Search results for: prediction capability

Authors: Rahma Fitriani, Eni Sumarminingsih, Suci Astutik

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In a fast growing region, conversion of agricultural lands which are surrounded by some new development sites will occur sooner than expected. This phenomenon has been experienced by many regions in Indonesia, especially the fringe of Jakarta (BoDeTaBek). Being Indonesia’s capital city, rapid conversion of land in this area is an unavoidable process. The land conversion expands spatially into the fringe regions, which were initially dominated by agricultural land or conservation sites. Without proper control or growth management, this activity will invite greater costs than benefits. The current land use is the use which maximizes its value. In order to maintain land for agricultural activity or conservation, some efforts are needed to keep the land value of this activity as high as possible. In this case, the knowledge regarding the functional relationship between land value and its driving forces is necessary. In a fast growing region, development externalities are the assumed dominant driving force. Land value is the product of the past decision of its use leading to its value. It is also affected by the local characteristics and the observed surrounded land use (externalities) from the previous period. The effect of each factor on land value has dynamic and spatial virtues; an empirical spatial dynamic land value model will be more useful to capture them. The model will be useful to test and to estimate the extent of land use externalities on land value in the short run as well as in the long run. It serves as a basis to formulate an effective urban growth management’s policy. This study will apply the model to the case of land value in the fringe of Jakarta Metropolitan. The model will be used further to predict the effect of externalities on land value, in the form of prediction map. For the case of Jakarta’s fringe, there is some evidence about the significance of neighborhood urban activity – negative externalities, the previous land value and local accessibility on land value. The effects are accumulated dynamically over years, but they will fully affect the land value after six years.

Keywords: growth management, land use externalities, land value, spatial panel dynamic

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Authors: Sonia Barbouchi, Meriem Samcha

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Scale deposition during water injection into aquifer of oil reservoirs is a serious problem experienced in the oil production industry. One of the primary causes of scale formation and injection well plugging is mixing two waters which are incompatible. Considered individually, the waters may be quite stable at system conditions and present no scale problems. However, once they are mixed, reactions between ions dissolved in the individual waters may form insoluble products. The purpose of this study is to identify the causes of well plugging in a southern Tunisian oilfield, where fresh water has been injected into the producing wells to counteract the salinity of the formation waters and inhibit the deposition of halite. X-ray diffraction (XRD) mineralogical analysis has been carried out on scale samples collected from the blocked well. Two samples collected from both formation water and injected water were analysed using inductively coupled plasma atomic emission spectroscopy, ion chromatography and other standard laboratory techniques. The results of complete waters analysis were the typical input parameters, to determine scaling tendency. Saturation indices values related to CaCO3, CaSO4, BaSO4 and SrSO4 scales were calculated for the water mixtures at different share, under various conditions of temperature, using a computerized scale prediction model. The compatibility study results showed that mixing the two waters tends to increase the probability of barite deposition. XRD analysis confirmed the compatibility study results, since it proved that the analysed deposits consisted predominantly of barite with minor galena. At the studied temperatures conditions, the tendency for barite scale is significantly increasing with the increase of fresh water share in the mixture. The future scale inhibition and removal strategies to be implemented in the concerned oilfield are being derived in a large part from the results of the present study.

Keywords: compatibility study, produced water, scaling, water injection

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Authors: Shoumodip Roy, Ankit Singhania, K. R. K. Rao, Ravi Shankar, M. K. Agarwal, R. V. Ramna, Uttam Singh

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The productivity of a blast furnace and the quality of the hot metal produced are significantly dependent on the smoothness and stability of furnace operation. The permeability of the furnace bed, as well as the gas flow pattern, influences the steady control of process parameters. The softening – melting zone that is formed inside the furnace contributes largely in distribution of the gas flow and the bed permeability. A better shape of softening-melting zone enhances the performance of blast furnace, thereby reducing the fuel rates and improving furnace life. Therefore, predictive model of the softening- melting zone profile can be utilized to control and improve the furnace operation. The shape of softening-melting zone depends upon the physical and chemical properties of the agglomerates and iron ore charged in the furnace. The variations in the agglomerate proportion in the burden at G Blast furnace disturbed the furnace stability. During such circumstances, it was analyzed that a w-shape softening-melting zone profile was formed inside the furnace. The formation of w-shape zone resulted in poor bed permeability and non-uniform gas flow. There was a significant increase in the heat loss at the lower zone of the furnace. The fuel demand increased, and the huge production loss was incurred. Therefore, visibility of softening-melting zone profile was necessary in order to pro-actively optimize the process parameters and thereby to operate the furnace smoothly. Using stave temperatures, a model was developed that predicted the shape of the softening-melting zone inside the furnace. It was observed that furnace operated smoothly during inverse V-shape of the zone and vice-versa during w-shape. This model helped to control the heat loss, optimize the burden distribution and lower the fuel rate at G Blast Furnace, TSL Jamshedpur. As a result of furnace stabilization productivity increased by 10% and fuel rate reduced by 80 kg/thm. Details of the process have been discussed in this paper.

Keywords: agglomerate, blast furnace, permeability, softening-melting

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Authors: Yu-Chen Wei

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The relationship between organizational human capital and organizational effectiveness have been a common topic of interest to organization researchers. Much of this research has concluded that higher human capital can predict greater organizational outcomes. Whereas human capital research has traditionally focused on organizations, the current study turns to the team level human capital. In addition, there are no known empirical studies assessing the effect of human capital divergence on team performance. Team human capital refers to the sum of knowledge, ability, and experience embedded in team members. Team human capital divergence is defined as the variation of human capital within a team. This study is among the first to assess the role of human capital divergence as a moderator of the effect of team human capital on team performance. From the traditional perspective, team human capital represents the collective ability to solve problems and reducing operational risk of all team members. Hence, the higher team human capital, the higher the team performance. This study further employs social learning theory to explain the relationship between team human capital and team performance. According to this theory, the individuals will look for progress by way of learning from teammates in their teams. They expect to have upper human capital, in turn, to achieve high productivity, obtain great rewards and career success eventually. Therefore, the individual can have more chances to improve his or her capability by learning from peers of the team if the team members have higher average human capital. As a consequence, all team members can develop a quick and effective learning path in their work environment, and in turn enhance their knowledge, skill, and experience, leads to higher team performance. This is the first argument of this study. Furthermore, the current study argues that human capital divergence is negative to a team development. For the individuals with lower human capital in the team, they always feel the pressure from their outstanding colleagues. Under the pressure, they cannot give full play to their own jobs and lose more and more confidence. For the smart guys in the team, they are reluctant to be colleagues with the teammates who are not as intelligent as them. Besides, they may have lower motivation to move forward because they are prominent enough compared with their teammates. Therefore, human capital divergence will moderate the relationship between team human capital and team performance. These two arguments were tested in 510 team-seasons drawn from major league baseball (1998–2014). Results demonstrate that there is a positive relationship between team human capital and team performance which is consistent with previous research. In addition, the variation of human capital within a team weakens the above relationships. That is to say, an individual working with teammates who are comparable to them can produce better performance than working with people who are either too smart or too stupid to them.

