Evaluating risk factors for protein-energy malnutrition in children under the age of six years: a case-control study from Iran

Introduction: Protein-energy malnutrition is one of the most important public health problems in Iran. It not only accounts for more than half of child mortality but can also produce somatic and mental impairment in survivors. The main aim of this study was to identify risk factors for protein-energy malnutrition in children under 6 years of age in Namin city. Methods: This was a population-based, multicenter case-control study. Seventy-six children with malnutrition and 76 children without malnutrition were randomly recruited for case and control groups. The prevalence of risk factors in the two groups was compared. Data were gathered from a health center database and interviews with mothers and health workers. The Wilcoxon signed-rank test and logistic regression were used for data analysis. Results: Female gender, poverty, short maternal height, and use of unhygienic latrines in the home were significantly associated with childhood malnutrition (P , 0.05). Conclusion: The results of this study indicate four main factors (poverty, small maternal height, female gender, and absence of hygienic latrines in the home) as underlying factors in malnutrition of children under the age of 6 years

FarsTail: A Persian Natural Language Inference Dataset

Natural language inference (NLI) is known as one of the central tasks in natural language processing (NLP) which encapsulates many fundamental aspects of language understanding. With the considerable achievements of data-hungry deep learning methods in NLP tasks, a great amount of effort has been devoted to develop more diverse datasets for different languages. In this paper, we present a new dataset for the NLI task in the Persian language, also known as Farsi, which is one of the dominant languages in the Middle East. This dataset, named FarsTail, includes 10,367 samples which are provided in both the Persian language as well as the indexed format to be useful for non-Persian researchers. The samples are generated from 3,539 multiple-choice questions with the least amount of annotator interventions in a way similar to the SciTail dataset. A carefully designed multi-step process is adopted to ensure the quality of the dataset. We also present the results of traditional and state-of-the-art methods on FarsTail including different embedding methods such as word2vec, fastText, ELMo, BERT, and LASER, as well as different modeling approaches such as DecompAtt, ESIM, HBMP, and ULMFiT to provide a solid baseline for the future research. The best obtained test accuracy is 83.38% which shows that there is a big room for improving the current methods to be useful for real-world NLP applications in different languages. We also investigate the extent to which the models exploit superficial clues, also known as dataset biases, in FarsTail, and partition the test set into easy and hard subsets according to the success of biased models. The dataset is available at https://github.com/dml-qom/FarsTai

Study On The Acoustic Characteristics Of Natural Date Palm Fibres: Experimental And Theoretical Approaches

The present study deals with the acoustic performance of natural fibres originated from the date palm empty fruit (DPEFB) fibres which is mainly considered as agricultural waste. The fibres were processed and fabricated to be sound absorber samples with two different densities of 100 kg/m3 and 200 kg/m3 and with thicknesses of 10–40 mm. The normal incidence absorption coefficients of the sound absorbers were measured using an impedance tube based on ISO 10534-2. The effects of fibre density and sample thickness are discussed. The findings reveal that for density of 100 kg/m3 the absorption coefficient is 0.6–0.8 above 1.5 kHz for the samples with the thickness of 20 mm and 30 mm. For the thickness of 40 mm, the values even reached the value of 0.9. The values can reach 0.7–0.8 above 1 kHz for the density of 200 kg/m3. Mathematical model using the optimized Delaney-Bazley model with Nelder-Mead simplex method is shown to successfully predict the sound absorption coefficient of the fibre samples. The Johnson-Champoux-Allard model follows the trend of the absorption coefficient, but underestimates the measured data at high frequencies above 2.5 kHz

Using the Analytic Network Process Method for Prioritizing and Weighing Shift Work Disorders Among the Personnel of Hospitals of Kerman University of Medical Sciences

