Academic literature on the topic 'Cluster weighted mod'
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Journal articles on the topic "Cluster weighted mod"
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Dou, Nan, Evaniya Shakya, Raphia Ngoutane, Roger Sodjinou, Christine Kaligirwa, Anne-Sophie Le Dain, Aashima Garg, et al. "Trends and Influencing Factors of Complementary Feeding Practices in Niger: An Analysis of National Surveys From 2000 – 2018." Current Developments in Nutrition 5, Supplement_2 (June 2021): 639. http://dx.doi.org/10.1093/cdn/nzab045_021.
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Abstract Objectives To examine the trends and influencing factors of suboptimal complementary feeding (CF) practices among children aged 6–23 months in Niger using national data from 2000 to 2018. Methods Using data from the 2000 Multiple Indicator Cluster Survey, 2012 Demographic and Health Surveys (DHS), and 2018 Standardized Monitoring and Assessment of Relief and Transitions survey in Niger, the trends and predictors of WHO-UNICEF CF indicators including timely introduction of complementary foods (INTRO), minimum meal frequency (MMF), minimum dietary diversity (MDD), and minimum acceptable diet (MAD) were estimated. Using the most completed data in CF and influencing factors (available from 2012 DHS), multilevel logistic regression models were applied to identify factors at the individual, household and community levels that were associated with meeting INTRO, MMF, MDD, and MAD. Results The weighted proportion of children aged 6–8 months meeting INTRO increased from 56.0% in 2000 to 84.4% in 2018. The weighted proportion of children meeting MMF (51.3% to 77.9%), MDD (9.8% to 14.2%), and MAD (5.6% to 10.9%) also increased between 2012 - 2018. At the individual level, children with mothers who were employed had higher odds of meeting all four indicators as compared to those whose mothers were unemployed. Older child age and maternal exposure to media were significantly associated with higher odds of meeting MMF, MDD, and MAD. Maternal education and child birth weight greater or smaller than average (reference) were positively associated with the odds of meeting MMF and MAD, and antenatal iron supplementation and currently breastfeeding were positively associated with the odds of achieving MDD and MAD. At the household level, the odds of meeting MMD and MAD were higher among children from wealthier households. At the community level, the odds of meeting INTRO and MMF were higher among children from communities with greater access to health services. Conclusions Despite the improvement in CF practices since 2000, only 10% of children from 6–23 months received minimum acceptable diets. Factors associated with CF were distributed across individual, household and community levels, suggesting the need for multi-level strategies to improve child nutrition in Niger. Funding Sources UNICEF West and Central Africa Regional Office (Grant # 43279190).
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Yoo, Jaewon, Jongwan Ko, Cristiano G. Sabiu, Jihye Shin, Kyungwon Chun, Ho Seong Hwang, Juhan Kim, M. James Jee, Hyowon Kim, and Rory Smith. "Comparison of Spatial Distributions of Intracluster Light and Dark Matter." Astrophysical Journal Supplement Series 261, no. 2 (July 27, 2022): 28. http://dx.doi.org/10.3847/1538-4365/ac7142.
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Abstract In a galaxy cluster, the relative spatial distributions of dark matter, member galaxies, gas, and intracluster light (ICL) may connote their mutual interactions over the cluster’s evolution. However, it is a challenging problem to provide a quantitative measure for matching the shapes between two multidimensional scalar distributions. We present a novel methodology, named the weighted overlap coefficient (WOC), to quantify the similarity of two-dimensional spatial distributions. We compare the WOC with a standard method known as the modified Hausdorff distance (MHD) method. We find that our method is robust, and performs well even with the existence of multiple substructures. We apply our methodology to search for a visible component whose spatial distribution resembles that of dark matter. If such a component could be found to trace the dark-matter distribution with high fidelity for more relaxed galaxy clusters, then the similarity of the distributions could also be used as a dynamical stage estimator of the cluster. We apply the method to six galaxy clusters at different dynamical stages, simulated within a GRT simulation, which is an N-body simulation using the galaxy replacement technique. Among the various components (stellar particles, galaxies, ICL), the ICL+brightest cluster galaxy (BCG) component most faithfully traced the dark-matter distribution. Among the sample galaxy clusters, the relaxed clusters show stronger similarity in the spatial distribution of the dark matter and ICL+BCG than the dynamically young clusters, while the results of the MHD method show a weaker trend with the dynamical stages.
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Saperia, Sarah, Daniel Felsky, Susana Da Silva, Ishraq Siddiqui, Zafiris Daskalakis, Aristotle Voineskos, Neil Rector, Gary Remington, Konstantine Zakzanis, and George Foussias. "S119. A DIMENSIONAL APPROACH TO UNDERSTANDING COST-BENEFIT DECISION-MAKING IN SCHIZOPHRENIA AND DEPRESSION." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S80. http://dx.doi.org/10.1093/schbul/sbaa031.185.