Keywords: human capital divergence, team human capital, team performance, team level research

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Authors: Ahmed Atwa, Ashraf Hafez, Mohamed Abdelhameed, Adel Nabeeh, Mohamed Dawaba, Tamer Helmy

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Introduction and Objective: Tumour staging and grading do not usually reflect the future behavior of Wilms' tumor (WT) regarding mortality. Therefore, in this study, P53, Ki67 and cyclin A immunohistochemistry were used in a trial to predict WT cancer-specific survival (CSS). Methods: In this nonconcurrent cohort study, patients' archived data, including age at presentation, gender, history, clinical examination and radiological investigations, were retrieved then the patients were reviewed at the outpatient clinic of a tertiary care center by history-taking, clinical examination and radiological investigations to detect the oncological outcome. Cases that received preoperative chemotherapy or died due to causes other than WT were excluded. Formalin-fixed, paraffin-embedded specimens obtained from the previously preserved blocks at the pathology laboratory were taken on positively charged slides for IHC with p53, Ki67 and cyclin A. All specimens were examined by an experienced histopathologist devoted to the urological practice and blinded to the patient's clinical findings. P53 and cyclin A staining were scored as 0 (no nuclear staining),1 (<10% nuclear staining), 2 (10-50% nuclear staining) and 3 (>50% nuclear staining). Ki67 proliferation index (PI) was graded as low, borderline and high. Results: Of the 75 cases, 40 (53.3%) were males and 35 (46.7%) were females, and the median age was 36 months (2-216). With a mean follow-up of 78.6±31 months, cancer-specific mortality (CSM) occurred in 15 (20%) and 11 (14.7%) patients, respectively. Kaplan-Meier curve was used for survival analysis, and groups were compared using the Log-rank test. Multivariate logistic regression and Cox regression were not used because only one variable (cyclin A) had shown statistical significance (P=.02), whereas the other significant factor (residual tumor) had few cases. Conclusions: Cyclin A IHC should be considered as a marker for the prediction of WT CSS. Prospective studies with a larger sample size are needed.

Keywords: wilms’ tumour, nephroblastoma, urology, survival

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Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

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Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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Authors: Krishnendu Mukhopadhyay, Subhashis Kundu, Mayank Tiwari, Sameeran Pani, Padmapal, Uttam Singh

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Blast Furnace is a counter current process where burden descends from top and hot gases ascend from bottom and chemically reduce iron oxides into liquid hot metal. One of the major problems of blast furnace operation is the erratic burden descent inside furnace. Sometimes this problem is so acute that burden descent stops resulting in Hanging and instability of the furnace. This problem is very frequent in blast furnaces worldwide and results in huge production losses. This situation becomes more adverse when blast furnaces are operated at low coke rate and high coal injection rate with adverse raw materials like high alumina ore and high coke ash. For last three years, H-Blast Furnace Tata Steel was able to reduce coke rate from 450 kg/thm to 350 kg/thm with an increase in coal injection to 200 kg/thm which are close to world benchmarks and expand profitability. To sustain this regime, elimination of irregularities of blast furnace like hanging, channeling, and scaffolding is very essential. In this paper, sustaining of zero hanging spell for consecutive three years with low coke rate operation by improvement in burden characteristics, burden distribution, changes in slag regime, casting practices and adequate automation of the furnace operation has been illustrated. Models have been created to comprehend and upgrade the blast furnace process understanding. A model has been developed to predict the process of maintaining slag viscosity in desired range to attain proper burden permeability. A channeling prediction model has also been developed to understand channeling symptoms so that early actions can be initiated. The models have helped to a great extent in standardizing the control decisions of operators at H-Blast Furnace of Tata Steel, Jamshedpur and thus achieving process stability for last three years.

Keywords: hanging, channelling, blast furnace, coke

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Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

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Authors: Min L. Stewart, Patrick Johnston

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Predictive coding has been proposed as a general explanatory framework for understanding the neural mechanisms of perception. As such, an underweighting of perceptual priors has been hypothesised to underpin a range of differences in inferential and sensory processing in autism spectrum disorders. However, empirical evidence to support this has not been well established. The present study uses an electroencephalography paradigm involving changes of facial identity and person category (actors etc.) to explore how levels of autistic traits (AT) affect predictive coding at multiple stages in the visual processing hierarchy. The study uses a rapid serial presentation of faces, with hierarchically structured sequences involving both periodic and aperiodic repetitions of different stimulus attributes (i.e., person identity and person category) in order to induce contextual expectations relating to these attributes. It investigates two main predictions: (1) significantly larger and late neural responses to change of expected visual sequences in high-relative to low-AT, and (2) significantly reduced neural responses to violations of contextually induced expectation in high- relative to low-AT. Preliminary frequency analysis data comparing high and low-AT show greater and later event-related-potentials (ERPs) in occipitotemporal areas and prefrontal areas in high-AT than in low-AT for periodic changes of facial identity and person category but smaller ERPs over the same areas in response to aperiodic changes of identity and category. The research advances our understanding of how abnormalities in predictive coding might underpin aberrant perceptual experience in autism spectrum. This is the first stage of a research project that will inform clinical practitioners in developing better diagnostic tests and interventions for people with autism.

