Search results for: binary segmentation

Authors: Wei-Chih Huang, Pei-Lung Chung, Ching-Heng Lin, Hsuan-Chia Yang, Der-Ming Liou

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Background: In-Hospital Cardiac Arrest (IHCA) threaten life of the inpatients, cause serious effect to patient safety, quality of inpatients care and hospital service. Health providers must identify the signs of IHCA early to avoid the occurrence of IHCA. This study will consider the potential association between early signs of IHCA and the essence of patient care provided by nurses and other professionals before an IHCA occurs. The aim of this study is to identify significant associations between nursing interventions and abnormal early evaluation results of IHCA that can assist health care providers in monitoring inpatients at risk of IHCA to increase opportunities of IHCA early detection and prevention. Materials and Methods: This study used one of the data mining techniques called association rules mining to compute associations between nursing interventions and abnormal early evaluation results of IHCA. The nursing interventions and abnormal early evaluation results of IHCA were considered to be co-occurring if nursing interventions were provided within 24 hours of last being observed in abnormal early evaluation results of IHCA. The rule based methods were utilized 23.6 million electronic medical records (EMR) from a medical center in Taipei, Taiwan. This dataset includes 733 concepts of nursing interventions that coded by clinical care classification (CCC) codes and 13 early evaluation results of IHCA with binary codes. The values of interestingness and lift were computed as Q values to measure the co-occurrence and associations’ strength between all in-hospital patient care measures and abnormal early evaluation results of IHCA. The associations were evaluated by comparing the results of Q values and verified by medical experts. Results and Conclusions: The results show that there are 4195 pairs of associations between nursing interventions and abnormal early evaluation results of IHCA with their Q values. The indication of positive association is 203 pairs with Q values greater than 5. Inpatients with high blood sugar level (hyperglycemia) have positive association with having heart rate lower than 50 beats per minute or higher than 120 beats per minute, Q value is 6.636. Inpatients with temporary pacemaker (TPM) have significant association with high risk of IHCA, Q value is 47.403. There is significant positive correlation between inpatients with hypovolemia and happened abnormal heart rhythms (arrhythmias), Q value is 127.49. The results of this study can help to prevent IHCA from occurring by making health care providers early recognition of inpatients at risk of IHCA, assist with monitoring patients for providing quality of care to patients, improve IHCA surveillance and quality of in-hospital care.

Keywords: in-hospital cardiac arrest, patient safety, nursing intervention, association rule mining

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Authors: Liliane Steiner

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Beyond the testimonial act, that sheds light on the feminine experience in the Holocaust, the survivors' writing voices first and foremost the abjection of the feminine self brutally inflicted by the Nazis in the Holocaust, and in the same movement redeems the self by the means of poetics, and brings it to an existential state of being a subject. This study aims to stress the poetics of this writing in order to promote the Holocaust literature from the margins to the mainstream and to contribute to the commemoration of the Holocaust in the next generations. Methodology: The study of the survivors' redeeming of self is based on Julia Kristeva's theory of the abject: the self-throws out everything that threatens its existence and Liliane Steiner's theory of the post- abjection of hell: the belated act of vomiting the abject experiences settles cores with the author of the abject to redeem the self. The research will focus on Ruth Sender's trilogy The Cage, To Life and The Holocaust Lady as a case study. Findings: The binary mode that characterizes this writing reflects the experience of Jewish women, who were subject(s), were treated violently as object(s), debased, defeminized and, eventually turned into abject by the Nazis. In a tour de force, this writing re-enacts the postponed resistance, that vomited the abject imposed on the feminine self by the very act of narration, which denounces the real abject, the perpetrators. The post-abjection of self is acted out in constructs of abject, relating the abject experience of the Holocaust as well as the rehabilitation of the surviving self (subject). The transcription of abject surfaces in deconstructing the abject through self- characterization, and in the elusive rendering of bad memories, having recourse to literary figures. The narrative 'I' selects, obstructs, mends and tells the past events from an active standpoint, as would a subject in control of its (narrative) fate. In a compensatory movement, the narrating I tells itself by reconstructing the subject and proving time and again that I is other. Moreover, in the belated endeavor to revenge, testify and narrate the abject, the narrative I defies itself, and represents itself as a dialectical I, splitting and multiplying itself in a deconstructing way. The dialectical I is never (one) I. It voices not only the unvoiced but also and mainly the other silenced 'I's. Drawing its nature and construct from traumatic memories, the dialectical I transgresses boundaries to narrate her story, and in the same breath, the story of Jewish women doomed to silence. In this narrative feat, the dialectical I stresses its essential dialectical existence with the past, never to be (one) again. Conclusion: The pattern of I is other generates patterns of subject(s) that defy, transgress and repudiate the abject and its repercussions on the feminine I. The feminine I writes itself as a survivor that defies the abject (Nazis) and takes revenge. The paradigm of metamorphosis that accompanies the journey of the Holocaust memoirist engenders life and surviving as well as a narration that defies stagnation and death.

Keywords: abject, feminine writing, holocaust, post-abjection

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Authors: Sardorbek Numonov, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Dongeun Choi, Byung-Woo Hong

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The detection of curvilinear structures often plays an important role in the analysis of images. In particular, it is considered as a crucial step for the diagnosis of chronic respiratory diseases to localize the fissures in chest CT imagery where the lung is divided into five lobes by the fissures that are characterized by linear features in appearance. However, the characteristic linear features for the fissures are often shown to be subtle due to the high intensity variability, pathological deformation or image noise involved in the imaging procedure, which leads to the uncertainty in the quantification of anatomical or functional properties of the lung. Thus, it is desired to enhance the linear features present in the chest CT images so that the distinctiveness in the delineation of the lobe is improved. We propose a recursive diffusion process that prefers coherent features based on the analysis of structure tensor in an anisotropic manner. The local image features associated with certain scales and directions can be characterized by the eigenanalysis of the structure tensor that is often regularized via isotropic diffusion filters. However, the isotropic diffusion filters involved in the computation of the structure tensor generally blur geometrically significant structure of the features leading to the degradation of the characteristic power in the feature space. Thus, it is required to take into consideration of local structure of the feature in scale and direction when computing the structure tensor. We apply an anisotropic diffusion in consideration of scale and direction of the features in the computation of the structure tensor that subsequently provides the geometrical structure of the features by its eigenanalysis that determines the shape of the anisotropic diffusion kernel. The recursive application of the anisotropic diffusion with the kernel the shape of which is derived from the structure tensor leading to the anisotropic scale-space where the geometrical features are preserved via the eigenanalysis of the structure tensor computed from the diffused image. The recursive interaction between the anisotropic diffusion based on the geometry-driven kernels and the computation of the structure tensor that determines the shape of the diffusion kernels yields a scale-space where geometrical properties of the image structure are effectively characterized. We apply our recursive anisotropic diffusion algorithm to the detection of curvilinear structure in the chest CT imagery where the fissures present curvilinear features and define the boundary of lobes. It is shown that our algorithm yields precise detection of the fissures while overcoming the subtlety in defining the characteristic linear features. The quantitative evaluation demonstrates the robustness and effectiveness of the proposed algorithm for the detection of fissures in the chest CT in terms of the false positive and the true positive measures. The receiver operating characteristic curves indicate the potential of our algorithm as a segmentation tool in the clinical environment. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: anisotropic diffusion, chest CT imagery, chronic respiratory disease, curvilinear structure, fissure detection, structure tensor

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Authors: Dieudonne Uwizeye, Reuben Muhayiteto

