Search results for: inverse docking

Authors: Hedi Dghim, Ahmed El-Naggar, Istvan Erlich

Abstract:

Power electronic converters are being introduced in low voltage (LV) grids at an increasingly rapid rate due to the growing adoption of power electronic-based home appliances in residential grid. Photovoltaic (PV) systems are considered one of the potential installed renewable energy sources in distribution power systems. This trend has led to high distortion in the supply voltage which consequently produces harmonic currents in the network and causes an inherent voltage unbalance. In order to investigate the effect of harmonic distortions, a case study of a typical LV grid configuration with high penetration of 3-phase and 1-phase rooftop mounted PV from southern Germany was first considered. Electromagnetic transient (EMT) simulations were then carried out under the MATLAB/Simulink environment which contain detailed models for power electronic-based loads, ohmic-based loads as well as 1- and 3-phase PV. Note that, the switching patterns of the power electronic circuits were considered in this study. Measurements were eventually performed to analyze the distortion levels when PV operating under different solar irradiance. The characteristics of the load-side harmonic impedances were analyzed, and their harmonic contributions were evaluated for different distortion levels. The effect of the high penetration of PV on the harmonic distortion of both positive and negative sequences was also investigated. The simulation results are presented based on case studies. The current distortion levels are in agreement with relevant standards, otherwise the Total Harmonic Distortion (THD) increases under low PV power generation due to its inverse relation with the fundamental current.

Keywords: harmonic distortion analysis, power quality, PV systems, residential distribution system

Procedia PDF Downloads 267

Authors: A. S. Gorobtsov, A. S. Polyanina, A. E. Andreev

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The movement of points feet of the anthropomorphous robot in space occurs along some stable trajectory of a known form. A large number of modifications to the methods of control of biped robots indicate the fundamental complexity of the problem of stability of the program trajectory and, consequently, the stability of the control for the deviation for this trajectory. Existing gait generators use piecewise interpolation of program trajectories. This leads to jumps in the acceleration at the boundaries of sites. Another interpolation can be realized using differential equations with fractional derivatives. In work, the approach to synthesis of generators of program trajectories is considered. The resulting system of nonlinear differential equations describes a smooth trajectory of movement having rectilinear sites. The method is based on the theory of an asymptotic stability of invariant sets. The stability of such systems in the area of localization of oscillatory processes is investigated. The boundary of the area is a bounded closed surface. In the corresponding subspaces of the oscillatory circuits, the resulting stable limit cycles are curves having rectilinear sites. The solution of the problem is carried out by means of synthesis of a set of the continuous smooth controls with feedback. The necessary geometry of closed trajectories of movement is obtained due to the introduction of high-order nonlinearities in the control of stabilization systems. The offered method was used for the generation of trajectories of movement of point’s feet of the anthropomorphous robot. The synthesis of the robot's program movement was carried out by means of the inverse method.

Keywords: control, limits cycle, robot, stability

Procedia PDF Downloads 331

Authors: Hussaini Bala

Abstract:

There are different opinions in the literature on the relationship between Audit Committee characteristics and earnings management. The mix of opinions makes the direction of their relationship ambiguous. This study investigated the relationship between Audit Committee characteristics and earnings management of listed food and beverages Firms in Nigeria. The study covered the period of six years from 2007 to 2012. Data for the study were extracted from the Firms’ annual reports and accounts. After running the OLS regression, a robustness test was conducted for the validity of statistical inferences. The dependent variable was generated using two steps regression in order to determine the discretionary accrual of the sample Firms. Multiple regression was employed to run the data of the study using Random Model. The results from the analysis revealed a significant association between audit committee characteristics and earnings management of the Firms. While audit committee size and committees’ financial expertise showed an inverse relationship with earnings management, committee’s independence, and frequency of meetings are positively and significantly related to earnings management. In line with the findings, the study recommended among others that listed food and beverages Firms in Nigeria should strictly comply with the provision of Companies and Allied Matters Act (CAMA) and SEC Code of Corporate Governance on the issues regarding Audit Committees. Regulators such as SEC should increase the minimum number of Audit Committee members with financial expertise and also have a statutory position on the maximum number of Audit Committees meetings, which should not be greater than four meetings in a year as SEC code of corporate governance is silent on this.

Keywords: audit committee, earnings management, listed Food and beverages size, leverage, Nigeria

Procedia PDF Downloads 271

Authors: Muhammad Farhan Ul Moazzam, Tamkeen Urooj Paracha, Ghani Rahman, Byung Gul Lee, Nasir Farid, Adnan Arshad

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The novel coronavirus pandemic disease (COVID-19) affected the whole globe, though there is a lack of clinical studies and its epidemiological features. But as per the observation, it has been seen that most of the COVID-19 infected patients show mild to moderate symptoms, and they get better without any medical assistance due to a better immune system to generate antibodies against the novel coronavirus. In this study, the active cases, serious cases, recovered cases, deaths and total confirmed cases had been analyzed using the geospatial inverse distance weightage technique (IDW) within the time span of 2nd March to 3rd June 2020. As of 3rd June, the total number of COVID-19 cases in Italy were 231,238, total deaths 33,310, serious cases 350, recovered cases 158,951, and active cases were 39,177, which has been reported by the Ministry of Health, Italy. March 2nd-June 3rd, 2020 a sum of 231,238 cases has been reported in Italy out of which 38.68% cases reported in the Lombardia region with a death rate of 18%, which is high from its national mortality rate followed by Emilia-Romagna (14.89% deaths), Piemonte (12.68% deaths), and Vento (10% deaths). As per the total cases in the region, the highest number of recoveries has been observed in Umbria (92.52%), followed by Basilicata (87%), Valle d'Aosta (86.85%), and Trento (84.54%). The COVID-19 evolution in Italy has been particularly found in the major urban area, i.e., Rome, Milan, Naples, Bologna, and Florence. Geospatial technology played a vital role in this pandemic by tracking infected patient, active cases, and recovered cases. Geospatial techniques are very important in terms of monitoring and planning to control the pandemic spread in the country.