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Abstract Background Reductions in motivation figure prominently in the clinical presentation of schizophrenia (SZ) and major depressive disorder (MDD). One critical nexus in the motivation system that drives real-world behaviour is effort-based decision-making (EBDM), which refers to the cost-benefit calculations involved in computing the amount of effort one is willing to expend in order to obtain a desired reward. Important individual differences are associated with these processes, and impairments in motivation can arise if any relevant cost-benefit information is not properly computed, appraised, or integrated. Thus, in order to better understand the computations guiding choice behaviour, the present study sought to utilize a more person-centric approach to characterize individual differences in the effort-cost computations that underlie cost-benefit decision-making in individuals with SZ and MDD. Methods A sample of 51 individuals with SZ, 43 individuals with MDD, and 51 healthy control (HC) participants underwent a comprehensive clinical and cognitive characterization, and completed the Effort Expenditure for Rewards Task (EEfRT) as a measure of EBDM. Random effects modelling was conducted to estimate the subject-specific predictors of reward magnitude, probability, and perceived cost on choice behaviour. Cluster analysis was subsequently applied to these predictors in order to identify subtypes of impairments within the entire sample, irrespective of diagnostic status. Results Data-driven cluster analysis identified unique subgroups of individuals with distinct patterns of utilizing cost-benefit information to guide effort-based decision-making. Analyses of variance revealed significant differences between clusters with respect to their utilization of reward (F (3, 133) = 51.58, p < .001), probability (F (3, 133) = 48.71, p < .001), and cost (F (3, 133) = 45.24, p < .001). The first cluster was characterized by an indifference to all cost-benefit information, the second cluster was more influenced by perceived cost, the third cluster demonstrated a preference for reward-based information, and the fourth cluster mainly utilized probability to guide their decision-making. While the clusters did not differ in their severity of clinical amotivation (p = .11), there was a significant effect for cognition, specifically with impairments in clusters 1 and 2. All diagnostic groups were represented in each cluster, but the distribution of SZ, MDD, and HC participants was significantly different (X2 (6, N = 137) = 16.18, p = .013). Discussion The emergence of four distinct subgroups in our sample suggests that there are individual differences amongst SZ, MDD, and HC participants in their utilization of cost-benefit information to guide choice behaviour. Moreover, with elevated levels of clinical amotivation present in all four clusters, it is possible that these unique cost-benefit decision-making patterns represent different underlying motivational impairments, the nature of which depending on how reward magnitude, probability, and perceived cost are weighed. Thus, by characterizing the specific mechanisms underlying EBDM in SZ and MDD, the results of this work may be able to help guide the identification of more precise targets for the effective treatment of motivation deficits.
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Hans, Kanwalgeet, Luke Mike, Robert Heidel, Paula Benavides, Robert Arnce, and Jan Talley. "Comorbid Patterns in the Homeless Population: A Theoretical Model to Enhance Patient Care." Western Journal of Emergency Medicine 23, no. 2 (February 23, 2022): 200–210. http://dx.doi.org/10.5811/westjem.2021.10.52539.
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Introduction: From the perspective of social determinants, homelessness perpetuates poor health and creates barriers to effective chronic disease management, necessitating frequent use of emergency department (ED) services. In this study we developed a screening algorithm (checklist) from common comorbidities observed in the homeless population in the United States. The result was a theoretical screening tool (checklist) to aid healthcare workers in the ED, including residents, medical students, and other trainees, to provide more efficacious treatment and referrals for discharge. Methods: In this retrospective cohort study we used the Nationwide Emergency Department Sample (NEDS) to investigate comorbidities and ED utilization patterns relating to 23 injury-related, psychiatric, and frequent chronic medical conditions in the US adult (≥18 years of age) homeless population. Cases were identified from the NEDS database for 2014–2017 using International Classification of Diseases, 9th and 10 revisions, and Clinical Classification Software diagnosis codes. We performed a two-step cluster analysis including pathologies with ≥10% prevalence in the sample to identify shared comorbidities. We then compared the clusters by sociodemographic and ED-related characteristics, including age, gender, primary payer, and patient disposition from the ED. Chi-square analysis was used to evaluate categorical variables (ie, gender, primary payer, patient disposition from the ED), and analysis of variance for continuous variables (age). Results: The study included 1,715,777 weighted cases. The two-step cluster analysis identified nine groups denominated by most prevalent disease: 1) healthy; 2) mixed psychiatric; 3) major depressive disorder (MDD); 4) psychosis; 5) addiction; 6) essential hypertension; 7) chronic obstructive pulmonary disease (COPD); 8) infectious disease; and (9) injury. The MDD, COPD, infectious disease, and Injury clusters demonstrated the highest prevalence of co-occurring disease, with the MDD cluster displaying the highest proportion of comorbidities. Although the addiction cluster existed independently, substance use was pervasive in all except the healthy cluster (prevalence 36-100%). We used the extracted screening algorithm to establish a screening tool (checklist) for ED healthcare workers, with physicians as the first point of contact for the initial use of the screening tool. Conclusion: Healthcare workers in the ED, including residents, medical students, and other trainees, provide services for homeless ED users. Screening tools (checklists) can help coordinate care to improve treatment, referrals, and follow-up care to reduce hospital readmissions. The screening tool may expedite targeted interventions for homeless patients with commonly occurring patterns of disease.
