bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Room Cleanliness Based on Digital Image Processing using SVM and NN Algorithm
Authors: Suparni Suparni , Rachmi Hilda , Kaafi Ahmad Al
Published: August 2022

A clean environment can prevent us from disease and can increase productivity. A neat and clean room arrangement can affect health, avoiding the possibility of stress, lethargy, and depression. The room recognition process based on its neatness is carried out through a process of matching and comparing the images that are used as training and testing sets. Technological developments make it possible to detect room conditions through image. Detection uses image processing by classifying images into 2 categories, clean and messy. It has been widely used in various fields, one of which is hospitality. In determining the clean room and messy room has problems due to image quality, different lighting, and image similarity. This study aims to detect clean and messy spaces by comparing the Support Vector Machine and Neural Network methods on a dataset of 199 images. Based on the test, the highest accuracy classification value was 98.0% for the Neural Network method with an AUC of 0.999
Detection Malaria Base Microscope Digital Image with Convolutional Neural Network
Authors: Untoro Meida Cahyo , Muttaqin Muhammad
Published: August 2022

Malaria is a tropical disease that infects human red blood cells caused by infection with the plasmodium parasite. Plasmodium parasites spread to humans through female Anopheles mosquitoes and can reproduce in human blood cells. Malaria is a health problem that is at risk of causing other health problems such as anemia and even death. The current gold standard for malaria diagnosis is laboratory diagnosis by microscopic examination to find the malaria parasite through the blood cells of the patient. However, the diagnosis of malaria through microscopic observation of blood cells has the potential to take a long time, because the plasmodium parasite has a very small size. The malaria detection system using the Convolutional Neural Network (CNN) method is designed to detect malaria in human blood cells. CNN is a machine learning method designed to classify objects in an image. The system was built in three stages of development, namely the development of a CNN model for malaria detection, software development and hardware development. The hardware components used in the system include Raspberry pi, Raspberry Pi camera module, and LCD. The results of the malaria detection test using the CNN model gave an accuracy of 98.76% which was tested on blood cell images from a microscope
Perfomance analysis of Naive Bayes method with data weighting
Authors: Afdhaluzzikri Afdhaluzzikri , Mawengkang Herman , Sitompul Opim Salim
Published: August 2022

Classification using naive bayes algorithm for air quality dataset has an accuracy rate of 39.97%. This result is considered not good and by using all existing data attributes. By doing pre-processing, namely feature selection using the gain ratio algorithm, the accuracy of the Naive Bayes algorithm increases to 61.76%. This proves that the gain ratio algorithm can improve the performance of the naive bayes algorithm for air quality dataset classification. Classification using naive bayes algorithm for air quality dataset. While the Water Quality dataset has an accuracy rate of 93.18%. These results are considered good and by using all the existing data attributes. By doing pre-processing, namely feature selection using the gain ratio algorithm, the accuracy of the Naive Bayes algorithm increases to 95.73%. This proves that the gain ratio algorithm can improve the performance of the naive bayes algorithm for air quality dataset classification. Classification using Naive Bayes algorithm for Water Quality dataset. Based on the tests that have been carried out on all data, it can be seen that the Weight nave Bayes classification model can provide better accuracy values ​​because there is a change in the weighting of the attribute values ​​in the dataset used. The value of the weighted Gain ratio is used to calculate the probability in Nave Bayes, which is a parameter to see the relationship between each attribute in the data, and is used as the basis for the weighting of each attribute of the dataset. The higher the Gain ratio of an attribute, the greater the relationship to the data class. So that the accuracy value increases than the accuracy value generated by the Naïve Bayes classification model. The increase in accuracy in the Naïve Bayes classification model is due to the number of weights from the attribute selection in the Gain ratio.
Api Service Infrastructure Using Kubernetes And Terraform Based On Microservices Ngoorder.Id
Authors: Habibi Azwar Riza
Published: August 2022

The growing number of ngorder.id service users causes traffic to Api Ngorder to be higher, so a new infrastructure is needed in order to maintain Api Ngorder uptime during high traffic and also maintain service stability. In the implementation process, Api scripts that are currently running on a monolith cluster will be divided into several categories and will be split into several kubernetes clusters. To support autoscale, a Horizontal Pod Autoscaler was added, and to route traffic it would use the Api Gateway from Amazon Web Service. In this infrastructure test, it is done by testing the logic script function using Katalon Studio and testing at the infrastructure level by doing a crash test in the form of failing to deploy and terminating the pod, as well as performing a stress test to test autoscaling in the cluster, the entire test can be run by performing a stress test on the php service pods. by setting the autoscaler parameter Memory Utilization Percentage 125%, 150% and 250%, proving that the HorizontalPodAutoscaler (HPA) as an autoscaler handler can function according to the targets and parameters that have been determined.
Development of Android-Based Early Reading Learning Media
Authors: Hapsari Estuning Dewi , Yuda Yoga Prisma , Mubarok Yoga Akmal
Published: August 2022