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Teenage pregnancy is a challenging problem for sustainable development due to restrictions it poses to socioeconomic opportunities for young mothers, their children and families. Being unable to take appropriate economic and social responsibilities, teen mothers get trapped into poverty and become economic burden to their family and country. Besides, teenage pregnancy is also a health problem because children born to very young mothers are vulnerable with greater risk of illnesses and deaths, and teenage mothers are more likely to be exposed to greater risk of maternal mortality and to other health and psychological problems. In Kigali city, in Rwanda, teenage pregnancy rate is currently high and its increase in recent years is worrisome. However, only individual factors influencing the teenage pregnancy tend to be the basis of interventions. It is important to understand the important socioeconomic factors at the household level that are associated with teenage pregnancy to help government, parents, and other stakeholders to appropriately address the problem with sustainable measures. This study analyzed secondary data from the Fifth Rwanda Demographic and Health Survey (RDHS-V 2014-2015) conducted by the National Institute of Statistics of Rwanda (NISR). The aim was to examine household socio-economic factors that are associated with incidence of teenage pregnancies in Kigali city. In addition to descriptive analysis, Pearson’s Chi Square and Binary Logistic Regression were used in the analysis. Findings indicate that marital status and age of household head, number of members in a household, number of rooms used for sleeping, educational level of the household head and household's wealth are significantly associated with teenage pregnancy in Rwanda ( p< 0.05). It was found that teenagers living with parents, those having parents with higher education and those from richer families are less likely to become pregnant. Age of household head was pinpointed as factor to teenage pregnancy, with teenage-headed households being more vulnerable. The findings also revealed that household composition correlates with the probability of teenage pregnancy (p < 0.05) with teenagers from households with less number of members being more vulnerable. Regarding the size of the house, the study suggested that the more rooms available in households, the less incidences of teenage pregnancy are likely to be observed (p < 0.05). However, teenage pregnancy was not significantly associated with physical violence among parents (p = 0.65) and sex of household heads (p = 0.52), except in teen-headed households of which female are predominantly heads. The study concludes that teenage pregnancy remains a serious social, economic and health problem in Rwanda. The study informs government officials, parents and other stakeholders to take interventions and preventive measures through community sex education, policies and strategies to foster effective parental guidance, care and control of young girls through meeting their necessary social and financial needs within households.

Keywords: household socio-economic factors, Rwanda, Rwanda demographic and health survey, teenage pregnancy

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Authors: Abdelkader Soumaya, Aymen Arfaoui, Noureddine Ben Ayed, Ali Kadri

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The Chotts belt represents the southernmost folded structure in the Tunisian Atlas domain. It is dominated by inherited deep extensional E-W trending fault zones, which are reactivated as strike-slip faults during the Cenozoic compression. By examining the geological maps at different scales and based on the fieldwork data, we propose new structural interpretations for the geometries and fault kinematics in the Chotts chain. A set of ENE-WSW right-lateral en echelon folds, with curved shapes and steeply inclined southern limbs, is visible in the map view of this belt. These asymmetric tight anticlines are affected by E-W trending fault segments linked by local bends and stepovers. The revealed kinematic indicators along one of these E-W striated faults (Tafferna segment), such as breccias and gently inclined slickenlines (N094, 80N, 15°W pitch angles), show direct evidence of dextral strike-slip movement. The calculated stress tensors from corresponding faults slip data reveal an overall strike-slip tectonic regime with reverse component and NW-trending sub-horizontal σ1 axis ranking between N130 to N150. From west to east, we distinguished several types of structures along the segmented dextral fault system of the Chotts Range. The NE-SW striking fold-thrust belt (~25 km-long) between two continuously linked E-W fault segments (NW of Tozeur town) has been suggested as a local restraining bend. The central part of the Chotts chain is occupied by the ENE-striking Ksar Asker anticlines (Taferna, Torrich, and Sif Laham), which are truncated by a set of E-W strike-slip fault segments. Further east, the fault segments of Hachichina and Sif Laham connected across the NW-verging asymmetric fold-thrust system of Bir Oum Ali, which can be interpreted as a left-stepping contractional bend (~20 km-long). The oriental part of the Chotts belt corresponds to an array of subparallel E-W oriented fault segments (i.e., Beidha, Bouloufa, El Haidoudi-Zemlet El Beidha) with similar lengths (around 10 km). Each of these individual separated segments is associated with curved ENE-trending en echelon right-stepping anticlines. These folds are affected by a set of conjugate R and R′ shear-type faults indicating a dextral strike-lip motion. In addition, the relay zones between these E-W overstepping fault segments define local releasing stepovers dominated by NW-SE subsidiary faults. Finally, the Chotts chain provides well-exposed examples of strike-slip tectonics along E-W distributed fault segments. Each fault zone shows a typical strike-slip architecture, including parallel fault segments connecting via local stepovers or bends. Our new structural interpretations for this region reveal a great influence of the E-W deep fault segments on regional tectonic deformations and stress field during the Cenozoic shortening.

Keywords: chotts belt, tunisian atlas, strike-slip fault, stepovers, fault segments

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Authors: Dejene Ermias Mekango, Mussie Alemayehu, Gebremedhin Berhe Gebregergs, Araya Abrha Medhanye, Gelila Goba

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Background: Maternal near miss (MNM) can be used as a proxy indicator of maternal mortality ratio. There is a huge gap in life time risk between Sub-Saharan Africa and developed countries. In Ethiopia, a significant number of women die each year from complications during pregnancy, childbirth and the post-partum period. Besides, a few studies have been performed on MNM, and little is known regarding determinant factors. This study aims to identify determinants of MNM among women in Tigray region, Northern Ethiopia. Methods: a case-control study in hospital found in Tigray region, Ethiopia was conducted from January 30 - March 30, 2016. The sample included 103 cases and 205 controls recruited from women seeking obstetric care at six public hospitals. Clients having a life-threatening obstetric complication including haemorrhage, hypertensive diseases of pregnancy, dystocia, infections, and anemia or clinical signs of severe anemia in women without haemorrhage were taken as cases and those with normal obstetric outcomes were considered as controls. Cases were selected based on proportional to size allocation while systematic sampling was employed for controls. Data were analyzed using SPSS version 20.0. Binary and multiple variable logistic regression (odds ratio) analyses were calculated with 95% CI. Results: The largest proportion of cases and controls was among the ages of20–29 years, accounting for37.9 %( 39) of cases and 31.7 %( 65) of controls. Roughly 90% of cases and controls were married. About two-thirds of controls and 45.6 %( 47) of cases had gestational age between 37-41 weeks. History of chronic medical conditions was reported in 55.3 %(57) of cases and 33.2%(68) of controls. Women with no formal education [AOR=3.2;95%CI:1.24, 8.12],being less than 16 years old at first pregnancy [AOR=2.5; 95%CI:1.12,5.63],induced labor[AOR=3; 95%CI:1.44, 6.17], history of Cesarean section (C-section) [AOR=4.6; 95%CI: 1.98, 7.61] or chronic medical disorder[AOR=3.5;95%CI:1.78, 6.93], and women who traveled more than 60 minutes before reaching their final place of care[AOR=2.8;95% CI: 1.19,6.35] all had higher odds of experiencing MNM. Conclusions: The Government of Ethiopia should continue its effort to address the lack of road and health facility access as well as education, which will help reduce MNM. Work should also be continued to educate women and providers about common predictors of MNM like the history of C-section, chronic illness, and teenage pregnancy. These efforts should be carried out at the facility, community, and individual levels. The targeted follow-up to women with a history of chronic disease and C-section could also be a practical way to reduce MNM.

Keywords: maternal near miss, severe obstetric hemorrhage, hypertensive disorder, c-section, Tigray, Ethiopia

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Authors: Aymen Arfaoui, Abdelkader Soumaya, Noureddine Ben Ayed

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The study region is located in the Tunisian Dorsal Backland (Central Mediterranean), which is the easternmost part of the Saharan Atlas mountain range, trending southwest-northeast. Based on our fieldwork, seismic tomography images, seismicity, and previous studies, we propose an interpretation of the relationship between the surface deformation and fault kinematics in the study area and the internal dynamic processes acting in the Central Mediterranean from the Cenozoic to the present. The subduction and dynamics of internal forces beneath the complicated Maghrebides mobile belt have an impact on the Tertiary and Quaternary tectonic regimes in the Pelagian and Atlassic foreland that is part of our study region. The left lateral reactivation of the major "Tunisian N-S Axis fault" and the development of a compressional relay between the Hammamet Korbous and Messella-Ressas faults are possibly a result of tectonic stresses due to the slab roll-back following the Africa/Eurasia convergence. After the slab segmentation and its eastward migration (5–4 Ma) and the formation of the Strait of Sicily "rift zone" further east, a transtensional tectonic regime has been installed in this area. According to seismic tomography images, the STEP fault of the "North-South Axis" at Hammamet-Korbous coincides with the western edge of the "Slab windows" of the Sicilian Channel and the eastern boundary of the positive anomalies attributed to the residual Slab of Tunisia. On the other hand, significant E-W Plio-Quaternary tectonic activity may be observed along the eastern portion of this STEP fault system in the Grombalia zone as a result of recent vertical lithospheric motion in response to the lateral slab migration eastward to Sicily Channel. According to SKS fast splitting directions, the upper mantle flow pattern beneath Tunisian Dorsal is parallel to the NE-SW to E-W orientation of the Shmin identified in the study area, similar to the Plio-Quaternary extensional orientation in the Central Mediterranean. Additionally, the removal of the lithosphere and the subsequent uplift of the sub-lithospheric mantle beneath the topographic highs of the Dorsal and its surroundings may be the cause of the dominant extensional to transtensional Quaternary regime. The occurrence of strike-slip and extensional seismic events in the Pelagian block reveals that the regional transtensional tectonic regime persists today. Finally, we believe that the geodynamic history of the study area since the Cenozoic is primarily influenced by the preexisting weak zones, the African slab detachment, and the upper mantle flow pattern in the central Mediterranean.

