Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Tropical Marine Invertebrates: a Manual for Pacific Island Resource Managers

Although the Pacific Islands region is relatively free from the pressures of large-scale industrialised exploitation, marine biodiversity and species of importance for food security or commercialisation are under pressure from a combination of subsistence harvesting (where coastal populations are high), commercial fishing activity and coastal development. Although there are few documented cases of widespread collapses, a lack of understanding of the status of resources and the health of coastal systems is a recognised shortfall in the ability to manage stocks over time. Managing resources and habitat by way of day-to-day perceptions suffers from a constant shift in understanding with changing generations.
Enhancing Business Performance through Circular Economy: A Comprehensive Mathematical Model and Statistical Analysis

In today’s dynamic and competitive free market, businesses strive to gain a distinct competitive advantage, enabling them to seize opportunities and overcome potential threats. Achieving and sustaining superior performance has become a fundamental objective for companies. Accordingly, the main objective and contribution of this research is to delve into the profound impact of circular economy practices, which are known to foster sustainability and resource efficiency, on financial performance—an essential metric for evaluating a company’s success. Through the development of a proposed mathematical model, we simulate and quantify the influence of circular economy practices on financial outcomes, capturing the intricate relationship between the two. Employing state-of-the-art optimization methods and statistical analysis, our analysis reveals that the implementation of circular economy principles significantly impacts financial performance, contributing to 15.7% of its variance. Interestingly, production diversity, while critical for corporate governance, does not exert a statistically significant influence on financial performance. Notably, although production diversity remains a pivotal aspect of effective corporate governance, our analysis indicates that it does not wield a statistically significant impact on financial performance. Moreover, the combined synergy of circular economy practices and financial performance unveils a noteworthy 24.8% variance in overall company performance, underscoring the intricate interdependence of these pivotal elements. By harnessing state-of-the-art modeling techniques and meticulous analysis, this research yields profound insights into the intricate interplay between circular economy practices and financial performance. This illumination empowers businesses to discern potential pathways for harnessing competitive advantages and nurturing sustainable growth in the dynamic tapestry of today’s business landscape.
High Frequency Link Ripple Power Compensation Strategies for 1-ϕ Bidirectional AC-DC Matrix Converters

Inherent ripple power compensation required during the 1-φ operation of direct matrix converters needs to be addressed in order to improve their power density, reliability, cost effectiveness, etc. Existing solutions in literature are scarce; most of the papers relevant to matrix converters are implemented either at the low frequency AC side of the matrix converter or at the DC port side. Two circuits are described in this paper that perform active ripple power compensation of direct matrix converter based high frequency isolated bidirectional AC-DC converters while operating at the high frequency link of the converter. Relevant analysis is given to explain the working principle of the topologies, and simulation results for a 3.45 kW electric vehicle charger, with a 230 V (RMS) AC grid input, feeding a 400 V battery are presented to illustrate the findings.
Construction of New Urbanization and Economic Growth of Resource-Based Cities: Evidence from China

development of a resource-based city economy. Using data from prefecture-level cities between 2011 and 2017, this study employs a double difference approach to assess the impact of the new urbanization comprehensive pilot policy on the economic growth of resource-based cities. According to the research �ndings, the new urbanization construction has promoted the growth of GDP per capita in resource-based cities, and has passed the robustness test; heterogeneity analysis shows that the policy effect of new urbanization construction in resource-rich cities is stronger than the policy effect of new urbanization construction in resource-poor cities, and the policy effect in energy resource-based cities is signi�cant, but the policy effect of metal and other resource-based cities is not signi�cant. The policy effect of resource-based cities in the eastern and western regions is signi�cant, while that in the central regions is not signi�cant.
Design and Simulation of High-Bandwidth 4-DOF Fast Steering Mirror

The accuracy and stability of the laser are affected not only by the external environment, but also by laser structure, heat source, input source, etc., resulting in four-degree-of-freedom (4-DOF) fluctuation errors. To reduce the laser fluctuation errors and improve laser quality, this study proposes a high-bandwidth 4-DOF fast steering mirror (FSM) with double Porro prisms driven by a voice coil motor (VCM), and has the advantage of shorter optical path length, fewer elements, and easier set-up at different locations in laser beam stabilization. The proposed 4-DOF FSM is verified by using the finite element analysis software ANSYS and MATLAB/Simulink. The proposed 4-DOF FSM has the movement range of ±0.1 mm and ±5 mrad along X and Y axis, respectively; the open-loop bandwidths of translational part and rotational part are 111 Hz and 113 Hz, respectively; and the closed-loop bandwidths of translational part and rotational part are 371 Hz and 379 Hz, respectively.
Contextual Detection of Anomalies within Hyperspectral Images