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Tamang, Bir Bahadur, Manoj Kumar Shah, Bishnu Dhakal, Pashupati Chaudhary, and Netra Chhetri. "Participatory ranking of fodders in the western hills of Nepal." Journal of Agriculture and Natural Resources 3, no. 1 (January 1, 2020): 20–28. http://dx.doi.org/10.3126/janr.v3i1.27001.
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Fodder is an important source of feed of the ruminants in Nepal. In the mid hills of Nepal, farmers generally practice integrated farming system that combines crop cultivation with livestock husbandry and agroforestry. Tree fodders are good sources of protein during the forage and green grass scarcity periods especially in dry season. Local communities possess indigenous knowledge for the selection of grasses and tree fodders at different seasons in mid hills of western Nepal. A study was conducted on the perception of farmers with respect to selection of fodder species in eight clusters in Kaski and Lumjung districts that range 900-2000 meter above sea level and receive average precipitation of 2000- 4500mm per annum. During the fodder preference ranking, farmers prepared the inventory of fodders found around the villages and nearby forests and selected top ten most important fodders in terms of their availability, palatability, fodder yield, milk yield and milk fat yield. In total, 23 top ranking fodders species were selected from the eight clusters. These fodder species were also ranked using pairwise ranking and weighted scoring methods and ranking was done on the basis of merit numbers obtained from weighted scores. The analysis revealed Artocarpus lakoocha as best tree fodder followed by Ficus semicordata, Thysanolena maxima and Ficus calvata. Similarly, the calendar of fodders trees for lopping season and the best feeding time was prepared on the basis of farmers’ local knowledge. This study suggests strategies for promotion of locally preferred tree fodder species and supplementing tree fodder with feed in different seasons depending on their availability and local preferences.
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Choi, Kwan Woo, Soonwook Kwon, Sung-Bom Pyun, and Woo-Suk Tae. "Shape Deformation in the Brainstem of Medication-Naïve Female Patients with Major Depressive Disorder." Psychiatry Investigation 17, no. 5 (May 15, 2020): 465–74. http://dx.doi.org/10.30773/pi.2020.0025.
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Objective Although neuroimaging studies have shown volumetric reductions, such as the anterior cingulate, prefrontal cortices, and hippocampus in patients with major depressive disorder (MDD), few studies have investigated the volume of or shape alterations in the subcortical regions and the brainstem. We hypothesized that medication-naïve female adult patients with MDD might present with shape and volume alterations in the subcortical regions, including the brainstem, compared to healthy controls (HCs).Methods A total of 20 medication-naïve female patients with MDD and 21 age-matched female HCs, underwent 3D T1-weighted structural magnetic resonance scanning. We analyzed the volumes of each subcortical region and each brainstem region, including the midbrain, pons, and medulla oblongata. We also performed surface-based vertex analyses on the subcortical areas and brainstem.Results Female patients with MDD showed non-significant volumetric differences in the subcortical regions, whole brainstem, and each brainstem region compared to the HCs. However, in the surface-based vertex analyses, significant shape contractions were observed in both cerebellar peduncles located on the lateral wall of the posterior brainstem [threshold-free cluster enhancement, corrected for family-wise error (FWE) at p<0.05] in patients with MDD.Conclusion We revealed shape alterations in the posterior brainstem in female patients with MDD.
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Gruebner, Oliver, Sarah R. Lowe, Melissa Tracy, Magdalena Cerdá, Spruha Joshi, Fran H. Norris, and Sandro Galea. "The Geography of Mental Health and General Wellness in Galveston Bay After Hurricane Ike: A Spatial Epidemiologic Study With Longitudinal Data." Disaster Medicine and Public Health Preparedness 10, no. 2 (January 28, 2016): 261–73. http://dx.doi.org/10.1017/dmp.2015.172.