Keywords: hierarchical visual processing, face processing, perceptual hierarchy, prediction error, predictive coding

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Authors: Richa Raje, Anumol Antony

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Playing is the foremost stepping stone for childhood development. Play is an essential aspect of a child’s development and learning because it creates meaningful enduring environmental connections and increases children’s performance. The children’s proficiencies are ever varying in their course of growth. There is innovation in the activities, as it kindles the senses, surges the love for exploration, overcomes linguistic barriers and physiological development, which in turn allows them to find their own caliber, spontaneity, curiosity, cognitive skills, and creativity while learning during play. This paper aims to comprehend the learning in play which is the most essential underpinning aspect of the outdoor play area. It also assesses the trend of playgrounds design that is merely hammered with equipment's. It attempts to derive a relation between the natural environment and children’s activities and the emotions/senses that can be evoked in the process. One of the major concerns with our outdoor play is that it is limited to an area with a similar kind of equipment, thus making the play highly regimented and monotonous. This problem is often lead by the strict timetables of our education system that hardly accommodates play. Due to these reasons, the play areas remain neglected both in terms of design that allows learning and wellbeing. Poorly designed spaces fail to inspire the physical, emotional, social and psychological development of the young ones. Currently, the play space has been condensed to an enclosed playground, driveway or backyard which confines the children’s capability to leap the boundaries set for him. The paper emphasizes on study related to kids ranging from 5 to 11 years where the behaviors during their interactions in a playground are mapped and analyzed. The theory of affordance is applied to various outdoor play areas, in order to study and understand the children’s environment and how variedly they perceive and use them. A higher degree of affordance shall form the basis for designing the activities suitable in play spaces. It was observed during their play that, they choose certain spaces of interest majority being natural over other artificial equipment. The activities like rolling on the ground, jumping from a height, molding earth, hiding behind tree, etc. suggest that despite equipment they have an affinity towards nature. Therefore, we as designers need to take a cue from their behavior and practices to be able to design meaningful spaces for them, so the child gets the freedom to test their precincts.

Keywords: children, landscape design, learning environment, nature and play, outdoor play

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Authors: Seungho Shin, Keunwoo Choi, Ali Akbar, Sukkee Um

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In this study, the nanoscale transport properties and catalyst utilization of vertically aligned carbon nanotube (VACNT) catalyst layers are computationally predicted by the three-dimensional lattice Boltzmann simulation based on the quasi-random nanostructural model in pursuance of fuel cell catalyst performance improvement. A series of catalyst layers are randomly generated with statistical significance at the 95% confidence level to reflect the heterogeneity of the catalyst layer nanostructures. The nanoscale gas transport phenomena inside the catalyst layers are simulated by the D3Q19 (i.e., three-dimensional, 19 velocities) lattice Boltzmann method, and the corresponding mass transport characteristics are mathematically modeled in terms of structural properties. Considering the nanoscale reactant transport phenomena, a transport-based effective catalyst utilization factor is defined and statistically analyzed to determine the structure-transport influence on catalyst utilization. The tortuosity of the reactant mass transport path of VACNT catalyst layers is directly calculated from the streaklines. Subsequently, the corresponding effective mass diffusion coefficient is statistically predicted by applying the pre-estimated tortuosity factors to the Knudsen diffusion coefficient in the VACNT catalyst layers. The statistical estimation results clearly indicate that the morphological structures of VACNT catalyst layers reduce the tortuosity of reactant mass transport path when compared to conventional catalyst layer and significantly improve consequential effective mass diffusion coefficient of VACNT catalyst layer. Furthermore, catalyst utilization of the VACNT catalyst layer is substantially improved by enhanced mass diffusion and electric current paths despite the relatively poor interconnections of the ion transport paths.

Keywords: Lattice Boltzmann method, nano transport phenomena, polymer electrolyte fuel cells, vertically aligned carbon nanotube

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Authors: Runlian Miao, Wei Xie, Hong Zhang

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In China, Beijing-Tianjin-Hebei is regarded as a strategically important region because itenjoys highest development in economic development, opening up, innovative capacity and andpopulation. Integrated development of Beijing-Tianjin-Hebei region is increasingly emphasized by the government recently years. In 2014, it has ascended to one of the national great development strategies by Chinese central government. In 2015, Coordinated Development Planning Compendium for Beijing-Tianjin-Hebei Region was approved. Such decisions signify Beijing-Tianjin-Hebei region would lead innovation-driven economic development in China. As an essential factor to achieve national innovation-driven development and significant part of regional industry chain, the optimization of science and technology resources allocation will exert great influence to regional economic transformation and upgrading and innovation-driven development. However, unbalanced distribution, poor sharing of resources and existence of information isolated islands have contributed to different interior innovation capability, vitality and efficiency, which impeded innovation and growth of the whole region. Under such a background, to integrate and vitalize regional science and technology resources and then establish high-end, fast-responding and precise innovation service system basing on regional resources, would be of great significance for integrated development of Beijing-Tianjin-Hebei region and even handling of unbalanced and insufficient development problem in China. This research uses the method of literature review and field investigation and applies related theories prevailing home and abroad, centering service path of science and technology resources for innovation. Based on the status quo and problems of regional development of Beijing-Tianjin-Hebei, theoretically, the author proposed to combine regional economics and new economic geography to explore solution to problem of low resource allocation efficiency. Further, the author puts forward to applying digital map into resource management and building a platform for information co-building and sharing. At last, the author presents the thought to establish a specific service mode of ‘science and technology plus digital map plus intelligence research plus platform service’ and suggestion on co-building and sharing mechanism of 3 (Beijing, Tianjin and Hebei ) plus 11 (important cities in Hebei Province).

Keywords: Beijing-Tianjin-Hebei, science and technology resources, innovation service, digital platform

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Authors: Joseph Lillington, Tom Gout, Mike Harrison, Ian Farnan

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The vitrification of high-level nuclear waste within borosilicate glass and its incorporation within a multi-barrier repository deep underground is widely accepted as the preferred disposal method. However, for this to happen, any safety case will require validation that the initially localized radionuclides will not be considerably released into the near/far-field. Therefore, accurate mechanistic models are necessary to predict glass dissolution, and these should be robust to a variety of incorporated waste species and leaching test conditions, particularly given substantial variations across international waste-streams. Here, machine learning is used to predict glass material properties (viscosity, density) and glass leaching model parameters from large-scale industrial data. A variety of different machine learning algorithms have been compared to assess performance. Density was predicted solely from composition, whereas viscosity additionally considered temperature. To predict suitable glass leaching model parameters, a large simulated dataset was created by coupling MATLAB and the chemical reactive-transport code HYTEC, considering the state-of-the-art GRAAL model (glass reactivity in allowance of the alteration layer). The trained models were then subsequently applied to the large-scale industrial, experimental data to identify potentially appropriate model parameters. Results indicate that ensemble methods can accurately predict viscosity as a function of temperature and composition across all three industrial datasets. Glass density prediction shows reliable learning performance with predictions primarily being within the experimental uncertainty of the test data. Furthermore, machine learning can predict glass dissolution model parameters behavior, demonstrating potential value in GRAAL model development and in assessing suitable model parameters for large-scale industrial glass dissolution data.