Keywords: COVID-19, public health, geospatial analysis, IDW, Italy

Procedia PDF Downloads 154

Authors: Alexander N. Pisarchik, Parth Chholak

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Intrinsic brain noise was estimated via magneto-encephalograms (MEG) recorded during perception of flickering visual stimuli with frequencies of 6.67 and 8.57 Hz. First, we measured the mean phase difference between the flicker signal and steady-state event-related field (SSERF) in the occipital area where the brain response at the flicker frequencies and their harmonics appeared in the power spectrum. Then, we calculated the probability distribution of the phase fluctuations in the regions of frequency locking and computed its kurtosis. Since kurtosis is a measure of the distribution’s sharpness, we suppose that inverse kurtosis is related to intrinsic brain noise. In our experiments, the kurtosis value varied among subjects from K = 3 to K = 5 for 6.67 Hz and from 2.6 to 4 for 8.57 Hz. The majority of subjects demonstrated leptokurtic kurtosis (K < 3), i.e., the distribution tails approached zero more slowly than Gaussian. In addition, we found a strong correlation between kurtosis and brain complexity measured as the correlation dimension, so that the MEGs of subjects with higher kurtosis exhibited lower complexity. The obtained results are discussed in the framework of nonlinear dynamics and complex network theories. Specifically, in a network of coupled oscillators, phase synchronization is mainly determined by two antagonistic factors, noise, and the coupling strength. While noise worsens phase synchronization, the coupling improves it. If we assume that each neuron and each synapse contribute to brain noise, the larger neuronal network should have stronger noise, and therefore phase synchronization should be worse, that results in smaller kurtosis. The described method for brain noise estimation can be useful for diagnostics of some brain pathologies associated with abnormal brain noise.

Keywords: brain, flickering, magnetoencephalography, MEG, visual perception, perception time

Procedia PDF Downloads 148

Authors: Manendra Singh Parihar, Sandip Ghosh Chowdhury

Abstract:

Austenitic stainless steels are widely used and give a good combination of properties. When this steel is plastically deformed, a phase transformation of the metastable Face Centred Cubic Austenite to the stable Body Centred Cubic (α’) or to the Hexagonal close packed (ԑ) martensite may occur, leading to the enhancement in the mechanical properties like strength. The work was based on variant selection and corresponding texture analysis for the strain induced martensitic transformation during deformation of the parent austenite FCC phase to form the product HCP and the BCC martensite phases separately, obeying their respective orientation relationships. The automated method for reconstruction of the parent phase orientation using the EBSD data of the product phase orientation is done using the MATLAB and TSL-OIM software. The method of triplets was used which involves the formation of a triplet of neighboring product grains having a common variant and linking them using a misorientation-based criterion. This led to the proper reconstruction of the pre-transformation phase orientation data and thus to its microstructure and texture. The computational speed of current method is better compared to the previously used methods of reconstruction. The reconstruction of austenite from ԑ and α’ martensite was carried out for multiple samples and their IPF images, pole figures, inverse pole figures and ODFs were compared. Similar type of results was observed for all samples. The comparison gives the idea for estimating the correct sequence of the transformation i.e. γ → ε → α’ or γ → α’, during deformation of AISI 304 austenitic stainless steel.

Keywords: variant selection, reconstruction, EBSD, austenitic stainless steel, martensitic transformation

Procedia PDF Downloads 497

Authors: Khaleel Alyahya, Faizah Alotaibi

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The coronavirus disease 19 (COVID-19) pandemic has caused an increase in general fear and anxiety around the globe. With the public health measures, including lockdown and travel restrictions, the COVID-19 period further resulted in a sudden increase in the vulnerability of people too ill mental health. This becomes greater among individuals who have a history of mental illness or are undergoing treatment and do not have easy access to medication and medical consultations. The study aims to measure the impact of COVID-19 and the degree of distress with the DASS scale on the mental health of residents living in Saudi Arabia. The study is a quantitative, observational, and cross-sectional conducted in Saudi Arabia to measure the impact of COVID-19 on the mental health of both citizens and residents of Saudi Arabia during pandemics. The study ran from February 2021 to June 2021, and a validated questionnaire was used. The targeted population of the study was Saudi citizens and non-Saudi residents. A sample size of 800 participants was calculated with a single proportion formula at 95% level of significance and 5% allowable error. The result revealed that participants who were always doing exercise experienced the lowest level of depression, anxiety, and stress. The highest prevalence of severe and extremely severe depression was among participants who sometimes do exercise at 53.2% for each. Similar results were obtained for anxiety and stress, where the extremely severe form was reported by those who sometimes did exercise at 54.8% and 72.2%, respectively. There was an inverse association between physical activity levels and levels of depression, anxiety, and stress during the COVID-19. Similarly, the levels of depression, anxiety, and stress differed significantly according to the exercise frequency during COVID-19.

Keywords: mental, COVID-19, pandemic, lockdown, depression, anxiety, stress

Procedia PDF Downloads 103

Authors: Junie B. Billones, Maria Constancia O. Carrillo, Voltaire G. Organo, Stephani Joy Y. Macalino, Inno A. Emnacen, Jamie Bernadette A. Sy

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The drug discovery and development process is generally known to be a very lengthy and labor-intensive process. Therefore, in order to be able to deliver prompt and effective responses to cure certain diseases, there is an urgent need to reduce the time and resources needed to design, develop, and optimize potential drugs. Computer-aided drug design (CADD) is able to alleviate this issue by applying computational power in order to streamline the whole drug discovery process, starting from target identification to lead optimization. This drug design approach can be predominantly applied to diseases that cause major public health concerns, such as tuberculosis. Hitherto, there has been no concrete cure for this disease, especially with the continuing emergence of drug resistant strains. In this study, CADD is employed for tuberculosis by first identifying a key enzyme in the mycobacterium’s metabolic pathway that would make a good drug target. One such potential target is the lipoate protein ligase B enzyme (LipB), which is a key enzyme in the M. tuberculosis metabolic pathway involved in the biosynthesis of the lipoic acid cofactor. Its expression is considerably up-regulated in patients with multi-drug resistant tuberculosis (MDR-TB) and it has no known back-up mechanism that can take over its function when inhibited, making it an extremely attractive target. Using cutting-edge computational methods, compounds from AnalytiCon Discovery Natural Derivatives database were screened and docked against the LipB enzyme in order to rank them based on their binding affinities. Compounds which have better binding affinities than LipB’s known inhibitor, decanoic acid, were subjected to in silico toxicity evaluation using the ADMET and TOPKAT protocols. Out of the 31,692 compounds in the database, 112 of these showed better binding energies than decanoic acid. Furthermore, 12 out of the 112 compounds showed highly promising ADMET and TOPKAT properties. Future studies involving in vitro or in vivo bioassays may be done to further confirm the therapeutic efficacy of these 12 compounds, which eventually may then lead to a novel class of anti-tuberculosis drugs.

