Search results for: image dataset

Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

Procedia PDF Downloads 157

Authors: Lucia Billeci, Gennaro Tartarisco, Maurizio Varanini

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Fetal cardiac monitoring by fetal electrocardiogram (fECG) can provide significant clinical information about the healthy condition of the fetus. Despite this potentiality till now the use of fECG in clinical practice has been quite limited due to the difficulties in its measuring. The recovery of fECG from the signals acquired non-invasively by using electrodes placed on the maternal abdomen is a challenging task because abdominal signals are a mixture of several components and the fetal one is very weak. This paper presents an approach for fECG extraction from abdominal maternal recordings, which exploits the characteristics of pseudo-periodicity of fetal ECG. It consists of devising a quality index (fQI) for fECG and of finding the linear combinations of preprocessed abdominal signals, which maximize these fQI (quality index optimization - QIO). It aims at improving the performances of the most commonly adopted methods for fECG extraction, usually based on maternal ECG (mECG) estimating and canceling. The procedure for the fECG extraction and fetal QRS (fQRS) detection is completely unsupervised and based on the following steps: signal pre-processing; maternal ECG (mECG) extraction and maternal QRS detection; mECG component approximation and canceling by weighted principal component analysis; fECG extraction by fQI maximization and fetal QRS detection. The proposed method was compared with our previously developed procedure, which obtained the highest at the Physionet/Computing in Cardiology Challenge 2013. That procedure was based on removing the mECG from abdominal signals estimated by a principal component analysis (PCA) and applying the Independent component Analysis (ICA) on the residual signals. Both methods were developed and tuned using 69, 1 min long, abdominal measurements with fetal QRS annotation of the dataset A provided by PhysioNet/Computing in Cardiology Challenge 2013. The QIO-based and the ICA-based methods were compared in analyzing two databases of abdominal maternal ECG available on the Physionet site. The first is the Abdominal and Direct Fetal Electrocardiogram Database (ADdb) which contains the fetal QRS annotations thus allowing a quantitative performance comparison, the second is the Non-Invasive Fetal Electrocardiogram Database (NIdb), which does not contain the fetal QRS annotations so that the comparison between the two methods can be only qualitative. In particular, the comparison on NIdb was performed defining an index of quality for the fetal RR series. On the annotated database ADdb the QIO method, provided the performance indexes Sens=0.9988, PPA=0.9991, F1=0.9989 overcoming the ICA-based one, which provided Sens=0.9966, PPA=0.9972, F1=0.9969. The comparison on NIdb was performed defining an index of quality for the fetal RR series. The index of quality resulted higher for the QIO-based method compared to the ICA-based one in 35 records out 55 cases of the NIdb. The QIO-based method gave very high performances with both the databases. The results of this study foresees the application of the algorithm in a fully unsupervised way for the implementation in wearable devices for self-monitoring of fetal health.

Keywords: fetal electrocardiography, fetal QRS detection, independent component analysis (ICA), optimization, wearable

Procedia PDF Downloads 283

Authors: Sarono, Hamim Zaky Hadibasyir, dan Ridho Kurniawan

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Estimation of paddy production is one of the areas that can be examined using the techniques of remote sensing and geographic information systems (GIS) in the field of agriculture. The purpose of this research is to know the amount of the paddy production estimation and how remote sensing and geographic information systems (GIS) are able to perform analysis of paddy production estimation in Tegalallang and Payangan Sub district, Bali Province, Indonesia. The method used is the method of land suitability. This method associates a physical parameters which are to be embodied in the smallest unit of a mapping that represents a mapping unit in a particular field and connecting with its field productivity. Analysis of estimated production using standard land suitability from FAO using matching technique. The parameters used to create the land unit is slope (FAO), climate classification (Oldeman), landform (Prapto Suharsono), and soil type. Land use map consist of paddy and non paddy field information obtained from Geo-eye 1 imagery using visual interpretation technique. Landsat image of the Data used for the interpretation of the landform, the classification of the slopes obtained from high point identification with method of interpolation spline, whereas climate data, soil, use secondary data originating from institutions-related institutions. The results of this research indicate Tegallalang and Payangan Districts in known wetland suitability consists of S1 (very suitable) covering an area of 2884,7 ha with the productivity of 5 tons/ha and S2 (suitable) covering an area of 482,9 ha with the productivity of 3 tons/ha. The sum of paddy production estimation as a results in both districts are 31.744, 3 tons in one year.

Keywords: production estimation, paddy, remote sensing, geography information system, land suitability

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Authors: Kristine Kalnica-Dorosenko, Aiga Svede

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Amblyopia or 'lazy eye' is impaired or dim vision without obvious defect or change in the eye. It is often associated with abnormal visual experience, most commonly strabismus, anisometropia or both, and form deprivation. The main task of amblyopia treatment is to ameliorate etiological factors to create a clear retinal image and, to ensure the participation of the amblyopic eye in the visual process. The treatment of amblyopia and eccentric fixation is usually associated with problems in the therapy. Eccentric fixation is present in around 44% of all patients with amblyopia and in 30% of patients with strabismic amblyopia. In Latvia, amblyopia is carefully treated in various clinics, but eccentricity diagnosis is relatively rare. Conflict which has developed relating to the relationship between the visual disorder and the degree of eccentric fixation in amblyopia should to be rethoughted, because it has an important bearing on the cause and treatment of amblyopia, and the role of the eccentric fixation in this case. Visuoscopy is the most frequently used method for determination of eccentric fixation. With traditional visuoscopy, a fixation target is projected onto the patient retina, and the examiner asks to look straight directly at the center of the target. An optometrist then observes the point on the macula used for fixation. This objective test provides clinicians with direct observation of the fixation point of the eye. It requires patients to voluntarily fixate the target and assumes the foveal reflex accurately demarcates the center of the foveal pit. In the end, by having a very simple method to evaluate fixation, it is possible to indirectly evaluate treatment improvement, as eccentric fixation is always associated with reduced visual acuity. So, one may expect that if eccentric fixation in amlyopic eye is found with visuoscopy, then visual acuity should be less than 1.0 (in decimal units). With occlusion or another amblyopia therapy, one would expect both visual acuity and fixation to improve simultaneously, that is fixation would become more central. Consequently, improvement in fixation pattern by treatment is an indirect measurement of improvement of visual acuity. Evaluation of eccentric fixation in the child may be helpful in identifying amblyopia in children prior to measurement of visual acuity. This is very important because the earlier amblyopia is diagnosed – the better the chance of improving visual acuity.

