Search results for: performance comparison

Authors: Geisa Lima Mesquita Zambrosi, Maisa Ciampi Guillardi, Flávia Rodrigues Patrício, Oliveiro Guerreiro Filho

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Certified agricultural products are important components of the food industry. However, certifiers have been expanding the list of restricted or prohibited pesticides, limiting the options of products for phytosanitary control of plant diseases, but without offering alternatives to the farmers. Soybean and coffee leaf rust, brown eye spots, and Phoma leaf spots are the main fungal diseases that pose a serious threat to soybean and coffee cultivation worldwide. In conventional farming systems, these diseases are controlled by using synthetic fungicides, which, in addition to intensifying the occurrence of fungal resistance, are highly toxic to the environment, farmers, and consumers. In organic, agroecological, or regenerative farming systems, product options for plant protection are limited, being available only copper-based compounds, and biodefensivesornon-standard homemade products. Therefore, there is a growing demand for effective bioprotectors with low environmental impact for adoption in more sustainable agricultural systems. Then, to contribute to covering such a gap, we have developed a compound based on plant extracts and metallic elements for foliar application. This product has both biostimulant and bioprotective action, which promotes sustainable disease control, increases productivity as well as reduces damage to the environment. The product's components have complementary mechanisms that promote protection against the disease by directly acting on the pathogens and activating the plant's natural defense system. The protective ability of the product against three coffee diseases (coffee leaf rust, brown eye spot, and Phoma leaf spot) and against soybean rust disease was evaluated, in addition to its ability to promote plant growth. Our goal is to offer an effective alternative to control the main coffee fungal diseases and soybean fungal diseases, with a biostimulant effect and low toxicity. The proposed product can also be part of the integrated management of coffee and soybean diseases in conventional farming associated with chemical and biological pesticides, offering the market a sustainable coffee and soybean with high added value and low residue content. Experiments were carried out under controlled conditions to evaluate the effectiveness of the product in controlling rust, phoma, and cercosporiosis in comparison to control-inoculated plants that did not receive the product. The in vitro and in vivo effects of the product on the pathogen were evaluated using light microscopy and scanning electron microscopy, respectively. The fungistatic action of the product was demonstrated by a reduction of 85% and 95% in spore germination and disease symptoms severity on the leaves of coffee plants, respectively. The formulation had both a protective effect, acting to prevent infection by coffee leaf rust, and a curative effect, reducing the rust symptoms after its establishment.

Keywords: plant disease, natural fungicide, plant health, sustainability, alternative disease management

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Authors: Ahmed I. Al-Amoud

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A laboratory and field study were conducted on subsurface drip irrigation systems. In the first laboratory study, eight subsurface drip irrigation lines available locally, were selected and a number of experiments were made to evaluate line hydraulic characteristics to insure it's suitability for drip irrigation design requirements and high performance to select the best for field experiments. The second study involves field trials on mature date palm trees to study the effect of subsurface drip irrigation system on the yield and water consumption of date palms, and to compare that with the traditional surface drip irrigation system. Experiments were conducted in Alwatania Agricultural Project, on 50 mature palm trees (17 years old) of Helwa type with 10 meters spacing between rows and between trees. A high efficiency subsurface line (Techline) was used based on the results of the first study. Irrigation scheduling was made through a soil moisture sensing device to ensure enough soil water levels in the soil. Experiment layouts were installed during 2001 season, measurements continued till end of 2008 season. Results have indicated that there is an increase in the yield and a considerable saving in water compared to the conventional drip irrigation method. In addition there were high increases in water use efficiency using the subsurface system. The subsurface system proves to be durable and highly efficient for irrigating date palm trees.

Keywords: drip irrigation, subsurface drip irrigation, date palm trees, date palm water use, date palm yield

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Authors: Pauline Calleja, Brooke Alexander

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In 2010 the College of Emergency Nursing Australasia (CENA) undertook sole administration of the Trauma Nursing Program (TNP) across Australia. The original TNP was developed from recommendations by the Review of Trauma and Emergency Services-Victoria. While participant and faculty feedback about the program was positive, issues were identified that were common for industry training programs in Australia. These issues included didactic approaches, with many lectures and little interaction/activity for participants. Participants were not necessarily encouraged to undertake deep learning due to the teaching and learning principles underpinning the course, and thus participants described having to learn by rote, and only gain a surface understanding of principles that were not always applied to their working context. In Australia, a trauma or emergency nurse may work in variable contexts that impact on practice, especially where resources influence scope and capacity of hospitals to provide trauma care. In 2011, a program review was undertaken resulting in major changes to the curriculum, teaching, learning and assessment approaches. The aim was to improve learning including a greater emphasis on pre-program preparation for participants, the learning environment and clinically applicable contextualized outcomes participants experienced. Previously if participants wished to undertake assessment, they were given a take home examination. The assessment had poor uptake and return, and provided no rigor since assessment was not invigilated. A new assessment structure was enacted with an invigilated examination during course hours. These changes were implemented in early 2012 with great improvement in both faculty and participant satisfaction. This presentation reports on a comparison of participant evaluations collected from courses post implementation in 2012 and in 2015 to evaluate if positive changes were sustained. Methods: Descriptive statistics were applied in analyzing evaluations. Since all questions had more than 20% of cells with a count of <5, Fisher’s Exact Test was used to identify significance (p = <0.05) between groups. Results: A total of fourteen group evaluations were included in this analysis, seven CENA TNP groups from 2012 and seven from 2015 (randomly chosen). A total of 173 participant evaluations were collated (n = 81 from 2012 and 92 from 2015). All course evaluations were anonymous, and nine of the original 14 questions were applicable for this evaluation. All questions were rated by participants on a five-point Likert scale. While all items showed improvement from 2012 to 2015, significant improvement was noted in two items. These were in regard to the content being delivered in a way that met participant learning needs and satisfaction with the length and pace of the program. Evaluation of written comments supports these results. Discussion: The aim of redeveloping the CENA TNP was to improve learning and satisfaction for participants. These results demonstrate that initial improvements in 2012 were able to be maintained and in two essential areas significantly improved. Changes that increased participant engagement, support and contextualization of course materials were essential for CENA TNP evolution.