Keywords: machine learning, predictive modelling, pattern recognition, radioactive waste glass

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Authors: Catherine Peyrols Wu

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Intercultural interactions are becoming increasingly common in organizations and life. These interactions are often the stage of miscommunication and conflict. In management research, these problems are commonly attributed to cultural differences in values and interactional norms. As a result, the notion that intercultural competence can minimize these challenges is widely accepted. Cultural differences, however, are not the only source of a challenge during intercultural interactions. The need to rely on a lingua franca – or common language between people who have different mother tongues – is another important one. In theory, a lingua franca can improve communication and ease coordination. In practice however, disparities in people’s ability and confidence to communicate in the language can exacerbate tensions and generate inefficiencies. In this study, we draw on power theory to develop a model of disparities in language competence and conflict in a multicultural work context. Specifically, we hypothesized that differences in language competence between interaction partners would be positively related to conflict such that people would report greater conflict with partners who have more dissimilar levels of language competence and lesser conflict with partners with more similar levels of language competence. Furthermore, we proposed that cultural intelligence (CQ) an intercultural competence that denotes an individual’s capability to be effective in intercultural situations, would weaken the relationship between disparities in language competence and conflict such that people would report less conflict with partners who have more dissimilar levels of language competence when the interaction partner has high CQ and more conflict when the partner has low CQ. We tested this model with a sample of 135 undergraduate students working in multicultural teams for 13 weeks. We used a round-robin design to examine conflict in 646 dyads nested within 21 teams. Results of analyses using social relations modeling provided support for our hypotheses. Specifically, we found that in intercultural dyads with large disparities in language competence, partners with the lowest level of language competence would report higher levels of interpersonal conflict. However, this relationship disappeared when the partner with higher language competence was also high in CQ. These findings suggest that communication in a lingua franca can be a source of conflict in intercultural collaboration when partners differ in their level of language competence and that CQ can alleviate these effects during collaboration with partners who have relatively lower levels of language competence. Theoretically, this study underscores the benefits of CQ as a complement to language competence for intercultural effectiveness. Practically, these results further attest to the benefits of investing resources to develop language competence and CQ in employees engaged in multicultural work.

Keywords: cultural intelligence, intercultural interactions, language competence, multicultural teamwork

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Authors: Konstantinos G. Kostinakis, Asimina M. Athanatopoulou

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A key issue in seismic risk analysis within the context of Performance-Based Earthquake Engineering is the evaluation of the expected seismic damage of structures under a specific earthquake ground motion. The assessment of the seismic performance strongly depends on the choice of the seismic Intensity Measure (IM), which quantifies the characteristics of a ground motion that are important to the nonlinear structural response. Several conventional IMs of ground motion have been used to estimate their damage potential to structures. Yet, none of them has been proved to be able to predict adequately the seismic damage. Therefore, alternative, scalar intensity measures, which take into account not only ground motion characteristics but also structural information have been proposed. Some of these IMs are based on integration of spectral values over a range of periods, in an attempt to account for the information that the shape of the acceleration, velocity or displacement spectrum provides. The adequacy of a number of these IMs in predicting the structural damage of 3D R/C buildings is investigated in the present paper. The investigated IMs, some of which are structure specific and some are nonstructure-specific, are defined via integration of spectral values. To achieve this purpose three symmetric in plan R/C buildings are studied. The buildings are subjected to 59 bidirectional earthquake ground motions. The two horizontal accelerograms of each ground motion are applied along the structural axes. The response is determined by nonlinear time history analysis. The structural damage is expressed in terms of the maximum interstory drift as well as the overall structural damage index. The values of the aforementioned seismic damage measures are correlated with seven scalar ground motion IMs. The comparative assessment of the results revealed that the structure-specific IMs present higher correlation with the seismic damage of the three buildings. However, the adequacy of the IMs for estimation of the structural damage depends on the response parameter adopted. Furthermore, it was confirmed that the widely used spectral acceleration at the fundamental period of the structure is a good indicator of the expected earthquake damage level.

Keywords: damage measures, bidirectional excitation, spectral based IMs, R/C buildings

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Authors: Xiaohong Li, Wenfan Yan

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Background: While it is widely considered that the university library plays a critical role in fulfilling the institution's mission and providing students’ learning experience beyond the classrooms, how the technology-enhanced library reform changed college students’ learning experience hasn’t been thoroughly investigated. The purpose of this study is to explore how technology-enhanced library reform affects students’ learning experience and career readiness and further identify the factors and effective conditions that enable the quality learning outcome of Chinese college students. Methodologies: This study selected the qualitative comparative analysis (QCA) method to explore the effects of technology-enhanced university library reform on college students’ learning experience and career readiness. QCA is unique in explaining the complex relationship between multiple factors from a holistic perspective. Compared with the traditional quantitative and qualitative analysis, QCA not only adds some quantitative logic but also inherits the characteristics of qualitative research focusing on the heterogeneity and complexity of samples. Shenyang Normal University (SNU) selected a sample of the typical comprehensive university in China that focuses on students’ learning and application of professional knowledge and trains professionals to different levels of expertise. A total of 22 current university students and 30 graduates who joined the Library Readers Association of SNU from 2011 to 2019 were selected for semi-structured interviews. Based on the data collected from these participating students, qualitative comparative analysis (QCA), including univariate necessity analysis and the multi-configuration analysis, was conducted. Findings and Discussion: QCA analysis results indicated that the influence of technology-enhanced university library restructures and reorganization on student learning experience and career readiness is the result of multiple factors. Technology-enhanced library equipment and other hardware restructured to meet the college students learning needs and have played an important role in improving the student learning experience and learning persistence. More importantly, the soft characteristics of technology-enhanced library reform, such as library service innovation space and culture space, have a positive impact on student’s career readiness and development. Technology-enhanced university library reform is not only the change in the building's appearance and facilities but also in library service quality and capability. The study also provides suggestions for policy, practice, and future research.

Keywords: career readiness, college student learning experience, qualitative comparative analysis (QCA), technology-enhanced library reform

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Authors: Glenn Auld Knierim

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Automated robotic winding of high-temperature superconductors (HTS) addresses precision, efficiency, and reliability critical to the commercialization of products. Today’s HTS materials are mature and commercially promising but require manufacturing attention. In particular to the exaggerated rectangular cross-section (very thin by very wide), winding precision is critical to address the stress that can crack the fragile ceramic superconductor (SC) layer and destroy the SC properties. Damage potential is highest during peak operations, where winding stress magnifies operational stress. Another challenge is operational parameters such as magnetic field alignment affecting design performance. Winding process performance, including precision, capability for geometric complexity, and efficient repeatability, are required for commercial production of current HTS. Due to winding limitations, current HTS magnets focus on simple pancake configurations. HTS motors, generators, MRI/NMR, fusion, and other projects are awaiting robotic wound solenoid, planar, and spherical magnet configurations. As with conventional power cables, full transposition winding is required for long length alternating current (AC) and pulsed power cables. Robotic production is required for transposition, periodic swapping of cable conductors, and placing into precise positions, which allows power utility required minimized reactance. A full transposition SC cable, in theory, has no transmission length limits for AC and variable transient operation due to no resistance (a problem with conventional cables), negligible reactance (a problem for helical wound HTS cables), and no long length manufacturing issues (a problem with both stamped and twisted stacked HTS cables). The Infinity Physics team is solving manufacturing problems by developing automated manufacturing to produce the first-ever reliable and utility-grade commercial SC cables and magnets. Robotic winding machines combine mechanical and process design, specialized sense and observer, and state-of-the-art optimization and control sequencing to carefully manipulate individual fragile SCs, especially HTS, to shape previously unattainable, complex geometries with electrical geometry equivalent to commercially available conventional conductor devices.

