Browse Articles

Design of parallel cascade controller for nonlinear continuous stirred tank reactor

Abstract This work presents an approach to control the temperature of a nonlinear continuous stirred tank reactor (NCSTR) through parallel cascade control structure (PCCS). For the first time, PCCS is used to control the temperature of NCSTR by (1) modelling the dynamic behavior of CSTR with a recirculating jacket heat transfer system into a third order unstable transfer function and (2) using the model matching technique to synthesize the controller parameters. The controller of the secondary loop of PCCS is designed to achieve enhanced regulatory performance whereas, the primary loop controller is designed for better setpoint tracking. The closed loop performance of the proposed method is evaluated by carrying out simulation on the differential equation of the NCSTR and comparing it with other structures such as series cascade control structure (CCS) and parallel control structure (PCS). The response shows that the proposed method provides satisfactory performance in nominal, perturbed and noisy conditions.

A study of the purchase intention of alternative foods

Mortality rates in physician staffed ground vs. air ambulance for severe trauma patients: retrospective analysis of the Japanese nationwide trauma registry

Fine description of natural fractures in the tight sandstone reservoir of the Yanchang reservoirs in the southern Ordos Basin

PI3Kα-specific inhibitor BYL-719 synergizes with cisplatin in vitro in PIK3CA-mutated ovarian cancer cells

AquaYOLO: Advanced YOLO-based fish detection for optimized aquaculture pond monitoring

Abstract Aquaculture plays an important role in ensuring global food security, supporting economic growth, and protecting natural resources. However, traditional methods of monitoring aquatic environments are time-consuming and labor-intensive. To address this, there is growing interest in using computer vision for more efficient aqua monitoring. Fish detection is a key challenging step in these vision-based systems, as it faces challenges such as changing light conditions, varying water clarity, different types of vegetation, and dynamic backgrounds. To overcome these challenges, we introduce a new model called AquaYOLO, an optimized model specifically designed for aquaculture applications. The backbone of AquaYOLO employs CSP layers and enhanced convolutional operations to extract hierarchical features. The head enhances feature representation through upsampling, concatenation, and multi-scale fusion. The detection head uses a precise 40 × 40 scale for box regression and dropping the final C2f layer to ensure accurate localization. To test the AquaYOLO model, we utilize DePondFi dataset (Detection of Pond Fish) collected from aquaponds in South India. DePondFi dataset contains around 50k bounding box annotations across 8150 images. Proposed AquaYOLO model performs well, achieving a precision, recall and mAP@50 of 0.889, 0.848, and 0.909 respectively. Our model ensures efficient and affordable fish detection for small-scale aquaculture.

Hydrogen escaping from a pair of exoplanets smaller than Neptune

Quality of life and clinical data in hemodialysis patients with different degrees of pruritus

Morning sprint interval training produces greater physical performance adaptations than evening training in soccer players

A novel MRI contrast agent NaGdF4@PEG–CLS@MMP-13 NPs for detecting articular cartilage injury

Study on hydration mechanism and ratio optimization of slag powder modified high-water material

Author Correction: Sex disparities in outcomes among hospitalizations for heart failure

Gender-differences in imaging phenotypes of osteoarthritis in the osteoarthritis initiative

Abstract In osteoarthritis (OA) research it is increasingly recognized that stratification according to disease phenotypes is essential for optimizing treatment regimens. Gender-specific differences in clinical OA manifestations have been identified, and this analysis aimed to assess whether these differences extend to imaging phenotypes. From the Osteoarthritis Initiative database 2523 participants (1409 women and 1114 men) with completed 3T MRI and whole-organ magnetic resonance imaging scores (WORMS) of the right knee at baseline were included. Imaging phenotypes were assigned based on modified Rapid OsteoArthritis MRI Eligibility Score: the inflammatory, meniscus-cartilage, and bone phenotype. Logistic regression was performed to investigate the effect of gender on phenotype, independent of BMI, race, Kellgren & Lawrence (KL) grade and level of physical activity. Female gender was independently associated with lower odds for the meniscus-cartilage (OR 0.61, 95%CI 0.47–0.80, p < 0.001) but not for the inflammatory (OR 1.04, 95%CI 0.89–1.24, p = 0.697) or the subchondral bone phenotype (OR 1.13, 95%CI 0.95–1.36, p = 0.166). This difference highlights an opportunity for future refinements to better accommodate gender/sex differences in disease trajectories while investigating different treatment regimes in knee OA.

Factors affecting visual outcome in patients with toxic optic neuropathy caused by ethambutol

Gourmet cockatoos like to fancy up their food

Author Correction: Potential shared mechanisms in atopic dermatitis and type 2 diabetes identified via transcriptomic and machine learning approaches

Utilizing non-invasive biomarkers for early and accurate differentiation of uncomplicated and complicated acute appendicitis: a retrospective cohort analysis

METTL3 promotes the progression of non-alcoholic fatty liver disease by mediating m6A methylation of FAS

Reliability and validity of a self-developed virtual reality-based test battery for assessing motor skills in sports performance

Abstract Athletes must master various motor skills for success in their sports. To assess performance and identify areas of improvement, effective sports-motoric tests are essential. Key abilities such as reaction time, jumping, and complex movement coordination are critical. Virtual reality (VR) offers a practical, traditional equipment-free tool for assessment, though new VR-based tests must be evaluated first. We evaluated a self-developed test battery to measure reaction time (drop-bar test), jumping ability (jump and reach test), and parkour execution involving multiple complex motor tasks (with/without a virtual opponent). 32 participants completed these tests twice in real environment (RE) and VR (pre- and post-test). Intraclass correlation coefficients showed high reliability for reaction time in RE (0.858) and VR (0.888), with moderate significant correlations between them (r = .445), suggesting validity. The jump and reach test showed even better reliability (RE: 0.944, VR: 0.886) with strong correlations between RE and VR (r = .838). The parkour test showed lower reliability (x̄ 0.770), particularly for one task, with significant differences between the conditions indicating different behavior in VR. However, the addition of a virtual opponent eliminated these differences. VR appears to be a promising alternative to traditional testing methods, revealing comparable values across conditions.

Enabling solid sample analysis in liquid spectrophotometers with a 3D-printed cuvette

Abstract Most commercial systems for ultraviolet-visible (UV–VIS), Fourier-transform infrared, circular dichroism (CD), and fluorescence spectroscopies are designed for measurement of liquid samples. Moreover, adapters enabling the measurement of solid samples are expensive or unavailable for most commercial instruments. Consequently, there is a significant need for solid sample adapters that enable measurement of both liquid and solid samples with a single system. Here, we report two versions of a solid sample adapter cuvette that can be used in most commercial spectroscopy instruments designed for transmission measurement of liquid samples. One version is designed for techniques that do not require changing the sample orientation, and the other allows easy sample rotation. We successfully fabricated these cuvettes by 3D printing with both fused deposition modeling and stereolithography and demonstrated how they enable us to study the optical properties of macroscopic films of aligned carbon nanotubes by performing UV–VIS and CD spectroscopy measurements with the cuvettes. These 3D printed cuvettes and their implementation will help enable a wide range of experiments at a low cost.