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AbstractObjectivesTo demonstrate a spatial epidemiologic approach that could be used in the aftermath of disasters to (1) detect spatial clusters and (2) explore geographic heterogeneity in predictors for mental health and general wellness.MethodsWe used a cohort study of Hurricane Ike survivors (n=508) to assess the spatial distribution of postdisaster mental health wellness (most likely resilience trajectory for posttraumatic stress symptoms [PTSS] and depression) and general wellness (most likely resilience trajectory for PTSS, depression, functional impairment, and days of poor health) in Galveston, Texas. We applied the spatial scan statistic (SaTScan) and geographically weighted regression.ResultsWe found spatial clusters of high likelihood wellness in areas north of Texas City and spatial concentrations of low likelihood wellness in Galveston Island. Geographic variation was found in predictors of wellness, showing increasing associations with both forms of wellness the closer respondents were located to Galveston City in Galveston Island.ConclusionsPredictors for postdisaster wellness may manifest differently across geographic space with concentrations of lower likelihood wellness and increased associations with predictors in areas of higher exposure. Our approach could be used to inform geographically targeted interventions to promote mental health and general wellness in disaster-affected communities. (Disaster Med Public Health Preparedness. 2016;10:261–273)
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Murti, Michelle, Tesfaye Bayleyegn, Martha Stanbury, William Dana Flanders, Ellen Yard, Mawuli Nyaku, and Amy Wolkin. "Household Emergency Preparedness by Housing Type from a Community Assessment for Public Health Emergency Response (CASPER), Michigan." Disaster Medicine and Public Health Preparedness 8, no. 1 (February 2014): 12–19. http://dx.doi.org/10.1017/dmp.2013.111.
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AbstractObjectivesWe examined the association between housing type and household emergency preparedness among households in Oakland County, Michigan.MethodsWe used interview data on household emergency preparedness from a cluster design survey in Oakland County, Michigan, in 2012. We compared survey-weighted frequencies of household demographics, medical conditions, and preparedness measures in single-detached homes versus multi-unit dwellings, and determined the unadjusted odds ratios (OR) and the income-level adjusted OR for each preparedness measure.ResultsHouseholds had similar demographics and medical conditions between housing types. Unadjusted ORs were statistically significant for single detached homes having a generator (11.1), back-up heat source (10.9), way to cook without utilities (5.8), carbon monoxide (CO) detector (3.8), copies of important documents (3.4), evacuation routes (3.1), and 3-day supply of water (2.5). Income level adjusted ORs remained statistically significant except for owning a CO detector.ConclusionsHouseholds in multi-unit dwellings were less likely to have certain recommended emergency plans and supplies compared to those in single detached homes. Further research is required to explore the feasibility, barriers, and alternatives for households in multi-unit dwellings in terms of complying with these measures. (Disaster Med Public Preparedness. 2014;0:1–8)
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Alkanhel, Reem, Amir Chaaf, Nagwan Abdel Samee, Manal Abdullah Alohali, Mohammed Saleh Ali Muthanna, Dmitry Poluektov, and Ammar Muthanna. "DEDG: Cluster-Based Delay and Energy-Aware Data Gathering in 3D-UWSN with Optimal Movement of Multi-AUV." Drones 6, no. 10 (October 1, 2022): 283. http://dx.doi.org/10.3390/drones6100283.
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The monitoring of underwater aquatic habitats and pipeline leakages and disaster prevention are assisted by the construction of an underwater wireless sensor network (UWSN). The deployment of underwater sensors consumes energy and causes delay when transferring the gathered sensed data via multiple hops. The consumption of energy and delays are minimized by means of an autonomous unmanned vehicle (AUV). This work addresses the idea of reducing energy and delay by incorporating an AUVs-assisted, three-dimensional UWSN (3D-UWSN) called DEDG 3D-UWSN. Energy in the sensor nodes is saved by clustering and scheduling; on the other hand, the delay is minimized by the movement of the AUV and inter-cluster routing. In clustering, multi-objective spotted hyena optimization (MO-SHO) is applied for the selection of the best sensor for the cluster head, which is responsible for assigning sleep schedules for members. According to the total number of members, an equal half of the members is provided with sleep slots based on the energy and hop counts. The redundancy in the gathered data is eliminated by measuring the Hassanat distance. Then, the moving AUV is able to predict its movement by the di-factor actor–critic path prediction method. The mid-point among the four heads is determined so that the AUV can collect data from four heads at a time. In cases where the waiting time of the CH is exceeded, three-step, inter-cluster routing is executed. The three steps are the discovery of possible routes, ignoring the longest paths and validating the filtered path with a fuzzy–LeNet method. In this 3D-UWSN, the sensed data are not always normal, and, hence, a weighted method is presented to transfer emergency events by selecting forwarders. This work is implemented on Network Simulator version 3.26 to test the results. It achieves better efficiency in terms of data collection delay, end-to-end delay, AUV tour length, network lifetime, number of alive nodes and energy consumption.
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Suganthi, R., and Dr K. Prabha. "An Adaptive Density Peak Clustering with Swarm Intelligence Algorithm for Detection of Overlapping Communities in Social Networks." Journal of Internet Services and Information Security 12, no. 4 (November 30, 2022): 204–23. http://dx.doi.org/10.58346/jisis.2022.i4.015.
