Miracle-dz/UniFAR-FTUs huggingface dataset:
WORKING RIGHT: THE ATMOSPHERES PEOPLE ENDEAVOR TO CREATE IN THEIR WORKSPACES.

Environmental psychology research has shown that people’s psychological well-being is enhanced when they personalize their workspaces and has also identified patterns in those personalizations, but it has not addressed the atmosphere people endeavor to create in their offices. Identifying desired atmospheres has practical value, because workspace design can facilitate the development of these intended psychological experiences. The research reported here explored the issue of atmosphere by content analyzing open-ended responses to inquiries about it posed to 259 employed people living in the United States, interviewed during a 10 year period (2000-2010). Across all population segments studied, the most prevalent atmosphere desired was one that nurtured the owner of the space and the second most frequently desired atmosphere was one that inspired optimal performance by people in the workspace. Relationships between desired atmospheres and factors such as gender, age, rank in organization, and organization type were investigated.
Twofold Fail-Work Remedy for Reconfigurable Driver and Windings of Four-Phase Permanent Magnet Fault-Tolerant Motor System

In this paper, a novel multiphase reconfigurable and fault-tolerant drive converter topology is proposed for driver with fail-work capability, and fault-tolerant strategies are proposed for open-circuit and short-circuit faults in the single-phase windings, aiming to improve the motor drive system's fail-work ability in the high reliability applications. The drive converter topology can isolate open-circuit and short-circuit faults in power supplies, power devices, or switches. Then, it can reconfigure the drive circuit topology from independent H-bridge to star type by reconfigurable switches and power devices, according to the fault-type and the fault-tolerant truth tables. After reconfiguration, remedial operation will be utilized for open- and short-circuit faults of windings, so that the motor system has twofold fail-work capabilities in driver and windings. Finally, based on a series of experiments on a transit co-simulation model and test bench, the effectiveness and validity of fault-tolerant capability and the strategies are verified, and has twofold fail-work remedy.
Mississippi River discharge over the last similar to 560,000 years - Indications from X-ray fluorescence core-scanning

: The long term history of terrigenous flux to the Gulf of Mexico via the Mississippi River is hardly known. We here present geochemical and sedimentological data to approximate the varying Mississippi River sediment influx into the northeastern Gulf of Mexico (GoM) over the last six glacial-interglacial cycles (MIS 1 to 14). Our study is based on the IMAGES sediment core MD02-2576 that was recovered from the DeSoto Canyon and is located similar to 200 km south to the recent Mississippi River delta and similar to 150 km east of the recent coastline of Florida. Concentrations of siliciclastic elements in bulk sediment samples were estimated from XRF scanning and calibrated by single bulk XRF-analyses. Elemental ratios of the sedimentary record correspond to ratios from the Mississippi River catchment rather than to the core close Alabama and Mobile River catchments. The siliciclastic major element potassium (K) with enhanced surface concentrations in the northwestern Mississippi River catchment shows varying occurrence downcore and here serves as a proxy for Mississippi River sediment discharge variability. Changes in sedimentation rate and magnetic susceptibility further support the variations in Mississippi River influx. Our data were compared with Mississippi River terrestrial archives in the form of loess and terrace deposits that back up our interpretations of enhanced glacial phase Mississippi River influx triggered by strengthened fluvial river runoff and changing fluvial and ice sheet dynamics. Mississippi River influx was at a maximum during glacial MIS 2/3, MIS 8 and MIS 10. Late glacial MIS 6 deviates from this pattern being a period of reduced Mississippi River influx at the core location, probably due to a westward shift of the Mississippi River delta. archives. Main sedimentation phases identified in these terrestrial archives coincide with phases of significantly enhanced Mississippi River discharge from the marine archive. Climatic changes, leading to waxing and waning of the Laurentide ice-sheet, precipitation changes over N-America, sea level fluctuations, and – closely related –Mississippi River delta shifting probably caused the Mississippi River discharge variability. Our study points to prominent Mississippi River sediment input during glacial MIS 2/3, late 8 and 10. The extremely reduced Mississippi River signal during MIS 6 is related to a shift of the Mississippi River delta to the west.
Robust hierarchical controller with conditional integrator based on small gain theorem for reference trajectory tracking of autonomous vehicles