Keywords: pharmacophore, molecular docking, lipoate protein ligase B (LipB), ADMET, TOPKAT

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Authors: Famurewa Olumide Joseph, Akinsulore Adesanmi

Abstract:

The current study investigated aggressive behaviour and its association with substance use disorder among senior secondary school students in Ilesha, Nigeria. Participants were three hundred and seventy-five (375) comprising (212) females and (163) males of senior secondary school students in Ilesa East and Ilesa West; who were randomly selected among the population of students from the schools. The mean age of the respondents was 14.61 years (S.D = 1.16), with 311 (82.9%) between 14 – 16 years. Female respondents were 212 (56.5%), while male respondents were 163 (43.5%). A cross sectional design was adopted. Three instruments were used for data collection. Buss Perry Aggression Questionnaire, Alcohol Use Disorder Identification Test (AUDIT) and Drug Abuse Screening Test (DAST). It was hypothesized that aggressive behaviour will be associated with substance use disorder among senior secondary school students in Ilesa East and Ilesa West. The result indicated that the overall prevalence of substance use disorder was 16.0%. Chi-Square test exploring the association between aggressive behaviour and substance use disorder shows that there is a significant association between aggressive behaviour and substance use disorder (χ2 =8.55, p =0.014). Results also showed that emotional problem (χ2 (2) =13.0; p = 0.001) was statistically significant while current medications intake (χ2 (2) =2.03; p =0.362) and overall wellbeing (χ2 (4) =2.49; p =0.646) were not statistically significant. There is an inverse association between prosocial behaviour and aggressive behaviour (r= -0.037, p>0.05). This indicates that as the level of prosocial behaviour increases, the level of aggressive behaviour among respondents decreases. However, alcohol use had no correlation with aggressive behaviour (r=0.070, p>0.05). Among the implications stated is that factors such as emotional symptoms, conduct problems, hyperactivity, peer problem and drug use contributed to the prevalence of aggressive behaviour among students. Suggestions for further studies were equally made.

Keywords: aggressive behaviour, alcohol, prevalence, students, substance use disorder (SUD)

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Authors: Zhibin Lei, Minghui Yang

Abstract:

Ningwu-Jingle basin is a structural syncline which has undergone a complex tectono-thermal history since Cretaceous. It stretches along the strike of the northern Lvliang Mountains which are the most important mountains in the middle and west of North China Craton. The Mesozoic units make up of the core of Ningwu-Jingle Basin, with pre-Mesozoic units making up of its flanks. The available low-temperature thermochronology implies that Ningwu-Jingle Basin has experienced two stages of uplifting: 94±7Ma to 111±8Ma (Albian to Cenomanian) and 62±4 to 75±5Ma (Danian to Maastrichtian). In order to constrain its tectono-thermal history in the Cenozoic, both apatite (U-Th-Sm)/He and fission track dating analysis are applied on 3 Middle Jurassic and 3 Upper Triassic sandstone samples. The central fission track ages range from 74.4±8.8Ma to 66.0±8.0Ma (Campanian to Maastrichtian) which matches well with previous data. The central He ages range from 20.1±1.2Ma to 49.1±3.0Ma (Ypresian to Burdigalian). Inverse thermal modeling is established based on both apatite fission track data and (U-Th-Sm)/He data. The thermal history obtained reveals that all 6 sandstone samples cross the high-temperature limit of fission track partial annealing zone by the uppermost Cretaceous and that of He partial retention zone by the uppermost Eocene to the early Oligocene. The result indicates that the middle and west of North China Craton is not stable in the Cenozoic.

Keywords: apatite fission track thermochronology, apatite (u–th)/he thermochronology, Ningwu-Jingle basin, North China craton, tectono-thermal history

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Authors: Samwel Boaz Otieno, Fred Were, Ephantus Kabiru, Kaunda Waza

Abstract:

A study was done to establish determinants of selenium intake in a high HIV prevalence fishing community in the Pala Bondo district, Kenya. It was established that most of the respondents (61%) were small holder Farmers and Fishermen {χ² (1, N=386) p<0.000}, and that most of them (91.2%) had up to college level education {χ².(1, N=386) p<0.000}, while the number of males and females were not significantly different {χ (1, N=386) p=0.263} and 83.5% of respondents were married {χ² (1, N=386) p=0.000}. The study showed that adults take on average 2.68 meals a day (N=382, SD=0.603), while children take 3.02 meals (N=386, SD=1.031) a day, and that in most households (82.6%) food is prepared by the women {χ² (1, N=386) p=0.000} and further that 50% of foods eaten in that community are purchased {χ² (1, N=386)=0.1818, p=0.6698}. The foods eaten by 75.2% of the respondents were Oreochromis niloticus, Lates niloticus, and Sorghum bicolour, 64.1% vegetables and that both children and adults eat same types of food, and further that traditional foods which have become extinct are mainly vegetables (46%). The study established that selenium levels in foods eaten in Pala sub-locations varies with traditional vegetables having higher levels of selenium; for example, Laurnea cornuta (148.5 mg/kg), Cleome gynandra (121.5 mg/kg), Vignia ungulata (21.97 mg/kg), while Rastrineobola argentea (51 mg/kg), Lates niloticus (0), Oreochromis niloticus (0) Sorgum bicolour (19.97 mg/kg), and Sorgum bicolour (0). The study showed that there is an inverse relationship between foods eaten and selenium levels {RR=1.21, p=0.000}, with foods eaten by 75.2% of respondents (Oreochromis niloticus/Lates niloticus) having no detectable selenium. The four soil types identified in the study area had varying selenium levels with pleat loam (13.3 mg/kg), sandy loam (10.7 mg/kg), clay (2.8 mg/kg) and loam (4.8 mg/kg). It was concluded from this study that for the foods eaten by most of the respondents the selenium levels were below Daily Reference Intake.