Keywords: amblyopia, eccentric fixation, visual acuity, visuoscopy

Procedia PDF Downloads 161

Authors: Syrine Bassi

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Sound symbolism has been able to give us an exciting new tool to target consumers’ brand perception. It acts on a subconscious level making them less likely to reject the implicit message delivered by the sound of the brand name. Most of the research conducted in the field was focused on the English language as it is the language used for international branding campaigns and global companies. However, more research is examining the sound symbolism in other languages and comparing it to the English language findings. Besides, researchers have been able to study luxury brand names and spot out the patterns used in them to provoke luxury and sophistication. It stands to a reason to connect the luxury brand names and the local language’s sound effects since a considerable number of these brands are promoting the origin of the Maison, therefore, have names in foreign languages. This study was established around the Hungarian luxury brand names. It aims to spot out the patterns used in these names that connect to the previous findings of luxury sound effects and also the differences. We worked with a non-Hungarian speaking sample who had some basic knowledge of the language just to make sure they were able to correctly pronounce the names. The results have shown both similarities and differences when it comes to perceiving luxury based on the brand name. As the Hungarian language can be qualified as a saturated language, consonant wise, it was easy to feed the luxury feeling only by using designers' names, however, some complicated names were too difficult and repulsive to consider as luxurious. On the other hand, oversimplifying some names did not convey the desired image as it was too simple and easy. Overall, some sounds have been proved to be linked to luxury as the literature suggests, the difficulty of pronunciation has also proved effective since it highlights the distant feeling consumers crave when looking for luxury. These results suggest that sound symbolism can set up an aura of luxury when used properly, leveraging each languages’ convenient assets.

Keywords: hungarian language, linguistics, luxury brands, sound symbolism

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Authors: Clesse C., Lighezzolo-Alnot J., De Lavergne S.

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Considered as the most common surgical procedure worldwide, episiotomy can be defined as an incision around the vulva performed to enlarge it, in the aim of preventing the traumatic rupture of the perineum during childbirth. Rather mediatized, this practice raises many questions in the field of mental health, relayed by different users and health professionals. Today, is topicality is moderately hectic since many queries about the prophylactic exercise of episiotomy are subject to a relative consensus, particularly since WHO advocated in 1996 that only 10% of childbirths should involve an episiotomy. This indicator appeared after the publication of numerous results from randomized clinical trials. Unfortunately, these papers seem mostly centered about somatic impacts of episiotomy. From the side of psychological studies, they mostly integrate a major clinical methodological bias, especially considering that every primiparous woman is identical to the others face to the experience of parturition. In the aim to fill this lack of knowledge, we developed a longitudinal research starting in the 7th month of pregnancy and ending one year after delivery. We are studying in a comparative way different possible psychological consequences inherent to the use of episiotomy. To do this, we use a standardized methodology which combines semi-structured clinical interviews (IRMAG, IRMAN ...), free clinical interviews, a projective test (Rorschach) and five questionnaires (QIC, EPDS, CPQ WOMBLSQ4, SF36). Therefore, we can comprehend with shrewdness the question of psychic impacts of episiotomy in a qualitative and quantitative way by comparing it to other obstetric interventions. In this paper, we will present the first results obtained about a population of twenty-two primiparous women by focusing on body image, sexuality, quality of life, depressive affects, post-traumatic stress disorder and investment of the maternal role. Finally, we will consider the different implications and perspectives of this research which could improve the public health policies in the field of perinatal care.

Keywords: assessment, episiotomy, mental health, psychical impacts

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Authors: Jeries Khoury

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The use of legendary, folkloric and religious symbols is one of the most important phenomena in modern Arabic poetry. Interestingly enough, most of the modern Arabic poetry’s pioneers were so fascinated by the biblical symbols and they managed to use many modern techniques to make these symbols adequate for their personal life from one side and fit to their Islamic beliefs from the other. One of the most famous poets to do so was al-Sayya:b. The way he employed one of these symbols ‘job’, the new features he adds to this character and the link between this character and his personal life will be discussed in this study. Besides, the study will examine the influence of al-Sayya:b on another modern poet Saadi Yusuf, who, following al-Sayya:b, used the character of Job in a special way, by mixing its features with al-Sayya:b’s personal features and in this way creating a new mixed character. A semantic, cultural and comparative analysis of the poems written by al-Sayya:b himself and the other poets who evoked the mixed image of al-Sayya:b-Job, can reveal the changes Arab poets made to the original biblical figure of Job to bring it closer to Islamic culture. The paper will make an intensive use of intertextuality idioms in order to shed light on the network of relations between three kinds of texts (indeed three ‘palimpsests’: 1- biblical- the primary text; 2- poetic- al-Syya:b’s secondary version; 3- re-poetic- Sa’di Yusuf’s tertiary version). The bottom line in this paper is that that al-Sayya:b was directly influenced by the dramatic biblical story of Job more than the brief Quranic version of the story. In fact, the ‘new’ character of Job designed by al-Sayya:b himself differs from the original one in many aspects that we can safely say it is the Sayyabian-Job that cannot be found in the poems of any other poets, unless they are evoking the own tragedy of al-Sayya:b himself, like what Saadi Yusuf did.

Keywords: Arabic poetry, intertextuality, job, meter, modernism, symbolism

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Authors: Vishnu Raj, Chockalingam Prathap

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The objective of this study was to explore the impact of variation in the exit annular area on the local flow field features and the flame stability of an annular premixed swirl burner (unconfined) operated with premixed n-butane air mixture at equivalence ratio (ϕ) = 1, 1 bar, and 300K. A swirl burner with an axial swirl generator having a swirl number of 1.5 was used. Three different burner heads were chosen to have the exit area increased from 100%, 160%, and 220% resulting in inner and outer diameters and cross-sectional areas as (1) 10mm&15mm, 98mm2 (2) 17.5mm&22.5mm, 157mm2 and (3) 25mm & 30mm, 216mm2. The bulk velocity and Reynolds number based on the hydraulic diameter and unburned gas properties were kept constant at 12 m/s and 4000. (i) Planar PIV with TiO2 seeding particles and (ii) OH* chemiluminescence were used to measure the velocity fields and reaction zones of the swirl flames at 5Hz, respectively. Velocity fields and the jet spreading rates measured at the isothermal and reactive conditions revealed that the presence of a flame significantly altered the flow field in the radial direction due to the gas expansion. Important observations from the flame measurements were: the height and maximum width of the recirculation bubbles normalized by the hydraulic diameter, and the jet spreading angles for the flames for the three exit area cases were: (a) 4.52, 1.95, 28ᵒ, (b) 6.78, 2.37, 34ᵒ, and (c) 8.73, 2.32, 37ᵒ. The lean blowout was also measured, and the respective equivalence ratios were: 0.80, 0.92, and 0.82. LBO was relatively narrow for the 157mm2 case. For this case, particle image velocimetry (PIV) measurements showed that Turbulent Kinetic Energy and turbulent intensity were relatively high compared to the other two cases, resulting in higher stretch rates and narrower lean blowout (LBO).