Keywords: emergency nursing education, industry training programs, teaching and learning, trauma education

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Authors: Sana Eid, Ahmad S. Darwish, Tarek Lemaoui, Maguy Abi Jaoude, Fawzi Banat, Shadi W. Hasan, Inas M. AlNashef

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Addressing the growing challenge of per- and polyfluoroalkyl substances (PFAS) pollution in water bodies, this study introduces natural deep eutectic solvents (NADESs) as a pioneering solution for the efficient extraction of perfluorooctanoic acid (PFOA), one of the most persistent and concerning PFAS pollutants. Among the tested NADESs, trioctylphosphine oxide: lauric acid (TOPO:LauA) in a 1:1 molar ratio was distinguished as the most effective, achieving an extraction efficiency of approximately 99.52% at a solvent-to-feed (S:F) ratio of 1:2, room temperature, and neutral pH. This efficiency is achieved within a notably short mixing time of only one min, which is significantly less than the time required by conventional methods, underscoring the potential of TOPO:LauA for rapid and effective PFAS remediation. TOPO:LauA maintained consistent performance across various operational parameters, including a range of initial PFOA concentrations (0.1 ppm to 1000 ppm), temperatures (15 °C to 100 °C), pH values (3 to 9), and S:F ratios (2:3 to 1:7), demonstrating its versatility and robustness. Furthermore, its effectiveness was consistently high over seven consecutive extraction cycles, highlighting TOPO:LauA as a sustainable, environmentally friendly alternative to hazardous organic solvents, with promising applications for reliable, repeatable use in combating persistent water pollutants such as PFOA.

Keywords: deep eutectic solvents, natural deep eutectic solvents, perfluorooctanoic acid, water remediation

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Authors: Kamal Tolani, Sandeep Kumar, Rohit Luthra, Ankit Dadhania, Krishnaprasad K., Ram Gupta, Deepa Joshi

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Background: Post-operative analgesia remains a clinical challenge, with central and peripheral sensitization playing a pivotal role in treatment-related complications and impaired quality of life. Centrally acting opioids offer poor risk benefit profile with increased intensity of gastrointestinal or central side effects and slow onset of clinical analgesia. The objective of this study was to assess the clinical feasibility of induction and maintenance therapy with Tapentadol Nasal Spray (NS) in moderate to severe acute post-operative pain. Methods: Phase III, randomized, active-controlled, non-inferiority clinical trial involving 294 cases who had undergone surgical procedures under general anesthesia or regional anesthesia. Post-surgery patients were randomized to receive either Tapentadol NS 45 mg or Tramadol 100mg IV as a bolus and subsequent 50 mg or 100 mg dose over 2-3 minutes. The frequency of administration of NS was at every 4-6 hours. At the end of 24 hrs, patients in the tramadol group who had a pain intensity score of ≥4 were switched to oral tramadol immediate release 100mg capsule until the pain intensity score reduced to <4. All patients who had achieved pain intensity ≤ 4 were shifted to a lower dose of either Tapentadol NS 22.5 mg or oral Tramadol immediate release 50mg capsule. The statistical analysis plan was envisaged as a non-inferiority trial involving comparison with Tramadol for Pain intensity difference at 60 minutes (PID60min), Sum of Pain intensity difference at 60 minutes (SPID60min), and Physician Global Assessment at 24 hrs (PGA24 hrs). Results: The per-protocol analyses involved 255 hospitalized cases undergoing surgical procedures. The median age of patients was 38.0 years. For the primary efficacy variables, Tapentadol NS was non-inferior to Inj/Oral Tramadol in relief of moderate to severe post-operative pain. On the basis of SPID60min, no clinically significant difference was observed between Tapentadol NS and Tramadol IV (1.73±2.24 vs. 1.64± 1.92, -0.09 [95% CI, -0.43, 0.60]). In the co-primary endpoint PGA24hrs, Tapentadol NS was non–inferior to Tramadol IV (2.12 ± 0.707 vs. 2.02 ±0.704, - 0.11[95% CI, -0.07, 0.28). However, on further assessment at 48hr, 72 hrs, and 120hrs, clinically superior pain relief was observed with the Tapentadol NS formulation that was statistically significant (p <0.05) at each of the time intervals. Secondary efficacy measures, including the onset of clinical analgesia and TOTPAR, showed non-inferiority to Tramadol. The safety profile and need for rescue medication were also similar in both the groups during the treatment period. The most common concomitant medications were anti-bacterial (98.3%). Conclusion: Tapentadol NS is a clinically feasible option for improved compliance as induction and maintenance therapy while offering a sustained and persistent patient response that is clinically meaningful in post-surgical settings.

Keywords: tapentadol nasal spray, acute pain, tramadol, post-operative pain

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Authors: Sukhwinder K. Bhullar, M. B. G. Jun

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The developments in biomedical industry have demanded the development of biocompatible, high performance materials to meet higher engineering specifications. The general requirements of such materials are to provide a combination of high stiffness and strength with significant weight savings, resistance to corrosion, chemical resistance, low maintenance, and reduced costs. Auxetic materials which come under the category of smart materials offer huge potential through measured enhancements in mechanical properties. Unique deformation mechanism, providing cushioning on indentation, automatically adjustable with its strength and thickness in response to forces and having memory returns to its neutral state on dissipation of stresses make them good candidate in biomedical industry. As simple extension and compression of tissues is of fundamental importance in biomechanics, therefore, to study the elastic behaviour of auxetic soft tissues implant is targeted in this paper. Therefore development and characterization of auxetic soft tissue implant is studied in this paper. This represents a real life configuration where soft tissue such as meniscus in knee replacement, ligaments and tendons often are taken as transversely isotropic. Further, as composition of alternating polydisperse blocks of soft and stiff segments combined with excellent biocompatibility make polyurethanes one of the most promising synthetic biomaterials. Hence selecting auxetic polyurathylene foam functional characterization is performed and compared with conventional polyurathylene foam.

