Terms Of Weight Research Articles

A case study of liraglutide in an obese diabetic patient in a District General Hospital

A case study of liraglutide in an obese diabetic patient in a District General Hospital

Ultrasound characteristics of the internal genital organs in adolescent girls with gynecological and extragenital pathologies born with low or high body weight

We studied the effect of birth weight on ultrasound parameters of the uterus and ovaries in adolescent girls with gynecological pathology. 65 adolescent girls aged from 10 to 18 years old, who were treated at the surgical department № 4 of the Regional Child Clinical Department, were examined. Study groups were formed according to data relating to gestational weight in terms of low or overweight. The differences in ultrasound scanning of the pelvic organs between the studied groups were revealed. So, with the syndrome of intrauterine growth retardation of the fetus, a lag in ultrasound indicators develops in the postnatal period, and with macrosomia, on the contrary, a tendency to an increase in the size of the uterus and ovaries is revealed. The revealed changes can serve as prognostic criteria in diagnosing the risk of developing disorders of puberty during ultrasound scanning of the internal genital organs of adolescent girls, depending on the body weight at birth. Keywords: epilepsy, affective disorders, rehabilitation, psychoeducation.

Probabilistic vehicle weight estimation using physics‐constrained generative adversarial network

AbstractTraffic information plays an important role in the design and management of civil transportation infrastructure. Bridge weigh‐in‐motion (BWIM) provides an effective tool for traffic information gathering by estimating vehicle parameters including its weight through bridge responses. Most existing BWIM algorithms rarely consider the epistemic uncertainty of vehicle weight in terms of the probabilistic distribution of estimated axle weights (AWs) of the vehicle. This paper proposes a novel methodology for probabilistic vehicle weight estimation using a physics‐constrained generative adversarial network (GAN). Generative models are introduced to describe the probabilistic distributions of estimated AWs and bridge responses. Physics constraints on the generative models are formulated and enforced by minimizing a physics‐based loss function. The generative models are then learned by training a physics‐constrained GAN using the observed bridge responses. Numerical study and field testing are conducted to demonstrate the proposed method using representative highway bridges and vehicles. The results show that the proposed method can successfully capture the uncertainty in the vehicle weight estimation and provide the probabilistic distributions of the estimated AWs for different vehicle types and loading conditions considered, which can enhance the application of BWIM for relevant tasks such as traffic data collection and truck overloading enforcement. Based on the results obtained from the numerical study and field testing, the maximum coefficient of variation obtained for the AWs and gross vehicle weight of the presented cases are 0.55 and 0.11, respectively.

Simple Baseline Machine Learning Text Classifiers for Small Datasets

Text classification is important to better understand online media. A major problem for creating accurate text classifiers using machine learning is small training sets due to the cost of annotating them. On this basis, we investigated how SVM and NBSVM text classifiers should be designed to achieve high accuracy and how the training sets should be sized to efficiently use annotation labor. We used a four-way repeated-measures full-factorial design of 32 design factor combinations. For each design factor combination 22 training set sizes were examined. These training sets were subsets of seven public text datasets. We study the statistical variance of accuracy estimates by randomly drawing new training sets, resulting in accuracy estimates for 98,560 different experimental runs. Our major contribution is a set of empirically evaluated guidelines for creating online media text classifiers using small training sets. We recommend uni- and bi-gram features as text representation, btc term weighting and a linear-kernel NBSVM. Our results suggest that high classification accuracy can be achieved using a manually annotated dataset of only 300 examples.

Effects of central tendency measures on term weighting in textual information retrieval

It has become evident that term weighting has a significant effect on relevant document retrieval for which various methods are proposed. However, the main question that arises is which weighting method is the best? In this paper, it is shown that proper aggregation of weights generated by carefully selected basic weighting methods improves retrieval of the relevant documents with respect to the user’s needs. Toward this aim, it is shown that even using simple central tendency measures such as average, median or mid-range over an appropriate subset of basic weighting methods provides term weight that not only outperforms using each basic weighting method but also results in more effective weights in comparison with recently proposed complicated weighting methods. Based on exploiting the proposed method on various datasets, we have studied the effects of normalization of the basic weights, normalization of the vector lengths, the use of different components in the term frequency factor, etc. Results reveal the criteria for selecting an appropriate subset of basic weighting methods that would be fed to the aggregator in order to achieve higher retrieval precision.

Hypertensive Disorders during Pregnancy (HDP), Maternal Characteristics, and Birth Outcomes among Japanese Women: A Hokkaido Study.

