was based on information devoted to two revolutions using local and major international news articles, journal and critical articles, in Armenian, Russian and English, also videos, posts and live streams of the revolutionary leaders. There can be many factors explaining the success or failure of a revolution. However, the investigation of the factors and their role to explain the outcome of a revolution other than the use of social media is beyond the scope of this research study. The study holds other variables constant and concludes that in the cases of 2008 and 2018 revolutions in Armenia the mobilization of society through social media explains the differences in the outcomes (failed or successful). The comparative case study of the revolutions in 2008 and 2018 in Armenia emphasizes the important role and impact of the use of social media on the success or failure of a revolution. The results highlight that the use of the Internet, particularly social media and live streams, by the opposition was the essential difference between two revolutions. Social media platforms, live streams, and communication apps that were absent in the revolutionary situation in 2008 were fundamental to the Armenian Velvet Revolution in 2018. The changes in the situation in favor of the opposition, so the outcome of the protests, were mainly based on the Internet-based mobilization of the society. It is also important to take into consideration that the country experienced a great increase in penetration rates over the decade. The percentage of access to the Internet drastically increased between 2008 and 2018. This fact may help to have a clearer understanding of the use of the Internet and social media by the opposition and the reliance on social media by society. According to the results of the continent analysis, the use of social media to direct the protests and to mobilize the society, have a vital role and positive impact on the outcome of a revolution. Thus the study concludes that it is the use of social media to initiate, organize, and direct the protests that explain the success or failure of two Armenian revolutions.

Keywords: social media, revolution, Armenia, success, failure

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Authors: Caroline Selai, Sushrut Jadhav

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Background: University College London (UCL), the first secular university in England to admit students regardless of their religion and gender, has nearly 29,000 students of which approximately 30% are international students. The UCL Cultural Consultation Service (CCS) for staff and students is a unique service that provides assistance to staff and students experiencing challenges in their teaching, enabling, support work or studies which they believe may have a cultural component. The service provides one-to-one and group consultations, lectures, seminars, ‘grand rounds’, interactive workshops and bespoke interventions. Data: This paper presents a content analysis of CCS referrals over the last 36 months. We focus on the experience of international students, many of whom experience not only a challenge to their academic identity but also a profound challenge to their personal cultural identity. We also present 3 vignettes to illustrate how students interpret, accept, contest and resist changes in their cultural and academic identity. Discussion: This paper highlights (i) how students from collectivist cultures attempt to assimilate within an individualistic, highly competitive western university that is bound by its own institutional norms; (ii) problems in negotiating challenges at the interface of culture and gender (iii) the impact of culturally different hierarchies of power, discrimination and authority and (iv) the significance of earlier traumatic and kinship conflicts. Many international students’ social identities are shaped by their cultural and family scripts. A large number have been taught that their teachers are to be revered and their teachings unchallenged. This is at odds with quintessential goal of the western university to encourage healthy scepticism and hone students’ critical thinking skills. Conclusions: Pupil-teacher ‘cultural transference’ and shifts in cultural academic identities of students underscore critical aspects of developmental and learning challenges for students. Staff-student cultural conflict requires a broader, systemic analysis of students, staff and the wider organisation. Our findings challenge Eurocentric psychodynamic concepts such as the nature of parent-child relationship in Western Europe. We argue for a broader, more inclusive approach to develop both effective pedagogic skills in euro-american academic institutions and culturally- appropriate psychodynamic theory to underpin counselling international students.

Keywords: academic identity, cultural transference, cultural consultation in higher education, cultural formulation, cultural identity.