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Community identification is an important technique for the investigation of complex networks because it makes it possible to examine mesoscopic features that are often connected to the organisational and functional properties of the underlying networks. In social media, there are billions of vertices and a variety of connections, thus community identification is a widely acknowledged approach of addressing the problem of grouping users. However, traditional methods are insufficient because of this. For the purpose of analysing social networks, overlapping community identification is crucial. On networks with complicated weight distributions, the current overlapping community recognition techniques seldom provide good results. Communities of any form may be easily and precisely found using density peaks clustering (DPC). Nevertheless, it also uses the truncation distance, and therefore is unable to automatically determine where the cluster centre is located. In this research work, an Adaptive density peak clustering (ADPC) with Modified Dragonfly Optimization (MDO) a suggested algorithm will decide the communities in a social network in an adaptable manner. Initially, the preprocessing methods such as Stemming, Stop-words removal, and Tokenization by bigrams, 1-to-3 grammars, and the unigram are three distinct types of data formats. Two feature extraction filters: Word Embedding Feature Extraction, and Term Frequency-Inverse Document Frequency (TF-IDF). In the Adaptive density peak clustering (ADPC) with Modified Dragonfly Optimization (MDO) algorithm, the clustering process is completed by determining the clustering centre by the MDO after determining the new local density based on the new neighborhood connection. ADPC-MDO adds a unique distance function based on common nodes to estimate the distance between nodes and takes weights into account to handle both weighted and unweighted social networks. A technique based on transitive consensus matrix building is used to generate a consensus matrix, which provides representative information of all dendrograms. Given a social networks dataset with a complicated weight distribution, the results show that the suggested ADPC-MDO performs better.
Dissertations / Theses on the topic "Cluster weighted mod"
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BARBERIS, STEFANO. "New developments in Cluster-Weighted Modeling." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2019. http://hdl.handle.net/10281/241157.
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In questo lavoro vengono presentate due estensioni del modello Cluster Weighted (un modello mistura di regressioni che considera non solo la distribuzione condizionata ma anche la distribuzione marginale delle covariate).
La prima estensione proposta presenta il modello GAM-CWM. Si tratta di un modello molto flessibile, in grado di descrivere relazioni complesse tra una variabile risposta e un insieme di covariate in ogni componente della mistura. In questo modello proposto la classe dei Generalized Additive Models è stata inserita all’interno del framework CWM.
La seconda estensione, è relativa alla regressione beta che rappresenta l'approccio standard per modellare una variabile dipendente in [0,1]. In alcune situazioni, un problema che potrebbe sorgere è una conseguenza diretta della flessibilità della distribuzione beta, perché quando viene utilizzata come componente in un modello mistura potrebbe essere troppo flessibile a causa della grande varietà di forme (incluse le forme multimodali) che può assumere. In questo caso quindi può essere difficile capire e interpretare il significato di ciascun gruppo latente. Per questo motivo, abbiamo sviluppato un'estensione dei modelli mistura di beta focalizzandoci sul sottoinsieme della distribuzioni beta unimodali, con l'obiettivo di migliorare l'interpretazione di ciascun componente e quindi interpretare meglio il rispettivo cluster nella popolazione.
Infine, un pacchetto R in fase di sviluppo che sarà pubblicato sul CRAN implementa le metodologie proposte.
La stima di questi modelli viene eseguita tramite la massima verosimiglianza con l'algoritmo EM. Con dati simulati e reali esaminiamo le prestazioni, i limiti e i benefici confrontando i nuovi modelli proposti con modelli simili presentati e disponibili in letteratura.In this work two extensions of Cluster Weighted Models (a mixture model with random covariate) are presented for model-based clustering applications. The first presents the Generalized Additive Cluster Weighted Model. This is a very flexible model, able to capture complex relations between a response variable and a set of covariates in each mixture component introducing the Generalized Additive Model into the CWM framework. The second, is related to the beta regression that represents the standard approach to model a dependent variable with the range in the unit interval [0,1]. In some situations, a problem that could arise is a direct consequence of flexibility of the beta distribution, because when it is considered as a mixture component it may be too flexible due to the great variety of shapes (including multi-modal shapes) that can assume so that it may be difficult to understand easily the real meaning of each component. For this reason, we developed an extension of the beta mixture models focusing on the subset of unimodal beta distribution, with the aim of improving the interpretation of each mixture component and then identifying better the respective cluster in the population. Finally, an R package under development that will published on the CRAN implements the proposed methodologies. The estimation of these models is performed via maximum likelihood with EM algorithm. With simulated and real data we investigate the performances, limits and benefits comparing this model with other models related to it.
Book chapters on the topic "Cluster weighted mod"
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Isaksen, Arne, and James Karlsen. "Combined and Complex Mode of Innovation in Regional Cluster Development: Analysis of the Light-Weight Material Cluster in Raufoss, Norway." In Interactive Learning for Innovation, 115–36. London: Palgrave Macmillan UK, 2012. http://dx.doi.org/10.1057/9780230362420_6.
