Search results for: DC power systems

Authors: Omil Nady Mahrous Maximous

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The article deals with the use of modern information technologies to achieve pro-ecological marketing goals in company-customer relationships. The purpose of the article is to show the possibilities of implementing modern information technologies. In B2C relationships, marketing departments face challenges stemming from the need to quickly segment customers and the current fragmentation of data across many systems, which significantly hinders the achievement of marketing goals. Thus, Article proposes the use of modern IT solutions in the field of marketing activities of companies, taking into account their environmental goals. As a result, its importance for the economic and social development of the emerging countries has increased. While traditional companies emphasize profit maximization as a core business principle, social enterprises must solve social problems at the expense of profit. This rationale gives social enterprises an edge over traditional businesses by meeting the needs of those at the bottom of the pyramid. This also represents a major challenge for social business, since social business acts on the one hand for the benefit of the public and on the other strives for financial stability. Otherwise, the company is unlikely to be fired from the company. Cultures play a role in business communication and research. Using the example of language in international relations, the article presents the problem of the articulation of research cultures in management and linguistics and of cultures as such. After an overview of current research on language in international relations, this article presents the approach to communication in international economy from a linguistic point of view and tries to explain the problems of communication in business starting from linguistic research. A step towards interdisciplinary research that brings together research in the fields of management and linguistics.

Keywords: international marketing, marketing mix, marketing research, small and medium-sized enterprises, strategic marketing, B2B digital marketing strategy, digital marketing, digital marketing maturity model, SWOT analysis consumer behavior, experience, experience marketing, marketing employee organizational performance, internal marketing, internal customer, direct marketing, mobile phones mobile marketing, Sms advertising

Procedia PDF Downloads 39

Authors: Simone F. Medeiros, Jessica M. Fonseca, Gizelda M. Alves, Danilo M. Santos, Sérgio P. Campana-Filho, Amilton M. Santos

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Stimuli responsive and biocompatible hydrogel nanoparticles have gained special attention as systems for potential applications in controlled release of drugs to improve their therapeutic efficacy while minimizing side effects. In this work, novel solid dispersions based on thermo- and pH-responsive poly(N-vinylcaprolactam-co-itaconic acid-co-ethylene- glycol dimethacrylate) hydrogel nanoparticles embedded in chitosan matrices were prepared via spray drying for controlled release of ketoprofen. Firstly, the hydrogel nanoparticles containing ketoprofen were prepared via precipitation polymerization and their stimuli-responsive behavior, thermal properties, chemical composition, encapsulation efficiency and morphology were characterized. Then, hydrogel nanoparticles with different particles size were embedded into chitosan matrices via spray-drying. Scanning electron microscopy (SEM) analyses were performed to investigate the particles size, dispersity and morphology. Finally, ketoprofen release profiles were studied as a function of pH and temperature. Chitosan/poly(NVCL-co-IA-co-EGDMA)-ketoprofen microparticles presented spherical shape, rough surface and pronounced agglomeration, indicating that hydrogels nanoparticles loaded with ketoprofen modified the surface of chitosan matrix. The maximum encapsulation efficiency of ketoprofen into hydrogel nanoparticles was 57.8% and the electrostatic interactions between amino groups from chitosan and carboxylic groups from hydrogel nanoparticles were able to control ketoprofen release. The hydrogel nanoparticles themselves were capable to retard the release of ketoprofen-loaded until 48h of in vitro release tests, while their incorporation into chitosan matrix achieved a maximum percentage of drug release of 45%, using a mass ratio of chitosan: poly(NVCL-co-IA-co-EGDMA equal to 10:7, and 69%, using a mass ratio of chitosan: poly(NVCL-co-IA-co-EGDMA equal to 5:2.

Keywords: hydrogel nanoparticles, poly(N-vinylcaprolactam-co-itaconic acid-co-ethylene- glycol dimethacrylate), chitosan, ketoprofen, spray-drying

Procedia PDF Downloads 256

Authors: Nadwah Onwi, Puspa Maniam, Azmawanie A. Aziz, Fairus Mukhtar, Nor Azrita Mohamed Zin, Nurul Haslina Mohd Zin, Nurul Fatehah Ismail, Mohamad Safwan Yusoff, Susilidianamanalu Abd Rahman, Siti Munirah Harris, Maryam Aizuddin

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Objective: Malaysia has a growing number of individuals with complex communication needs (CCN). The initiation of augmentative and alternative communication (AAC) intervention may facilitate individuals with CCN to understand and express themselves optimally and actively participate in activities in their daily life. AAC is defined as multimodal use of communication ability to allow individuals to use every mode possible to communicate with others using a set of symbols or systems that may include the symbols, aids, techniques, and strategies. It is consequently critical to evaluate the deficits to inform treatment for AAC intervention. However, no known measurement tools are available to evaluate the user with CCN available locally. Design: A systematic review (SR) is designed to analyze the psychometric properties of AAC assessment for adolescents with CCN published in peer-reviewed journals. Tools are rated by the methodological quality of studies and the psychometric measurement qualities of each tool. Method: A literature search identifying AAC assessment tools with psychometrically robust properties and conceptual framework was considered. Two independent reviewers screened the abstracts and full-text articles and review bibliographies for further references. Data were extracted using standardized forms and study risk of bias was assessed. Result: The review highlights the psychometric properties of AAC assessment tools that can be used by speech-language therapists applicable to be used in the Malaysian context. The work outlines how systematic review methods may be applied to the consideration of published material that provides valuable data to initiate the development of Malay Language AAC assessment tools. Conclusion: The synthesis of evidence has provided a framework for Malaysia Speech-Language therapists in making an informed decision for AAC intervention in our standard operating procedure in the Ministry of Health, Malaysia.

Keywords: augmentative and alternative communication, assessment, adolescents, complex communication needs

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Authors: Shehu Isyaku

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The general objective of the study was to investigate ‘the relationship between the external business environment and the sustainability of micro, small and medium enterprises (MSMEs) in Jigawa state’, Nigeria. Specifically, the study was to examine the relationship between 1) the economic environment, 2) the social environment, 3) the technological environment, and 4) the political environment and the sustainability of MSMEs in Jigawa state, Nigeria. The study was drawn on Resource-Based View (RBV) Theory and Knowledge-Based View (KBV). The study employed a descriptive cross-sectional survey design. A researcher-made questionnaire was used to collect data from the 350 managers/owners who were selected using stratified, purposive and simple random sampling techniques. Data analysis was done using means and standard deviations, factor analysis, Correlation Coefficient, and Pearson Linear Regression analysis. The findings of the study revealed that the sustainability potentials of the managers/owners were rated as high potential (economic, environmental, and social sustainability using 5 5-point Likert scale. Mean ratings of effectiveness of the external business environment were; as highly effective. The results from the Pearson Linear Regression Analysis rejected the hypothesized non-significant effect of the external business environment on the sustainability of MSMEs. Specifically, there is a positive significant relationship between 1) economic environment and sustainability; 2) social environment and sustainability; 3) technological environment and sustainability and political environment and sustainability. The researcher concluded that MSME managers/owners have a high potential for economic, social and environmental sustainability and that all the constructs of the external business environment (economic environment, social environment, technological environment and political environment) have a positive significant relationship with the sustainability of MSMEs. Finally, the researcher recommended that 1) MSME managers/owners need to develop marketing strategies and intelligence systems to accumulate information about the competitors and customers' demands, 2) managers/owners should utilize the customers’ cultural and religious beliefs as an opportunity that should be utilized while formulating business strategies.