Early reading is a skill that students should have. This skill becomes a provision for the next stage of skills .Learning to recognize letters, especially early reading in Golan Kindergarten during the pandemic, experienced problems. Students feel less interested when the learning process is carried out conventionally. In addition, parents also have difficulties when it comes to delivering material to children.  Through the use of android-based learning media, the learning process is expected to attract students. The method developed the Borg & Gall model, which consisted of ten stages. The data collection techniques used include observation, interviews, and questionnaires. Observation is used to find out the learning conditions in schools. Interviews, conducted with teachers to find out the use value of the media created. Meanwhile, the questionnaire is used as a reference to find out the level of needs in schools. The resulting learning media is tested through media expert validation tests and practicality tests. Validation of media experts to assess whether media is suitable for use as an alternative to learning media in schools. Practicality test, used to assess the level of practicality of the resulting medium.  The results of media expert validation obtained a percentage of 81.5, stating that the media was valid. The practicality test was 8,262, and the mean score of students was 77. The two results presented that the android-based learning media for early reading was feasible
Supervised Model for Sentiment Analysis Based on Hotel Review Clusters using RapidMiner
Authors: Juliadi Revin Novian , Puspitarani Yan
Published: August 2022

Customer feedback in the modern era like today is mostly presented in the form of digital reviews, including customer feedback at an inn or hotel, customer feedback is very valuable data where from this data the management can find out, identify and analyze the customer experience and what they need. With customer feedback in the form of digital reviews, it will allow a lot of data that can be obtained by hotel management and will provide many benefits if the data is processed correctly. To take advantage of large  text review data, a combination of data mining and natural language processing techniques was chosen to process text in depth and efficiently.  Text mining in the form of creating an opinion mining model using the Naïve Bayes classification algorithm is applied to find information and measure the main sentiments expressed in the reviewed text dataset, then the application of K-Means text grouping aims to group texts and get information about the main topics discussed from the content of the review dataset text in each group . By applying the constructed sentiment analysis model, approximately 90.90% accuracy results were obtained in reading texts and measuring sentiments related to hotel customer feedback data.
Performance Comparison of K-Means and DBScan Algorithms for Text Clustering Product Reviews
Authors: Andriyani Fitri , Puspitarani Yan
Published: August 2022

The purpose of this study was to compare the accuracy performance of the K-Means and DBScan algorithms in clustering product reviews. This comparison evaluated to determine which algorithm is better in terms of accuracy. The two algorithms were chosen because they have different methods of clustering, K-Means uses centroid-based while DBScan uses density-based. Text clustering results can be implemented on e-commerce platforms, marketplaces or product review platforms. This can help customers in deciding what product they will buy. One of the factors that customers have difficulty in determining what product they will buy is the number of reviews that each product has, and the difficulty in concluding the advantages of each product that will be matched their needs or desires. With text clustering, it can be easier and faster for customer to determine whether the product is worth buying or not based on the product reviews they read. The data set used in this study is a review of the Cetaphil Facial Wash product from the Female Daily website. Firstly, data set goes through the Text Pre-Processing stage; then it will be clustered using two algorithms, K-Means and DBScan. After that, the results of the clustering of the two algorithms calculated for their accuracy performance and the performance results obtained. From the results of this study, it concluded that, in the review clustering of Cetaphil Facial Wash products, DBScan has 99.80% accuracy, which higher to compare with K-Means with only has 99.50% accuracy.
Forecasting of Health Sector Stock Prices During Covid-19 Pandemic Using Arima And Winter Methods
Authors: Tamamudin Tamamudin , Rusyida Wilda Yulia
Published: August 2022

This study aims to compare the accuracy of the ARIMA and WINTER methods in forecasting or predicting the daily stock price of the health sector. The data used in this study is secondary data in the form of historical data on the daily share price of PT. Darya Varia Laboratori, PT. Indofara Persero, PT. Kimia Farma, PT. Kalbe Farma, and PT. Merck Indonesia from March 14, 2020 to April 14, 2021. From the results of the research, PT. Kimia Farma is suitable to use the ARIMA (1, 0, 1) model, while others use the Additive and Multiplicative WINTER method. The daily stock price predictions of the five issuers from April 14, 2021 to July 15, 2021 tend to increase. This is presumably because investors tend to increase their capital due to the effect of health protocols that are getting tighter during the second wave and the assumption is that when the level of virus spread has begun to decline, the health sector shares will continue to rise, although not significantly.
A Decision Model For Tackling Logistic Optimization Problem in Online Business Environment
Authors: Syahraini Syahraini , Efendi Syahril , Sitorus Syahriol
Published: August 2022

Online business has increased during the COVID-19 pandemic, but the emergence of a number of problems, namely reduced material supply, price fluctuations because an item is difficult to distribute and slow delivery due to transportation of goods based on the type of transportation used (Trucks, Trains, Airplanes and Ships). a number of declines due to the COVID-19 virus pandemic, resulting in longer order waiting times. Pick-up and Delivery Issues are variations of Vehicle Routing Issues that appear in many real-world transportation scenarios, such as product delivery and courier services. This work studies the Pickup and Delivery Problem with Time Windows, where goods must be transported from one location to another, with taking into account certain time limits and vehicle capacity. This aims to minimize the number of vehicles used, as well as operational costs for all routes. To solve this problem, a mathematical model in the form of is used Mixed Integer Linear Programming (MILP) from Pickup and Delivery Problems with Time Windows
Using the Deep Constrained Clustering Approach to Create a Business Profile
Authors: Latif Abdul , Sutarman Sutarman , Damius Open
Published: August 2022

