Miracle-dz/UniFAR-FTUs huggingface dataset:
High production of proinflammatory and Th1 cytokines by dendritic cells from patients with rheumatoid arthritis, and down regulation upon FcgammaR triggering.

OBJECTIVE To assess whether DC from RA produce altered cytokine levels and whether this is regulated by triggering of Fc gamma receptors (FcgammaR). METHODS The production of proinflammatory (TNFalpha, IL1, IL6), Th1 (IL12, IFNgamma), and Th2 (IL10) cytokine profiles of immature DC (iDC) from patients with RA and healthy subjects upon triggering of FcgammaR dependent and independent pathways was investigated. iDC, derived from blood monocytes by standardised protocols, were stimulated with immune complexes (IC) at day 6 for 48 hours and, subsequently, for 2 days with LPS in the presence or absence of IC or IFNgamma, resulting in fully matured DC (mDC). IL1, IL6, TNFalpha, IFNgamma, IL12, and IL10 levels in supernatants were measured by ELISA and RIA. RESULTS mDC from patients with RA showed a markedly increased production of IL1, IL6, TNFalpha, and IL10 compared with DC from healthy donors. Triggering of FcgammaR decreased the production of proinflammatory cytokines IL1, IL12, and IFNgamma by iDC and mDC in RA and controls. The production of IL6 and TNFalpha decreased in patients with RA, whereas it was increased in controls. Triggering of FcgammaR independent mechanisms using IFNgamma increased the production of proinflammatory and Th1 cytokines, which was more pronounced in RA. CONCLUSION FcgammaR dependent pathways influence cytokine production by DC. A skewed balance towards proinflammatory and Th1 cytokines in RA can, at least partly, be restored by triggering FcgammaR on DC in RA. Insight into the mechanism which determines the FcgammaR balance might lead to new strategies to abrogate Th1 driven inflammatory processes in RA.
Robotics and Autonomous Systems

This paper addresses the problem of visual dynamic control based on passivity to solve the target tracking problem of mobile manipulators with eyes-in-hand configuration in the 3D-workspace. The redundancy of the system is used for obstacles avoidance and singular configuration prevention through the system’s manipulability control. The design of the stable control system is based on its passivity properties. A robustness analysis and an L 2 -gain performance analysis are also presented. Finally, simulation and experimental results are reported to verify the stability and L 2 -gain performance of the dynamic visual feedback system.
Prediction of Tenderness, Juiciness, and Flavor Profile of 2 Beef Muscles with Different Aging Times Using Rapid Evaporative Ionization Mass Spectrometry (REIMS)

: Rapid evaporative ionization mass spectrometry (REIMS) is a novel technique that provides rapid chemical information on biological tissues and has the potential to predict beef quality attributes in real time. This study aims to assess the ability of analysis by REIMS coupled with chemometric modeling to predict the quality attributes of wet-aged beef at the grading time. USDA Select and upper two-thirds Choice ( n = 42, N = 84) striploins (longissimus lumborum [LL]) and tenderloins (psoas major [PM]) were collected 36 h postmortem from a commercial beef abattoir. The LL and PM were cut into portions and aged for 3, 14, and 28 d. Aged samples were analyzed for slice shear force, Warner-Bratzler shear force (WBS), and trained sensory panels (tenderness, juiciness, and flavor attributes), and results were used to categorize both LL and PM into binary classes. Additionally, slivers of the longissimus dorsi muscle between the 12th and 13th rib were collected during grading (36 h postmortem) and analyzed using REIMS. The REIMS data were used to build predictive models for tenderness, juiciness, and flavor classes for the 3 aging periods and 2 muscles. Prediction accuracies of all models were higher than classifying the samples by chance ( P < 0.05), except WBS of 3 d aging model ( P > 0.05). However, model accuracies were not too high, which could be due to overlaps between classes, small sample sizes, and unbalanced data, which could negatively affect predictive models. Results demonstrated that the chemical finger-prints obtained with REIMS could potentially sort carcasses by flavor, juiciness, and tenderness in real time. However, the full realization of this approach will require an increased sample size and the development of a sampling method that allows improved separation between sensory classes.
Modes of governance of new service development for mobile networks. A life cycle perspective

