SFS-A68: a dataset for the segmentation of space functions in apartment buildings

Analyzing building models for usable area, building safety, or energy analysis requires function classification data of spaces and related objects. Automated space function classification is desirable to reduce input model preparation effort and errors. Existing space function classifiers use space feature vectors or space connectivity graphs as input. The application of deep learning (DL) image segmentation methods to space function classification has not been studied. As an initial step towards addressing this gap, we present a dataset, SFS-A68, that consists of input and ground truth images generated from 68 digital 3D models of space layouts of apartment buildings. The dataset is suitable for developing DL models for space function segmentation. We use the dataset to train and evaluate an experimental space function segmentation network based on transfer learning and training from scratch. Test results confirm the applicability of DL image segmentation for space function classification. The code and the dataset of the experiments are publicly available online (https://github.com/A2Amir/SFS-A68).Comment: Published in proceedings of the 29th International Workshop on Intelligent Computing in Engineering, EG-ICE 2022, Aarhus, Denmark. https://doi.org/10.7146/aul.455.c22

Batch Layer Normalization, A new normalization layer for CNNs and RNN

This study introduces a new normalization layer termed Batch Layer Normalization (BLN) to reduce the problem of internal covariate shift in deep neural network layers. As a combined version of batch and layer normalization, BLN adaptively puts appropriate weight on mini-batch and feature normalization based on the inverse size of mini-batches to normalize the input to a layer during the learning process. It also performs the exact computation with a minor change at inference times, using either mini-batch statistics or population statistics. The decision process to either use statistics of mini-batch or population gives BLN the ability to play a comprehensive role in the hyper-parameter optimization process of models. The key advantage of BLN is the support of the theoretical analysis of being independent of the input data, and its statistical configuration heavily depends on the task performed, the amount of training data, and the size of batches. Test results indicate the application potential of BLN and its faster convergence than batch normalization and layer normalization in both Convolutional and Recurrent Neural Networks. The code of the experiments is publicly available online (https://github.com/A2Amir/Batch-Layer-Normalization).Comment: Published in proceedings of the 6th international conference on Advances in Artificial Intelligence, ICAAI 2022, Birmingham, U

SAGC-A68: a space access graph dataset for the classification of spaces and space elements in apartment buildings

The analysis of building models for usable area, building safety, and energy use requires accurate classification data of spaces and space elements. To reduce input model preparation effort and errors, automated classification of spaces and space elements is desirable. A barrier hindering the utilization of Graph Deep Learning (GDL) methods to space function and space element classification is a lack of suitable datasets. To bridge this gap, we introduce a dataset, SAGC-A68, which comprises access graphs automatically generated from 68 digital 3D models of space layouts of apartment buildings. This graph-based dataset is well-suited for developing GDL models for space function and space element classification. To demonstrate the potential of the dataset, we employ it to train and evaluate a graph attention network (GAT) that predicts 22 space function and 6 space element classes. The dataset and code used in the experiment are available online. https://doi.org/10.5281/zenodo.7805872, https://github.com/A2Amir/SAGC-A68.Comment: Published in proceedings of the 30th International Workshop on Intelligent Computing in Engineering, EG-ICE 2023, London, England. https://www.ucl.ac.uk/bartlett/construction/sites/bartlett_construction/files/sagc-a68_a_space_access_graph_dataset_for_the_classification_of_spaces_and_space_elements_in_apartment_buildings.pd

Comparison of adjunctive therapy with metformin and acarbose in patients with Type-1 diabetes mellitus

ABSTRACT Objective: All the aforementioned data have stimulated interest in studying other potential therapies for T1DM including noninsulin pharmacological therapies. The present study attempts to investigate the effect of adjunctive therapy with metformin and acarbose in patients with Type-1 diabetes mellitus. Method: In a single-center, placebo-controlled study (IRCT201102165844N1) we compared the results of two clinical trials conducted in two different time periods on 40 patients with Type-1 diabetes mellitus. In the first section, metformin was given to the subjects.After six months, metformin was replaced with acarbose in the therapeutic regimen. In both studies, subjects were checked for their BMI, FBS, HbA1C, TGs, Cholesterol, LDL, HDL, 2hpp, unit of NPH and regular insulin variations. Results: Placebo-controlled evaluation of selected factors has showna significant decrease in FBS and TG levels in the metformin group during follow up but acarbose group has shown substantial influence on two hour post prandial (2hpp) and regular insulin intake decline.Moreover, Comparison differences after intervention between two test groups has shown that metformin has had superior impact on FBS and HbA1C decline in patients. Nonetheless, acarbose treatment had noteworthy influence on 2hpp, TGs, Cholesterol, LDL, and regular insulin intake control. Conclusion: The results of this experiment demonstrate that the addition of acarbose or metformin to patients with Type-1 diabetes mellitus who are controlled with insulin is commonly well tolerated and help to improve metabolic control in patients. KEYWORDS: Acarbose, Metformin, Type-1 diabetes mellitus

Predictors of hypoglycemia fear in patients with type 2 diabetes under treatment of oral anti hyperglycemic agents