Keywords: chemiluminescence, jet spreading rate, lean blowout, swirl flow

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Authors: Almudena Espin Perez, Tyler Risom, Carl Pelz, Isabel English, Robert M. Angelo, Rosalie Sears, Andrew J. Gentles

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Pancreatic ductal adenocarcinoma (PDAC) is one of the most deadly malignancies. The role of the tumor microenvironment (TME) is gaining significant attention in cancer research. Despite ongoing efforts, the nature of the interactions between tumors, immune cells, and stromal cells remains poorly understood. The cell-intrinsic properties that govern cell lineage plasticity in PDAC and extrinsic influences of immune populations require technically challenging approaches due to the inherently heterogeneous nature of PDAC. Understanding the cell lineage plasticity of PDAC will improve the development of novel strategies that could be translated to the clinic. Members of the team have demonstrated that the acquisition of ductal to neuroendocrine lineage plasticity in PDAC confers therapeutic resistance and is a biomarker of poor outcomes in patients. Our approach combines computational methods for deconvolving bulk transcriptomic cancer data using CIBERSORTx and high-throughput single-cell imaging using Multiplexed Ion Beam Imaging (MIBI) to study lineage plasticity in PDAC and its relationship to the infiltrating immune system. The CIBERSORTx algorithm uses signature matrices from immune cells and stroma from sorted and single-cell data in order to 1) infer the fractions of different immune cell types and stromal cells in bulked gene expression data and 2) impute a representative transcriptome profile for each cell type. We studied a unique set of 300 genomically well-characterized primary PDAC samples with rich clinical annotation. We deconvolved the PDAC transcriptome profiles using CIBERSORTx, leveraging publicly available single-cell RNA-seq data from normal pancreatic tissue and PDAC to estimate cell type proportions in PDAC, and digitally reconstruct cell-specific transcriptional profiles from our study dataset. We built signature matrices and optimized by simulations and comparison to ground truth data. We identified cell-type-specific transcriptional programs that contribute to cancer cell lineage plasticity, especially in the ductal compartment. We also studied cell differentiation hierarchies using CytoTRACE and predict cell lineage trajectories for acinar and ductal cells that we believe are pinpointing relevant information on PDAC progression. Collaborators (Angelo lab, Stanford University) has led the development of the Multiplexed Ion Beam Imaging (MIBI) platform for spatial proteomics. We will use in the very near future MIBI from tissue microarray of 40 PDAC samples to understand the spatial relationship between cancer cell lineage plasticity and stromal cells focused on infiltrating immune cells, using the relevant markers of PDAC plasticity identified from the RNA-seq analysis.

Keywords: deconvolution, imaging, microenvironment, PDAC

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Authors: Iman Shabanzadeh

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The economic growth and the special model of development in China have caused sensitivity in the public opinion of the world regarding the nature of this growth and development. In this regard, the Chinese have tried to put an end to such alarming procedures by using all the tools at their disposal and seek to present a peaceful and cooperative image of themselves. In this way, one of the most important diplomatic tools that Beijing has used to reduce the concerns caused by the Threat Theory has been the use of soft power resources and its tools in its development policies. This article begins by analyzing the concept of soft power and examining its foundations in international relations, and continues to examine the components of soft power in its Chinese version. The main purpose of the article is to figure out about the position of West Asia in China's soft power strategy and resources China use to achieve its goals in this region. In response to the main question, the paper's hypothesis is that soft power in its Chinese version had significant differences from Joseph Nye's original idea. In fact, the Chinese have imported the American version of soft power and adjusted, strengthened and, in other words, internalized it with their abilities, capacities and political philosophy. Based on this, China's software presence in West Asia can be traced in three areas. The first source of China's soft power in this region of West Asia is cultural in nature and is realized through strategies such as "use of educational tools and methods", "media methods" and "tourism industry". The second source is related to political soft power, which is applied through the policy of "balance of influence" and the policy of "mediation" and relying on the "ideological foundations of Confucianism". The third source also refers to China's economic soft power and is realized through three tools: "energy exchanges", "foreign investments" and "Belt-Road initiative". The research method of this article is descriptive-analytical.

Keywords: soft power, cooperative power, china, west asia

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Authors: Olga Bernikova, Oleg Redkin

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Islamic Studies and the Arabic language are indivisible from each other starting from the appearance of Islam and formation of the Classical language. The present paper demonstrates correlation among linguistics and religion in historical perspective with regard to peculiarities of the Arabic language which distinguish it from the other prophetic languages. Islamic Studies and Linguistics are indivisible from each other starting from the invent of Islam and formation of the Classical language. In historical perspective, the Arabic language has been and remains a tool for the expression of Islamic rhetoric being a prophetic language. No other language in the world has preserved its stability for more than 14 centuries. Islam is considered to be one of the most important factors which secure this stability. The analysis and study of the text of Qurʾān are of special importance for those who study Islamic civilization, its role in the destinies of the mankind, its values and virtues. Without understanding of the polyphony of this sacred text, indivisible unity of its form and content it is impossible to understand social developments both in the present and the past. Since the first years of Islam Qurʾān had been in the center of attention of Muslim scholars, and in the center of attention of theologians, historians, philologists, jurists, mathematicians. Only quite recently it has become an object of analysis of the specialists of computer technologies. In Arabic and Islamic studies mediaeval texts i.e. textual documents are considered the main source of information. Hence the analysis of the multiplicity of various texts and finding of interconnections between them help to set scattered fragments of the riddle into a common and eloquent picture of the past, which reflects the state of the society on certain stages of its development. The text of the Qurʾān like any other phenomenon is a multifaceted object that should be studied from different points of view. As a result, this complex study will allow obtaining a three-dimensional image rather than a flat picture alone.