ABSTRACT A robust trajectory tracking controller is designed for autonomous vehicles based on a hierarchical architecture to make the autonomous vehicle track a given reference trajectory. The controller consists of two sub controllers: kinematic controller and dynamic controller. Based on the kinematics of tracking reference trajectory, a desired yaw rate is calculated by kinematic controller to make the lateral deviation global asymptotic stable. Then, steering wheel angle is calculated by a vehicle dynamic controller to make the vehicle yaw rate converge to the desired value and make the vehicle dynamic stable. Conditional integration method is used in the sub controllers. This method guarantees global asymptotic stability of tracking reference values and considers the uncertainty of parameters and constraints of desired yaw rate and actuators. Then based on small-gain theorem, the condition of the finite-gain L stability is given to the hierarchical controller to ensure the interconnected sub systems stable and prevent the amplification of system disturbance. Finally, the effectiveness and robustness of the controller are validated by real vehicle experiments.
Collaborative Groupware Implementations: A Systematic Literature Review

— Application software utilized to assist groups consisting of two or more individuals working towards same outcome is called collaborative software. These software mostly function by allowing process managers to keep track of required group processes that are needed to obtain a specific result. Software development heavily relies upon inter/intra-team collaboration between small teams of developers to build functional software modules. Utilization of collaborative groupware software monitors individual contributions towards process outcomes. Mapping individual contributions will cause a boost in overall productivity by allowing the organization process managers to highlight specific unfulfilled processes over the span of a Software Development Life Cycle (SDLC). Tools designed to facilitate inter/intra-team collaborative interaction were examined. This paper studies factors which influence design of collaborative groupware implementations along with their adoption by end-users in a post COVID (SARS-CoV-2) pandemic impacted world. We present our inferences on existing productivity groupware implementations after going through referenced literature pertaining to their construction and impact on the end-user. We detail the variables which influence usage patterns and implementation of productivity tool, investigating whether User Interfaces (UI) allow for end-user to have an uncluttered experience while navigating the tool, checking for cohesive user engagement using local variables unique to the experiences of domestic teams. Lastly, we conclude with a few points regarding complications faced while designing resources to assist globally distributed virtual networks of teams carrying out complex projects.
The Role of Thyroid Hormones on Management of Cartilaginous Joint Disorders

The purpose of the present research is to demonstrate the involvement of thyroid hormones and function on orthopaedic health, particularly focusing on the management of cartilaginous joint disorders. There is more than sufficient evidence in the literature suggesting that fluctuations in levels of thyroid hormones, that is, deficiency as well as excess, can lead to a wide array of complications and even the manifestation of systemic diseases. Several studies demonstrate the indispensable biological value of thyroid hormones and their role in diverse mammalian target tissues, especially in skeletal cells and chondrocytes. The investigations discussed in this article also shine light on cellular and molecular mechanisms of hormonal regulation, interaction and even thread further into the genetic perspective behind the metabolic processes. It is also well known that thyroid hormone receptors TRα1 and TRβ1 are both expressed in the skeleton, growth plate chondrocytes, bone marrow, osteoblasts and even stromal cells; deiodinase type 3 is expressed in all skeletal cells, further suggesting their relevance in human health. Inregards to thyroidal hormone impact on cartilage, appreciable studies evaluate the potential of parathyroid hormones in stimulating chondrocytes, ultimately suggesting that timing and duration of hormone application are vital, as chondrocytes seem to require time to adapt and respond to hormonal stimuli. Alternative approaches indicate that the implementation of small doses of dietary iodine in individuals with deficits in concentration of this micronutrient show significant changes and can be helpful in regulating thyroid status.
Robust Cluster Analysis and Variable Selection