Keywords: automated winding manufacturing, high temperature superconductor, magnet, power cable

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Authors: Alexander A. Tokmakov

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Cell-free protein synthesis is widely used to synthesize recombinant proteins. It allows genome-scale expression of various polypeptides under strictly controlled uniform conditions. However, only a minor fraction of all proteins can be successfully expressed in the systems of protein synthesis that are currently used. The factors determining expression success are poorly understood. At present, the vast volume of data is accumulated in cell-free expression databases. It makes possible comprehensive bioinformatics analysis and identification of multiple features associated with successful cell-free expression. Here, we describe an approach aimed at identification of multiple physicochemical and structural properties of amino acid sequences associated with protein solubility and aggregation and highlight major correlations obtained using this approach. The developed method includes: categorical assessment of the protein expression data, calculation and prediction of multiple properties of expressed amino acid sequences, correlation of the individual properties with the expression scores, and evaluation of statistical significance of the observed correlations. Using this approach, we revealed a number of statistically significant correlations between calculated and predicted features of protein sequences and their amenability to cell-free expression. It was found that some of the features, such as protein pI, hydrophobicity, presence of signal sequences, etc., are mostly related to protein solubility, whereas the others, such as protein length, number of disulfide bonds, content of secondary structure, etc., affect mainly the expression propensity. We also demonstrated that amenability of polypeptide sequences to cell-free expression correlates with the presence of multiple sites of post-translational modifications. The correlations revealed in this study provide a plethora of important insights into protein folding and rationalization of protein production. The developed bioinformatics approach can be of practical use for predicting expression success and optimizing cell-free protein synthesis.

Keywords: bioinformatics analysis, cell-free protein synthesis, expression success, optimization, recombinant proteins

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Authors: Wenzheng Fu, Yue Fu, Zhijiang Dong, Yujian Fu

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The integration of artificial intelligence (AI) and machine learning (ML) into project management is transforming how engineering projects are executed, monitored, and controlled. This paper provides a comprehensive survey of AI and ML applications in project management, systematically categorizing their use in key areas such as project data analytics, monitoring, tracking, scheduling, and reporting. As project management becomes increasingly data-driven, AI and ML offer powerful tools for improving decision-making, optimizing resource allocation, and predicting risks, leading to enhanced project outcomes. The review highlights recent research that demonstrates the ability of AI and ML to automate routine tasks, provide predictive insights, and support dynamic decision-making, which in turn increases project efficiency and reduces the likelihood of costly delays. This paper also examines the emerging trends and future opportunities in AI-driven project management, such as the growing emphasis on transparency, ethical governance, and data privacy concerns. The research suggests that AI and ML will continue to shape the future of project management by driving further automation and offering intelligent solutions for real-time project control. Additionally, the review underscores the need for ongoing innovation and the development of governance frameworks to ensure responsible AI deployment in project management. The significance of this review lies in its comprehensive analysis of AI and ML’s current contributions to project management, providing valuable insights for both researchers and practitioners. By offering a structured overview of AI applications across various project phases, this paper serves as a guide for the adoption of intelligent systems, helping organizations achieve greater efficiency, adaptability, and resilience in an increasingly complex project management landscape.

Keywords: artificial intelligence, decision support systems, machine learning, project management, resource optimization, risk prediction

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Authors: Strahinja Kovacevic, Milica Karadzic Banjac, Jasmina Vitas, Stefan Vukmanovic, Radomir Malbasa, Lidija Jevric, Sanja Podunavac-Kuzmanovic

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The present study deals with chemometric regression analysis of quality parameters and the radical scavenging ability of kombucha fermented kefir-like products obtained with winter savory (WS), peppermint (P), stinging nettle (SN) and wild thyme tea (WT) kombucha inoculums. Each analyzed sample was described by milk fat content (MF, %), total unsaturated fatty acids content (TUFA, %), monounsaturated fatty acids content (MUFA, %), polyunsaturated fatty acids content (PUFA, %), the ability of free radicals scavenging (RSA Dₚₚₕ, % and RSA.ₒₕ, %) and pH values measured after each hour from the start until the end of fermentation. The aim of the conducted regression analysis was to establish chemometric models which can predict the radical scavenging ability (RSA Dₚₚₕ, % and RSA.ₒₕ, %) of the samples by correlating it with the MF, TUFA, MUFA, PUFA and the pH value at the beginning, in the middle and at the end of fermentation process which lasted between 11 and 17 hours, until pH value of 4.5 was reached. The analysis was carried out applying univariate linear (ULR) and multiple linear regression (MLR) methods on the raw data and the data standardized by the min-max normalization method. The obtained models were characterized by very limited prediction power (poor cross-validation parameters) and weak statistical characteristics. Based on the conducted analysis it can be concluded that the resulting radical scavenging ability cannot be precisely predicted only on the basis of MF, TUFA, MUFA, PUFA content, and pH values, however, other quality parameters should be considered and included in the further modeling. This study is based upon work from project: Kombucha beverages production using alternative substrates from the territory of the Autonomous Province of Vojvodina, 142-451-2400/2019-03, supported by Provincial Secretariat for Higher Education and Scientific Research of AP Vojvodina.