Keywords: business environment, sustainability, small and medium enterprises, external business environment

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Authors: Seulki Lee, Seoung Bum Kim

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Statistical process control (SPC) is a practical and effective method for quality control. The most important and widely used technique in SPC is a control chart. The main goal of a control chart is to detect any assignable changes that affect the quality output. Most conventional control charts, such as Hotelling’s T2 charts, are commonly based on the assumption that the quality characteristics follow a multivariate normal distribution. However, in modern complicated manufacturing systems, appropriate control chart techniques that can efficiently handle the nonnormal processes are required. To overcome the shortcomings of conventional control charts for nonnormal processes, several methods have been proposed to combine statistical learning algorithms and multivariate control charts. Statistical learning-based control charts, such as support vector data description (SVDD)-based charts, k-nearest neighbors-based charts, have proven their improved performance in nonnormal situations compared to that of the T2 chart. Beside the nonnormal property, time-varying operations are also quite common in real manufacturing fields because of various factors such as product and set-point changes, seasonal variations, catalyst degradation, and sensor drifting. However, traditional control charts cannot accommodate future condition changes of the process because they are formulated based on the data information recorded in the early stage of the process. In the present paper, we propose a SVDD algorithm-based control chart, which is capable of adaptively monitoring time-varying and nonnormal processes. We reformulated the SVDD algorithm into a time-adaptive SVDD algorithm by adding a weighting factor that reflects time-varying situations. Moreover, we defined the updating region for the efficient model-updating structure of the control chart. The proposed control chart simultaneously allows efficient model updates and timely detection of out-of-control signals. The effectiveness and applicability of the proposed chart were demonstrated through experiments with the simulated data and the real data from the metal frame process in mobile device manufacturing.

Keywords: multivariate control chart, nonparametric method, support vector data description, time-varying process

Procedia PDF Downloads 295

Authors: Harika Atmaca, Emir Bozkurt, Latife Merve Oktay, Selim Uzunoglu, Ruchan Uslu, Burçak Karaca

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Microarrays have been developed for highly parallel enzyme-linked immunosorbent assay (ELISA) applications. The most common protein arrays are produced by using multiple monoclonal antibodies, since they are robust molecules which can be easily handled and immobilized by standard procedures without loss of activity. Protein expression profiling with protein array technology allows simultaneous analysis of the protein expression pattern of a large number of proteins. Trabectedin, a tetrahydroisoquinoline alkaloid derived from a Caribbean tunicate, Ecteinascidia turbinata, has been shown to have antitumor effects. Here, we used a novel proteomic approach to explore the mechanism of action of trabectedin in prostate cancer cell line PC-3 by apoptosis antibody microarray. XTT cell proliferation kit and Cell Death Detection Elisa Plus Kit (Roche) was used for measuring cytotoxicity and apoptosis. Human Apoptosis Protein Array (R&D Systems) which consists of 35 apoptosis related proteins was used to assess the omic protein expression pattern. Trabectedin induced cytotoxicity and apoptosis in prostate cancer cells in a time and concentration-dependent manner. The expression levels of the death receptor pathway molecules, TRAIL-R1/DR4, TRAIL R2/DR5, TNF R1/TNFRSF1A, FADD were significantly increased by 4.0-, 21.0-, 4.20- and 11.5-fold by trabectedin treatment in PC-3 cells. Moreover, mitochondrial pathway related pro-apoptotic proteins Bax, Bad, Cytochrome c, and Cleaved Caspase-3 expressions were induced by 2.68-, 2.07-, 2.8-, and 4.5-fold and the expression levels of anti-apoptotic proteins Bcl-2 and Bcl-XL were reduced by 3.5- and 5.2-fold in PC-3 cells. Proteomic (antibody microarray) analysis suggests that the mechanism of action of trabectedin may be exerted via the induction of both intrinsic and extrinsic apoptotic pathways. The antibody microarray platform can be utilised to explore the molecular mechanism of action of novel anticancer agents.

Keywords: trabectedin, prostate cancer, omic protein expression profile, apoptosis

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Authors: Wesley Preßler, Lucie Schmidt

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Digital transformation is playing an increasingly important role in the development of smart residential quarters. In order to accompany and steer this process and ultimately make the success of the transformation efforts measurable, it is helpful to use an appropriate maturity model. However, conventional maturity models for digital transformation focus primarily on the evaluation of processes and neglect the information and power imbalances between the stakeholders, which affects the validity of the results. The Multi-Generation Smart Community (mGeSCo) research project is developing an interdisciplinary maturity model that integrates the dimensions of digital literacy, interpretive patterns, and technology acceptance to address this gap. As part of the mGeSCo project, the technological development of selected dimensions in the Smart Quarter Jena-Lobeda (Germany) is being investigated. A specific maturity model, based on Cohen's Smart Cities Wheel, evaluates the central dimensions Working, Living, Housing and Caring. To improve the reliability and relevance of the maturity assessment, the factors Digital Literacy, Interpretive Patterns and Technology Acceptance are integrated into the developed model. The digital literacy dimension examines stakeholders' skills in using digital technologies, which influence their perception and assessment of technological maturity. Digital literacy is measured by means of surveys, interviews, and participant observation, using the European Commission's Digital Literacy Framework (DigComp) as a basis. Interpretations of digital technologies provide information about how individuals perceive technologies and ascribe meaning to them. However, these are not mere assessments, prejudices, or stereotyped perceptions but collective patterns, rules, attributions of meaning and the cultural repertoire that leads to these opinions and attitudes. Understanding these interpretations helps in assessing the overarching readiness of stakeholders to digitally transform a/their neighborhood. This involves examining people's attitudes, beliefs, and values about technology adoption, as well as their perceptions of the benefits and risks associated with digital tools. These insights provide important data for a holistic view and inform the steps needed to prepare individuals in the neighborhood for a digital transformation. Technology acceptance is another crucial factor for successful digital transformation to examine the willingness of individuals to adopt and use new technologies. Surveys or questionnaires based on Davis' Technology Acceptance Model can be used to complement interpretive patterns to measure neighborhood acceptance of digital technologies. Integrating the dimensions of digital literacy, interpretive patterns and technology acceptance enables the development of a roadmap with clear prerequisites for initiating a digital transformation process in the neighborhood. During the process, maturity is measured at different points in time and compared with changes in the aforementioned dimensions to ensure sustainable transformation. Participation, co-creation, and co-production are essential concepts for a successful and inclusive digital transformation in the neighborhood context. This interdisciplinary maturity model helps to improve the assessment and monitoring of sustainable digital transformation processes in smart residential quarters. It enables a more comprehensive recording of the factors that influence the success of such processes and supports the development of targeted measures to promote digital transformation in the neighborhood context.