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Lee, Christine U., and James F. Glockner. "Case 4.20." In Mayo Clinic Body MRI Case Review, edited by Christine U. Lee and James F. Glockner, 224–25. Oxford University Press, 2014. http://dx.doi.org/10.1093/med/9780199915705.003.0118.
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30-year-old woman with VHL syndrome and prior pancreatic surgery Axial diffusion-weighted images (b=100 s/mm2) (Figure 4.20.1) reveal multiple hyperintense hepatic lesions. Axial fat-suppressed FSE T2-weighted images (Figure 4.20.2) demonstrate extensive cystic disease involving the pancreas. Note also that several lesions consist of clustered cysts. Axial (...
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Lee, Christine U., and James F. Glockner. "Case 7.19." In Mayo Clinic Body MRI Case Review, edited by Christine U. Lee and James F. Glockner, 343–44. Oxford University Press, 2014. http://dx.doi.org/10.1093/med/9780199915705.003.0180.
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50-year-old man with Crohn disease and urinary frequency and urgency; a cystic renal mass was found at renal sonography Axial fat-suppressed T2-weighted FSE (Figure 7.19.1), coronal SSFSE (Figure 7.19.2), and coronal postgadolinium 2D SPGR (Figure 7.19.3) images show multiple small cystic lesions without significant enhancement clustered in the upper pole of the right kidney....
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Ferreira, Adaliene Versiani Matos, Laís Bhering Martins, Nayara Mussi Monteze, Geneviève Marcelin, and Karine Clément. "Immunology of Eating Disorders." In Immunopsychiatry, 241–50. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190884468.003.0014.
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Eating disorders (EDs) are characterized by dysregulation in eating behavior leading to extreme increase or decrease in food intake that, in turn, changes body weight, adiposity, and physical health. Anorexia nervosa (AN), bulimia nervosa (BN), and binge eating disorder (BED) are the three major eating disorders. Peculiar immune abnormalities occur in these conditions. Previous studies have reported a higher number of CD4+ T lymphocytes in patients with AN, which are related to a relative resistance to viral infections, even in the presence of leukopenia. It has also been proposed that a cluster of cytokines is altered in these patients. A chronic low-grade inflammation has been observed in obese people with BED and in patients with AN, but with a different profile in each condition. In this context, antagonist drugs of specific cytokines, such as anti-TNF, showed improvement of AN-related symptoms, but increased weight gain in obese subjects. The identification of specific molecules and/or immune cells that impair neuronal circuits implicated in eating behaviors may contribute to the development of pharmacological strategies for eating disorders.
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Rastogi, Rohit, Devendra Kumar Chaturvedi, and Mayank Gupta. "Mental Health Through Biofeedback Is Important to Analyze." In Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning, 402–23. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-2742-9.ch020.
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Many apps and analyzers based on machine learning have been designed to help and cure the stress issue. This chapter is based on an experiment that the authors performed at Research Labs and Scientific Spirituality Centers of Dev Sanskriti VishwaVidyalaya, Haridwar and Patanjali Research Foundations, Uttarakhand. In the research work, the correctness and accuracy have been studied and compared for two biofeedback devices named as electromyography (EMG) and galvanic skin response (GSR), which can operate in three modes: audio, visual and audio-visual with the help of data set of tension type headache (TTH) patients. The authors used some data visualization techniques that EMG (electromyography) in audio mode is best among all other modes, and in this experiment, they have used a data set of SF-36 and successfully clustered them into three clusters (i.e., low, medium, and high) using K-means algorithm. After clustering, they used classification algorithm to classify a user (depending upon the sum of all the weights of questions he had answered) into one of these three class. They have also implemented various algorithms for classifications and compared their accuracy out of which decision tree algorithm has given the best accuracy.
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Palmer, Brian A., and Bhanuprakash Kolla. "Substance Use Disorders, Personality Disorders, and Eating Disorders." In Mayo Clinic Internal Medicine Board Review, edited by Christopher M. Wittich, Thomas J. Beckman, Sara L. Bonnes, Nina M. Schwenk, Jason H. Szostek, Nerissa M. Collins, and Christopher R. Stephenson, 775–78. 12th ed. Oxford University PressNew York, 2019. http://dx.doi.org/10.1093/med/9780190938369.003.0072.
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Abstract Alcohol and other substance use disorders are a major concern in all age groups and across all ethnic, socioeconomic, and racial groups. Despite high lifetime prevalence, less than 10% of persons with substance use disorders are involved in treatment. Personality disorders are grouped into 3 clusters and demand the most from internists. The disorder is treatable and generally improves despite common perceptions to the contrary. The 2 common eating disorders are anorexia nervosa and bulimia. Both are markedly more prevalent among women than men. Eating disorders are increasingly found across all income, racial, and ethnic groups. Both disorders have a primary symptom of preoccupation with weight and distortion of body image. Eating disorders have the highest lethality of all psychiatric illnesses.