Keywords: auxetic materials, deformation mechanism, enhanced mechanical properties, soft tissues

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Authors: Prathiksha Kamath, Pratibha Jamkhandi, Prateek Ghanti, Priyanshu Gupta, M. Lakshmi Neelima

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Combining Image Captioning and Visual Question Answering (VQA) tasks have emerged as a new and exciting research area. The image captioning task involves generating a textual description that summarizes the content of the image. VQA aims to answer a natural language question about the image. Both these tasks include computer vision and natural language processing (NLP) and require a deep understanding of the content of the image and semantic relationship within the image and the ability to generate a response in natural language. There has been remarkable growth in both these tasks with rapid advancement in deep learning. In this paper, we present a comprehensive review of recent progress in combining image captioning and visual question-answering (VQA) tasks. We first discuss both image captioning and VQA tasks individually and then the various ways in which both these tasks can be integrated. We also analyze the challenges associated with these tasks and ways to overcome them. We finally discuss the various datasets and evaluation metrics used in these tasks. This paper concludes with the need for generating captions based on the context and captions that are able to answer the most likely asked questions about the image so as to aid the VQA task. Overall, this review highlights the significant progress made in combining image captioning and VQA, as well as the ongoing challenges and opportunities for further research in this exciting and rapidly evolving field, which has the potential to improve the performance of real-world applications such as autonomous vehicles, robotics, and image search.

Keywords: image captioning, visual question answering, deep learning, natural language processing

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Authors: Seyedmirsajad Mokhtarimousavi, Danial Talebi, Hamidreza Asgari

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Assigning aircrafts’ activities to appropriate gates is one the most challenging issues in airport authorities’ multiple criteria decision making. The potential financial loss due to imbalances of demand and supply in congested airports, higher occupation rates of gates, and the existing restrictions to expand facilities provide further evidence for the need for an optimal supply allocation. Passengers walking distance, towing movements, extra fuel consumption (as a result of awaiting longer to taxi when taxi conflicts happen at the apron area), etc. are the major traditional components involved in GAP models. In particular, the total cost associated with gate assignment problem highly depends on the airport terminal layout. The study herein presents a well-elaborated literature review on the topic focusing on major concerns, applicable variables and objectives, as well as proposing a three-objective mathematical model for the gate assignment problem. The model has been tested under different concourse layouts in order to check its performance in different scenarios. Results revealed that terminal layout pattern is a significant parameter in airport and that the proposed model is capable of dealing with key constraints and objectives, which supports its practical usability for future decision making tools. Potential solution techniques were also suggested in this study for future works.

Keywords: airport management, terminal layout, gate assignment problem, mathematical modeling

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Authors: Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Diego Santibañez Oyarce, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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Streptococcus pyogenes is a gram-positive bacteria involved in a wide range of diseases and is a major-human-specific bacterial pathogen. In Chile, this year the 'Ministerio de Salud' declared an alert due to the increase in strains throughout the year. This increase can be attributed to the multitude of factors including antimicrobial resistance (AMR) and Virulence Factors (VF). Understanding these VF and AMR is crucial for developing effective strategies and improving public health responses. Moreover, experimental identification and characterization of these pathogenic mechanisms are labor-intensive and time-consuming. Therefore, new computational methods are required to provide robust techniques for accelerating this identification. Advances in Machine Learning (ML) algorithms represent the opportunity to refine and accelerate the discovery of VF associated with Streptococcus pyogenes. In this work, we evaluate the accuracy of various machine learning models in predicting the virulence factors and antimicrobial resistance of Streptococcus pyogenes, with the objective of providing new methods for identifying the pathogenic mechanisms of this organism.Our comprehensive approach involved the download of 32,798 genbank files of S. pyogenes from NCBI dataset, coupled with the incorporation of data from Virulence Factor Database (VFDB) and Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. These datasets provided labeled examples of both virulent and non-virulent genes, enabling a robust foundation for feature extraction and model training. We employed preprocessing, characterization and feature extraction techniques on primary nucleotide/amino acid sequences and selected the optimal more for model training. The feature set was constructed using sequence-based descriptors (e.g., k-mers and One-hot encoding), and functional annotations based on database prediction. The ML models compared are logistic regression, decision trees, support vector machines, neural networks among others. The results of this work show some differences in accuracy between the algorithms, these differences allow us to identify different aspects that represent unique opportunities for a more precise and efficient characterization and identification of VF and AMR. This comparative analysis underscores the value of integrating machine learning techniques in predicting S. pyogenes virulence and AMR, offering potential pathways for more effective diagnostic and therapeutic strategies. Future work will focus on incorporating additional omics data, such as transcriptomics, and exploring advanced deep learning models to further enhance predictive capabilities.

Keywords: antibiotic resistance, streptococcus pyogenes, virulence factors., machine learning

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Authors: Shirley S. Ho, Alisius X. L. D. Leong, Jiemin Looi, Agnes S. F. Chuah

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Nuclear energy is a contentious technology that has attracted much public debate over the years. The prominence of nuclear energy in Southeast Asia (SEA) has burgeoned due to the surge of interest and plans for nuclear development in the region. Understanding public perceptions of nuclear energy in SEA is pertinent given the limited number of studies conducted. In particular, five SEA nations – Singapore, Malaysia, Indonesia, Thailand, and Vietnam are of immediate interest as that they are amongst the most economically developed or developing nations in the SEA region. High energy demands from economic development in these nations have led to considerations of adopting nuclear energy as an alternative source of energy. This study aims to explore whether differences in the nuclear developmental stage in each country affects public perceptions of nuclear energy. In addition, this study seeks to find out about the type and importance of communication credibility as a judgement heuristic in facilitating message acceptance across these five countries. Credibility of a communication channel is a crucial component influencing public perception, acceptance, and attitudes towards nuclear energy. Aside from simply identifying the frequently used communication channels, it is of greater significance to understand public perception of source and media credibility. Given the lack of studies conducted in SEA, this exploratory study adopts a qualitative approach to elicit a spectrum of opinions and insights regarding the key communication aspects influencing public perceptions of nuclear energy. Specifically, the capitals of each of the abovementioned countries - Kuala Lumpur, Bangkok, and Hanoi - were selected, with the exception of Singapore, an island city-state, and Yogyakarta, the most populous island of Indonesia to better understand public perception towards nuclear energy. Focus group discussions were utilized as the mode of data collection to elicit a wide variety of viewpoints held by the participants, which is well-suited for exploratory research. In total, 156 participants took part in the 13 focus group discussions. The participants were either local citizens or permanent residents aged between 18 and 69 years old. Each of the focus groups consists of 8-10 participants, including both male and female participants. The transcripts from each focus group were analysed using NVivo 10, and the text was organised according to the emerging themes or categories. The general public in all the countries was familiar but had no in-depth knowledge with nuclear energy. Four dimensions of nuclear energy communication were identified based on the focus group discussions: communication channels, perceived credibility of sources, circumstances for discussion, and discussion style. The first dimension, communication channels refers to the medium through which participants receive information about nuclear energy. Four types of media emerged from the discussions. They included online and social media, broadcast media, print media, and word-of- mouth (WOM). Collectively, across all five countries, participants were found to engage in different types of knowledge acquisition and information seeking behavior depending on the communication channels used.