Keywords: digital transformation, interdisciplinary, maturity model, neighborhood

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Authors: Erica Cochran Hameen, Bobuchi Ken-Opurum, Mounica Guturu

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The United Stated (U.S.) populous spends the majority of their time indoors in spaces where building codes and voluntary sustainability standards provide clear Indoor Environmental Quality (IEQ) metrics. The existing sustainable building standards and codes are aimed towards improving IEQ, health of occupants, and reducing the negative impacts of buildings on the environment. While they address the post-occupancy stage of buildings, there are fewer standards on the pre-occupancy stage thereby placing a large labor population in environments much less regulated. Construction personnel are often exposed to a variety of uncomfortable and unhealthy elements while on construction sites, primarily thermal, visual, acoustic, and air quality related. Construction site power generators, equipment, and machinery generate on average 9 decibels (dBA) above the U.S. OSHA regulations, creating uncomfortable noise levels. Research has shown that frequent exposure to high noise levels leads to chronic physiological issues and increases noise induced stress, yet beyond OSHA no other metric focuses directly on the impacts of noise on contractors’ well-being. Research has also associated natural light with higher productivity and attention span, and lower cases of fatigue in construction workers. However, daylight is not always available as construction workers often perform tasks in cramped spaces, dark areas, or at nighttime. In these instances, the use of artificial light is necessary, yet lighting standards for use during lengthy tasks and arduous activities is not specified. Additionally, ambient air, contaminants, and material off-gassing expelled at construction sites are one of the causes of serious health effects in construction workers. Coupled with extreme hot and cold temperatures for different climate zones, health and productivity can be seriously compromised. This research evaluates the impact of existing green building metrics on construction and risk management, by analyzing two codes and nine standards including LEED, WELL, and BREAM. These metrics were chosen based on the relevance to the U.S. construction industry. This research determined that less than 20% of the sustainability context within the standards and codes (texts) are related to the pre-occupancy building sector. The research also investigated the impact of construction personnel’s health and well-being on construction management through two surveys of project managers and on-site contractors’ perception of their work environment on productivity. To fully understand the risks of limited Environmental and Health Quality metrics for contractors (EHQ) this research evaluated the connection between EHQ factors such as inefficient lighting, on construction workers and investigated the correlation between various site coping strategies for comfort and productivity. Outcomes from this research are three-pronged. The first includes fostering a discussion about the existing conditions of EQH elements, i.e. thermal, lighting, ergonomic, acoustic, and air quality on the construction labor force. The second identifies gaps in sustainability standards and codes during the pre-occupancy stage of building construction from ground-breaking to substantial completion. The third identifies opportunities for improvements and mitigation strategies to improve EQH such as increased monitoring of effects on productivity and health of contractors and increased inclusion of the pre-occupancy stage in green building standards.

Keywords: construction contractors, health and well-being, environmental quality, risk management

Procedia PDF Downloads 130

Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

Procedia PDF Downloads 120

Authors: Humphrey Agevi, Harrison Tsingalia, Richard Onwonga, Shem Kuyah

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Most of the world ecosystems have been affected by the effects of climate change. Efforts have been made to mitigate against climate change effects. While most studies have been done in forest ecosystems and pure plant plantations, trees on farms including agroforestry have only received attention recently. Agroforestry systems and tree cover on agricultural lands make an important contribution to climate change mitigation but are not systematically accounted for in the global carbon budgets. This study sought to: (i) determine tree diversity in different agroforestry practices; (ii) determine tree biomass in different agroforestry practices. Study area was determined according to the Land degradation surveillance framework (LSDF). Two study sites were established. At each of the site, a 5km x 10km block was established on a map using Google maps and satellite images. Way points were then uploaded in a GPS helped locate the blocks on the ground. In each of the blocks, Nine (8) sentinel clusters measuring 1km x 1km were randomized. Randomization was done in a common spreadsheet program and later be downloaded to a Global Positioning System (GPS) so that during surveys the researchers were able to navigate to the sampling points. In each of the sentinel cluster, two farm boundaries were randomly identified for convenience and to avoid bias. This led to 16 farms in Kakamega South and 16 farms in Kakamega North totalling to 32 farms in Kakamega Site. Species diversity was determined using Shannon wiener index. Tree biomass was determined using allometric equation. Two agroforestry practices were found; homegarden and hedgerow. Species diversity ranged from 0.25-2.7 with a mean of 1.8 ± 0.10. Species diversity in homegarden ranged from 1-2.7 with a mean of 1.98± 0.14. Hedgerow species diversity ranged from 0.25-2.52 with a mean of 1.74± 0.11. Total Aboveground Biomass (AGB) determined was 13.96±0.37 Mgha-1. Homegarden with the highest abundance of trees had higher above ground biomass (AGB) compared to hedgerow agroforestry. This study is timely as carbon budgets in the agroforestry can be incorporated in the global carbon budgets and improve the accuracy of national reporting of greenhouse gases.

Keywords: agroforestry, allometric equations, biomass, climate change

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Authors: Mohammad Anwarul Kabir, Fayezul Islam

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Language invariably is learned / taught to be used primarily as means of communications. Teaching a language for its native audience differs from teaching it to non-native audience. Moreover, teaching a language for communication only is different from teaching it for specific purposes. Arabic language is primarily regarded as the language of the Quran and the Sunnah (Prophetic tradition). Arabic is, therefore, learnt and spread all over the globe. However, Arabic is also a cultural heritage shared by all Islamic nations which has used Arabic for a long period to record the contributions of Muslim thinkers made in the field of wide spectrum of knowledge and scholarship. That is why the phenomenon of teaching Arabic by different educational institutes became quite rife, and the idea of teaching Arabic for specific purposes is heavily discussed in the academic sphere. Although the number of learners of Arabic is increasing consistently, yet their purposes vary. These include religious purpose, international trade, diplomatic purpose, better livelihood in the Arab world extra. By virtue of this high demand for learning Arabic, numerous institutes have been established all over the world including Bangladesh. This paper aims at focusing on the current status of the language institutes which has been established for learning Arabic for specific purposes in Bangladesh including teaching methodology, curriculum, and teachers’ quality. Such curricula and using its materials resulted in a lot of problems. The least, it confused teachers and students as well. Islamic educationalists have been working hard to professionally meet the need. They are following a systematic approach of stating clear and achievable goals, building suitable content, and applying new technology to present these learning experiences and evaluate them. It also suggests a model for designing instructional systems that responds to the need of non-Arabic speaking Islamic communities and provide the knowledge needed in both linguistic and cultural aspects. It also puts forward a number of suggestions for the improvement of the teaching / learning Arabic for specific purposes in Bangladesh after a detailed investigation in the following areas: curriculum, teachers’ skills, method of teaching and assessment policy.