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Authors: Charisse H. Tay

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Background: Schizophrenia is a severe chronic mental disorder that can result in hallucinations, delusions, reduced social engagement, and lack of motivation. While antipsychotic medications often provide the basis for treatment, psychosocial strategies complement the benefit of medications and can result in meaningful improvements in symptoms and functioning. The aim of the study was to investigate psychosocial strategies used by internet self-help forum participants to effectively manage symptoms caused by schizophrenia. Internet self-help forums are a resource for medical and psychological problems and are commonly used to share information about experiences with symptom management. Method: Three international self-help internet forums on schizophrenia were identified using a search engine. 1,181 threads regarding non-pharmacological, psychosocial self-management of schizophrenia symptoms underwent screening, resulting in the final identification and coding of 91 threads and 191 posts from 134 unique forum users that contained details on psychosocial strategies endorsed personally by users that allowed them to effectively manage symptoms of schizophrenia, including positive symptoms (e.g., auditory/visual/tactile hallucinations, delusions, paranoia), negative symptoms (e.g.., avolition, apathy, anhedonia), symptoms of distress, and cognitive symptoms (e.g., memory loss). Results: Effective symptom management strategies personally endorsed by online forum users were psychological skills (e.g., re-focusing, mindfulness/meditation, reality checking; n = 94), engaging in activities (e.g., exercise, working/volunteering, hobbies; n = 84), social/familial support (n = 48), psychotherapy (n = 33), diet (n = 18), and religion/spirituality (n = 14). 44.4% of users reported using more than one strategy to manage their symptoms. The most common symptoms targeted and effectively managed, as specified by users, were positive symptoms (n = 113), negative symptoms (n = 17), distress (n = 8), and memory loss (n = 6). 10.5% of users reported more than one symptom effectively targeted. 70.2% of users with positive symptoms reported that psychological skills were effective for symptom relief. 88% of users with negative symptoms and 75% with distress symptoms reported that engaging in activities was effective. Discussion: Individuals with schizophrenia rely on a variety of different psychosocial methods to manage their symptoms. Different symptomology appears to be more effectively targeted by different types of psychosocial strategies. This may help to inform treatment strategy and tailored for individuals with schizophrenia.

Keywords: psychosocial treatment, qualitative methods, schizophrenia, symptom management

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Authors: Luiz Carlos Wrobel, Matjaz Hribersek, Jure Marn, Jurij Iljaz

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Dynamic thermography has been clinically proven to be a valuable diagnostic technique for skin tumor detection as well as for other medical applications such as breast cancer diagnostics, diagnostics of vascular diseases, fever screening, dermatological and other applications. Thermography for medical screening can be done in two different ways, observing the temperature response under steady-state conditions (passive or static thermography), and by inducing thermal stresses by cooling or heating the observed tissue and measuring the thermal response during the recovery phase (active or dynamic thermography). The numerical modelling of heat transfer phenomena in biological tissue during dynamic thermography can aid the technique by improving process parameters or by estimating unknown tissue parameters based on measured data. This paper presents a nonlinear numerical model of multilayer skin tissue containing a skin tumor, together with the thermoregulation response of the tissue during the cooling-rewarming processes of dynamic thermography. The model is based on the Pennes bioheat equation and solved numerically by using a subdomain boundary element method which treats the problem as axisymmetric. The paper includes computational tests and numerical results for Clark II and Clark IV tumors, comparing the models using constant and temperature-dependent thermophysical properties, which showed noticeable differences and highlighted the importance of using a local thermoregulation model.

Keywords: boundary element method, dynamic thermography, static thermography, skin tumor diagnostic

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Authors: Ngoc-Hieu Vu

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Dairy production in Vietnam is a relatively new agricultural activity and milk production increased remarkably in recent years. Smallholders are still the main drivers for this development, especially in the southern part of the country. However, information on the farming practices is very limited. Therefore, this study aimed to determine factors influencing milk yield and quality (milk fat, total solids, solids-not-fat, total number of bacteria, and somatic cell count) and revenue of dairy farms in Southern Vietnam. The collection of data was at the farm level; individual animal records were unavailable. The 539 studied farms were located in the provinces Lam Dong (N=111 farms), Binh Duong (N=69 farms), Long An (N=174 farms), and Ho Chi Minh city (N=185 farms). The dataset included 9221 monthly test-day records of the farms from January 2013 to May 2015. Seasons were defined as rainy and dry. Farms sizes were classified as small (< 10 milking cows), medium (10 to 19 milking cows) and large (≥ 20 milking cows). The model for each trait contained year-season and farm region-farm size as subclass fixed effects, and individual farm and residual as random effects. Results showed that year-season, region, and farm size were determining sources of variation affecting all studied traits. Milk yield was higher in dry than in rainy seasons (P < 0.05), while it tended to increase from years 2013 to 2015. Large farms had higher yields (445.6 kg/cow) than small (396.7 kg/cow) and medium (428.0 kg/cow) farms (P < 0.05). Small farms, in contrast, were superior to large farms in terms of milk fat, total solids, solids-not-fat, total number of bacteria, and somatic cell count than large farms (P < 0.05). Revenue per cow was higher in large compared with medium and small farms. In conclusion, large farms achieved higher milk yields and revenues per cow, while small farms were superior in milk quality. Overall, milk yields were low and better training, financial support and marketing opportunities for farmers are needed to improve dairy production and increase farm revenues in Southern Vietnam.