Identification of customers in the business sector that really needs to be done as an evaluation of a business that is run so that it can continue to grow and be able to follow business developments in the same sector. The deep constraint clustering approach is used to cluster customers towards a business. In this study, a clustering of customers using rail mass transportation will be carried out. The results achieved are the formation of 6 clusters using trains be built. The result of research expected to be a consideration in improving services to the company
Development of The Steepest Descent Method for Unconstrained Optimization of Nonlinear Function
Authors: Evada Zakiah , Tulus Tulus , Herawati Elvina
Published: August 2022

The q-gradient method used a Yuan step size for odd steps, and geometric recursion as an even step size (q-GY). This study aimed to accelerate convergence to a minimum point by minimizing the number of iterations, by dilating the parameter q to the independent variable and then comparing the results with three algorithms namely, the classical steepest descent (SD) method, steepest descent method with Yuan Steps (SDY), and q-gradient method with geometric recursion (q-G). The numerical results were presented in tables and graphs. The study used Rosenbrock function f(x)=〖(1-x_1)〗^2+100〖(x_2-〖x_1〗^2)〗^2  and determined μ=1,σ_0=0.5,β=0.999, the starting point (x_0) with a uniform distribution on the interval x_0= (-2.048, 2.048) in R^2, with 49 starting points (x_0) executed using the Python online compiler on a 64bit core i3 laptop. The maximum number of iterations was 58,679. Using tolerance limits as stopping criteria is 10-4 and the inequality 〖f(x〗^*)>f to get numerical results. q-GY method down ward movement towards the minimum point was better than the SD and SDY methods while the numerical results of the Rosenbrock function showed good enough performance to increase convergence to the minimum point
Support Vector Machine Using A Classification Algorithm
Authors: Ovirianti Nurul Huda , Zarlis Muhammad , Mawengkang Herman
Published: August 2022

Support vector machine is a part of machine learning approach based on statistical learning theory. Due to the higher accuracy of values, Support vector machines have become a focus for frequent machine learning users. This paper will introduce the basic theory of the Support vector machine, the basic idea of classification and the classification algorithm for the support vector machine that will be used. Solving the problem will use an algorithm, and prove the effectiveness of the algorithm on the data that has been used. In this study, the support vector machine has obtained very good accuracy results in its completion. The SVM classification uses kernel RBF with optimum parameters Cost = 5 and gamma = 2 is 88%.
Analysis of Air Quality Measuring Device Using Internet of Things-Based MQ-135 Sensor
Authors: Sitanggang Delima , Sitompul Chris Samuel , Suyanto Jao Han , Kumar Sharen , Indra Evta
Published: August 2022

Air is a gas that is indispensable for the survival of living beings. As the times progress, the air we breathe is increasingly not good for the health of living beings. In most situations, humans cannot tell the difference between good and bad air conditions. The purpose of this research is to design a tool that can monitor air quality in many places using an Internet of Things-based concept, the MQ-135 gas sensor and display it on a 16x2 LCD and Blynk application. This study uses a direct test method to identify gases around the MQ-135 sensor with the NodeMCU ESP 8266 as a controller. Air quality is divided into 5 categories, which consists of good, average, unhealthy, very unhealthy, and dangerous. After the air quality value is displayed on the 16x2 LCD screen, the user can monitor the air quality remotely using the blynk application on the smartphone. It can be concluded that the design of this tool can detect air quality in classrooms, vehicle exhaust fumes, gas lighters, house rooms, and burned paper. If the air quality is bad, the buzzer will release the sound to notify that the air quality is poor according to the index of air quality.
E-government in the public health sector: kansei engineering method for redesigning website
Authors: Zonyfar Candra , Maharina Maharina
Published: August 2022

The role of government health websites as a source of referrals and credible health information is very important, especially now that everything is digital. People use the internet and make health websites as the first step in finding health information, government policies related to health, and public health services. So it is very important to consider the user aspect in designing the appearance of an appropriate health website. This study utilizes the Kansei Engineering KEPack type 1 in analyzing various emotional factors related to the e-government website interface in the health sector. So that it can be found that the psychological emotional factors of users are important and become the main recommendations in the design of the website interface. We are focuses on user preferences for the e-government site interface of the Karawang District Health Office with the Kansei Engineering Type I approach. The Kansei Engineering study was conducted to analyze various emotional factors related to the user interface by comparing 5 specimens of e-Government sites in the health sector. A total of 20 kansei words were identified which were then processed using the multivariate statistical method Cronbach's Alpha (CA), Coefficient Correlation Analysis (CCA), Factor Analysis (FA). The result is that 4 kansei words have a high influence and successfully present a matrix of design element recommendations with 7 main elements and 45 sub-criteria for specific design elements.
Evaluating the utility of deep learning for predicting therapeutic response in diabetic eye disease
Authors: Dong Vincent , Sevgi Duriye Damla , Kar Sudeshna Sil , Srivastava Sunil K. , Ehlers Justis P. , Madabhushi Anant
Published: August 2022

Purpose

Deep learning (DL) is a technique explored within ophthalmology that requires large datasets to distinguish feature representations with high diagnostic performance. There is a need for developing DL approaches to predict therapeutic response, but completed clinical trial datasets are limited in size. Predicting treatment response is more complex than disease diagnosis, where hallmarks of treatment response are subtle. This study seeks to understand the utility of DL for clinical problems in ophthalmology such as predicting treatment response and where large sample sizes for model training are not available.

