Search results for: fruit recognition

Authors: D. R. Apoorva

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Ichthyosis follicularis, alopecia, and photophobia (IFAP) syndrome is a rare oculocutaneous disorder of genetic origin. This disorder results from mutations in the membrane-bound transcription factor protease site, two genes that impair cholesterol homeostasis, and the ability to cope with endoplasmic reticulum stress. We report a rare case of IFAP syndrome with an atypical presentation, and it was interesting to note that the child had patchy non-scarring alopecia over the scalp along with unilateral madarosis. To our best knowledge, this unique presentation has not been described earlier. The child presented with photophobia and unilateral ptosis. The child also had short stature and intellectual disability. Skin histopathology was nonspecific and consisted of dilated hair follicles with keratin plugs extending above the skin surface. This rare oculocutaneous disorder requires proper documentation so that identification of its variants may be possible in the future. Early recognition of atypical presentations can help in preventing cardiovascular complications, which remain the major cause of death.

Keywords: alopecia, photophobia, ichthyosis follicularis, IFAP syndrome

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Authors: Emad A. Shalaby

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Cancer is a disease that causes abnormal cell proliferation and invades nearby tissues. Lung cancer is the second most frequent cancer worldwide. Natural anti-cancer drugs have been developed with low side effects and toxicity. Citrus peels and extracts have been demonstrated to have significant pharmacological and physiological effects as a result of the high concentration of phenolic compounds found in citrus fruits, particularly peels. Tangerine peels can serve as an effective source of bioactive substances such as phenolics, flavonoids, and catechins, which have antioxidant, antibacterial, anticancer, and anti-inflammatory properties. Consequently, this work aims to determine the anticancer activity of ethanol extract of Tangerine peels against the A549 cell line and identify the phenolic compound profile (19 compounds) by using HPLC. Anticancer and antioxidant potentials of the extract were evaluated by MTT assay and TLC- TLC-bioautography sprayed with DPPH reagent, respectively. The obtained results revealed that tangerine peel extract showed significant activity against the A549 cell line with IC50 of 97.66 μg/mL. HPLC analysis proved that the highest concentration is naringenin 464.05 mg/g. More studies indicate that naringenin has significant anticancer potential on A549 cancer cells. The results showed that naringenin binds t0 EGFR protein in A549 with high binding affinity and thus may reduce lung cancer cell migration and enhance the apoptosis of cancer cells. From the obtained results it could be concluded that tangerine peel extract is an effective anti-cancer agent that may potentially serve as a natural therapeutic option for lung cancer treatment.

Keywords: tangerine peel, A549 cell line, anticancer, naringenin, HPLC analysis, naringenin, TLC bioautography

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Authors: Marisa Almeida AraúJo

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Artificial intelligence (AI) tools are being used (including in the criminal justice system) and becomingincreasingly popular. The many questions that these (future) super-beings pose the neuralgic center is rooted in the (old) problematic between rationality and morality. For instance, if we follow a Kantian perspective in which morality derives from AI, rationality will also surpass man in ethical and moral standards, questioning the nature of mind, the conscience of self and others, and moral. The recognition of superior intelligence in a non-human being puts us in the contingency of having to recognize a pair in a form of new coexistence and social relationship. Just think of the humanoid robot Sophia, capable of reasoning and conversation (and who has been recognized for Saudi citizenship; a fact that symbolically demonstrates our empathy with the being). Machines having a more intelligent mind, and even, eventually, with higher ethical standards to which, in the alluded categorical imperative, we would have to subject ourselves under penalty of contradiction with the universal Kantian law. Recognizing the complex ethical and legal issues and the significant impact on human rights and democratic functioning itself is the goal of our work.

Keywords: ethics, artificial intelligence, legal rules, principles, philosophy

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Authors: Sebaa H., Cherifi F., Djabeur Abderrezak M.

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Argania spinosa, Sapotaceae sole representative in Algeria and Morocco; hence it is endemic in these regions. However, it is a recognised oil, forage, and timber tree highly adapted to aridity. The exploitation of the argan fruits produces considerable amounts of under or related products. These products, such as the endocarps of a fruit, recuperated after the use of kernels to extract oil. This research studies in detail the contents of total phenolic content was determined by Folin Ciocalteu reagent and Flavonoids by aluminum chloride colorimetric assay). Antioxidant activity of extracts was expressed as the percentage of DPPH radical inhibition and IC50 values (μg/mL). Antimicrobial activity evaluated using agar disk diffusion method against reference Pseudomonas aeruginosa ATTC 27453, Escherichia coli ATCC 23922. Immature endocarps showed a higher polyphenol content than mature endocarps. The total phenolic content in immature endocarps was found to vary from 983,75+ /- 0.45 to 980,1 +/- 0.43 mg gallic acid equivalents/g dry weight, whereas in mature endocarps, the polyphenol content ranged from 100,58 mg/g +/- 0.42 to 105 +/- 0.55% mg gallic acid equivalent / g dry weight. The flavonoid content was 16.5 mg equivalent catechin/g dry weight and 9.81mg equivalent catechin /g dry weight for immature and mature endocarp fruits, respectively. DPPH assay of the endocarps extract yielded a half-maximal effective concentration (IC50) value in the immature endocarps (549.33 μg/mL) than in mature endocarps (322 μg/mL). This result can be attributed to the higher phenolics and flavonoid compounds in the immature endocarps. Methanol extract of immature endocarps exhibited antibacterial activity against E.colie (inhibition zone, 11mm).