Keywords: nuclear energy, public perception, communication, Southeast Asia, source credibility

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Authors: Shatha Ghareeb, Rawaa Al-Jumeily, Thar Baker

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In Abu Dhabi, there are many different education curriculums where sector of private schools and quality assurance is supervising many private schools in Abu Dhabi for many nationalities. As there are many different education curriculums in Abu Dhabi to meet expats’ needs, there are different requirements for registration and success. In addition, there are different age groups for starting education in each curriculum. In fact, each curriculum has a different number of years, assessment techniques, reassessment rules, and exam boards. Currently, students that transfer curriculums are not being placed in the right year group due to different start and end dates of each academic year and their date of birth for each year group is different for each curriculum and as a result, we find students that are either younger or older for that year group which therefore creates gaps in their learning and performance. In addition, there is not a way of storing student data throughout their academic journey so that schools can track the student learning process. In this paper, we propose to develop a computational framework applicable in multicultural countries such as UAE in which multi-education systems are implemented. The ultimate goal is to use cloud and fog computing technology integrated with Artificial Intelligence techniques of Machine Learning to aid in a smooth transition when assigning students to their year groups, and provide leveling and differentiation information of students who relocate from a particular education curriculum to another, whilst also having the ability to store and access student data from anywhere throughout their academic journey.

Keywords: admissions, algorithms, cloud computing, differentiation, fog computing, levelling, machine learning

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Authors: Saeed Pourhassan, Nastaran Maghbouli

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1) Background It has been hypothesized that, in individuals with diabetes mellitus, the peripheral nerve is swollen due to sorbitol over-accumulation. Additionally growing evidence supported electro diagnostic study of diabetes induced neuropathy as a method having some challenges. 2) Objective To examine the performance of sonographic cross-sectional area (CSA) measurements in the diagnosis of diabetic polyneuropathy (DPN). 3) Data Sources Electronic databases, comprising PubMed and EMBASE and Google scholar, were searched for the appropriate studies before Jan 1, 2020. 4) Study Selection Eleven trials comparing different peripheral nerve CSA measurements between participants with and without DPN were included. 5) Data Extraction Study design, participants' demographic characteristics, diagnostic reference of DPN, and evaluated peripheral nerves and methods of CSA measurement. 6) Data Synthesis Among different peripheral nerves, Tibial nerve diagnostic odds ratios pooled from five studies (713 participants) were 4.46 (95% CI, 0.35–8.57) and the largest one with P<0.0001, I²:64%. Median nerve CSA at wrist and mid-arm took second and third place with ORs= 2.82 (1.50-4.15), 2.02(0.26-3.77) respectively. The sensitivities and specificities pooled from two studies for Sural nerve were 0.78 (95% CI, 0.68–0.89), and 0.68 (95% CI, 0.53–0.74). Included studies for other nerves were limited to one study. The largest sensitivity was for Sural nerve and the largest specificity was for Tibial nerve. 7) Conclusions The peripheral nerves CSA measured by ultrasound imaging is useful for the diagnosis of DPN and is most significantly different between patients and participants without DPN at the Tibial nerve. Because the Tibial nerve CSA in healthy participants, at various locations, rarely exceeds 24 mm2, this value can be considered as a cutoff point for diagnosing DPN.

Keywords: diabetes, diagnosis, polyneuropathy, ultrasound

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Authors: Sormeh Sharifi, Wasim Saman, Alemu Alemu, David Whaley

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Although various energy rating schemes and compulsory building codes are using around the world, there are increasing reports on overheating in energy efficient dwellings. Given that the cooling demand of buildings is rising globally because of the climate change, it is more likely that the overheating issue will be observed more. This paper studied the summer indoor temperature in eight air-conditioned multi-level houses in Adelaide which have complied with the Australian Nationwide Houses Energy Rating Scheme (NatHERS) minimum energy performance of 7.5 stars. Through monitored temperature, this study explores that overheating is experienced on 75.5% of top floors during cooling periods while the air-conditioners were running. This paper found that the energy efficiency regulations have significantly improved thermal comfort in low floors, but not on top floors, and the energy-efficient house is not necessarily adapted with the air temperature fluctuations particularly on top floors. Based on the results, this study suggests that the envelope of top floors for multi-level houses in South Australian context need new criteria to make the top floor more heat resistance in order to: preventing the overheating, reducing the summer pick electricity demand and providing thermal comfort. Some methods are used to improve the envelope of the eight case studies. The results demonstrate that improving roofs was the most effective part of the top floors envelope in terms of reducing the overheating.

Keywords: building code, climate change, energy-efficient building, energy rating, overheating, thermal comfort

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Authors: B. K. Kanungo, Monika Thakur, Minati Baral