Keywords: Tunisia, lithospheric discontinuity (STEP fault), geodynamic evolution, Tunisian dorsal backland, strike-slip fault, seismic tomography, seismicity, central Mediterranean

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Authors: Nur Fareza Mustapha

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Solutions to policy problems need to be curated to the local context, taking into account the trajectory of the local development path to ensure its efficacy. For Kuala Lumpur, rapid urbanization and migration into the city for the past few decades have increased the demand for housing to accommodate a growing urban population. As a critical factor affecting housing affordability, land supply constraints have been attributed to intensifying market pressures, which grew in tandem with the demands of urban development, along with existing institutional constraints in the governance of land. While demand-side pressures are inevitable given the fixed supply of land, supply-side constraints in regulations distort markets and if addressed inappropriately, may lead to mistargeted policy interventions. Given Malaysia’s historical development, regulatory barriers for land may originate from the British colonial period, when many aspects of the current laws governing tenure were introduced and formalized, and henceforth, became engrained in the system. This research undertakes a postcolonial institutional analysis approach to uncover the causal mechanism driving the evolution of land tenure systems in post-colonial Kuala Lumpur. It seeks to determine the sources of these shifts, focusing on the incentives and bargaining positions of actors during periods of institutional flux/change. It aims to construct a conceptual framework to further this understanding and to elucidate how this historical trajectory affects current access to urban land markets for housing. Archival analysis is used to outline and analyse the evolution of land tenure systems in Kuala Lumpur while stakeholder interviews are used to analyse its impact on the current urban land market, with a particular focus on the provision of and access to affordable housing in the city. Preliminary findings indicate that many aspects of the laws governing tenure that were introduced and formalized during the British colonial period have endured until the present day. Customary rules of tenure were displaced by rules following a European tradition, which found legitimacy through a misguided interpretation of local laws regarding the ownership of land. Colonial notions of race and its binary view of native vs. non-natives have also persisted in the construction and implementation of current legislation regarding land tenure. More concrete findings from this study will generate a more nuanced understanding of the regulatory land supply constraints in Kuala Lumpur, taking into account both the long and short term spatial and temporal processes that affect how these rules are created, implemented and enforced.

Keywords: colonial discourse, historical institutionalism, housing, land policy, post-colonial city

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Authors: Nguyen J. M., Lucas G., Ruan S., Digonnet H., Antonioli D.

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Introduction: Deep Learning (DL) is a very powerful tool for analyzing image data. But for tabular data, it cannot compete with machine learning methods like XGBoost. The research question becomes: can tabular data be transformed into images that can be analyzed by simple CNNs (Convolutional Neuron Networks)? Will DL be the absolute tool for data classification? All current solutions consist in repositioning the variables in a 2x2 matrix using their correlation proximity. In doing so, it obtains an image whose pixels are the variables. We implement a technology, DeepNIC, that offers the possibility of obtaining an image for each variable, which can be analyzed by simple CNNs. Material and method: The 'ROP' (Regression OPtimized) model is a binary and atypical decision tree whose nodes are managed by a new artificial neuron, the Neurop. By positioning an artificial neuron in each node of the decision trees, it is possible to make an adjustment on a theoretically infinite number of variables at each node. From this new decision tree whose nodes are artificial neurons, we created the concept of a 'Random Forest of Perfect Trees' (RFPT), which disobeys Breiman's concepts by assembling very large numbers of small trees with no classification errors. From the results of the RFPT, we developed a family of 10 statistical information criteria, Nguyen Information Criterion (NICs), which evaluates in 3 dimensions the predictive quality of a variable: Performance, Complexity and Multiplicity of solution. A NIC is a probability that can be transformed into a grey level. The value of a NIC depends essentially on 2 super parameters used in Neurops. By varying these 2 super parameters, we obtain a 2x2 matrix of probabilities for each NIC. We can combine these 10 NICs with the functions AND, OR, and XOR. The total number of combinations is greater than 100,000. In total, we obtain for each variable an image of at least 1166x1167 pixels. The intensity of the pixels is proportional to the probability of the associated NIC. The color depends on the associated NIC. This image actually contains considerable information about the ability of the variable to make the prediction of Y, depending on the presence or absence of other variables. A basic CNNs model was trained for supervised classification. Results: The first results are impressive. Using the GSE22513 public data (Omic data set of markers of Taxane Sensitivity in Breast Cancer), DEEPNic outperformed other statistical methods, including XGBoost. We still need to generalize the comparison on several databases. Conclusion: The ability to transform any tabular variable into an image offers the possibility of merging image and tabular information in the same format. This opens up great perspectives in the analysis of metadata.

Keywords: tabular data, CNNs, NICs, DeepNICs, random forest of perfect trees, classification

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Authors: Maximilian Engelhardt, Stephan Seeck

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The COVID-19 pandemic is accelerating the already growing field of e-commerce. The resulting urban freight transport volume leads to traffic and negative environmental impact. Furthermore, the service level of parcel logistics service provider is lacking far behind the expectations of consumer. These challenges can be solved by radically reorganize the urban last mile distribution structure: parcels could be consolidated in a micro hub within the inner city and delivered within time windows by cargo bike. This approach leads to a significant improvement of consumer satisfaction with their overall delivery experience. However, this approach also leads to significantly increased costs per parcel. While there is a relevant share of online shoppers that are willing to pay for such a delivery service there are no deeper insights about this target group available in the literature. Being aware of the importance of knowing target groups for businesses, the aim of this paper is to elaborate the most important factors that determine the willingness to pay for sustainable and service-oriented parcel delivery (factor analysis) and to derive customer segments (cluster analysis). In order to answer those questions, a data set is analyzed using quantitative methods of multivariate statistics. The data set was generated via an online survey in September and October 2020 within the five largest cities in Germany (n = 1.071). The data set contains socio-demographic, living-related and value-related variables, e.g. age, income, city, living situation and willingness to pay. In a prior work of the author, the data was analyzed applying descriptive and inference statistical methods that only provided limited insights regarding the above-mentioned research questions. The analysis in an exploratory way using factor and cluster analysis promise deeper insights of relevant influencing factors and segments for user behavior of the mentioned parcel delivery concept. The analysis model is built and implemented with help of the statistical software language R. The data analysis is currently performed and will be completed in December 2021. It is expected that the results will show the most relevant factors that are determining user behavior of sustainable and service-oriented parcel deliveries (e.g. age, current service experience, willingness to pay) and give deeper insights in characteristics that describe the segments that are more or less willing to pay for a better parcel delivery service. Based on the expected results, relevant implications and conclusions can be derived for startups that are about to change the way parcels are delivered: more customer-orientated by time window-delivery and parcel consolidation, more environmental-friendly by cargo bike. The results will give detailed insights regarding their target groups of parcel recipients. Further research can be conducted by exploring alternative revenue models (beyond the parcel recipient) that could compensate the additional costs, e.g. online-shops that increase their service-level or municipalities that reduce traffic on their streets.