Hypertension during pregnancy causes a greater risk of adverse birth outcomes worldwide; however, formal evidence of hypertensive disorders during pregnancy (HDP) in Japan is limited. We aimed to understand the association between maternal characteristics, HDP, and birth outcomes. In total, 18,833 mother-infant pairs were enrolled in the Hokkaido study on environment and children’s health, Japan, from 2002 to 2013. Medical records were used to identify hypertensive disorders and birth outcomes, namely, small for gestational age (SGA), SGA at full term (term-SGA), preterm birth (PTB), and low birth weight (LBW). The prevalence of HDP was 1.9%. Similarly, the prevalence of SGA, term-SGA, PTB, and LBW were 7.1%, 6.3%, 7.4%, and 10.3%, respectively. The mothers with HDP had increased odds of giving birth to babies with SGA (2.13; 95% Confidence Interval (CI): 1.57, 2.88), PTB (3.48; 95%CI: 2.68, 4.50), LBW (3.57; 95%CI: 2.83, 4.51) than normotensive pregnancy. Elderly pregnancy, low and high body mass index, active and passive smoking exposure, and alcohol consumption were risk factors for different birth outcomes. Therefore, it is crucial for women of reproductive age and their families to be made aware of these risk factors through physician visits, health education, and various community-based health interventions.

Ketogenic Diet as a Preventive and Supportive Care for COVID-19 Patients.

Severe obesity is associated with an increased risk of admission to intensive care units and need for invasive mechanical ventilation in patients with COVID-19. The association of obesity and COVID-19 prognosis may be related to many different factors, such as chronic systemic inflammation, the predisposition to severe respiratory conditions and viral infections. The ketogenic diet is an approach that can be extremely effective in reducing body weight and visceral fat in the short term, preserving the lean mass and reducing systemic inflammation. Therefore, it is a precious preventive measure for severely obese people and may be considered as an adjuvant therapy for patients with respiratory compromise.

A method of non-bug report identification from bug report repository

One of the most common issues addressed by bug report studies is misclassification when identifying and then filtering non-bug reports from the bug report repository. Having to filter out unrelated reports wastes time in identifying actual bug reports, and this escalates costs as extra maintenance and effort are required to triage and fix bugs. Therefore, this issue has been seriously studied and is addressed here. To tackle this problem, this study proposes a method of automatically identifying non-bug reports in the bug report repository using classification techniques. Three points are considered here. First, the bug report features used are unigram and CamelCase, where CamelCase words are used for feature expansion. Second, five term weighting schemes are compared to determine an appropriate term weighting scheme for this task. Lastly, the support vector machine (SVM) family i.e. binary-class SVM, one class SVM based on Scholkopf methodology and support vector data description (SVDD) are used as the main mechanisms for modeling non-bug report identifiers. After testing by recall, precision, and F1, the results demonstrate the efficiency of identifying non-bug reports in the bug report repository. Our results may be acceptable after comparing to the previous well-known studies, and the performance of non-bug report identifiers with tf-igm and modified tf-icf weighting schemes for both Scolkopf methodology and SVDD methods yielded the best value when compared to others.

Comparison of Postnatal Growth Charts of Singleton Preterm and Term Infants Using World Health Organization Standards at 40-160 Weeks Postmenstrual Age: A Chinese Single-Center Retrospective Cohort Study.

There remains controversy regarding whether the growth charts constructed from data of term infants, such as those produced by the World Health Organization (WHO) standards, can appropriately evaluate the postnatal growth of preterm infants. This retrospective cohort study, conducted in the First Affiliated Hospital of Shandong First Medical University in Jinan China, aimed to compare the postnatal growth charts of singleton preterm and term infants using WHO standards at 40–160 weeks postmenstrual age (PMA). A total of 5,459 and 15,185 sets of longitudinal measurements [length/height, weight, head circumference (HC), and body mass index (BMI)] from birth to 160 weeks PMA were used to construct growth charts for 559 singleton preterm (mean PMA at birth, 33.84 weeks) and 1,596 singleton term infants (born at 40 weeks PMA), respectively, using the Generalized Additive Models for Location, Scale, and Shape (GAMLSS) method. Z-scores (prematurity corrected) were calculated using WHO Anthro software. Compared to WHO standards, all parameters of preterm infants were increased, especially in terms of length/height and weight; the gap between the two almost spanned two adjacent centile curves. Compared to term controls, the length/height, weight, and BMI of preterm infants were higher at 40 weeks PMA, surpassed by term infants at 52–64 weeks PMA, and quite consistent thereafter. The HC of preterm infants at 40–160 weeks PMA was quite consistent with both term controls and the WHO standards. The Z-scores for length/height, weight, and BMI of preterm infants relative to the WHO standards gradually decreased from 1.20, 1.13, and 0.74 at 40–44 weeks PMA to 0.67, 0.42, and 0.03 at 132–160 weeks PMA, respectively; Z-scores for HC of preterm infants rapidly decreased from 0.73 to 0.29 at 40–50 weeks PMA, and then fluctuated in the range of 0.08–0.23 at 50–160 weeks PMA. Preterm infants had higher growth trajectories than the WHO standards and similar but not identical trajectories to term infants during the first 2 years of life. These findings reemphasize the necessity of constructing local growth charts for Chinese singleton preterm infants.