Keywords: chemometrics, regression analysis, kombucha, quality control

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Authors: Agustin Maciel-Padilla

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This paper explores the most significant change to Japan’s security strategy since the end of World War II, in particular Prime Minister Fumio Kishida’s government publication, in late 2022, of 3 policy documents (the National Security Strategy [NSS], the National Defense Strategy and the Defense Buildup Program) that basically propose to expand the country’s military capabilities and to increase military spending over a 5-year period. These policies represent a remarkable transformation of Japan’s defense-oriented policy followed since 1946. These proposals have been under analysis and debate since they were announced, as it was also Japan’s historic ambition to strengthening its deterrence capabilities in the context of a more complex regional security environment. Even though this new defense posture has attracted significant international attention, it is far from representing a done deal because of the fact that there is still a long way to go to implement this vision because of a wide variety of political and economic issues. Japan is currently experiencing the most dangerous security environment since the end of World War II, and this situation led Japan to intensify its dialogue with the United States to reflect a re-evaluation of deterrence in the face of a rapidly worsening security environment, a changing balance of power in East Asia, and the arrival of a new era of “great power competition”. Japan’s new documents, for instance, identify China and North Korea’s as posing, respectively, a strategic challenge and an imminent threat. Japan has also noted that Russia’s invasion of Ukraine has contributed to erode the foundation of the international order. It is considered that Russia’s aggression was possible because Ukraine’s defense capability was not enough for effective deterrence. Moreover, Japan’s call for “counterstrike capabilities” results from a recognition that China and North Korea’s ballistic and cruise missiles could overwhelm Japan’s air and missile defense systems, and therefore there is an urgent need to strengthen deterrence and resilience. In this context, this paper will focus on the impact of these changes on the US-Japan alliance. Adapting this alliance to Tokyo’s new ambitions and capabilities could be critical in terms of updating their traditional protection/access to bases arrangement, interoperability and joint command and control issues, as well as regarding the security–economy nexus. While China is Japan’s largest trading partner, and trade between the two has been growing, US-Japan economic relationship has been slower, notwithstanding the fact that US-Japan security cooperation has strengthened significantly in recent years.

Keywords: us-japan alliance, japan security, great power competition, interoperability

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Authors: Abdullah Alenezi, Mane Alsudrawi, Rafat Misak

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Kuwait is faced with a potentially wide and harmful range of both natural and anthropogenic hazardous events such as dust storms, floods, fires, nuclear accidents, earthquakes, oil spills, tsunamis and other disasters. For Kuwait can be highly vulnerable to these complex environmental risks, an up-to-date and in-depth understanding of their typology, genesis, and impact on the Kuwaiti society is needed. Adequate anticipation and management of environmental crises further require a comprehensive system of decision support to the benefit of decision makers to further bridge the gap between (technical) risk understanding and public action. For that purpose, the Kuwait Institute for Scientific Research (KISR), intends to establish a decision support center for management of the environmental crisis in Kuwait. The center will support policy makers, stakeholders and national committees with technical information that helps them efficiently and effectively assess, monitor to manage environmental disasters using decision support tools. These tools will build on state of the art quantification and visualization techniques, such as remote sensing information, Geographical Information Systems (GIS), simulation and prediction models, early warning systems, etc. The center is conceived as a central facility which will be designed, operated and managed by KISR in coordination with national authorities and decision makers of the country. Our vision is that by 2035 the center will be recognized as a leading national source of scientific advice on national risk management in Kuwait and build unity of effort among Kuwaiti’s institutions, government agencies, public and private organizations through provision and sharing of information. The project team now focuses on capacity building through upgrading some KISR facilities manpower development, build strong collaboration with international alliance.

Keywords: decision support, environment, hazard, Kuwait

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Authors: Iddy Iddy, Qin Jiang, Changkuan Zhang

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This paper addresses the hydraulic performance of curtain wall breakwaters as a coastal structure protection based on the particles method modelling. The hydraulic functions of curtain wall as wave barriers by reflecting large parts of incident waves through the vertical wall, a part transmitted and a particular part was dissipating the wave energies through the eddy flows formed beneath the lower end of the plate. As a Lagrangian particle, the Moving Particle Semi-implicit (MPS) method which has a robust capability for numerical representation has proven useful for design of structures application that concern free-surface hydrodynamic flow, such as wave breaking and overtopping. In this study, a vertical two-dimensional numerical model for the simulation of violent flow associated with the interaction between the curtain-wall breakwaters and progressive water waves is developed by MPS method in which a higher precision pressure gradient model and free surface particle recognition model were proposed. The wave transmission, reflection, and energy dissipation of the vertical wall were experimentally and theoretically examined. With the numerical wave flume by particle method, very detailed velocity and pressure fields around the curtain-walls under the action of waves can be computed in each calculation steps, and the effect of different wave and structural parameters on the hydrodynamic characteristics was investigated. Also, the simulated results of temporal profiles and distributions of velocity and pressure in the vicinity of curtain-wall breakwaters are compared with the experimental data. Herein, the numerical investigation of hydraulic performance of curtain wall breakwaters indicated that the incident wave is largely reflected from the structure, while the large eddies or turbulent flows occur beneath the curtain-wall resulting in big energy losses. The improved MPS method shows a good agreement between numerical results and analytical/experimental data which are compared to related researches. It is thus verified that the improved pressure gradient model and free surface particle recognition methods are useful for enhancement of stability and accuracy of MPS model for water waves and marine structures. Therefore, it is possible for particle method (MPS method) to achieve an appropriate level of correctness to be applied in engineering fields through further study.

Keywords: curtain wall breakwaters, free surface flow, hydraulic performance, improved MPS method

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Authors: Radul Shishkov, Orlin Davchev

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The digital era has revolutionized architectural practices, with building information modeling (BIM) emerging as a pivotal tool for architects, engineers, and construction professionals. However, the transition from traditional methods to BIM-centric approaches poses significant challenges, particularly in the context of existing structures. This research introduces a technical approach to bridge this gap through the development of algorithms that facilitate the automated transformation of 3D point cloud data into detailed BIM models. The core of this research lies in the application of algorithmic modeling and computational design methods to interpret and reconstruct point cloud data -a collection of data points in space, typically produced by 3D scanners- into comprehensive BIM models. This process involves complex stages of data cleaning, feature extraction, and geometric reconstruction, which are traditionally time-consuming and prone to human error. By automating these stages, our approach significantly enhances the efficiency and accuracy of creating BIM models for existing buildings. The proposed algorithms are designed to identify key architectural elements within point clouds, such as walls, windows, doors, and other structural components, and to translate these elements into their corresponding BIM representations. This includes the integration of parametric modeling techniques to ensure that the generated BIM models are not only geometrically accurate but also embedded with essential architectural and structural information. Our methodology has been tested on several real-world case studies, demonstrating its capability to handle diverse architectural styles and complexities. The results showcase a substantial reduction in time and resources required for BIM model generation while maintaining high levels of accuracy and detail. This research contributes significantly to the field of architectural technology by providing a scalable and efficient solution for the integration of existing structures into the BIM framework. It paves the way for more seamless and integrated workflows in renovation and heritage conservation projects, where the accuracy of existing conditions plays a critical role. The implications of this study extend beyond architectural practices, offering potential benefits in urban planning, facility management, and historic preservation.

