Explore the vast range of titles available.

Microgrids face significant challenges due to the unpredictability of distributed generation (DG) technologies and fluctuating load demands. These challenges result in complex power management systems characterised by voltage/frequency variations and intricate interactions with the utility grid. Model predictive control (MPC) has emerged as a powerful technique to effectively address these challenges. By applying a receding horizon control strategy, MPC offers promising solutions for optimising constraints and enhancing microgrid operations. The purpose of this review paper is to comprehensively analyse the application of MPC in microgrids, covering various levels of the hierarchical control structure. Furthermore, this paper explores the emerging trend of employing MPC across microgrid applications, ranging from converter control levels for power quality to overarching energy management systems. It also investigates the future research perspectives by considering the challenges associated with establishing MPC-based microgrid control. The key conclusion derived from this review paper is that the implementation of MPC techniques in microgrid operations can greatly improve their overall performance, efficiency, and resilience. This paper thoroughly examines the various challenges faced in MPC-based microgrid operations, underscoring the significance of conducting research in advanced artificial intelligence (AI)-based MPC methods. It highlights how these cutting-edge AI techniques can bring about economic benefits in microgrid operations, addressing the complex demands of efficient energy management in a rapidly evolving landscape. The presented insights strive to enhance the comprehension and adoption of MPC techniques in microgrid settings, actively contributing to the ongoing improvement of their operational processes. By shedding light on key aspects and offering valuable guidance, this work aims to propel the advancement and effective utilisation of MPC methodologies in microgrids, ultimately leading to optimised performance and enhanced overall operations.

This study focuses on assessing the role of various bank-specific, industry-specific and macroeconomic determinants in Indian commercial banks performance. Performance of the Indian banks has been measured by Return on Assets (ROA), Return on Equity (ROE) and Net Interest Margin (NIM) and Pre-provision profit ratio. The study analyses impact of various bank-specific factors like bank size, capital ratio, risk, cost to income ratio, funding cost, revenue diversification, labour productivity and bank age on bank performance. It also tries to assess the relationship between various bank-specific and industry-specific variables like bank concentration, inflation rate and GDP growth rate with bank performance. Fixed effects estimation model and Generalized Method of Moments (GMM) have been used on a panel data of 19 years for 64 commercial banks of India. The findings reveal that private sector banks are more profitable than the public sector banks. Additionally, the results of the study show that bank size, non-performing loan ratio and revenue diversification are the major determinants of the commercial banks performance in India. Furthermore, the results reveal that during the crisis period the impact of bank size, bank age, labour productivity and revenue diversification on the performance of the Indian banks is robust. The higher non-government stake leads to the enhanced performance of the commercial banks in India. The higher capital adequacy leads to the increase in the performance of the banks. The larger banks are less profitable. The results provide better insights about the determinants of Indian banks profitability.

In the era of Internet of things (IoT), network Connection of an enormous number of agriculture machines and service centers is an expectation. However, it will be with a generation of massive volume of data, thus overwhelming the network traffic and storage system especially when manufacturers give maintenance service typically by various data analytic applications on the cloud. The situation is more complex in the context of low latency applications such as health monitoring of agriculture machines, although require emergency responses. Performing the computational intelligence on edge devices is one of the best approaches in developing green communications and managing the blast of network traffic. Due to the increasing usage of smartphone applications, the edge computation on the smartphone can highly assist the network traffic management. In connection with the mentioned point, in the context of exploiting the limited computation power of smartphones, the design of an AI-based data analytic technique is a challenging task. On the other hand, the users’ need for economic technology makes it not to be easily pierced. This research work aims both targets by presenting a bi-level genetic algorithm approach of an optimized data analytic AI technique for monitoring the health of the agriculture vehicles which can be economically utilized on smartphone end-devices using the built-in microphones instead of expensive IoT sensors.

Type I mode, direct metastasis to the bronchus; Type II mode, bronchial invasion by parenchymal lesion; Type III mode, bronchial invasion by mediastinal or hilar lymph node metastasis; and Type IV mode, peripheral lesions extending along the proximal bronchus. [4] King and Castleman have reported that seven patients in their series of 109 patients with lung metastasis had only microscopic endobronchial involvement on the autopsy study. [8] Overall, a high degree of clinical suspicion and use of appropriate diagnostic techniques help in early identification of EBM which ultimately may lead to better treatment results and early palliation of distressing respiratory symptoms.