Keywords: Arabic, Islamic studies, linguistics, religion

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Authors: Muhammad Nasar-u-Minallah, Dagmar Haase, Salman Qureshi

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Rapid urbanization significantly change land use, urban nature, land surface vegetation cover, and heat distribution, leading to the formation of urban heat island (UHI) effect and affecting the healthy growth of cities and the comfort of human living style. Past information and present changes in Land Surface Temperature (LST) and urban landscapes could be useful to geographers, environmentalists, and urban planners in an attempt to shape the urban development process and mitigate the effects of urban heat islands (UHI). This study aims at using Satellite Remote Sensing (SRS) and GIS techniques to develop an approach for assessing the urban nature and UHI effects in Lahore, Pakistan. The study employed the Radiative Transfer Method (RTM) in estimating LST to assess the SUHI effect during the interval of 20 years (2000-2020). The assessment was performed by the available Landsat 7/ETM+ and Landsat 8/OIL_TIRs data for the years 2000, 2010, and 2020 respectively. Pearson’s correlation and normalized mutual information were applied to investigate the relationship between green space characteristics and LST. The result of this work revealed that the influence of urban heat island is not always at the city centers but sometimes in the outskirt where a lot of development activities were going on towards the direction of expansion of Lahore, Pakistan. The present study explores the usage of image processing and spatial analysis in the drive towards achieving urban greening of Lahore and a sustainable urban environment in terms of urban planning, policy, and decision making and promoting the healthy and sustainable urban environment of the city.

Keywords: urban nature, urban heat islands, urban green space, land use, Lahore

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Authors: Akintunde Alo

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The incessant encroachments into the forest ecosystem by the farmers and local contractors constitute a major threat to the conservation of genetic resources and biodiversity in Nigeria. To propose a viable monitoring system, this study employed Geographic Information System (GIS) technology to assess the changes that occurred for a period of five years (between 2011 and 2016) in Ikere forest reserve. Landsat imagery of the forest reserve was obtained. For the purpose of geo-referencing the acquired satellite imagery, ground-truth coordinates of some benchmark places within the forest reserve was relied on. Supervised classification algorithm, image processing, vectorization and map production were realized using ArcGIS. Various land use systems within the forest ecosystem were digitized into polygons of different types and colours for 2011 and 2016, roads were represented with lines of different thickness and colours. Of the six land-use delineated, the grassland increased from 26.50 % in 2011 to 45.53% in 2016 of the total land area with a percentage change of 71.81 %. Plantations of Gmelina arborea and Tectona grandis on the other hand reduced from 62.16 % in 2011 to 27.41% in 2016. The farmland and degraded land recorded percentage change of about 176.80 % and 8.70 % respectively from 2011 to 2016. Overall, the rate of deforestation in the study area is on the increase and becoming severe. About 72.59% of the total land area has been converted to non-forestry uses while the remnant 27.41% is occupied by plantations of Gmelina arborea and Tectona grandis. Interestingly, over 55 % of the plantation area in 2011 has changed to grassland, or converted to farmland and degraded land in 2016. The rate of change over time was about 9.79 % annually. Based on the results, rapid actions to prevail on the encroachers to stop deforestation and encouraged re-afforestation in the study area are recommended.

Keywords: land use change, forest reserve, satellite imagery, geographical information system

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Authors: Mahesh Kumar Jat, Manisha Choudhary

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Rapid population and economic growth resulted in changes in large-scale land use land cover (LULC) changes. Changes in the biophysical properties of the Earth's surface and its impact on climate are of primary concern nowadays. Different approaches, ranging from location-based relationships or modelling earth surface - atmospheric interaction through modelling techniques like surface energy balance (SEB) have been used in the recent past to examine the relationship between changes in Earth surface land cover and climatic characteristics like temperature and precipitation. A remote sensing-based model i.e., Surface Energy Balance Algorithm for Land (SEBAL), has been used to estimate the surface heat fluxes over Mahi Bajaj Sagar catchment (India) from 2001 to 2020. Landsat ETM and OLI satellite data are used to model the SEB of the area. Changes in observed precipitation and temperature, obtained from India Meteorological Department (IMD) have been correlated with changes in surface heat fluxes to understand the relative contributions of LULC change in changing these climatic variables. Results indicate a noticeable impact of LULC changes on climatic variables, which are aligned with respective changes in SEB components. Results suggest that precipitation increases at a rate of 20 mm/year. The maximum and minimum temperature decreases and increases at 0.007 ℃ /year and 0.02 ℃ /year, respectively. The average temperature increases at 0.009 ℃ /year. Changes in latent heat flux and sensible heat flux positively correlate with precipitation and temperature, respectively. Variation in surface heat fluxes influences the climate parameters and is an adequate reason for climate change. So, SEB modelling is helpful to understand the LULC change and its impact on climate.

Keywords: remote sensing, GIS, object based, classification

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Authors: Linyi Fan, C.J. Schumaker

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Background: Biomedical efforts to treat Alzheimer’s disease (AD) have typically produced mixed to poor results, while more lifestyle-focused treatments such as exercise may fare better than existing biomedical treatments. A few promising studies have indicated that activities of daily life (ADL) may be a useful way of predicting AD. However, the existing cross-sectional studies fail to show how functional-related issues such as ADL in early years predict AD and how social factors influence health either in addition to or in interaction with individual risk factors. This study would helpbetterscreening and early treatments for the elderly population and healthcare practice. The findings have significance academically and practically in terms of creating positive social change. Methodology: The purpose of this quantitative historical, correlational study was to examine the relationship between early years’ ADL and the development of AD in later years. The studyincluded 4,526participantsderived fromRAND HRS dataset. The Health and Retirement Study (HRS) is a longitudinal household survey data set that is available forresearchof retirement and health among the elderly in the United States. The sample was selected by the completion of survey questionnaire about AD and dementia. The variablethat indicates whether the participant has been diagnosed with AD was the dependent variable. The ADL indices and changes in ADL were the independent variables. A four-step multilevel regression model approach was utilized to address the research questions. Results: Amongst 4,526 patients who completed the AD and dementia questionnaire, 144 (3.1%) were diagnosed with AD. Of the 4,526 participants, 3,465 (76.6%) have high school and upper education degrees,4,074 (90.0%) were above poverty threshold. The model evaluatedthe effect of ADL and change in ADL on onset of AD in late years while allowing the intercept of the model to vary by level of education. The results suggested that the only significant predictor of the onset of AD was changes in early years’ ADL (b = 20.253, z = 2.761, p < .05). However, the result of the sensitivity analysis (b = 7.562, z = 1.900, p =.058), which included more control variables and increased the observation period of ADL, are not supported this finding. The model also estimated whether the variances of random effect vary by Level-2 variables. The results suggested that the variances associated with random slopes were approximately zero, suggesting that the relationship between early years’ ADL were not influenced bysociodemographic factors. Conclusion: The finding indicated that an increase in changes in ADL leads to an increase in the probability of onset AD in the future. However, this finding is not support in a broad observation period model. The study also failed to reject the hypothesis that the sociodemographic factors explained significant amounts of variance in random effect. Recommendations were then made for future research and practice based on these limitations and the significance of the findings.