Keywords: antioxidant activity, antimicrobial activity, total phenolic content, DPPH assay

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Authors: Tiantian Gu, Dezhi Li, Mian Zhang, Ying Jiang

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Considering the characteristics of residents’ participation in the governance of old community renewal (OCR), a theoretical model of the determinant of residents’ intention to participate in the governance of OCR has been built based on the theory of planned behavior. Seven old communities in Nanjing have been chosen as cases to conduct empirical analysis. The result indicates that participation attitude, subjective norm and perceived behavioral control have significant positive effects on residents’ intention to participate in the governance of the OCR. Recognition of the community, cognition of the OCR and perceived behavioral control have indirect positive effects on residents’ intention to participate in the OCR. In addition, the education level and the length of residence have positive effects on their participation intention, while the gender, age, and monthly income have little effect on it. The research result provides suggestions for the improvement of residents’ participation in the OCR.

Keywords: old community renewal, residents’ participation in governance, intention, theory of planned behavior

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Authors: Alena Kulikova, Leonid Parmaksiz, Ekaterina Orel

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Social and emotional skills are considered by modern researchers as predictors of a person's success both in specific areas of activity and in the life of a person as a whole. The popularity of this scientific direction ensures the emergence of a large number of practices aimed at developing and evaluating socio-emotional skills. Assessment of social and emotional development is carried out at the national level, as well as at the level of individual regions and institutions. Despite the fact that many of the already existing social and emotional skills assessment tools are quite convenient and reliable, there are now more and more new technologies and task formats which improve the basic characteristics of the tools. Thus, the goal of the current study is to develop a tool for assessing social and emotional skills such as emotion recognition, emotion regulation, empathy and a culture of self-care. To develop a tool assessing social and emotional skills, Rasch-Gutman scenario-based approach was used. This approach has shown its reliability and merit for measuring various complex constructs: parental involvement; teacher practices that support cultural diversity and equity; willingness to participate in the life of the community after psychiatric rehabilitation; educational motivation and others. To assess emotion recognition, we used a situational judgment task based on OCC (Ortony, Clore, and Collins) emotions theory. The main advantage of these two approaches compare to classical Likert scales is that it reduces social desirability in answers. A field test to check the psychometric properties of the developed instrument was conducted. The instrument was developed for the presidential autonomous non-profit organization “Russia - Land of Opportunity” for nationwide soft skills assessment among higher education students. The sample for the field test consisted of 500 people, students aged from 18 to 25 (mean = 20; standard deviation 1.8), 71% female. 67% of students are only studying and are not currently working and 500 employed adults aged from 26 to 65 (mean = 42.5; SD 9), 57% female. Analysis of the psychometric characteristics of the scales was carried out using the methods of IRT (Item Response Theory). A one-parameter rating scale model RSM (Rating scale model) and Graded Response model (GRM) of the modern testing theory were applied. GRM is a polyatomic extension of the dichotomous two-parameter model of modern testing theory (2PL) based on the cumulative logit function for modeling the probability of a correct answer. The validity of the developed scales was assessed using correlation analysis and MTMM (multitrait-multimethod matrix). The developed instrument showed good psychometric quality and can be used by HR specialists or educational management. The detailed results of a psychometric study of the quality of the instrument, including the functioning of the tasks of each scale, will be presented. Also, the results of the validity study by MTMM analysis will be discussed.

Keywords: social and emotional skills, psychometrics, MTMM, IRT

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Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

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The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

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Authors: Luciane Lauffer

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Over the past decade, the expansion of women’s football as a competitive sport has gained more attention from the media and researchers. However, the practice of the sport is not new, and in Asia and Oceania, women’s football has emerged as a common physical activity in many countries since the 1970s. This study recovers the major occurrences that made women’s football possible in an international context, also resulting from the main achievements of the feminist movement in most Westernized countries. Using archival research, the author reviews documents that compose the history of the women’s game, marked by many imposed barriers imposed by social and gender norms. This materials present how women managed their sport in their respective countries and regions, mostly prompted by a spirit of cooperation and partnerships that allowed the staging of major international events. The findings point out that, despite the layers of gendered boundaries that attempted to contain the expansion of the sport, women from Asia and Oceania made the sport flourish and eventually achieving recognition at the international level.