Keywords: customer segmentation, e-commerce, last mile delivery, parcel service, urban logistics, willingness-to-pay

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Authors: Sophie-Bo Heinkel, Andrea Rechenburg, Thomas Kistemann

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The current status of wellbeing and life satisfaction of subsistence farmers in a wetland in Uganda and the contributing role of place attachment has been assessed. The aim of this study is to shed light on environmental factors supporting wellbeing in a wetland setting. Furthermore, it has been assessed, how the emotional bonding to the wetland as ‘place’ influences the peoples’ wellbeing and life satisfaction. The results shed light on the human-environment-relationship. A survey was carried out in three communities in urban and rural areas in a wetland basin in Uganda. A sample (n=235) provided information about the attachment to the wetland, the participants’ relation to the place of their residence and their emotional wellbeing. The Wellbeing Index (WHO-5) was assessed as well as the Perceived Stress Scale (PSS-10) and Rosenberg’s Self-Esteem scale (RSE). Furthermore, the Satisfaction With Life Scale (SWLS) was applied as well as the Place Attachment Inventory (PAI), which consists of the two intertwined dimensions of place identity and place dependence. Beside this, binary indicators as ‘feeling save’ and ‘feeling comfortable’ and ‘enjoying to live at the place of residence’ have been assessed. A bivariate correlation analysis revealed a high interconnectivity between all metric scales. Especially, the subscale ‘place identity’ showed significances with all other scales. A cluster analysis revealed three groups, which differed in the perception of place-related indicators and their attachment to the wetland as well as the status of wellbeing. First, a cluster whose majority is dissatisfied with their lives, but mainly had a good status of emotional well-being. This group does not feel attached to the wetland and lives in a town. Comparably less persons of this group feel safe and comfortable at their place of residence. In the second cluster, persons feel highly attached to the wetland and identify with it. This group was characterized by the high number of persons preferring their current place of residence and do not consider moving. All persons feel well and satisfied with their lives. The third group of persons is mainly living in rural areas and feels highly attached to the wetland. They are satisfied with their lives, but only a small minority is in a good emotional state of wellbeing. The emotional attachment to a place influences life satisfaction and, indirectly, the emotional wellbeing. In the present study it could be shown that subsistence farmers are attached to the wetland, as it is the source of their livelihood. While those living in areas with a good infrastructure are less dependent on the wetland and, therefore, less attached to. This feeling also was mirrored in the perception of a place as being safe and comfortable. The identification with a place is crucial for the feeling of being at “home”. Subsistence farmers feel attached to the ecosystem, but they also might be exposed to environmental and social stressors influencing their short-term emotional wellbeing. The provision of place identity is an ecosystem service provided by wetlands, which supports the status of wellbeing in human beings.

Keywords: mental health, positive environments, quality of life, wellbeing

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Authors: Vangmayee. V. Subban, Somashekara H. S, Shwetha Prabhu, Jayashree S. Bhat

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Introduction and Need: Phonological processing is critical in learning to read alphabetical and non-alphabetical languages. However, its role in learning to read Kannada an alphasyllabary is equivocal. The literature has focused on the developmental role of phonological awareness on reading. To the best of authors knowledge, the role of phonological memory and phonological naming has not been addressed in alphasyllabary Kannada language. Therefore, there is a need to evaluate the comprehensive role of the phonological processing skills in Kannada on word decoding skills during the early years of schooling. Aim and Objectives: The present study aimed to explore the phonological processing abilities and their role in learning to decode pseudowords in children learning to read the Kannada language during initial years of formal schooling between 5.6 to 8.6 years. Method: In this cross sectional study, 60 typically developing Kannada speaking children, 20 each from Grade I, Grade II, and Grade III between the age range of 5.6 to 6.6 years, 6.7 to 7.6 years and 7.7 to 8.6 years respectively were selected from Kannada medium schools. Phonological processing abilities were assessed using an assessment tool specifically developed to address the objectives of the present research. The assessment tool was content validated by subject experts and had good inter and intra-subject reliability. Phonological awareness was assessed at syllable level using syllable segmentation, blending, and syllable stripping at initial, medial and final position. Phonological memory was assessed using pseudoword repetition task and phonological naming was assessed using rapid automatized naming of objects. Both phonological awareneness and phonological memory measures were scored for the accuracy of the response, whereas Rapid Automatized Naming (RAN) was scored for total naming speed. Results: The mean scores comparison using one-way ANOVA revealed a significant difference (p ≤ 0.05) between the groups on all the measures of phonological awareness, pseudoword repetition, rapid automatized naming, and pseudoword reading. Subsequent post-hoc grade wise comparison using Bonferroni test revealed significant differences (p ≤ 0.05) between each of the grades for all the tasks except (p ≥ 0.05) for syllable blending, syllable stripping, and pseudoword repetition between Grade II and Grade III. The Pearson correlations revealed a highly significant positive correlation (p=0.000) between all the variables except phonological naming which had significant negative correlations. However, the correlation co-efficient was higher for phonological awareness measures compared to others. Hence, phonological awareness was chosen a first independent variable to enter in the hierarchical regression equation followed by rapid automatized naming and finally, pseudoword repetition. The regression analysis revealed syllable awareness as a single most significant predictor of pseudoword reading by explaining the unique variance of 74% and there was no significant change in R² when RAN and pseudoword repetition were added subsequently to the regression equation. Conclusion: Present study concluded that syllable awareness matures completely by Grade II, whereas the phonological memory and phonological naming continue to develop beyond Grade III. Amongst phonological processing skills, phonological awareness, especially syllable awareness is crucial for word decoding than phonological memory and naming during initial years of schooling.

Keywords: phonological awareness, phonological memory, phonological naming, phonological processing, pseudo-word decoding

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Authors: Alexandru-Ion Marinescu

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There exist a plethora of methods in the scientific literature which tackle the well-established task of credit score evaluation. In its most abstract form, a credit scoring algorithm takes as input several credit applicant properties, such as age, marital status, employment status, loan duration, etc. and must output a binary response variable (i.e. “GOOD” or “BAD”) stating whether the client is susceptible to payment return delays. Data imbalance is a common occurrence among financial institution databases, with the majority being classified as “GOOD” clients (clients that respect the loan return calendar) alongside a small percentage of “BAD” clients. But it is the “BAD” clients we are interested in since accurately predicting their behavior is crucial in preventing unwanted loss for loan providers. We add to this whole context the constraint that the algorithm must yield an actual, tractable mathematical formula, which is friendlier towards financial analysts. To this end, we have turned to genetic algorithms and genetic programming, aiming to evolve actual mathematical expressions using specially tailored mutation and crossover operators. As far as data representation is concerned, we employ a very flexible mechanism – LINQ expression trees, readily available in the C# programming language, enabling us to construct executable pieces of code at runtime. As the title implies, they model trees, with intermediate nodes being operators (addition, subtraction, multiplication, division) or mathematical functions (sin, cos, abs, round, etc.) and leaf nodes storing either constants or variables. There is a one-to-one correspondence between the client properties and the formula variables. The mutation and crossover operators work on a flattened version of the tree, obtained via a pre-order traversal. A consequence of our chosen technique is that we can identify and discard client properties which do not take part in the final score evaluation, effectively acting as a dimensionality reduction scheme. We compare ourselves with state of the art approaches, such as support vector machines, Bayesian networks, and extreme learning machines, to name a few. The data sets we benchmark against amount to a total of 8, of which we mention the well-known Australian credit and German credit data sets, and the performance indicators are the following: percentage correctly classified, area under curve, partial Gini index, H-measure, Brier score and Kolmogorov-Smirnov statistic, respectively. Finally, we obtain encouraging results, which, although placing us in the lower half of the hierarchy, drive us to further refine the algorithm.

Keywords: expression trees, financial credit scoring, genetic algorithm, genetic programming, symbolic evolution

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Authors: Geday Elias, Montaigne Etienne, Padilla Martine, Tollossa Degefa

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Smallholder farmers’ participation in agricultural value chain identified as a pathway to get out of poverty trap in Ethiopia. The smallholder dairy activities have a huge potential in poverty reduction through enhancing income, achieving food and nutritional security in the country. However, much less is known about the effects of smallholder’s participation in milk value chain on household food security and nutrition. This paper therefore, aims at evaluating the effects of smallholders’ participation in milk value chain on household food security taking in to account the four pillars of food security measurements (availability, access, utilization and stability). Using a semi-structured interview, a cross sectional farm household data collected from a randomly selected sample of 333 households (170 in Amhara and 163 in Oromia regions).Binary logit and propensity score matching( PSM) models are employed to examine the mechanisms through which smallholder’s participation in the milk value chain affects household food security where crop production, per capita calorie intakes, diet diversity score, and food insecurity access scale are used to measure food availability, access, utilization and stability respectively. Our findings reveal from 333 households, only 34.5% of smallholder farmers are participated in the milk value chain. Limited access to inputs and services, limited access to inputs markets and high transaction costs are key constraints for smallholders’ limited access to the milk value chain. To estimate the true average participation effects of milk value chain for participated households, the outcome variables (food security) of farm households who participated in milk value chain are compared with the outcome variables if the farm households had not participated. The PSM analysis reveals smallholder’s participation in milk value chain has a significant positive effect on household income, food security and nutrition. Smallholder farmers who are participated in milk chain are better by 15 quintals crops production and 73 percent of per capita calorie intakes in food availability and access respectively than smallholder farmers who are not participated in the market. Similarly, the participated households are better in dietary quality by 112 percents than non-participated households. Finally, smallholders’ who are participated in milk value chain are better in reducing household vulnerability to food insecurity by an average of 130 percent than non participated households. The results also shows income earned from milk value chain participation contributed to reduce capital’s constraints of the participated households’ by higher farm income and total household income by 5164 ETB and 14265 ETB respectively. This study therefore, confirms the potential role of smallholders’ participation in food value chain to get out of poverty trap through improving rural household income, food security and nutrition. Therefore, identified the determinants of smallholder participation in milk value chain and the participation effects on food security in the study areas are worth considering as a positive knock for policymakers and development agents to tackle the poverty trap in the study area in particular and in the country in general.

