bluuebunny/crossref_metadata_2025_split huggingface dataset:
Artificial or intelligent? Machine learning and medical selection: possibilities and risks
Authors: Tiffin Paul , Paton Lewis 
Published: November 2018

This article was migrated. The article was marked as recommended. Machine learning approaches form the basis of “artificial intelligence” and have been increasingly applied in health services settings. It has been shown that such approaches may produce more accurate predictions in some contexts, compared to conventional statistical approaches, and may also reduce the costs of decision-making through automation. Nevertheless, there are both general limitations to developing and implementing machine learning approaches that must be borne in mind. To date, relatively little research has been published on the potential for machine learning to support personnel selection. Moreover, there are particular challenges and issues that need to be considered if such methods are to be used to support decision-making in medical selection scenarios. This article describes some of these potential advantages and challenges and presents an illustrative example, based on real-world data, related to the selection of medical undergraduates.
How Does a Supervised Exercise Program Improve Quality of Life in Patients with Cancer? A Concept Mapping Study Examining Patients' Perspectives
Authors: Sweegers Maike G. , Buffart Laurien M. , van Veldhuizen Wouke M. , Geleijn Edwin , Verheul Henk M.W. , Brug Johannes , Chinapaw Mai J.M. , Altenburg Teatske M. 
Published: November 2018

Abstract

Background
Previous systematic reviews and meta-analyses demonstrated beneficial effects of exercise during or following cancer treatment on quality of life (QoL). Aiming to understand how exercise contributes to a patient's QoL, we examined patients' perspectives via a process called concept mapping. This unique method provides structure and objectivity to rich qualitative data.

Methods
Patients with cancer who were participating in an exercise program were invited to enroll. Eleven meetings with 3–10 patients were organized in which patients generated ideas in response to the question “How has participating in a supervised exercise program contributed positively to your QoL?” Next, patients individually clustered (based on similarity) and rated (based on importance) the ideas online. The online assessments were combined, and one concept map was created, visualizing clusters of ideas of how patients perceive that participating in a supervised exercise program improved their QoL. The research team labelled the clusters of ideas, and physiotherapists reflected on the clusters during semistructured interviews.

Results
Sixty patients attended the meetings; of these, one patient was not able to generate an idea in response to the statement. Forty-four patients completed the online clustering and rating of ideas. The resulting concept map yielded six clusters: personalized care, coaching by a physiotherapist, social environment, self-concept, coping, and physical fitness and health. Personalized care was rated as most important. Overall, physiotherapists recognized these clusters in practice.

Conclusion
Patients with cancer reported that participating in a supervised exercise program improved their physical fitness and influenced social, mental, and cognitive factors, resulting in improvements in QoL. These results can be used to increase the awareness of the importance of supervised exercise programs for the QoL of patients with cancer.
aCGH Analysis of Predictive Biomarkers for Response to Bevacizumab plus Oxaliplatin- or Irinotecan-Based Chemotherapy in Patients with Metastatic Colorectal Cancer
Authors: Fujita Yoshihiko , Taguri Masataka , Yamazaki Kentaro , Tsurutani Junji , Sakai Kazuko , Tsushima Takahiro , Nagase Michitaka , Tamagawa Hiroshi , Ueda Shinya , Tamura Takao , Tsuji Yasushi , Murata Kohei , Taira Koichi , Denda Tadamichi , Moriwaki Toshikazu , Funai Sadao , Nakajima Takako Eguchi , Muro Kei , Tsuji Akihito , Yoshida Motoki , Suyama Koichi , Kurimoto Takuya , Sugimoto Naotoshi , Baba Eishi , Seki Nobuhiko , Sato Mikio , Shimura Takaya , Boku Narikazu , Hyodo Ichinosuke , Yamanaka Takeharu , Nishio Kazuto 
Published: November 2018