Keywords: alzheimer’s disease, epidemiology, moderation, multilevel modeling

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Authors: Ammarah Irum, Muhammad Ali Tahir

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Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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Authors: Krešimir Begović, Miloš Rydval, Jan Tumajer, Kristyna Svobodová, Thomas Langbehn, Yumei Jiang, Vojtech Čada, Vaclav Treml, Ryszard Kaczka, Miroslav Svoboda

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Environmental changes have increased the frequency and intensity of climatic extremes, particularly hotter droughts, leading to altered tree growth patterns and multi-year lags in tree recovery. The effects of shifting climatic conditions on tree growth are inhomogeneous across species’ natural distribution ranges, with large spatial heterogeneity and inter-population variability, but generally have significant consequences for contemporary forest dynamics and future ecosystem functioning. Despite numerous studies on the impacts of regional drought effects, large uncertainties remain regarding the mechanistic basis of drought legacy effects on wood formation and the ability of individual species to cope with increasingly drier growing conditions and rising year-to-year climatic variability. To unravel the complexity of climate-growth interactions and assess species-specific responses to severe droughts, we combined forward modeling of tree growth (VS-lite model) with correlation analyses against climate (temperature, precipitation, and the SPEI-3 moisture index) and growth responses to extreme drought events from multiple tree-ring parameters (tree-width and blue intensity parameters). We used an extensive dataset with over 1000 tree-ring samples from 23 nature forest reserves across an altitudinal range in Czechia and Slovakia. Our results revealed substantial spatiotemporal variability in growth responses to summer season temperature and moisture availability across species and tree-ring parameters. However, a general trend of increasing spring moisture-growth sensitivity in recent decades was observed in the Scots pine mountain forests and lowland forests of both species. The VS-lite model effectively captured nonstationary climate-growth relationships and accurately estimated high-frequency growth variability, indicating a significant incidence of regional drought events and growth reductions. Notably, growth reductions during extreme drought years and discrete legacy effects identified in individual wood components were most pronounced in the lowland forests. Together with the observed growth declines in recent decades, these findings suggest an increasing vulnerability of Norway spruce and Scots pine in dry lowlands under intensifying climatic constraints.

Keywords: dendroclimatology, Vaganova–Shashkin lite, conifers, central Europe, drought, blue intensity

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Authors: Aruna Bommareddi

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The journey of the novel is well examined in Indian academia as an offshoot of the novel in English. There have been many attempts to understand aspects of the early novel in India which shared a commonality with the English novel. The regional novel has had an entirely different trajectory which is mapped in the paper. The main focus of the paper would be to look at the historical emergence of the genre of the regional novel in Indian Literatures with specific reference to Kannada, Hindi, and Bengali. The selection of these languages is guided not only by familiarity with these languages as also based on the significance that these languages enjoy in the sub-continent and for the emergence of the regional novel as a specific category in these languages. The regional novels under study are Phaneeswaranath Renu’s Maila Anchal, Tarashankar Bandopadhyaya’s Ganadevata, and Kuvempu’s House of Kanuru for exploration of the themes of its emergence and some aspects of the regional novel common to and different from each other. The paper would explore the various movements that have shaped the genre regional novel in these Literatures. Though Phaneeswarnath Renu’s Maila Anchal is published in 1956, the novel is set in pre-Independent India and therefore shares a commonality of themes with the other two novels, House of Kanuru and Ganadevata. All three novels explore themes of superstition, ignorance, poverty, and the interventions of educated youth to salvage the crises in these backward regional worlds. In fact, it was Renu who assertively declared that he was going to write a regional novel and hence the tile of the first regional novel in Hindi is Maila Anchal meaning the soiled border. In Hindi, anchal also means the region therefore, the title is suggestive of a dirty region as well. The novel exposes the squalor, ignorance, and the conflict ridden life of the village or region as opposed to the rosy image of the village in literature. With this, all such novels which depicted conflicts of the region got recognized as regional novels even though they may have been written prior to Renu’s declaration. All three novels under study succeed in bringing out the complexity of rural life at a given point of time in its history.

Keywords: bengali, hindi, kannada, regional novel, telugu

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Authors: Daniel R. dos Santos, Mateus S. Maldonado, Estevão J. R. Batista

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The military commanders increasingly dependent on spatial awareness, as knowing where enemy are, understanding how war battle scenarios change over time, and visualizing these trends in ways that offer insights for decision-making. Thanks to advancements in geospatial technologies and artificial intelligence algorithms, the commanders are now able to modernize military operations on a universal scale. Thus, geovisualisation has become an essential asset in the defense sector. It has become indispensable for better decisionmaking in dynamic/temporal scenarios, operation planning and management for the war field, situational awareness, effective planning, monitoring, and others. For example, a 3D visualization of war field data contributes to intelligence analysis, evaluation of postmission outcomes, and creation of predictive models to enhance decision-making and strategic planning capabilities. However, old-school visualization methods are slow, expensive, and unscalable. Despite modern technologies in generating 3D point clouds, such as LIDAR and stereo sensors, monocular depth values based on deep learning can offer a faster and more detailed view of the environment, transforming single images into visual information for valuable insights. We propose a dedicated monocular depth reconstruction approach via deep learning techniques for 3D geovisualisation of satellite images. It introduces scalability in terrain reconstruction and data visualization. First, a dataset with more than 7,000 satellite images and associated digital elevation model (DEM) is created. It is based on high resolution optical and radar imageries collected from Planet and Copernicus, on which we fuse highresolution topographic data obtained using technologies such as LiDAR and the associated geographic coordinates. Second, we developed an imagery-DEM fusion strategy that combine feature maps from two encoder-decoder networks. One network is trained with radar and optical bands, while the other is trained with DEM features to compute dense 3D depth. Finally, we constructed a benchmark with sparse depth annotations to facilitate future research. To demonstrate the proposed method's versatility, we evaluated its performance on no annotated satellite images and implemented an enclosed environment useful for Geovisualisation applications. The algorithms were developed in Python 3.0, employing open-source computing libraries, i.e., Open3D, TensorFlow, and Pythorch3D. The proposed method provides fast and accurate decision-making with GIS for localization of troops, position of the enemy, terrain and climate conditions. This analysis enhances situational consciousness, enabling commanders to fine-tune the strategies and distribute the resources proficiently.