Agents are intelligent entities that act flexibly and autonomously and make wise decisions based on their intelligence and experience. A multi-agent system (MAS) contains multiple, intelligent, and interconnected collaborating agents for solving a problem beyond the ability of a single agent. A smart grid (SG) combines advanced intelligent systems, control techniques, and sensing methods with an existing utility power network. For controlling smart grids, various control systems with different architectures have already been developed. MAS-based control of power system operations has been shown to overcome the limitations of time required for analysis, relaying, and protection; transmission switching; communication protocols; and management of plant control. These systems provide an alternative for fast and accurate power network control. This paper provides a comprehensive overview of MASs used for the control of smart grids. The paper provides a wide-spectrum view of the status of smart grids, MAS-based control techniques and their implementation for the control of smart grids. Use of MASs in the control of various aspects of smart grids—including the management of energy, marketing energy, pricing, scheduling energy, reliability, network security, fault handling capability, communication between agents, SG-electrical vehicles, SG-building energy systems, and soft grids—have been critically reviewed. More than a hundred publications on the topic of MAS-based control of smart grids have been critically examined, classified, and arranged for fast reference.

Ixazomib, the first oral proteasome inhibitor, is approved in combination with lenalidomide and dexamethasone for the treatment of patients with multiple myeloma (MM) who have received at least one prior therapy. Ixazomib is a selective, potent, and reversible inhibitor of the 20S proteasome, and preferentially binds to and inhibits the β5 chymotrypsin-like proteolytic site. Ixazomib absorption is rapid, with a median time to reach maximum plasma concentration of approximately 1 h post-dose. Ixazomib pharmacokinetics (PK) are adequately described by a three-compartment model (terminal half-life of 9.5 days) with first-order linear absorption (oral bioavailability of 58%). Plasma exposures of ixazomib increase in a dose-proportional manner. A high-fat meal decreases both the rate and extent of ixazomib absorption, supporting administration on an empty stomach. Population PK analyses demonstrated that no dose adjustment is required based on age, body size/weight, race, sex, mild-to-moderate renal impairment, or mild hepatic impairment. Results from dedicated studies indicate that a reduced starting dose (from 4 to 3 mg) is appropriate for patients with severe renal impairment, end-stage renal disease requiring dialysis, or moderate-to-severe hepatic impairment. Non-cytochrome P450 (CYP)-mediated metabolism appears to be the major clearance mechanism for ixazomib. Drug–drug interaction studies have shown no meaningful effects of strong inhibitors of CYP3A on ixazomib PK; however, the strong inducer rifampin caused a clinically relevant reduction in ixazomib exposure, supporting the recommendation to avoid concomitant administration of ixazomib with strong CYP3A inducers. Exposure–response analyses of data from the phase III TOURMALINE-MM1 registrational study demonstrate a favorable benefit–risk profile for the approved dose and regimen of weekly ixazomib 4 mg on days 1, 8, and 15 of each 28-day cycle.

Background Psychotropic polypharmacy is common, increasing, and associated with higher risks of adverse effects, hospitalisations and mortality. This study aimed to explore the attitudes and beliefs of people receiving inpatient mental health care toward deprescribing ( discontinuing a medication when the current or potential risk outweighs the current or potential benefit ) and determine any patient characteristics associated with these attitudes and beliefs. Methods A cross-sectional survey of patients admitted to two open acute psychiatric inpatient units was conducted over a 6-month period in the Australian metropolitan city of Adelaide. Individuals were eligible to participate regardless of their reason for admission, if they were at least 18 years old and able to converse, read and write in English, and provide informed consent. Participant characteristics and responses to the validated revised Patients’ Attitudes Towards Deprescribing (rPATD) questionnaire were collected. The rPATD includes questions grouped into four factors: (i) perceived burden of medications, (ii) involvement in medication management, (iii) belief in appropriateness of medications, and (iv) concerns about stopping, plus two global questions. Participants were encouraged to think about medications that they use for their mental health conditions when completing the questionnaire. Results One hundred participants were recruited, with a mean age of 41.6 (SD = 13.7). 65% of participants agreed that they would be willing to stop one or more of their psychotropic medications if their doctor said it was possible. In a binary logistic regression model, willingness to have a medication deprescribed was mostly strongly predicted by Involvement factor score (odds ratio [OR] = 5.92, 95% confidence interval [CI] = 2.10-15-16.70, p  < 0.001). Conclusions A majority of participants were open to having one or more medication deprescribed. When medically justified, mental health professionals should feel comfortable initiating conversations about deprescribing to understand patient attitudes and preferences, fostering shared decision-making for psychotropic medication management. Clinical trial number Not applicable.

