Assessing rice (Oryza sativa L.) quality: A comprehensive review of current techniques and future directions

Rice (Oryza sativa L.) grain quality (RGQ) is a multifaceted trait influenced by various factors, including milling quality, appearance, sensory and nutritional properties, and hygiene. As the demand for high-quality rice increases globally, understanding the genetic factors contributing to rice quality is crucial for breeders and seed companies to meet consumer demands. Genetic studies have identified numerous genes and quantitative trait loci (QTLs) associated with grain quality, although these traits are complex. Grain size, shape, and weight are important factors that influence rice yield and market value. Accurate measurement of RGQ parameters is essential for successful rice breeding. The availability of the entire rice genome sequence and annotation has provided valuable insights into the genetic control of rice phenotypes. Consumer preferences, cultural differences, and market demands shape the demand for high-quality rice, with different regions favoring specific grain characteristics. This review article provides a comprehensive overview of the current developments and prospects of RGQ assessment methods and determination tools. Additionally, this article focuses on elite genes and their applications in breeding practices to quickly develop superior-quality rice varieties that meet various consumer demands. Future research should focus on enhancing grain quality traits through genetic improvement and developing nutrient-dense rice varieties to address malnutrition and value addition in rice breeding programs

Design of dual loop controller for boost converter based on PI controller

Boost converters are widely used in industry for many applications, such as electrical vehicles, wind energy systems, and photovoltaic energy systems, to step up the low voltages. Using the topology structure of the DC–DC boost circuit, this paper studied and designed a dual loop control method based on proportional integral controllers for improving the converter efficiency. The inner loop and outer loop controls of the traditional boost circuit are adopted in MATLAB/Simulink software to make the output of the system more stable. The input voltage is set to 24 V DC, and the desired output voltage varies from 36 to 48 V. Through simulation verification, the influence of a 1 kW sudden load connection by using a switch at a nominal output voltage of 48 V DC is studied, and the results show that it reduces the transient output voltage dips during the sudden load connection. Simulation analysis verifies the design scheme of the system, reduces the fluctuation in output voltage and power, reduces the output current ripple, minimizes the dip in voltage to a minimum possible value, and improves the dynamic characteristics and overall efficiency of the converter

Prognostic factors, oncological treatment and outcomes of uterine sarcoma: 10 years’ clinical experience from a tertiary care center in Pakistan

Abstract Background Uterine sarcoma is an uncommon aggressive malignancy. Optimal management and prognostic factors have yet to be well recognized due to their rarity and various histological subtypes. This study aims to investigate these patients' prognostic factors, treatment modalities, and oncological outcomes. Methods A single-center retrospective cohort study was conducted on all patients diagnosed with uterine sarcoma and treated from January 2010 to December 2019 in a tertiary-care hospital in Pakistan. The data were analyzed using STATA software and stratified on the histological subtype. Survival rates were estimated using the Kaplan–Meier method. Crude and adjusted hazard ratios with 95% CI were estimated using univariate and multivariate analysis. Results Of the 40 patients, 16(40%) had uterine leiomyosarcoma (u-LMS), 10(25%) had high-grade endometrial stromal sarcoma (HGESS), 8(20%) had low-grade endometrial stromal sarcoma (LGESS) and 6(15%) had other histological subtypes. The median age of all patients was 49 (40–55.5). Thirty-seven (92.5%) patients underwent primary surgical resection, and 24 (60%) patients received adjuvant systemic chemotherapy. The survival plots showed the overall population's DFS of 64 months and the OS of 88 months (p-value = 0.001). The median DFS in all patients was 12 months, and the median OS was 14 months (p-value = 0.001). A small but significant DFS benefit was found in patients who received adjuvant systemic chemotherapy, 13.5 versus 11 months (p-value = 0.001). Multivariate Cox-regression analysis revealed that large tumor size and advanced FIGO stage were substantial factors associated with decreased survival. Conclusion Uterine sarcomas are rare malignancies with poor prognosis. Multiple factors, including tumor size, mitotic count, stage of the disease, and myometrial invasion, impact survival outcomes. Adjuvant treatment may decrease the recurrence rate and improve DFS but do not affect OS

A review on gasification and pyrolysis of waste plastics

Gasification and pyrolysis are thermal processes for converting carbonaceous substances into tar, ash, coke, char, and gas. Pyrolysis produces products such as char, tar, and gas, while gasification transforms carbon-containing products (e.g., the products from pyrolysis) into a primarily gaseous product. The composition of the products and their relative quantities are highly dependent on the configuration of the overall process and on the input fuel. Although in gasification, pyrolysis processes also occur in many cases (yet prior to the gasification processes), gasification is a common description for the overall technology. Pyrolysis, on the other hand, can be used without going through the gasification process. The current study evaluates the most common waste plastics valorization routes for producing gaseous and liquid products, as well as the key process specifications that affected the end final products. The reactor type, temperatures, residence time, pressure, the fluidizing gas type, the flow rate, and catalysts were all investigated in this study. Pyrolysis and waste gasification, on the other hand, are expected to become more common in the future. One explanation for this is that public opinion on the incineration of waste in some countries is a main impediment to the development of new incineration capacity. However, an exceptional capability of gasification and pyrolysis over incineration to conserve waste chemical energy is also essential

Energy efficient indoor localisation for narrowband internet of things

Abstract There are an increasing number of Narrow Band IoT devices being manufactured as the technology behind them develops quickly. The high co‐channel interference and signal attenuation seen in edge Narrow Band IoT devices make it challenging to guarantee the service quality of these devices. To maximise the data rate fairness of Narrow Band IoT devices, a multi‐dimensional indoor localisation model is devised, consisting of transmission power, data scheduling, and time slot scheduling, based on a network model that employs non‐orthogonal multiple access via a relay. Based on this network model, the optimisation goal of Narrow Band IoT device data rate ratio fairness is first established by the authors, while taking into account the Narrow Band IoT network: The multi‐dimensional indoor localisation optimisation model of equipment tends to minimize data rate, energy constraints and EH relay energy and data buffer constraints, data scheduling and time slot scheduling. As a result, each Narrow Band IoT device's data rate needs are met while the network's overall performance is optimised. We investigate the model's potential for convex optimisation and offer an algorithm for optimising the distribution of multiple resources using the KKT criterion. The current work primarily considers the NOMA Narrow Band IoT network under a single EH relay. However, the growth of Narrow Band IoT devices also leads to a rise in co‐channel interference, which impacts NOMA's performance enhancement. Through simulation, the proposed approach is successfully shown. These improvements have boosted the network's energy efficiency by 44.1%, data rate proportional fairness by 11.9%, and spectrum efficiency by 55.4%

DataSheet1_Self-adaptive heat extraction controller for solar thermal tower operational with molten salt tanks.pdf

Molten salts are commonly used in solar thermal power plants to store heat when sunlight is unavailable. However, solidifying the salts can lead to operational interruptions and prevent an optimal energy output. A self-adaptive heat extraction method has been proposed to regulate salt pipeline temperatures, enabling continuous operations that mitigate unplanned shut-downs. Such a method focuses on maintaining operational temperatures and preventing interferences caused by the freezing of the salts. The proposed Self-Adaptive Heat Extraction Controller (SAHEC) relies on fuzzy logic integrated into MATLAB Simulink to ensure optimal heat extraction control utilizing four distinct temperature variables. Modeling this approach through a created MATLAB-based simulation reveals that SAHEC offers an undeniable improvement over standard conventional methods for manipulating temperatures.</p