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Enhancing catch-based stock assessment in data-limited fisheries with proxy CPUE indicators in the Yellow Sea
Roles of basic amino acid residues in substrate binding and transport of the light-driven anion pump Synechocystis halorhodopsin (SyHR)
Enhancing rapid nitrogen freezer performance for Litchi fruit: a Taguchi-based approach to reduce cracking, time, and nitrogen consumption
Abstract This study employed the Taguchi technique to investigate the influence of various liquid nitrogen quick-freezing parameters on litchi fruit cracking, nitrogen consumption, and freezing time. The experiments included testing different freezing temperatures (− 40, − 50, − 60, and − 70 °C), two types of nitrogen spraying nozzles (Hollow-cone and Full-cone), and two fan speeds (800 and 1200 rpm). Before freezing, the litchis were soaked in a solution and precooled as a pre-treatment to mitigate peel cracking and preserve quality. The results revealed that the crack ratio, freezing time, and nitrogen consumption decreased as temperature and fan speed increased. Among the nozzle types, Full-cone nozzles exhibited superior performance, achieving reductions of more than 15% in crack ratio, over 8% in freezing time, and more than 4% in nitrogen consumption compared to Hollow-cone nozzles. The predicted values derived from the Taguchi method showed strong alignment with the experimental data, validating the robustness of the optimization approach. This study contributes novel insights to the field of food freezing technology by introducing an innovative method for minimizing fruit cracking during freezing without the need for packaging. The findings also highlight the potential for reducing freezing time, operational costs, and nitrogen usage, offering practical implications for the food processing industry.
Molecular dissection of tendon development and healing: Insights into tenogenic phenotypes and functions
Enterprise modelling for decision-making in the software ecosystem
Abstract Even with the availability of modelling languages such as 4EM and ArchiMate, a noticeable uncertainty persists among professionals regarding the efficient development of process models in the software ecosystem. While current enterprise modelling frameworks and guidelines provide valuable perspectives on essential quality aspects, they are usually more abstract to apply in real-world scenarios directly. This study compares the features of 4EM and ArchiMate, underlining their distinct characteristics for a specific context of software outsourcing. Further, this paper demonstrates a choice of appropriate views of these two modelling languages to model a decision-making scenario for software vendor analysis and selection. Thus, this research supports software enterprises to understand their business processes related explicitly to outsourcing and benefits company personnel involved in decision-making. In addition to model development, 4EM and ArchiMate are tested for the extent they fit for modelling the given decision-making context in the software ecosystem. It is observed that ArchiMate is better suited to the given context. Afterwards, the models are validated using the SEQUAL framework which resulted in identification and incorporation of a new process activity in ‘As-Is’ scenario. This further provided means for digital innovation for ‘To-Be’ scenario of enterprise business process. However, the models developed in this study are premature since they are validated with a theoretical framework only, and the involvement of experts is limited. Thus, more validation studies are required in actual settings with more experts to improve the models further.
Dissecting the mechanism of NOP56 GGCCUG repeat-associated non-AUG translation using cell-free translation systems
A damage zone detection method in concrete hydraulic structures based on multi-frequency ultrasonic characteristics
The 2-methylcitrate cycle and the glyoxylate shunt in Pseudomonas aeruginosa are linked through enzymatic redundancy
Jellyfish shape as a mechanical balance
Why are jellyfish round? Animals get their shapes as they develop. After development, however, how animals keep their shapes is less understood. Moon jellies respond to perturbations to body shape, such as being halved or quartered, by reorganizing existing body parts and regaining radial symmetry, i.e., their round shape. The robust recovery of radial symmetry led us to investigate, in this study, how being round is encoded. We tested perturbing shape by grafting body sections in varying configurations. Testing these perturbations confirms the moon jellies’ ability to recover their round shape from many perturbations. However, in response to some perturbations, the jellies can also adopt other stable body shapes, such as oval, quadrilateral, and triangular. Thus, although the jellies are characterized by a radially symmetrical body plan, perturbations can lead to them recovering to bilateral shapes. Employing mathematical modeling, we find that interactions between forces from muscle contractions and viscoelastic tissues can explain the recovery to different shapes. A stable body shape is achieved when the mechanical forces are locally balanced, regardless of symmetry. Consistent with the model prediction that stable shape is the outcome of balancing mechanical forces, modulating the mechanical parameter in the system, i.e., the muscle contraction rate, can produce shape-shifting. Maintaining shapes dynamically as the balance of mechanical forces may enable the animals to readily adapt to changing physical environments.