Keywords: communication, Quran, sunnah, educational institutes, specific purposes, curriculum, method of teaching

Procedia PDF Downloads 276

Authors: Katie Emerson, Sara Perez-Ojalvo, Jim Komorowski, Danielle Greenberg

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The purpose of this study was to evaluate arginase activity levels in response to combinations of an inositol-stabilized arginine silicate (ASI; Nitrosigine®), L-arginine, and Inositol. Arginine acts as a vasodilator that promotes increased blood flow resulting in enhanced delivery of oxygen and nutrients to the brain and other tissues. ASI alone has been shown to improve performance on cognitive tasks. Arginase, found in human serum, catalyzes the conversion of arginine to ornithine and urea, completing the last step in the urea cycle. Decreasing arginase levels maintains arginine and results in increased nitric oxide production. This study aimed to determine the most effective combination of ASI, L-arginine and inositol for minimizing arginase levels and therefore maximize ASI’s effect on cognition. Serum was taken from untreated healthy donors by separation from clotted factors. Arginase activity of serum in the presence or absence of test products was determined (QuantiChrom™, DARG-100, Bioassay Systems, Hayward CA). The remaining ultra-filtrated serum units were harvested and used as the source for the arginase enzyme. ASI alone or combined with varied levels of Inositol were tested as follows: ASI + inositol at 0.25 g, 0.5 g, 0.75 g, or 1.00 g. L-arginine was also tested as a positive control. All tests elicited changes in arginase activity demonstrating the efficacy of the method used. Adding L-arginine to serum from untreated subjects, with or without inositol only had a mild effect. Adding inositol at all levels reduced arginase activity. Adding 0.5 g to the standardized amount of ASI led to the lowest amount of arginase activity as compared to the 0.25g 0.75g or 1.00g doses of inositol or to L-arginine alone. The outcome of this study demonstrates an interaction of the pairing of inositol with ASI on the activity of the enzyme arginase. We found that neither the maximum nor minimum amount of inositol tested in this study led to maximal arginase inhibition. Since the inhibition of arginase activity is desirable for product formulations looking to maintain arginine levels, the most effective amount of inositol was deemed preferred. Subsequent studies suggest this moderate level of inositol in combination with ASI leads to cognitive improvements including reaction time, executive function, and concentration.

Keywords: arginine, inositol, arginase, cognitive benefits

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Authors: Sheraz Gul

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The requirements for progressing a compound to clinical trials is well established and relies on the results from in-vitro and in-vivo animal tests to indicate that it is likely to be safe and efficacious when testing in humans. The typical data package required will include demonstrating compound safety, toxicity, bioavailability, pharmacodynamics (potential effects of the compound on body systems) and pharmacokinetics (how the compound is potentially absorbed, distributed, metabolised and eliminated after dosing in humans). If the desired criteria are met and the compound meets the clinical Candidate criteria and is deemed worthy of further development, a submission to regulatory bodies such as the US Food & Drug Administration for an exploratory Investigational New Drug Study can be made. The purpose of this study is to collect data to establish that the compound will not expose humans to unreasonable risks when used in limited, early-stage clinical studies in patients or normal volunteer subjects (Phase I). These studies are also designed to determine the metabolism and pharmacologic actions of the drug in humans, the side effects associated with increasing doses, and, if possible, to gain early evidence on their effectiveness. In order to reach the above goals, we have developed a pre-clinical high throughput Absorption, Distribution, Metabolism and Excretion–Toxicity (ADME–Toxicity) panel of assays to identify compounds that are likely to meet the Lead and Candidate compound acceptance criteria. This panel includes solubility studies in a range of biological fluids, cell viability studies in cancer and primary cell-lines, mitochondrial toxicity, off-target effects (across the kinase, protease, histone deacetylase, phosphodiesterase and GPCR protein families), CYP450 inhibition (5 different CYP450 enzymes), CYP450 induction, cardio-toxicity (hERG) and gene-toxicity. This panel of assays has been applied to multiple compound series developed in a number of projects delivering Lead and clinical Candidates and examples from these will be presented.

Keywords: absorption, distribution, metabolism and excretion–toxicity , drug discovery, food and drug administration , pharmacodynamics

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Authors: Daniel Alfonso Reséndiz-García, Luis Antonio García-Villanueva

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As a result of the high industrial activity, which arises from the search to satisfy the needs of products and services for society, several chemical accidents have occurred, causing serious damage to different sectors: human, economic, infrastructure and environmental losses. Historically, with the study of this chemical accidents, it has been determined that the causes are mainly due to human errors (inexperienced personnel, negligence, lack of maintenance and deficient risk analysis). The industries have the aim to increase production and reduce costs. However, it should be kept in mind that the costs involved in risk studies, implementation of barriers and safety systems is much cheaper than paying for the possible damages that could occur in the event of an accident, without forgetting that there are things that cannot be replaced, such as human lives.Therefore, it is of utmost importance to implement risk studies in all industries, which provide information for prevention and planning. The aim of this study is to compare risk methodologies by identifying the consequences of accidents related to the storage of flammable, dangerous goods for decision making and emergency response.The methodologies considered in this study are qualitative and quantitative risk analysis and consequence analysis. The latter, by means of modeling software, which provides radius of affectation and the possible scope and magnitude of damages.By using risk analysis, possible scenarios of occurrence of chemical accidents in the storage of flammable substances are identified. Once the possible risk scenarios have been identified, the characteristics of the substances, their storage and atmospheric conditions are entered into the software.The results provide information that allows the implementation of prevention, detection, control, and combat elements for emergency response, thus having the necessary tools to avoid the occurrence of accidents and, if they do occur, to significantly reduce the magnitude of the damage.This study highlights the importance of risk studies applying tools that best suited to each case study. It also proves the importance of knowing the risk exposure of industrial activities for a better prevention, planning and emergency response.

Keywords: chemical accidents, emergency response, flammable substances, risk analysis, modeling

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Authors: Charles Amoatey, Ebenezer Kumah

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Purpose: The purpose of this paper is to assess the effects of implementation of Distributor Management Solution (DMS) on supply chain performance in the Fast Moving Consumer Goods (FMCG) industry in Ghana. Methodology: A purposive sampling approach was used in selecting the respondents for the study. Data was collected from senior management and field supervisors from sales, distribution and customer service units of the case study firm and its channel members. This study made use of systematic literature review and results of survey data analysis to assess how information system has been used to improve supply chain performance. Findings: Results from the study showed that the critical effect factors from implementation of a DMS include (1) Obtain prompt and reliable feedback from the market; (2) Building the capacity and skills levels of employees as well as 3rd Party Agents; (3) Motivated top management to invest in MIS; and (4) Performance improvement in sales route management. The most critical challenges to an effective and sustainable MIS implementation are lack of enough trained IT employees and high barriers to cultural change especially with distributors. The paper recommends consistent investment in IS infrastructure and development of IT skills. Research limitations/implications: This study contributes to the literature by exploring the effects of distribution management solution implementation and supply chain performance in a developing country context. Considering the fact that this study is based on data from only one case study firm and its channel members, generalization of the results should be treated with caution. Practical implications: The findings have confirmed the benefits of implementing a Management Information System. The result should encourage channel members to allocate adequate resources for building MIS capacity to enhance their supply chain performance. Originality/Value: In this paper, the relationship between DMS/MIS implementation and improvement in supply chain performance, in the Ghanaian context, has been established.