Keywords: women’s football, gender norms, game development, Asia-pacific

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Authors: Norah Mohammed Alshahrani, Abdulaziz Almaleh

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Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD and they are Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then Feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by the Support Vector Machine (SVM), achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: autism spectrum disorder, machine learning, feature selection, support vector machine

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Authors: Magdalena Chrabąszcz, Teresa Wolniewicz, Cezary Maciejewski, Joanna Czuwara

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BACKGROUND: Dermoscopy is a clinical tool known to improve the early detection of melanoma and other malignancies of the skin. Over the past few years melanoma has grown into a disease of socio-economic importance due to the increasing incidence and persistently high mortality rates. Early diagnosis remains the best method to reduce melanoma and non-melanoma skin cancer– related mortality and morbidity. Dermoscopy is a noninvasive technique that consists of viewing pigmented skin lesions through a hand-held lens. This simple procedure increases melanoma diagnostic accuracy by up to 35%. Dermoscopy is currently the standard for clinical differential diagnosis of cutaneous melanoma and for qualifying lesion for the excision biopsy. Like any clinical tool, training is required for effective use. The introduction of small and handy dermoscopes contributed significantly to the switch of dermatoscopy toward a first-level useful tool. Non-dermatologist physicians are well positioned for opportunistic melanoma detection; however, education in the skin cancer examination is limited during medical school and traditionally lecture-based. AIM: The aim of this randomized study was to determine whether the adjunct of dermoscopy to the standard fourth year medical curriculum improves the ability of medical students to distinguish between benign and malignant lesions and assess acceptability and satisfaction with the intervention. METHODS: We performed a prospective study in 2 cohorts of fourth-year medical students at Medical University of Warsaw. Groups having dermatology course, were randomly assigned to:  cohort A: with limited access to dermatoscopy from their teacher only – 1 dermatoscope for 15 people  Cohort B: with a full access to use dermatoscopy during their clinical classes:1 dermatoscope for 4 people available constantly plus 15-minute dermoscopy tutorial. Students in both study arms got an image-based test of 10 lesions to assess ability to differentiate benign from malignant lesions and postintervention survey collecting minimal background information, attitudes about the skin cancer examination and course satisfaction. RESULTS: The cohort B had higher scores than the cohort A in recognition of nonmelanocytic (P < 0.05) and melanocytic (P <0.05) lesions. Medical students who have a possibility to use dermatoscope by themselves have also a higher satisfaction rates after the dermatology course than the group with limited access to this diagnostic tool. Moreover according to our results they were more motivated to learn dermatoscopy and use it in their future everyday clinical practice. LIMITATIONS: There were limited participants. Further study of the application on clinical practice is still needed. CONCLUSION: Although the use of dermatoscope in dermatology as a specialty is widely accepted, sufficiently validated clinical tools for the examination of potentially malignant skin lesions are lacking in general practice. Introducing medical students to dermoscopy in their fourth year curricula of medical school may improve their ability to differentiate benign from malignant lesions. It can can also encourage students to use dermatoscopy in their future practice which can significantly improve early recognition of malignant lesions and thus decrease melanoma mortality.

Keywords: dermatoscopy, early detection of melanoma, medical education, skin cancer

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Authors: Jin Young Kim, Kwon Kyoo Kang

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The SGR1 (STAYGREEN1) protein is a critical regulator of plant leaves in chlorophyll degradation and senescence. The functions and mechanisms of tomato SGR1 action are poorly understood and worthy of further investigation. To investigate the function of the SGR1 gene, we generated a SGR1-knockout (KO) null line via clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9-mediated gene editing and conducted RNA sequencing and gas chromatography tandem mass spectrometry (GC-MS/MS) analysis to identify the differentially expressed genes. The SlSGR1 (Solanum lycopersicum SGR1) knockout null line clearly showed a turbid brown color with significantly higher chlorophyll and carotenoid content compared to wild-type (WT) fruit. Differential gene expression analysis revealed 728 differentially expressed genes (DEGs) between WT and sgr1 #1-6 line, including 263 and 465 downregulated and upregulated genes, respectively, for which fold change was >2, and the adjusted p-value was <0.05. Most of the DEGs were related to photosynthesis and chloroplast function. In addition, the pigment, carotenoid changes in sgr1 #1-6 line was accumulated of key primary metabolites such as sucrose and its derivatives (fructose, galactinol, raffinose), glycolytic intermediates (glucose, G6P, Fru6P) and tricarboxylic acid cycle (TCA) intermediates (malate and fumarate). Taken together, the transcriptome and metabolite profiles of SGR1-KO lines presented here provide evidence for the mechanisms underlying the effects of SGR1 and molecular pathways involved in chlorophyll degradation and carotenoid biosynthesis.

Keywords: tomato, CRISPR/Cas9, null line, RNA-sequencing, metabolite profiling

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Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk

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Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.

Keywords: radiological search, radiological mapping, radioactivity, radiation protection

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Authors: S. Hosseini, M. Ahmadi Najafabadi, M. Akhlaghi

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The health of the journal bearings is very important in preventing unforeseen breakdowns in rotary machines, and poor lubrication is one of the most important factors for producing the bearing failures. Hydrodynamic lubrication (HL), mixed lubrication (ML), and boundary lubrication (BL) are three regimes of a journal bearing lubrication. This paper uses acoustic emission (AE) measurement technique to correlate features of the AE signals to the three lubrication regimes. The transitions from HL to ML based on operating factors such as rotating speed, load, inlet oil pressure by time domain and time-frequency domain signal analysis techniques are detected, and then metal-to-metal contacts between sliding surfaces of the journal and bearing are identified. It is found that there is a significant difference between theoretical and experimental operating values that are obtained for defining the lubrication regions.