Keywords: effects, food security and nutrition, milk, participation, smallholders, value chain

Procedia PDF Downloads 320

Authors: Hui-Chieh Li

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Circular economy promotes greater resource productivity and avoids pollution through greater recycling and re-use which bring benefits for both the environment and the economy. The concept is contrast to a linear economy which is ‘take, make, dispose’ model of production. A well-design reverse logistics service strategy could enhance the willingness of recycling of the users and reduce the related logistics cost as well as carbon emissions. Moreover, the recycle brings the manufacturers most advantages as it targets components for closed-loop reuse, essentially converting materials and components from worn-out product into inputs for new ones at right time and right place. This study considers demand-supply interaction, time-dependent recycle demand, time-dependent surplus value of recycled product and constructs models on recycle service strategy for the recyclable waste collector. A crucial factor in optimizing a recycle service strategy is consumer demand. The study considers the relationships between consumer demand towards recycle and product characteristics, surplus value and user behavior. The study proposes a recycle service strategy which differs significantly from the conventional and typical uniform service strategy. Periods with considerable demand and large surplus product value suggest frequent and short service cycle. The study explores how to determine a recycle service strategy for recyclable waste collector in terms of service cycle frequency and duration and vehicle type for all service cycles by considering surplus value of recycled product, time-dependent demand, transportation economies and demand-supply interaction. The recyclable waste collector is responsible for the collection of waste product for the manufacturer. The study also examines the impacts of utilization rate on the cost and profit in the context of different sizes of vehicles. The model applies mathematical programming methods and attempts to maximize the total profit of the distributor during the study period. This study applies the binary logit model, analytical model and mathematical programming methods to the problem. The model specifically explores how to determine a recycle service strategy for the recycler by considering product surplus value, time-dependent recycle demand, transportation economies and demand-supply interaction. The model applies mathematical programming methods and attempts to minimize the total logistics cost of the recycler and maximize the recycle benefits of the manufacturer during the study period. The study relaxes the constant demand assumption and examines how service strategy affects consumer demand towards waste recycling. Results of the study not only help understanding how the user demand for recycle service and product surplus value affects the logistics cost and manufacturer’s benefits, but also provide guidance such as award bonus and carbon emission regulations for the government.

Keywords: circular economy, consumer demand, product surplus value, recycle service strategy

Procedia PDF Downloads 377

Authors: Noga Bregman

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Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.

Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves

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Authors: Shailaja Thakur

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Managerial literature abounds with discussions on business strategies, success stories as well as cases of failure, which provide an indication of the parameters that should be considered in gauging the dynamism of an entrepreneur. Neoclassical economics has reduced entrepreneurship to a mere factor of production, driven solely by the profit motive, thus stripping him of all creativity and restricting his decision making to mechanical calculations. His ‘dynamism’ is gauged simply by the amount of profits he earns, marginalizing any discussion on the means that he employs to attain this objective. With theoretical backing, we have developed an Index of Entrepreneurial Dynamism (IED) giving weights to the different moves that the entrepreneur makes during his business journey. Strategies such as changes in product lines, markets and technology are gauged as very important (weighting of 4); while adaptations in terms of technology, raw materials used, upgradations in skill set are given a slightly lesser weight of 3. Use of formal market analysis, diversification in related products are considered moderately important (weight of 2) and being a first generation entrepreneur, employing managers and having plans to diversify are taken to be only slightly important business strategies (weight of 1). The maximum that an entrepreneur can score on this index is 53. A semi-structured questionnaire is employed to solicit the responses from the entrepreneurs on the various strategies that have been employed by them during the course of their business. Binary as well as graded responses are obtained, weighted and summed up to give the IED. This index was tested on about 150 tribal entrepreneurs in Mizoram, a state of India and was found to be highly effective in gauging their dynamism. This index has universal acceptability but is devoid of the socio-cultural context, which is very central to the success and performance of the entrepreneurs. We hypothesize that a society that respects risk taking takes failures in its stride, glorifies entrepreneurial role models, promotes merit and achievement is one that has a conducive socio- cultural environment for entrepreneurship. For obtaining an idea about the social acceptability, we are putting forth questions related to the social acceptability of business to another set of respondents from different walks of life- bureaucracy, academia, and other professional fields. Similar weighting technique is employed, and index is generated. This index is used for discounting the IED of the respondent entrepreneurs from that region/ society. This methodology is being tested for a sample of entrepreneurs from two very different socio- cultural milieus- a tribal society and a ‘mainstream’ society- with the hypothesis that the entrepreneurs in the tribal milieu might be showing a higher level of dynamism than their counterparts in other regions. An entrepreneur who scores high on IED and belongs to society and culture that holds entrepreneurship in high esteem, might not be in reality as dynamic as a person who shows similar dynamism in a relatively discouraging or even an outright hostile environment.

Keywords: index of entrepreneurial dynamism, India, social acceptability, tribal entrepreneurs

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Authors: B. S. Muddukrishna, Karthik Aithal, Aravind Pai

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Introduction: Preparation of binary cocrystals of Etraverine (ETR) by using Tartaric Acid (TAR) as a conformer was the main focus of this study. Etravirine is a Class IV drug, as per the BCS classification system. Methods: Cocrystals were prepared by slow evaporation technique. A mixture of total 500mg of ETR: TAR was weighed in molar ratios of 1:1 (371.72mg of ETR and 128.27mg of TAR). Saturated solution of Etravirine was prepared in Acetone: Methanol (50:50) mixture in which tartaric acid is dissolved by sonication and then this solution was stirred using a magnetic stirrer until the solvent got evaporated. Shimadzu FTIR – 8300 system was used to acquire the FTIR spectra of the cocrystals prepared. Shimadzu thermal analyzer was used to achieve DSC measurements. X-ray diffractometer was used to obtain the X-ray powder diffraction pattern. Shake flask method was used to determine the equilibrium dynamic solubility of pure, physical mixture and cocrystals of ETR. USP buffer (pH 6.8) containing 1% of Tween 80 was used as the medium. The pure, physical mixture and the optimized cocrystal of ETR were accurately weighed sufficient to maintain the sink condition and were filled in hard gelatine capsules (size 4). Electrolab-Tablet Dissolution tester using basket apparatus at a rotational speed of 50 rpm and USP phosphate buffer (900 mL, pH = 6.8, 37 ˚C) + 1% Tween80 as a media, was used to carry out dissolution. Shimadzu LC-10 series chromatographic system was used to perform the analysis with PDA detector. An Hypersil BDS C18 (150mm ×4.6 mm ×5 µm) column was used for separation with mobile phase comprising of a mixture of ace¬tonitrile and phosphate buffer 20mM, pH 3.2 in the ratio 60:40 v/v. The flow rate was 1.0mL/min and column temperature was set to 30°C. The detection was carried out at 304 nm for ETR. Results and discussions: The cocrystals were subjected to various solid state characterization and the results confirmed the formation of cocrystals. The C=O stretching vibration (1741cm-1) in tartaric acid was disappeared in the cocrystal and the peak broadening of primary amine indicates hydrogen bond formation. The difference in the melting point of cocrystals when compared to pure Etravirine (265 °C) indicates interaction between the drug and the coformer which proves that first ordered transformation i.e. melting endotherm has disappeared. The difference in 2θ values of pure drug and cocrystals indicates the interaction between the drug and the coformer. Dynamic solubility and dissolution studies were also conducted by shake flask method and USP apparatus one respectively and 3.6 fold increase in the dynamic solubility were observed and in-vitro dissolution study shows four fold increase in the solubility for the ETR: TAR (1:1) cocrystals. The ETR: TAR (1:1) cocrystals shows improved solubility and dissolution as compared to the pure drug which was clearly showed by solid state characterization and dissolution studies.

