Displaying publications 21 - 40 of 754 in total

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  1. Almogahed A, Mahdin H, Omar M, Zakaria NH, Gu YH, Al-Masni MA, et al.
    PLoS One, 2023;18(11):e0293742.
    PMID: 37917752 DOI: 10.1371/journal.pone.0293742
    Refactoring, a widely adopted technique, has proven effective in facilitating and reducing maintenance activities and costs. Nonetheless, the effects of applying refactoring techniques on software quality exhibit inconsistencies and contradictions, leading to conflicting evidence on their overall benefit. Consequently, software developers face challenges in leveraging these techniques to improve software quality. Moreover, the absence of a categorization model hampers developers' ability to decide the most suitable refactoring techniques for improving software quality, considering specific design goals. Thus, this study aims to propose a novel refactoring categorization model that categorizes techniques based on their measurable impacts on internal quality attributes. Initially, the most common refactoring techniques used by software practitioners were identified. Subsequently, an experimental study was conducted using five case studies to measure the impacts of refactoring techniques on internal quality attributes. A subsequent multi-case analysis was conducted to analyze these effects across the case studies. The proposed model was developed based on the experimental study results and the subsequent multi-case analysis. The model categorizes refactoring techniques into green, yellow, and red categories. The proposed model, by acting as a guideline, assists developers in understanding the effects of each refactoring technique on quality attributes, allowing them to select appropriate techniques to improve specific quality attributes. Compared to existing studies, the proposed model emerges superior by offering a more granular categorization (green, yellow, and red categories), and its range is wide (including ten refactoring techniques and eleven internal quality attributes). Such granularity not only equips developers with an in-depth understanding of each technique's impact but also fosters informed decision-making. In addition, the proposed model outperforms current studies and offers a more nuanced understanding, explicitly highlighting areas of strength and concern for each refactoring technique. This enhancement aids developers in better grasping the implications of each refactoring technique on quality attributes. As a result, the model simplifies the decision-making process for developers, saving time and effort that would otherwise be spent weighing the benefits and drawbacks of various refactoring techniques. Furthermore, it has the potential to help reduce maintenance activities and associated costs.
    Matched MeSH terms: Software*
  2. Ghani NSA, Emrizal R, Moffit SM, Hamdani HY, Ramlan EI, Firdaus-Raih M
    Nucleic Acids Res, 2022 Jul 05;50(W1):W375-W383.
    PMID: 35639505 DOI: 10.1093/nar/gkac402
    The GrAfSS (Graph theoretical Applications for Substructure Searching) webserver is a platform to search for three-dimensional substructures of: (i) amino acid side chains in protein structures; and (ii) base arrangements in RNA structures. The webserver interfaces the functions of five different graph theoretical algorithms - ASSAM, SPRITE, IMAAAGINE, NASSAM and COGNAC - into a single substructure searching suite. Users will be able to identify whether a three-dimensional (3D) arrangement of interest, such as a ligand binding site or 3D motif, observed in a protein or RNA structure can be found in other structures available in the Protein Data Bank (PDB). The webserver also allows users to determine whether a protein or RNA structure of interest contains substructural arrangements that are similar to known motifs or 3D arrangements. These capabilities allow for the functional annotation of new structures that were either experimentally determined or computationally generated (such as the coordinates generated by AlphaFold2) and can provide further insights into the diversity or conservation of functional mechanisms of structures in the PDB. The computed substructural superpositions are visualized using integrated NGL viewers. The GrAfSS server is available at http://mfrlab.org/grafss/.
    Matched MeSH terms: Software*
  3. Alu'datt MH, Khamayseh Y, Alhamad MN, Tranchant CC, Gammoh S, Rababah T, et al.
    Food Chem, 2022 Mar 30;373(Pt B):131531.
    PMID: 34823940 DOI: 10.1016/j.foodchem.2021.131531
    The nutrient composition of 50 commonly consumed Jordanian food dishes was determined to support the development of a novel nutrition management system designed to assist with dietary intake assessment and diet management. Composite dishes were selected by interviewing households located in the northern region of Jordan. For each dish, five different recipes were collected from experienced chefs and the typical recipe was formulated based on the average weights of ingredients and net weight of the dish. Proximate composition as well as vitamin and mineral contents were determined and related to ingredient composition and cooking conditions. The newly created food composition database was used to develop a user-centric nutrition management software tailored to reflect the characteristics of the Jordanian diet with representative items from this diet. This novel nutrition management system is customizable, enabling users to build daily meal plans in accordance with personalized dietary needs and goals.
