Disturbance rejecting PID-FF controller design of a non-ideal buck converter using an innovative snake optimizer with pattern search algorithm.

The optimal design of a proportional-integral-derivative controller with two cascaded first-order low-pass filters (PID-FF) for non-ideal buck converters faces significant challenges, including effective disturbance rejection, robustness to parameter variations, and the mitigation of high-frequency signal noise, with existing approaches often struggling and leading to suboptimal performance in practical applications. This study addresses these challenges by introducing a constraint on the open-loop crossover frequency to mitigate high-frequency noise and ensuring the controller prioritizes maintaining constant output voltage and robust responsiveness to input voltage and load current variations. This study also introduces an innovative metaheuristic algorithm, the opposition-based snake optimizer with pattern search (OSOPS), designed to address these limitations. OSOPS enhances the Snake Optimizer (SO) by integrating opposition-based learning (OBL) and Pattern Search (PS), thereby improving its exploration and exploitation capabilities. The proposed algorithm design includes a crossover frequency constraint aimed at counteracting high-frequency noise and ensuring robust performance under diverse disturbances. The efficacy of the OSOPS algorithm is demonstrated through rigorous statistical box plot analysis and convergence response comparisons with the original SO algorithm. Additionally, we systematically compare the performance of the OSOPS-based PID-FF-controlled non-ideal buck converter system against systems utilizing the original SO algorithm and the classical pole placement (PP) method. This evaluation encompasses transient and frequency responses, disturbance rejection, and robustness analysis. The results reveal that the OSOPS-based system outperforms the SO- and PP-based systems with 14.21 % and 32.10 % faster rise times, along with 15.38 % and 84.95 % faster settling times, respectively. The OSOPS and SO systems also exhibit higher bandwidths, exceeding the PP-based system by 18.74 % and 17.03 %, respectively. By addressing the key challenges in PID-FF controller design for non-ideal buck converters, this study provides a substantial advancement in control strategy, promising enhanced performance in practical applications.

Targeted delivery of temozolomide by nanocarriers based on folic acid-hollow TiO2 -nanospheres for the treatment of glioblastoma.

Glioblastoma multiforme (GBM) is a highly malignant brain tumor. Its standard treatment includes a combination of surgery, radiation, and chemotherapy. The last involves the oral delivery of free drug molecules to GBM such as Temozolomide (TMZ). However, this treatment has limited effectiveness owing to the drugs premature degradation, lack of cell selectivity, and poor control of pharmacokinetics. In this work, the development of a nanocarrier based on hollow titanium dioxide (HT) nanospheres functionalized with folic acid (HT-FA) for the targeted delivery of temozolomide (HT-TMZ-FA) is reported. This approach has the potential benefits of prolonging TMZ degradation, targeting GBM cells, and increasing TMZ circulation time. The HT surface properties were studied, and the nanocarrier surface was functionalized with folic acid as a potential targeting agent against GBM. The loading capacity, protection from degradation, and drug retention time were investigated. Cell viability was performed to assess the cytotoxicity of HT against LN18, U87, U251, and M059K GBM cell lines. The cell internalization of HT configurations (HT, HT-FA, HT-TMZ-FA) was evaluated to study targeting capabilities against GBM cancer. Results show that HT nanocarriers have a high loading capacity, retain and protect TMZ for at least 48 h. Folic acid-functionalized HT nanocarriers successfully delivered and internalized TMZ to glioblastoma cancer cells with high cytotoxicity through autophagic and apoptotic cellular mechanisms. Thus, HT-FA nanocarriers could be a promising targeted delivery platform for chemotherapeutic drugs for the treatment of GBM cancer.

Modeling decision support rule interactions in a clinical setting.

Traditionally, rule interactions are handled at implementation time through rule task properties that control the order in which rules are executed. By doing so, knowledge about the behavior and interactions of decision rules is not captured at modeling time. We argue that this is important knowledge that should be integrated in the modeling phase. In this project, we build upon current work on a conceptual schema to represent clinical knowledge for decision support in the form of if then rules. This schema currently captures provenance of the clinical content, context where such content is actionable (i.e. constraints) and the logic of the rule itself. For this project, we borrowed concepts from both the Semantic Web (i.e., Ontologies) and Complex Adaptive Systems (CAS), to explore a conceptual approach for modeling rule interactions in an enterprise-wide clinical setting. We expect that a more comprehensive modeling will facilitate knowledge authoring, editing and update; foster consistency in rules implementation and maintenance; and develop authoritative knowledge repositories to promote quality, safety and efficacy of healthcare.

Size control of gold nanoparticles grown on polyaniline nanofibers for bistable memory devices.

Controlling reaction temperature for a set time enables the size of gold nanoparticles autoreduced on the surface of polyaniline nanofibers to be controlled. The size of the gold nanoparticles can be used to tune the electrical bistable memory effect in gold/polyaniline nanofiber composite devices. Turn-on voltages and on/off ratios improve with decreasing nanoparticle size, making this a promising method to enhance performance and create smaller devices. Long-term stability of the composites can be improved by the addition of stabilizers following autoreduction of the gold nanoparticles.

Nanoscale memory characterization of virus-templated semiconducting quantum dots.

We have developed a substrate-based bottom-up approach to assemble two different color emitting quantum dots (CdSe/ZnS core/shell QDs) on the surface of a novel virus mutant, CPMV-T184C. Electrical characteristics of individual hybrids were investigated by conductive atomic force microscopy for potential digital memory applications (i.e., RAM). These individual 40 nm CPMV-QD(1,2) hybrids exhibited reversible bistable electrical behavior during repeatable writing-reading-erasing processes at the nanoscale.