PURPOSE OF REVIEW: Recent advancements in the understanding of the genetic background of genitourinary cancers allowed for a successful introduction of targeted antitumor agents to prostate cancer (PCa) treatment. Inhibitors of the poly ADP-ribose polymerase enzyme (PARPi) transformed the treatment landscape of metastatic prostate cancer, and being increasingly studied in earlier disease stages. However, they are associated with nonnegligible toxicity, therefore, we aimed to summarize their side-effect profile in patients with PCa. RECENT FINDINGS: Hematologic toxicities, particularly anemia, thrombocytopenia, and neutropenia are among the most common and serious adverse events associated with PARPi, highlighting the need for regular blood count monitoring. Nonhematologic side effects, including fatigue, nausea, vomiting, diarrhea, and constipation, are common, and can be mitigated with supportive interventions like dietary modifications, antiemetics, or stool management techniques. Special attention should be given to patients with therapy-resistant or persistent cytopenia, in whom bone marrow biopsy should be considered, as it can indicate myelodysplastic syndrome and acute myeloid leukemia. SUMMARY: PARP inhibitors represent a major advancement in the management of metastatic prostate cancer, offering a significant survival benefit in applicable cases. However, patients need to be carefully selected and informed, to allow for optimal balancing between the benefits and nonneglectable risks of severe toxicities. Better understanding of PARPi toxicity profile can improve personalized decision-making and enhance treatment compliance, through raising patients' awareness about the possible side effects of PARPi.
- Klíčová slova
- BRCA, adverse event, anemia, fatigue, genetic test, niraparib, olaparib, poly ADP-ribose polymerase inhibitors, prostate cancer, side effects, talazoparib, toxicity,
- MeSH
- lidé MeSH
- nádory prostaty * farmakoterapie patologie MeSH
- PARP inhibitory * škodlivé účinky MeSH
- urogenitální nádory * farmakoterapie MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
- Názvy látek
- PARP inhibitory * MeSH
The rising energy demand, substantial transmission and distribution losses, and inconsistent power quality in remote regions highlight the urgent need for innovative solutions to ensure a stable electricity supply. Microgrids (MGs), integrated with distributed generation (DG), offer a promising approach to address these challenges by enabling localized power generation, improved grid flexibility, and enhanced reliability. This paper introduces the Improved Lyrebird Optimization Algorithm (ILOA) for optimal sectionalizing and scheduling of multi-microgrid systems, aiming to minimize generation costs and active power losses while ensuring system reliability. To enhance search efficiency, ILOA incorporates the Levy Flight technique for local search, which introduces adaptive step sizes with long-distance jumps, improving the exploration-exploitation balance. Unlike conventional local search strategies that rely on fixed step sizes, Levy Flight prevents premature convergence by allowing the algorithm to escape local optima and explore the solution space more effectively. Additionally, a chaotic sine map is integrated to enhance global search capability, ensuring better diversity and superior optimization performance compared to traditional algorithms. Simulation studies are conducted on a modified 33-bus distribution system segmented into three independent microgrids. The algorithm is evaluated under single-objective scenarios (cost and loss minimization) and a multi-objective optimization framework combining both objectives. In single-objective optimization, ILOA achieves a generation cost of $19,254.64/hr with 0.7118 kW of power loss, demonstrating marginal improvements over the standard Lyrebird Optimization Algorithm and significant gains over Genetic Algorithm (GA) and Jaya Algorithm (JAYA). In multi-objective optimization, ILOA surpasses competing methods by achieving a generation cost of $89,792.18/hr and 10.26 kW of power loss. The optimization results indicate that, for the IEEE-33 bus system without considering EIR, the proposed ILOA algorithm achieves savings of approximately 0.0014%, 0.0041%, and 0.657% in operation costs compared to LOA, JAYA, and GA, respectively, when MG-1, MG-2, and MG-3 are operational. The analysis of real power loss reduction demonstrates that, in the IEEE-33 bus system without considering EIR, the proposed ILOA algorithm effectively minimizes power loss by approximately 0.692%, 1.696%, and 1.962% in comparison to LOA, JAYA, and GA, respectively, under the operational conditions of MG-1, MG-2, and MG-3. Additionally, reliability constraints based on the Energy Index of Reliability (EIR) are effectively incorporated, further validating the robustness of the proposed approach. Considering EIR, the real power loss analysis for the IEEE-33 bus system highlights that the proposed ILOA algorithm achieves a reduction of approximately 1.319%, 2.069%, and 2.134% in comparison to LOA, JAYA, and GA, respectively, under the operational scenario where MG-1, MG-2, and MG-3 are active. The results confirm that ILOA is a highly efficient and reliable solution for distributed generation scheduling and multi-microgrid sectionalizing, showcasing its potential for real-world applications such as dynamic economic dispatch and demand response integration in smart grid systems.