Keywords: determinants, HIV, food, fishing, Selenium

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Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah

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Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.

Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning

Procedia PDF Downloads 32

Authors: Hamzeh Alipour, Masoumeh Bagheri, Abbasali Raz, Javad Dadgar Pakdel, Kourosh Azizi, Aboozar Soltani, Mohammad Djaefar Moemenbellah-Fard

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Background: Maggot debridement therapy is an appropriate, effective, and controlled method using sterilized larvae of Luciliasericata (L.sericata) to treat wounds. Netrin-A is an enzyme in the Laminins family which secreted from salivary gland of L.sericata with a central role in neural regeneration and angiogenesis. This study aimed to production of new recombinant Netrin-A protein of Luciliasericata larvae by baculovirus expression vector system (BEVS) in SF9. Material and methods: In the first step, gene structure was subjected to the in silico studies, which were include determination of Antibacterial activity, Prion formation risk, homology modeling, Molecular docking analysis, and Optimization of recombinant protein. In the second step, the Netrin-A gene was cloned and amplified in pTG19 vector. After digestion with BamH1 and EcoR1 restriction enzymes, it was cloned in pFastBac HTA vector. It was then transformed into DH10Bac competent cells, and the recombinant Bacmid was subsequently transfected into insect Sf9 cells. The expressed recombinant Netrin-A was thus purified in the Ni-NTA agarose. This protein evaluation was done using SDS-PAGE and western blot, respectively. Finally, its concentration was calculated with the Bradford assay method. Results: The Bacmid vector structure with Netrin-A was successfully constructed and then expressed as Netrin-A protein in the Sf9 cell lane. The molecular weight of this protein was 52 kDa with 404 amino acids. In the in silico studies, fortunately, we predicted that recombinant LSNetrin-A have Antibacterial activity and without any prion formation risk.This molecule hasa high binding affinity to the Neogenin and a lower affinity to the DCC-specific receptors. Signal peptide located between amino acids 24 and 25. The concentration of Netrin-A recombinant protein was calculated to be 48.8 μg/ml. it was confirmed that the characterized gene in our previous study codes L. sericata Netrin-A enzyme. Conclusions: Successful generation of the recombinant Netrin-A, a secreted protein in L.sericata salivary glands, and because Luciliasericata larvae are used in larval therapy. Therefore, the findings of the present study could be useful to researchers in future studies on wound healing.

Keywords: blowfly, BEVS, gene, immature insect, recombinant protein, Sf9

Procedia PDF Downloads 93

Authors: Manendra Singh Parihar, Sandip Ghosh Chowdhury

Abstract:

Austenitic stainless steels are widely used and give a good combination of properties. When this steel is plastically deformed, a phase transformation of the metastable Face Centred Cubic Austenite to the stable Body Centred Cubic (α’) or to the Hexagonal close packed (ԑ) martensite may occur, leading to the enhancement in the mechanical properties like strength. The work was based on variant selection and corresponding texture analysis for the strain induced martensitic transformation during deformation of the parent austenite FCC phase to form the product HCP and the BCC martensite phases separately, obeying their respective orientation relationships. The automated method for reconstruction of the parent phase orientation using the EBSD data of the product phase orientation is done using the MATLAB and TSL-OIM software. The method of triplets was used which involves the formation of a triplet of neighboring product grains having a common variant and linking them using a misorientation-based criterion. This led to the proper reconstruction of the pre-transformation phase orientation data and thus to its micro structure and texture. The computational speed of current method is better compared to the previously used methods of reconstruction. The reconstruction of austenite from ԑ and α’ martensite was carried out for multiple samples and their IPF images, pole figures, inverse pole figures and ODFs were compared. Similar type of results was observed for all samples. The comparison gives the idea for estimating the correct sequence of the transformation i.e. γ → ε → α’ or γ → α’, during deformation of AISI 304 austenitic stainless steel.

Keywords: variant selection, reconstruction, EBSD, austenitic stainless steel, martensitic transformation

Procedia PDF Downloads 489

Authors: P. G. Romeo

Abstract:

A Lie group is a highly sophisticated structure which is a smooth manifold whose underlying set of elements is equipped with the structure of a group such that the group multiplication and inverse-assigning functions are smooth. This structure was introduced by the Norwegian mathematician So- phus Lie who founded the theory of continuous groups. The Lie groups are well developed and have wide applications in areas including Mathematical Physics. There are several advances and generalizations for Lie groups and Lie groupoids is one such which is termed as a "many-object generalization" of Lie groups. A groupoid is a category whose morphisms are all invertible, obviously, every group is a groupoid but not conversely. Definition 1. A Lie groupoid G ⇒ M is a groupoid G on a base M together with smooth structures on G and M such that the maps α, β: G → M are surjective submertions, the object inclusion map x '→ 1x, M → G is smooth, and the partial multiplication G ∗ G → G is smooth. A bundle is a triple (E, p, B) where E, B are topological spaces p: E → B is a map. Space B is called the base space and space E is called total space and map p is the projection of the bundle. For each b ∈ B, the space p−1(b) is called the fibre of the bundle over b ∈ B. Intuitively a bundle is regarded as a union of fibres p−1(b) for b ∈ B parametrized by B and ’glued together’ by the topology of the space E. A cross-section of a bundle (E, p, B) is a map s: B → E such that ps = 1B. Example 1. Given any space B, a product bundle over B with fibre F is (B × F, p, B) where p is the projection on the first factor. Definition 2. A principal bundle P (M, G, π) consists of a manifold P, a Lie group G, and a free right action of G on P denoted (u, g) '→ ug, such that the orbits of the action coincide with the fibres of the surjective submersion π : P → M, and such that M is covered by the domains of local sections σ: U → P, U ⊆ M, of π. Definition 3. A Lie group bundle, or LGB, is a smooth fibre bundle (K, q, M ) in which each fibre (Km = q−1(m), and the fibre type G, has a Lie group structure, and for which there is an atlas {ψi: Ui × G → KUi } such that each {ψi,m : G → Km}, is an isomorphism of Lie groups. A morphism of LGB from (K, q, M ) to (K′, q′, M′) is a morphism (F, f ) of fibre bundles such that each Fm: Km → K′ is a morphism of Lie groups. In this paper, we will be discussing the Lie groupoid bundles. Here it is seen that to a Lie groupoid Ω on base B there is associated a collection of principal bundles Ωx(B, Ωx), all of which are mutually isomorphic and conversely, associated to any principal bundle P (B, G, p) there is a groupoid called the Ehresmann groupoid which is easily seen to be Lie. Further, some interesting properties of the category of Lie groupoids and bundles will be explored.