Keywords: depth, deep learning, geovisualisation, satellite images

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Authors: Vaishali Joshi, Pallav Joshi

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Environment concern has become an important topic and continues to acquire more popularity in the coming scenario. We all are exposed to messages daily, which encourage us to involve in green behavior. Factors such as Global Warming, Climate change are creating a big buzz amongst the people. Realizing this, many firms/companies are adopting the bright way of making profit along with creating a brand image, by going green. These firms/companies persuade consumers to use purchase eco-friendly products for the benefit of the environment and the society. In such scenario, it becomes very essential for such firms/companies to approach the customers in a better way. In other words, we can say that marketing approach plays a crucial role for such firm/companies. Hence in this research study, we have tried to create a marketing approach for the firms/companies for selling the eco-friendly apparels. We have studied the hypothetical apparel brand who has taken a green initiative of making their products eco-friendly. We have named this hypothetical brand as “Go-Green”. By taking this hypothetical brand we have studied about how this brand can achieve better marketing approach. In particular, we have studied the four types of print advertisements of this brand as follows :(i) print advertisement showing only eco-friendly apparel (ii) print advertisement showing eco-friendly apparel labeled with eco-label (iii) print advertisement showing eco-friendly apparel along with information about the benefit of the featured apparel and (iv) print advertisement showing eco-friendly apparel with both eco-label and information about the benefit of the featured apparel. The conclusion of this research suggest that respondents more positively evaluate the print advertisement of eco-friendly apparel labeled with eco-labels and information about the benefit of the featured apparel, compared by other three print advertisement. Moreover, in this research study, we have studied environment knowledge, as the moderating factor affecting the consumer green purchase behavior.

Keywords: eco-friendly apparel, print advertisement, eco-label, environment knowledge

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Authors: Aamir Hasan, Subhash Mishra

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The purpose of the study was to determine the key drivers which influence the shopping behavior of the customers in the retail store. In today‟s competitive world with increasing number of retail stores, the retailers need to be more customer oriented. Retail has changed and expanded in all lines of business, be it apparel,jewelry, footwear, groceries etc. The modern consumer is posing a challenging task for the Indian retailer. More aware, more confident and much more demanding, therefore the retailers are looking for ways to deliver better consumer value and to increase consumer purchase intention. Retailers tend to differentiate themselves by making their service easier to consumers. The study aims to study the key drivers that can influence shopping behavior in retail store. A survey (store intercept) method was employed to elicit primary information from 300 shoppers in different retail stores of Lucknow. The findings reveal the factors that play a greater role in influencing the shopping behavior of customers in retail store. As such, a survey of retail store customers‟ attitude towards reduced price, sales promotion, quality of the products, proximity to the home, customer service, store atmospherics were analyzed to identify the key drivers influencing shopping behavior in retail store. A questionnaire based on a five-item Likert scale, as well as random sampling, was employed for data collection. Data analysis was accomplished using SPSS software. The paper has found shopping experience, store image and value for money as three important variable out of which shopping experience emerged as a dominant factor which influences the consumer's shopping behavior in the retail store. Since the research has established empirical evidences in determining the key drivers which influences the shopping behavior of the customers in the retail store, it serves as a foundation for a deeper probe into the shopping behavior of the customers in the retail store research domain in the Indian context.

Keywords: retail, shopping, customers, questionnaire

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Authors: Keivan Amirbagheri, Ana Nuñez-Carballosa, Laura Guitart-Tarrés

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Over the last couple of decades, enterprises have begun to accept the need for environmental management and have started to implement environmental management programs to compete in the markets. The implementation of green supply chain management (GSCM) practices can provide valuable opportunities to improve firm performance. Through the prior investigations, the ascending tendency of the numbers of published papers in the field of green supply chain management practices has been reported and it shows the high interest level of the authors to work in this area. Besides, there is still a gap to study more about the relationship of GSCM to the organizational performance (OP). So, the purpose of this research is to study the practices related to green supply chain management that influence the results of the company as an organizational performance. Based on our previous works, from one part we have collected these GSCM practices (planning, operational, and communication practices) and classified them through conducting some literature reviews to analyze their effects on the OP’s factors (balanced scorecard’s perspectives). To do so we design a case study methodology through semi-structured interviews and secondary data from some multinational well-known companies based in Spain. The cases have been selected with the criterion of trying to collect members of the entire supply chain to have a vision as global as possible. The results report the considerable influence of green supply chain management practices on the organizational performance of the companies of the study. In addition, they represent that the implementation of green supply chain management practices especially in a long-term perspective can be economically justified. From the point of view of the personal, they feel better about being a member of this type of company that has been structured on environmental issues. Also, for these companies, the image that has been created by the implementation of these practices helps them to facilitate their marketing program.

Keywords: green supply chain management, organizational performance, case study, Spain

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Authors: Shang-Yu Chiang, Yu-Shan Tsai, Shih-Hsien Sung, Chung-Ming Lo

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Mitral regurgitation (MR) is a heart disorder which the mitral valve does not close properly when the heart pumps out blood. MR is the most common form of valvular heart disease in the adult population. The diagnostic echocardiographic finding of MR is straightforward due to the well-known clinical evidence. In the determination of MR severity, quantification of sonographic findings would be useful for clinical decision making. Clinically, the vena contracta is a standard for MR evaluation. Vena contracta is the point in a blood stream where the diameter of the stream is the least, and the velocity is the maximum. The quantification of vena contracta, i.e. the vena contracta width (VCW) at mitral valve, can be a numeric measurement for severity assessment. However, manually delineating the VCW may not accurate enough. The result highly depends on the operator experience. Therefore, this study proposed an automatic method to quantify VCW to evaluate MR severity. Based on color Doppler ultrasound, VCW can be observed from the blood flows to the probe as the appearance of red or yellow area. The corresponding brightness represents the value of the flow rate. In the experiment, colors were firstly transformed into HSV (hue, saturation and value) to be closely align with the way human vision perceives red and yellow. Using ellipse to fit the high flow rate area in left atrium, the angle between the mitral valve and the ultrasound probe was calculated to get the vertical shortest diameter as the VCW. Taking the manual measurement as the standard, the method achieved only 0.02 (0.38 vs. 0.36) to 0.03 (0.42 vs. 0.45) cm differences. The result showed that the proposed automatic VCW extraction can be efficient and accurate for clinical use. The process also has the potential to reduce intra- or inter-observer variability at measuring subtle distances.