Keywords: BIM, 3D point cloud, algorithmic modeling, computational design, architectural reconstruction

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Authors: I. Ahumada, L. Ascar, C. Pedraza, J. Montecino

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It has been found that the addition of biosolids to soil is beneficial to soil health, enriching soil with essential nutrient elements. Although this sludge has properties that allow for the improvement of the physical features and productivity of agricultural and forest soils and the recovery of degraded soils, they also contain trace elements, organic trace and pathogens that can cause damage to the environment. The application of these biosolids to land without the total reclamation and the treated wastewater can transfer these compounds into terrestrial and aquatic environments, giving rise to potential accumulation in plants. The general aim of this study was to evaluate the bioavailability of bisphenol A (BPA), and 17 α-ethynyl estradiol (EE2) in a soil-biosolid system using wheat (Triticum aestivum) plant assays and a predictive extraction method using a solution of hydroxypropyl-β-cyclodextrin (HPCD) to determine if it is a reliable surrogate for this bioassay. Two soils were obtained from the central region of Chile (Lo Prado and Chicauma). Biosolids were obtained from a regional wastewater treatment plant. The soils were amended with biosolids at 90 Mg ha-1. Soils treated with biosolids, spiked with 10 mgkg-1 of the EE2 and 15 mgkg-1 and 30 mgkg-1of BPA were also included. The BPA, and EE2 concentration were determined in biosolids, soils and plant samples through ultrasound assisted extraction, solid phase extraction (SPE) and gas chromatography coupled to mass spectrometry determination (GC/MS). The bioavailable fraction found of each one of soils cultivated with wheat plants was compared with results obtained through a cyclodextrin biosimulator method. The total concentration found in biosolid from a treatment plant was 0.150 ± 0.064 mgkg-1 and 12.8±2.9 mgkg-1 of EE2 and BPA respectively. BPA and EE2 bioavailability is affected by the organic matter content and the physical and chemical properties of the soil. The bioavailability response of both compounds in the two soils varied with the EE2 and BPA concentration. It was observed in the case of EE2, the bioavailability in wheat plant crops contained higher concentrations in the roots than in the shoots. The concentration of EE2 increased with increasing biosolids rate. On the other hand, for BPA, a higher concentration was found in the shoot than the roots of the plants. The predictive capability the HPCD extraction was assessed using a simple linear correlation test, for both compounds in wheat plants. The correlation coefficients for the EE2 obtained from the HPCD extraction with those obtained from the wheat plants were r= 0.99 and p-value ≤ 0.05. On the other hand, in the case of BPA a correlation was not found. Therefore, the methodology was validated with respect to wheat plants bioassays, only in the EE2 case. Acknowledgments: The authors thank FONDECYT 1150502.

Keywords: emerging compounds, bioavailability, biosolids, endocrine disruptors

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Authors: A. Rezaei, M. Huisman, W. Van Paepegem

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Atomic interactions in molecular systems are mainly studied by particle mechanics. Nevertheless, researches have also put on considerable effort to simulate them using continuum methods. In early 2000, simple equivalent finite element models have been developed to study the mechanical properties of carbon nanotubes and graphene in composite materials. Afterward, many researchers have employed similar structural simulation approaches to obtain mechanical properties of nanostructured materials, to simplify interface behavior of fiber-reinforced composites, and to simulate defects in carbon nanotubes or graphene sheets, etc. These structural approaches, however, are limited to small deformations due to complicated local rotational coordinates. This article proposes a method for the finite element simulation of molecular mechanics. For ease in addressing the approach, here it is called Structural Finite Element Molecular Modeling (SFEMM). SFEMM method improves the available structural approaches for large deformations, without using any rotational degrees of freedom. Moreover, the method simulates molecular conformation, which is a big advantage over the previous approaches. Technically, this method uses nonlinear multipoint constraints to simulate kinematics of the atomic multibody interactions. Only truss elements are employed, and the bond potentials are implemented through constitutive material models. Because the equilibrium bond- length, bond angles, and bond-torsion potential energies are intrinsic material parameters, the model is independent of initial strains or stresses. In this paper, the SFEMM method has been implemented in ABAQUS finite element software. The constraints and material behaviors are modeled through two Fortran subroutines. The method is verified for the bond-stretch, bond-angle and bond-torsion of carbon atoms. Furthermore, the capability of the method in the conformation simulation of molecular structures is demonstrated via a case study of a graphene sheet. Briefly, SFEMM builds up a framework that offers more flexible features over the conventional molecular finite element models, serving the structural relaxation modeling and large deformations without incorporating local rotational degrees of freedom. Potentially, the method is a big step towards comprehensive molecular modeling with finite element technique, and thereby concurrently coupling an atomistic domain to a solid continuum domain within a single finite element platform.

Keywords: finite element, large deformation, molecular mechanics, structural method

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Authors: Xin Wu, Yongfeng Zhao, Qingxiang Meng

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In China, quite low proportion of crop residues were used as feedstuff because of its poor palatability and low digestibility. Steam explosion is a physical and chemical feed processing technology which has great potential to improve sapidity and digestibility of crop residues. To investigate the effect of the steam explosion on chemical compositions and efficient energy values, crop residues (rice straw, wheat straw and maize stover) were processed by steam explosion (steam temperature 120-230°C, steam pressure 2-26kg/cm², 40min). Steam-exploded crop residues were regarded as treatment groups and untreated ones as control groups, nutritive compositions were analyzed and effective energy values were calculated by prediction model in INRA (1988, 2010) for both groups. Results indicated that the interaction between treatment and variety has a significant effect on chemical compositions of crop residues. Steam explosion treatment of crop residues decreased neutral detergent fiber (NDF) significantly (P < 0.01), and compared with untreated material, NDF content of rice straw, wheat straw, and maize stover lowered 21.46%, 32.11%, 28.34% respectively. Acid detergent lignin (ADL) of crop residues increased significantly after the steam explosion (P < 0.05). The content of crude protein (CP), ether extract (EE) and Ash increased significantly after steam explosion (P < 0.05). Moreover, predicted effective energy values of each steam-exploded residue were higher than that of untreated ones. The digestible energy (DE), metabolizable energy (ME), net energy for maintenance (NEm) and net energy for gain (NEg)of steam-exploded rice straw were 3.06, 2.48, 1.48and 0.29 MJ/kg respectively and increased 46.21%, 46.25%, 49.56% and 110.92% compared with untreated ones(P < 0.05). Correspondingly, the energy values of steam-exploded wheat straw were 2.18, 1.76, 1.03 and 0.15 MJ/kg, which were 261.78%, 261.29%, 274.59% and 1014.69% greater than that of wheat straw (P < 0.05). The above predicted energy values of steam exploded maize stover were 5.28, 4.30, 2.67 and 0.82 MJ/kg and raised 109.58%, 107.71%, 122.57% and 332.64% compared with the raw material(P < 0.05). In conclusion, steam explosion treatment could significantly decrease NDF content, increase ADL, CP, EE, Ash content and effective energy values of crop residues. The effect of steam explosion was much more obvious for wheat straw than the other two kinds of residues under the same condition.