Text Classification Using Novel Term Weighting Scheme-Based Improved TF-IDF for Internet Media Reports

With the rapid development of the internet technology, a large amount of internet text data can be obtained. The text classification (TC) technology plays a very important role in processing massive text data, but the accuracy of classification is directly affected by the performance of term weighting in TC. Due to the original design of information retrieval (IR), term frequency-inverse document frequency (TF-IDF) is not effective enough for TC, especially for processing text data with unbalanced distributions in internet media reports. Therefore, the variance between the DF value of a particular term and the average of all DFsDF¯, namely, the document frequency variance (ADF), is proposed to enhance the ability in processing text data with unbalanced distribution. Then, the normal TF-IDF is modified by the proposed ADF for processing unbalanced text collection in four different ways, namely, TF-IADF, TF-IADF+, TF-IADFnorm, and TF-IADF+norm. As a result, an effective model can be established for the TC task of internet media reports. A series of simulations have been carried out to evaluate the performance of the proposed methods. Compared with TF-IDF on state-of-the-art classification algorithms, the effectiveness and feasibility of the proposed methods are confirmed by simulation results.

Using modified term frequency to improve term weighting for text classification

Text classification (TC) is an essential task of natural language processing (NLP). In order to improve the performance of TC, term weighting is often used to obtain effective text representation by assigning appropriate weights to each term. A term weighting scheme is generally composed of term frequency factor, collection frequency factor and normalization factor. The normalization factor is commonly used as an optional factor to offset the influence of document length. Through the investigation of the existing term weighting schemes, we found that most of them focus on finding a more effective collection frequency factor, but rarely pay attention to finding a new term frequency factor. In this paper, we first proposed a new term frequency factor called modified term frequency (MTF). Different from the normalization factor, MTF directly modifies the raw term frequency based on the length information of all training documents. Then we proposed a new term weighting scheme by combining MTF with an existing collection frequency factor called modified distinguishing feature selector (MDFS). We denoted our scheme by MTF-MDFS (MDFS-based MTF). Extensive experimental results on 19 benchmark text datasets and 6 real-world text datasets show that our proposed MTF and MTF-MDFS are all much better than their state-of-the-art competitors in terms of the classification accuracy and the weighted average of F1 of widely used base classifiers, such as MNB, SVM and LR.

Evaluation of significance of control directives for software errors detection in functional programming of on-board computers

Modern farm machinery is equipped with on-board computers that execute complicated tasks. The main efforts are aimed at selecting and justifying methods for adequate hardware-software translation of functional programming from one computer system to another, while increasing its stability to failures of computer hardware. The development of approaches to the selection of procedures for detecting errors determines the degree of their relative information value when analyzing the programs progress. As it follows from the analysis of error types in functional programming, it is established that errors occur at the stages of forming the technical task, when developing algorithms, when programming, and when configuring programs. Errors have different frequency and different weight in terms of the impact on the functioning of on-board computers used in agricultural machinery. The article contains a detailed list of errors that must be detected when debugging working programs of on-board computers. Based on expert assessments, the errors are divided into 33 different types and formed into 6 groups. By combining errors, it is possible to minimize the time spent on performing static debugging of the functional programming of on-board computers. Using the hierarchy analysis method, matrices of paired comparisons of control directives with error types in each group are formed. Thus, the relationship between groups of errors, control directives, and values of error types is established. The first thing, programs debugging is performed using the control directives that have the highest degree of significance, since they can be used to identify and eliminate the most dangerous errors.