Materials and Methods

Four DL architectures were trained using cross-validated transfer learning to classify ultra-widefield angiograms (UWFA) and fluid-compartmentalized optical coherence tomography (OCT) images from a completed clinical trial (PERMEATE) dataset (n=29) as tolerating or requiring extended interval Anti-VEGF dosing. UWFA images (n=217) from the Anti-VEGF study were divided into five increasingly larger subsets to evaluate the influence of dataset size on performance. Class activation maps (CAMs) were generated to identify regions of model attention.

Results

The best performing DL model had a mean AUC of 0.507 ± 0.042 on UWFA images, and highest observed AUC of 0.503 for fluid-compartmentalized OCT images. DL had a best performing AUC of 0.634 when dataset size was incrementally increased. Resulting CAMs show inconsistent regions of interest.

Conclusions

This study demonstrated the limitations of DL for predicting therapeutic response when large datasets were not available for model training. Our findings suggest the need for hand-crafted approaches for complex and data scarce prediction problems in ophthalmology.
Free Will, the Holocaust, and The Problem of Evil
Authors: Johnson David Kyle
Published: August 2022

In this paper, I ask whether the occurrence of the Holocaust is good reason to doubt the existence of God. To do so, I will explore different varieties of the problem of evil to determine exactly what kind of argument the problem of the Holocaust is. I will then explore proposed solutions to the relevant varieties of the problem of evil to see if they can solve the problem of the Holocaust. The logical problem of the Holocaust, I will argue, can only be solved at the cost of embracing an unorthodox (heretical?) “open” view of God. The evidential problem of the Holocaust can be solved, but only at the cost of embracing a deistic view of God that would entail that he might as well not exist. What’s more, both solutions are rooted in the idea of free will. Consequently, either the theist will have to answer the myriad of arguments which suggest that libertarian free will doesn’t exist, or embrace a compatibilist notion of free will which renders the above solutions moot and turns the problem of the Holocaust into a version of the logical problem of natural evil—a problem which has not yet been satisfactorily solved.
An “Italian Citizen of Jewish Race”: Primo Levi on Belief, Blasphemy and Becoming a Jew
Authors: Rempel Morgan
Published: August 2022

While religious belief is not a dominant theme in Levi’s Holocaust writing, over the course of a forty-year writing career this longstanding nonbeliever offers a number of thoughtful reflections on God, faith, and the Holocaust. The first half of my paper examines the Jewish identity of the young Levi, as well as the isolated thoughts on God, faith, and religion found in Survival in Auschwitz (1947). While that early work deliberately focuses on day-to-day exigencies amidst the unrelenting struggle for existence at Auschwitz-Monovitz, it still raises provocative questions about prayer and belief in the context of the Holocaust. In his later writing and interviews, Levi digs deeper and with greater frequency into matters concerning God and the Holocaust. From the recurring charge of “blasphemy” to his career-long characterization of his unlikely survival as a matter of simple luck rather than Divine Providence, my paper goes on to examine the later Levi’s increasingly subtle reflections on matters related to God and the Holocaust. Finally, I look at the later Levi’s repeated insistence that the years of persecution brought with them a newfound understanding of himself as a Jew. By examining his thoughts on how his Auschwitz imprisonment simultaneously confirmed his nonbelief and inaugurated his self-conception as a Jew, my paper demonstrates that Levi’s scattered reflections on God, faith, and the Holocaust are both challenging and well worth our careful, continued study.
HANDWRITING EXPERTISE IN THE FORENSIC SCIENCE CENTRE OF LITHUANIA: PRESENT ACTIONS AND FUTURE VISION
Authors: Tamošiūnaitė Rasa
Published: August 2022

Recently, the number of expert investi gations in handwriting evidence at the Lithuanian Forensic Examination Centre (LTEC) has significantly decreased. The decrease has been observed for several years already.

The present article analyses possible reasons for the decrease in the number of expert investigations in handwriting in LT EC and the importance of such investigation in the context of judicial research, court proceeding, and criminal investigations.

Also, the article deals with the use of electronic signatures and associated security problems in the digital environment.

Key words: handwriting examination, signature, digital signature, digitized sig-
nature, informativeness of signatures.
TYPES OF WATERMARKS ON BANKNOTES AND METHODS OF THEIR IMITATION
Authors: Zubova Nataliia , Naumenko Serhii , Somov Viktor
Published: August 2022

The article deals with the consideration of ways to imitate watermarks in the manufacture of counterfeit banknotes. The watermark is an important public security element for banknotes issued for cash circulation. The basis of any banknote related to paper money is banknote paper. The article briefly describes the stages of the technological process of manufacturing banknote paper and methods for forming watermarks on it. The criteria for the classification of watermarks depending on their location on the banknote (general, local stripe), in relation to the overall tone of the paper (one-tone, two-tone, local, filigree, combined), composition, as well as drawings illustrating these types of watermarks are given. signs. The watermarks developed using modern technologies in recent decades are described, as well as their illustrations. The levels of counterfeiting are determined depending on the subject and its technical capabilities for the manufacture of counterfeit banknotes. The ways of imitation of watermarks are generalized. Firstly, watermarked paper intended for other purposes can be used to make counterfeit banknotes. Secondly, the imitation of watermarks is possible using specially made forms: embossed, used for embossing paper, and printed-screen or letterpress. Widely used to imitate watermarks of copiers. Less common are watermarks, which are imitated using fat-containing substances, or painted with a dye. The article provides examples of the implementation of the relevant methods with their illustration based on studies of counterfeit banknotes.