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8-hydroxyquinoline, (8HQ), experiences a renaissance due to its utility as a building block in metallosupramolecular chemistry and its versatile use of its derivatives in various fields of analytical chemistry, materials science, and pharmaceutics. It forms stable complexes with a variety of metal ions. Assembly of more than one such unit to form a polydentate chelator enhances its coordinating ability and the related properties due to the chelate effect resulting in high stability constant. Keeping in view the above, a nonadentate chelator N-[3,5-bis(8-hydroxyquinoline-2-amido)cyclohexyl]-8-hydroxyquinoline-2-carboxamide, (TACH2OX), containing a central cis,cis-1,3,5-triaminocyclohexane appended to three 8-hydroxyquinoline at 2-position through amide linkage is developed, and its solution thermodynamics, photophysical and Density Functional Theory (DFT) studies were undertaken. The synthesis of TACH2OX was carried out by condensation of cis,cis-1,3,5-triaminocyclohexane, (TACH) with 8‐hydroxyquinoline‐2‐carboxylic acid. The brown colored solid has been fully characterized through melting point, infrared, nuclear magnetic resonance, electrospray ionization mass and electronic spectroscopy. In solution, TACH2OX forms protonated complexes below pH 3.4, which consecutively deprotonates to generate trinegative ion with the rise of pH. Nine protonation constants for the ligand were obtained that ranges between 2.26 to 7.28. The interaction of the chelator with two trivalent metal ion Fe3+ and Al3+ were studied in aqueous solution at 298 K. The metal-ligand formation constants (ML) obtained by potentiometric and spectrophotometric method agree with each other. The protonated and hydrolyzed species were also detected in the system. The in-silico studies of the ligand, as well as the complexes including their protonated and deprotonated species assessed by density functional theory technique, gave an accurate correlation with each observed properties such as the protonation constants, stability constants, infra-red, nmr, electronic absorption and emission spectral bands. The nature of electronic and emission spectral bands in terms of number and type were ascertained from time-dependent density functional theory study and the natural transition orbitals (NTO). The global reactivity indices parameters were used for comparison of the reactivity of the ligand and the complex molecules. The natural bonding orbital (NBO) analysis could successfully describe the structure and bonding of the metal-ligand complexes specifying the percentage of contribution in atomic orbitals in the creation of molecular orbitals. The obtained high value of metal-ligand formation constants indicates that the newly synthesized chelator is a very powerful synthetic chelator. The minimum energy molecular modeling structure of the ligand suggests that the ligand, TACH2OX, in a tripodal fashion firmly coordinates to the metal ion as hexa-coordinated chelate displaying distorted octahedral geometry by binding through three sets of N, O- donor atoms, present in each pendant arm of the central tris-cyclohexaneamine tripod.

Keywords: complexes, DFT, formation constant, TACH2OX

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Authors: Susan K. Steele-Moses, Aimee Badeaux

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Background Literature: Nurse anesthesia education placed high demands on students both personally and professionally. High levels of anxiety affect student’s mental, emotional, and physical well-being, which impacts their student success. Whereas more research has focused on the health and well-being of graduate students, far less has focused specifically on nurse anesthesia students (SNRAs), who may experience higher levels of anxiety due to the rigor of their academic program. Current literature describes stressors experienced by SRNAs that cause anxiety and affect their performance, including personal, academic, clinical, interpersonal, emotional, and financial. Sample: DNP-NA 2025 and DNP-NA 2024 cohorts (N = 36). Eighteen (66.7%) students participated in the study. Instrumentation: The DASS-21 was used to measure stress (7 items; α = .87) and anxiety (7 items; α = .74) from the participants. Intervention: The mind-shift meditation app, based on cognitive behavioral therapy, is being used daily before clinical and exams to decrease nurse anesthesia students’ stress and anxiety over time. Results: At baseline, the students exhibited a moderate level of stress, but their anxiety levels were low. The range of scores was 4-21 (out of 28) for stress (M = 12.88; SD = 5.40) and 0-16 (out of 28) for anxiety (M = 6.81; SD = 5.04). Both stress and anxiety were normally distributed [SW = .242 (stress); SW = .210 (anxiety)] without any outliers. There was a significant difference between their stress and anxiety levels (t = 5.55; p < .001) at baseline. Stress and anxiety will be measured over time, with the change analyzed using repeated measures ANOVA. Implications for Practice: The use of purposeful mindfulness meditation has been shown to decrease stress and anxiety in nursing students.

Keywords: mindfulness, meditation, graduate nursing education, nursing education

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Authors: Saqib Warsi

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The evolution of optical communication technologies is pivotal in meeting the growing data demand driven by emerging technologies such as 5G, IoT, and upcoming 6G networks. This paper presents advancements in Dense Wavelength Division Multiplexing (DWDM) systems, focusing on the integration of Zero Touch Provisioning (ZTP) for simplified deployment and the ability to scale data transmission over single fiber pairs. The proposed methodology leverages high-capacity DWDM channels capable of supporting data rates exceeding 800G, ensuring future-proof solutions for both residential and enterprise communication infrastructures. Moreover, this paper examines the impact of these technologies on operational efficiency by minimizing the need for manual configuration, leading to reduced costs and faster deployment timelines. We also explore how the integration of optical amplifiers, Optical Line Amplifier (OLA) alternatives, and optical control plane protocols (such as ASON, GMPLS, OpenFlow, and SDN) play a critical role in enhancing the flexibility, scalability, and energy efficiency of optical networks. By focusing on optical solutions, this paper seeks to address the future challenges of reducing fiber pair consumption and improving network performance without compromising on capacity or reliability.

Keywords: zero-touch provisioning (ZTP), dense wavelength division multiplexing (DWDM), optical networks, optical control plane (ASON, GMPLS, OpenFlow, SDN)

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Authors: Vertika Goswami, Gargi Sharma

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The rapid evolution of fintech has led to the rise of robo-advisor platforms that utilize artificial intelligence (AI) and machine learning to offer personalized investment solutions efficiently and cost-effectively. This research paper conducts a comprehensive sentiment analysis of investor experiences with these platforms, employing natural language processing (NLP) and sentiment classification techniques. The study investigates investor perceptions, engagement, and satisfaction, identifying key drivers of positive sentiment such as clear communication, low fees, consistent returns, and robust security. Conversely, negative sentiment is linked to issues like inconsistent performance, hidden fees, poor customer support, and a lack of transparency. The analysis reveals that addressing these pain points—through improved transparency, enhanced customer service, and ongoing technological advancements—can significantly boost investor trust and satisfaction. This paper contributes valuable insights into the fields of behavioral finance and fintech innovation, offering actionable recommendations for stakeholders, practitioners, and policymakers. Future research should explore the long-term impact of these factors on investor loyalty, the role of emerging technologies, and the effects of ethical investment choices and regulatory compliance on investor sentiment.