Keywords: groupoid, lie group, lie groupoid, bundle

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Authors: Çağan Alevkayali, Şermin Tağil

Abstract:

Determination of soil pH surface distribution in urban areas is substantial for sustainable development. Changes on soil properties occur due to functions on performed in agriculture, industry and other urban functions. Soil pH is important to effect on soil productivity which based on sensitive and complex relation between plant and soil. Furthermore, the spatial variability of soil reaction is necessary to measure the effects of urbanization. The objective of this study was to explore the spatial variation of soil pH quality and the influence factors of human land use on soil Ph around Balikesir City using data for 2015 and Geographic Information Systems (GIS). For this, soil samples were taken from 40 different locations, and collected with the method of "Systematic Random" from the pits at 0-20 cm depths, because anthropologic sourced pollutants accumulate on upper layers of soil. The study area was divided into a grid system with 750 x 750 m. GPS was used to determine sampling locations, and Inverse Distance Weighting (IDW) interpolation technique was used to analyze the spatial distribution of pH in the study area and to predict the variable values of un-exampled places with the help from the values of exampled places. Natural soil acidity and alkalinity depend on interaction between climate, vegetation, and soil geological properties. However, analyzing soil pH is important to indirectly evaluate soil pollution caused by urbanization and industrialization. The result of this study showed that soil pH around the Balikesir City was neutral, in generally, with values were between 6.5 and 7.0. On the other hand, some slight changes were demonstrated around open dump areas and the small industrial sites. The results obtained from this study can be indicator of important soil problems and this data can be used by ecologists, planners and managers to protect soil supplies around the Balikesir City.

Keywords: Balikesir, IDW, GIS, spatial variability, soil pH, urbanization

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Authors: Min Chen, Rubi Gupta

Abstract:

Understanding and predicting stock market movements is a challenging problem. It is believed stock markets are partially driven by public sentiments, which leads to numerous research efforts to predict stock market trend using public sentiments expressed on social media such as Twitter but with limited success. Recently a microblogging website StockTwits is becoming increasingly popular for users to share their discussions and sentiments about stocks and financial market. In this project, we analyze the text content of StockTwits tweets and extract financial sentiment using text featurization and machine learning algorithms. StockTwits tweets are first pre-processed using techniques including stopword removal, special character removal, and case normalization to remove noise. Features are extracted from these preprocessed tweets through text featurization process using bags of words, N-gram models, TF-IDF (term frequency-inverse document frequency), and latent semantic analysis. Machine learning models are then trained to classify the tweets' sentiment as positive (bullish) or negative (bearish). The correlation between the aggregated daily sentiment and daily stock price movement is then investigated using Pearson’s correlation coefficient. Finally, the sentiment information is applied together with time series stock data to predict stock price movement. The experiments on five companies (Apple, Amazon, General Electric, Microsoft, and Target) in a duration of nine months demonstrate the effectiveness of our study in improving the prediction accuracy.

Keywords: machine learning, sentiment analysis, stock price prediction, tweet processing

Procedia PDF Downloads 156

Authors: Thinakar Mani Balusamy, Venkateswaran A. R., Bharat Narasimhan, Ratnakar Kini S., Kani Sheikh M., Prem Kumar K., Pugazhendi Thangavelu, Arun Murugan, Sibi Thooran Karmegam, Radhakrishnan N., Mohammed Noufal, Amit Soni

Abstract:

Background and Aims: The liver is integral to lipid metabolism, and a compromise in its function leads to perturbations in these pathways. In this study, we hope to determine the correlation between CLD severity and its effect on lipid parameters. We also look at the etiology-specific effects on lipid levels. Materials and Methods: This is a retrospective cross-sectional analysis of 250 patients with cirrhosis compared to 250 healthy age and sex-matched controls. Severity assessment of CLD using MELD and Child-Pugh scores was performed and etiological details collected. A questionnaire was used to obtain patient demographic details and lastly, a fasting lipid profile (Total, LDL, HDL cholesterol, Triglycerides and VLDL) was obtained. Results: All components of the lipid profile declined linearly with increasing severity of CLD as determined by MELD and Child-Pugh scores. Lipid levels were clearly lower in CLD patients as compared to healthy controls. Interestingly, preliminary analysis indicated that CLD of different etiologies had differential effects on Lipid profiles. This aspect is under further analysis. Conclusion: All components of the lipid profile were definitely lower in CLD patients as compared to controls and demonstrated an inverse correlation with increasing severity. The utilization of this parameter as a prognosticating aid requires further study. Additionally, preliminary analysis indicates that various CLD etiologies appear to have specific effects on the lipid profile – a finding under further analysis.