Key words: banknote, banknote paper, watermark, types of watermarks, watermark imitation.
FIXATION AND EXAMINATION OF VOLUMETRIC TRACKS OF FOOTWEAR USING 3D SCANNING TECHNOLOGIES
Authors: Kovalenko Artiom
Published: August 2022

The article is devoted to demonstrating the possibilities of using 3D scanning technologies to capture and study volumetric footprints. The author notes that traditional methods of visual fixation of such reflections (description, measurement, photography) are not informative enough, and the main method of object fixation (making plaster and other molds) is associated with the risk of significant damage to the fixed trace. At the same time, the use of contactless 3D scanners allows you to quickly, efficiently, and non-invasively create detailed digital 3D models of volumetric footprints.

The author experimentally tested the fixation of shoe footprint in terms of inspection of the scene (at the place of its detection), scanning of the potential trace-forming object in terms of its separate inspection (in the laboratory), as well as a study of 3D models using laser 3D scanners Artec Leo and Artec Space Spider and Artec Studio 16 software. Possibilities of using Artec Studio 16 software to study and compare 3D models of forensically significant objects are demonstrated.

The author’s experiments showed that with the use of 3D scanners with a scanning accuracy of up to 0.1 mm and the appropriate software, it is possible to scan and examine shoe prints with medium and large tread pattern elements, and using scanners with scanning accuracy up to 0.05 mm and more – fixation of traces left by shoes with more complex patterns of sole protector. The 3D models obtained in this way are accurate and detailed, accurately convey the size, shape, and color of scanned objects, and can be used for visual inspection and comparison of objects, and their visual demonstration (for example, in court). The level of detail of 3D models obtained with Artec Leo and Artec Space Spider allows comparative studies of shoe traces and the corresponding traceorming objects on their 3D models. Methods similar to those described in this article can be effectively used to capture and study other types of volumetric traces and their corresponding trace-forming objects: traces of tire treads and other parts of vehicles, breakage tools, bullet holes, etc.

Key words: 3D scanning, 3D scanner, fixation, foot traces, comparative research.
Intervención terapéutica en resiliencia a pacientes drogodependientes
Authors: Pedroso Roller Taimy , Tarazona Mesa Anicia Katherine
Published: August 2022

Esta investigación fue elaborada con el objetivo de aplicar una intervención terapéutica para fomentar resiliencia en pacientes drogodependientes. Se realizó mediante un enfoque mixto con un diseño no experimental longitudinal. Fue de tipo descriptivo y utilizó el método de análisis síntesis en una muestra de 19 pacientes. Se aplicó el instrumento SV-RES de Saavedra y Villalta para medir la resiliencia de los pacientes determinando la existencia de un nivel de resiliencia alto del 37%, medio 53% y bajo del 10% previo a la intervención. Los factores por componentes que mayor impacto tuvieron en los niveles de resiliencia alcanzados antes y después de la intervención terapéutica: Yo soy – Yo estoy (identidad, autonomía y satisfacción); Yo tengo (metas y vínculos); Yo puedo (autoeficacia). Se logró un incremento del nivel de resiliencia alto del 74% y una disminución del nivel bajo de un 0%, evidenciando el impacto positivo de la intervención en los pacientes drogodependientes.
Karakteristik Asap Cair Dari Limbah Kulit Buah Pinang (Areca Catechu) Dengan Berbagai Variasi Suhu Pirolisis Dan Waktu Pirolisis
Authors: Yulia Ruka , Lamona Asmeri , Makmur Teuku , Yuslinaini Yuslinaini
Published: August 2022

Limbah kulit buah pinang merupakan bahan yang melimpah yang masih kurang penggunaannya. Limbah ini mengandung hemiselulosa, selulosa dan lignin yang merupakan sumber komponen dalam pembuatan asap cair. Tujuan dari penelitian ini adalah untuk menentukan karakteristik  asap cair dari limbah kulit buah pinang dengan berbagai variasi suhu pirolisis dan waktu pirolisis. Penelitian ini menggunakan metode deskritif yang terdiri dari variabel suhu pirolisis yaitu 250oC, 300oC, 350oC, 400 oC, 450oC dan waktu pirolisis yaitu 2 jam dan 3 jam. Hasil penelitian menunjukkan bahwa kondisi optimum diperoleh pada suhu pirolisis 450oC dan waktu pirolisis 3 jam dengan rendemen sebesar 25,2%, pH sebesar 0,23, kadar asam asetat 32,4%, dan kadar fenol sebesar 0,63 ppm.
Kesetimbangan Adsorbsi Zat Warna Metilen Blue dengan Adsorben Karbon Aktif Tongkol Jagung Terimpregnasi Fe2O3
Authors: Ristianingsih Yuli , Istiani Alit , Irfandy Fauzan
Published: August 2022