Introduction Mixture and classification models and their likelihood estimators General consistency and asymptotic normality Local likelihood estimates Maximum likelihood estimates Notes Mixture models and their likelihood estimators Latent distributions Finite mixture models Identifiable mixture models Asymptotic properties of local likelihood maxima Asymptotic properties of the MLE: constrained nonparametric mixture models Asymptotic properties of the MLE: constrained parametric mixture models Notes Classification models and their criteria Probabilistic criteria for general populations Admissibility and size constraints Steady partitions Elliptical models Normal models Geometric considerations Consistency of the MAP criterion Notes Robustification by trimming Outliers and measures of robustness Outliers The sensitivities Sensitivity of ML estimates of mixture models Breakdown points Trimming the mixture model Trimmed likelihood function of the mixture model Normal components Universal breakdown points of covariance matrices, mixing rates, and means Restricted breakdown point of mixing rates and means Notes Trimming the classification model - the TDC Trimmed MAP classification model Normal case - the Trimmed Determinant Criterion, TDC Breakdown robustness of the constrained TDC Universal breakdown point of covariance matrices and means Restricted breakdown point of the means Notes Algorithms EM algorithm for mixtures General mixtures Normal mixtures Mixtures of multivariate t-distributions Trimming - the EMT algorithm Order of Convergence Acceleration of the mixture EM Notes k-Parameters algorithms General and elliptically symmetric models Steady solutions and trimming Using combinatorial optimization Overall algorithms Notes Hierarchical methods for initial solutions Favorite solutions and cluster validation Scale balance and Pareto solutions Number of components of uncontaminated data Likelihood-ratio tests Using cluster criteria as test statistics Model selection criteria Ridgeline manifold Number of components and outliers Classification trimmed likelihood curves Trimmed BIC Adjusted BIC Cluster validation Separation indices Normality and related tests Visualization Measures of agreement of partitions Stability Notes Variable selection in clustering Irrelevance Definition and general properties The normal case Filters Univariate filters Multivariate filters Wrappers Using the likelihood ratio test Using Bayes factors and their BIC approximations Maximum likelihood subset selection Consistency of the MAP cluster criterion with variable selection Practical guidelines Notes Applications Miscellaneous data sets IRIS data SWISS BILLS STONE FLAKES Gene expression data Supervised and unsupervised methods Combining gene selection and profile clustering Application to the LEUKEMIA data Notes Appendix A: Geometry and linear algebra Appendix B: Topology Appendix C: Analysis Appendix D: Measures and probabilities Appendix E: Probability Appendix F: Statistics Appendix G: Optimization
CRN Survey and A Simple Sequential MAC Protocol for CRN Learning

—With the idea to use the spectrum band efficiently, much of the research is being published in the field of cognitive radio network to share the licensed spectrum band with unlicensed users when licensed users are not active. Cognitive Radio Network (CRN) has introduced a lot of new challenges in the field of wireless networks. In this research paper, we had listed the cognitive radio network issues by conducting a survey of MAC protocols for CRNs. We have also developed a very simple MAC protocol for learning CRN for the entry level researcher.
A comparison between artiﬁcial neural networks and ARIMA models in trafﬁc forecasting

Motivation: Trafﬁc forecasting is becoming a vital component of our travel experience. It plays a key role in intelligent transportation systems that allow us to make smarter use of existing transportation networks. This study focuses on the possible role of artiﬁcial neural networks in these systems and what data can be best feed in to them to retrieve the best results. Aim: The goal of this study is to see whether two layered feed forward neural networks outperform the statistical ARIMA model in motorway trafﬁc forecasting. In speciﬁc, whether or not the usage of upstream and multivariate data decreases the forecasting errors of the neural network, how this relates to the amount of samples used as input, and how this relates to the amount of time steps that is forecasted ahead. Results and conclusions: Two different trafﬁc networks are used to train and test the models. The testing results show that, when doing predictions using time steps covering 10 minutes of trafﬁc data and forecasting one time step ahead, the optimal amount of samples used as input is 4. Increasing the input length after this does not result in better predictions, it even slightly increases the prediction errors. Moreover, it became clear that up to 3 or 4 time steps forecasting in the future, the neural networks using upstream data outperform the ARIMA model. After this an ARIMA model that uses deseasonalized data or a neural network that uses deseasonalized data is a better option. There is always a two layered neural network that outperforms the ARIMA models. Furthermore, the usage of upstream data almost always decreases the prediction errors. This is different with the usage of multivariate data, which hardly contributes to a better prediction in the used form.
Single-ReagentPolarizationFluoroimmunoassayfor Amphetaminein Urine

