The problem of designing tablet geometry and its internal structure that results into a specified release profile of the drug during dissolution was considered. A solution method based on parametric programming, inspired by CAD (computer-aided design) approaches currently used in other fields of engineering, was proposed and demonstrated. The solution of the forward problem using a parametric series of structural motifs was first carried out in order to generate a library of drug release profiles associated with each structural motif. The inverse problem was then solved in three steps: first, the combination of basic structural motifs whose superposition provides the closest approximation of the required drug release profile was found by a linear combination of pre-calculated release profiles. In the next step, the final tablet design was constructed and its dissolution curve found computationally. Finally, the proposed design was 3D printed and its dissolution profile was confirmed experimentally. The computational method was based on the numerical solution of drug diffusion in a boundary layer surrounding the tablet, coupled with erosion of the tablet structure encoded by the phase volume function. The tablets were 3D printed by fused deposition modelling (FDM) from filaments produced by hot-melt extrusion. It was found that the drug release profile could be effectively controlled by modifying the tablet porosity. Custom release profiles were obtained by combining multiple porosity regions in the same tablet. The computational method yielded accurate predictions of the drug release rate for both single- and multi-porosity tablets.
- Keywords
- 3D printing, dissolution, hot-melt extrusion, mathematical modelling, parametric programming,
- MeSH
- Printing, Three-Dimensional * MeSH
- Technology, Pharmaceutical methods MeSH
- Porosity MeSH
- Tablets chemistry pharmacokinetics MeSH
- Drug Liberation MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Tablets MeSH
This paper introduces a novel two-step generalized parametric approach for addressing Fuzzy Multi-Objective Transportation Problems (FMOTPs), commonly encountered in logistics and transportation systems when essential parameters-such as supply, demand, and transportation costs-are uncertain. Driven by the necessity for resilient and flexible decision-making amidst uncertainty, the method employs Triangular Fuzzy Numbers (TFNs) and an accuracy parameter μ ∈ [0,1] to turn fuzzy data into precise equivalents through parametric transformation. Initially, imprecise input data are methodically converted into a sequence of Crisp Multi-Objective Transportation Problems (CMOTPs). In the subsequent phase, these CMOTPs are addressed by Fuzzy Linear Programming (FLP), and the most equitable solution at each μ-level is determined by its Euclidean distance from the fuzzy ideal solution. The suggested method is tested by numerical case studies and compared with current models-such as Nomani's approach, fuzzy DEA, and Grey Relational Analysis (GRA)-showing enhanced performance in optimality proximity, solution stability, and ranking accuracy. This research has practical applications, including improved managerial capacity to manage uncertainty, reconcile trade-offs among cost, time, and service quality, and execute robust transportation strategies in fluctuating environments. The model's scalability and openness make it suited for integration into enterprise logistics systems across industries such as manufacturing, retail, distribution, and e-commerce. The study offers a systematic and computationally efficient framework that enhances both theoretical comprehension and practical implementation of fuzzy optimization in multi-objective transportation planning.
The authors describe the EPI INFO system suitable for introducing on a personal computer, compatible with the standard IBM XT/AT. The system was elaborated by a group of workers from Centres of Disease Control in Alabama in 1988. The advantage of the system is in addition to ready availability (it is distributed on a non-commercial basis), in particular because it combines the advantages of the data base and statistical programme system. It makes it possible storage of data, their easy processing by classification and tabulation, evaluation by some statistical (parametric and non-parametric) tests and simple graphical presentation of results, e.g. in histograms or figures using columns. Moreover, it is possible to make in the EPI INFO system further modifications of the stored data and to combine groups of similar or different format. The system does not only create its own external data groups but makes also possible their conversion into other systems and conversely is able to create from external groups of data its own groups of data.
- MeSH
- Epidemiologic Methods * MeSH
- Software * MeSH
- Statistics as Topic MeSH
- Publication type
- English Abstract MeSH
- Journal Article MeSH
Magnetic resonance spectroscopic imaging (MRSI) involves a huge number of spectra to be processed and analyzed. Several tools enabling MRSI data processing have been developed and widely used. However, the processing programs primarily focus on sophisticated spectra processing and offer limited support for the analysis of the calculated spectroscopic maps. In this paper the jSIPRO (java Spectroscopic Imaging PROcessing) program is presented, which is a java-based graphical interface enabling post-processing, viewing, analysis and result reporting of MRSI data. Interactive graphical processing as well as protocol controlled batch processing are available in jSIPRO. jSIPRO does not contain a built-in fitting program. Instead, it makes use of fitting programs from third parties and manages the data flows. Currently, automatic spectra processing using LCModel, TARQUIN and jMRUI programs are supported. Concentration and error values, fitted spectra, metabolite images and various parametric maps can be viewed for each calculated dataset. Metabolite images can be exported in the DICOM format either for archiving purposes or for the use in neurosurgery navigation systems.