Keywords: acoustic emission technique, pressure fed journal bearing, time and frequency signal analysis, metal-to-metal contact

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Authors: Farrukh Shahzad

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The rich Islamic resources related to religious text, Islamic sciences, and history are widely available in print and in electronic format online. However, most of these works are only available in Arabic language. In this research, an attempt is made to utilize these resources to create interactive web applications in Arabic, English and other languages. The system utilizes the Pattern Recognition, Knowledge Management, Data Mining, Information Retrieval and Management, Indexing, storage and data-analysis techniques to parse, store, convert and manage the information from authentic Arabic resources. These interactive web Apps provide smart multi-lingual search, tree based search, on-demand information matching and linking. In this paper, we provide details of application architecture, design, implementation and technologies employed. We also presented the summary of web applications already developed. We have also included some screen shots from the corresponding web sites. These web applications provide an Innovative On-line Learning Systems (eLearning and computer based education).

Keywords: Islamic resources, Muslim scholars, hadith, narrators, history, fiqh

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Authors: Eko Budi Santoso

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There is a growing interest in Corporate Social Responsibility (CSR) issues in developing countries such as Indonesia. Firms disclose their CSR activities, and some provide assurance to gain recognition as socially responsible firms. However, several of those socially responsible firms involve in tax scandals and raise a question of whether CSR disclosure is used to disguise firm misconduct or as a reflection of socially responsible firms. Specifically, whether firms engage in CSR disclosure and its assurance also responsible for their tax matters. This study examines the association between CSR disclosure and tax aggressiveness and the role of sustainability reporting assurance to the association. This research develops a modified index according to global reporting initiatives to measure CSR disclosure and various measurement for tax aggressiveness. Using a sample of Indonesian go public companies issued CSR disclosure, the empirical result shows that there is an association between CSR disclosure and tax aggressiveness. In addition, results also indicate sustainability reporting assurance moderate those association. The findings suggest that stakeholder in developing countries should examine carefully firms with active CSR disclosure before label it as socially responsible firms. JEL Classification: M14

Keywords: CSR disclosure, tax aggressiveness, assurance, business ethics

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Authors: Do Su Park, Sang Jun Park, Cheon Soon Jeong

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This study was performed in order to investigate the optimum ripening conditions for the marketing of Squash. Research sample 'Bochang' was grown at Hongcheonin in Gangwon province in August 2014. Ripening the samples were stored under the conditions of 25℃, 30℃, and 35℃ with the humidity RH70 ± 5%. They were checked every 3 days for 21 days. The respiration rate, water loss, hardness, coloration, the contents of soluble solids, starch, total sugar were evaluated after storage. Respiration rate was reduced in all treatments with longer storage period. Water loss was increased in the higher temperature. The 13% water loss was found at 35℃ on 21st storage day. The store initially 25℃ and 30℃ Hardness 47N and the ripening 21 days decreased slightly. On the other hand, in the case of 35℃ showed a large reduction than 25℃ and 30℃. Soluble solid contents were increased with longer ripening period. 30℃ and 35℃ was highest ripening 15 days. In the case of 25℃, it was highest on 21th day. The higher the temperature, the higher the soluble solids content are. 25℃ and 30℃ Coloration was increased rapidly until the ripening 12 days. In case of 35℃, continued increase up to 21 days. 25℃ and 30℃ showed no differences. Meanwhile, in case of 35℃, appearance quality was reduced in Occurrence of yellowing phenomenon of pericarp occurs from after ripening for 9 days. The coloration of fruit flesh is increase until after ripening for 9 days and decrease from after ripening for 9 days. There was no significant difference depending on the conditions of temperature. The higher the temperature, the lower the content of the starch. In case of 30℃ and 35℃, was reduced with longer storage period. 25℃ was minimal content change. Total sugar was increased in all treatments with longer storage period. The higher the temperature, the higher the amount of total sugar content is. Therefore, at 25℃ for 18-21 days and at 30℃ for 12-15 days is suitable for ripening.