This paper focuses on governance modes for service development of mobile telephone networks (GSM, WAP, GPRS, UMTS). 'Services' refer to services embodying a specific content. The paper shows that the phase of the life cycle of the network and the service affects the choice of governance mode of new service development projects. Governance modes include internal development by the telecom operator, several forms of collaboration between telecom operator and service firm, and only providing a network by the telecom operator to the service firm, which then develops and provides its services (external). In this paper a model is developed for the governance mode of service development in different phases of the life cycles of the mobile network and service, based on the degrees of uncertainty and urgency involved in the network and service development processes. Four cases are presented of service development projects for mobile telecom networks. These cases indicate that the number of redesigns and the level of communication costs in collaboration projects indeed depend on the degree of urgency and uncertainty involved in these projects, which are in turn affected by the life cycle of the network and service.
A New Criterion to Improve Operational Drizzle Detection with Ground-Based Remote Sensing

Light shallow precipitation in the form of drizzle is one of the mechanisms for liquid water removal, affecting cloud lifetime and boundary layer dynamics and thermodynamics. The early formation of drizzle drops is of particular interest for quantifying aerosol–cloud–precipitation interactions. In models, drizzle initiation is represented by the autoconversion, that is, the conversion of liquid water from a cloud liquid water category (where particle sedimentation is ignored) into a precipitating liquid water category. Various autoconversion parameterizations have been proposed in recent years, but their evaluation is challenging due to the lack of proper observations of drizzle development in the cloud. This work presents a new algorithm for Classification of Drizzle Stages (CLADS). CLADS is based on the skewness of the Ka-band radar Doppler spectrum. Skewness is sensitive to the drizzle growth in the cloud: the observed Gaussian Doppler spectrum has skewness zero when only cloud droplets are present without any significant fall velocity. Defining downward velocities positive, skewness turns positive when embryonic drizzle forms and becomes negative when drizzle starts to dominate the spectrum. CLADS identifies spatially coherent structures of positive, zero, and negative skewness in space and time corresponding to drizzle seeding, drizzle growth/nondrizzle, and drizzle mature, respectively. We test CLADS on case studies from the Jülich Observatory for Cloud Evolution Core Facility (JOYCE-CF) and the Barbados Cloud Observatory (BCO) to quantitatively estimate the benefits of CLADS compared to the standard Cloudnet target categorization algorithm. We suggest that CLADS can provide additional observational constraints for understanding the processes related to drizzle formation better.
e-Publications@Marquette e-Publications@Marquette

This paper examines advisor choice decisions by publicly traded REITs and listed property companies in Asia-Pacific real estate markets. Using a sample of 168 firms, we find robust evidence that firms strategically evaluate and compare the increased agency costs associated with external advisement against the potential benefits associated with collocating decision rights with location specific soft information. Our empirical results reveal real estate companies tend to hire external advisors when they invest in countries: 1) that are more economically and politically unstable, 2) whose legal system is based on civil law, 3) where the level of corruption is perceived to be high
Title : Evaluation of item candidates for a diabetic retinopathy quality of life item bank.