    Matched MeSH terms: Software
  4. Al Shinwan M, Abualigah L, Huy TD, Younes Shdefat A, Altalhi M, Kim C, et al.
    Sensors (Basel), 2022 Jan 04;22(1).
    PMID: 35009891 DOI: 10.3390/s22010349
    Reaching a flat network is the main target of future evolved packet core for the 5G mobile networks. The current 4th generation core network is centralized architecture, including Serving Gateway and Packet-data-network Gateway; both act as mobility and IP anchors. However, this architecture suffers from non-optimal routing and intolerable latency due to many control messages. To overcome these challenges, we propose a partially distributed architecture for 5th generation networks, such that the control plane and data plane are fully decoupled. The proposed architecture is based on including a node Multi-session Gateway to merge the mobility and IP anchor gateway functionality. This work presented a control entity with the full implementation of the control plane to achieve an optimal flat network architecture. The impact of the proposed evolved packet Core structure in attachment, data delivery, and mobility procedures is validated through simulation. Several experiments were carried out by using NS-3 simulation to validate the results of the proposed architecture. The Numerical analysis is evaluated in terms of total transmission delay, inter and intra handover delay, queuing delay, and total attachment time. Simulation results show that the proposed architecture performance-enhanced end-to-end latency over the legacy architecture.
    Matched MeSH terms: Software
  5. Ishaq M, Khan A, Su'ud MM, Alam MM, Bangash JI, Khan A
    Comput Math Methods Med, 2022;2022:8691646.
    PMID: 35126641 DOI: 10.1155/2022/8691646
    Task scheduling in parallel multiple sequence alignment (MSA) through improved dynamic programming optimization speeds up alignment processing. The increased importance of multiple matching sequences also needs the utilization of parallel processor systems. This dynamic algorithm proposes improved task scheduling in case of parallel MSA. Specifically, the alignment of several tertiary structured proteins is computationally complex than simple word-based MSA. Parallel task processing is computationally more efficient for protein-structured based superposition. The basic condition for the application of dynamic programming is also fulfilled, because the task scheduling problem has multiple possible solutions or options. Search space reduction for speedy processing of this algorithm is carried out through greedy strategy. Performance in terms of better results is ensured through computationally expensive recursive and iterative greedy approaches. Any optimal scheduling schemes show better performance in heterogeneous resources using CPU or GPU.
    Matched MeSH terms: Software
  6. Sayeed S, Ahmad AF, Peng TC
    F1000Res, 2022;11:17.
    PMID: 38269303 DOI: 10.12688/f1000research.73613.1
    The Internet of Things (IoT) is leading the physical and digital world of technology to converge. Real-time and massive scale connections produce a large amount of versatile data, where Big Data comes into the picture. Big Data refers to large, diverse sets of information with dimensions that go beyond the capabilities of widely used database management systems, or standard data processing software tools to manage within a given limit. Almost every big dataset is dirty and may contain missing data, mistyping, inaccuracies, and many more issues that impact Big Data analytics performances. One of the biggest challenges in Big Data analytics is to discover and repair dirty data; failure to do this can lead to inaccurate analytics results and unpredictable conclusions. We experimented with different missing value imputation techniques and compared machine learning (ML) model performances with different imputation methods. We propose a hybrid model for missing value imputation combining ML and sample-based statistical techniques. Furthermore, we continued with the best missing value inputted dataset, chosen based on ML model performance for feature engineering and hyperparameter tuning. We used k-means clustering and principal component analysis. Accuracy, the evaluated outcome, improved dramatically and proved that the XGBoost model gives very high accuracy at around 0.125 root mean squared logarithmic error (RMSLE). To overcome overfitting, we used K-fold cross-validation.
    Matched MeSH terms: Software
  7. Kirubakaran R, Stocker SL, Carlos L, Day RO, Carland JE
    Ther Drug Monit, 2021 Dec 01;43(6):736-746.
    PMID: 34126624 DOI: 10.1097/FTD.0000000000000909
    BACKGROUND: Therapeutic drug monitoring is recommended to guide tacrolimus dosing because of its narrow therapeutic window and considerable pharmacokinetic variability. This study assessed tacrolimus dosing and monitoring practices in heart transplant recipients and evaluated the predictive performance of a Bayesian forecasting software using a renal transplant-derived tacrolimus model to predict tacrolimus concentrations.