Introduction: Increasing population, the need for services, and industrialization of societies have led to a growing demand for shift work. Shiftwork causes several disorders, and determining the weight of each disorders is important for their prevention and treatment. Therefore, the purpose of the present study was to use Analytic Network Process (ANP) to prioritize and weigh shift work disorders among the personnel of hospitals of Kerman University of Medical Sciences. Methods: This cross-sectional, descriptive-analytical study was conducted in 2017 among 300 shift work personnel of 10 public hospitals affiliated with Kerman University of Medical Sciences. ANP was used to prioritize and weigh shift work disorders. To this end, the criteria, sub-criteria, and alternatives were initially identified. Then, shift work disorders were categorized into 7 general criteria, 20 sub-criteria, and 3 alternatives. After designing the ANP and determining the effect of each criterion on the sub-criteria, the ANP questionnaire was developed and administered among the shift work personnel, who filled it out based on ANP. Super Decisions was subsequently used to weigh and prioritize shift work disorders. Results: The results indicated that shift work disorders among the nurses included sleep disorders (0.297), psychological disorders (0.275), digestive disorders (0.137), personal life disorders (0.122), etc., in that order of weighing. With respect to the support staff, the major shift work disorders involved sleep disorders (0.252), digestive disorders (0.198), personal life disorders (0.168), and psychological disorders (0.164). Considering security personnel, the top four shift work disorders were sleep disorders (0.201), digestive disorders (0.186), psychological disorders (0.174), and personal life disorders (0.145). Conclusion: According to the findings, sleep disorders had the highest weight in the three studied groups. Moreover, the night shift had the most profound effect on shift work disorders among the personnel in the three groups. It was followed by the evening shift. Morning shift had the lowest influence on shift work disorders. Therefore, the schedules should be taken to prevent these complications in the shift workers. It is suggested that work shift complications be included in the periodic examination program and, in case of discovery of any rhythmic disorder in each shift workers, the person should not remain in the shiftwork group for some time

Application of Tripod-Beta Approach and Map – Overlaying Technique to Analyze Occupational Fatal Accidents in a Chemical Industry in Iran

The undesirable effects and consequences of occupational fatal accidents have placed a great emphasis on applying preventive measures. This study was aimed to analyze and specify the latent causes of occupational fatal accidents in Exir Chemical Plant, Urmia - Iran in 2008-2009. The analytical Tripod-BETA method was used. A geographic Information System (GIS) was then used to determine a list of the most significant preconditions and active failures contributing to occupational fatal accidents. The total number of recognized preconditions and latent failures were 572 and 852 respectively. The most frequent preconditions and latent failures were determined by overlaying the coded sheets on each other. Results of the study showed that Promoting and enhancement of the company's safety culture, a carrot and stick motivation policy accompanied by comprehensive assessments to prioritize safety training programs, were among recommended preventive actions to control and reduce fatal accidents

Sound absorbers from walnut shell waste: measurement and models

Waste walnut shells have been cleaned, dried, chopped, glued, pressed, and molded to form porous cylinders for measurement of normal incidence sound absorption coefficient spectra in an impedance tube. Porosities and flow resistivities have been measured non-acoustically. Field Emission Scanning Electron Microscopy images, used to obtain fragment size for determining shell density, reveal that the fragment surfaces are rough, which may influence acoustical performance. Measured absorption spectra have been compared with predictions of two analytical models for acoustical properties of rigid porous media, which assume microstructures of identical uniform parallel slanted slits (SS) and non-uniform cylindrical pores with a log normal radius distribution (NUPSD) respectively. Measured values of flow resistivity and porosity are used in the models but tortuosity is adjusted to give best agreement with the quarter wavelength resonance in the measured absorption coefficient spectra. Predictions agree best with data for samples made from the smallest shell fragments. These samples have the highest values of tortuosity, flow resistivity and offer good absorption at speech frequencies which suggests that recyclable and sustainable sound absorbers made from walnut shell wastes could be useful for controlling indoor reverberation.