Keywords: marketing, ripening, temperature, winter squash

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Authors: Eun Young Park, Jongwon Park

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A physical touch of a product can provide ample diagnostic information about the product attributes and quality. However, consumers’ product judgments and purchases can be erroneously influenced by non-diagnostic haptic information. For example, consumers’ evaluations of the coffee they drink could be affected by the heaviness of a cup that is used for just serving the coffee. This important issue has received little attention in prior research. The present research contributes to the literature by identifying when and how non-diagnostic haptic information can have an influence and why such influence occurs. Specifically, five studies experimentally varied the content of non-diagnostic haptic information, such as the weight of a cup (heavy vs. light) and the texture of a cup holder (smooth vs. rough), and then assessed the impact of the manipulation on product judgments and decisions. Results show that non-diagnostic haptic information has a biasing impact on consumer judgments. For example, the heavy (vs. light) cup increases consumers’ perception of the richness of coffee in it, and the rough (vs. smooth) texture of a cup holder increases the perception of the healthfulness of fruit juice in it, which in turn increases consumers’ purchase intentions of the product. When consumers are cognitively distracted during the touch experience, the impact of the content of haptic information is no longer evident, but the valence (positive vs. negative) of the haptic experience influences product judgments. However, consumers are able to avoid the impact of non-diagnostic haptic information, if and only if they are both knowledgeable about the product category and undistracted from processing the touch experience. In sum, the nature of the influence by non-diagnostic haptic information (i.e., assimilation effect vs. contrast effect vs. null effect) is determined by the content and valence of haptic information, the relative impact of which depends on whether consumers can identify the content and source of the haptic information. Theoretically, to our best knowledge, this research is the first to document the empirical evidence of the interplay between cognitive and affective processes that determines the impact of non-diagnostic haptic information. Managerial implications are discussed.

Keywords: consumer behavior, haptic information, product judgments, touch effect

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Authors: W. P. Hu, J. V. Kumar, Jeffrey J. P. Tsai

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The inhibition of SH2 domain regulated protein-protein interactions is an attractive target for developing an effective chemotherapeutic approach in the treatment of disease. Molecular simulation is a useful tool for developing new drugs and for studying molecular recognition. In this study, we searched potential drug compounds for the inhibition of SH2 domain by performing structural similarity search in PubChem Compound Database. A total of 37 compounds were screened from the database, and then we used the LibDock docking program to evaluate the inhibition effect. The best three compounds (AP22408, CID 71463546 and CID 9917321) were chosen for MD simulations after the LibDock docking. Our results show that the compound CID 9917321 can produce a more stable protein-ligand complex compared to other two currently known inhibitors of Src SH2 domain. The compound CID 9917321 may be useful for the inhibition of SH2 domain based on these computational results. Subsequently experiments are needed to verify the effect of compound CID 9917321 on the SH2 domain in the future studies.

Keywords: nonpeptide inhibitor, Src SH2 domain, LibDock, molecular dynamics simulation

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Authors: Maryam Panahiazar, Andrew M. Bishara, Yorick Chern, Roohallah Alizadehsani, Dexter Hadleye, Ramin E. Beygui

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Early detection plays a crucial role in enhancing the outcome for a patient with coronary artery disease (CAD). We utilized a big data analytics platform on ~23,000 patients with CAD from a total of 960,129 UCSF patients in 8 years. We traced the patients from their first encounter with a physician to diagnose and treat CAD. Characteristics such as demographic information, comorbidities, vital, lab tests, medications, and procedures are included. There are statistically significant gender-based differences in patients younger than 60 years old from the time of the first physician encounter to coronary artery bypass grafting (CABG) with a p-value=0.03. There are no significant differences between the patients between 60 and 80 years old (p-value=0.8) and older than 80 (p-value=0.4) with a 95% confidence interval. This recognition would affect significant changes in the guideline for referral of the patients for diagnostic tests expeditiously to improve the outcome by avoiding the delay in treatment.

Keywords: electronic medical records, coronary artery disease, data analytics, young women

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Authors: Reza Rezaeipour Honarmandzad

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Wavelet analysis is an exciting method for solving difficult problems in mathematics, physics, and engineering, with modern applications as diverse as wave propagation, data compression, signal processing, image processing, pattern recognition, etc. Wavelets allow complex information such as signals, images and patterns to be decomposed into elementary forms at different positions and scales and subsequently reconstructed with high precision. In this paper a wavelet-based signal processing algorithm for airplane cable fault location is proposed. An orthogonal discrete wavelet decomposition and reconstruction algorithm is used to eliminate the noise in the aircraft cable fault signal. The experiment result has shown that the character of emission pulse and reflect pulse used to test the aircraft cable fault point are reserved and the high-frequency noise are eliminated by means of the proposed algorithm in this paper.

Keywords: wavelet analysis, signal processing, orthogonal discrete wavelet, noise, aircraft cable fault signal

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Authors: Shierwin Agagen Cabunilas