Keywords: chemical compositions, crop residues, efficient energy values, steam explosion

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Authors: Fulufhelo Amanda Doboro, Kgomotso Sebeko, Stephen Njiro, Moritz Van Vuuren

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Ovine herpesvirus 2 (OvHV-2) genome obtained from the lymphopblastoid cell line of a BJ1035 cow was recently sequenced in the United States of America (USA). Information on the sequences of OvHV-2 genes obtained from South African strains from bovine or other African countries and molecular characterization of OvHV-2 is not documented. Present investigation provides information on the nucleotide and derived amino acid sequences and genetic diversity of Ov 7, Ov 8 ex2, ORF 27 and ORF 73 genes, of these genes from OvHV-2 strains circulating in South Africa. Gene-specific primers were designed and used for PCR of DNA extracted from 42 bovine blood samples that previously tested positive for OvHV-2. The expected PCR products of 495 bp, 253 bp, 890 bp and 1632 bp respectively for Ov 7, Ov 8 ex2, ORF 27 and ORF 73 genes were sequenced and multiple sequence analysis done on the selected regions of the sequenced PCR products. Two genotypes for ORF 27 and ORF 73 gene sequences, and three genotypes for Ov 7 and Ov 8 ex2 gene sequences were identified, and similar groupings for the derived amino acid sequences were obtained for each gene. Nucleotide and amino acid sequence variations that led to the identification of the different genotypes included SNPs, deletions and insertions. Sequence analysis of Ov 7 and ORF 27 genes revealed variations that distinguished between sequences from SA and reference OvHV-2 strains. The implication of geographic origin among SA sequences was difficult to evaluate because of random distribution of genotypes in the different provinces, for each gene. However, socio-economic factors such as migration of people with animals, or transportation of animals for agricultural or business use from one province to another are most likely to be responsible for this observation. The sequence variations observed in this study have no impact on the antibody binding activities of glycoproteins encoded by Ov 7, Ov 8 ex2 and ORF 27 genes, as determined by prediction of the presence of B cell epitopes using BepiPred 1.0. The findings of this study will be used for selection of gene candidates for the development of diagnostic assays and vaccine development as well.

Keywords: amino acid, genetic diversity, genes, nucleotide

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Authors: Yunha Ryu, Kyoungsik Kim

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Raman spectroscopy is one of the most powerful techniques for chemical detection, but the low sensitivity originated from the extremely small cross-section of the Raman scattering limits the practical use of Raman spectroscopy. To overcome this problem, Surface Enhanced Raman Scattering (SERS) has been intensively studied for several decades. Because the SERS effect is mainly induced from strong electromagnetic near-field enhancement as a result of localized surface plasmon resonance of metallic nanostructures, it is important to design the plasmonic structures with high density of electromagnetic hot spots for SERS substrate. One of the useful fabrication methods is using porous nanomaterial as a template for metallic structure. Internal pores on a scale of tens of nanometers can be strong EM hotspots by confining the incident light. Also, porous structures can capture more target molecules than non-porous structures in a same detection spot thanks to the large surface area. Herein we report the facile fabrication method of porous SERS substrate by integrating solvent-assisted nanoimprint lithography and selective etching of block copolymer. We obtained nanostructures with high porosity via simple selective etching of the one microdomain of the diblock copolymer. Furthermore, we imprinted of the nanocone patterns into the spin-coated flat block copolymer film to make three-dimensional SERS substrate for the high density of SERS hot spots as well as large surface area. We used solvent-assisted nanoimprint lithography (SAIL) to reduce the fabrication time and cost for patterning BCP film by taking advantage of a solvent which dissolves both polystyrenre and poly(methyl methacrylate) domain of the block copolymer, and thus block copolymer film was molded under the low temperature and atmospheric pressure in a short time. After Ag deposition, we measured Raman intensity of dye molecules adsorbed on the fabricated structure. Compared to the Raman signals of Ag coated solid nanocone, porous nanocone showed 10 times higher Raman intensity at 1510 cm(-1) band. In conclusion, we fabricated porous metallic nanocone arrays with high density electromagnetic hotspots by templating nanoimprinted diblock copolymer with selective etching and demonstrated its capability as an effective SERS substrate.

Keywords: block copolymer, porous nanostructure, solvent-assisted nanoimprint, surface-enhanced Raman spectroscopy

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Authors: Nehal F. Hassib, Rasha M. El Hossini, Inas M. Sayed, Maha R. Abouzeid, Nermeen A. Bayoumi, Aida M. Mosaad, Lamia K. Gadallah, Moataz Bellah A. T. Abdelbari, Heba A. El-Sayed, Hasnaa Elbendary, Ghada Abdel-Salam, Maha Zaki, Mostafa I. Mostafa, Mohamed S. Abdel-Hamid

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Enamel, the outermost layer of the tooth crown, is the hardest dental tissue and serves as a protective barrier. Amelogenesis, the process of enamel formation, is regulated by multiple genes to ensure normal, defect-free enamel. Defective enamel manifests as hypoplasia or as amelogenesis imperfecta (AI), which may occur in isolation or as part of a syndrome. This study presents 29 patients from 18 unrelated families (16 females and 13 males) who exhibited distinctive enamel abnormalities. We conducted thorough clinical examinations and requested laboratory and radiological investigations. Blood samples were collected for molecular analysis, utilizing a targeted panel for known AI variants and whole exome sequencing for unknown variants. Eleven variants linked to enamel anomalies were identified: four genes associated with isolated AI (WDR72, ACP4, SLC24A4, and FAM83H) and seven associated with syndromic forms, including enamel renal syndrome (FAM20A), tricho-dento-osseous syndrome (DLX3), Jalili syndrome (CNNM4), and others linked to neurological and mitochondrial disorders, skeletal dysplasia, and peroxisome disorders. Abnormal oral and dental phenotypes in individuals may indicate serious inherited disorders. Enamel defects have significant implications for aesthetics, function, and patients' psychological well-being. Dental examination, alongside clinical and molecular investigations, is crucial for the accurate diagnosis and prediction of inherited conditions.

Keywords: amelogenesis imperfecta, enamel defect, Enamel renal syndrome, DLX3, Jalili syndrome, WDR72, FAM83H, whole exome sequencing

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