Study of fetal hemoglobin with different gestational age and birth weight of the newborn

Background: In many parts of the developing country estimation of antenatal gestational age is still not possible and challenging condition of proper perinatal care. This study aimed to find out relationship between the gestational age and birth weight of the newborn with fetal hemoglobin concentration.Methods: In this comparative study, we included 90 pregnant women who delivered their babies by normal vaginal delivery. Out of these 90 babies, 27 were preterm with gestational age 28-36 weeks, 55 were term with gestational age 37-41 weeks and remaining 8 were post term with gestational age of more than 41 weeks. All these 90 newborn infants were also divided into two groups: low birth weight (birth weight <2.5 kg) and birth weight ≥2.5 kg. Fetal hemoglobin was estimated by using alkali denaturation technique of Chernoff and Singer on appropriate spectrophotometer. Statistical analysis was performed using SPSS windows version 20.0 software.Results: The total number of newborns were significantly (p<0.001) higher in term group and with normal birth weight group. Fetal hemoglobin level was significantly (p<0.0001) lower in term, post term and normal birth weight groups. Study showed a definite negative correlation between gestational age and the fetal hemoglobin concentration. Fetal hemoglobin level was gradually declining with increasing gestational age and birth weight.Conclusions: It is concluded from this study that the concentration of fetal hemoglobin decreases at the rate of 2.4% per week with considerable variation of values at every week of advancing gestational age. Hence level of fetal hemoglobin estimation can be taken as an important criterion for evaluation of gestational age.

Hate Speech Classification in Indonesian Language Tweets by Using Convolutional Neural Network

The rapid development of social media, added with the freedom of social media users to express their opinions, has influenced the spread of hate speech aimed at certain groups. Online based hate speech can be identified by the used of derogatory words in social media posts. Various studies on hate speech classification have been done, however, very few researches have been conducted on hate speech classification in the Indonesian language. This paper proposes a convolutional neural network method for classifying hate speech in tweets in the Indonesian language. Datasets for both the training and testing stages were collected from Twitter. The collected tweets were categorized into hate speech and non-hate speech. We used TF-IDF as the term weighting method for feature extraction. The most optimal training accuracy and validation accuracy gained were 90.85% and 88.34% at 45 epochs. For the testing stage, experiments were conducted with different amounts of testing data. The highest testing accuracy was 82.5%, achieved by the dataset with 50 tweets in each category.

Short-term impact of the COVID-19 confinement measures on health behaviours and weight gain among adults in Belgium

BackgroundIn Belgium, confinement measures were introduced on the 13th of March 2020 to curb the spread of the coronavirus disease (COVID-19). These measures may affect health behaviours of the population such as eating habits, physical activity and alcohol consumption, which in turn can lead to weight gain resulting in overweight and obesity, increasing the risk of several chronic diseases, but also of severe COVID-19. The purpose of this study is to assess the impact of confinement measures on health behaviours and their associations with weight gain.MethodsData were derived from the second national COVID-19 health survey. Data were collected between the 16th and the 23rd of April 2020. The recruitment of participants was based on snowball sampling via Sciensano’s website, invitations via e-mail and social media. The study sample includes participants aged 18 years and over with no missing data on the variables of interest (n = 28,029). The association between self-reported weight gain and health behaviour changes, adjusted for gender, age group and household composition was assessed through OR’s (95% CI) calculated with logistic regression models, using post-stratification weights.ResultsOverall, 28.6% reported weight gain after 6 weeks of confinement. Higher odds of weight gain were observed among participants who increased or decreased their consumption of sugar-sweetened beverages (OR = 1.39 (1.15–1.68) and 1.29 (1.04–1.60), respectively), among those who increased their consumption of sweet or salty snacks (OR = 3.65 (3.27–4.07)), among those who became less physically active (OR = 1.91 (1.71–2.13)), and among those who increased their alcohol consumption (OR = 1.86 (1.66–2.08)).ConclusionsThe most important correlates of weight gain during confinement were an increased consumption of sweet or salty snacks and being less physically active. These findings confirm the impact of diet and exercise on short term weight gain and plead to take more action, in supporting people to achieve healthier behaviours in order to tackle overweight and obesity, especially during the COVID-19 pandemic.

Nutrition and hypertension : What one should pay attention to in addition to the pharmaceutical treatment

Arterial hypertension along with anumber of dietary risk factors top the global mortality statistics for noncommunicable diseases. The so-called Western diet and an increasingly sedentary lifestyle are partly responsible for the high prevalence of hypertension. Ahealthier diet has amajor role in the prevention and treatment of hypertension. Given the wide range of options for dietary modifications, it is necessary to define important evidence-based cornerstones of ablood pressure-lowering diet and to assess its blood pressure-lowering potential. While extensive evidence has been generated in recent decades and guidelines emphasize healthier diets, implementation of dietary modifications remains achallenge in everyday clinical practice. Information and education as well as medical and nutritional support for patients can help to implement measures, such as weight and sodium restriction in the long term to improve the prognosis of patients with hypertension.