The optimal siting and sizing of DGs are vital for the efficient operation of both radial and microgrid distribution systems. From an operational perspective, minimizing real power loss, reducing voltage deviation, and improving voltage stability index are the three primary objectives considered in this study. This manuscript addresses these issues by proposing a novel quasi-oppositional forensic-based investigation (QOFBI) algorithm, an evolutionary meta-optimization technique designed to optimize the location and sizing of DGs under various operating conditions, while adhering to system constraints. The approach introduces a weighting factor-based multiobjective formulation, where optimal weighting factors are computed dynamically. This ensures a balanced approach to minimizing power loss, voltage deviation, and enhancing voltage stability. Extensive simulations were conducted on the IEEE 33-bus and IEEE 69-bus standard distribution systems, evaluating the impact of DG placement with varying power factors under operational constraints. The results demonstrate the superiority of the proposed approach in terms of faster convergence, reduced complexity, and improved performance compared to existing optimization methods. The QOFBI algorithm achieves a 94.44% reduction in active power loss, highlighting its robust performance across different operational scenarios. These findings underscore the potential of QOFBI as a highly effective tool for DG optimization in modern distribution systems, offering both operational efficiency and system reliability.
Temperature control in continuous stirred tank heater (CSTH) systems is essential for ensuring energy efficiency, safety, and product quality in industrial processes. However, the nonlinear dynamics and external disturbances make conventional proportional-integral-derivative (PID) control inadequate for reliable operation. This study presents a novel two-degrees-of-freedom PID (2DoF-PID) controller optimized using the quadratic interpolation optimization (QIO) algorithm to enhance CSTH temperature regulation. The QIO-based approach allows independent tuning for setpoint tracking and disturbance rejection, overcoming the limitations of classical PID controllers. Extensive nonlinear time-domain simulations, reference tracking, and disturbance rejection tests demonstrate the superior performance of the proposed controller in terms of reduced overshoot, faster settling time, and minimal steady-state error. Furthermore, comparative evaluations with traditional tuning methods (Murrill and Rovira) and several state-of-the-art metaheuristic optimizers (DE, PSO, FLA, MGO) validate the effectiveness and robustness of the QIO-optimized strategy. This work introduces a pioneering application of the QIO algorithm in industrial temperature control, offering a scalable and cost-efficient solution for complex nonlinear systems.