(PFIA) is a rapid homogeneous technique (involving no separation of labeled and unlabeled analyte) based on the increase in signal associated with antibody binding of a fluorophore-labeled antigen (1-4). We describe the development of a novel PFIA to screen urine for the presence of amphetamine. To improve specificity, we used an antiserum raised against an amphetamine immunogen conjugated via the para position of the drug’s phenyl ring. To simplify the procedure, we reagent, by mixing antiserum with fluorescein-labeled tracer.
Video Retrieval by Learning Uncertainties in Concept Detection from Imbalanced Annotation Data

—Concept-based video retrieval retrieves shots relevant to a query based on detection results of concepts, such as Person , Building and Car . However, concept detection is ‘uncertain’ because even state-of-the-art methods cannot accurately detect various concepts. Thus, we introduce a video retrieval method, which models the uncertainty in the detection of each concept using ‘plausibilities’. A plausibility represents an upper bound of probability that the concept is present (or absent) in a shot. Using such plausibilties, false positive and false negative detections of the concept can be effectively managed. We derive plausibilities by estimating the density ratio between shots annotated with the concept’s presence and absence. However, annotating randomly sampled shots does not lead appropriate plausibilities due to the ‘imbalanced problem’. This means that the number of shots where the concept is present is generally much smaller than the number of shots where it is absent. To overcome this, a selective sampling method is developed to preferentially sample unannotated shots, which are similar to shots already annotated with the concept’s presence. Experimental results on TRECVID 2009 video data validates the effectiveness of derived plausibilities.
The Aminotetraline Derivative, CHF-1024, Displays Cardioprotection in Post-Ischemic Ventricular Dysfunction of the Rat Heart

To analyse the protective effects of the aminotetraline derivative CHF-1024, a compound endowed with DA 2 -dopaminergic/ α 2 -adrenergic receptor agonistic activity, in myocardial ischemia/reperfusion damage. A model of isolated and perfused (15 ml/min) electrically driven (300 beats/min) rat heart subjected to global ischemia (1 ml/min for 20 min) and reperfusion (15 ml/min for 30 min) was followed. Cardiac mechanics changes were evaluated together with biochemical markers of cardiac ischemia in perfusate and tissue tumor necrosis factor- α ( TNF- α) . CHF-1024, perfused through the heart for 15 min before ischemia at different molar concentrations (from 1 to 100 nM), significantly improved left ventricle developed pressure during reperfusion, and normalized left ventricular end-diastolic pressure and coronary perfusion pressure. This anti-ischemic effect of CHF-1024 was associated to a decrease in creatine kinase and lactate dehydrogenase, both released during heart reperfusion. These events were concomitant with maintenance of a higher production of 6-keto-prostaglandin F 1 α The ability of CHF-1024 to improve post-ischemic ventricular dysfunction was correlated with a dose-dependent inhibition of the release of both norepinephrine (NE), from sympathetic nerve endings, and TNF- α from cardiac tissue. The effect of CHF-1024 on NE release was almost completely antagonized by specific antagonists of presynaptic inhibitory receptors, domperidone and rauwolscine. The finding that this new aminotetraline derivative possesses anti-ischemic properties and limits NE release from cardiac nerve endings may bear some therapeutic potential in cardiovascular diseases.
Vascular Injury Triggers Krüppel-Like Factor 6 (KLF6) Mobilization and Cooperation with Sp1 to Promote Endothelial Activation through Upregulation of the Activin Receptor-Like Kinase 1 (ALK1) Gene