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The unitary form of Philippine government has built a tradition of bureaucracy that strengthened oligarch and clientele politics. Consequently, the Philippines is lagged behind development. There is so much poverty, unemployment, and inadequate social services. In addition, it seems that the rights of national ethnic minority groups like the Igorots to develop their political and economic interests, linguistic and cultural heritage are neglected. Given these circumstances, a paradigm shift is inevitable. The author advocates a transition from a unitary to a federal system of government. Contrary to the notion that a unitary system facilitates better governance, it actually stifles it. As a unitary government, the Philippines seems (a) to exhibit incompetence in delivering efficient, necessary services to the people and (b) to exclude the minority from political participation and policy making. This shows that Philippine unitary system is highly centralized and operates from a top-bottom scheme. However, a federal system encourages decentralization, plurality and political participation. In my view, federalism is beneficial to the Philippine society and congenial to the Igorot indigenous peoples insofar as participative decision-making and development goals are concerned. This research employs critical and constructive analyses. The former interprets some complex practices of Philippine politics while the latter investigates how theories of federalism can be appropriated to deal with political deficits, ethnic diversity, and indigenous peoples’ rights to self-determination. The topic is developed accordingly: First, the author briefly examines the unitary structure of the Philippines and its impact on inter-governmental affairs and processes, asserting that bureaucracy and corruption, for example, are counterproductive to a participative political life, to economic development and to the recognition of national ethnic minorities. Second, he scrutinizes why federalism might transform this. Here, he assesses various opposing philosophical contentions on federal system in managing ethnically diverse society, like the Philippines, and argue that decentralization of political power, economic and cultural developments are reasons to exit from unitary government. Third, he suggests that federalism can be instrumental to Igorots self-determination. Self-determination is neither opposed to national development nor to the ideals of democracy – liberty, justice, solidarity. For example, as others have already noted, a politics in the vernacular facilitates greater participation among the people. Hence, there is a greater chance to arrive at policies that serve the interest of the people. Some may wary that decentralization disintegrates a nation. According to the author, however, the recognition of minority rights which includes self-determination may promote filial devotion to the state. If Igorot indigenous peoples have access to suitable institutions to determine their political life, economic goals, social needs, i.e., education, culture, language, chances are it moves the country forward to development fostering national unity. Remarkably, federal system thus best responds to the Philippines’s democratic and development deficits. Federalism can also significantly rectify the practices that oppress and dislocate national ethnic minorities as it ensures the creation of localized institutions for optimum political, economic, cultural determination and maximizes representation in the public sphere.

Keywords: federalism, Igorot, indigenous peoples, self-determination

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, S. Meenakshi Sundaram

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Alzheimer’s disease is one of the prevalent kind of ailment, expected for impudent reconciliation or an effectual therapy is to be accredited hitherto. Probable detonation of patients in the upcoming years, and consequently an enormous deal of apprehension in early discovery of the disorder, this will conceivably chaperon to enhanced healing outcomes. Complex impetuosity of the brain is an observant symbolic of the disease and a unique recognition of genetic sign of the disease. Machine learning alongside deep learning and decision tree reinforces the aptitude to absorb characteristics from multi-dimensional data’s and thus simplifies automatic classification of Alzheimer’s disease. Susceptible testing was prophesied and realized in training the prospect of Alzheimer’s disease classification built on machine learning advances. It was shrewd that the decision trees trained with deep neural network fashioned the excellent results parallel to related pattern classification.

Keywords: Alzheimer's diagnosis, decision trees, deep neural network, machine learning, pattern classification

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Authors: Chia-Chun Wu, Yu-Hsien Sung

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This study aims to examine the consistency between students’ predictions and their actual observations on the bullying prevalence rate among different types of high-risk victims, thereby clarifying the reliability of students’ reports on the identification of bullying. A total of 1,732 Taiwanese students (734 males and 998 females) participated in this study. A Rasch model was adopted for data analysis. The results showed that students with “personality or behavioral issues” are more likely to be bullied in schools, based on both students’ predictions and actual observations. Moreover, the results differed significantly between genders and between various educational levels in students’ predictions and their actual observations on the bullying prevalence rate of different types of high-risk victims. To summarize, this study not only suggests that students’ reports on the identification of bullying are accurate and could be a valuable reference in terms of recognizing a bullying incident, but it also argues that more attention should be paid to students’ gender and educational level when taking their perspectives into consideration when it comes to identifying bullying behaviors.

Keywords: school bullying, student, bullying recognition, high-risk victims

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Authors: Fei Jia, Xingjian Bai, Xiaowei Zhang, Wenjie Yan, Ruitong Dai, Xingmin Li, Jozef Kokini