Methylene blue merupakan zat warna organik yang banyak digunakan pada industri tekstil, memiliki sifat mudah larut dalam air dan berbahaya bagi kesehatan manusia. Pada penelitian ini, adsorbsi zat warna metilen blue dilakukan dengan menggunakan adsorben karbon aktif dari tongkol jagung yang terimpregnasi Fe2O3. Proses adsorbsi dijalankan pada sebuah reaktor batch selama 120 menit dengan menggunakan adsorben KAJ/Fe2O3 sebanyak 0,025 gram dan kecepatan pengadukan 150 rpm. Tujuan penelitian ini adalah untuk mempelajari pengaruh suhu (30 0C, 40 0C, 50 0C) serta variasi penambahan reagen fenton H2O2 dan tanpa penambahan H2O2 pada proses adsorbsi zat warna metilen blue. Hasil penelitian diperoleh bahwa penambahan reagen fenton (H2O2) dapat meningkatkan kapasitas adsorbsi sebesar 25,98%. Suhu optimum proses adsorbsi terjadi pada suhu 30 0C dengan kapasitas penjerapan rata-rata sebesar 71,93%. Model kesetimbangan adsorbsi yang sesuai pada penelitian ini ada isotherm Langmuir dengan nilai konstanta Langmuir (b) dan kapasitas penjerapan maksimum (qm) yang diperoleh masing-masing sebesar 0,49 dan 15,38 mg/L.
Polycyclic Aromatic Hydrocarbons from Bottled Water: A New Automated Solid Phase Extraction Method and Simulation of Cancer Risk
Authors: Mahdavi Doost Fatemeh , Emamjome Mohammad Mehdi , Jamali Hamze Ali , Karyab Hamid
Published: August 2022

Considering the adverse effects of polycyclic aromatic hydrocarbons (PAHs) on human health and the complexity of their detection in water resources, this study was developed to assess the performance of a new automated device for the identification of PAHs in water based on the solid-phase extraction and to simulate the cancer risk of 16 priority PAHs by Monte Carlo technique. All operational modes of extraction were automatically performed using the proprietary software program. Three spiked aliquots of PAHs including 100, 500, and 1000 ng/L were used to evaluate the performance of the automated-solid phase extraction (SPE) apparatus. The time of extraction in the automatic-SPE apparatus was 50±4 minutes for simultaneous extraction of 4 water samples, which was four times faster than that of manual-SPE apparatus. The mean recoveries of PAHs were 89.22±4.94, 91.70±4.45, and 94.61±6.28% in spiked samples, with a mean of 91.84±5.22%. Except for naphthalene, all obtained recoveries were in an acceptable range (85-115%). The results of Monte Carlo simulation showed that the cancer risk attributable to eight detected PAHs including naphthalene, fluorene, phenanthrene (Phe), benzoanthracene, chrysene, benzo(k) fluoranthene, indeno(cd)pyrene, and dibenzo(a,h)anthracene ranged from 0.05E-6 to 0.11E-6, with the cancer risk of 0.012E-6 having the highest probability (P=0.82). Additionally, this simulation showed that 99% of the probability density of cancer risk was located within the range lower than 0.05E-6. Our results showed that the novel automated-SPE apparatus could be utilized for the extraction of PAHs from water resources with a good recovery (85%-115%), high operational speed, and potential for separation of solvents from the air in the drying step. Therefore, this device can be used for the extraction of trace PAHs and similar organic compounds from water resources.
The Effect of Eight Weeks of Incremental Pump Body Training on Some Atherogenic Factors in Obese Women With Dyslipidemia
Authors: Lailaei Atefeh , Vafaei Morvarid , Abedi Bahram
Published: August 2022

Background: Dyslipidemia is one of the main risk factors for coronary artery disease, stroke, and peripheral vascular disease. This study aimed to evaluate the effect of eight weeks of incremental pump body training on some atherogenic factors in obese women with dyslipidemia. Materials and Methods: In this quasi-experimental study, 40 obese female subjects in the age range of 30-50 years suffering from dyslipidemia were randomly divided into two groups of body pump training (n=20) and control (n=20). The body pump training program consisted of eight weeks with a frequency of 3 sessions per week for 45 minutes with overload and 48 hours of rest. Data were analyzed using independent samples t test and paired samples t test. Results: The results showed that eight weeks of body pump training significantly decreased triglyceride, cholesterol, low-density lipoprotein (LDL), and atherogenic index (AI) in obese women with dyslipidemia, while there was a significant increase in high-density lipoprotein (HDL) (P˂0.001). Conclusion: The results of this study show that body pump training can properly prevent the progression of dyslipidemia in people suffering this complication.
Combination Therapy of ReciGen Interferon, Methylprednisolone, and Sovodak as a Candidate for Treatment of Patients With Severe COVID-19 in Iran: A Case Series
Authors: Kamiab Zahra , Esmaeili Nadimi Ali , Bahrehmand Fatemeh
Published: August 2022