    METHODS: A retrospective audit of heart transplant recipients (n = 87) treated with tacrolimus was performed. Relevant data were collected from the time of transplant to discharge. The concordance of tacrolimus dosing and monitoring according to hospital guidelines was assessed. The observed and software-predicted tacrolimus concentrations (n = 931) were compared for the first 3 weeks of oral immediate-release tacrolimus (Prograf) therapy, and the predictive performance (bias and imprecision) of the software was evaluated.

    RESULTS: The majority (96%) of initial oral tacrolimus doses were guideline concordant. Most initial intravenous doses (93%) were lower than the guideline recommendations. Overall, 36% of initial tacrolimus doses were administered to transplant recipients with an estimated glomerular filtration rate of <60 mL/min/1.73 m despite recommendations to delay the commencement of therapy. Of the tacrolimus concentrations collected during oral therapy (n = 1498), 25% were trough concentrations obtained at steady-state. The software displayed acceptable predictions of tacrolimus concentration from day 12 (bias: -6%; 95%confidence interval, -11.8 to 2.5; imprecision: 16%; 95% confidence interval, 8.7-24.3) of therapy.

    CONCLUSIONS: Tacrolimus dosing and monitoring were discordant with the guidelines. The Bayesian forecasting software was suitable for guiding tacrolimus dosing after 11 days of therapy in heart transplant recipients. Understanding the factors contributing to the variability in tacrolimus pharmacokinetics immediately after transplant may help improve software predictions.