Introduction: Hypoglycemia is a medical emergency that disrupt routine life. Hypoglycemia experience likely causes fear of its recurrence. Even mild or moderate episodes may worry patients for frequent events. Limited studies have assessed predictors offear of hypoglycemia in patients with diabetes. The aim of the present study was to determine the predicting factors of hypoglycemia in type 2 diabetic patients treated with oral anti-hyperglycemic agents. Materials and Methods: This cross-sectional study was conducted on 357 patients with type 2 diabetes treated with oral anti-diabetic drugs. Data was collected through interviews by using a three-part questionnaire (socio-demographic & clinical characteristics, HFS-II). The data was analyzed with descriptive and deductive statistic methods (Generalized Linear Models) at 5<0.05 using SPSSv.16 software. Results: Mean age of patients was 54.11±11.54 years and the majority were female (56.6%). The mean HFS score was 16.8±16.33. In regression analysis, frequency of hospitalization (p<0.001), employment (p<0.048), number of medications (p<0.029), hyperlipidemia (p<0.026), hypoglycemia (p<0.001) and hypoglycemia intensity (p<0.001) were related to fear of hypoglycemia. Conclusion: According to the results of the present study, hypoglycemia and its intensity are considered as the strongest predictors of fear of hypoglycemia. Therefore, prevention of hypoglycemia occurrence and reduction of its related fear can be performed by modifying the other predictors identified in this study. Keywords: Fear of hypoglycemia, Diabetes Mellitus, Oral anti-hyperglycemic agent

What amount of alcohol is not harmful for human health?

For downloading the full-text of this article please click here.Oh, Prophet! They ask you about wine and gambling. Tell them that they are great sins and also have some benefits for people; and their sins exceed their profitFor downloading the full-text of this article please click here.Please cite this article as: Ziaee S.A.M, Shadnia S. What amount of alcohol is not harmful for human health. J Res Relig Health. 2019; 5(1): 1- 6. doi:  https://doi.org/10.22037/jrrh.v5i1.2408

Prevalence of Anxiety and Depression in Diabetic Patients: A Comparative Study

Background: Living with diabetes and managing it can have substantial emotional burden on individuals. These changes might affect individuals’ lives in terms of stress and depression. The purpose of this study was to determine the prevalence of stress and depression among diabetic women who referred to endocrine clinic of Qazvin in 2014. Methods: For this purpose, 250 patients (125 individuals suffering from diabetes and 125 individuals as a control group) participated in this study. All individuals completed the beck depression inventory and the cattell anxiety inventory. In addition to these, demographic and clinical records were collected from their medical records and were analyzed by appropriate statistical methods. Results: In terms of the Maximum of mild anxiety there were 52 diabetic individuals (41.6%) versus 69 individuals of the control group (55.2%); in terms of Moderate-severe anxiety there were 73 cases (58.4%) versus 56 patients (44.8%) (P value = 0.031). In studying the Maximum of mild depression, there were 43 patients (34.4%) versus 92 (73.6%); in terms of Moderate-severe depression, there were 82 patients (65.6%) versus 33 (26.4%) (P value=0.001). Ona closer examination among age, type of diabetes, duration of diabetes, and insulin injections; only the duration of having diabetes was significantly associated with depression as one of the mental health variables. Conclusions: This study showed that anxiety and depression are significantly more common among diabetic patients in comparison to the control group in the city of Qazvin; therefore, it is necessary to develop primary care by a system based on the reaction, so that an effective treatment for mental health would take place and, ultimately, the impact of these interventions should be studied. Keywords: Mental Health, Anxiety, Depression, Diabete

Comparison of adjunctive therapy with metformin and acarbose in patients with Type-1 diabetes mellitus

Objective: All the aforementioned data have stimulated interest in studying other potential therapies for T1DM including noninsulin pharmacological therapies. The present study attempts to investigate the effect of adjunctive therapy with metformin and acarbose in patients with Type-1 diabetes mellitus. Method: In a single-center, placebo-controlled study (IRCT201102165844N1) we compared the results of two clinical trials conducted in two different time periods on 40 patients with Type-1 diabetes mellitus. In the first section, metformin was given to the subjects.After six months, metformin was replaced with acarbose in the therapeutic regimen. In both studies, subjects were checked for their BMI, FBS, HbA1C, TGs, Cholesterol, LDL, HDL, 2hpp, unit of NPH and regular insulin variations. Results: Placebo-controlled evaluation of selected factors has showna significant decrease in FBS and TG levels in the metformin group during follow up but acarbose group has shown substantial influence on two hour post prandial (2hpp) and regular insulin intake decline.Moreover, Comparison differences after intervention between two test groups has shown that metformin has had superior impact on FBS and HbA1C decline in patients. Nonetheless, acarbose treatment had noteworthy influence on 2hpp, TGs, Cholesterol, LDL, and regular insulin intake control. Conclusion: The results of this experiment demonstrate that the addition of acarbose or metformin to patients with Type-1 diabetes mellitus who are controlled with insulin is commonly well tolerated and help to improve metabolic control in patients. KEYWORDS: Acarbose, Metformin, Type-1 diabetes mellitus

The Efficacy of Licorice Root Extract in Decreasing Transaminase Activities in Non-alcoholic Fatty Liver Disease: A Randomized Controlled Clinical Trial

This study was performed to investigate the effects of licorice on non-alcoholic fatty liver disease (NAFLD). In this double blind randomized clinical trial, 66 patients were divided into case and control groups. All patients had elevated liver enzymes and had increased liver echogenicity (lipid accumulation) on sonography. The case group was treated with one capsule containing 2 g aqueous licorice root extract per day for 2 months while the control group was treated in the same manner with a placebo. Weight, body mass index (BMI) and liver transaminase levels were measured for each patient before and after the study. In the case group, the mean alanine aminotransferase (ALT) level decreased from 64.09 to 51.27 IU/mL and the aspartate aminotransferase (AST) level decreased from 58.18 to 4