Keywords: artificial intelligence in finance, automated investment, financial technology, investor satisfaction, investor sentiment, robo-advisors, sentimental analysis

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Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

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Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

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Authors: Andreas Stollwitzer, Lara Bettinelli, Josef Fink

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The expansion of the high-speed rail network over the past decades has resulted in new challenges for engineers, including traffic-induced resonance vibrations of railway bridges. Excessive resonance-induced speed-dependent accelerations of railway bridges during high-speed traffic can lead to negative consequences such as fatigue symptoms, distortion of the track, destabilisation of the ballast bed, and potentially even derailment. A realistic prognosis of bridge vibrations during high-speed traffic must not only rely on the right choice of an adequate calculation model for both bridge and train but first and foremost on the use of dynamic model parameters which reflect reality appropriately. However, comparisons between measured and calculated bridge vibrations are often characterised by considerable discrepancies, whereas dynamic calculations overestimate the actual responses and therefore lead to uneconomical results. This gap between measurement and calculation constitutes a complex research issue and can be traced to several causes. One major cause is found in the dynamic properties of the ballasted track, more specifically in the persisting, substantial uncertainties regarding the consideration of the ballasted track (mechanical model and input parameters) in dynamic calculations. Furthermore, the discrepancy is particularly pronounced concerning the damping values of the bridge, as conservative values have to be used in the calculations due to normative specifications and lack of knowledge. By using a large-scale test facility, the analysis of the dynamic behaviour of ballasted track has been a major research topic at the Institute of Structural Engineering/Steel Construction at TU Wien in recent years. This highly specialised test facility is designed for isolated research of the ballasted track's dynamic stiffness and damping properties – independent of the bearing structure. Several mechanical models for the ballasted track consisting of one or more continuous spring-damper elements were developed based on the knowledge gained. These mechanical models can subsequently be integrated into bridge models for dynamic calculations. Furthermore, based on measurements at the test facility, model-dependent stiffness and damping parameters were determined for these mechanical models. As a result, realistic mechanical models of the railway bridge with different levels of detail and sufficiently precise characteristic values are available for bridge engineers. Besides that, this contribution also presents another practical application of such a bridge model: Based on the bridge model, determination equations for the damping factor (as Lehr's damping factor) can be derived. This approach constitutes a first-time method that makes the damping factor of a railway bridge calculable. A comparison of this mathematical approach with measured dynamic parameters of existing railway bridges illustrates, on the one hand, the apparent deviation between normatively prescribed and in-situ measured damping factors. On the other hand, it is also shown that a new approach, which makes it possible to calculate the damping factor, provides results that are close to reality and thus raises potentials for minimising the discrepancy between measurement and calculation.

Keywords: ballasted track, bridge dynamics, damping, model design, railway bridges

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Authors: Same Noel Ngando, Yakub Abdulfatai Olatunji

Abstract:

Renewable energy micro-grids, such as those powered by solar or wind energy, are often intermittent in nature. This means that the amount of energy generated by these systems can vary depending on weather conditions or other factors, which can make it difficult to ensure a steady supply of power. To address this issue, energy storage systems have been developed to increase the reliability of renewable energy micro-grids. Battery systems have been the dominant energy storage technology for renewable energy micro-grids. Batteries can store large amounts of energy in a relatively small and compact package, making them easy to install and maintain in a micro-grid setting. Additionally, batteries can be quickly charged and discharged, allowing them to respond quickly to changes in energy demand. However, the process involved in recycling batteries is quite costly and difficult. An alternative energy storage system that is gaining popularity is hydrogen storage. Hydrogen is a versatile energy carrier that can be produced from renewable energy sources such as solar or wind. It can be stored in large quantities at low cost, making it suitable for long-distance mass storage. Unlike batteries, hydrogen does not degrade over time, so it can be stored for extended periods without the need for frequent maintenance or replacement, allowing it to be used as a backup power source when the micro-grid is not generating enough energy to meet demand. When hydrogen is needed, it can be converted back into electricity through a fuel cell. Energy consumption data is got from a particular residential area in Daegu, South Korea, and the data is processed and analyzed. From the analysis, the total energy demand is calculated, and different hybrid energy system configurations are designed using HOMER Pro (Hybrid Optimization for Multiple Energy Resources) and MATLAB software. A techno-economic and environmental comparison and life cycle assessment (LCA) of the different configurations using battery and hydrogen as storage systems are carried out. The various scenarios included PV-hydrogen-grid system, PV-hydrogen-grid-wind, PV-hydrogen-grid-biomass, PV-hydrogen-wind, PV-hydrogen-biomass, biomass-hydrogen, wind-hydrogen, PV-battery-grid-wind, PV- battery -grid-biomass, PV- battery -wind, PV- battery -biomass, and biomass- battery. From the analysis, the least cost system for the location was the PV-hydrogen-grid system, with a net present cost of about USD 9,529,161. Even though all scenarios were environmentally friendly, taking into account the recycling cost and pollution involved in battery systems, all systems with hydrogen as a storage system produced better results. In conclusion, hydrogen is becoming a very prominent energy storage solution for renewable energy micro-grids. It is easier to store compared with electric power, so it is suitable for long-distance mass storage. Hydrogen storage systems have several advantages over battery systems, including flexibility, long-term stability, and low environmental impact. The cost of hydrogen storage is still relatively high, but it is expected to decrease as more hydrogen production, and storage infrastructure is built. With the growing focus on renewable energy and the need to reduce greenhouse gas emissions, hydrogen is expected to play an increasingly important role in the energy storage landscape.

Keywords: renewable energy systems, microgrid, hydrogen production, energy storage systems

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Authors: M. Mesrar, T. Lamcharfi, Nor-S. Echatoui, F. Abdi

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The solid-state reaction method was used to synthesize ferroelectric systems with lead-free properties, specifically (1-x-y)(Na₀.₅Bi₀.₅)TiO₃-xBaTiO₃-y(K₀.₅ Bi₀.₅)TiO₃. To achieve a pure perovskite phase, the optimal calcination temperature was determined to be 1000°C for 4 hours. X-ray diffraction (XRD) analysis identified the presence of the morphotropic phase boundary (MPB) in the (1-x-y)NBT xBT-yKBT ceramics for specific molar compositions, namely (0.95NBT-0.05BT, 0.84NBT-0.16KBT, and 0.79NBT-0.05BT-0.16KBT). To enhance densification, the sintering temperature was set at 1100°C for 4 hours. Scanning electron microscopy (SEM) images exhibited homogeneous distribution and dense packing of the grains in the ceramics, indicating a uniform microstructure. These materials exhibited favorable characteristics, including high dielectric permittivity, low dielectric loss, and diffused phase transition behavior. The ceramics composed of 0.79NBT-0.05BT-0.16KBT exhibited the highest piezoelectric constant (d33=148 pC/N) and electromechanical coupling factor (kp = 0.292) among all compositions studied. This enhancement in piezoelectric properties can be attributed to the presence of the morphotropic phase boundary (MPB) in the material. This study presents a comprehensive approach to improving the performance of lead-free ferroelectric systems of composition 0.79(Na₀.₅Bi₀.₅)Ti O₃-0.05BaTiO₃-0.16(K₀.₅Bi₀.₅)TiO₃.