    Matched MeSH terms: Software
  8. Mohidem NA, Osman M, Muharam FM, Mohd Elias S, Shaharudin R, Hashim Z
    Geospat Health, 2021 Oct 19;16(2).
    PMID: 34672178 DOI: 10.4081/gh.2021.980
    In the last few decades, public health surveillance has increasingly applied statistical methods to analyze the spatial disease distributions. Nevertheless, contact tracing and follow up control measures for tuberculosis (TB) patients remain challenging because public health officers often lack the programming skills needed to utilize the software appropriately. This study aimed to develop a more user-friendly application by applying the CodeIgniter framework for server development, ArcGIS JavaScript for data display and a web application based on JavaScript and Hypertext Preprocessor to build the server's interface, while a webGIS technology was used for mapping. The performance of this approach was tested based on 3325 TB cases and their sociodemographic data, such as age, gender, race, nationality, country of origin, educational level, employment status, health care worker status, income status, residency status, and smoking status between 1st January 2013 and 31st December 2017 in Gombak, Selangor, Malaysia. These data were collected from the Gombak District Health Office and Rawang Health Clinic. Latitude and longitude of the location for each case was geocoded by uploading spatial data using Google Earth and the main output was an interactive map displaying location of each case. Filters are available for the selection of the various sociodemographic factors of interest. The application developed should assist public health experts to utilize spatial data for the surveillance purposes comprehensively as well as for the drafting of regulations aimed at to reducing mortality and morbidity and thus minimizing the public health impact of the disease.
    Matched MeSH terms: Software
  9. Gharaei N, Ismail W, Grosan C, Hendradi R
    Artif Intell Med, 2021 10;120:102151.
    PMID: 34629147 DOI: 10.1016/j.artmed.2021.102151
    Tele-rehabilitation is an alternative to the conventional rehabilitation service that helps patients in remote areas to access a service that is practical in terms of logistics and cost, in a controlled environment. It includes the usage of mobile phones or other wireless devices that are applied to rehabilitation exercises. Such applications or software include exercises in the form of virtual games, treatment monitoring based on the rehabilitation progress and data analysis. However, nowadays, physiotherapists use a default profiling setting for patients carrying out rehabilitation, due to lack of information. Medical Interactive Rehabilitation Assistant (MIRA) is a computer-based (virtual reality) rehabilitation platform. The profile setting includes: a level of difficulty, percentage of tolerance and maximum range. To the best of our knowledge, there is a lack of optimization in the parameter values setting of MIRA exergames that could enhance patients' performance. Generally, non-optimal profile setting leads to reduced effectiveness. Therefore, this study aims to develop a method that optimizes the profile setting of each patient according to the estimated (desired) optimal results. The proposed method is developed using unsupervised and supervised machine learning techniques. We use Self-Organizing Map (SOM) to cluster patient records into several distinct clusters. K-fold cross validation is applied to construct the prediction models. Classification And Regression Tree (CART) is utilized to predict the patient's optimal input setting for playing the MIRA games. The combination of these techniques seems to improve the efficiency of the standard (default) way in predicting the optimal settings for exergames. To evaluate the proposed method, we conduct an experiment with data collected from a rehabilitation center. We use three metrics to quantify the quality of the results: R-squared (R2), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The results of experimental analysis demonstrate that the proposed method is effective in predicting the adequate parameter setting in MIRA platform. The method has potential to be implemented as an intelligent system for MIRA prediction in healthcare. Moreover, the method could be extended to similar platforms for which data is available to train our method on.
    Matched MeSH terms: Software
  10. Nasution A, Yusuf A, Lean Keng S, Rasudin NS, P Iskandar YH, Ab Hadi IS
    Asian Pac J Cancer Prev, 2021 Oct 01;22(10):3151-3163.
    PMID: 34710991 DOI: 10.31557/APJCP.2021.22.10.3151
    BACKGROUND: Mobile health technologies are widely being used for delivering health behaviour interventions. However, there is insufficient evidence that they are integrating theory and only a few researchers utilized a qualitative approach in their study.

    OBJECTIVES: This paper aims to identify requirements in developing a breast examination awareness mobile app based on the component of the Health Belief Model (HBM) for integration in health promotion strategy.

    METHODS: A qualitative approach using semi-structured in-depth interview was utilized in this study. A purposive sampling method was conducted among public women attending hospital services, software and content experts in a tertiary teaching hospital in the East coast of Peninsular Malaysia. These interviews were recorded, transcribed and organized using NVIVO 11. The main themes were identified through thematic analysis of the interview transcripts.  Results: A total of 37 participants recruited in this study. The themes that emerged from the analysis are vulnerability, forecasting, reactive, influence, outcome and obstacles. The sub-themes findings supported the HBM's component in terms of the requirement for are an infographic risk factor, video (symptoms, self-examination), info (metastasis, survival, screening, triple assessment, treatment, myth and facts, benefit of early treatment, support groups), features (screening reminder, sharing button, prompt) and mobile app's design.

    CONCLUSION: The research findings could provide a guide for future app development from public women, content and software experts.  The information will be used to develop a breast examination awareness mobile app integrated with health theories.