- Keywords
- DICOM export, LCModel, Metabolite images, Spectra processing, Spectroscopic imaging, TARQUIN, jMRUI,
- MeSH
- Electronic Data Processing statistics & numerical data MeSH
- Fourier Analysis MeSH
- Functional Neuroimaging statistics & numerical data MeSH
- Humans MeSH
- Magnetic Resonance Imaging statistics & numerical data MeSH
- Brain metabolism pathology MeSH
- Programming Languages MeSH
- Software * MeSH
- Imaging, Three-Dimensional MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
The objective of this study was to ascertain changes in symptoms of patients with borderline personality disorder undergoing psychodynamic day treatment with a duration of 9 months and the factors that predict clinical outcome or dropouts from the program.In an observational study, demographic characteristics (age, number of psychiatric hospitalizations, number of suicide attempts, current involvement in work or study activities), day doses of antipsychotic and antidepressant medication, psychiatric symptoms, and social functioning (Health of the Nation Outcome Scales), and symptoms of dissociation (Dissociative Experiences Scale) were assessed in patients at the beginning of treatment (N = 105). Further, psychiatric symptoms and social functioning were assessed at 3 stages: beginning of the program, end of the program, and 1-year follow-up. To study the differences between baseline values and values at the end of the treatment and follow-up values, the Wilcoxon signed-rank test was used. To discover baseline factors related to the effect of the treatment, Spearman correlation coefficients were calculated. To evaluate the differences between patients who completed the program (N = 67) and patients who dropped out (N = 38), differences in baseline factors between both groups were compared, using the Mann-Whitney test for independent samples.Improvement in symptoms (Health of the Nation Outcome Scales - version for external evaluators) at the end of the therapy (N = 67, P < .001) and at the 1-year follow-up (N = 46, P < .001) was found. Experience of an intimate relationship was positively related to clinical improvement at follow-up examinations (P < .001). Predictors of dropout included a higher number of psychiatric hospitalizations (P = .004), suicide attempts (P = .004), more severe pretreatment symptoms (P = .002), and symptoms of dissociation (P = .046).The results indicate that a psychodynamic day treatment is feasible for the treatment of less clinically disturbed patients with a history of intimate relationships. Patients with a higher number of previous psychiatric hospitalizations, more suicide attempts in the past, more severe pretreatment symptoms, and symptoms of dissociation are more likely not to complete the program.
- MeSH
- Day Care, Medical methods MeSH
- Adult MeSH
- Borderline Personality Disorder therapy MeSH
- Humans MeSH
- Statistics, Nonparametric MeSH
- Suicide, Attempted statistics & numerical data MeSH
- Psychiatric Status Rating Scales MeSH
- Psychotherapy, Psychodynamic methods MeSH
- Regression Analysis MeSH
- Risk Factors MeSH
- Feasibility Studies MeSH
- Patient Dropouts statistics & numerical data MeSH
- Treatment Outcome MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Observational Study MeSH
A simple semiautomated system for evaluation of histomorphometric parametres in bioptic bone sections was designed in cooperation of programmer and a pathologist. It saves time and effort of pathologist substantially and shows a relative numerical precision. It is based on digitalization of microscopical picture projected on a desk and computerized processing of digitalized picture.
- MeSH
- Biopsy * MeSH
- Bone and Bones pathology MeSH
- Humans MeSH
- Image Processing, Computer-Assisted * MeSH
- Software * MeSH
- Check Tag
- Humans MeSH
- Publication type
- English Abstract MeSH
- Journal Article MeSH
This article deals with continuous-time Linear Time-Invariant (LTI) Single-Input Single-Output (SISO) systems affected by unstructured multiplicative uncertainty. More specifically, its aim is to present an approach to the construction of uncertain models based on the appropriate selection of a nominal system and a weight function and to apply the fundamentals of robust stability investigation for considered sort of systems. The initial theoretical parts are followed by three extensive illustrative examples in which the first order time-delay, second order and third order plants with parametric uncertainty are modeled as systems with unstructured multiplicative uncertainty and subsequently, the robust stability of selected feedback loops containing constructed models and chosen controllers is analyzed and obtained results are discussed.