Keywords: distributor management solution, fast-moving consumer goods, supply chain management, information systems, Ghana

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Authors: Rasha Elsawy

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Aside from the rapid growth of global information technology and the Internet, another key trend is the swift proliferation of wearable technologies. The future of wearable technologies is very bright as an emerging revolution in this technological world. Beyond this, individual continuance intention toward IT is an important area that drew academics' and practitioners' attention. The literature review exhibits that continuance usage is an important concern that needs to be addressed for any technology to be advantageous and for consumers to succeed. However, consumers noticeably abandon their wearable devices soon after purchase, losing all subsequent benefits that can only be achieved through continued usage. Purpose-This thesis aims to develop an integrated model designed to explain and predict consumers' behavioural intention(BI) and continued use (CU) of wearable fitness technology (WFT) to identify the determinants of the CU of technology. Because of this, the question arises as to whether there are differences between technology adoption and post-adoption (CU) factors. Design/methodology/approach- The study employs the unified theory of acceptance and use of technology2 (UTAUT2), which has the best explanatory power, as an underpinning framework—extending it with further factors, along with user-specific personal characteristics as moderators. All items will be adapted from previous literature and slightly modified according to the WFT/SW context. A longitudinal investigation will be carried out to examine the research model, wherein a survey will include these constructs involved in the conceptual model. A quantitative approach based on a questionnaire survey will collect data from existing wearable technology users. Data will be analysed using the structural equation modelling (SEM) method based on IBM SPSS statistics and AMOS 28.0. Findings- The research findings will provide unique perspectives on user behaviour, intention, and actual continuance usage when accepting WFT. Originality/value- Unlike previous works, the current thesis comprehensively explores factors that affect consumers' decisions to continue using wearable technology. That is influenced by technological/utilitarian, affective, emotional, psychological, and social factors, along with the role of proposed moderators. That novel research framework is proposed by extending the UTAUT2 model with additional contextual variables classified into Performance Expectancy, Effort Expectancy, Social Influence (societal pressure regarding body image), Facilitating Conditions, Hedonic Motivation (to be split up into two concepts: perceived enjoyment and perceived device annoyance), Price value, and Habit-forming techniques; adding technology upgradability as determinants of consumers' behavioural intention and continuance usage of Information Technology (IT). Further, using personality traits theory and proposing relevant user-specific personal characteristics (openness to technological innovativeness, conscientiousness in health, extraversion, neuroticism, and agreeableness) to moderate the research model. Thus, the present thesis obtains a more convincing explanation expected to provide theoretical foundations for future emerging IT (such as wearable fitness devices) research from a behavioural perspective.

Keywords: wearable technology, wearable fitness devices/smartwatches, continuance use, behavioural intention, upgradability, longitudinal study

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Authors: N. G. I. Aroshana, S. Edirisooriya

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Construction of highway is the most emerging development tendency in Sri Lanka. With these development activities, there are a lot of environmental and social issues started. Landscape fragmentation is one of the main issues that highly effect to the environment by the construction of expressways. Sri Lankan expressway system getting effort to treat fragmented landscape by using highway crossing structures. This paper designates, a highway post construction landscape study on the effectiveness of the landscape connectivity structures to restore connectivity. Geographic Information Systems (GIS), least cost path tool has been used in the selected two plots; 25km alone the expressway to identify animal crossing paths. Animal accident data use as measure for determining the most contributed plot for landscape connectivity. Number of patches, Mean patch size, Class area use as a parameter to determine the most effective land use class to reestablish the landscape connectivity. The findings of the research express scrub, grass and marsh were the most positively affected land use typologies for increase the landscape connectivity. It represents the growth increased by 8% within the 12 years of time. From the least cost analysis within the plot one, 28.5% of total animal crossing structures are within the high resistance land use classes. Southern expressway used reinforced compressed earth technologies for construction. It has been controlled the growth of the climax community. According to all findings, it could assume that involvement of the landscape crossing structures contributes to re-establish connectivity, but it is not enough to restore the majority of disturbance performed by the expressway. Connectivity measures used within the study can use as a tool for re-evaluate future involvement of highway crossing structures. Proper placement of the highway crossing structures leads to increase the rate of connectivity. The study recommends that monitoring the all stages (preconstruction, construction and post construction) of the project and preliminary design, and the involvement of the research applied connectivity assessment strategies helps to overcome the complication regarding the re-establishment of landscape connectivity using the highway crossing structures that facilitate the growth of flora and fauna.

Keywords: landscape fragmentation, least cost path, land use analysis, landscape connectivity structures

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Authors: Alon Cohen, Jeffrey Kantor, Shalom Levy

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The use of the audit risk model in auditing has faced limitations and difficulties, leading auditors to rely on a conceptual level of its application. The qualitative approach to assessing risks has resulted in different risk assessments, affecting the quality of audits and decision-making on the adoption of CAATTs. This study aims to investigate risk factors impacting the implementation of the audit risk model and propose a complementary risk-based instrument (KRIs) to form substance risk judgments and mitigate against heightened risk of material misstatement (RMM). The study addresses the question of how risk factors impact the implementation of the audit risk model, improve risk judgments, and aid in the adoption of CAATTs. The study uses a three-stage scale development procedure involving a pretest and subsequent study with two independent samples. The pretest involves an exploratory factor analysis, while the subsequent study employs confirmatory factor analysis for construct validation. Additionally, the authors test the ability of the KRIs to predict audit efforts needed to mitigate against heightened RMM. Data was collected through two independent samples involving 767 participants. The collected data was analyzed using exploratory factor analysis and confirmatory factor analysis to assess scale validity and construct validation. The suggested KRIs, comprising two risk components and seventeen risk items, are found to have high predictive power in determining audit efforts needed to reduce RMM. The study validates the suggested KRIs as an effective instrument for risk assessment and decision-making on the adoption of CAATTs. This study contributes to the existing literature by implementing a holistic approach to risk assessment and providing a quantitative expression of assessed risks. It bridges the gap between intuitive risk evaluation and the theoretical domain, clarifying the mechanism of risk assessments. It also helps improve the uniformity and quality of risk assessments, aiding audit standard-setters in issuing updated guidelines on CAATT adoption. A few limitations and recommendations for future research should be mentioned. First, the process of developing the scale was conducted in the Israeli auditing market, which follows the International Standards on Auditing (ISAs). Although ISAs are adopted in European countries, for greater generalization, future studies could focus on other countries that adopt additional or local auditing standards. Second, this study revealed risk factors that have a material impact on the assessed risk. However, there could be additional risk factors that influence the assessment of the RMM. Therefore, future research could investigate other risk segments, such as operational and financial risks, to bring a broader generalizability to our results. Third, although the sample size in this study fits acceptable scale development procedures and enables drawing conclusions from the body of research, future research may develop standardized measures based on larger samples to reduce the generation of equivocal results and suggest an extended risk model.

