Memberdayakan Guru Sekolah Dasar menulis karya tulis ilmiah di Kabupaten Bone

Abstract The Elementary Teacher is providing services to students to develop students' knowledge, attitudes, and skills. Besides those three aspects, teachers are also required to improve their career by increasing their academic promotion starting from the level of Lector or First Class Junior Superintendent (III/b). There are requirements that must be fulfilled in order to go to the next level of promotion for teachers. One of them is able to show physical evidence in the form of Scientific Paper (KTI). The KTI type must be a result of Classroom Action Research (PTK) and articles. According to the Head of UPTD Dua Boccoe, one of the factors inhibiting the increased of teachers’ level is the KTI requirement. Therefore, it was necessary to conduct a KTI training by collaborating with PGSD Lecturers at VI Campus of UNM Bone in the form of PKM by using the workshop method. The objectives of this activity were (1) to provide knowledge for Dua Boccoe Elementary School teachers to write research articles and (2) Provide writing skills, including articles and non-research articles for teachers of UPTD Elementary School, Dua Boccoe Regency. The method used was a workshop strategy with lecture, question and answer techniques which aimed at providing KTI mastery and assignment methods for writing a draft and KTI development. The results of the KTI workshop activities showed that 20 participants in PKM had mastered KTI knowledge and were able to make KTI in the form of research articles in the ‘good' category

Political Arabic Articles Orientation Using Rough Set Theory with Sentiment Lexicon

Sentiment analysis is an emerging research field that can be integrated with other domains, including data mining, natural language processing and machine learning. In political articles, it is difficult to understand and summarise the state or overall views due to the diversity and size of social media information. A number of studies were conducted in the area of sentiment analysis, especially using English texts, while Arabic language received less attention in the literature. In this study, we propose a detection model for political orientation articles in the Arabic language. We introduce the key assumptions of the model, present and discuss the obtained results, and highlight the issues that still need to be explored to further our understanding of subjective sentences. The main purpose of applying this new approach based on Rough Set (RS) theory is to increase the accuracy of the models in recognizing the orientation of the articles. We present extensive simulation results, which demonstrate the superiority of the proposed model over other algorithms. It is shown that the performance of the proposed approach significantly improves by adding discriminating features. To summarize, the proposed approach demonstrates an accuracy of 85.483%, when evaluating the orientation of political Arabic datasets, compared to 72.58% and 64.516% for the Support Vector Machines and Naïve Bayes methods, respectively

Polycyclic Aromatic Hydrocarbons in Some Fishes from the Iraqi Marine Waters

This study represent the concentrations of 16 PAHs in 12 of commercial fish species (Euryglossa orientalis , Acanthopagrus araticus , Epinephelus coioides , Chirocentrus dorab , Scomberoidescommersonnianus , Scomberoides lysan , Otolithes ruber , Alepes diedaba , Tenualosa ilisha , Parastromateus niger , Pampus  argentetus , Ablennws hians ) . which were collected from the coastal area of the of Iraqi marine water during 2015. The analysis of Polycyclic Aromatic Hydrocarbons (PAHs) in fish muscles were determined using HPLC to identify the sources of PAHs, The total concentration of PAHs in fishes ranged between (0.432) ng/g dry weight in P. niger and (14.939) ng/g dry weight in  T. ilisha muscles . When we calculated the ratio of (Flouranthene to Pyrene)  and the ration of (Phenanthrene to Anthracene) and ratio of low molecular weight to high molecular weight of PAHs and the ration of Anthracene to (Anthracene + Phenanthrene ) and the ration of Benzo[a]anthracene to (Benzo[a]anthracene+ Chrysene), it is showed that the PAHs origin in fishes were Pyrogenic and Petrogenic . T. ilisha showns high ability to accumulate PAHs compounds  like Fluorene , Anthracene, Acenaphthene and Phenanthrene in muscles compared with other fishes ,  there was different ability of fish to accumulate  the PAHs from surrounded environments  . Keywords: PAHs compounds, HPLC, fishes, Iraqi marine water

Categorization of Arabic posts using Artificial Neural Network and hash features

Sentiment analysis is an important study topic with diverse application domains including social network monitoring and automatic analysis of the body of natural language communication. Existing research on sentiment analysis has already utilised substantial domain knowledge available online comprising users’ opinion in various areas such as business, education, and social media. There is however limited literature available on Arabic language sentiment analysis. Furthermore, datasets used in majority of these studies have poor classification. In the present study, we utilised a primary dataset comprising 2122 sentences and 15,331 words compiled from 206 publicly available online posts to perform sentiment classification by using advanced machine learning technique based on Artificial Neural Networks. Unlike lexicon-based techniques that suffer from low accuracy due to their computational nature and parameter configuration, Artificial Neural Networks were used to classify people opinion posts into three categories including conservative, reform and revolution, accompanied by multiple hasher vector size to benchmark the performance of the proposed model. Extensive simulation results indicated an accuracy of 93.33%, 100%, and 100% for the classification of conservation, reform, and revolutionary classes, respectively