Keywords: solid-state method, (1-x-y)NBT-xBT-yKBT, morphotropic phase boundary, Raman spectroscopy, dielectric properties

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Authors: Kassahun Zewdie

Abstract:

-- A field experiment was conducted at Holetta research center and farmers fields during 2017 and 2018 to determine the effects of haulauxifen-methyl + florasulam (QULEX 200 WG) on broadleaf weeds in wheat. The design was a Randomized Complete Block with three replications. The treatments were included haulauxifen-Methyl + florasulam @ 25gm, 50gm and 75gm ha-1, (King-D) 2, 4-D dimethyl amine @1.0 L ha-1, 2, 4-Dichlorophenoxy acetic acid @1.0 L ha-1 rate (standard check), farmers practice twice hand weeding (25-30 and 55-60) days after sowing and weedy check. Herbicides were applied with knapsack sprayer with a spray volume of 200 L ha-1. The wheat variety “Denda” was sown at 20 cm spacing. The recommended rate of fertilizer was applied. Weed density and biomass were recorded at (25-30 and 55-60) days after sowing. The results revealed that post emergence application of haulauxifen-methyl + florasulam @50gm ha-1 had a significant (P<0.05) effect on Guizotia scabra, Polygonum nepalense, Plantago lanceolata, Galinsoga parviflora, Sonchus spp., Galium spurium, Amaranthus hybridus, Raphanus raphanistrum and Medicago polymorpha population. The magnitude ranged from two to four folds when comparing with weed densities recorded in the unweeded plot. The grain yield harvested from the untreated check plot was significantly lower than the rest treatments. The grain yield was improved by 17.3% over the standard check with better performance.

Keywords: broadleaf, grass, weeds, control

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Authors: Sachin Jain, Daniel Perez-Astudillo, Dunia A. Bachour, Antonio P. Sanfilippo

Abstract:

The future of solar energy in Qatar is evolving steadily. Hence, high-quality spatial solar radiation data is of the uttermost requirement for any planning and commissioning of solar technology. Generally, two types of solar radiation data are available: satellite data and ground observations. Satellite solar radiation data is developed by the physical and statistical model. Ground data is collected by solar radiation measurement stations. The ground data is of high quality. However, they are limited to distributed point locations with the high cost of installation and maintenance for the ground stations. On the other hand, satellite solar radiation data is continuous and available throughout geographical locations, but they are relatively less accurate than ground data. To utilize the advantage of both data, a product has been developed here which provides spatial continuity and higher accuracy than any of the data alone. The popular satellite databases: National Solar radiation Data Base, NSRDB (PSM V3 model, spatial resolution: 4 km) is chosen here for merging with ground-measured solar radiation measurement in Qatar. The spatial distribution of ground solar radiation measurement stations is comprehensive in Qatar, with a network of 13 ground stations. The monthly average of the daily total Global Horizontal Irradiation (GHI) component from ground and satellite data is used for error analysis. The normalized root means square error (NRMSE) values of 3.31%, 6.53%, and 6.63% for October, November, and December 2019 were observed respectively when comparing in-situ and NSRDB data. The method is based on the Empirical Bayesian Kriging Regression Prediction model available in ArcGIS, ESRI. The workflow of the algorithm is based on the combination of regression and kriging methods. A regression model (OLS, ordinary least square) is fitted between the ground and NSBRD data points. A semi-variogram is fitted into the experimental semi-variogram obtained from the residuals. The kriging residuals obtained after fitting the semi-variogram model were added to NSRBD data predicted values obtained from the regression model to obtain the final predicted values. The NRMSE values obtained after merging are respectively 1.84%, 1.28%, and 1.81% for October, November, and December 2019. One more explanatory variable, that is the ground elevation, has been incorporated in the regression and kriging methods to reduce the error and to provide higher spatial resolution (30 m). The final GHI maps have been created after merging, and NRMSE values of 1.24%, 1.28%, and 1.28% have been observed for October, November, and December 2019, respectively. The proposed merging method has proven as a highly accurate method. An additional method is also proposed here to generate calibrated maps by using regression and kriging model and further to use the calibrated model to generate solar radiation maps from the explanatory variable only when not enough historical ground data is available for long-term analysis. The NRMSE values obtained after the comparison of the calibrated maps with ground data are 5.60% and 5.31% for November and December 2019 month respectively.

Keywords: global horizontal irradiation, GIS, empirical bayesian kriging regression prediction, NSRDB

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Authors: Naheem Olakunle Adesina

Abstract:

The memristor is considered as one of the promising candidates for mamoelectronic engineering and applications. Owing to its high compatibility with CMOS, nanoscale size, and low power consumption, memristor has been employed in the design of commonly used circuits such as phase-locked loop (PLL). In this paper, we designed a memristor-based loop filter (LF) together with other components of PLL. Following this, we evaluated the noise-rejection feature of loop filter by comparing the noise levels of input and output signals of the filter. Our SPICE simulation results showed that memristor behaves like a linear resistor at high frequencies. The result also showed that loop filter blocks the high-frequency components from phase frequency detector so as to provide a stable control voltage to the voltage controlled oscillator (VCO). In addition, we examined the effects of temperature on the performance of the designed phase locked loop circuit. A critical temperature, where there is frequency drift of VCO as a result of variations in control voltage, is identified. In conclusion, the memristor is a suitable choice for nanoelectronic systems owing to a small area, low power consumption, dense nature, high switching speed, and endurance. The proposed memristor-based loop filter, together with other components of the phase locked loop, can be designed using memristive emulator and EDA tools in current CMOS technology and simulated.