Abstract : The majority of anomaly detectors in Hyperspectral Imaging use only the statistical aspects of the spectral readings in the image. These detectors fail to use the spatial context that is contained in the images. The use of this information can yield detectors that out perform their spatially myopic counterparts. To demonstrate this, we will use an independent component analysis based detector, autonomous global anomaly detector (AutoGAD), developed at AFIT augmented to account for the spatial context of the detected anomalies. Through the use of segmentation algorithms, the anomalies identified are formed into regions. The size and shape of these regions are then used to decide if the region is anomalous or not. A Bayesian Belief Network structure is used to update a posterior probability of the region being anomalous.
Structural Vibration Self-sensing Piezoelectric Device

This paper aims to harvest the wasted structural mechanical vibrations and convert them to functioning power to operate sensors in remote and inaccessible locations for structural health monitoring purposes. The proposed sensing device is a uniform simply supported composite-piezoelectric beam. The energy effectiveness of earthquake-induced structural vibrations is presented. The proposed sensor can be employed in structural health monitoring to transmit important information like earthquake-induced structural vibrations. The analytical modelling is presented based on Euler-Bernoulli’s theory. The analytical results are then numerically verified using FEM results. MATLAB is employed to simulate the analytical results and COMSOL multi-physics is employed to model and simulate numerically the proposed sensing device.
Variable Impedance Control for Force Tracking Based on PILCO in Uncertain Environment

Traditional impedance control is a simple and valid way for robot force tracking, but the uncertainty of the contact environment can seriously interfere with tracking accuracy. In this paper, we present a novel reinforcement learning variable impedance scheme based on PILCO algorithm, which trains a RBF policy network that dynamically adjusts the damping coefficient to compensate for environment uncertainty. Considering the randomness of environment and learning efficiency, a contact state transition model is established by Gaussian process regression, which can be used for state prediction and policy evaluation. The policy is then updated by a gradient-based approach. The simulation study indicates that our robot only takes 18 interactions with an unknown environment to learn an optimal variable impedance policy, which can be applied to various unknown contact environments and has better control accuracy than traditional methods.
Willingness to pay for agricultural mechanization services by smallholder farmers in Malawi

One of the main barriers to adopting smallholder agricultural mechanization in developing countries is the mismatch between the economies of scale of machines and farm size. Private sector‐led mechanization services hold a promise to address this challenge, but there is a lack of evidence on demand for smallholder mechanization services. This study estimates the farmers' willingness to pay for mechanization services using the double‐bounded contingent valuation method and data from 1512 households. Results show that, on average, farmers are willing to pay 11%, 33%, and 5% more than prevailing market rates for land preparation, maize shelling, and transportation services, respectively. The amounts farmers are willing to pay for the mechanization services vary by sex, age group, size of cultivated land, the value of farmer assets, market access, and agroecology. Men are willing to pay 26%, 25%, and 11% more than women for land preparation, maize shelling, and transportation services. Moreover, 40% of female and 90% of male farmers are willing to pay more than or equal to the prevailing market rate for land preparation services. The high demand for mechanization services among smallholder farmers points to the need for making the machinery available to rural communities through mechanization service providers or machinery hiring centers run by the private sector. The paper concludes by discussing the contextual factors and policy options for promoting smallholder mechanization in Malawi. [EconLit Citations: O33, Q11, Q13, Q16].
Cytokinin Promotes Jasmonic Acid Accumulation in the Control of Maize Leaf Growth

Plant organ growth results from the combined activity of cell division and cell expansion. The co-ordination of these two processes depends on the interplay between multiple hormones that determine the final organ size. Using the semidominant Hairy Sheath Frayed1 (Hsf1) maize mutant that hypersignals the perception of cytokinin (CK), we show that CK can reduce leaf size and growth rate by decreasing cell division. Linked to CK hypersignaling, the Hsf1 mutant has an increased jasmonic acid (JA) content, a hormone that can inhibit cell division. The treatment of wild-type seedlings with exogenous JA reduces maize leaf size and growth rate, while JA-deficient maize mutants have increased leaf size and growth rate. Expression analysis revealed the increased transcript accumulation of several JA pathway genes in the Hsf1 leaf growth zone. A transient treatment of growing wild-type maize shoots with exogenous CK also induced the expression of JA biosynthetic genes, although this effect was blocked by the co-treatment with cycloheximide. Together, our results suggest that CK can promote JA accumulation, possibly through the increased expression of specific JA pathway genes.
Effects of Different Cutting Stages and Additives on the Fermentation Quality and Microbial Community of Sudangrass (Sorghum sudanense Stapf.) Silages