Introduction: During the current worldwide pandemic of coronavirus disease 2019 (CPVID-19), this disease was first identified in Iran at the end of February. This study was conducted to examine patients with severe COVID-19 disease, who were treated with three medications, namely ReciGen, methylprednisolone, and Sovodak. Case Presentation: We identified 10 patients (3 males and 7 females) with the mean (±SD) age of 55.70±21.48 years, who were admitted to the only referral hospital in Rafsanjan County (Iran) from March to July 2020 with confirmed infections with severe COVID-19. They were treated with the combination therapy of subcutaneous ReciGen interferon every other day, methylprednisolone at a dose of 250 mg every 6 hours for 5 days, and one tablet of Sovodak daily. Conclusion: In the series of cases investigated in this study, the general conditions of all patients improved in terms of their clinical parameters after receiving the combination therapy, and all patients were discharged with a blood oxygen level of≥93% and in good general conditions.
A comparison between the total and best regions of trabecular bone scores and evaluating the added value of combining the trabecular bone scores with bone-mineral density
Authors: Rajaei Alireza , dehghan pooneh , Hatami Samaneh
Published: August 2022

Introduction: Bone mineral density (BMD) and trabecular bone score (TBS) are recognized as two indexes for diagnosis of osteoporosis. Objectives: The present study assesses the TBS performance as an alternative test for BMD. Patients and Methods: A retrospective descriptive study conducted on 2,106 patients were referred to two central hospitals; Resalat and Loghman in Tehran, Iran. Necessary data have been collected for the analysis process, including age, gender, body mass index, and L1-L4 TBS. Results: Four-hundred eligible patients were considered for our analysis process. Among these patients, about 13.8 and 86.3% were men and women with mean ages of 54.04 ± 10.92 and 53.83 ± 10.16 years, respectively (P=0.88). Our study showed a statistically significant difference between the mean TBS of all regions in patients (P=0.001), while this value was dependent on the gender and age of patients. The mean TBS of all regions in women younger than 50 years was significantly higher than those older than 50 years (P<0.001). Moreover, a statistically significant difference was observed between the means of the best regional TBS in all study groups (P<0.001). This study showed the lumbar spine TBS had a negative correlation with body mass index in women, while this correlation was not significant in men. Conclusion: Trabecular bone score can be conducted as a complementary index along with BMD, it can be employed independently as an appropriate indicator for osteoporosis.
Evaluation of FLANG versus mitoxantrone and etoposide for the treatment of refractory/relapsed acute leukemia
Authors: Mehrzad Valiollah , Mirpourian Maryam , Farrokhi Pegah
Published: August 2022

Introduction: Failure to respond to the chemotherapy and relapse occurrence is considerably high in acute leukemia as one of the most common hematologic malignancies requiring emergent efficacious well-tolerated salvage therapy. However, varieties of regimens have been investigated, since the best approach with an optimal response is a question. Objectives: In our study, we aimed to compare the efficacy of FLANG (fludarabine, cytosine arabinoside, mitoxantrone and G-CSF) versus mitoxantrone and etoposide for the treatment of refractory/relapsed acute leukemia. Patients and Methods: In this retrospective cohort study, 45 patients with acute leukemia were randomly divided into two groups of salvage therapy with FLANG (n=23) and mitoxantrone and etoposide (n=22). The patients were followed for five years. Progression-free survival, response to the treatment, chemotherapy-induced toxicity based on Criteria for Adverse Effects version 4 (CTCAE-4), and mortality were compared between the groups. Besides, to estimate the survival Kaplan-Meier curve and Cox regression were used. Results: Comparison of the two regimens revealed insignificant differences in terms of response rate (P=0.87), chemotherapy-induced toxicity (P=0.22) and mortality rate (P=0.26) and etiology of mortality (P=0.98). The median progression-free survival following FALNG and the latter regimen was four months (95% CI: 3.183, 4.862) versus three months (95% CI: 1.777, 4.223; P=0.38 ), respectively. Conclusion: Based on this study, the two salvage regimens of mitoxantrone plus etoposide and FLANG were similar in terms of complete remission, progression-free survival, and toxicity for the cases with refractory/ relapsed acute leukemia. Trial Registration: This study has been registered in the Iranian Registry of Clinical Trials and obtained code IRCT20190618043939N1 (https://en.irct.ir/trial/40272, Ethical code# IR.MUI.MED.REC.1398.586).
Serum level of interleukin-17 in patients with psoriasis
Authors: Sobhan Mohammadreza , Ghasemi Basir Hamid Reza , Seif Rabiee Mohammad Ali , Shadfar Fariba
Published: August 2022

Introduction: Psoriasis is one of the most common chronic and disabling dermatoses. Recent studies showed that interleukin-17 (IL-17) may play a role in the development of psoriasis. Objectives: In this study, serum levels of IL-17 in psoriatic patients was compared with healthy controls; besides, in patients with psoriasis, serum levels of IL-17 were compared with pre-treatment levels, after topical treatments. Patients and Methods: In this case-control study, serum levels of IL-17 were measured and compared in 30 psoriatic patients and 30 healthy individuals matched to age, gender and body mass index. After evaluating the severity of psoriasis with PASI (Psoriasis Area Severity Index), they were treated with psoriasis topical corticosteroids for four weeks. IL-17 and PASI levels were re-evaluated after the treatment without any intervention. Results: Before the start of treatment, the mean±SD of serum level of IL-17 was 6.24±4.65 pg/mL and 2.0 ± 0.75 pg/mL in psoriatic patients and control group, respectively (P=0.001). The mean±SD of PASI severity scale of patients was 10.68 ± 6.65 and 6.16±4.2 before and after treatment, respectively (P<0.001). The mean±SD of serum level of IL-17 of patients before and one month after treatment were 6.24±4.65 and 3.34±1.77 pg/mL, respectively. Conclusion: In psoriatic patients, serum levels of IL-17 increased significantly compared to healthy subjects. Treatment of psoriasis with topical corticosteroids for four weeks reduced the serum level of IL-17 and the severity of disease.
Epidural abscess; a case report
Authors: Zamani Alavijeh Majid , Heydari Farhad , Abootalebi Alireza
Published: August 2022