The Relationship between Occupational Noise Exposure and Noise Induced Hearing Loss (NIHL) in Small-Scale Industries: A Case Study in the City of Damavand, Iran

Background: Exposure to the excessive levels of occupational noise is one of the principal harmful agents affecting the workers’ health. This study aimed to investigate the relationship between the occupational noise exposure and the hearing loss caused by working in small-scale service industries in the city of Damavand, close to the metropolitan capital city of Tehran, Iran. Methods: This descriptive cross-sectional study investigated the occupational noise levels within the 90 small-scale industries (mainly service industries and workshops) working under the supervision of Damavand healthcare network governed by the Iranian ministry of health and medical education. A sound level meter (Bruel and Kjær 2250) was employed to determine the noise exposure levels based on the dB A, and according to the standard ISO 9612: 2009. The audiometric exam tests were performed by an audiometer (model MEVOX SA-900). The obtained data were then analysed by SPSS 16, using linear regression and t-test. Results: The highest measured 8-hour equivalent continuous sound pressure levels (Leqs) were associated with auto body mechanics (89.2 dB A), foundry and casting workers (88.8 dB A), aluminium products fabrication workers (86.32 dB A), blacksmiths and forging (85.8 dB A) carpenters (84.93 dB A), and cabinet manufacturers, respectively (84 dB A). Results from the hearing threshold shifts of the workers from the studied occupational groups revealed that the highest work related hearing loss associated with the right ear occurred among the auto body mechanics, aluminium products fabrication workers and carpenters. However, the most significant work-related hearing loss associated with the left ear was noticed among carpenters, aluminium products fabrication workers, and auto body mechanics, respectively. Pearson correlation coefficient was tested between Leqs, work experience and hearing loss, and the results implied that the progress of workers’ hearing loss was correlated with the increase in work history and experience. Conclusions: The 8-hour Leqs and work experience were, respectively, the most important factors affecting the rate of hearing loss among the participants of this study. Keywords: Noise-Induced Hearing Loss, Sound Pressure Level, Small-Scale Industrie

The Impact of Fiber Size on the Sound Absorption Behavior of Composites Made from Sugarcane Bagasse Wastes Fibers

Natural fibers obtained from the agricultural wastes are a promising source within the field of acoustic and have already shown favorable results for mitigating the noise pollution. Supported by the experimental data and via an eco-friendly approach, the current study evaluates the impact of fiber size on the sound absorption values of the samples fabricated from sugarcane bagasse (SCB) waste fibers. The samples were formed based on the fiber size and constant bulk densities and thicknesses. The empirical models such as Delany-Bazley (D-B model) along with Best-fit-Nelder-Mead method were also employed to predict the acoustic absorption coefficients of the samples. Therefore, the least-square fit procedure was taken to evaluate the results which is compatible with both the impedance test tube and prediction models. Hence, according to the analyses, the lowest fiber size measured the highest absorption performance (α≃0.63) and airflow resistivity (σ = 6750), indicating that the performance of the fibers reached peaks at lower frequency and slightly decreased at mid and high frequency ranges while the fiber size 0.29–0.37 mm saw a slight rise again. Also, airflow resistivity and sound absorption performance of the SCB fibers decreased with increased fiber sizes

Systems Thinking Accident Analysis Models: A Systematic Review for Sustainable Safety Management

Accident models are mental models that make it possible to understand the causality of adverse events. This research was conducted based on five major objectives: (i) to systematically review the relevant literature about AcciMap, STAMP, and FRAM models and synthesize the theoretical and experimental findings, as well as the main research flows; (ii) to examine the standalone and hybrid applications for modeling the leading factors of the accident and the behavior of sociotechnical systems; (iii) to highlight the strengths and weaknesses of exploring the research opportunities; (iv) to describe the safety and accident models in terms of safety-I-II-III; and finally, to investigate the impact of the systemic models’ applications in enhancing the system’s sustainability. The systematic models can identify contributory factors, functions, and relationships in different system levels which helps to increase the awareness of systems and enhance the sustainability of safety management. Furthermore, their hybrid extensions can significantly overcome the limitations of these models and provide more reliable information. Applying the safety II and III concepts and their approaches in the system can also progress their safety levels. Finally, the ethical control of sophisticated systems suggests that further research utilizing these methodologies should be conducted to enhance system analysis and safety evaluations.Peer reviewe