AbstractBackgroundThe randomized phase III study (WJOG4407G) showed equivalent efficacy between FOLFOX and FOLFIRI in combination with bevacizumab as the first-line treatment for metastatic colorectal cancer (mCRC). We studied whole genome copy number profiles using array-based comparative genomic hybridization (aCGH) analysis of tumor tissue samples obtained in this study. The aim of this study was to identify gene copy number alterations that could aid in selecting either FOLFOX or FOLFIRI in combination with bevacizumab for patients with mCRC.Materials and MethodsDNA was purified from 154 pretreatment formalin-fixed paraffin-embedded tissue samples (75 from the FOLFOX arm and 79 from the FOLFIRI arm) of 395 patients enrolled in the WJOG4407G trial and analyzed by aCGH. Genomic regions greater than 1.2-fold were regarded as copy number gain (CNG).ResultsPatient characteristics between the treatment arms were well balanced except for tumor laterality (left side; 64% in FOLFOX arm and 80% in FOLFIRI arm, p = .07). FOLFIRI showed a trend toward better response rate (RR), progression-free survival (PFS) and overall survival (OS) than FOLFOX in the patients with CNG of chromosome 8q24.1 (Fisher's exact test, p = .134 for RR; interaction test, p = .102 for PFS and p = .003 for OS) and 8q24.2 (Fisher's exact test, p = .179 for RR; interaction test, p = .144 for PFS and p = .002 for OS).ConclusionChromosome 8q24.1–q24.2 may contain genes that could potentially serve as predictive markers for selecting either FOLFOX or FOLFIRI in combination with bevacizumab for treatment of patients with mCRC.Implications for PracticeBevacizumab has been used as a standard first-line treatment for patients with metastatic colorectal cancer (mCRC) in combination with either oxaliplatin-based or irinotecan-based chemotherapy. Until now, there has been no predictive marker to choose between the two combination chemotherapies. This array-based comparative genomic hybridization analysis revealed that the difference in therapeutic effect between the two combination chemotherapies is prominent in patients with mCRC with gene copy number gain in chromosome 8p24.1–p24.2. Such patients showed more favorable response and survival when treated with irinotecan-based combination chemotherapy. Overlapping genes commonly found in this region may be predictive biomarkers of the efficacy of the combination chemotherapy with bevacizumab.
Los costes sociales del proyecto de la presa El Zapotillo: el caso de Temacapulín
Authors: Lezama Escalante Cecilia 
Published: November 2018

En este artículo se abordan los impactos sociales ocasionados por la construcción de una presa que permitirá el trasvase de agua de una cuenca a otra para el suministro urbano de agua a dos ciudades en crecimiento: Guadalajara y León. El trabajo realizado en campo hace énfasis en los costes sociales asociados a la construcción de la presa de El Zapotillo, cuyo embalse amenaza con inundar tres comunidades rurales en los Altos de Jalisco. El propósito es dar testimonio de los costos sociales que conlleva la construcción de grandes obras de infraestructura hidráulica para una población que es forzada a desalojar su territorio y con ello, sus medios de sustento y su patrimonio. Los costos sociales trascienden la pérdida del patrimonio material de las personas afectadas; puesto que también implica la pérdida irreversible del patrimonio cultural tangible e intangible que los pobladores han forjado a lo largo de siglos de historia. Aquí se presenta una descripción etnográfica como un aporte antropológico para entender las verdaderas pérdidas que dan origen al movimiento de resistencia de los pobladores de Temacapulín.
Ant Colony Optimization Based Subset Feature Selection in Speech Processing: Constructing Graphs with Degree Sequences
Authors: Rajoo R. Rajesvary , Abdul Salam Rosalina 
Published: November 2018

Feature selection or the process of selecting the most discriminating feature subset is an essential practice in speech processing that significantly affects the performance of classification. However, the volume of features that presents in speech processing makes the feature selection perplexing. Moreover, finding the optimal feature subset is a NP-hard problem (2n). Thus, a good searching strategy is required to avoid evaluating large number of combinations in the whole feature subsets. As a result, in recent years, many heuristic based search algorithms are developed to address this NP-hard problem. One of the several meta heuristic algorithms that is applied in many application domains to solve feature selection problem is Ant Colony Optimization (ACO) based algorithms. ACO based algorithms are nature-inspired from the foraging behavior of actual ants. The success of an ACO based feature selection algorithm depends on the choice of the construction graph with respect to runtime behavior. While most ACO based feature selection algorithms use fully connected graphs, this paper proposes ACO based algorithm that uses graphs with prescribed degree sequences. In this method, the degree of the graph representing the search space will be predicted and the construction graph that satisfies the predicted degree will be generated. This research direction on graph representation for ACO algorithms may offer possibilities to reduce computation complexity from O(n2) to O(nm) in which m is the number of edges. This paper outlines some popular optimization based feature selection algorithms in the field of speech processing applications and overviewed ACO algorithm and its main variants. In addition to that, ACO based feature selection is explained and its application in various speech processing tasks is reviewed. Finally, a degree based graph construction for ACO algorithms is proposed.
Automatic Detection of Shadda in Modern Standard Arabic Continuous Speech
Authors: Al-Sabri Ammar , Adam Afzan , Rosdi Fadhilah 
Published: November 2018

