Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors influencing the physical activity levels of older people from culturally-diverse communities: an Australian experience

ABSTRACT Inactivity has been identified as a major contributor to the burden of disease among older Australians, particularly those in culturally-diverse communities. This study assessed the facilitators and barriers to physical activity in older people from culturally-diverse communities, and investigated the predictors of physical activity participation by recruiting 333 older people from seven different communities in the western suburbs of Melbourne, Australia. A survey questionnaire that recorded physical activity and the barriers to and facilitators of activity was interviewer-administered in the participants' preferred language. The data were analysed using bivariate and multivariate inferential statistical methods. Personal barriers to physical activity, such as poor health, lacking the energy to exercise, being too tired and low motivation, were highly prevalent in all groups. Specific factors, such as ‘being self-conscious about my looks’, were more prevalent among the Vietnamese, as were concerns about the weather among Macedonians and Croatians. Across all groups, perceptions of health and safety strongly influenced physical activity behaviour, more so than the external environment. Some of the barriers can be addressed with a common approach, but others in some communities will require particular strategies.
Self, Soul and Management Learning: Constructing the Genre of the Spiritualized Manager

What form of management is suggested by the increased interest in organizational spirituality and what genre of manager does spiritual learning attempt to construct? The growth of interest in organizational spirituality and its implications for management learning and development are discussed. Various approaches for understanding the self are explored, and a model for organizing these approaches, and the ‘Selves’ they imply, are presented. Burgoyne's (2002) outline of the different styles of learning approaches and the types of ‘Self’ they seek to construct are discussed in an attempt to clarify how spiritual management learning approaches are understood with the aim of clarifying a new, spiritualized form (or genre) of managerial self, which the discourse of organizational spirituality appears to seek.
INCIDENCE OF TRYPANOSOMA CRUZI (CHAGAS) IN WILD VECTORS AND RESERVOIRS IN EAST-CENTRAL ALABAMA.

TrypanOsoma cruzi (Chagas) was isolated from 17 of 126 (13.5%) opossums and 5 of 35 (14.3%) raccoons from east-central Alabama. Inoculation of blood, heart muscle, kidney tissue, urine, and peritoneal fluid from survey animals into NNN or Chang's medium showed that the organism was most often isolated from heart muscle followed by blood, kidney, peritoneal fluid, and urine. The trypanosome was recovered from 11 of 181 (6%) triatomid bugs collected in the same area. Of the 44 collections, 32 were from hollow trees or stumps, 10 were from human habitations, and 2 from the quarters of domestic animals. In some instances, both infected vectors and reservoirs were found in heavily populated areas. Trypanosoma cruzi (Chagas), the etiologic agent of Chagas' disease, was first reported from triatomid bugs and man by Chagas (1909). Subsequent reports showed the organism to be present in many areas of Latin America. The first report of T. cruzi in the United States was that of Kofoid and McCulloch (1916), who found the flagellate in triatomid bugs in California. At the time, they named the organism Trypanosoma triatomae since they could not find the organism in the blood of wood rats upon which the bugs were feeding. Later reports verified the presence of T. cruzi in vertebrate reservoirs and triatomid bugs in the southwestern United States (Kofoid and Donat, 1933; Kofoid and Whitaker, 1936; Wood and Wood, 1941). Woody and Woody (1955) reported the first naturally acquired human case of Chagas' disease in the United States in a child from Corpus Christi, Texas. In the same year, a second indigenous case, also diagnosed in a child, was reported from Bryan, Texas, according to a report by Goble (1958). Walton et al. (1956) reported the isolation of T. cruzi from three raccoons captured in Maryland; however, they were unable to find triatomid vectors in the area where the raccoons were captured, according to a report in 1958. McKeever et al. (1958) reported finding an organism resembling T. cruzi in 107 animals of four species in southwestern Georgia and northwestern Florida. Later research verified that the organism was T. cruzi (Norman et al., 1959). Yaeger (1961) found inf cted triatomid bugs in areas of Louisiana where mammals harboring trypanosomes had been collected. These reports indicate that T. cruzi is probably present throughout the southeastern United States. This paper reports the incidence of T. cruzi in wild mammals and triatomid bugs collected in east-central Alabama between September 1960 and June 1963.
Cross-Correlation in the Auditory Coincidence Detectors of Owls