Purpose : We are developing an item bank assessing the impact of diabetic retinopathy (DR) on quality of life (QoL) using a rigorous multi-staged process combining qualitative and quantitative methods. We describe here the first two, qualitative phases: content development and item evaluation. Methods: After a comprehensive literature review, items were generated from four sources: 1) 34 previously validated patient-reported outcome measures; 2) five published qualitative articles; 3) eight focus groups and 18 semi-structured interviews with 57 DR patients; and 4) seven semi-structured interviews with diabetes or ophthalmic experts. Items were then evaluated during 3 stages, namely binning (grouping) and winnowing (reduction) based on key criteria and panel consensus; development of item stems and response options; and pre-testing of items via cognitive interviews with patients. Results : The content development phase yielded 1165 unique items across 7 QoL domains. After 3 sessions of binning and winnowing, items were reduced to a minimally representative set (n=312) across 9 domains of QoL: Visual symptoms; Ocular surface symptoms; Activity limitation; Mobility; Emotional; Health concerns; Social; Convenience; and Economic. After 8 cognitive interviews, 42 items were amended, resulting in a final set of 314 items. Conclusions : We have employed a systematic approach to develop items for a DR-specific QoL item bank. The psychometric properties of the nine QoL subscales will be assessed using Rasch analysis. The resulting validated item bank will allow clinicians and researchers to better understand the QoL impact of DR and DR therapies from the patients’ perspective.
STELLATE BLOCKADE COMBINED TO ILOPROST AS SUPPORTIVE TREATMENT OPTION IMPROVES PAIN AND ISCHAEMIC SYMPTOMS IN PATIENTS WITH SYSTEMIC SCLEROSIS

Background: Peripheral ischaemia is a common symptom in systemic sclerosis (SSc) patients with risk of development of digital ulcers (DU). For its treatment, intravenous iloprost is the most effective option. Accompanying pain symptoms worsen the ischaemic symptoms, so a combination with anaesthetic procedures may improve ischaemic status and the subjective sensation of raynaud and pain.
Computational Genealogy – Continuities and Discontinuities in the Political Rhetoric of US Presidents

Articulations of discontinuity and moments of dissent have been central to critical historical work. However, such vocabularies and analyses of historical change have received less attention in the emerging field of digital methods. Digital methods based on discerning patterns have focused on continuities, while discontinuities and ruptures have been derivative of trends and patterns. By contrast, genealogical methods attend to the entanglement of continuity and discontinuity, and focus on contingency and singularity. This article proposes to develop methods of computational genealogy to analyse multiple temporalities in historical discourses. We experiment with our proposed computational genealogy using the archive of Inaugural speeches by US Presidents. In particular, we show that there is neither a linear advance to Trump’s rhetoric nor an exceptional rupture. Our analysis shows that Trump’s speech is much more the struggle of the Republicans with their own past ideas than struggles with Democrats.
The case for grassroots collaboration : social capital and ecosystem restoration at the local level

List of Figures List of Abbreviations Foreword Acknowledgments Introduction Chapter 1: Grassroots Collaborations to Solve Environmental Problems Chapter 2: A Framework for Collaboration: Building Social Capital, Improving Environmental Outcomes, and Maximizing Democratic Values Chapter 3: The Chesapeake Bay: Local Efforts, Regional Connections Chapter 4: Restoring Princess Elizabeth's River Chapter 5: The Return of the Oyster to the Lynnhaven River Chapter 6: The Nansemond: A Tale of Two Rivers Chapter 7: Conclusion: One Watershed at a Time Appendix: List of Interviewees Reference List About the Authors Index
CONTINGENCY ANALYSIS OF REDUCED 220 KV KPTCL SYSTEM USING MAT-LAB SIMULINK MODEL

In the modern days the power system is becoming wide and complex. Contingency Analysis (CA) is critical in power system analysis. Due to the tremendous and yet increasing amount of data computed by CA, effective visualizations are needed to present the CA results to assist the system operators and engineers to comprehend the static security status of the system in a quick and intuitive manner. The desirable functionalities of such visualizations include showing the overall system security status, showing the severity levels of the contingencies in terms of their associated limit violations. Continuing interconnections of bulk power systems brought about by economic and environmental pressures has led to an increasingly complex system which must be operated closer to the limits of stability. This situation is worst when contingencies occur in the stressed network. This work presents a new technique for contingency analysis based on line flow analysis. Contingency analysis is performed considering the line and generator outage contingencies with different loading conditions in order to identify the effect of an increase in loading to critical line and generator outages. The proposed technique is demonstrated considering 220kV KPTCL system for which the simulink model is developed to evaluate contingency. This will helps to identify the severity level of the system & weak cluster of system.
: how employees mind the implementation gap