The presence of diacritics Shadda in Arabic continuous speech may lead to the reduction of the accuracy of automatic Word Boundary Detection (WBD), which caused one word will be wrongly detected as two words. Therefore, this will affect the accuracy of Automatic Speech Recognition (ASR), if it is based on WBD. Shadda is one of the essential characteristics of the Arabic language which represents a consonant doubling. In this paper, a proposed method of automatic detection of Shadda in Modern Standard Arabic (MSA) continuous speech was introduced to improve the accuracy of WBD in MSA continuous speech. The prosodic features namely Short Time Energy (STE), Fundamental Frequency and Intensity were investigated for its ability as Shadda pattern detection in continuous MSA speech. We have analyzed the proposed features by implementing a separated algorithm for each feature to detect Shadda pattern automatically. In addition, a new proposed method which is a combination of STE and Intensity were introduced. The dataset in this work is a collection of 1-hour TV broadcast news from Aljazeera Arabic TV channel for 2018 - broadcasters. We found that the Shadda pattern is very similar to unvoiced regions of speech, and this represents a big challenge for the improvement of WDB using Shadda. Results showed that the detection of Shadda using Short Time Energy and Intensity outperforms the Fundamental frequency with 55% of accuracy. Intensity achieved 71.5% in accuracy. In addition, a combination between Intensity & STE features was performed and achieved good results with 67.15% in accuracy. The number of false positive too has been reduced compared to Intensity alone.
Usability of ReSt Module Using Four-Step Approach Based on Case Study Example and Infographic for SPSS Novice Users
Authors: Ishak Azura , Din Rosseni , Mohamed Hazura 
Published: November 2018

The application of analysis data software packages, such as SPSS, appears challenging for those who lack experience in quantitative researches particularly amongst novice users. Prior studies have proven that SPSS novice users face some difficulties in analyzing data correctly for their research purposes. The existing modules that serve as references are insufficiently interesting to promote SPSS learning and does not support on students’ cognitive ability. Hence, a module using four-step approach based on learning via case study example and infographic called ‘ReSt’ module was developed as an effort to assist novice users in learning quantitative data analysis methods using the SPSS. With that, the research design employed in this study was the survey method in order to determine the ReSt module usability level perception. A total of 78 novice users who comprised of undergraduate and postgraduate students participated in this research throughout a two-day SPSS basic course in order to evaluate their perception regarding the usability level of the module. A usability questionnaire categorized four primary domains, which are usefulness, ease of use, ease of learning, and satisfaction was applied to evaluate the ReSt module usability level perception. The outcomes revealed that the usability level of the proposed module had been high among the novice users, for the contexts of usefulness, ease of use, ease of learning, and satisfaction. Therefore, the use of the ReSt module for SPSS novice users is indeed relevant and appropriate, thus fulfill the usability amongst novice users to function as a reference in data analysis learning using the SPSS, especially amongst core quantitative researchers.
Effectiveness of Bamboo Biochar Combined with Compost and NPK Fertilizer to Improved Soil Quality and Corn Yield
Authors: Situmeang Yohanes Parlindungan , Adnyana I Made , Netera Subadiyasa I Nengah , Merit I Nyoman 
Published: November 2018