3D human skin bioprinting: a view from the bio side

Based on the 3D printing technologies and the concepts developed in tissue engineering during the last decades, 3D bioprinting is emerging as the most innovative and promising technology for the generation of human tissues and organs. In the case of skin bioprinting, thanks to the research process carried out during the last years, interfollicular skin has been printed with a structural and functional quality that paves the way for clinical and industrial applications. This review analyzes the present achievements and the future improvements that this area must bring about if bioprinted skin is to become widely used. We have made an effort to integrate the technological and the biological/biomedical sides of the subject.We thank the Spanish Fundación Ramón Areces for its continuous support. This work was partially supported by grant DPI2014-61887-EXP from the Spanish Ministerio de Economía y Competitividad

Image dataset of healthy and infected fig leaves with Ficus leaf worm

This work presents an extensive dataset comprising images meticulously obtained from diverse geographic locations within Iraq, depicting both healthy and infected fig leaves affected by Ficus leafworm. This particular pest poses a significant threat to economic interests, as its infestations often lead to the defoliation of trees, resulting in reduced fruit production. The dataset comprises two distinct classes: infected and healthy, with the acquisition of images executed with precision during the fruiting season, employing state-of-the-art high-resolution equipment, as detailed in the specifications table. In total, the dataset encompasses a substantial 2,321 images, with 1,350 representing infected leaves and 971 depicting healthy ones. The images were acquired through a random sampling approach, ensuring a harmonious blend of balance and diversity across data emanating from distinct fig trees. The proposed dataset carries substantial potential for impact and utility, featuring essential attributes such as the binary classification of infected and healthy leaves. The presented dataset holds the potential to be a valuable resource for the pest control industry within the domains of agriculture and food production

Extremism Arabic Text Detection using Rough Set Theory: Designing a Novel Approach

The linguistics related research and particularly, sentiment analysis using data-driven approaches, has been growing in recent years. However, the large number of users and excessive amount of information available on social media, make it difficult to detect extremism text on these platforms. The literature revealed a plethora of research studies focusing the sentiment analysis primarily, for English texts, however, very limited studies are available concerning the Arabic language which is the 4th mostly spoken language in the world. We first time in this study, propose a text detection mechanism for extremism orientations distinction in Arabic language, to improve the comprehension of subjective phrases. The study introduces a novel method based on Rough Set theory to enhance the accuracy of selected models and recognize text orientation reliably. Experimental outcomes indicate that the proposed method outperforms existing algorithms by contributing towards feature discriminations. Our method achieved 90.853%, 81.707% and 71.951% accuracies for unigram, bigram, and trigram representations, respectively. This study significantly contributes to the limited research in the field of machine learning and linguistics in Arabic language

Molecular evidence of Rickettsia felis infection in dogs from northern territory, Australia

The prevalence of spotted fever group rickettsial infection in dogs from a remote indigenous community in the Northern Territory (NT) was determined using molecular tools. Blood samples collected from 130 dogs in the community of Maningrida were subjected to a spotted fever group (SFG)-specific PCR targeting the ompB gene followed by a Rickettsia felis-specific PCR targeting the gltA gene of R. felis. Rickettsia felis ompB and gltA genes were amplified from the blood of 3 dogs. This study is the first report of R. felis infection in indigenous community dogs in NT

A System Dynamics Approach for Hospital Waste Management in a City in a Developing Country: The Case of Nablus, Palestine

Hospitals and health centers provide a variety of healthcare services and normally generate hazardous waste as well as general waste. General waste has a similar nature to that of municipal solid waste and therefore could be disposed of in municipal landfills. However, hazardous waste poses risks to public health, unless it is properly managed. The hospital waste management system encompasses many factors, i.e., number of beds, number of employees, level of service, population, birth rate, fertility rate, and not in my back yard (NIMBY) syndrome. Therefore, this management system requires a comprehensive analysis to determine the role of each factor and its influence on the whole system. In this research, a hospital waste management simulation model is presented based on the system dynamics technique to determine the interaction among these factors in the system using a software package, ithink. This model is used to estimate waste segregation as this is important in the hospital waste management system to minimize risk to public health. Real data has been obtained from a case study of the city of Nablus, Palestine to validate the model. The model exhibits wastes generated from three types of hospitals (private, charitable, and government) by considering the number of both inpatients and outpatients depending on the population of the city under study. The model also offers the facility to compare the total waste generated among these different types of hospitals and anticipate and predict the future generated waste both infectious and non-infectious and the treatment cost incurred

Pleuro-pulmonary tumours detected by clinical and chest X-ray analyses in rats transplanted with mesothelioma cells

New strategies for cancer therapy must be developed, especially in severe neoplasms such as malignant pleural mesothelioma. Animal models of cancer, as close as possible to the human situation, are needed to investigate novel therapeutical approaches. Orthotopic transplantation of cancer cells is then relevant and efforts should be made to follow up tumour evolution in animals. In the present study, we developed a method for the orthotopic growth of mesothelioma cells in the pleural cavity of Fischer 344 and nude rats, along with a procedure for clinical survey. Two mesothelioma cell lines, of rat and human origin, were inoculated by transthoracic puncture. Body weight determination and chest X-ray analyses permitted the follow-up of tumour evolution by identifying different stages. Autopsies showed that tumours localized on the whole pleural cavity (diaphragm, parietal pleura), mediastinum and pericardium. Tumour morphology and antigenic characteristics were consistent with those of the inoculated cells and were similar in both types of rats inoculated with the same cell type. These results demonstrate that mesothelioma formation in rats can be followed up by clinical and radiographic survey after gentle intrathoracic inoculation of mesothelioma cells, thus allowing the definition of stages of interest for further experimental trials. © 1999 Cancer Research Campaig