Predicting the chemical equilibrium point of reacting components in gaseous mixtures through a novel Hierarchical Manta-Ray Foraging Optimization Algorithm
Abstract This study proposes a Hierarchical Manta-Ray Foraging Optimization (HMRFO) algorithm for calculating the equilibrium points of chemical reactions. To improve the solution diversity in the trial Manta-Ray population and enhance the general optimization effectivity of the algorithm, an ordered hierarchy is integrated into the original algorithm, taking into account the efficient search strategies of Elite-Opposition learning, Dynamic Opposition Learning, and Quantum search operator. Within this proposed concept, the Manta-ray population is divided into three main sub-populations: the Elite Oppositional learning scheme manipulates top elite individuals, Dynamic Oppositional learning search equations update average population members, and quantum-based learning equations process the worst members. The improved MRFO is applied to a hundred 30D and 500D optimization benchmark functions, and results have been compared to those obtained from state-of-art metaheuristic optimizers. Then, the proposed optimizer solved twenty-eight test problems previously employed in CEC-2013 competitions, and corresponding results were benchmarked against well-reputed metaheuristics. This research study also suggests a novel mathematical model for solving chemical equilibrium problems for ideal gas mixtures. Four challenging case studies related to chemical equilibrium problems have been performed by the HMRFO for varying test conditions, and it is observed that HMRFO can effectively cope with the tedious nonlinearities and complexities of the governing thermodynamic models associated with solving chemical equilibrium problems for gaseous reacting mixture components.
Functional dynamics of G protein-coupled receptors reveal new routes for drug discovery
Distinct neuronal vulnerability and metabolic dysfunctions are characteristic features of fast-progressing Alzheimer's patients with Lewy bodies
COVID-19 and neuropathy in type 2 diabetes
Abstract This study investigated the risk factors for COVID-19 and its impact on diabetic peripheral neuropathy (DPN) in patients with type 2 diabetes (T2D). Patients with T2D underwent assessments with the NICE post-COVID questionnaire, DN4 questionnaire, vibration perception threshold (VPT), and corneal confocal microscopy (CCM) before and 11.0 ± 8.9 months after developing COVID-19. Of 76 participants with T2D, 35 (46.1%) developed COVID-19, of whom 8 (22.9%) developed severe COVID-19 and 9 (25.7%) developed long-COVID. The development of COVID-19 was associated with lower systolic blood pressure (P < 0.05). The presence and severity of DPN were not associated with developing COVID-19, severe COVID-19, or long-COVID (P = 0.42–0.94). Women were eight times more likely to develop long-COVID (P < 0.05) and elevated body weight, LDL, and VPT were associated with the development of long-COVID (P < 0.05 − 0.01). The long-COVID group exhibited significant changes in triglycerides and LDL (P < 0.05 for both) and body weight (P < 0.01) at follow-up. Their impact on clinical and neuropathy measures was comparable in patients with and without COVID-19 (P = 0.08–0.99). There was a significant reduction in corneal nerve measures (P < 0.05-0.0001) in patients with and without COVID-19. A low systolic blood pressure, altered lipids, body weight, higher VPT, and gender may determine the impact of COVID-19 in patients with T2D, but there was no evidence of an impact of COVID-19 on the development or progression of DPN.