Biochar is a carbon-rich material produced from incomplete combustion of agricultural biomass through pyrolysis process. Bamboo biochar can increase soil carbon content, improve soil fertility and restore the degraded soil. Previously we found that bamboo-biochar was effective to improve maize yield with an optimum dosage 10.52 t ha-1 biochar. Here, we examined the effectiveness of bamboo-biochar combined with compost and NPK fertilizer to improved soil quality and crop yield. In this experiment, we used a randomized block design (RBD) with two factors, three replications. The first factor was biochar dosage (four levels), namely without biochar, biochar dosage 5.26 t ha-1, biochar dosage 10.52 t ha-1, biochar dosage 15.78 t ha-1. The second factor is the type of fertilizer with four types, namely: without fertilizer, compost, NPK, and compost+NPK. The results showed that biochar dosage 10.52 t ha-1 combined with compost+NPK could increase P and K availability, increase total soil microbes, and improved soil quality to be very good with soil quality rating value 18. The biochar dosage 10.52 t ha-1 combined with compost+NPK gave the dry weight seed-corn highest of 12.84 tons per hectare that increased 38.61% when compared with without biochar and with compost+NPK. The highest yield 12.84 tons of the dry weight of seed-corn per hectare provides the highest effectiveness-agronomic value 119.69% and feasibility of corn crop farming in drylands value 1.27.
Comparison of Repair Costs for Small and Mid-Sizes Farm Machinery in Malaysian Oil Palm Plantation
Authors: Samsudin Siti Nabilah , El Pebrian Darius , Wan Ajeng Jok 
Published: November 2018

Farm machinery has been tremendously used to perform laborious tasks and speed-up the in-field operations in Malaysian oil palm plantation. In line with significant increase in farm machinery usage in Malaysian oil palm plantation, hence, repair costs of farm machinery should be well-managed. Failure to do so may result the plantations profits will be affected. This study aims to analyze and compare the current data of repair costs for small and mid-sizes farm machinery that are commonly used in Malaysian oil palm plantation. Besides, this study also aims to update and adapt the values of repair factors for cumulative repair and maintenance (Crm) costs model of farm machinery in Malaysian oil palm plantation. The relevant data were collected through a survey that was carried out at several oil palm plantations in Melaka and Negeri Sembilan states of Malaysia. The findings indicated the common sizes of farm machinery used Malaysian oil palm plantation were in range of small-size (28HP) to mid-size (75HP). It was found that annual average repair costs of mid-size farm machinery was 60.08% higher than the small-size one. Meanwhile, mean ages of mid-size farm machinery was also 80.7 % longer than the small-size one. The values of repairs factors 1 (RF1) and repairs factor 2 (RF2) for cumulative repair and maintenance costs model (Crm) of farm machinery in Malaysian oil palm plantation were 1.4061 and 1.6588, respectively. Conclusively, the findings of study can give a valuable contribution to the oil palm plantations management in developing their strategic planning concerning to the allocation of overall costs of farm machinery.
Effect of Edible Coating on Quality of Chips from Potato Variety Granola
Authors: Wibowo Condro , Wicaksono Rumpoko , Erminawati Erminawati 
Published: November 2018

In recent years, Indonesia requires a large quantity of potatoes to meet demands. The required tuber is processing potato for producing French fries and potato chips. In order to provide sufficient supply throughout the year, import is conducted. It occurs due to the widely variety cultivated in Indonesia is Granola that reach about 90% of total area. Due to its inherent characteristic, the tuber is appropriate for table potato and not for processing one. Therefore, an alternative treatment is required for using variety Granola for processing purpose. An alternative is processed Granola tuber into flour and used it as raw material for processed food. This research aims to evaluate the properties' of potato chips that resulted from various combinations of other flours and application of edible coating. Tuber variety Granola was obtained from the potato farmers in Dieng, one of a central potato producer in Indonesia. Tuber was powdered and used as raw material for chips combined with other flours include: wheat, rice and maize flour. In addition, edible coating was introduced before frying of potato slices. Starch based edible coating was applied in this research. Quality of potato chips observed were: content of moisture, ash and fat, and sensory properties including colour, crispiness, flavor and overall acceptance. The result shows that through mixing with other flour, potato flour from variety Granola can be utilized as raw material for potato chips. Application of edible coating significantly improves the quality of chips by minimizing oil absorption during frying. Chips produced in the present research are accepted by the panellist; nonetheless, any effort is still required in order chips' quality meets the criteria of Indonesian National Standard (SNI).
The Utilization of Ceramic Membrane for Treating of Water from Sekanak River Palembang to Produce Clean Water
Authors: Sisnayati - , Said Muhammad , Nasir Subriyer , Priadi Dwi Putro 
Published: November 2018