Keywords: dynamic solubility, Etraverine, in vitro dissolution, slurry method

Procedia PDF Downloads 325

Authors: Pirta Palola, Richard Bailey, Lisa Wedding

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Societies and economies worldwide fundamentally depend on natural capital. Alarmingly, natural capital assets are quickly depreciating, posing an existential challenge for humanity. The development of robust natural capital accounting systems is essential for transitioning towards sustainable economic systems and ensuring sound management of capital assets. However, the accurate, equitable and comprehensive estimation of natural capital asset stocks and their accounting values still faces multiple challenges. In particular, the representation of socio-cultural values held by groups or communities has arguably been limited, as to date, the valuation of natural capital assets has primarily been based on monetary valuation methods and assumptions of individual rationality. People relate to and value the natural environment in multiple ways, and no single valuation method can provide a sufficiently comprehensive image of the range of values associated with the environment. Indeed, calls have been made to improve the representation of multiple types of value (instrumental, intrinsic, and relational) and diverse ontological and epistemological perspectives in environmental valuation. This study addresses this need by establishing a novel valuation framework, Environmental Value Functions (EVF), that allows for the integration of multiple types of value in natural capital accounting systems. The EVF framework is based on the estimation and application of value functions, each of which describes the relationship between the value and quantity (or quality) of an ecosystem component of interest. In this framework, values are estimated in terms of change relative to the current level instead of calculating absolute values. Furthermore, EVF was developed to also support non-marginalist conceptualizations of value: it is likely that some environmental values cannot be conceptualized in terms of marginal changes. For example, ecological resilience value may, in some cases, be best understood as a binary: it either exists (1) or is lost (0). In such cases, a logistic value function may be used as the discriminator. Uncertainty in the value function parameterization can be considered through, for example, Monte Carlo sampling analysis. The use of EVF is illustrated with two conceptual examples. For the first time, EVF offers a clear framework and concrete methodology for the representation of multiple types of value in natural capital accounting systems, simultaneously enabling 1) the complementary use and integration of multiple valuation methods (monetary and non-monetary); 2) the synthesis of information from diverse knowledge systems; 3) the recognition of value incommensurability; 4) marginalist and non-marginalist value analysis. Furthermore, with this advancement, the coupling of EVF and ecosystem modeling can offer novel insights to the study of spatial-temporal dynamics in natural capital asset values. For example, value time series can be produced, allowing for the prediction and analysis of volatility, long-term trends, and temporal trade-offs. This approach can provide essential information to help guide the transition to a sustainable economy.

Keywords: economics of biodiversity, environmental valuation, natural capital, value function

Procedia PDF Downloads 177

Authors: Rakesh Mishra

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India’s Demography has always amazed the world because of its unprecedented outcomes in the presence of multifaceted socioeconomic and geographical characteristics. Being the first one to implement family panning in 1952, it occupies 2nd largest population of the world, with some of its state like Uttar Pradesh contributing 5th largest population to the world population surpassing Brazil. Being the one with higher in number it is more prone to the demographic disparity persisting into its territories brought upon by the inequalities in availability, accessibility and attainability of socioeconomic and various other resources. Fifth goal of Millennium Development Goal emphasis to improve maternal and child health across the world as Children’s development is very important for the overall development of society and the best way to develop national human resources is to take care of children. The target is to reduce the infant deaths by three quarters between 1990 and 2015. Child health status depends on the care and delivery by trained personnel, particularly through institutional facilities which is further associated with the status of the mother. However, delivery in institutional facilities and delivery by skilled personnel are rising slowly in India. The main objective of the present study is to measure the child health status on based on the educational and occupational background of the women in India. Study indicates that women education plays a very crucial role in deciding the health of the new born care and access to family planning, but the women autonomy indicates to have mixed results in different states of India. It is observed that rural women are 1.61 times more likely to exclusive breastfed their children compared to urban women. With respect to Hindu category, women belonging to other religious community were 21 percent less likely to exclusive breastfed their child. Taking scheduled caste as reference category, the odds of exclusive breastfeeding is found to be decreasing in comparison to other castes, and it is found to be significant among general category. Women of high education status have higher odds of using family planning methods in most of the southern states of India. By and large, girls and boys are about equally undernourished. Under nutrition is generally lower for first births than for subsequent births and consistently increases with increasing birth order for all measures of nutritional status. It is to be noted that at age 12-23 months, when many children are being weaned from breast milk, 30 percent of children are severely stunted and around 21 percent are severely underweight. So, this paper presents the evidence on the patterns of prevailing child health status in India and its states with reference to the mother socioeconomics and biological characteristics and examines trends in these, and discusses plausible explanations.

Keywords: immunization, exclusive breastfeeding, under five mortality, binary logistic regression, ordinal regression and life table

Procedia PDF Downloads 251

Authors: Yiorgos Hadjichristou

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The paper will focus on the hybrid living typologies which are brought about due to the Global Crisis. Mixing of the generations and the groups of people, mingling the functions of living with working and socializing, merging the act of living in synergy with the urban realm and its constituent elements will be the springboard of proposing an essential sustainable housing approach and the respective urban development. The thematic will be based on methodologies developed both on the academic, educational environment including participation of students’ research and on the practical aspect of architecture including case studies executed by the author in the island of Cyprus. Both paths of the research will deal with the explorative understanding of the hybrid ways of living, testing the limits of its autonomy. The evolution of the living typologies into substantial hybrid entities, will deal with the understanding of new ways of living which include among others: re-introduction of natural phenomena, accommodation of the activity of work and services in the living realm, interchange of public and private, injections of communal events into the individual living territories. The issues and the binary questions raised by what is natural and artificial, what is private and what public, what is ephemeral and what permanent and all the in-between conditions are eloquently traced in the everyday life in the island. Additionally, given the situation of Cyprus with the eminent scar of the dividing ‘Green line’ and the waiting of the ‘ghost city’ of Famagusta to be resurrected, the conventional way of understanding the limits and the definitions of the properties is irreversibly shaken. The situation is further aggravated by the unprecedented phenomenon of the crisis on the island. All these observations set the premises of reexamining the urban development and the respective sustainable housing in a synergy where their characteristics start exchanging positions, merge into each other, contemporarily emerge and vanish, changing from permanent to ephemeral. This fluidity of conditions will attempt to render a future of the built- and unbuilt realm where the main focusing point will be redirected to the human and the social. Weather and social ritual scenographies together with ‘spontaneous urban landscapes’ of ‘momentary relationships’ will suggest a recipe for emerging urban environments and sustainable living. Thus, the paper will aim at opening a discourse on the future of the sustainable living merged in a sustainable urban development in relation to the imminent solution of the division of island, where the issue of property became the main obstacle to be overcome. At the same time, it will attempt to link this approach to the global need for a sustainable evolution of the urban and living realms.