Keywords: audit risk model, audit efforts, CAATTs adoption, key risk indicators, sustainability

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Authors: Irena Maus, Katharina Gabriella Cibis, Andreas Bremges, Yvonne Stolze, Geizecler Tomazetto, Daniel Wibberg, Helmut König, Alfred Pühler, Andreas Schlüter

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Within the agricultural sector, the production of biogas from organic substrates represents an economically attractive technology to generate bioenergy. Complex consortia of microorganisms are responsible for biomass decomposition and biogas production. Recently, species belonging to the phylum Thermotogae were detected in thermophilic biogas-production plants utilizing renewable primary products for biomethanation. To analyze adaptive genome features of representative Thermotogae strains, Defluviitoga tunisiensis L3 was isolated from a rural thermophilic biogas plant (54°C) and completely sequenced on an Illumina MiSeq system. Sequencing and assembly of the D. tunisiensis L3 genome yielded a circular chromosome with a size of 2,053,097 bp and a mean GC content of 31.38%. Functional annotation of the complete genome sequence revealed that the thermophilic strain L3 encodes several genes predicted to facilitate growth of this microorganism on arabinose, galactose, maltose, mannose, fructose, raffinose, ribose, cellobiose, lactose, xylose, xylan, lactate and mannitol. Acetate, hydrogen (H2) and carbon dioxide (CO2) are supposed to be end products of the fermentation process. The latter gene products are metabolites for methanogenic archaea, the key players in the final step of the anaerobic digestion process. To determine the degree of relatedness of dominant biogas community members within selected digester systems to D. tunisiensis L3, metagenome sequences from corresponding communities were mapped on the L3 genome. These fragment recruitments revealed that metagenome reads originating from a thermophilic biogas plant covered 95% of D. tunisiensis L3 genome sequence. In conclusion, availability of the D. tunisiensis L3 genome sequence and insights into its metabolic capabilities provide the basis for biotechnological exploitation of genome features involved in thermophilic fermentation processes utilizing renewable primary products.

Keywords: genome sequence, thermophilic biogas plant, Thermotogae, Defluviitoga tunisiensis

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Authors: Raquel Galante, Marina Braga, Daniela Ghisleni, Terezinha J. A. Pinto, Rogério Colaço, Ana Paula Serro

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The sensitive nature of soft biomaterials, such as hydrogels, renders their sterilization a particularly challenging task for the biomedical industry. Widely used contact lenses are now studied as promising platforms for topical corneal drug delivery. However, to the best of the authors knowledge, the influence of sterilization methods on these systems has yet to be evaluated. The main goal of this study was to understand how different pairs drug-hydrogel would interact under an ozone-based sterilization method in comparison with two conventional processes (steam heat and gamma irradiation). For that, Si-Hy containing hydroxylethyl methacrylate (HEMA) and [tris(trimethylsiloxy)silyl]propyl methacrylate (TRIS) was produced and soaked in different drug solutions, commonly used for the treatment of ocular diseases (levofloxacin, chlorhexidine, diclofenac and timolol maleate). The drug release profiles and main material properties were evaluated before and after the sterilization. Namely, swelling capacity was determined by water uptake studies, transparency was accessed by UV-Vis spectroscopy, surface topography/morphology by scanning electron microscopy (SEM) and mechanical properties by performing tensile tests. The drug released was quantified by high performance liquid chromatography (HPLC). The effectiveness of the sterilization procedures was assured by performing sterility tests. Ozone gas method led to a significant reduction of drug released and to the formation of degradation products specially for diclofenac and levofloxacin. Gamma irradiation led to darkening of the loaded Si-Hys and to the complete degradation of levofloxacin. Steam heat led to smoother surfaces and to a decrease of the amount of drug released, however, with no formation of degradation products. This difference in the total drug released could be the related to drug/polymer interactions promoted by the sterilization conditions in presence of the drug. Our findings offer important insights that, in turn, could be a useful contribution to the safe development of actual products.

Keywords: drug delivery, silicone hydrogels, sterilization, gamma irradiation, steam heat, ozone gas

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Authors: B. Voucko, M. Benkovic, N. Cukelj, S. Drakula, D. Novotni, S. Balbino, D. Curic

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Oxidative stress is considered as one of the causes leading to metabolic disorders in humans. Therefore, the ability of antioxidants to inhibit free radical production is their primary role in the human organism. Antioxidants originating from cereals, especially flavonoids and polyphenols, are mostly bound and indigestible. Micronization damages the cell wall which consecutively results in bioactive material to be more accessible in vivo. In order to ensure complete fragmentation, micronization is often combined with high temperatures (e.g., for bran 200°C) which can lead to degradation of bioactive compounds. The innovative non-thermal technology of cryo-milling is an ultra-fine micronization method that uses liquid nitrogen (LN2) at a temperature of 195°C to freeze and cool the sample during milling. Freezing at such low temperatures causes the material to become brittle which ensures the generation of fine particles while preserving the bioactive content of the material. The aim of this research was to determine if production of ultra-fine material with cryo-milling will result in the augmentation of available bioactive compounds of buckwheat and pumpkin seed cake. For that reason, buckwheat and pumpkin seed cake were ground in a ball mill (CryoMill, Retch, Germany) with and without the use of LN2 for 8 minutes, in a 50 mL stainless steel jar containing one grinding ball (Ø 25 mm) at an oscillation frequency of 30 Hz. The cryo-milled samples were cooled with LN2 for 2 minutes prior to milling, followed by the first cycle of milling (4 minutes), intermediary cooling (2 minutes), and finally the second cycle of milling (further 4 minutes). A continuous process of milling was applied to the samples ground without freezing with LN2. Particle size distribution was determined using the Scirocco 2000 dry dispersion unit (Malvern Instruments, UK). Antioxidant activity was determined by 2,2-Diphenyl-1-picrylhydrazyl (DPPH) test and ferric reducing antioxidant power (FRAP) assay, while the total phenol content was determined using the Folin Ciocalteu method, using the ultraviolet-visible spectrophotometer (Specord 50 Plus, Germany). The content of the free phenolic acids, rutin in buckwheat, tyrosol in pumpkin seed cake, was determined with an HPLC-PDA method (Agilent 1200 series, Germany). Cryo-milling resulted in 11 times smaller size of buckwheat particles, and 3 times smaller size of pumpkin seed particles than milling without the use of LN2, but also, a lower uniformity of the particle size distribution. Lack of freezing during milling of pumpkin seed cake caused a formation of agglomerates due to its high-fat content (21 %). Cryo-milling caused augmentation of buckwheat flour antioxidant activity measured by DPPH test (23,9%) and an increase in available rutin content (14,5%). Also, it resulted in an augmentation of the total phenol content (36,9%) and available tyrosol content (12,5%) of pumpkin seed cake. Antioxidant activity measured with the FRAP test, as well as the content of phenolic acids remained unchanged independent of the milling process. The results of this study showed the potential of cryo-milling for complete raw material utilization in the food industry, as well as a tool for extraction of aimed bioactive components.