Keywords: mitral regurgitation, vena contracta, color doppler, image processing

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Authors: Monika Michałowska, Anna Alichniewicz

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Detrimental outcomes of advanced maternal age on the chances of fertilization, pregnancy as well as mother and fetus health have been recognized for several decades. It seemed interesting to investigate whether there is a comparable awareness of the detrimental influence on the reproductive outcomes of late fatherhood, given that it has been already ten years since an intense and growing interest concerning later-age fatherhood commenced in medical research. To address that issue a two-step research was done. First, we performed a review of the subject literature to answer the following questions: 1) What age is defined as advanced?; 2) Is the same age defined as advanced in both genders?; 3) What terminology concerning age issues is used?; 4) Is the same age terminology used regarding both genders? The second part of our studies was devoted to the views of medical students. This part of our research comprised both quantitative and qualitative studies. Opinions of medical students in one of the Polish medical universities on several issues connected with assisted reproduction technology (ART) were gathered: 1) students’ attitude to in vitro fertilization (IVF) for women over 40 and for postmenopausal women; 2) students’ attitude to late fatherhood; 3) students’ reasoning given against acceptability of IVF procedure for all of these group of patients involved in an IVF procedure. Our analyses revealed that: First, there is no universal definition of the term ‘advanced age’; secondly, there is a general tendency to adopt different age limits depending on whether they refer to maternal or paternal age, but no justification is provided by the researchers explaining why they set different age limits for women and men; thirdly, the image of postponed fatherhood stands in stark contrast to postponed motherhood - while postponed fatherhood is frequently portrayed as a reasonable and conscious decision enabling a stable family environment for a child, the reasonableness of postponed motherhood is often questioned; finally, the bias regarding maternal versus paternal age is deeply embedded in medical students’ attitude to IVF for women over 40 and for postmenopausal women.

Keywords: gender stereotypes, reproductive medicine, maternal age, paternal age

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Authors: Violetta Cataldo, Renata Savy, Simona Sbranna

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Background: Foreign Language Learning (FLL) is characterised by prosodic transfer phenomena regarding pitch accents placement, intonation patterns, and pitch range excursion from the learners’ mother tongue to their Foreign Language (FL) which suggests that the gradual development of general linguistic competence in FL does not imply an equally correspondent improvement of the prosodic competence. Topic: The present study aims to monitor the development of prosodic competence of learners of Italian and German throughout the FLL process. The primary object of this study is to investigate the intonational features and the f₀ range excursion of Italian and German from a cross-linguistic perspective; analyses of native speakers’ productions point out the differences between this pair of languages and provide models for the Target Language (TL). A following crosscheck compares the L2 productions in Italian and German by non-native speakers to the Target Language models, in order to verify the occurrence of prosodic interference phenomena, i.e., type, degree, and modalities. Methodology: The subjects of the research are university students belonging to two groups: Italian native speakers learning German as FL and German native speakers learning Italian as FL. Both of them have been divided into three subgroups according to the FL proficiency level (beginners, intermediate, advanced). The dataset consists of wh-questions placed in situational contexts uttered in both speakers’ L1 and FL. Using a phonetic approach, analyses have considered three domains of intonational contours (Initial Profile, Nuclear Accent, and Terminal Contour) and two dimensions of the f₀ range parameter (span and level), which provide a basis for comparison between L1 and L2 productions. Findings: Results highlight a strong presence of prosodic transfer phenomena affecting L2 productions in the majority of both Italian and German learners, irrespective of their FL proficiency level; the transfer concerns all the three domains of the contour taken into account, although with different modalities and characteristics. Currently, L2 productions of German learners show a pitch span compression on the domain of the Terminal Contour compared to their L1 towards the TL; furthermore, German learners tend to use lower pitch range values in deviation from their L1 when improving their general linguistic competence in Italian FL proficiency level. Results regarding pitch range span and level in L2 productions by Italian learners are still in progress. At present, they show a similar tendency to expand the pitch span and to raise the pitch level, which also reveals a deviation from the L1 possibly in the direction of German TL. Conclusion: Intonational features seem to be 'resistant' parameters to which learners appear not to be particularly sensitive. By contrast, they show a certain sensitiveness to FL pitch range dimensions. Making clear which the most resistant and the most sensitive parameters are when learning FL prosody could lay groundwork for the development of prosodic trainings thanks to which learners could finally acquire a clear and natural pronunciation and intonation.

Keywords: foreign language learning, German, Italian, L2 prosody, pitch range, transfer

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Authors: Elham Koohikerade, Silvio Jose Gumiere

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In this research, irrigation is highlighted as crucial for improving both the yield and quality of ‎potatoes due to their high sensitivity to soil moisture changes. The study presents a hybrid Long ‎Short-Term Memory (LSTM) model aimed at optimizing irrigation scheduling in potato fields in ‎Quebec City, Canada. This model integrates model-based and satellite-derived datasets to simulate ‎soil moisture content, addressing the limitations of field data. Developed under the guidance of the ‎Food and Agriculture Organization (FAO), the simulation approach compensates for the lack of direct ‎soil sensor data, enhancing the LSTM model's predictions. The model was calibrated using indices ‎like Surface Soil Moisture (SSM), Normalized Vegetation Difference Index (NDVI), Enhanced ‎Vegetation Index (EVI), and Normalized Multi-band Drought Index (NMDI) to effectively forecast ‎soil moisture reductions. Understanding soil moisture and plant development is crucial for assessing ‎drought conditions and determining irrigation needs. This study validated the spectral characteristics ‎of vegetation and soil using ECMWF Reanalysis v5 (ERA5) and Moderate Resolution Imaging ‎Spectrometer (MODIS) data from 2019 to 2023, collected from agricultural areas in Dolbeau and ‎Peribonka, Quebec. Parameters such as surface volumetric soil moisture (0-7 cm), NDVI, EVI, and ‎NMDI were extracted from these images. A regional four-year dataset of soil and vegetation moisture ‎was developed using a machine learning approach combining model-based and satellite-based ‎datasets. The LSTM model predicts soil moisture dynamics hourly across different locations and ‎times, with its accuracy verified through cross-validation and comparison with existing soil moisture ‎datasets. The model effectively captures temporal dynamics, making it valuable for applications ‎requiring soil moisture monitoring over time, such as anomaly detection and memory analysis. By ‎identifying typical peak soil moisture values and observing distribution shapes, irrigation can be ‎scheduled to maintain soil moisture within Volumetric Soil Moisture (VSM) values of 0.25 to 0.30 ‎m²/m², avoiding under and over-watering. The strong correlations between parcels suggest that a ‎uniform irrigation strategy might be effective across multiple parcels, with adjustments based on ‎specific parcel characteristics and historical data trends. The application of the LSTM model to ‎predict soil moisture and vegetation indices yielded mixed results. While the model effectively ‎captures the central tendency and temporal dynamics of soil moisture, it struggles with accurately ‎predicting EVI, NDVI, and NMDI.‎