Keywords: farm size, milk yield and quality, season, Southern Vietnam

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Authors: Molakala Mourya Vardhan Reddy, Kandimala Revanth, Koduru Sumanth, Beena B. M.

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Emergency response and recovery operations are severely hampered by natural catastrophes, especially floods. Understanding post-flood scenarios is essential to disaster management because it facilitates quick evaluation and decision-making. To this end, we introduce FloodNet, a brand-new high-resolution aerial picture collection created especially for comprehending post-flood scenes. A varied collection of excellent aerial photos taken during and after flood occurrences make up FloodNet, which offers comprehensive representations of flooded landscapes, damaged infrastructure, and changed topographies. The dataset provides a thorough resource for training and assessing computer vision models designed to handle the complexity of post-flood scenarios, including a variety of environmental conditions and geographic regions. Pixel-level semantic segmentation masks are used to label the pictures in FloodNet, allowing for a more detailed examination of flood-related characteristics, including debris, water bodies, and damaged structures. Furthermore, temporal and positional metadata improve the dataset's usefulness for longitudinal research and spatiotemporal analysis. For activities like flood extent mapping, damage assessment, and infrastructure recovery projection, we provide baseline standards and evaluation metrics to promote research and development in the field of post-flood scene comprehension. By integrating FloodNet into machine learning pipelines, it will be easier to create reliable algorithms that will help politicians, urban planners, and first responders make choices both before and after floods. The goal of the FloodNet dataset is to support advances in computer vision, remote sensing, and disaster response technologies by providing a useful resource for researchers. FloodNet helps to create creative solutions for boosting communities' resilience in the face of natural catastrophes by tackling the particular problems presented by post-flood situations.

Keywords: image classification, segmentation, computer vision, nature disaster, unmanned arial vehicle(UAV), machine learning.

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Authors: Anahita Izadyar, My Ni Van, Kayleigh Amber Rodriguez, Ilwoo Seok, Elizabeth E. Hood

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Using a recombinant enzyme derived from corn and a simple modification, we fabricated a facile, fast, and cost-beneficial biosensor to measure glucose. The Nafion/ Plant Produced Mn Peroxidase (PPMP)– glucose oxidase (GOx)- Bovine serum albumin (BSA) /Au electrode showed an excellent amperometric response to detect glucose. This biosensor is capable of responding to a wide range of glucose—20.0 µM−15.0 mM and has a lower detection limit (LOD) of 2.90µM. The reproducibility response using six electrodes is also very substantial and indicates the high capability of this biosensor to detect a wide range of 3.10±0.19µM to 13.2±1.8 mM glucose concentration. Selectivity of this electrode was investigated in an optimized experimental solution contains 10% diet green tea with citrus containing ascorbic acid (AA), and citric acid (CA) in a wide concentration of glucose at 0.02 to 14.0mM with an LOD of 3.10µM. Reproducibility was also investigated using 4 electrodes in this sample and shows notable results in the wide concentration range of 3.35±0.45µM to of 13.0 ± 0.81 mM. We also used other voltammetry methods to evaluate this biosensor. We applied linear sweep voltammetry (LSV) and this technique shows a wide range of 0.10−15.0 mM to detect glucose with a lower detection limit of 19.5µM. The performance and strength of this enzyme biosensor were the simplicity, wide linear ranges, sensitivities, selectivity, and low limits of detection. We expect that the modified biosensor has the potential for monitoring various biofluids.

