Miracle-dz/UniFAR-FTUs huggingface dataset:
P-CSEM: An Attention Module for Improved Laparoscopic Surgical Tool Detection

Minimal invasive surgery, more specifically laparoscopic surgery, is an active topic in the field of research. The collaboration between surgeons and new technologies aims to improve operation procedures as well as to ensure the safety of patients. An integral part of operating rooms modernization is the real-time communication between the surgeon and the data gathered using the numerous devices during surgery. A fundamental tool that can aid surgeons during laparoscopic surgery is the recognition of the different phases during an operation. Current research has shown a correlation between the surgical tools utilized and the present phase of surgery. To this end, a robust surgical tool classifier is desired for optimal performance. In this paper, a deep learning framework embedded with a custom attention module, the P-CSEM, has been proposed to refine the spatial features for surgical tool classification in laparoscopic surgery videos. This approach utilizes convolutional neural networks (CNNs) integrated with P-CSEM attention modules at different levels of the architecture for improved feature refinement. The model was trained and tested on the popular, publicly available Cholec80 database. Results showed that the attention integrated model achieved a mean average precision of 93.14%, and visualizations revealed the ability of the model to adhere more towards features of tool relevance. The proposed approach displays the benefits of integrating attention modules into surgical tool classification models for a more robust and precise detection.
Modelling extreme rain accumulation with an application to the 2011 Lake Champlain flood

A simple strategy is proposed to model total accumulation in non‐overlapping clusters of extreme values from a stationary series of daily precipitation. Assuming that each cluster contains at least one value above a high threshold, the cluster sum S is expressed as the ratio S=M/P of the cluster maximum M and a random scaling factor P ∈ (0,1]. The joint distribution for the pair (M,P) is then specified by coupling marginal distributions for M and P with a copula. Although the excess distribution of M is well approximated by a generalized Pareto distribution, it is argued that, conditionally on P<1, a scaled beta distribution may already be sufficiently rich to capture the behaviour of P. An appropriate copula for the pair (M,P) can also be selected by standard rank‐based techniques. This approach is used to analyse rainfall data from Burlington, Vermont, and to estimate the return period of the spring 2011 precipitation accumulation which was a key factor in that year's devastating flood in the Richelieu Valley Basin in Québec, Canada.
Citizen science can add value to Phytophthora monitoring: five case studies from western North America

Phytophthora species are plant pathogens responsible for many notable biological invasions in agricultural, forests, and natural ecosystems. Detection and monitoring for invasive introductions of Phytophthora spp. is time and resource intensive. Development of citizen science detection and monitoring programs can aid in these efforts focused on reducing Phythophthora impacts. There are multiple methods for monitoring and detecting Phytophthora invasions suitable for citizen science approaches such as, leaf sampling, stream baiting or soil collections. Here we summarize five active projects in western North America where citizen scientists are aiding the monitoring and research efforts surrounding Phytophthora species and their impacts. Projects varied in scope, scale, methods, and capacity, but each project increased citizen scientists’ abilities for surveillance and advanced detection or knowledge of Phytophthora species. Some projects were integrated with school programs, others involved hands-on training with small groups, and another approach invited mass participation from interested citizens. Overall, all projects had positive outcomes multiplied across education, monitoring, and research. Together these case studies demonstrate how citizen scientists can amplify surveillance efforts, advance baseline knowledge, and reduce the impacts of biological invasions.
Multi-Optimization of Novel Conditioned Adaptive Barrier Function Integral Terminal SMC for Trajectory Tracking of a Quadcopter System