Keywords: Fast Fourier Transform, hysteresis curve, loop filter, memristor, noise, phase locked loop, voltage controlled oscillator

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Authors: Jimoh Olumide Yusuf

Abstract:

Various factors have continued to bedevil the effective teaching and learning of English Language in Nigeria and prominent among these factors are learners’ characteristics. Unfortunately, these particular factors seem to have recorded paucity of research efforts by scholars and the problem of lack of proficiency in the target language continues to linger. This study therefore investigates the relationship between specific learners’ characteristics and effective teaching of English as a Second Language (ESL) in senior secondary schools in Nigeria. To this end, Self-Determination, and Integrative Motivation Theories were applied to investigate motivation, language learning, learners’ characteristics and its relationship to language proficiency. A survey of 500 students and 100 English Language teachers across 20 schools was conducted. Descriptive statistics was used to analyze the data and findings revealed that; specific learners’ characteristics such as learners’ age, learning style and motivation significantly determine the performance of students in English Language. Specifically, students with appropriate school age, visual learning style and intrinsic motivation, demonstrated English Language proficiency; as they performed better than students with extrinsic motivation, audio and kinaesthetic learning styles. Moreover, teachers related factors such as teaching experience; teaching strategies and teachers’ extrinsic motivation also emerged as essential correlates of effective language teaching. The findings conclude that learning characteristics are significant factors that should be considered by the teachers and education planners for adequate, sequential and effective implementation of the ESL curriculum in Nigeria.

Keywords: senior secondary school, English as a second language, intrinsic motivation, Kinaesthetic learning style

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Authors: De Castro-Pardo M., Cabello J. M., Martin J. M., Ruiz F.

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In this paper, we propose a new Water Sustainability Indicator based on a Multi-Reference methodology that permits modeling compensation between the analysed criteria and provides a participative approach. The proposed indicator provides results based on 19 variables grouped into 5 dimensions: availability, access, resilience, good governance and economic capacity. The indicator was applied to assess water sustainability in 27 European countries. The results showed that Finland, the Netherlands, Sweden and the United Kingdom obtained the best global results in terms of weak water (compensatory) sustainability. In terms of strong water (non-compensatory) sustainability, no country gained acceptable results in terms of strong sustainability. Climate change and the state of freshwater resources were detected as especially vulnerable in all the analysed countries. The results identified some eastern European countries with low GDP and good performance of availability and cost of water, with bad results in terms of governance and water productivity. These results could jeopardize water sustainability in the event of a potential economic development if these limitations are not addressed. In a context of economic and political instability due to the current armed conflict in nearby countries such as Ukraine, it is especially important to pay attention to these countries, whose good governance indicators could worsen even more. The proposed indicator allowed to the identification of warning signs and could contribute to the improvement in decision-making processes. Moreover, it could improve the monitoring of international water policies.

Keywords: water sustainability, composite indicators, compensatory approach, sustainability European policies

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we propose a novel inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multi-class. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: bayesian rule, gaussian process classification model with multiclass, gaussian process prior, human action classification, laplace approximation, variational EM algorithm

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Authors: Xue Wang, Li-Wei Fan

Abstract:

The technology innovation has become the driving force of social and economic development and transformation. The guidance and support of public policies is an important condition to promote the realization of technology innovation goals. Policy effectiveness evaluation is instructive in policy learning and adjustment. This paper reviews existing studies and systematically evaluates the effectiveness of policy-driven technological innovation. We used 167 articles from WOS and CNKI databases as samples to clarify the measurement of technological innovation indicators and analyze the classification and application of policy evaluation methods. In general, technology innovation input and technological output are the two main aspects of technological innovation index design, among which technological patents are the focus of research, the number of patents reflects the scale of technological innovation, and the quality of patents reflects the value of innovation from multiple aspects. As for policy evaluation methods, statistical analysis methods are applied to the formulation, selection and evaluation of the after-effect of policies to analyze the effect of policy implementation qualitatively and quantitatively. The bibliometric methods are mainly based on the public policy texts, discriminating the inter-government relationship and the multi-dimensional value of the policy. Decision analysis focuses on the establishment and measurement of the comprehensive evaluation index system of public policy. The economic analysis methods focus on the performance and output of technological innovation to test the policy effect. Finally, this paper puts forward the prospect of the future research direction.

Keywords: technology innovation, index, policy effectiveness, evaluation of policy, bibliometric analysis

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Authors: Sajed Yaghoubnezhad, Sedygheh Rezai

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Background and Aim: Since currently in Iran, students with learning disabilities are identified after entering school, and with the approach to the gap between IQ and academic achievement, the purpose of this study is to design and calculate the content validity of the pre-school screening checklist (5-7) exposed to learning difficulties. Methods: This research is a fundamental study, and in terms of data collection method, it is quantitative research with a descriptive approach. In order to design this checklist, after reviewing the research background and theoretical foundations, cognitive abilities (visual processing, auditory processing, phonological awareness, executive functions, spatial visual working memory and fine motor skills) are considered the basic variables of school learning. The basic items and worksheets of the screening checklist of pre-school students 5 to 7 years old with learning difficulties were compiled based on the mentioned abilities and were provided to the specialists in order to calculate the content validity ratio index. Results: Based on the results of the table, the validity of the CVR index of the background information checklist is equal to 0.9, and the CVR index of the performance checklist of preschool children (5 to7 years) is equal to 0.78. In general, the CVR index of this checklist is reported to be 0.84. The results of this study provide good evidence for the validity of the pre-school sieve screening checklist (5-7) exposed to learning difficulties.

Keywords: checklist, screening, preschoolers, learning difficulties

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Authors: Teja Joshi

Abstract:

Laterality has shown to play a role in performance as well as injuries especially in unilateral sports disciplines. Uniquely, Artistic Gymnastics involves combination of unilateral, bilateral and complex multi-planer elements as well as gymnastics specific rotational preference. Therefore, this study was conducted to explore if any such preferences are associated with number of injuries in artistic gymnasts. To explore the association between lateral preferences, rotational preferences and injuries incidence in artistic gymnastics. Artistic gymnasts above 16 years of age, were invited to participate in an online survey. The survey included consent, lateral preference inventory, injury data collection according to anatomical locations and rotational preference for selected gymnastics elements performed on the floor exercise. SPSS version 24 was used to analyse Non-parametric data using Kruskal-Wallis (K- independent test) test. Multiple regression was performed to identify the predictor for injuries and their side in gymnasts. Total number of injuries per gymnast was associated with handedness (p value-0.049) and no significant association was noted for footdness (p value-0.207), eyedness (p value-0.491) and eardness (p value-0.798). Additionally, rotational preferences did not influence number of injuries (p value-0.521). In multiple regression, eyedness was identified as a predicting factor to determine the number of injuries. Rotational preferences were neither determined as a national strategy nor a product of lateral preference. Dominant hand had higher number of injuries in artistic gymnasts. Rotational preference is independent of laterality, number of injuries and nationality.

Keywords: sports injury, rotational preference, gymnastics, handedness

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