The aims of this research is to produce clean water from Sekanak River by using the ceramic membrane. Also, this study is to analyze the performance of ceramic membranes in terms of its ability to reduce the pollutants contained in water from Sekanak River. The ceramic membrane was tube-shaped, made from clay (87.5 %w), iron powder (2.5 %w) and activated carbon of oil palm empty bunch (10 %w). The operation condition of membrane separation was of 15 minutes, 30 minutes, 45 minutes, 60 minutes, 75 minutes, 90 minutes and the applied pressure was of 1.0 bar, 1.5 bar and 2.0 bar. The reduction pollutants (Fe, Mn, Zn, NH3-N, NO2-, PO4-3,H2S, BOD5, and TSS) concentration increased with increasing the pressure and the operating time of membrane separation. After treating by the ceramic membrane, the average rejection of Fe, Mn, Zn, NH3-N, NO2-, PO4-3, H2S, BOD5, and TSS are 81.22%, 95.00%, 99.00%, 85.19%, 78.85%, 73.95%, 97.78%, 87.55%, and 75.46% respectively. The pollutant concentrations in the effluent were met the Environmental Quality Standards (BML).
Microstructure Analysis of Hydroxyapatite Coating on Stainless Steel 316L Using Investment Casting Technique for Implant Application
Authors: Nuswantoro Nuzul Ficky , Gunawarman Gunawarman , Saputra Masagus Rifqie , Nanda Is Prima , Idris Mohammad Hasbullah , Arafat Andril 
Published: November 2018

Osteoporosis and traffic accident are major factor that causes bone fracture in Indonesia. One of solution for the bones fracture treatment is by using fixation implant that has similar characteristics with the human bones. Stainless Steel (SS) 316L is one of biomaterial that has been used as an implant material due to its corrosion resistance, good biocompatibility, and excellent mechanical properties. However, the bioactivity properties of the material is needed to improve by coating it with hydroxyapatite (HA). In this research, HA was coated to the surface of 316L SS by using investment casting technique. A slurry of HA was poured into casting cavity surface prior to metal casting process, and then followed by sintering at temperatures of 850oC, 900oC, and 950oC. Characterization of HA coating layer on specimen surface was conducted by Optical Microscope, Scanning Electron Microscope (SEM), and Energy Dispersive X-Ray (EDX). Hardness of the samples was measured by Vickers Hardness Tester. Result of the experiment shows that the invvestment casting is successfully to coat the HA on the SS 316L surface. Pouring method produces HA layer with thickness (spongy and porous surface) in the range of 60 µm - 110 µm. The increasing of sintering temperature increases the hardness number of the surfaces, and affect the purity of HA, but it is not related to coating thickness. Optimum sintering temperature is obtained at 900oC which produces the best calcium and phosphate ratio. The investment casting method is found as a simple and non-expensive technique that can be used to coat HA powder to SS 316L that produces good properties and optimum crystallinity of HA that suitable for orthopedic implant application.
Random Forest Weighting based Feature Selection for C4.5 Algorithm on Wart Treatment Selection Method
Authors: Nugroho Handoyo Widi , Adji Teguh Bharata , Setiawan Noor Akhmad 
Published: November 2018

Research in the field of health, especially treatment of wart disease has been widely practiced. One of the research topics related to the treatment of wart disease is in order to provide the most appropriate treatment method recommendations. Treatment methods are widely used by doctors for treatment of patients with wart disease that is the method of cryotherapy and immunotherapy. Previous research has been done on cryotherapy and immunotherapy datasets which resulted in two different prediction methods, but the accuracy level has not been satisfactory. In this study, two datasets are combined to produce a single prediction method. The method uses C4.5 algorithm combined with Random Forest Feature Weighting (C4.5+RFFW) used to select the relevant features to improve accuracy. Experimental results show that the proposed method can improve performance with accuracy and informedness are 87.22% and 71.24%, respectively. These results further facilitate physicians in determining treatment methods for patients with a single predictive method and better-predicted performance.