The combination of bortezomib, lenalidomide, and dexamethasone is a highly effective therapy for newly diagnosed multiple myeloma. Ixazomib is an investigational, oral, proteasome inhibitor with promising anti-myeloma effects and low rates of peripheral neuropathy. In a phase 1/2 trial we aimed to assess the safety, tolerability, and activity of ixazomib in combination with lenalidomide and dexamethasone in newly diagnosed multiple myeloma. We enrolled patients newly diagnosed with multiple myeloma aged 18 years or older with measurable disease, Eastern Cooperative Oncology Group performance status 0–2, and no grade 2 or higher peripheral neuropathy, and treated them with oral ixazomib (days 1, 8, 15) plus lenalidomide 25 mg (days 1–21) and dexamethasone 40 mg (days 1, 8, 15, 22) for up to 12 28-day cycles, followed by maintenance therapy with ixazomib alone. In phase 1, we gave patients escalating doses of ixazomib (1·68–3·95 mg/m2) to establish the recommended dose for phase 2. The primary endpoints were maximum tolerated dose for phase 1, and the rate of very good partial response or better for phase 2. Safety analyses were done in all patients who received at least one dose of study drug; efficacy analyses were done in all patients who received at least one dose of study drug at the phase 2 dose, had measurable disease at baseline, and had at least one post-baseline response assessment. This study is registered at ClinicalTrials.gov, number NCT01217957. Between Nov 22, 2010, and Feb 28, 2012, we enrolled 65 patients (15 to phase 1 and 50 to phase 2). Four dose-limiting toxic events were noted in phase 1: one at a dose of ixazomib of 2·97 mg/m2 and three at 3·95 mg/m2. The maximum tolerated dose of ixazomib was established as 2·97 mg/m2 and the recommended phase 2 dose was 2·23 mg/m2, which was converted to a 4·0 mg fixed dose based on population pharmacokinetic results. Grade 3 or higher adverse events related to any drug were reported in 41 (63%) patients, including skin and subcutaneous tissue disorders (11 patients, 17%), neutropenia (eight patients, 12%), and thrombocytopenia (five patients, 8%); drug-related peripheral neuropathy of grade 3 or higher occurred in four (6%) patients. Five patients discontinued because of adverse events. In 64 response-evaluable patients, 37 (58%, 95% CI 45–70) had a very good partial response or better. The all-oral combination of weekly ixazomib plus lenalidomide and dexamethasone was generally well tolerated and appeared active in newly diagnosed multiple myeloma. These results support the phase 3 trial development of this combination for multiple myeloma. Millennium Pharmaceuticals, a wholly owned subsidiary of Takeda Pharmaceutical International Company.

Transactive energy is a highly effective technique for peers to exchange and trade energy resources. Several interconnected blocks, such as generation businesses, prosumers, the energy market, energy service providers, transmission and distribution networks, and so on, make up a transactive energy framework. By incorporating the prosumers concept and digitalization into energy systems at the transmission and distribution levels, transactive energy systems have the exciting potential to reduce transmission losses, lower electric infrastructure costs, increase reliability, increase local energy use, and lower customers’ electricity bills at the transmission and distribution levels. This article provides a state-of-the-art review of transactive energy concepts, primary drivers, architecture, the energy market, control and management, network management, new technologies, and the flexibility of the power system, which will help researchers comprehend the various concepts involved.