Researchers in the domain of unmanned aerial vehicles (UAVs) have recently shown a great deal of interest in the quadcopter domain due to its wide variety of applications. In addition to their military applications, quadcopters are now widely used in the civilian sector. This paper presents optimized controllers for attitude and altitude control of a quadcopter system. A novel conditioned adaptive barrier function integral terminal sliding mode controller (CABFIT-SMC) is designed to address the trajectory tracking problem of the quadcopter, and a sliding mode control (SMC) is implemented for comparative analysis. Four optimization algorithms (i.e., Ant Colony Optimization, Artificial Bee Colony, Particle Swarm Optimization, and Genetic Algorithm) have been used to optimize the proposed control laws. The quadcopter’s non-linear model is formulated through the Lagrange formalism in MATLAB ODE-45, incorporating gyroscopic moments and aerodynamic effects. A Lyapunov stability analysis is carried out to verify the system’s asymptotic stability. A graphical and tabular comparative analysis is provided for all optimized control laws. Five performance indexes, including mean absolute percentage error, root mean square error, integral square error, integral absolute error, and integral time absolute error, are used to determine the best control law. The proposed optimized controllers are evaluated for performance and consistency using a 3D-helical complex trajectory. Based on the rigorous performance evaluation, it has been demonstrated that the CABFIT-SMC controller optimized with the ABC algorithm achieved the most superior results, with the lowest MAPE value of 13.245, RMSE value of 0.0043, and transient response characteristics yielding the quickest rise and settling times. The commendable performance of the ABC-optimized CABFIT-SMC further reinforces its potential as a robust controller for precise attitude, altitude, heading, and position tracking in quadcopter systems.
Plasma Amino Acids in NAFLD Patients with Obesity Are Associated with Steatosis and Fibrosis: Results from the MAST4HEALTH Study

Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) have been linked to changes in amino acid (AA) levels. The objective of the current study was to examine the relationship between MRI parameters that reflect inflammation and fibrosis and plasma AA concentrations in NAFLD patients. Plasma AA levels of 97 NAFLD patients from the MAST4HEALTH study were quantified with liquid chromatography. Medical, anthropometric and lifestyle characteristics were collected and biochemical parameters, as well as inflammatory and oxidative stress biomarkers, were measured. In total, subjects with a higher MRI-proton density fat fraction (MRI-PDFF) exhibited higher plasma AA levels compared to subjects with lower PDFF. The concentrations of BCAAs (p-Value: 0.03), AAAs (p-Value: 0.039), L-valine (p-Value: 0.029), L-tyrosine (p-Value: 0.039) and L-isoleucine (p-Value: 0.032) were found to be significantly higher in the higher PDFF group compared to lower group. Plasma AA levels varied according to MRI-PDFF. Significant associations were also demonstrated between AAs and MRI-PDFF and MRI-cT1, showing the potential utility of circulating AAs as diagnostic markers of NAFLD.
THE ABILITY OF Lactiplantibacillus plantarum TSD-10 AND DR-162 TO REDUCE AFLATOXIN AND MICROBIAL CONTAMINATION OF CORN

Feed safety becoming the main factor to produce good quality food. The purpose of this study was to evaluate the ability of lactic acid bacteria in degrading aflatoxin B1, suppressing the growth of contaminant bacteria, and its application on feed. Biological degradation of aflatoxin B1 (AFB1) in liquid cultures and Escherichia coli and Saccharomyces aureus inhibition by Lactobacillus plantarum were examined. Fermentation of corn for 24 hours by L. plantarum was used to determine the ability of LAB to decrease E. coli, coliform, mold, and AFB1 on a solid substrate. This study showed that both L. plantarum TSD-10 and DR-162 could inhibit E. coli growth at 3% and 5% supernatant addition. The addition of 5% L. plantarum DR-162 and TSD-10 could inhibit S. aureus at 97.40% and 97.28%, respectively. Furthermore, viable cells of L. plantarum DR-162 and TSD-10 removed 56.97% and 64.65% AFB1 within 72 h of incubation, respectively. The AFB1 reduction by nonviable cell was lower than the viable cell. The population of E. coli, coliform, and mold completely disappeared in both fermentation treatment of corn by L. plantarum DR-162 and TSD-10 at 3% and 5%. AFB1 significantly decreased by 17.57% and 22.60% on 5% L. plantarum DR-162 and TSD-10 treatment.
Level I Fieldwork: Could Simulation be the Answer? A Descriptive Study