    Matched MeSH terms: Software Design
  11. Apriono C, Muin F, Juwono FH
    Sensors (Basel), 2021 Aug 28;21(17).
    PMID: 34502698 DOI: 10.3390/s21175807
    Recently, rapid advances in radio detection and ranging (radar) technology applications have been implemented in various fields. In particular, micro-Doppler radar has been widely developed to perform certain tasks, such as detection of buried victims in natural disaster, drone system detection, and classification of humans and animals. Further, micro-Doppler radar can also be implemented in medical applications for remote monitoring and examination. This paper proposes a human respiration rate detection system using micro-Doppler radar with quadrature architecture in the industrial, scientific, and medical (ISM) frequency of 5.8 GHz. We use a mathematical model of human breathing to further explore any insights into signal processes in the radar. The experimental system is designed using the USRP B200 mini-module as the main component of the radar and the Vivaldi antennas working at 5.8 GHz. The radar system is integrated directly with the GNU Radio Companion software as the processing part. Using a frequency of 5.8 GHz and USRP output power of 0.33 mW, our proposed method was able to detect the respiration rate at a distance of 2 m or less with acceptable error. In addition, the radar system could differentiate different frequency rates for different targets, demonstrating that it is highly sensitive. We also emphasize that the designed radar system can be used as a portable device which offers flexibility to be used anytime and anywhere.
    Matched MeSH terms: Software
  12. Emrizal R, Hamdani HY, Firdaus-Raih M
    Int J Mol Sci, 2021 Aug 09;22(16).
    PMID: 34445259 DOI: 10.3390/ijms22168553
    The increasing number and complexity of structures containing RNA chains in the Protein Data Bank (PDB) have led to the need for automated structure annotation methods to replace or complement expert visual curation. This is especially true when searching for tertiary base motifs and substructures. Such base arrangements and motifs have diverse roles that range from contributions to structural stability to more direct involvement in the molecule's functions, such as the sites for ligand binding and catalytic activity. We review the utility of computational approaches in annotating RNA tertiary base motifs in a dataset of PDB structures, particularly the use of graph theoretical algorithms that can search for such base motifs and annotate them or find and annotate clusters of hydrogen-bond-connected bases. We also demonstrate how such graph theoretical algorithms can be integrated into a workflow that allows for functional analysis and comparisons of base arrangements and sub-structures, such as those involved in ligand binding. The capacity to carry out such automatic curations has led to the discovery of novel motifs and can give new context to known motifs as well as enable the rapid compilation of RNA 3D motifs into a database.
    Matched MeSH terms: Software*
  13. Zeng H, Zhang J, Preising GA, Rubel T, Singh P, Ritz A
    Nucleic Acids Res, 2021 07 02;49(W1):W257-W262.
    PMID: 34037782 DOI: 10.1093/nar/gkab420
    Networks have been an excellent framework for modeling complex biological information, but the methodological details of network-based tools are often described for a technical audience. We have developed Graphery, an interactive tutorial webserver that illustrates foundational graph concepts frequently used in network-based methods. Each tutorial describes a graph concept along with executable Python code that can be interactively run on a graph. Users navigate each tutorial using their choice of real-world biological networks that highlight the diverse applications of network algorithms. Graphery also allows users to modify the code within each tutorial or write new programs, which all can be executed without requiring an account. Graphery accepts ideas for new tutorials and datasets that will be shaped by both computational and biological researchers, growing into a community-contributed learning platform. Graphery is available at https://graphery.reedcompbio.org/.