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Theodoridou, Glykeria, Efthimia Tsakiridou, Nikos Kalogeras, and Konstantinos Mattas. "Food Consumption Patterns in Times of Economic Recession." In Urban Agriculture and Food Systems, 116–30. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8063-8.ch006.
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The aim of this study is to identify the factors influencing consumers' purchasing behaviour for food, in times of crisis. Intercept survey was conducted in a random selected sample consisted of 553 consumers between January and May 2016 in the Prefecture of Thessaloniki. Multivariate data analysis was performed to explore the factors influencing consumers' purchasing behaviour, identify consumers with similar behaviour based on their socio-demographic characteristics and their attitudes towards food consumption in times of crisis. Results demonstrate that the factors affecting consumers' purchasing behaviour are (a) Product's Feature and Natural contents, (b) Economic issues, (c) Identity & Sensory Appeal, (d) Mood, (e) Weight Control & Health and (f) Convenience. Furthermore, cluster analysis was employed to classify consumers with similar buying behaviour towards food, five groups of consumers were identified: (a) neutrals, (b) influenced by psychological issues, (c) influenced by economic issues, (d) low diet/healthy eaters and (e) influenced by availability and easy access.
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Andreyev, Jervoise. "Investigation of gastrointestinal function." In Oxford Textbook of Medicine, edited by Jack Satsangi, 2757–64. Oxford University Press, 2020. http://dx.doi.org/10.1093/med/9780198746690.003.0289.
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There are two main reasons for investigating the gastrointestinal (GI) tract: first, to identify diseases at an early stage (e.g. endoscopic screening for neoplasia); second, to diagnose and manage symptoms. A pathological process can potentially affect any part of the GI tract, but apart from mass lesions, pathological change per se hardly ever causes symptoms directly. Symptoms depend on whether critical physiological change has been triggered by the pathological insult. Individual symptoms or clusters of symptoms are not a reliable indicator of the underlying cause, and different physiological changes can produce identical symptoms. Critical symptoms indicative of significant GI tract pathology include ‘red flag’ symptoms (e.g. a palpable mass, rectal bleeding, weight loss) and other symptoms that are frequently missed by patients and clinicians alike (e.g. steatorrhoea, nocturnal waking to defecate). Dietary intake requires systematic assessment. Routine investigation should usually include thyroid function testing, vitamin B12 and vitamin D status, coeliac screen, iron studies, and inflammatory markers. Endoscopy and cross-sectional radiology provide excellent anatomical visualization but provide little information about the dynamic function and physiology of the GI tract, for which various tests for specific physiological functions can be used. Failure to investigate adequately misses easily treated diagnoses and means ongoing symptoms for patients. For many patients with multiple comorbidities, there is often more than one cause for their GI symptoms, which will not improve unless all causes are identified and treated.
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Fakeye, Attah, Olusegun Ige, and Olufemi Ogunsanwo. "Multivariate Assessment of California Bearing Ratio with Contrasted Geotechnical Properties of Soils in Ilorin-Lokoja Highway." In Engineering Geology. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.93523.
Full textAbstract:
California Bearing Ratio (CBR) is an important parameter used in designing pavement layers in road construction but testing this parameter requires time, labor, and huge cost. The study therefore applies multivariate approach to evaluate CBR based on contrasted geotechnical parameters along Ilorin-Lokoja highway. The results obtained showed that the migmatite-gneiss-derived soils are slightly more fines (< 0.075 mm; 7.4–59.6%), more plastic (PI; 1.6–39%), and have low strength (MDD = 1.8 mg/m3; CBR = 29.0%) than the metasediments (11–57.7%, 2.0–30%, 1.6 mg/m3, 23.6%) and older granite soils (8.2–32.7%, 2.6–13.4%, 1.7 mg/m3, 27.8%), respectively. The principal component analysis (PCA) revealed three major components (eigenvalues >1) which accounted for 83.8% of the total variance at the rate of 33.4, 14.7, and 11.4%. Major contributing variables for the components were fines (R = 0.87), plasticity index (R = 0.7), and coarse sand (R = 0.67%). Spatial distribution of these groups established interplay of sediment-gradation and moisture-connection evident in hierarchical cluster analysis that revealed patterns of homogeneity and soil relationships. Regression analysis established five models from predictor variables such as fines, activity, free swell, liquid and plastic limits, weighted plasticity index, optimum moisture content, and maximum dry density with the coefficient of determination (R2 = 0.33) and root mean square error (RMSE) of 7.80.
Conference papers on the topic "Cluster weighted mod"
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Hetsroni, G. "Boiling of Water and Surfactants in Confined Space." In ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2008. http://dx.doi.org/10.1115/esda2008-59216.