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Pseudomonas aeruginosa is a Gram-negative, aerobic, opportunistic human pathogen that is present in the soil, water, and food. This microbe has been recognized as a representative food-borne spoilage bacterium that can lead to many types of infections. Considering the casualties and property loss caused by P. aeruginosa, the development of a rapid and reliable technique for the detection of P. aeruginosa is crucial. The whole-cell aptasensor, an emerging biosensor using aptamer as a capture probe to bind to the whole cell, for food-borne pathogens detection has attracted much attention due to its convenience and high sensitivity. Here, a low-field magnetic resonance imaging (LF-MRI) aptasensor for the rapid detection of P. aeruginosa was developed. The basic detection principle of the magnetic relaxation switch (MRSw) nanosensor lies on the ‘T₂-shortening’ effect of magnetic nanoparticles in NMR measurements. Briefly speaking, the transverse relaxation time (T₂) of neighboring water protons get shortened when magnetic nanoparticles are clustered due to the cross-linking upon the recognition and binding of biological targets, or simply when the concentration of the magnetic nanoparticles increased. Such shortening is related to both the state change (aggregation or dissociation) and the concentration change of magnetic nanoparticles and can be detected using NMR relaxometry or MRI scanners. In this work, two different sizes of magnetic nanoparticles, which are 10 nm (MN₁₀) and 400 nm (MN₄₀₀) in diameter, were first immobilized with anti- P. aeruginosa aptamer through 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC)/N-hydroxysuccinimide (NHS) chemistry separately, to capture and enrich the P. aeruginosa cells. When incubating with the target, a ‘sandwich’ (MN₁₀-bacteria-MN₄₀₀) complex are formed driven by the bonding of MN400 with P. aeruginosa through aptamer recognition, as well as the conjugate aggregation of MN₁₀ on the surface of P. aeruginosa. Due to the different magnetic performance of the MN₁₀ and MN₄₀₀ in the magnetic field caused by their different saturation magnetization, the MN₁₀-bacteria-MN₄₀₀ complex, as well as the unreacted MN₄₀₀ in the solution, can be quickly removed by magnetic separation, and as a result, only unreacted MN₁₀ remain in the solution. The remaining MN₁₀, which are superparamagnetic and stable in low field magnetic field, work as a signal readout for T₂ measurement. Under the optimum condition, the LF-MRI platform provides both image analysis and quantitative detection of P. aeruginosa, with the detection limit as low as 100 cfu/mL. The feasibility and specificity of the aptasensor are demonstrated in detecting real food samples and validated by using plate counting methods. Only two steps and less than 2 hours needed for the detection procedure, this robust aptasensor can detect P. aeruginosa with a wide linear range from 3.1 ×10² cfu/mL to 3.1 ×10⁷ cfu/mL, which is superior to conventional plate counting method and other molecular biology testing assay. Moreover, the aptasensor has a potential to detect other bacteria or toxins by changing suitable aptamers. Considering the excellent accuracy, feasibility, and practicality, the whole-cell aptasensor provides a promising platform for a quick, direct and accurate determination of food-borne pathogens at cell-level.

Keywords: magnetic resonance imaging, meat spoilage, P. aeruginosa, transverse relaxation time

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Authors: Nausheen Irshad

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Human-wildlife conflict (HWC) exists in both developed and developing countries though it is more serious in developing nations. Knowledge of species ecology and species sensitivity to anthropogenic pressures is an important prerequisite for conservation/management. Therefore, three districts (Poonch, Bagh, and Muzaffarabad) of Azad Jammu and Kashmir were selected to highlight the wildlife hunting practices from January 2015 to November 2018. The study area was thoroughly explored to recover dead animals. Moreover, the local community was investigated (questionnaire survey) to catch on motives of killing. The results showed HWC mainly arises due to feeding habits of wild animals as some are frugivorous (small Indian civet and small Kashmir flying squirrel) who damaged human cultivated fruit trees. Besides, Indian crested porcupine and wild boar act as serious crop pests. The feeding upon domestic animals (common leopard) and poultry (Asiatic Jackal and Red fox) were also reported as factors of conflict. Hence numerous wild animals and birds (N=120) were found killed by natives in revenge. Despite protected status in Pakistan, the killed mammals belonged to categories of critically endangered (Panthera pardus) and near threatened (Viverricula indica) species. The important birds include critically endangered (Falco peregrines) and endangered (Lophura leucomelanos) species. It was found that mammals were primarily killed due to HWC (60%) followed by recreation (20%) and trade (15%) Whereas, the foremost hunting reasons for birds are recreation (50%), food (25%) and trade (25%). The drastic hunting/killing of the species needs our immediate attention. This unwarranted killing must be stopped forthwith otherwise these animals become extinct.

Keywords: Azad Jammu and Kashmir, anthropogenic pressures, endangered species, human-wildlife conflicts

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Authors: Magdalena Twaruzek, Karolina Ropejko

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Mycotoxins are secondary metabolites of molds. Ochratoxin A (OTA) is the most common in the Polish climate. It is produced by fungi of the genera Aspergillus and Penicillium. It is produced as a result of improper food storage. It is present in many products that are consumed both by humans and animals: cereals, wheat gluten, coffee, dried fruit, wine, grape juice, spices, beer, and products based on them. OTA is nephrotoxic, hepatotoxic, potentially carcinogenic, and teratogenic. OTA mainly enters an organism by oral intake. The aim of the study was to detect the presence of OTA in milk, urine, and serum of lactating women. A survey was also conducted regarding the daily diet of women. The research group consisted of 32 lactating women (11 were the donors from the Milk Bank in Toruń, the other 21 were recruited for this study). Results of the analysis showed the occurrence of OTA only in 3 milk samples (9.38%). The minimum level was 0.01 ng/ml, while the maximum 0.018 ng/ml and the mean 0.0013 ng/ml. Twenty-six urine samples (81.25%) were OTA positive, with minimum level 0.013 ng/ml, maximum level 0.117 ng/ml and mean 0.0192 ng/ml. Also, all 32 serum samples (100%) were contaminated by OTA, with a minimum level of 0.099 ng/ml, a maximum level of 2.38 ng/ml, and a mean of 0.4649 ng/ml. In the case of 3 women, OTA was present in all tested body fluids. Based on the results, the following conclusions can be drawn: the breast-milk of women in the study group is slightly contaminated with ochratoxin A. Ten samples of urine contained ochratoxin A above its average content in tested samples. Moreover, serum of 8 women contains ochratoxin A at a level above the average content of this mycotoxin in tested samples. The average ochratoxin A level in serum in the presented studies was 0.4649 ng/ml, which is much lower than the average serum ochratoxin A level established in several countries in the world, i.e., 0.7 ng/ml. Acknowledgment: This study was supported by the Polish Minister of Science and Higher Education under the program 'Regional Initiative of Excellence' in 2019 - 2022 (Grant No. 008/RID/2018/19).