Keywords: CLD, cholesterol, HDL, LDL, lipid profile, triglycerides, VLDL

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Authors: E. Er, Y. S. Cheng

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The role of parents and caregivers in their children’s education is pivotal. Parental involvement (PI) is often associated with a range of student outcomes. This includes academic achievements, socioemotional development, adaptive skills, physical fitness and school attendance. This study is the first in Singapore to (1) explore the relationship between parental involvement and student outcomes; (2) determine the effects of family structure and socioeconomic status (SES) on parental involvement and (3) investigate factors that inform involvement in parents of children with specific developmental disabilities. Approval for the study was obtained from Nanyang Technological University’s Institutional Review Board in Singapore. The revised version of a comprehensive theoretical model on parental involvement was used as the theoretical framework in this study. Parents were recruited from a SPED school in Singapore which caters to school-aged children (7 to 21 years old). Pearson’s product moment correlation, analysis of variance and multiple regression analyses were used as statistical techniques in this study. Results indicate that there are significant associations between parental involvement and educational outcomes in students with developmental disabilities. Next, SES has a significant impact on levels of parental involvement. In addition, parents in the current study reported being more involved at home, in school activities and the community, when teachers specifically requested their involvement. Home-based involvement was also predicted by parents’ perceptions of their time and energy, efficacy and beliefs in supporting their child’s education, as well as their children’s invitations to be more involved. An interesting and counterintuitive inverse relationship was found between general school invitations and parental involvement at home. Research findings are further discussed, and suggestions are put forth to increase involvement for this specific group of parents.

Keywords: autism, developmental disabilities, intellectual disabilities, parental involvement, Singapore

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Authors: Swati Bajpai, S. P. K Jena

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Background: There is dramatic increase in the prevalence and severity of overweight in adolescents, raising concerns about their psychosocial and cognitive consequences, thereby indicating the immediate need to understand the effects of increased weight on scholastic performance. Although the body of research is currently limited, available results have identified an inverse relationship between obesity and cognition in adolescents. Aim: to examine the association between increased Body Mass Index in adolescents and their neurocognitive functioning. Methods: A case –control study of 28 subjects in the age group of 11-17 years (14 Males and 14 females) was taken on the basis of main inclusion criteria (Body Mass Index). All of them were randomized to (experimental group: overweight) and (control group: normal weighted). A complete neurocognitive assessment was carried out using validated psychological scales namely, Color Progressive Matrices (to assess intelligence); Bender Visual Motor Gestalt Test (Perceptual motor functioning); PGI-Memory Scale for Children (memory functioning) and Malin’s Intelligence Scale Indian Children (verbal and performance ability). Results: statistical analysis of the results depicted that 57% of the experimental group lack in cognitive abilities, especially in general knowledge (99.1±12.0 vs. 102.8±6.7), working memory (91.5±8.4 vs. 93.1±8.7), concrete ability (82.3±11.5 vs. 92.6±1.7) and perceptual motor functioning (1.5±1.0 vs. 0.3±0.9) as compared to control group. Conclusion: Our investigations suggest that weight gain results, at least in part, from a neurological predisposition characterized by reduced executive function, and in turn obesity itself has a compounding negative impact on the brain. Though, larger sample is needed to make more affirmative claims.

Keywords: adolescents, body mass index, neurocognition, obesity

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Authors: Khuram Nawaz Sadozai, Sonia

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The agriculture sector is deemed more vulnerable to climate change as its variation can directly affect the crop’s productivity, but farmers’ adaptation strategies play a vital role in climate change-agriculture relationship. Therefore, this research has been undertaken to assess the Climate Change impact on wheat productivity and farmers’ adaptability strategies in Khyber Pakhtunkhwa province, Pakistan. The panel dataset was analyzed to gauge the impact of changing climate variables (i.e., temperature, rainfall, and humidity) on wheat productivity from 1985 to 2015. Amid the study period, the fixed effect estimates confirmed an inverse relationship of temperature and rainfall on the wheat yield. The impact of temperature is observed to be detrimental as compared to the rainfall, causing 0.07 units reduction in the production of wheat with 1C upsurge in temperature. On the flip side, humidity revealed a positive association with the wheat productivity by confirming that high humidity could be beneficial to the production of the crop over time. Thus, this study ensures significant nexus between agricultural production and climatic parameters. However, the farming community in the underlying study area has limited knowledge about the adaptation strategies to lessen the detrimental impact of changing climate on crop yield. It is recommended that farmers should be well equipped with training and advanced agricultural management practices under the realm of climate change. Moreover, innovative technologies pertinent to the agriculture system should be encouraged to handle the challenges arising due to variations in climate factors.

Keywords: climate change, fixed effect model, panel data, wheat productivity

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Authors: Rahaf Alasiri, Tarek Alghamdi, Abdullah Zarkan

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Background: Due to measures such as school closure, social distancing, and virtual teaching during the pandemic, primary school children's psychological well-being is greatly affected. These measures have short and long-term consequences on the children's well-being and mental health. Identifying these consequences is important. Aim: This study aimed to evaluate mood and behavior changes in children who attended school virtually. Subjects and methods: This is a cross-sectional study conducted among children and their parents who visited the outpatient clinic. A self-administered questionnaire was given to the parents of children aged between 6 to 14 years. The questionnaire includes socio-demographic characteristics, Conor's modifies scale to assess the attention deficit hyperactivity disorder (ADHD) of children, and the parental stress scale (PSS) to assess the stress symptoms of the parents. Results: Of the 66 surveyed children, 60.6% were aged between 10 to 14 years old, with the female being dominant (77.3%). The most common medical condition was asthma (7.6%), and nearly two-thirds (63.6%) indicated good health conditions during the pandemic. There was a significant inverse correlation observed between ADHD score and PSS score (r=-0.387). No significant differences are in ADHD and PSS scores in relation to the socio-demographic characteristics of the children, including age, gender, and having an associated medical condition (p>0.05). Conclusion: During the pandemic, children who attended virtual classes did not seem to affect even with restrictions. Most children indicated good health conditions during the pandemic. However, it is surprising to know that in spite of children’s high spirits during the pandemic, their parents were seen to have an increased level of stress. Strategies to address parents’ psychological disorders during the pandemic are warranted.

Keywords: children's mood, COVID-19, ADHD, parental stress

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Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager

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This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.

Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties

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Authors: Alaa A. H. Shehada, Eman Abdelnasser Abouhassanein, Reem Mohsen Ali, Joyce J. Moawad, Hiba Bawadi, Abdelhamid Kerkadi

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Background: The association between obesity and micronutrient deficiencies is well documented. Among minerals that have been widely studied: zinc, iron and magnesium. Objectives: This study aims to determine the association between obesity indices and mineral status among Qatari adults. Methods: Secondary data was obtained from Qatar Biobank. 414 healthy Qatari aged 20-50 years old were randomly selected from the database. Anthropometric measurements (WC, Weight, and height), body fat, and mineral status (Fe, Mg, Ca, K, Na) were obtained for all selected participants. Differences in anthropometric measurements and mineral status were analyzed by t-test or ANOVA. Spearman correlation coefficients were determined to assess the association between minerals and anthropometric variables. Statistical significance for the hypothesis tests was set at p <0.05. All statistical analysis was preformed using SPSS software version 23.0. Results: Iron, calcium, and sodium levels decreased with an increase in body mass index. Moreover, only iron showed a significant correlation with waist circumference, and waist to height ratio increased. Additionally, calcium, iron, magnesium, and sodium had a statistically significant negative correlation with total body fat percentage and trunk fat percentage. There were statistically significant negative correlations of anthropometrics with minerals. Conclusion: Body fat and trunk fat percentage had a significant inverse relationship with iron, calcium, sodium, and magnesium, while there was no correlation between body fat or trunk fat percentage with potassium.

Keywords: Qatar biobank, body fat distribution, mineral status, Qatari adults

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Authors: A. Bahmanpour, I. Eames, C. Klettner, A. Dimakopoulos

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We develop a new set of diagnostic tools to analyze inundation into a model district using three-dimensional CFD simulations, with a view to generating a database against which to test simpler models. A three-dimensional model of Oregon city with different-sized groups of building next to the coastline is used to run calculations of the movement of a long period wave on the shore. The initial and boundary conditions of the off-shore water are set using a nonlinear inverse method based on Eulerian spatial information matching experimental Eulerian time series measurements of water height. The water movement is followed in time, and this enables the pressure distribution on every surface of each building to be followed in a temporal manner. The three-dimensional numerical data set is validated against published experimental work. In the first instance, we use the dataset as a basis to understand the success of reduced models - including 2D shallow water model and reduced 1D models - to predict water heights, flow velocity and forces. This is because models based on the shallow water equations are known to underestimate drag forces after the initial surge of water. The second component is to identify critical flow features, such as hydraulic jumps and choked states, which are flow regions where dissipation occurs and drag forces are large. Finally, we describe how future tsunami inundation models should be modified to account for the complex effects of buildings through drag and blocking.Financial support from UCL and HR Wallingford is greatly appreciated. The authors would like to thank Professor Daniel Cox and Dr. Hyoungsu Park for providing the data on the Seaside Oregon experiment.

Keywords: computational fluid dynamics, extreme events, loading, tsunami

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Authors: T. D. Ibragimov, A. R. Imamaliyev, G. M. Bayramov

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Influence of barium titanate particles on electro-optic properties of liquid crystal 4-cyano-4′-pentylbiphenyl (5CB) with positive dielectric anisotropy and the liquid crystalline (LC) mixture Н-37 consisting of 4-methoxybezylidene-4'–butylaniline and 4-ethoxybezylidene-4'–butylaniline with negative dielectric anisotropy was investigated. It was shown that a presence of particles inside 5СВ and H-37 decreased the clearing temperature from 35.2 °С to 32.5°С and from 61.2 oC to 60.1oC, correspondingly. The threshold voltage of the Fredericksz effect became 0.3 V for the BaTiO3-5CB colloid while the beginning of this effect of the pure 5СВ was observed at 2.1 V. Threshold voltage of the Fredericksz effect increased from 2.8 V to up 3.1 V at additive of particles into H-37. A rise time of the BaTiO3-5CB colloid improved while a decay time worsened in comparison with the pure 5CB at all applied voltages. The inverse trends were observed for the H-37 matrix, namely, a rise time worsened and a decay time improved. Among other things, the effect of fast light modulation was studied at application of the rectangular impulse with direct bias to an electro-optical cell with the BaTiO3 particles+5CB and the pure 5CB. At this case, a rise time of the composite worsened, a decay time improved in comparison with the pure 5CB. The pecularities of electrohydrodynamic instability (EHDI) formation was also investigated into the composite with the H-37 matrix. It was found that the voltage of the EHDI formation decreased, a rise time increased and a decay time decreased in comparison with the pure H-37. First of all, experimental results are explained by appearance of local electric fields near the polarized ferroelectric particles at application of external electric field and an existence of the additional obstacles (particles) for movement of ions.

Keywords: liquid crystal, ferroelectric particles, composite, electro-optics

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Authors: Soufiane Fal, Abderahim Aasfar, Ali Ouhssain, Hasnae Choukri, Abelaziz Smouni, Hicham El Arroussi

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Heavy metals contamination is a major environmental concern around the world. It has a harmful impact on plant productivity and poses a serious risk to humans and animals health. In the present study, the effect of Microalgae Crude Extract (MCE) on tomato growth and nutrients uptake exposed to 2 mM Pb2+ and Cd2+ was investigated. In results, 2 mM Pb2+ and Cd2+ showed a significant reduction of tomatobiomass and perturbation in nutrients absorption. Moreover, MCE application in tomato plant exposed to Pb2+ and Cd2+ showed a significant enhancement of biomass compared to tomato plants under Pb2+ and Cd2+. On the other hand, MCE application favoured heavy metals accumulation in root and inhibited their translocation to shoot as phytostabilisation mechanism. Tomato plants showed biochemical responses to Pb2+ and Cd2+ stress with elevation of scavenging enzymes and molecules such as POD, CAT, SOD, Proline, and polyphenols, etc. In addition, the treatment by MCE showed a significant reduction level of the majority of these parameters. Furthermore, the metabolomic analysis revealed a significant change in important metabolites. Pb2+ and Cd2+ showed decrease in SFA and increase of UFA, VLFA, alkanes, alkenes, sterols, which known accumulated as tolerance and resistance mechanism to heavy metal (H.M) stress. However, MCE treatment showed the inverse of these response to return tomato plants to normal state and enhanced tolerance and resistance to heavy metal stress. In the present study, we emphasized that MCE can alleviate H.M stress, enhance tomato plant growth nutrients absorption and improve biochemical responses.