Keywords: bioactive, ball-mill, buckwheat, cryo-milling, pumpkin seed cake

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Authors: D. Velayadum, P. Sthandiwe , N. Maharaj, T. Munien, S. Ndamase, G. Zulu, S. Xulu, F. Oosthuizen

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Introduction and aims of the study: It is the responsibility of the pharmacist to manage drug-related problems in order to ensure the greatest benefit to the patient. In order to prevent drug-related morbidity, pharmacists should be aware of medicines that may contribute to certain drug-related problems due to their pharmacological action. In an attempt to assist healthcare practitioners to prevent drug-related morbidity (PDRM), indicators for prevention have been designed. There are currently no indicators available for primary health care in developing countries like South Africa, where the majority of the population access primary health care. There is, therefore, a need to develop such indicators, specifically with the aim of assisting healthcare practitioners in primary health care. Methods: A literature study was conducted to compile a comprehensive list of PDRM indicators as developed internationally using the search engines Google Scholar and PubMed. MESH term used to retrieve suitable articles was 'preventable drug-related morbidity indicators'. The comprehensive list of PDRM indicators obtained from the literature study was further evaluated for face validity. Face validity was done in duplicate by 2 sets of independent researchers to ensure 1) no duplication of indicators when compiling a single list, 2) inclusion of only medication available in primary healthcare, and 3) inclusion of medication currently available in South Africa. Results: The list of indicators, compiled from PDRM indicators in the USA, UK, Portugal, Australia, India, and Canada contained 324 PDRM. 184 of these indicators were found to be duplicates, and the duplications were omitted, leaving a final list of 140. The 140 PDRM indicators were evaluated for face-validity, and 97 were accepted as relevant to primary health care in South Africa. 43 indicators did not comply with the criteria and were omitted from the final list. Conclusion: This study is a first step in compiling a list of PDRM indicators for South Africa. It is important to take cognizance to the fact the health systems differ vastly internationally, and it is, therefore, important to develop country-specific indicators.

Keywords: drug-related morbidity, primary healthcare, South Africa, developing countries

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Authors: Siddharth Ahuja, T. M. Muruganandam

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An analytical investigation is performed to study the unsteady response of a one-dimensional, non-linear dynamic shock system to external downstream pressure perturbations in a supersonic flow in a varying area duct. For a given pressure ratio across a wind tunnel, the normal shock's location can be computed as per one-dimensional steady gas dynamics. Similarly, for some other pressure ratio, the location of the normal shock will change accordingly, again computed using one-dimensional gas dynamics. This investigation focuses on the small-time interval between the first steady shock location and the new steady shock location (corresponding to different pressure ratios). In essence, this study aims to shed light on the motion of the shock from one steady location to another steady location. Further, this study aims to create the foundation of the Unsteady Gas Dynamics field enabling further insight in future research work. According to the new pressure ratio, a pressure pulse, generated at the exit of the tunnel which travels and perturbs the shock from its original position, setting it into motion. During such activity, other numerous physical phenomena also happen at the same time. However, three broad phenomena have been focused on, in this study - Traversal of a Wave, Fluid Element Interactions and Wave Interactions. The above mentioned three phenomena create, alter and kill numerous waves for different conditions. The waves which are created by the above-mentioned phenomena eventually interact with the shock and set it into motion. Numerous such interactions with the shock will slowly make it settle into its final position owing to the new pressure ratio across the duct, as estimated by one-dimensional gas dynamics. This analysis will be extremely helpful in the prediction of inlet 'unstart' of the flow in a supersonic engine intake and its prominence with the incoming flow Mach number, incoming flow pressure and the external perturbation pressure is also studied to help design more efficient supersonic intakes for engines like ramjets and scramjets.

Keywords: analytical investigation, compression and expansion waves, fluid element interactions, shock trajectory, supersonic flow, unsteady gas dynamics, varying area duct, wave interactions

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Authors: Aadila Cayenne, Hinrich Uellendahl

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Optimization of the anaerobic digestion (AD) process of halophytic plants is essential as the biomass contains a high salt content that can inhibit the AD process. Anaerobic co-digestion, together with manure, can resolve the inhibitory effects of saline biomass in order to dilute the salt concentration and establish favorable conditions for the microbial consortia of the AD process. The present laboratory study investigated the co-digestion of S. ramosissima (Sram), and pig manure (PM) in batch and semi-continuous stirred tank reactors (CSTR) under mesophilic (38oC) conditions. The 0.5L batch reactor experiments were in mono- and co-digestion of Sram: PM using different percent volatile solid (VS) based ratios (0:100, 15:85, 25:75, 35:65, 50:50, 100:0) with an inoculum to substate (I/R) ratio of 2. Two 5L CSTR systems (R1 and R2) were operated for 133 days with a feed of PM in a control reactor (R1) and with a co-digestion feed in an increasing Sram VS ratio of Sram: PM of 15:85, 25:75, 35:65 in reactor R2 at an organic loading rate (OLR) of 2 gVS/L/d and hydraulic retention time (HRT) of 20 days. After a start-up phase of 8 weeks for both reactors R1 and R2 with PM feed alone, the halophyte biomass Sram was added to the feed of R2 in an increasing ratio of 15 – 35 %VS Sram over an 11-week period. The process performance was monitored by pH, total solid (TS), VS, total nitrogen (TN), ammonium-nitrogen (NH4 – N), volatile fatty acids (VFA), and biomethane production. In the batch experiments, biomethane yields of 423, 418, 392, 365, 315, and 214 mL-CH4/gVS were achieved for mixtures of 0:100, 15:85, 25:75, 35:65, 50:50, 100:0 %VS Sram: PM, respectively. In the semi-continuous reactor processes, the average biomethane yields were 235, 387, and 365 mL-CH4/gVS for the phase of a co-digestion feed ratio in R2 of 15:85, 25:75, and 35:65 %VS Sram: PM, respectively. The methane yield of PM alone in R1 was in the corresponding phases on average 260, 388, and 446 mL-CH4/gVS. Accordingly, in the continuous AD process, the methane yield of the halophyte Sram was highest at 386 mL-CH4/gVS in the co-digestion ratio of 25:75%VS Sram: PM and significantly lower at 15:85 %VS Sram: PM (100 mL-CH4/gVS) and at 35:65 %VS Sram (214 mL-CH4/gVS). The co-digestion process showed no signs of inhibition at 2 – 4 g/L NH4 – N, 3.5 – 4.5 g/L TN, and total VFA of 0.45 – 2.6 g/L (based on Acetic, Propionic, Butyric and Valeric acid). This study demonstrates that a stable co-digestion process of S. ramosissima and pig manure can be achieved with a feed of 25%VS Sram at HRT of 20 d and OLR of 2 gVS/L/d.