Agriculture constitutes a foundational pillar of the Indian economy, contributing nearly 18% to the national Gross Domestic Product (GDP) and ranking second globally in horticultural output. Beyond its economic significance, the sector underpins rural employment, food security, and a wide range of agro-based downstream industries. Despite these strengths, Indian agriculture continues to encounter critical bottlenecks-most notably, post-harvest losses in fruits, which are estimated to range between 6.02% and 15.05%. These losses are predominantly attributed to the lack of accessible and decentralized cold storage infrastructure. Maintaining optimal temperature and humidity levels throughout the cold chain is essential to curtail physicochemical degradation and suppress microbial growth, both of which substantially diminish the quality and shelf life of perishable produce. This study introduces a solar photovoltaic (PV)-driven micro cold storage (MCS) system, specifically engineered for seamless integration with electric vehicles (EVs) to effectively mitigate post-harvest losses in perishable agricultural commodities. The research undertakes a comprehensive performance evaluation of the proposed system, which employs a thermoelectric cooling mechanism powered entirely by solar energy. Emphasis is placed on assessing the system's thermal, electrical, and microbial preservation capabilities under both static and dynamic operational conditions, highlighting its potential for sustainable and mobile cold chain applications in rural agricultural contexts. The system comprises a 100 Wp polycrystalline solar photovoltaic (PV) module, which supplies power to a 12 V/6A shunt-configured thermoelectric cooler with a 12 L storage capacity via a 12 V/8A solar charge controller. Functioning as an off-grid refrigeration unit, the system is supported by a 12 V/40Ah battery energy storage system. The experimental analysis focuses on assessing the shelf life of Vitis vinifera (grapes) over a one-week storage period by measuring physiological loss in weight (PLW) as the key parameter for evaluating storage efficiency. The refrigeration chamber maintains a controlled temperature range of + 2 °C to + 8 °C. Findings indicate a controlled weight reduction of up to 87.6% in refrigerated grapes compared to those stored under ambient conditions. Also, the system's performance to maintain proper storage conditions during short-distance transportation (six hours) is evaluated to demonstrate effective farm-to-market connectivity through electric vehicle utilization. The study evaluates the electrical and thermal performance of a system for renewable energy-integrated electric vehicle applications. It also investigates the effectiveness of a solar-powered modified controlled storage (MCS) system in preventing microbial growth and maintaining agro-produce quality during storage and transport. The microbial load, including bacterial, fungal, and yeast populations, was quantified using colony-forming unit (CFU) counts per millilitre to evaluate the system's efficacy in ensuring food safety. The findings underscore the environmental sustainability and practical applicability of the MCS system in the preservation of perishable agricultural produce. By enabling access to affordable, reliable, and renewable energy sources, the system directly contributes to the achievement of Sustainable Development Goal (SDG) 7, while simultaneously addressing food waste reduction and improving the efficiency and resilience of agro-supply chains.
- Klíčová slova
- Cold chain, Electric vehicles, Micro cold storage, Microbial load estimation, Post-harvest loss, Solar photovoltaic, Sustainable development goals, Thermoelectric cooling,
- MeSH
- doprava MeSH
- konzervace potravin * metody MeSH
- ovoce * mikrobiologie MeSH
- skladování potravin * metody MeSH
- sluneční energie * MeSH
- zemědělství * metody MeSH
- Publikační typ
- časopisecké články MeSH
This paper presents a comprehensive techno-economic analysis of three molten salt Concentrated Solar Power (CSP) tower plants located in the regions of Mechria, Adrar, and Tindouf in Algeria. The study evaluates the thermal efficiency, economic feasibility, and performance of these CSP using the System Advisor Model (SAM) software, which accurately models Direct Normal Irradiance (DNI), a critical factor influencing plant performance. Key parameters analyzed include Solar Multiple (SM), Thermal energy storage (TES) hours, capacity factor (CF), and the Levelized Cost of Energy (LCOE). The results demonstrate that an optimal heliostat field configuration with a SM of 1.8 and 10 h of TES achieves a capacity factor of 51.49%, with a minimum LCOE of 0.097 $/kWh. In Mechria, with operational and maintenance costs projected at 2.51 million dollars. For the Adrar region, a SM of 1.6 and TES of 2 h yield an LCOE of 0.18 $/kWh at a capacity factor of 24.03%. Similarly, in Tindouf, a SM of 1.6 and TES of 8 h result in a capacity factor of 18.95% and an LCOE of 0.17 $/kWh. The analysis reveals that the design of CSP systems, particularly the combination of solar Multiple and TES, plays a pivotal role in optimizing the economic performance of the plants, This approach enables researchers to save time and costs by using satellite-derived DNI estimations, enhancing data accuracy and optimizing CSP deployment.