    Matched MeSH terms: Software*
  14. Amir SH, Yuswan MH, Aizat WM, Mansor MK, Desa MNM, Yusof YA, et al.
    J Proteomics, 2021 06 15;241:104240.
    PMID: 33894373 DOI: 10.1016/j.jprot.2021.104240
    Mass spectrometry-based proteomics relies on dedicated software for peptide and protein identification. These software include open-source or commercial-based search engines; wherein, they employ different algorithms to establish their scoring and identified proteins. Although previous comparative studies have differentiated the proteomics results from different software, there are still yet studies specifically been conducted to compare and evaluate the search engine in the field of halal analysis. This is important because the halal analysis is often using commercial meat samples that have been subjected to various processing, further complicating its analysis. Thus, this study aimed to assess three open-source search engines (Comet, X! Tandem, and ProteinProspector) and a commercial-based search engine (ProteinPilot™) against 135 raw tandem mass spectrometry data files from 15 types of pork-based food products for halal analysis. Each database search engine contained high false-discovery rate (FDR); however, a post-searching algorithm called PeptideProphet managed to reduce the FDR, except for ProteinProspector and ProteinPilot™. From this study, the combined database search engine (executed by iProphet) reveals a thorough protein list for pork-based food products; wherein the most abundant proteins are myofibrillar proteins. Thus, this proteomics study will aid the identification of potential peptide and protein biomarkers for future precision halal analysis. SIGNIFICANCE: A critical challenge of halal proteomics is the availability of a database to confirm the inferential peptides as well as proteins. Currently, the established database such as UniProtKB is related to animal proteome; however, the halal proteomics is related to the highly processed meat-based food products. This study highlights the use of different database search engines (Comet, X! Tandem, ProteinProspector, and ProteinPilot™) and their respective algorithms to analyse 135 raw tandem mass spectrometry data files from 15 types of pork-based food products. This is the first attempt that has compared different database search engines in the context of halal proteomics to ensure the effectiveness of controlling the FDR. Previous studies were just focused on the advantages of a certain algorithm over another. Moreover, other previous studies also have mainly reported the use of mass spectrometry-based shotgun proteomics for meat authentication (the most similar field to halal analysis), but none of the studies were reported on halal aspects that used samples originated from highly processed food products. Hence, a systematic comparative study is duly needed for a more comprehensive and thorough proteomics analysis for such samples. In this study, our combinatorial approach for halal proteomics results from the different search engines used (Comet, X! Tandem, and ProteinProspector) has successfully generated a comprehensive spectral library for the pork-based meat products. This combined spectral library is freely available at https://data.mendeley.com/datasets/6dmm8659rm/3. Thus far, this is the first and new attempt at establishing a spectral library for halal proteomics. We also believe this study is a pioneer for halal proteomics that aimed at non-conventional and non-model organism proteomics, protein analytics, protein bioinformatics, and potential biomarker discovery.
    Matched MeSH terms: Software
  15. Khan IM, Mani SA, Doss JG, Danaee M, Kong LYL
    BMC Oral Health, 2021 Jun 02;21(1):283.
    PMID: 34078349 DOI: 10.1186/s12903-021-01643-8
    BACKGROUND: Toothbrushing is an important yet neglected behaviour that affects the oral health of preschool children. Little is reported on parental supervision, an essential aspect of routine effective toothbrushing in this age group. The aim of this study was to evaluate pre-schoolers' toothbrushing behaviour including parental involvement and its association with their oral health.