Keywords: irrigation scheduling, LSTM neural network, remotely sensed indices, soil and vegetation ‎monitoring

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Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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Authors: Hiroyuki Aoki, Toru Asada, Tomomi Tanii

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The properties of a spin-cast film of a polymer material are different from those in the bulk material because the polymer chains are frozen in an un-equilibrium state due to the rapid evaporation of the solvent. However, there has been little information on the un-equilibrated conformation and dynamics in a spin-cast film at the single chain level. The real-space observation of individual chains would provide direct information to discuss the morphology and dynamics of single polymer chains. The recent development of super-resolution fluorescence microscopy methods allows the conformational analysis of single polymer chain. In the current study, the conformation of a polymer chain in a spin-cast film by the super-resolution microscopy. Poly(methyl methacrylate) (PMMA) with the molecular weight of 2.2 x 10^6 was spin-cast onto a glass substrate from toluene and chloroform. For the super-resolution fluorescence imaging, a small amount of the PMMA labeled by rhodamine spiroamide dye was added. The radius of gyration (Rg) was evaluated from the super-resolution fluorescence image of each PMMA chain. The mean-square-root of Rg was 48.7 and 54.0 nm in the spin-cast films prepared from the toluene and chloroform solutions, respectively. On the other hand, the chain dimension in a bulk state (a thermally annealed 10- μm-thick sample) was observed to be 43.1 nm. This indicates that the PMMA chain in the spin-cast film takes an expanded conformation compared to the unperturbed chain and that the chain dimension is dependent on the solvent quality. In a good solvent, the PMMA chain has an expanded conformation by the excluded volume effect. The polymer chain is frozen before the relaxation from an un-equilibrated expanded conformation to an unperturbed one by the rapid solvent evaporation.

Keywords: chain conformation, polymer thin film, spin-coating, super-resolution optical microscopy

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Authors: Sahar Rakhshan, Simonetta Geninatti Crich, Diego Alberti, Rachele Stefania

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The combination of imaging and therapeutic agents in the same smart nanoparticle is a promising option to perform a minimally invasive imaging guided therapy. In this study, Low density lipoproteins (LDL), one of the most attractive biodegradable and biocompatible nanoparticles, were used for the simultaneous delivery of Paclitaxel (PTX), a hydrophobic antitumour drug and an amphiphilic contrast agent, Gd-AAZTA-C17, in B16-F10 melanoma cell line. These cells overexpress LDL receptors, as assessed by Flow cytometry analysis. PTX and Gd-AAZTA-C17 loaded LDLs (LDL-PTX-Gd) have been prepared, characterized and their stability was assessed under 72 h incubation at 37 ◦C and compared to LDL loaded with Gd-AAZTA-C17 (LDL-Gd) and LDL-PTX. The cytotoxic effect of LDL-PTX-Gd was evaluated by MTT assay. The anti-tumour drug loaded into LDLs showed a significantly higher toxicity on B16-F10 cells with respect to the commercially available formulation Paclitaxel Kabi (PTX Kabi) used in clinical applications. It was possible to demonstrate a high uptake of LDL-Gd in B16-F10 cells. As a consequence of the high cell uptake, melanoma cells showed significantly high cytotoxic effect when incubated in the presence of PTX (LDL-PTX-Gd). Furthermore, B16-F10 have been used to perform Magnetic Resonance Imaging. By the analysis of the image signal intensity, it was possible to extrapolate the amount of internalized PTX indirectly by the decrease of relaxation times caused by Gd, proportional to its concentration. Finally, the treatment with PTX loaded LDL on B16-F10 tumour bearing mice resulted in a marked reduction of tumour growth compared to the administration of PTX Kabi alone. In conclusion, LDLs are selectively taken-up by tumour cells and can be successfully exploited for the selective delivery of Paclitaxel and imaging agents.

Keywords: low density lipoprotein, melanoma cell lines, MRI, paclitaxel, personalized medicine application, theragnostic System

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Authors: Jenyu Peng

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Incestuous abuse can be considered a form of domestic violence that exemplifies gender inequality. It challenges the common image of home as “haven of safety”. In Taiwan, even after years of feminist NGOs’ effort to encourage victims to speak up, the shared cultural representations of family, still praising piety towards the parents, seem to keep the incest trauma in secret. As clinical practitioners have observed, most devastating psychological sequels of incest trauma are often related to silencing. Thus one can expect that in families centered cultures, the difficulties for victims to disclose are greater, and the traumatic consequences more severe. This poses crucial therapeutic issues for clinicians working in those cultures. Since 2009, the author, a trained psychoanalyst and researcher, has been conducting “clinical fieldwork” on incest trauma in Taiwan. Employing ethnographical method, our theoretical references are both psychoanalytical and anthropological. The necessity of interdisciplinary efforts in incest trauma research will be addressed and discussed. The analyses of the present paper will focus on five incestuous families: four Han families, and one aboriginal. Although Taiwanese aboriginal peoples have been pretty much sinicized since decades, it is worth observing the convergent and divergent aspects in these two cultures. Moreover, findings of a previous research conducted in France during 2002-2004 will serve as background for the purpose of comparison. The results will be presented along with three questions: 1) How the perception of family influences the process of disclosure? 2) How the incestuous experience comes into play with victims’ gender identity and sexuality, pivotal for the subjectification? 3) How victims more successful in gendered subjectification modify their dynamics with their traumatizing family? This research finds that most victims tend to defend their own incestuous families, and that victims’ subjectivity and agency are actually entangled in the power structure of incestuous family.

Keywords: incestuous family, subjectification, gender identity, agency

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