Keywords: plant-produced manganese peroxidase, enzyme-based biosensors, glucose, modified gold electrode, glucose oxidase

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Authors: Tingwei Shu, Dong Zhou, Chengjun Guo

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Semantic communication is an emerging form of communication that realize intelligent communication by extracting semantic information of data at the source and transmitting it, and recovering the data at the receiving end. It can effectively solve the problem of data transmission under the situation of large data volume, low SNR and restricted bandwidth. With the development of Deep Learning, semantic communication further matures and is gradually applied in the fields of the Internet of Things, Uumanned Air Vehicle cluster communication, remote sensing scenarios, etc. We propose an improved semantic communication system for the situation where the data volume is huge and the spectrum resources are limited during the transmission of remote sensing images. At the transmitting, we need to extract the semantic information of remote sensing images, but there are some problems. The traditional semantic communication system based on Convolutional Neural Network cannot take into account the global semantic information and local semantic information of the image, which results in less-than-ideal image recovery at the receiving end. Therefore, we adopt the improved vision-Transformer-based structure as the semantic encoder instead of the mainstream one using CNN to extract the image semantic features. In this paper, we first perform pre-processing operations on remote sensing images to improve the resolution of the images in order to obtain images with more semantic information. We use wavelet transform to decompose the image into high-frequency and low-frequency components, perform bilinear interpolation on the high-frequency components and bicubic interpolation on the low-frequency components, and finally perform wavelet inverse transform to obtain the preprocessed image. We adopt the improved Vision-Transformer structure as the semantic coder to extract and transmit the semantic information of remote sensing images. The Vision-Transformer structure can better train the huge data volume and extract better image semantic features, and adopt the multi-layer self-attention mechanism to better capture the correlation between semantic features and reduce redundant features. Secondly, to improve the coding efficiency, we reduce the quadratic complexity of the self-attentive mechanism itself to linear so as to improve the image data processing speed of the model. We conducted experimental simulations on the RSOD dataset and compared the designed system with a semantic communication system based on CNN and image coding methods such as BGP and JPEG to verify that the method can effectively alleviate the problem of excessive data volume and improve the performance of image data communication.

Keywords: semantic communication, transformer, wavelet transform, data processing

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Authors: Vedanki Khandenwal, Pawan Srivastava, Kartick Tarafder, Subhasis Ghosh

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We present here the experimental realization of controlled doping of graphene monolayers through charge transfer by trapping selected organic molecules between the graphene layer and underlying substrates. This charge transfer between graphene and trapped molecule leads to controlled n-type or p-type doping in monolayer graphene (MLG), depending on whether the trapped molecule acts as an electron donor or an electron acceptor. Doping controllability has been validated by a shift in corresponding Raman peak positions and a shift in Dirac points. In the transfer characteristics of field effect transistors, a significant shift of Dirac point towards positive or negative gate voltage region provides the signature of p-type or n-type doping of graphene, respectively, as a result of the charge transfer between graphene and the organic molecules trapped within it. In order to facilitate the charge transfer interaction, it is crucial for the trapped molecules to be situated in close proximity to the graphene surface, as demonstrated by findings in Raman and infrared spectroscopies. However, the mechanism responsible for this charge transfer interaction has remained unclear at the microscopic level. Generally, it is accepted that the dipole moment of adsorbed molecules plays a crucial role in determining the charge-transfer interaction between molecules and graphene. However, our findings clearly illustrate that the doping effect primarily depends on the reactivity of the constituent atoms in the adsorbed molecules rather than just their dipole moment. This has been illustrated by trapping various molecules at the graphene−substrate interface. Dopant molecules such as acetone (containing highly reactive oxygen atoms) promote adsorption across the entire graphene surface. In contrast, molecules with less reactive atoms, such as acetonitrile, tend to adsorb at the edges due to the presence of reactive dangling bonds. In the case of low-dipole moment molecules like toluene, there is a lack of substantial adsorption anywhere on the graphene surface. Observation of (i) the emergence of the Raman D peak exclusively at the edges for trapped molecules without reactive atoms and throughout the entire basal plane for those with reactive atoms, and (ii) variations in the density of attached molecules (with and without reactive atoms) to graphene with their respective dipole moments provides compelling evidence to support our claim. Additionally, these observations were supported by first principle density functional calculations.

Keywords: graphene, doping, charge transfer, liquid phase exfoliation

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