    METHODS: This was a cross-sectional study. A total of 92 preschool children (4-6 years) were invited to participate with their parents/guardians. Nine parameters of toothbrushing behaviour were assessed from parental responses (questionnaire) and observation of child and parents/guardians (video recording). Oral examination included recording plaque, gingival and dental caries indices. BORIS software was used to assess toothbrushing parameters and Smart PLS was used to perform association with a second-generation multivariate analysis to create models with and without confounding factors.

    RESULTS: Girls were slightly more (53%) than boys (47%). Children aged 4 years were slightly more in number (38%), followed by 6-year-olds and 5-year-olds. Nearly, 90% parents had tertiary education and 46% had more than 2 children. Differences were recorded in the reported and observed behaviour. Thirty-five percent parents/guardians reported using pea-size toothpaste amount but only 28% were observed. Forty percent reported to brush for 30 s-1 min, however 51% were observed to brush for 1-2 min. Half the children were observed to use fluoridated toothpaste (F 

    Matched MeSH terms: Software
  16. Zaini MF, Sarudin A, Muhammad MM, Osman Z, Mohamed Redzwan HF, Al-Muhsin MA
    Data Brief, 2021 Jun;36:107013.
    PMID: 33898671 DOI: 10.1016/j.dib.2021.107013
    House Building Tips is the title of a classic text containing historical information on early house construction in Malay communities. These tips were written by a scholar with knowledge of house construction through observation of the surrounding environment. In Malaysia, written sources or records of house construction are scarce and underexposed. As such, this research was conducted to guarantee the written legacy of the construction of Malay houses. The purpose of this paper is to introduce a statistical data source of house building tips that is laden with Malay ingenuity and identity. The wordlists generated from this study can become a source of reference for the field of Malay architecture. Accordingly, this study utilises the quantitative method by applying the Linguistic Corpus Statistical Approach; these data utilise specific corpus development procedures, beginning with text collection, scanning and cleaning processes, text annotation, and data storing in plain text. Next, the data analysis procedure utilises a corpus software, LancsBox, to generate specialised wordlists. The bubble graphs are developed based on these wordlists through the Tableau software, and illustrate the most used lexical items with the raw and relative frequency values. This facilitates searches for, and the reading of, architectural words and architectural word references. These data represent written sources that need to be preserved and become points of reference concerning Malay architectural ingenuity and identity.
    Matched MeSH terms: Software
  17. Syarifah SM, Mohd Kassim AS, Mohd Aripin A, Chan CM, Zainulabidin MH, Ishak N, et al.
    Data Brief, 2021 Jun;36:107030.
    PMID: 34026964 DOI: 10.1016/j.dib.2021.107030
    This article presents experimental data on oil palm biomass (oil palm leaves, oil palm trunk and empty fruit bunch) handsheet production characterization by biodelignification treatment using Bacillus cereus extracted from termite gut (Coptotermus curvignathus). It associates the lignocellulose chemical composition obtained via technical association pulp and paper industry TAPPI T 222 om-02 testing on lignin content reduction determination, holocellulose and hemicellulose content determination (Kurscher-Hoffner method). Several data obtained for handsheet characterization presents brightness, opacity, contrast ratio, din transparency, thickness, bursting and tearing indexes are collected. Handsheet surface morphology was also observed on ratio of gaps differences between fiber bonding conducted using scanning electron microscope (SEM) and ImageJ software. The raw data findings supplement chemical composition analysis for both untreated and treated substrates on handsheet quality performance check as presented in the research article "Bio-Mechanical Pulping of Bacteria Pre-Treatment on Oil Palm Biomass for Handsheet Production" [1]. For understanding correlations into the difference among lignocellulose content composition which affect the handsheet formation and mechanical strength refer to article from this research [1]. This dataset is made publicly available for optimizing alternative waste material reuse in the pulp and paper industrial section.
    Matched MeSH terms: Software
  18. Farook TH, Barman A, Abdullah JY, Jamayet NB
    J Prosthodont, 2021 Jun;30(5):420-429.
    PMID: 33200429 DOI: 10.1111/jopr.13286
    PURPOSE: Mesh optimization reduces the texture quality of 3D models in order to reduce storage file size and computational load on a personal computer. This study aims to explore mesh optimization using open source (free) software in the context of prosthodontic application.

    MATERIALS AND METHODS: An auricular prosthesis, a complete denture, and anterior and posterior crowns were constructed using conventional methods and laser scanned to create computerized 3D meshes. The meshes were optimized independently by four computer-aided design software (Meshmixer, Meshlab, Blender, and SculptGL) to 100%, 90%, 75%, 50%, and 25% levels of original file size. Upon optimization, the following parameters were virtually evaluated and compared; mesh vertices, file size, mesh surface area (SA), mesh volume (V), interpoint discrepancies (geometric similarity based on virtual point overlapping), and spatial similarity (volumetric similarity based on shape overlapping). The influence of software and optimization on surface area and volume of each prosthesis was evaluated independently using multiple linear regression.

    RESULTS: There were clear observable differences in vertices, file size, surface area, and volume. The choice of software significantly influenced the overall virtual parameters of auricular prosthesis [SA: F(4,15) = 12.93, R2 = 0.67, p < 0.001. V: F(4,15) = 9.33, R2 = 0.64, p < 0.001] and complete denture [SA: F(4,15) = 10.81, R2 = 0.67, p < 0.001. V: F(4,15) = 3.50, R2 = 0.34, p = 0.030] across optimization levels. Interpoint discrepancies were however limited to <0.1mm and volumetric similarity was >97%.