(1) Background: Previous studies have indicated that ferulic acid esterase (FAE), cellulase and xylanase have synergistic effects in lignocellulose degradation, and the cutting stage has a major impact on silages. Whether these additives affect the silages at different cutting stages is unclear. (2) Methods: Sudangrass height at the tested cutting stages was 1.8 m (S1) and 2.0 m (S2). The silage from the two cutting stages was treated with FAE-producing Lactobacillus plantarum (LP), cellulase and xylanase (CX) and a combination of LP and CX (LP+CX) for 30 and 60 days. (3) Results: Compared with CK, adding LP+CX significantly decreased the pH and the content of neutral detergent fiber (NDF) and acidic detergent fiber (ADF) (p < 0.05) and increased the lactic acid (LA) concentration (p < 0.05), dry matter (DM) content and crude protein content. Adding LP+CX effectively degraded lignocellulose in sudangrass, and the NDF and ADF degradation rates at the two stages were all more than 30%. In comparison, cutting at the S2 stage led to a lower pH and higher LA and DM contents (p < 0.05). Additives and the cutting stage exerted a strong effect on the silage microbial community, and Firmicutes and Lactiplantibacillus became the most dominant bacterial phyla and genera, especially at the S2 stage. (4) Conclusions: The results suggest that FAE-producing L. plantarum, cellulase and xylanase had synergistic effects on sudangrass silages, especially at the S2 stage, and their use can thus serve as an efficient method for ensiling.
Overview of GaN HEMT technology for high frequency applications

GaN HEMT devices feature the advantages of high frequency, high efficiency, and high power density for power converters due to their excellent performances. At high frequencies, GaN is highly sensitive to parasitic parameters, which can lead to voltage and current overshoot, electromagnetic interference, additional power losses, and even device failure. These issues are very important for the power devices and the whole power conversion systems. However, there is a lack of a comprehensive and in-depth overview of GaN technology in high frequency applications. This paper focuses on the issues of driver circuit and power loop design, the parallel technology, the short-circuit protection technology, which is helpful for better use of GaN devices in high frequency applications.
Pathophysiology of Disseminated Intravascular Coagulation in Sepsis: A Clinically Focused Overview

Sepsis is a major global health problem that results from a dysregulated and uncontrolled host response to infection, causing organ failure. Despite effective anti-infective therapy and supportive treatments, the mortality rate of sepsis remains high. Approximately 30–80% of patients with sepsis may develop disseminated intravascular coagulation (DIC), which can double the mortality rate. There is currently no definitive treatment approach for sepsis, with etiologic treatment being the cornerstone of therapy for sepsis-associated DIC. Early detection, diagnosis, and treatment are critical factors that impact the prognosis of sepsis-related DIC. Over the past several decades, researchers have made continuous efforts to better understand the mechanisms of DIC in sepsis, as well as improve its quantitative diagnosis and treatment. This article aims to provide a comprehensive overview of the current understanding of sepsis-related DIC, focusing on common causes and diagnoses, with the goal of guiding healthcare providers in the care of patients with sepsis.
Prospection des hydrocarbures par une approche intégrée de pétrographie, géochimie et modélisation de la transformation de la matière organique : analyse et reconstitution de l'histoire thermique des Bassins Carbonifère Central des Asturies (Espagne) et Sabinas - Piedras Negras (Coahuila, Mexique)

Le Bassin Carbonifere Central des Asturies montre que les charbons ont ete formes dans un marecage avec un facies riche en vitrinite, une teneur en soufre et en cendres faible, un niveau phreatique haut et un climat humide. Le rang du charbon, la reflectance de la vitrinite et la teneur en matieres volatiles montrent une tendance N-S qui peut etre correlee avec les paleotemperatures calculees. Ces donnees suggerent l'influence de deux gradients thermiques. L'evolution des maceraux fut observee dans les residus solides. METAGAZ-1D fut utilise pour simuler la production des hydrocarbures. Le Bassin Sabinas - Piedras Negras montre une diminution du flux de chaleur mesure. Les epaisseurs des depots determines suggerent une evolution d'avant-pays pendant le Cretace tardif et le debut du Paleocene. L'histoire thermique simulee indiquerait une anomalie qui est liee aux corps intrusifs. Les horsts localises dans la partie est paraissent avoir controle la sedimentation et ont diminue les quantites des depots. La generation des hydrocarbures fut provoquee par l'enfouissement, et l'anomalie thermique n'a pas induit une augmentation de la production des hydrocarbures.
Segmentation of 2D-echocardiographic sequences using level-set constrained with shape and motion priors