Abstract This article describes the creation and outcomes of simulation as Level I Fieldwork for entry level graduate occupational therapy students. The simulations were created by a team of interprofessional educators following the International Nursing Association for Clinical Simulation and Learning best practices. Additionally, the simulations were designed to meet the student learning outcomes of Level I Fieldwork. Students participated in eight high-fidelity simulations and were evaluated with self-ratings, peer ratings, and faculty ratings. Each student completed a student evaluation of the fieldwork experience, with rating scales and open-ended questions to understand student perceptions of the experience. The vast majority of students met or exceeded expectations on all rating scales. Faculty ratings on student performance were consistently higher than peer ratings and self-ratings. Student perceptions of their experiences were mostly positive, and the majority of students reported meeting the student learning outcomes. The results of this study indicate that Level I Fieldwork with well-designed simulation can result in positive student perceptions, achievement of student learning outcomes, and a consistent student experience.
Osmolytes Modulate Photoactivation of Phytochrome: Probing Protein Hydration

Phytochromes are bistable red/far-red light-responsive photoreceptor proteins found in plants, fungi, and bacteria. Light-activation of the prototypical phytochrome Cph1 from the cyanobacterium Synechocystis sp. PCC 6803 allows photoisomerization of the bilin chromophore in the photosensory module and a subsequent series of intermediate states leading from the red absorbing Pr to the far-red-absorbing Pfr state. We show here via osmotic and hydrostatic pressure-based measurements that hydration of the photoreceptor modulates the photoconversion kinetics in a controlled manner. While small osmolytes like sucrose accelerate Pfr formation, large polymer osmolytes like PEG 4000 delay the formation of Pfr. Thus, we hypothesize that an influx of mobile water into the photosensory domain is necessary for proceeding to the Pfr state. We suggest that protein hydration changes are a molecular event that occurs during photoconversion to Pfr, in addition to light activation, ultrafast electric field changes, photoisomerization, proton release and uptake, and the major conformational change leading to signal transmission, or simultaneously with one of these events. Moreover, we discuss this finding in light of the use of Cph1-PGP as a hydration sensor, e.g., for the characterization of novel hydrogel biomaterials.
Confidence in dementia care and care approach toward dementia among the nursing staff in long-term care facilities in China: a cross-sectional survey

Background Confidence and appropriate care approach toward dementia among nursing staff (nurses and care assistants) are crucial manifestations of competency to deal with the complexity of dementia care in long-term care facilities (LTCFs). The purpose of this study was to investigate the confidence in dementia care and care approach among nursing staff in LTCFs in mainland China. Methods A cross-sectional study design was utilized in LTCFs in Shandong Province, mainland China. A convenient sample included of 317 nursing staff drawn from 15 LTCFs. Survey questions included (a) demographics, (b) dementia knowledge, (c) dementia care confidence, and (d) approach to care for people with dementia. Data were analyzed with descriptive statistics. Factors associated with confidence and care approach for people with dementia were examined using Pearson’s correlation and multivariate regression analyses. Results Dementia care confidence was generally moderate. Factors affecting confidence to care for people with dementia included educational level, months of caring dementia patients, and dementia knowledge. Most nursing staff did not use a person-centered care approach which was significantly associated with their age, dementia-learning experience, and knowledge and confidence toward caring for people with dementia. Conclusion A positive correlation was identified between confidence to care for people with dementia and nursing staff care approach. Clinical recommendations are provided to further develop education strategies tailored for nursing staff to meet the growing demand for dementia care services.
Rewarding outcomes enhance attentional capture and delay attentional disengagement