- Klíčová slova
- Concentrating solar power, Direct normal irradiance, Energy performance, Optimization, Solar tower system, System advisor model, Techno-Economic analysis,
- Publikační typ
- časopisecké články MeSH
The exponential deployment of electric vehicles (EVs) in the residential sectors in recent years allows better energy utilization in the decentralized and centralized levels of distribution systems due to their bidirectional operation and energy storage capabilities. However, to execute these, it is necessary to adopt residential demand side management (RDSM) to schedule energy utilization effectively to fetch economical and efficient energy consumption and grid stability and reliability, particularly during peak load conditions. The paper aims to formulate a robust and efficient RDSM technique to provide an energy utilization scheduling considering various influential factors and critical roles of EVs in RDSM. A Binary Whale Optimization Algorithm (BWOA) approach is proposed as an efficient algorithm for EV's impact on the RDSM for better energy scheduling. A single-objective formulation is presented with detailed modelling considering economic energy utilization as the primary objective with all possible equality and inequality system operational constraints. Secondly, the impact of EVs on the RDSM is studied from various perspectives in result analysis, considering EVs as load, storage devices, and different bidirectional modes of operation with other vehicles, residential components, and grids. In addition, the EVs role and the mutual influence with the integration of renewable energy sources (RES) and energy storage devices (ESDs) are extensively analyzed to provide better residential energy management (REM) in terms of economic, environmental, robust, and reliable points of view. The load priority based on consumer choice is also incorporated in the formulation. Extensive simulation is done for the proposed approach to show the effect of EVs on REM, and the results are impressive to show the EV's role as a load, as a storage device, and as a mutually supportive device to RES, ESD, and grid.
Demand-side management (DSM) enhances distribution network efficiency by shifting or reducing loads, alleviating network stress. The Load Shifting Policy (LSP) reallocates flexible loads to low-price periods without altering total demand, while the Load Curtailing Policy (LCP) incentivizes consumers to reduce peak demand. This study introduces a hybrid DSM approach that combines LSP and LCP with a smart charging strategy for plug-in hybrid electric vehicles (PHEVs). Using the hybrid load shifting and curtailment policy (HLSCP), the microgrid (MG) load profile was optimized, reducing generation costs from 707¥ for the base load to 682¥ with HLSCP and 676¥ when incorporating smart PHEV charging. Emissions decreased correspondingly, from 1267kg to 1246kg. These results demonstrate the hybrid DSM's capacity to tackle economic and environmental challenges in power systems. The Differential Evolution (DE) optimization method further validated the robustness and efficiency of this cost-effective, sustainable microgrid management approach.
- Klíčová slova
- Energy Resources, Energy engineering, Energy systems, Environmental policy,
- Publikační typ
- časopisecké články MeSH
OBJECTIVE: This study aimed to perform a systematic review and meta-analysis of stretched, erect, and flaccid penis length as well as circumference according to geographic WHO regions. METHODS: PubMed, Embase, Scopus, and Cochrane Library were searched for articles published until February 2024. Studies in which a healthcare professional evaluated the penis size were considered eligible. After assessing the risk of bias, a systematic review and meta-analyses were performed according to the Preferred Reporting Items for Systematic Review and Meta-analysis statement, and the outcomes were grouped based on the WHO regions. RESULTS: A total of 33 studies comprising 36 883 patients were included. The risk of bias in the included studies was moderate/low. A comprehensive systematic review was done and meta-analyses performed for flaccid length [n = 28 201, mean (SE) 9.22 (0.24) cm], stretched length [n = 20 814, mean (SE) 12.84 (0.32) cm], erect length [n = 5669, mean (SE) 13.84 (0.94) cm], flaccid circumference [n = 30 117, mean (SE) 9.10 (0.12) cm], and erect circumference [n = 5168, mean (SE) 11.91 (0.18) cm]. The mean length of the stretched penis was largest in Americans [14.47 (0.90) cm]. The mean length of the flaccid penis was the largest in the Americas [10.98 (0.064) cm]. The mean flaccid penile circumference was largest in Americans [n = 29 714, mean (SE) 10.00 (0.04) cm]. CONCLUSIONS: Penis sizes vary across WHO regions, suggesting the need to adjust standards according to geography to better understand councilmen and their partners. These data provide a framework for discussing body image expectations and therapeutic strategies in this sensitive and emotional subject matter.
- Klíčová slova
- Penis, circumference, length, world health organization,
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