Spinal epidural abscess is an infectious and debilitating disease of the spine requiring clinical diagnosis and early treatment including medical and surgical. Delay in proper action leads to irreversible neurological complications. In this study, a case with spinal epidural abscess was introduced that trying to help her with minimal spinal lesions and instability by surgery. In this study, it was shown that by making the right and quick decision to do surgery, it can prevent complications and achieve maximum improvement and satisfaction.
Designing a data set for registry of patients with adrenal insufficiency
Authors: Zakerkish Mehrnoosh , Taghipour Mahboubeh , Shahbazian Hajieh , Nouhjah Sedigheh , Moazen Shirin , Latifi Seyed Mahmoud
Published: August 2022

Introduction: Adrenal insufficiency is one of the most important life-threatening disorders with serious complications. Establishing a standard data element can provide earlier diagnosis, timely treatment, and follow-up to reduce disease crisis. Objectives: This study aimed to draft a data set for the registry of patients with adrenal insufficiency. Patients and Methods: The present cross-sectional study developed data elements for the registry of patients with adrenal insufficiency using a two-round Delphi technique of 2015. The informational elements selected by more than 75% of participants with a value of "very high" and "high" were accepted as the main elements. Results: The final data set included four main groups, 15 subclass and 114 data elements for the registry of patients with adrenal insufficiency. Our results have demonstrated that the primary data groups include administrative data; signs, symptoms, medical and family history data elements; paraclinical diagnostic data, treatment, and follow-up data to improve patient management. Conclusion: This study designed data set registry forms for patients with adrenal insufficiency using a standard method. Our finding indicated that, applying a uniform data set can provide better data management, patient care, and prevention of disease complications, especially in adrenal insufficiency disorder.
The dilemma of COVID-19 diagnosis in pregnancy
Authors: Nori Wassan , Hamed Roaa Mokram , Akram Wisam , Munshid Maha Chasib
Published: August 2022

Coronavirus disease 2019 (COVID-19) is a new and rapidly developing health crisis. Ongoing research looks at the prevalence and consequences of COVID-19 in the obstetric community and postnatal period. In the COVID-19 era, pregnant mothers were prone to infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with a higher risk of poor pregnancy outcomes. Therefore, an accurate and early diagnosis is necessary for this vulnerable group screening for asymptomatic carriers is a cornerstone to limiting the COVID-19 pandemic. It is vital to evaluate patients’ clinical symptoms and epidemiological history carefully. Although the serological test, reverse transcription polymerase chain reaction (RT-PCR), can confirm infection, it cannot determine the degree or severity of the illness. Moreover, it has false-negative results. Imaging tests allow an exact diagnosis of lung damage, the severity of the disease, and the classification of patients. Comprehensive analysis of serological and imaging data will assist in the formation of an appropriate clinical diagnosis. This review will discuss what is new and important in confirming COVID-19 infection in pregnant women and the pros and cons of each.
Evaluation of humoral immune responses, effective factors on responses and re-infection in recovered COVID-19 patients
Authors: Asadi-Samani Majid , Soltani Marziyeh , Altememy Dhiya , Imani Fatemeh , Moradi Mohammad Taghi , Kheiri Soleiman , Asadi-Samani Fatemeh
Published: August 2022

Introduction: Despite large studies on the COVID-19 pandemic, little evidence is available on immune response in recovered patients. Objectives: The aim of this study was to investigate the humoral immune responses (IgM and IgG antibodies) in recovered COVID-19 patients and the role of risk factors and symptoms with respect to the immune responses. Patients and Methods: In this descriptive-analytical study, which was conducted by call-out method, the serum levels of IgM and IgG antibodies were measured using enzyme-linked immunosorbent assay (ELISA) in 248 recovered patients. Effective factors on immune response were determined. Re-infection was investigated through patient follow-up and using information drawn from the hospital information system. Chi-square, t test, ANOVA, and regression analysis in SPSS 15 and Stata 14 were conducted to investigate the relationship between variables. Results: IgG positivity was 86.3% among our participants. Among those who did not show antibody response to COVID-19 (IgM- and IgG-), the most common symptoms at admission were fever, muscle pain (90.9%), chills and anorexia (81.8%). IgG levels remained positive in recovered patients for over seven months. IgG response showed a significant relationship with body mass index, hospital stay length, smoking, residence place, mortality rate, vomiting, and appetite (P<0.05). The re-infection rate after recovery was only 1.6%. Conclusion: High seroprevalence of IgG antibody against COVID-19 and low re-infection rate in Chaharmahal and Bakhtiari province was observed. In addition, the effects of factors such as fever, muscle pain, chills, vomiting, and anorexia on immune responses were demonstrated. These results can be used to manage disease control efficiently, and follow up the treatment process and re-infection in the recovered patients.