Rationale : Activin receptor-Like Kinase-1 (ALK1) is an endothelial TGF- β receptor involved in angiogenesis. ALK1 expression is high in the embryo vasculature, becoming less detectable in the quiescent endothelium of adult stages. However, ALK1 expression becomes rapidly increased after angiogenic stimuli such as vascular injury. Objective : To characterize the molecular mechanisms underlying the regulation of ALK1 upon vascular injury. Methods and Results : Alk1 becomes strongly upregulated in endothelial (EC) and vascular smooth muscle cells (vSMC) of mouse femoral arteries after wire-induced endothelial denudation. In vitro, denudation of monolayers of Human Umbilical Vein Endothelial Cells (HUVEC) also leads to an increase in ALK1. Interestingly, a key factor in tissue remodeling, Krüppel-like factor 6 (KLF6), translocates to the cell nucleus during wound healing, concomitantly with an increase in the ALK1 gene transcriptional rate. KLF6 knock down in HUVECs promotes ALK1 mRNA downregulation. Moreover, Klf6 +/- mice have lower levels of Alk1 in their vasculature compared with their wild type siblings. Chromatin immunoprecipitation assays show that KLF6 interacts with ALK1 promoter in ECs, and this interaction is enhanced during wound healing. We demonstrate that KLF6 is transactivating ALK1 gene, and this transactivation occurs by a synergistic cooperative mechanism with Sp1. Finally, Alk1 levels in vSMCs are not directly upregulated in response to damage, but in response to soluble factors, such as IL-6, released from ECs after injury. Conclusions : ALK1 is upregulated in ECs during vascular injury by a synergistic cooperative mechanism between KLF6 and Sp1, and in vSMCs by an EC-vSMC paracrine communication during vascular remodeling.
Temporal structure of plant-frugivorous bird networks is influenced by migration and fruit availability

Background. Ecological communities are dynamic collections whose composition and structure changes over time, making up complex interspecific interaction networks. Mutualistic plant-animal networks can be approached through complex network analysis; these networks are characterized by a nested structure consisting of a core of generalist species, which endows the network with stability and robustness against disturbance. Those mutualistic network structures can vary as a consequence of seasonal fluctuations and food availability, as well as the arrival of new species into the system that might disorder the mutualistic network structure (e.g. a decrease in nested pattern). However, there is no assessment on how the arrival of migratory species into seasonal tropical systems can modify such patterns. Emergent and fine structural temporal patterns are adressed here for the first time for plant-frugivorous bird networks in a highly seasonal tropical environment. Methods. In a plant-frugivorous bird community, we analyzed the temporal turnover of bird species comprising the network core and periphery of ten temporal networks resulting from different bird migration periods. Additionally, we evaluated how fruit abundance and richness, as well as the arrival of migratory birds into the system, explained the temporal changes in network parameters such as network size, connectance, nestedness, specialization, interaction strength asymmetry and niche overlap. The analysis included data from 10 quantitative plant-frugivorous bird networks registered from November 2013 to November 2014. Results. We registered a total of 319 interactions between 42 plant species and 44 frugivorous bird species; only eleven bird species were part of the network core. We witnessed a noteworthy turnover of the species comprising the network periphery during migration periods, as opposed to the network core, which did not show significant temporal changes in species composition. Our results revealed that migration and fruit richness explain the temporal variations in network size, connectance, nestedness and interaction strength asymmetry. On the other hand, fruit abundance only explained connectance and nestedness. Discussion. By means of a fine temporal resolution analysis, we evidenced for the first time how temporal changes in the interaction network structure respond to the arrival of migratory species into the system and fruit availability. Additionally, few migratory bird species established components, while most of them were peripheral species. We showed the relevance of studying bird-plant interactions at fine temporal scales, considering changing scenarios of species composition with a quantitative network approach.