Keywords: social ritual scenographies, spontaneous urban landscapes, substantial hybrid entities, re-introduction of natural phenomena

Procedia PDF Downloads 250

Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

Procedia PDF Downloads 104

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

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

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

Procedia PDF Downloads 266

Authors: Scott M. Black, Craig Maclean, Pauline Hall Barrientos, Konstantinos Ritos, Asimina Kazakidi

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Aortic aneurysms and dissections are leading causes of death in cardiovascular disease. Both inevitably lead to hemodynamic instability without surgical intervention in the form of vascular stent-graft deployment. An accurate description of the aortic geometry and blood flow in patient-specific cases is vital for treatment planning and long-term success of such grafts, as they must generate physiological branch perfusion and in-stent hemodynamics. The aim of this study was to create patient-specific computational fluid dynamics (CFD) models through a multi-modality, multi-dimensional approach with boundary condition optimization to predict branch flow rates and in-stent hemodynamics in custom stent-graft configurations. Three-dimensional (3D) thoracoabdominal aortae were reconstructed from four-dimensional flow-magnetic resonance imaging (4D Flow-MRI) and computed tomography (CT) medical images. The former employed a novel approach to generate and enhance vessel lumen contrast via through-plane velocity at discrete, user defined cardiac time steps post-hoc. To produce patient-specific boundary conditions (BCs), the aortic geometry was reduced to a one-dimensional (1D) model. Thereafter, a zero-dimensional (0D) 3-Element Windkessel model (3EWM) was coupled to each terminal branch to represent the distal vasculature. In this coupled 0D-1D model, the 3EWM parameters were optimized to yield branch flow waveforms which are representative of the 4D Flow-MRI-derived in-vivo data. Thereafter, a 0D-3D CFD model was created, utilizing the optimized 3EWM BCs and a 4D Flow-MRI-obtained inlet velocity profile. A sensitivity analysis on the effects of stent-graft configuration and BC parameters was then undertaken using multiple stent-graft configurations and a range of distal vasculature conditions. 4D Flow-MRI granted unparalleled visualization of blood flow throughout the cardiac cycle in both the pre- and postsurgical states. Segmentation and reconstruction of healthy and stented regions from retrospective 4D Flow-MRI images also generated 3D models with geometries which were successfully validated against their CT-derived counterparts. 0D-1D coupling efficiently captured branch flow and pressure waveforms, while 0D-3D models also enabled 3D flow visualization and quantification of clinically relevant hemodynamic parameters for in-stent thrombosis and graft limb occlusion. It was apparent that changes in 3EWM BC parameters had a pronounced effect on perfusion distribution and near-wall hemodynamics. Results show that the 3EWM parameters could be iteratively changed to simulate a range of graft limb diameters and distal vasculature conditions for a given stent-graft to determine the optimal configuration prior to surgery. To conclude, this study outlined a methodology to aid in the prediction post-surgical branch perfusion and in-stent hemodynamics in patient specific cases for the implementation of custom stent-grafts.

Keywords: 4D flow-MRI, computational fluid dynamics, vascular stent-grafts, windkessel

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Authors: Dolly Kumari, H. Lhungdim

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Maternal health is one of the crucial health indicators for any country. 5th goal of Millennium Development Goals is also emphasising on improvement of maternal health. Soon after Independence government of India realizing the importance of maternal and child health care services, and took steps to strengthen in 1st and 2nd five year plans. In past decade the other health indicator which is life expectancy at birth has been observed remarkable improvement. But still maternal mortality is high in India and in some states it is observe much higher than national average. Government of India pour lots of fund and initiate National Rural Health Mission (NRHM) in 2005 to improve maternal health in country by providing affordable and accessible health care services. Accredited Social Heath Activist (ASHA) is one of the key components of the NRHM. Mainly ASHAs are selected female aged 25-45 years from village itself and accountable for the monitoring of maternal health care for the same village. ASHA are trained to works as an interface between the community and public health system. This study tries to assess the role of ASHA in utilizing maternal health care services and to see the level of awareness about benefits given under JSY scheme and utilization of those benefits by eligible women. For the study concurrent evaluation data from National Rural health Mission (NRHM), initiated by government of India in 2005 has been used. This study is based on 78205 currently married women from 70 different districts of India. Descriptive statistics, chi2 test and binary logistic regression have been used for analysis. The probability of institutional delivery increases by 2.03 times (p<0.001) while if ASHA arranged or helped in arranging transport facility the probability of institutional delivery is increased by 1.67 times (p<0.01) than if she is not arranging transport facility. Further if ASHA facilitated to get JSY card to the pregnant women probability of going for full ANC is increases by 1.36 times (p<0.05) than reference. However if ASHA discuses about institutional delivery and approaches to get register than probability of getting TT injection is 1.88 and 1.64 times (p<0.01) higher than that if she did not discus. Further, Probability of benefits from JSY schemes is 1.25 times (p<0.001) higher among women who get married after 18 years. The probability of benefits from JSY schemes is 1.25 times (p<0.001) higher among women who get married after 18 year of age than before 18 years, it is also 1.28 times (p<0.001) and 1.32 times (p<0.001) higher among women have 1 to 8 year of schooling and with 9 and above years of schooling respectively than the women who never attended school. Those women who are working have 1.13 times (p<0.001) higher probability of getting benefits from JSY scheme than not working women. Surprisingly women belongs to wealthiest quintile are .53times (P<0.001) less aware about JSY scheme. Results conclude that work done by ASHA has great influence on maternal health care utilization in India. But results also show that still substantial numbers of needed population are far from utilization of these services. Place of delivery is significantly influenced by referral and transport facility arranged by ASHA.

Keywords: institutional delivery, JSY beneficiaries, referral faculty, public health

Procedia PDF Downloads 311

Authors: Alicia Ettlin

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Amid the rise of neoliberalism to the leading economic policy model in Western societies in the 1980s, people have started to internalise a neoliberal way of thinking, whereby the human body has become an entity that can and needs to be precisely managed through free yet rational decision-making processes. The neoliberal citizen has consequently become an entrepreneur of the self who is free, independent, rational, productive and responsible for themselves, their health and wellbeing as well as their appearance. The focus on individuals as entrepreneurs who manage their bodies through the rationally thinking mind has, however, become increasingly criticised for viewing the social actor as ‘disembodied’, as a detached, social actor whose powerful mind governs over the passive body. On the other hand, the discourse around embodiment seeks to connect rational decision-making processes to the dominant neoliberal discourse which creates an embodied understanding that the body, just as other areas of people’s lives, can and should be shaped, monitored and managed through cognitive and rational thinking. This perspective offers an understanding of the body regarding its connections with the social environment that reaches beyond the debates around mind-body binary thinking. Hence, following this argument, body management should not be thought of as either solely guided by embodied discourses nor as merely falling into a mind-body dualism, but rather, simultaneously and inseparably as both at once. The descriptive, qualitative analysis of semi-structured in-depth interviews conducted with young Australian amateur athletes between the age of 18 and 24 has shown that most participants are interested in measuring and managing their body to create self-knowledge and self-improvement. The participants thereby connected self-improvement to weight loss, muscle gain or simply staying fit and healthy. Self-knowledge refers to body measurements including weight, BMI or body fat percentage. Self-management and self-knowledge that are reliant on one another to take rational and well-thought-out decisions, are both characteristic values of the neoliberal doctrine. A neoliberal way of thinking and looking after the body has also by many been connected to rewarding themselves for their discipline, hard work or achievement of specific body management goals (e.g. eating chocolate for reaching the daily step count goal). A few participants, however, have shown resistance against these neoliberal values, and in particular, against the precise monitoring and management of the body with the help of self-tracking devices. Ultimately, however, it seems that most participants have internalised the dominant discourses around self-responsibility, and by association, a sense of duty to discipline their body in normative ways. Even those who have indicated their resistance against body work and body management practices that follow neoliberal thinking and measurement systems, are aware and have internalised the concept of the rational operating mind that needs or should decide how to look after the body in terms of health but also appearance ideals. The discussion around the collected data thereby shows that embodiment and the mind/body dualism constitute two connected, rather than two separate or opposing concepts.

Keywords: dualism, embodiment, mind, neoliberalism

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Authors: Navid Kaboudi, Ali Shayanfar

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Introduction: Feeding infants with safe milk from the beginning of their life is an important issue. Drugs which are used by mothers can affect the composition of milk in a way that is not only unsuitable, but also toxic for infants. Consuming permeable drugs during that sensitive period by mother could lead to serious side effects to the infant. Due to the ethical restrictions of drug testing on humans, especially women, during their lactation period, computational approaches based on structural parameters could be useful. The aim of this study is to develop mechanistic models to predict the M/P ratio of drugs during breastfeeding period based on their structural descriptors. Methods: Two hundred and nine different chemicals with their M/P ratio were used in this study. All drugs were categorized into two groups based on their M/P value as Malone classification: 1: Drugs with M/P>1, which are considered as high risk 2: Drugs with M/P>1, which are considered as low risk Thirty eight chemical descriptors were calculated by ACD/labs 6.00 and Data warrior software in order to assess the penetration during breastfeeding period. Later on, four specific models based on the number of hydrogen bond acceptors, polar surface area, total surface area, and number of acidic oxygen were established for the prediction. The mentioned descriptors can predict the penetration with an acceptable accuracy. For the remaining compounds (N= 147, 158, 160, and 174 for models 1 to 4, respectively) of each model binary regression with SPSS 21 was done in order to give us a model to predict the penetration ratio of compounds. Only structural descriptors with p-value<0.1 remained in the final model. Results and discussion: Four different models based on the number of hydrogen bond acceptors, polar surface area, and total surface area were obtained in order to predict the penetration of drugs into human milk during breastfeeding period About 3-4% of milk consists of lipids, and the amount of lipid after parturition increases. Lipid soluble drugs diffuse alongside with fats from plasma to mammary glands. lipophilicity plays a vital role in predicting the penetration class of drugs during lactation period. It was shown in the logistic regression models that compounds with number of hydrogen bond acceptors, PSA and TSA above 5, 90 and 25 respectively, are less permeable to milk because they are less soluble in the amount of fats in milk. The pH of milk is acidic and due to that, basic compounds tend to be concentrated in milk than plasma while acidic compounds may consist lower concentrations in milk than plasma. Conclusion: In this study, we developed four regression-based models to predict the penetration class of drugs during the lactation period. The obtained models can lead to a higher speed in drug development process, saving energy, and costs. Milk/plasma ratio assessment of drugs requires multiple steps of animal testing, which has its own ethical issues. QSAR modeling could help scientist to reduce the amount of animal testing, and our models are also eligible to do that.