Attentional capture and disengagement are distinct process involved in attentional orienting. Most current studies have examined either the process of attentional capture or disengagement by manipulating stimuli associated with either positive (gains) or negative outcomes (losses). However, few studies have investigated whether attentional capture and disengagement are modulated by reward and loss outcomes. In the current study, we want to examine whether positive or negative outcomes could modulate distinguishing process of attentional capture and disengagement. Here, we manipulated different colored singleton stimuli associated with reward or loss outcomes; these stimuli were either presented at the center of screen or at the peripheral location. The participants’ task was to search the target and identify the orientation of line segment in target as quickly as possible. The results showed that people had difficulty disengaging from a central reward-distractor, in comparison to loss- and neutral-distractor when target was presented at peripheral location. Similarly, peripheral reward-distractor captured more attention than loss- and neutral-distractor when target was presented at the center of screen after central fixation disappeared. Through our discoveries, we can conclude that positive rewards can increase attentional capture and delay attentional disengagement in healthy people.
Perceptions of Corporate Social Responsibility in a Post-Disaster Context: The Impact of CSR on Employee Trust and Identification

Corporate social responsibility (CSR) has become increasingly recognized for being a source of positive organizational outcomes. More specifically, CSR has been positively associated with employees experiencing higher levels of organizational trust and organizational identification. The purpose of this study was to examine the relationship among these variables in a post-disaster context – the aftermath of Hurricane Ida. In such conditions, employers’ CSR actions may be particularly salient to employees’ perceptions of and attitudes toward their organization. Based on a set of quantitative and qualitative survey data in a sample of South Louisiana employees, our study finds evidence that organizations’ CSR actions directed toward employees may be a stronger influence on employee trust and identification than actions taken to help the community. Implications for theory and practice and directions for future research are discussed.
Unilateral Multiple Evanescent White Dot Syndrome-Like Reaction Following the CyberKnife Stereotactic Radiotherapy for Choroidal Malignant Melanoma

A 58-year-old otherwise healthy man received a diagnosis of choroidal malignant melanoma (CMM) in June 2021 and underwent a single session of (21 Gy) CyberKnife stereotactic radiotherapy (SRT). Eleven months later, we noticed 3+ anterior chamber cells with occasional vitreous cells in the left eye. Though the tumor looked regressed, there were mild optic disc leakage, early hypofluorescent and late hyperfluorescent punctate lesions scattered 360 degrees, and late staining of the mass on fluorescein angiogram. The findings were compatible with a unilateral multiple evanescent white dot syndrome (MEWDS)-like reaction that was most likely related to CyberKnife SRT-induced tumor necrosis, and a dexamethasone implant was administered intravitreally into the left eye together with topical steroids. A second intravitreal injection of dexamethasone was given three months later due to remittance of the angiographic features. As there are only a few reports on CyberKnife SRT for the treatment of CMM, we wanted to share our interesting observation of a post-treatment MEWDS-like reaction likely related to tumor necrosis syndrome with the ophthalmic community.
Mapping and Candidate Gene Prediction of qPL7-25: A Panicle Length QTL in Dongxiang Wild Rice

Panicle length (PL) is an important trait closely related to rice yield. More than 200 quantitative trait loci (QTL) for PL have been identified, but only a few can be used for breeding. Dongxiang wild rice contains many excellent genes, and mining favorable PL-related QTL from DXWR is helpful for rice variety improvement. Here, we report a QTL analysis for PL using a recombinant inbred line population consisting of 143 individuals derived from a cross between Dongxiang wild rice and indica cultivar Guangluai 4. A total of four QTL (qPL1-37, qPL4-26, qPL7-25, and qPL8-4) for PL were identified and located on chromosomes 1, 4, 7, and 8. Among them, qPL7-25 showed the largest F-value of 32.32 and 16.80, and the QTL explained 18.66% and 13.06% of the phenotypic variation of Dongxiang wild rice in Hangzhou and Hainan, respectively. QTL mapping was performed using a population of 1800 individuals derived from the crossing of NIL-qPL7-25 and GLA4. qPL7-25 was located between two InDel markers, InDel-24591 and InDel-24710, in a 119 kb region containing 14 predicted genes. Using Sanger sequencing and qRT-PCR analysis, we propose that LOC_Os07g41200 is probably a new allele of the well-known GL7 gene, which affects grain length and appearance quality in rice. These results provide new insights into the use of molecular marker-assisted selection for breeding high-yielding and high-quality rice varieties.
Defence spending and economic growth: a case study of Greece and comparison with Spain and Portugal (1960-1996).