Keywords: breast-milk, urine, serum, contamination, ochratoxin A

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Authors: E. Younsi, H. Andriamboavonjy, A. David, S. Dokou, B. Lemrabet

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Software and time optimization are very important factors in financial markets, which are competitive fields, and emergence of new computer tools further stresses the challenge. In this context, any improvement of technical indicators which generate a buy or sell signal is a major issue. Thus, many tools have been created to make them more effective. This worry about efficiency has been leading in present paper to seek best (and most innovative) way giving largest improvement in these indicators. The approach consists in attaching a signature to frequent market configurations by application of frequent patterns extraction method which is here most appropriate to optimize investment strategies. The goal of proposed trading algorithm is to find most accurate signatures using back testing procedure applied to technical indicators for improving their performance. The problem is then to determine the signatures which, combined with an indicator, outperform this indicator alone. To do this, the FP-Tree algorithm has been preferred, as it appears to be the most efficient algorithm to perform this task.

Keywords: quantitative analysis, back-testing, computational models, apriori algorithm, pattern recognition, data mining, FP-tree

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Authors: L. Steponavičiūtė, L. Steponavičienė

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Despite the rapid nanotechnology progress and recognition, its potential impact in ecosystems and health of humans is still not fully known. In this paper, the study of ecotoxicological dangers of nanomaterials is presented. By chemical reduction method, silver (AgNPs) and gold (AuNPs) nanoparticles were synthesized, characterized and used in experiments to examine their impact on microorganisms (Escherichia coli, Staphylococcus aureus and Candida albicans) and terrestrial flora (Phaseolus vulgaris and Lepidium sativum). The results collected during experiments with terrestrial flora show tendentious growth stimulations caused by gold nanoparticles. In contrast to these results, silver nanoparticle solutions inhibited growth of beans and garden cress, compared to control samples. The results obtained from experiments with microorganisms show similarities with ones collected from experiments with terrestrial plants. Samples treated with AuNPs of size 13 nm showed stimulation in the growth of the colonies compared with 3,5 nm size nanoparticles.

Keywords: nanomaterials, ecotoxicology, nanoparticles, ecosystems

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Authors: Mansouri Nabila, Ben Jemaa Yousra, Motamed Cina, Watelain Eric

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Research and development efforts in intelligent Advanced Driver Assistance Systems (ADAS) seek to save lives and reduce the number of on-road fatalities. For traffic and emergency monitoring, the essential but challenging task is vehicle detection and tracking in reasonably short time. This purpose needs first of all a powerful dynamic car detector model. In fact, this paper presents an optimized HOG process based on shape and motion parameters fusion. Our proposed approach mains to compute HOG by bloc feature from foreground blobs using configurable research window and pathway in order to overcome the shortcoming in term of computing time of HOG descriptor and improve their dynamic application performance. Indeed we prove in this paper that HOG by bloc descriptor combined with motion parameters is a very suitable car detector which reaches in record time a satisfactory recognition rate in dynamic outside area and bypasses several popular works without using sophisticated and expensive architectures such as GPU and FPGA.

Keywords: car-detector, HOG, motion, computing time

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Authors: Christoph Linse, Thomas Martinetz

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Recent findings have shown that Neural Networks generalize also in over-parametrized regimes with zero training error. This is surprising, since it is completely against traditional machine learning wisdom. In our empirical study we fortify these findings in the domain of fine-grained image classification. We show that very large Convolutional Neural Networks with millions of weights do learn with only a handful of training samples and without image augmentation, explicit regularization or pretraining. We train the architectures ResNet018, ResNet101 and VGG19 on subsets of the difficult benchmark datasets Caltech101, CUB_200_2011, FGVCAircraft, Flowers102 and StanfordCars with 100 classes and more, perform a comprehensive comparative study and draw implications for the practical application of CNNs. Finally, we show that VGG19 with 140 million weights learns to distinguish airplanes and motorbikes with up to 95% accuracy using only 20 training samples per class.

Keywords: convolutional neural networks, fine-grained image classification, generalization, image recognition, over-parameterized, small data sets

Procedia PDF Downloads 74