    CONCLUSION: Open-source mesh optimization of smaller dental prostheses in this study produced minimal loss of geometric and volumetric details. SculptGL models were most influenced by the amount of optimization performed.

    Matched MeSH terms: Software
  19. El Saftawy EA, Shash RY, Aboulhoda BE, Arsanyos SF, Albadawi EA, Abou-Fandoud SM, et al.
    Trop Biomed, 2021 Jun 01;38(2):53-62.
    PMID: 33973573 DOI: 10.47665/tb.38.2.037
    BACKGROUND: toxoplasmosis is a cosmopolitan protozoan disease with a wide range of neuropathology. Recent studies identified its potential association with several mental disorders e.g. schizophrenia dependable on apoptosis in their pathogenesis. We investigated value of toxoplasmosis to induce apoptosis of the neuronal cells.

    METHODS: per-orally infected C57BL/6 mice with 15-20 cysts of the avirulent T. gondii Beverly strain at 9-11 weeks of age were examined 12 weeks later during parasite establishment. Distributions of the parasite's cysts and the histopathological lesions in the brains were analyzed using Image J software. Relative expression of TNF-α and iNOS of cell-mediated immunity (CMI), Bax (pro-apoptosis) and Bcl-2 (anti-apoptosis) were all assessed using immunohistochemistry.

    RESULTS: higher parasite burden was seen in the forebrain with p value <= 0.05. Dramatically increased TNF-α, iNOS, and Bax expressions with Bax/Bcl-2 ratio 2.42:0.52 were reported (p value <= 0.05). The significant correlation between Bax data and different CMI biomarkers including TNF-α and i-NOS was evaluated. Interestingly, no significant correlation was seen between TNF-α, iNOS, Bax and Bcl-2 expressions and location of the parasite. However, Bax/Bcl-2 ratio was statistically correlated with CMI biomarkers and whole sample mean parasite burden, p value <= 0.05.

    CONCLUSION: Chronic toxoplasmosis exhibits an immense pro-apoptotic signal on the cerebral tissues of experimental mice.

    Matched MeSH terms: Software
  20. Rogers BD, Rengarajan A, Abrahao L, Bhatia S, Bor S, Carlson DA, et al.
    Neurogastroenterol Motil, 2021 06;33(6):e14009.
    PMID: 33094875 DOI: 10.1111/nmo.14009
    BACKGROUND: Esophagogastric junction contractile integral (EGJ-CI) and EGJ morphology are high-resolution manometry (HRM) metrics that assess EGJ barrier function. Normative data standardized across world regions and HRM manufacturers are limited.

    METHODS: Our aim was to determine normative EGJ metrics in a large international cohort of healthy volunteers undergoing HRM (Medtronic, Laborie, and Diversatek software) acquired from 16 countries in four world regions. EGJ-CI was calculated by the same two investigators using a distal contractile integral-like measurement across the EGJ for three respiratory cycles and corrected for respiration (mm Hg cm), using manufacturer-specific software tools. EGJ morphology was designated according to Chicago Classification v3.0. Median EGJ-CI values were calculated across age, genders, HRM systems, and regions.

    RESULTS: Of 484 studies (28.0 years, 56.2% F, 60.7% Medtronic studies, 26.0% Laborie, and 13.2% Diversatek), EGJ morphology was type 1 in 97.1%. Median EGJ-CI was similar between Medtronic (37.0 mm Hg cm, IQR 23.6-53.7 mm Hg cm) and Diversatek (34.9 mm Hg cm, IQR 22.1-56.1 mm Hg cm, P = 0.87), but was significantly higher using Laborie equipment (56.5 mm Hg cm, IQR 35.0-75.3 mm Hg cm, P 

    Matched MeSH terms: Software
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