Integral to employees’ working lives are the HR policies and more importantly, the practices that follow those and their implementation, which employees experience directly. To date, research on HR implementation considers how HRM is ‘done to’ employees by management and therefore ignores the agency of individuals to shape how HRM is ‘done to them’. Taking the perspective of employees, in a qualitative study of female lawyers, this paper examines employees’ roles in shaping HR implementation, addressing a lack of understanding about the role of ‘others’ in the process. Drawing on the concept of social power, the article focuses on the implementation of agile working practices within UK-based law firms. It finds that despite lacking legitimate position power to influence processes, employees draw on a variety of other power sources (e.g. referent, information, coercive) and tactics (e.g. leveraging membership of professional networks) in order to influence their working environment with respect to HR policy and practice, particularly in response to perceived implementation gaps. The current study underlines that employees may be integral to bridging the gap between policy and practice and therefore to ensuring the link between HRM and organisational performance. It also proposes that behavioural responses to HR practices should be considered in future theorising of the HRM-performance relationship.
HIGH-THROUGHPUT METHODOLOGY FOR EMR-BASED IDENTIFICATION OF CLINICAL SUB-PHENOTYPES IN COMPLEX PATIENT POPULATIONS

Background: Heterogeneity in disease populations complicates discovery of risk factors. To identify risk factors for subpopulations of diseases, we need analytical methods that can deal with unidentified disease subgroups. Objectives: Inspired by successful approaches from the Big Data field, we developed a high-throughput approach to identify subpopulations within patients with heterogeneous, complex diseases using the wealth of information available in Electronic Medical Records (EMRs). Methods: We extracted longitudinal healthcare-interaction records coded by 1,853 PheCodes[1] of the 64,819 patients from the Boston’s Partners-Biobank. Through dimensionality reduction using t-SNE[2] we created a 2D embedding of 32,424 of these patients (set A). We then identified distinct clusters post-t-SNE using DBscan[3] and visualized the relative importance of individual PheCodes within them using specialized spectrographs. We replicated this procedure in the remaining 32,395 records (set B). Results: Summary statistics of both sets were comparable (
Caregiver preparedness is associated with desire to seek long‐term care admission of hospitalized persons with dementia

Hospitalized patients with dementia are more likely to be discharged to long‐term care compared to persons without dementia. Little research has been conducted to examine the associations of caregiver preparedness and strain with desire to seek long‐term care in hospitalized persons with dementia at discharge. The purpose of this study was to examine caregiver preparedness and strain as factors associated with desire to seek long‐term care admission in caregivers of persons with dementia at hospital discharge.
The dementia-inclusive choices in exercise project: Using participatory action research to improve physical activity supports for persons with dementia

Persons with dementia have the right to equal inclusion in rehabilitation, including physical activity. However, the perspectives of persons with dementia are rarely integrated into decision-making related to physical activity programming, services, and supports. Here, we describe the participatory action research (PAR) approach used to develop the Dementia-Inclusive Choices for Exercise (DICE) toolkit, which aims to increase the quality and number of physical activity opportunities available to persons with dementia. The DICE Research Team included persons with dementia, a family care partner, exercise professionals, community and dementia service providers, health care professionals, and researchers who worked to: 1) Engage/maintain the Research Team; 2) Set/navigate ways of engagement; 3) Understand barriers to physical activity; 4) Prioritize the audience and actions; 5) Develop the toolkit; 6) Conduct usability testing; and 7) Implement and evaluate. Guided by the Behaviour Change Wheel, and informed by interviews, focus groups, and existing research, our PAR Team chose to prioritize training exercise providers; exercise providers can enable exercise for persons with dementia if they understand common changes with dementia and how to support persons with dementia in exercise. The content and format of the toolkit was co-developed: drafted by our Research Team, adapted through a stakeholder workshop, and refined through iterative development and usability testing. The product of our PAR process, the DICE toolkit, includes videos meant to destigmatize dementia, training modules and a training manual for exercise providers, a physical activity handout for persons with dementia, and wallet cards to help persons with dementia communicate their abilities, needs, and preferences. Our usability study indicated that the toolkit could be used by exercise providers and may improve attitudes about dementia. Our vision is that our co-developed DICE toolkit will empower exercise providers to improve physical activity opportunities and support for persons with dementia.
Decoding energy decomposition analysis: Machine-learned Insights on the impact of the density functional on the bonding analysis