Keywords: microalgae crude extract, heavy metal stress, nutrient uptake, metabolomic analysis, solanum lycopersicum (Tomato), phytostabilisation

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Authors: Reza Karimpour

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Ports play a decisive role in the EU's external and internal trade, as about 74% of imports and exports and 37% of exchanges go through ports. Although ports, especially Deep Sea Shipping (DSS) ports, are integral nodes within multimodal logistic flows, Short Sea Shipping (SSS) and inland waterways are not so well integrated. The automated vessels and supply chain optimisations for sustainable shortsea shipping (MOSES) project aims to enhance the short sea shipping component of the European supply chain by addressing the vulnerabilities and strains related to the operation of large containerships. The MOSES concept can be shortly described as a large containership (mother-vessel) approaching a DSS port (or a large container terminal). Upon her arrival, a combined intelligent mega-system consisting of the MOSES Autonomous tugboat swarm for manoeuvring and the MOSES adapted AutoMoor system. Then, container handling processes are ready to start moving containers to their destination via hinterland connections (trucks and/or rail) or to be shipped to destinations near small ports (on the mainland or island). For the first case, containers are stored in a dedicated port area (Storage area), waiting to be moved via trucks and/or rail. For the second case, containers are stacked by existing port equipment near-dedicated berths of the DSS port. They then are loaded on the MOSES Innovative Feeder Vessel, equipped with the MOSES Robotic Container-Handling System that provides (semi-) autonomous (un) feeding of the feeder. The Robotic Container-Handling System is remotely monitored through a Shore Control Centre. When the MOSES innovative Feeder vessel approaches the small port, where her docking is achieved without tugboats, she automatically unloads the containers using the Robotic Container-Handling System on the quay or directly on trucks. As a result, ports with minimal or no available infrastructure may be effectively integrated with the container supply chain. Then, the MOSES innovative feeder vessel continues her voyage to the next small port, or she returns to the DSS port. MOSES exploitation activity mainly aims to exploit research outcomes beyond the project, facilitate utilisation of the pilot results by others, and continue the pilot service after the project ends. By the mid-lifetime of the project, the exploitation plan introduces the reader to the MOSES project and its key exploitable results. It provides a plan for delivering the MOSES innovations to the market as part of the overall exploitation plan.

Keywords: automated vessels, exploitation, shortsea shipping, supply chain

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Authors: Yepeng Cheng, Yasuhiko Morimoto

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Customer relationship analysis is vital for retail stores, especially for supermarkets. The point of sale (POS) systems make it possible to record the daily purchasing behaviors of customers as an identification point of sale (ID-POS) database, which can be used to analyze customer behaviors of a supermarket. The customer value is an indicator based on ID-POS database for detecting the customer loyalty of a store. In general, there are many supermarkets in a city, and other nearby competitor supermarkets significantly affect the customer value of customers of a supermarket. However, it is impossible to get detailed ID-POS databases of competitor supermarkets. This study firstly focused on the customer value and distance between a customer's home and supermarkets in a city, and then constructed the models based on logistic regression analysis to analyze correlations between distance and purchasing behaviors only from a POS database of a supermarket chain. During the modeling process, there are three primary problems existed, including the incomparable problem of customer values, the multicollinearity problem among customer value and distance data, and the number of valid partial regression coefficients. The improved customer value, Huff’s gravity model, and inverse attractiveness frequency are considered to solve these problems. This paper presents three types of models based on these three methods for loyal customer classification and competitors’ influence analysis. In numerical experiments, all types of models are useful for loyal customer classification. The type of model, including all three methods, is the most superior one for evaluating the influence of the other nearby supermarkets on customers' purchasing of a supermarket chain from the viewpoint of valid partial regression coefficients and accuracy.

Keywords: customer value, Huff's Gravity Model, POS, Retailer

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Authors: Simin Shahvazi, Sepideh Soltani, Seyed Mehdi Ahmadi, Russell J. De Souza, Amin Salehi-Abargouei

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Background and Objectives: Vitamin D has received attention for its potential to disrupt cancer processes such as attenuating cell proliferation and exacerbating differentiation and apoptosis. However, whether there exists a role for vitamin D in the treatment of prostate cancer specifically remains controversial. We systematically review the literature to assess whether supplementation with vitamin D influences PSA response and overall survival in patients with prostate cancer. Methods: We searched PubMed, Scopus, ISI Web of Science and Google scholar from inception through up to 10 September 2017 for both before-and-after and randomized trials that evaluated the effect of vitamin D supplementation on the prostate specific antigen (PSA) response rate in participants with prostate cancer. The DerSimonian and Laird, inverse-weighted random-effects model was used to pool effect estimates from the studies. Heterogeneity and potential publication bias were evaluated. Subgroup analyses were also performed. Results: Twenty-two studies (16 before-after and 6 randomized controlled trials) were found and included in meta-analysis. The analysis on controlled clinical trials revealed that PSA change from baseline [weighted mean difference (WMD) = -1.66 ng/ml, 95%CI: -0.69, 0.36, P= 0.543)], PSA response (RR=1.18, 95%CI: 0.97, 1.45, P=0.104) and mortality rate (risk ratio (RR) = 1.05, 95% CI: 0.81-1.36; P=0.713) was not significantly different between vitamin D supplementation and placebo groups. Single arm trials revealed that vitamin D supplementation had had a modest effect on PSA response rate: 19% of those enrolled had at least a 50% reduction in PSA by the end of treatment (95% CI: 7% to 31%; p=0.002). Conclusion: We found that vitamin D modestly increases the PSA response rate in single arm studies. No effect on serum PSA levels, PSA response and mortality was seen in randomized controlled clinical trials. It does not seem patients with prostate cancer benefit from vitamin D supplementation.

Keywords: mortality, prostatic neoplasms, PSA response, vitamin D

Procedia PDF Downloads 195