Keywords: anaerobic co-digestion, biomethane production, halophytes, pig manure, salicornia ramosissima

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Authors: Glenda Wrenn, Juliet Muzere, Meldra Hall, Allyson Belton, Kisha Holden, Chanita Hughes-Halbert, Martha Kent, Bekh Bradley

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Understanding the help seeking decision making process and experiences of health disparity populations with posttraumatic stress disorder (PTSD) is central to development of trauma-informed, culturally centered, and patient focused services. Yet, little is known about the decision making process among adult Black women who are non-treatment seekers as they are, by definition, not engaged in services. Methods: Audiotaped interviews were conducted with 30 African American adult women with clinically significant PTSD symptoms who were engaged in primary care, but not in treatment for PTSD despite symptom burden. A qualitative interview guide was used to elucidate key themes. Independent coding of themes mapped to theory and identification of emergent themes were conducted using qualitative methods. An existing quantitative dataset was analyzed to contextualize responses and provide a descriptive summary of the sample. Results: Emergent themes revealed that active mental avoidance, the intermittent nature of distress, ambivalence, and self-identified resilience as undermining to help seeking decisions. Participants were stuck within the help-seeking phase of ‘recognition’ of illness and retained a sense of “it is my decision” despite endorsing significant social and environmental negative influencers. Participants distinguished ‘help acceptance’ from ‘help seeking’ with greater willingness to accept help and importance placed on being of help to others. Conclusions: Elucidation of the decision-making process from the perspective of non-treatment seekers has implications for outreach and treatment within models of integrated and specialty systems care. The salience of responses to trauma symptoms and stagnation in the help seeking recognition phase are findings relevant to integrated care service design and community engagement.

Keywords: culture, help-seeking, integrated care, PTSD

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Authors: Kousay Abid

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The aim of this paper is to better understand talent and talent management (TM) in small French companies as well as in medium-sized ones (SME). While previous empirical investigations have largely focused on multinationals and big companies and concentrated on the Anglo-Saxon context, we focus on the pressing need for implementing TM strategies and practices, not only on a new ground of SME but also within a new European context related to France and the French context. This study also aims at understanding strategies adopted by those firms as means to attract, retain, maintain and to develop talents. We contribute to TM issues by adopting a multilevel approach, holding the goal of reaching a global holistic vision of interactions between various levels while applying TM, to make it more and more familiar to us. A qualitative research methodology based on a multiple-case study design, bottomed firstly on a qualitative survey and secondly on two in-depth case study, both built on interviews, will be used in order to develop an ideal analysis for TM strategies and practices. The findings will be based on data collected from more than 15 French SMEs. Our theoretical contributions are the fruit of context considerations and the dynamic of multilevel approach. Theoretically, we attempt first to clarify how talents and TM are seen and defined in French SMEs and consequently to enrich the literature on TM in SMEs out of the Anglo-Saxon context. Moreover, we seek to understand how SMEs manage jointly their talents and their TM strategies by setting up this contextualized pilot study. As well, we focus on the systematic TM model issue from French SMEs. Our prior managerial goal is to shed light on the need for TM to achieve a better management of these organizations by directing leaders to better identify the talented people whom they hold at all levels. In addition, our TM systematic model strengthens our analysis grid as recommendations for CEO and Human Resource Development (HRD) to make them rethink about the companies’ HR business strategies. Therefore, our outputs present a multiple lever of action that should be taken into consideration while reviewing HR strategies and systems, as well as their impact beyond organizational boundaries.

Keywords: french context, multilevel approach, small and medium-sized enterprises, talent management

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Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Nastaran Cheshmehkaboodi, Lotfi Guizani, Noureddine Ghlamallah

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Seismic isolation proves to be a powerful technology in reducing seismic hazards and enhancing overall structural resilience. However, the performance of the technology can be influenced by various factors, including seismic inputs and soil conditions. This research aims to investigate the effects of moderate and strong earthquakes associated with different distances of the source on the seismic responses of conventional and isolated bridges, considering the soil-structure interaction effects. Two groups of moderate and strong near-fault records are applied to the conventional and isolated bridges, with and without considering the underlying soil. For this purpose, using the direct method, three soil properties representing rock, dense, and stiff soils are modeled in Abaqus software. Nonlinear time history analysis is carried out, and structural responses in terms of maximum deck acceleration, deck displacement, and isolation system displacement are studied. The comparison of dynamic responses between both earthquake groups demonstrates a consistent pattern, indicating that the bridge performance and the effects of soil-structure interaction are primarily influenced by the ground motions and their frequency contents. Low ratios of PGA/PGV are found to significantly impact all dynamic responses, resulting in higher force and displacement responses, regardless of the distance associated with the ruptured fault. In addition, displacement responses increase drastically on softer soils. Thus, meticulous consideration is crucial in designing isolation systems to avoid underestimating displacement demands and to ensure sufficient displacement capacity. Despite a lower PGA value in high seismicity areas in this study, the acceleration demand during strong earthquakes is up to 1.3 times higher in conventional bridges and up to 3 times higher in isolated bridges than in moderate earthquakes. Additionally, the displacement demand in strong earthquakes is up to 2 times higher in conventional bridges and up to 5 times higher in isolated bridges compared to moderate earthquakes, highlighting the increased force and displacement demand in strong earthquakes.

Keywords: bridges, seismic isolation, near-fault, earthquake characteristics, soil-structure interaction

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Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

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Authors: Kunkanit Sutamchai, Kate E. Rowlands

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Recent public ethical scandals in many organizations around the world have raised concern about organizational ethics, which have, in turn, made ethical behaviors and conducts on the part of leaders become more critical topics in organizational studies. However, current research on the benefits of mindfulness within the workplace contexts has predominantly focused on stress reduction and work performance enhancement, while the aspects of ethical behavior development have been far less investigated in mindfulness research in the organizational and management fields. Only recently has there been an emerging call for organizational researchers and practitioners to study mindfulness concepts and practices from the original Buddhist perspectives given that ethics is regarded as a foundation for Buddhist mindfulness. Yet little, if any, empirical research on the contributions of mindfulness practices to ethical leadership has been done in Eastern Buddhist contexts. Therefore, this study aims to explore the extent to which and how Buddhist-based mindfulness practices can influence organizational leaders’ ethical values and practices. On this basis, Thailand was selected as a context of study due to a predominantly Buddhist society and culture. Qualitative data were gathered through in-depth semi-structured interviews with twenty executive leaders from various private organizations in Thailand, who practice Buddhist-based mindfulness meditation regularly. The findings from this study shed light on the role Buddhist-based mindfulness practices can play in promoting ethical behavior among executive leaders in Thailand. The results also suggest that ethical values and practices influenced by Buddhist-based mindfulness practices are well aligned with the elements appeared in the inter-disciplinary and cross-cultural ethical leadership framework, namely: humane, justice, sustainability and responsibility, and moderation. This study concludes that the integration of ethical dimensions to mindfulness practices may provide promising opportunities for ethical leadership development, particularly in the context of Thailand. This could contribute significantly to the future development of both organizations and society at large. The study also suggests that mindfulness interventions in organizational contexts should place more explicit emphasis on ethics. This may be done by relating the ethical principles underlying Buddhist-based mindfulness to other ethical systems in different contexts and cultures where they can be aligned.

Keywords: Buddhism, ethical leadership, leadership development, mindfulness, Thailand, training

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