The concept of chemical bonding is a crucial aspect of chemistry that aids in understanding the complexity and reactivity of molecules and materials. However, the interpretation of chemical bonds can be hindered by the choice of the theoretical approach and the specific method utilized. This study aims to investigate the effect of choosing different density functionals on the interpretation of bonding achieved through energy decomposition analysis (EDA). To achieve this goal, a data set was created, representing four bonding groups and various combinations of functionals and dispersion correction schemes. The calculations showed significant variation among the different functionals for the EDA terms, with the dispersion correction terms exhibiting the highest variability. More information was extracted by using machine learning in combination with dimensionality reduction on the data set. Results indicate that, despite the differences in the EDA terms obtained from different functionals, the functional has the least significant impact, suggesting minimal influence on the bonding interpretation.
The eSAH Score: A Simple Practical Predictive Model for SAH Mortality & Outcomes.

Background: We developed a simple quantifiable scoring system that predicts aneurysmal subarachnoid hemorrhage (aSAH) mortality, delayed cerebral ischemia (DCI) and modified Rankin Scale outcomes using readily available SAH admission clinical data with a new radiographic quantitative volumetric SAH method. Methods: We analyzed 277 patients with aneurysmal SAH (aSAH) admitted at our Comprehensive Stroke Center (CSC) at Mayo Clinic Florida between 2012 and 2022. We developed a mathematical model that measures aSAH basal cisternal subarachnoid hemorrhage volume (SAHV) using a derivation of the ABC/2 ellipsoid formula, where A = width/thickness, B = length, C = vertical extension) on non-contrast CT (NCCT), which we previously demonstrated comparable to pixel based manual segmentation on NCCT scans. Data was analyzed using t-test, chi-square, receiver operator characteristics (ROC) curve, and area under curve analysis. Multivariate logistic regression analysis with stepwise elimination of variables not contributing to the model (0.05 significance level for entry into the model) was used to develop an enhanced SAH (eSAH) scoring system. Results: Using regression and logistic regression, we found that age, GCS score and SAHV were significantly associated with final discharge outcome, prediction on in-hospital DCI, and in-hospital mortality. A weighted eSAH score was developed using these factors that ranged between 0-5 and was strongly predictive of outcome (AUC=0.88), DCI (AUC=0.75) and in-hospital mortality (AUC=0.87). Conclusions: A volumetrically-enhanced SAH (eSAH) score is a simple quantitative model based on SAH volumetrics, GCS and age and appears to predict mortality and outcomes in SAH patients. A larger cohort validation study is planned.
UniST: Towards Unifying Saliency Transformer for Video Saliency Prediction and Detection

Video saliency prediction and detection are thriving research domains that enable computers to simulate the distribution of visual attention akin to how humans perceiving dynamic scenes. While many approaches have crafted task-specific training paradigms for either video saliency prediction or video salient object detection tasks, few attention has been devoted to devising a generalized saliency modeling framework that seamlessly bridges both these distinct tasks. In this study, we introduce the Unified Saliency Transformer (UniST) framework, which comprehensively utilizes the essential attributes of video saliency prediction and video salient object detection. In addition to extracting representations of frame sequences, a saliency-aware transformer is designed to learn the spatio-temporal representations at progressively increased resolutions, while incorporating effective cross-scale saliency information to produce a robust representation. Furthermore, a task-specific decoder is proposed to perform the final prediction for each task. To the best of our knowledge, this is the first work that explores designing a transformer structure for both saliency modeling tasks. Convincible experiments demonstrate that the proposed UniST achieves superior performance across seven challenging benchmarks for two tasks, and significantly outperforms the other state-of-the-art methods.