- MeSH
- Uncertainty * MeSH
- Programming, Linear * MeSH
- Publication type
- Journal Article MeSH
OBJECTIVE: The aim of the study was to investigate the effectiveness and feasibility of conducting a complementary 8-week comprehensive lifestyle modification program (CLMP) compared to standard care in patients with bronchial asthma over a 6-month period. METHODS: This was a randomized controlled pilot trial with two groups: intervention (N = 15) group and attention-placebo control (N = 14) group. The intervention group received an 8-week CLMP in addition to standard care. Quality of life, asthma control, lung function, reduction of rescue medication, perceived stress, and psychosocial and spiritual status were measured at the end of the intervention and at the 4-month follow-up. RESULTS: In the intervention group, there was a statistically significant difference in the improvements of quality of life, asthma control, lung function, and the reduction of rescue medication intake at both the end of the intervention and at the 4-month follow-up, with no change being observed in the control group. Significant stress reduction and greater psychosocial and spiritual well-being were observed during the 8-week CLMP in the intervention group. At the end of the intervention, the measures of stress and psychological and spiritual well-being reached statistical significance. CONCLUSIONS: Preliminary findings suggest that adding a CLMP to standard care in patients with bronchial asthma offers greater clinical benefit than standard care alone and also suggest that conducting a large randomized clinical trial is feasible.
- MeSH
- Anti-Asthmatic Agents administration & dosage MeSH
- Behavior Therapy methods MeSH
- Asthma drug therapy physiopathology psychology therapy MeSH
- Quality of Life MeSH
- Middle Aged MeSH
- Humans MeSH
- Statistics, Nonparametric MeSH
- Pilot Projects MeSH
- Respiratory Function Tests MeSH
- Life Style MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Randomized Controlled Trial MeSH
- Comparative Study MeSH
- Names of Substances
- Anti-Asthmatic Agents MeSH
Crop improvement is a long-term, expensive institutional endeavor. Genomic selection (GS), which uses single nucleotide polymorphism (SNP) information to estimate genomic breeding values, has proven efficient to increasing genetic gain by accelerating the breeding process in animal breeding programs. As for crop improvement, with few exceptions, GS applicability remains in the evaluation of algorithm performance. In this study, we examined factors related to GS applicability in line development stage for grain yield using a hard red winter wheat (Triticum aestivum L.) doubled-haploid population. The performance of GS was evaluated in two consecutive years to predict grain yield. In general, the semi-parametric reproducing kernel Hilbert space prediction algorithm outperformed parametric genomic best linear unbiased prediction. For both parametric and semi-parametric algorithms, an upward bias in predictability was apparent in within-year cross-validation, suggesting the prerequisite of cross-year validation for a more reliable prediction. Adjusting the training population's phenotype for genotype by environment effect had a positive impact on GS model's predictive ability. Possibly due to marker redundancy, a selected subset of SNPs at an absolute pairwise correlation coefficient threshold value of 0.4 produced comparable results and reduced the computational burden of considering the full SNP set. Finally, in the context of an ongoing breeding and selection effort, the present study has provided a measure of confidence based on the deviation of line selection from GS results, supporting the implementation of GS in wheat variety development.
MOTIVATION: Genome analysis has become one of the most important tools for understanding the complex process of cancerogenesis. With increasing resolution of CGH arrays, the demand for computationally efficient algorithms arises, which are effective in the detection of aberrations even in very noisy data. RESULTS: We developed a rather simple, non-parametric technique of high computational efficiency for CGH array analysis that adopts a median absolute deviation concept for breakpoint detection, comprising median smoothing for pre-processing. The resulting algorithm has the potential to outperform any single smoothing approach as well as several recently proposed segmentation techniques. We show its performance through the application of simulated and real datasets in comparison to three other methods for array CGH analysis. IMPLEMENTATION: Our approach is implemented in the R-language and environment for statistical computing (version 2.6.1 for Windows, R-project, 2007). The code is available at: http://www.iba.muni.cz/~budinska/msmad.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