Production and effect of vermiwash singly and in combination with vermicompost on the growth, development and productivity of tomato in the greenhouse in Suriname

Abstract. Awadhpersad VRR, Ori L, Ansari A. 2021. Production and effect of vermiwash singly and in combination with vermicompost on the growth, development, and productivity of tomatoes in the greenhouse in Suriname. Asian J Agric 5: 29-34. In Suriname farmers often largely rely on high inputs of synthetic fertilizers and pesticides to achieve high yield. To overcome this, sustainable agriculture seeks to introduce agricultural practices that are environmentally sound, economically viable, and socially supportive. In the present study, the effect of vermicompost and vermiwash and in combination was evaluated on the growth and yield of tomato (Lycopersicon esculentum Mill.) in the greenhouse. The experiment was a Randomized Block Design with four treatments and three replications. The growth parameters were measured for plant height, shoot wet and dry weight, root weight, and length, and yield in terms of the number of fruits and fruit weight. The produced vermiwash was a brownish colored liquid and had all the essential macro and micro plant nutrients, which indicates an environmentally friendly enriched nutrient liquid fertilizer for sustainable agriculture. The research results at harvest time indicated that the plant height, shoot fresh and dry weight, root weight, root density, root length, yield and fruit weight were higher for the plants treated with a combination of vermicompost and vermiwash. It was also noted that the flowering and fruiting ratio were significantly enhanced by application of vermiwash as a foliar spray. The combination of vermicompost and vermiwash (50 g + 50 mL) significantly (p < 0.05) resulted in the highest yielding plants, followed by vermiwash (100 mL) and vermicompost (100 g).

Characterization and suppression of the hydrodynamic instability in the time domain for acoustic propagation in a lined flow duct

The gradient term suppression (GTS) method for removing the hydrodynamic instability appearing in the time-domain solutions of the linearized Euler equations (LEE) along a lined flow duct is assessed. For this, the characterization of a convective instability in the time domain, with the aid of a complementary modal analysis, is first presented. The effect of the mesh size and spatial filtering on the instability is investigated. In particular, a convergence of the instability in the time domain is achieved for a small enough grid size. The consequence of suppressing the mean flow gradient term on the modes is then investigated. It is shown that the unstable modes are indeed removed, but also that acoustic modes are significantly modified, especially for low Helmholtz numbers. The GTS method is finally applied to the NASA grazing impedance tube benchmark. It is found that tuning the weight of the mean flow gradient term within the LEE can be effective for suppressing the instability while conserving a reasonable accuracy of the acoustic component.

Elaboration of the initial requirements in the design activities

In solving the design problems, the initial requirements’ clear statement significantly affects the design process’s final result. Right from when the design problems are identified, the main requirements must be defined so that the final product meets the designed equipment requirements. Designers noted that design requirements do not have equal significance, and different solutions have been proposed to consider their weight in terms of end-use properties. The weighting can be achieved by simpler and operative methods and by more detailed methods of analysis. The paper approaches the problem of using the double input matrix method for weighting the functional requirements when discussing the problem of designing equipment to investigate the behavior of a computer component when the environment temperature is different compared to the normal temperature. The functional requirements assessment could provide an overview of the financial resources that could be invested in components to adequately meet the functional requirements. A first version of the tracked equipment was designed so that the previously established functional requirements are met.

WITHDRAWN: Nano-technologies and Nano-materials for civil engineering construction works applications

The applications of Nano-technologies and related Nano-materials have observed the possibility of using such materials in general engineering applications, spanning a range of topics from structural engineering, geotechnical reinforcement, and building materials. The objective of this paper is state an overview of Nano-technologies applications in civil engineering in general and exemplified the usage of Nano-materials in some applications, where there are many nanoscale methods that use nanomaterials, which have proven their efficiency when used in construction applications. Metal structures of light weight and stronger in terms of withstanding different conditions, and coating materials with technical specifications such as high temperature tolerance and moisture resistance, cement material added to some materials that improve some chemical properties, materials included in reducing the rate of thermal transfer and increase the insulation of the basic properties. The role of nanomaterials in engineering applications. Furthermore, it has been proved that adding some Nano-materials to the constricting essential materials like cement or steel will improved their main properties like increasing strength performance, durability, and many other properties.