Keywords: logistic regression, breastfeeding, descriptors, penetration

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Authors: Stojan Kravanja, Andrej Ivanič, Tomaž Žula

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This contribution focuses on structural optimization in civil engineering using mixed integer non-linear programming (MINLP). MINLP is characterized as a versatile method that can handle both continuous and discrete optimization variables simultaneously. Continuous variables are used to optimize parameters such as dimensions, stresses, masses, or costs, while discrete variables represent binary decisions to determine the presence or absence of structural elements within a structure while also calculating discrete materials and standard sections. The optimization process is divided into three main steps. First, a mechanical superstructure with a variety of different topology-, material- and dimensional alternatives. Next, a MINLP model is formulated to encapsulate the optimization problem. Finally, an optimal solution is searched in the direction of the defined objective function while respecting the structural constraints. The economic or mass objective function of the material and labor costs of a structure is subjected to the constraints known from structural analysis. These constraints include equations for the calculation of internal forces and deflections, as well as equations for the dimensioning of structural components (in accordance with the Eurocode standards). Given the complex, non-convex and highly non-linear nature of optimization problems in civil engineering, the Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm is applied. This algorithm alternately solves subproblems of non-linear programming (NLP) and main problems of mixed-integer linear programming (MILP), in this way gradually refines the solution space up to the optimal solution. The NLP corresponds to the continuous optimization of parameters (with fixed topology, discrete materials and standard dimensions, all determined in the previous MILP), while the MILP involves a global approximation to the superstructure of alternatives, where a new topology, materials, standard dimensions are determined. The optimization of a convex problem is stopped when the MILP solution becomes better than the best NLP solution. Otherwise, it is terminated when the NLP solution can no longer be improved. While the OA/ER algorithm, like all other algorithms, does not guarantee global optimality due to the presence of non-convex functions, various modifications, including convexity tests, are implemented in OA/ER to mitigate these difficulties. The effectiveness of the proposed MINLP approach is demonstrated by its application to various structural optimization tasks, such as mass optimization of steel buildings, cost optimization of timber halls, composite floor systems, etc. Special optimization models have been developed for the optimization of these structures. The MINLP optimizations, facilitated by the user-friendly software package MIPSYN, provide insights into a mass or cost-optimal solutions, optimal structural topologies, optimal material and standard cross-section choices, confirming MINLP as a valuable method for the optimization of structures in civil engineering.

Keywords: MINLP, mixed-integer non-linear programming, optimization, structures

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Authors: Samil Ozcan

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Airlines companies target different customer segments in consideration of pricing, service quality, flight network, etc. and their brand positioning accords with the marketization strategies developed in the same direction. The object of this study, Turkish Airlines, has many peculiarities regarding its brand positioning as compared to its rivals in the sector. In the first place, it appeals to a global customer group because of its Star Alliance membership and its broad flight network with 315 destination points. The second group in its customer segmentation includes domestic customers. For this group, the company follows a marketing strategy that plays to local culture and accentuates the image of Turkishness as an emotional allurement. The advertisements and publicity projects designed in this regard put little emphasis on the service quality the company offers to its clients; it addresses the emotions of the consumers rather than individual benefits and relies on the historical memory of the nation and shared cultural values. This study examines the publicity work which aims at the second segment customer group focusing on Turkish Airlines’ 85th Anniversary Commercial through a symbolic meaning analysis approach. The commercial presents six stories with undertones of nationalism in its theme. Nationalism is not just the product of collective interests based on reason but a result of patriotism in the sense of loyalty to state and nation and love of ethnic belonging. While nationalism refers to concrete notions such as blood tie, common ancestor, shared history, it is not the actuality of these notions that it draws its real strength but the emotions invested in them. The myths of origin, the idea of common homeland, boundary definitions, and symbolic acculturation have instrumental importance in the development of these commonalities. The commercial offers concrete examples for an analysis of Connor’s definition of nationalism based on emotions. Turning points in the history of the Turkish Republic and the historical mission Turkish Airlines undertook in these moments are narrated in six stories in the commercial with a highly emotional theme. These emotions, in general, depend on collective memory generated by national consciousness. Collective memory is not simply remembering the past. It is constructed through the reconstruction and reinterpretation of the past in the present moment. This study inquires the motivations behind the nationalist emotions generated within the collective memory by engaging with the commercial released for the 85th anniversary of Turkish Airlines as the object of analysis. Symbols and myths can be read as key concepts that reveal the relation between 'identity and memory'. Because myths and symbols do not merely reflect on collective memory, they reconstruct it as well. In this sense, the theme of the commercial defines the image of Turkishness with virtues such as self-sacrifice, helpfulness, humanity, and courage through a process of meaning creation based on symbolic mythologizations like flag and homeland. These virtues go beyond describing the image of Turkishness and become an instrument that defines and gives meaning to Turkish identity.

Keywords: collective memory, emotions, identity, nationalism

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Authors: Igor Guatelli

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The universe of aesthetic perception entails impasses about sensitive divergences that each text or visual object may be subjected to. If approached through intertextuality that is not based on the misleading notion of kinships or similarities a priori admissible, the possibility of anachronistic, heterogeneous - and non-diachronic - assemblies can enhance the emergence of interval movements, intermediate, and conflicting, conducive to a method of reading, interpreting, and assigning meaning that escapes the rigid antinomies of the mere being and non-being of things. In negative, they operate in a relationship built by the lack of an adjusted meaning set by their positive existences, with no remainders; the generated interval becomes the remnant of each of them; it is the opening that obscures the stable positions of each one. Without the negative of absence, of that which is always missing or must be missing in a text, concept, or image made positive by history, nothing is perceived beyond what has been already given. Pairings or binary oppositions cannot lead only to functional syntheses; on the contrary, methodological disturbances accumulated by the approximation of signs and entities can initiate a process of becoming as an opening to an unforeseen other, transformation until a moment when the difficulties of [re]conciliation become the mainstay of a future of that sign/entity, not envisioned a priori. A counter-history can emerge from these unprecedented, misadjusted approaches, beginnings of unassigned injunctions and disjunctions, in short, difficult alliances that open cracks in a supposedly cohesive history, chained in its apparent linearity with no remains, understood as a categorical historical imperative. Interstices are minority fields that, because of their opening, are capable of causing opacity in that which, apparently, presents itself with irreducible clarity. Resulting from an incomplete and maladjusted [at the least dual] marriage between the signs/entities that originate them, this interval may destabilize and cause disorder in these entities and their own meanings. The interstitials offer a hyphenated relationship: a simultaneous union and separation, a spacing between the entity’s identity and its otherness or, alterity. One and the other may no longer be seen without the crack or fissure that now separates them, uniting, by a space-time lapse. Ontological, semantic shifts are caused by this fissure, an absence between one and the other, one with and against the other. Based on an improbable approximation between some conceptual and semantic shifts within the design production of architect Rem Koolhaas and the textual production of the philosopher Jacques Derrida, this article questions the notion of unity, coherence, affinity, and complementarity in the process of construction of thought from these ontological, epistemological, and semiological fissures that rattle the signs/entities and their stable meanings. Fissures in a thought that is considered coherent, cohesive, formatted are the negativity that constitutes the interstices that allow us to move towards what still remains as non-identity, which allows us to begin another story.

Keywords: clearing, interstice, negative, remnant, spectrum

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