The aim of this work is to propose an algorithm to segment and track the myocardium using the level-set formalism. The myocardium is first approximated by a geometric model (hyperquadrics) which allows to handle asymetric shapes such as the myocardium while avoiding a learning step. This representation is then embedded into the level-set formalism as a shape prior for the joint segmentation of the endocardial and epicardial borders. This shape prior term is coupled with a local data attachment term and a thickness term that prevents both contours from merging. The algorithm is validated on a dataset of 80 images at end diastolic and end systolic phase with manual references from 3 cardiologists. In a second step, we propose to segment whole sequences using motion information. To this end, we apply a level conservation constraint on the implicit function associated to the level-set and express this contraint as an energy term in a variational framework. This energy is then added to the previously described algorithm in order to constrain the temporal evolution of the contour. Finally the algorithm is validated on 20 echocardiographic sequences with manual references of 2 experts (corresponding to approximately 1200 images).
Maternal Dietary Diversity and Small for Gestational Age: The Effect Modification by Pre-Pregnancy Body Mass Index and Gestational Weight Gain in a Prospective Study within Rural Sichuan, China (2021–2022)

Infants born small for gestational age (SGA) remains a significant global public health concern, with potential interconnections among maternal diet, pre-pregnancy BMI, gestational weight gain (GWG), and SGA. This prospective study investigated the association between dietary diversity (DD) during pregnancy and the risk of SGA, as well as the synergistic effect of DD with pre-pregnancy BMI and GWG on SGA. Maternal dietary intake during pregnancy was assessed using 24 h dietary recalls, and dietary diversity scores (DDS) were calculated based on the FAO’s Minimum Dietary Diversity for Women index. Infant information was followed up. The Poisson regression model was employed to determine the association between maternal DD and SGA. Interactions between DD and pre-pregnancy BMI or GWG were evaluated under additive and multiplicative models. Among the 560 singleton live births, 62 (11.07%) were classified as SGA. After adjusting for potential confounders, the DDS exhibited a protective effect against SGA (aRR: 0.76; 95% CI: 0.62–0.95). DD modified the association between being underweight prior to pregnancy and SGA on the additive scale (interaction contrast ratio = 7.39; 95% CI: 5.84, 8.94). These findings suggest that improving dietary diversity during pregnancy, particularly among women with a low pre-pregnancy BMI, may be a feasible strategy to reduce the risk of SGA newborns.
Development of Beta-Amyloid-Specific CAR-Tregs for the Treatment of Alzheimer’s Disease

Background: Alzheimer’s disease (AD) is a neurodegenerative disease that remains uncured. Its pathogenesis is characterized by the formation of β-amyloid (Aβ) plaques. The use of antigen-specific regulatory T cells (Tregs) through adoptive transfer has shown promise for the treatment of many inflammatory diseases, although the effectiveness of polyspecific Tregs is limited. Obtaining a sufficient number of antigen-specific Tregs from patients remains challenging. Aims and Methods: To address this problem, we used an antibody-like single-chain variable fragment from a phage library and subsequently generated a chimeric antigen receptor (CAR) targeting β-amyloid. Results: The β-amyloid-specific CARs obtained were stimulated by both recombinant and membrane-bound Aβ isolated from the murine brain. The generated CAR-Tregs showed a normal Treg phenotype, were antigen-specific activatable, and had suppressive capacity. Conclusion: This study highlights the potential of CAR technology to generate antigen-specific Tregs and presents novel approaches for developing functional CARs.
The Role of Social Network Analysis in Social Media Research

Previous studies regarding social interactions commonly adopt research methods that investigate causal relationships between variables. The existing approaches often utilize variables derived from general contexts, aiming to apply them universally across diverse situations. However, social interactions, including the usage of social media, are intricately woven within the immediate social context. The interpretability of these generalized variables has been attenuated by the dynamic and transient nature of social contexts; these variables have diverse impacts on social interactions. Consequently, researchers have been diligently seeking new variables relevant to specific social contexts in order to complement the existing generalized ones. However, the ever-changing nature of social contexts poses a challenge, impeding researchers from exhaustively defining all variables that influence social interactions. To address this complexity, this study proposes social network analysis as a suitable research method capable of capturing the ever-evolving dynamics of social interactions, including social media usage. Furthermore, this study puts forth hypotheses that specifically explore the role of individual social networks in social media research, with the aim of stimulating future investigations that center on the interactive and dynamic nature of social media usage.
A Study of Non-Isolated Resonant Step-Down Converter with Peak Charge Control for High Power Density

Non-isolated resonant converter with peak charge control for high power density is studied in this paper. Step-down converter is required for system on chip (SoC) operation. Buck converter is mainly used, and many studies have been conducted to improve power density by reducing the size of converter. Increasing the switching frequency of converter can contribute to the size reduction. Therefore, class D/E resonant converter suitable for high-frequency operation due to zero voltage switching (ZVS) is chosen as a step-down converter instead of conventional hard switching buck converter. Furthermore, the output capacitor ripple current-based peak charge control and adaptive voltage position (AVP) are simultaneously applied to the class D/E resonant converter. Based on this control method, the size of passive components can be further minimized. The operation of converter with peak charge control and AVP is shown by simulation. Finally, comparison of passive component values according to topology and control method is provided.