Full textAbstract:
Natural convection boiling of water and surfactant solutions at atmospheric pressure in narrow horizontal annular channels was studied experimentally. The Alkyl (8–16) Glucoside with molecular weight of 390 g/mol was used in the experiments. It is a nonionic surfactant with negligible environmental impact. The length of the horizontal channels was 24 mm and 36 mm, the gape size was in the range of 0.45–3.7 mm, the heat flux was in the range of 20–500 kW/m2, the concentration of surfactant solutions was varied from 10 to 600 ppm. The gap size of the vertical channels was changed in the range of 1–80 mm. The flow pattern was visualized by high-speed video recording to identify the different regimes of boiling of water and surfactant solutions with different concentrations. At heat flux q<100 kW/m2 the rapid growth of elongated bubble was observed in the water. The rapid bubble growth pushes the liquid-vapor interface on both open sides of the channel. When a bubble departs from a nucleus cavity, its cavity is then recovered by liquid, and next bubble will appear on the heated tube after a certain interval. The behavior of the long vapor bubbles occurring in small size annular channels is not similar to annular flow with intermitted slugs between two vapor trains. Surfactant solution promotes activation of nucleation sites in a clustered mode. The cluster contains a number of small bubbles, the location of nucleation sites and time behavior of each bubble cannot be traced exactly. At higher values of heat flux coalescence process was observed during boiling of water and surfactant solutions. For water boiling in horizontal channels at Bond numbers Bo<1 the CHF in restricted space is lower than that in unconfined apace. This effect increases with increasing the channel length. For water at Bond number Bo = 1.52, boiling can be considered as unconfined. Additive of surfactant led to enhancement of heat transfer compared to water boiling in the same gap size, however, this effect decreased with decreasing gap size. For the same gap size, CHF in surfactant solutions was significantly lower than that in water. Hysteresis was observed for boiling in degraded surfactant solutions.
Reports on the topic "Cluster weighted mod"
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Lichter, Amnon, David Obenland, Nirit Bernstein, Jennifer Hashim, and Joseph Smilanick. The role of potassium in quality of grapes after harvest. United States Department of Agriculture, October 2015. http://dx.doi.org/10.32747/2015.7597914.bard.
Full textAbstract:
Objectives: The objectives of the proposal were to study how potassium (K) enters the berry and in what tissues it accumulates, to determine what is the sensitive phenological stage that is responsive to K, to study the influence of K on sugar translocation, to determine if K has effects on expression of genes in source and sink organs and to study applied aspects of the responses to K at the vineyard level. During the research it was realized that K acts externally so a major part of the original objectives had to be deserted and new ones, i.e. the role of K in enhancing water loss from the berry, had to be developed. In addition, the US partners developed practical objectives of understanding the interaction of K application and water deficit as well as application of growth regulators. Background: In our preliminary data we showed that application of K at mid-ripening enhanced sugar accumulation of table grapes. This finding is of major implications to both early and late harvested grapes and it was essential to understand the mode of action of this treatment. Our major hypothesis was that K enters the berry and by that increases sugar translocation into the berry. In addition it was important to cover practical issues of the application which may influence its efficacy and its reproducibility. Conclusions: The major conclusion from the research was that our initial hypothesis was wrong. Mineral analysis of pulp tissue indicated that upon application of K there was a significant increase in most of the major minerals. Subsequently, we developed a new hypothesis that K acts by increasing the water loss from the berry. In vitro studies of K-treated berries corroborated this hypothesis showing greater weight-loss of treated berries. This was not necessarily expressed in the vineyard as in some experiments berry weight remained unchanged, suggesting that the vine compensated for the enhanced water loss. Importantly, we also discovered that the efficacy of different K salts was strongly correlated to the pH of the salt solution: basic K salts had better efficacy than neutral or acidic salts and modifying the pH of the same salt changed its efficacy. It was therefore suggested that K changes the properties of the cuticle making it more susceptible to water loss. Of the practical aspects it was found that application of K to the clusters was sufficient to trigger its affect and that dual application of K had a stronger effect than single application. With regard to timing, it was realized that application of K after veraison was affective and the berries responded also when ripe. While the effect of K application was significant at harvest, it was mostly insignificant one week after application, suggesting that prolonged exposure to K was required. Implications: The scientific implications of the study are that the external mineral composition of the berry may have a significant role in sugar accumulation and that water loss may have an important role in sugar accumulation in grapes. It is not entirely clear how K modulates the cuticle but according to the literature its incorporation into the cuticle may increase its polarity and facilitate generation of "water bridges" between the flesh and the environment. The practical implications of this study are very significant because realizing the mode of action of K can facilitate a much more efficient application strategy. For example, it can be understood that sprays must be directed to the clusters rather than the whole vines and it can be predicted that the length of exposure is important. Also, by increasing the pH of simple K salts, the efficacy of the treatment can be enhanced, saving in the costs of the treatment. Finally, the ability of grape growers to apply K in a safe and knowledgeable way can have significant impact on the length of the season of early grape cultivars and improve the flavor of high grape yields which may otherwise have compromised sugar levels.