This thesis provides a case study of the economic effects of military expenditure in Greece and a comparison with two other similar countries. Portugal and Spain. Greece provides a particularly valuable focus for empirical investigation since tor many years it has been allocating a relatively high proportion of its national income to defence, much higher than other countries in NATO and EU. It is also situated in a complex geostrategic environment (the Balkans) and has many security concerns. in particular the confrontation with Turkey. At the same time. the Greek economy has gone through periods of high economic growth as well as periods of stagnation and has been the poorest member of the EU for the last two decades. Lick of a concensus on the economic effects of defence spending as well as the limited amount of research on the issue in newly industrialised economies intrigued the author and led to this research on whether high military expenditure has contributed to this poor economic performance. In this way the thesis contributes to an ongoing debate in the literature and provides a valuable additional case study. It provides a further contribution by comparing the results of the analysis for Greece with two similar economies, Spain and Portugal, giving insights into the transferability of results across countries. In undertaking this analysis, a systematic empirical approach is taken which employs three different methodologies: a Granger causality analysis, a supply-side analysis and a demand and supply analysis, all enriched with advanced econometric techniques. Overall, the results for Greece suggest that the high military burden has been harmful to economic performance and has made a significant contribution to- the backwardness of the economy. While the results for Portugal and Spain show some differences, they do not contradict the overall conclusion for Greece. Portugal shows a clear negative effect of military burden awhile the results for Spain are much less clearcut.
Classification of Coronary Calcifications using Deep Learning Approach: A Feasibility Study with the orCaScore Database

This document presents a deep learning method for the automatic detection and classification of calcified lesions in coronary arteries using Convolutional Neural Networks (CNN) based on the AlexNet architecture. The demonstration of this proposal uses orCaScore, a standardized and labeled database of low-dose radiation computed tomography (CT) images of the heart. The methodology division was designed starting with the region of interest (ROI) extraction for consecutively utilizing a patch-based approach. We tested this approach in 7,386 patches and achieved an accuracy of 67%, sensitivity of 100%, precision of 67% and specificity of 75%. Our technique aims to reinforce the detection and quantification of coronary calcified lesions, enabling accurate diagnosis and treatment of cardiovascular diseases.
Nonnegative Tensor-Based Linear Dynamical Systems for Recognizing Human Action from 3D Skeletons

Recently, skeleton-based action recognition has become a very important topic in the field of computer vision. It is a challenging task to accurately build a human action model and precisely distinguish similar human actions. In this paper, an action (skeleton sequence) is represented as a third-order nonnegative tensor time series to capture the original spatiotemporal information of the action. As a linear dynamical system (LDS) is an efficient tool for encoding the spatiotemporal data in various disciplines, this paper proposes a nonnegative tensor-based LDS (nLDS) to model the third-order nonnegative tensor time series. Nonnegative Tucker decomposition (NTD) is utilized to estimate the parameters of the nLDS model. These parameters are used to build extended observability sequence O∞T for the action, which implies that O∞T can be considered as the feature descriptor of the action. To avoid the limitations introduced by approximating O∞T with a finite-order matrix, we represent an action as a point on infinite Grassmann manifold comprising the orthonormalized extended observability sequences. The classification task can be performed by dictionary learning and sparse coding on the infinite Grassmann manifold. The experimental results on the MSR-Action3D, UTKinect-Action, and G3D-Gaming datasets demonstrate that the proposed approach achieves a better performance in comparison with the state-of-the-art methods.