Interaural time difference (ITD) plays a central role in many auditory functions, most importantly in sound localization. The classic model for how ITD is computed was put forth by Jeffress (1948). One of the predictions of the Jeffress model is that the neurons that compute ITD should behave as cross-correlators. Whereas cross-correlation-like properties of the ITD-computing neurons have been reported, attempts to show that the shape of the ITD response function is determined by the spectral tuning of the neuron, a core prediction of cross-correlation, have been unsuccessful. Using reverse correlation analysis, we demonstrate in the barn owl that the relationship between the spectral tuning and the ITD response of the ITD-computing neurons is that predicted by cross-correlation. Moreover, we show that a model of coincidence detector responses derived from responses to binaurally uncorrelated noise is consistent with binaural interaction based on cross-correlation. These results are thus consistent with one of the key tenets of the Jeffress model. Our work sets forth both the methodology to answer whether cross-correlation describes coincidence detector responses and a demonstration that in the barn owl, the result is that expected by theory.
Incremental Bisimulation Abstraction Refinement

Abstraction refinement techniques in probabilistic model checking are prominent approaches to the verification of very large or infinite-state probabilistic concurrent systems. At the core of the refinement step lies the implicit or explicit analysis of a counterexample. This paper proposes an abstraction refinement approach for the probabilistic computation tree logic (PCTL), which is based on incrementally computing a sequence of may- and must-quotient automata. These are induced by depth-bounded bisimulation equivalences of increasing depth. The approach is both sound and complete, since the equivalences converge to the genuine PCTL equivalence. Experimental results with a prototype implementation show the effectiveness of the approach.
Mapping GPS-denied aquatic environments

Building a representation of space and estimating a robot's location within that space is a fundamental task in robotics known as simultaneous localization and mapping (SLAM). This work examines the problem of solving SLAM in aquatic environments using an unmanned surface vessel under conditions that restrict global knowledge of the robots pose. These conditions refer specifically to the absence of a global positioning system to estimate position, a poor vehicle motion model, and the lack of a strong stable magnetic field to estimate absolute heading. These conditions can be found in terrestrial environments where the line of sight to overhead satellites is occluded by surrounding structures and local magnetic inference disrupts reliable compass measurements. Similar conditions are anticipated in extra-terrestrial environments such as on Titan where the lack of a global satellite network inhibits the use of traditional positioning sensors and the lack of a stable magnetic core limits the applicability of a compass. This work develops a solution to the SLAM problem that utilizes shore features coupled with information about the depth of the water column. Theoretical results are validated experimentally using an autonomous surface vehicle utilizing omnidirectional video and a depth sounder. Solutions are compared to ground truth obtained using GPS.
Altered membrane NTPase activity in Lesch–Nyhan disease fibroblasts: comparison with HPRT knockout mice and HPRT‐deficient cell lines

Lesch–Nyhan disease (LND) is a rare disorder caused by a defect of an enzyme in the purine salvage pathway, hypoxanthine phosphoribosyl transferase (HPRT). It is still unknown how the metabolic defect translates into the complex neuropsychiatric phenotype characterized by self‐injurious behavior, dystonia and mental retardation. There are abnormalities in purine and pyrimidine nucleotide content in HPRT‐deficient cells. We hypothesized that altered nucleotide concentrations in HPRT deficiency change G‐protein‐mediated signal transduction. Therefore, our original study aim was to examine the high‐affinity GTPase activity of G‐proteins in membranes from primary human skin and immortalized mouse skin fibroblasts, rat B103 neuroblastoma cells and mouse Neuro‐2a neuroblastoma cells. Unexpectedly, in membranes from human fibroblasts, B103‐ and Neuro‐2a cells, Vmax of low‐affinity nucleoside 5′‐triphosphatase (NTPase) activities was decreased up to 7‐fold in HPRT deficiency. In contrast, in membranes from mouse fibroblasts, HPRT deficiency increased NTPase activity up to 4‐fold. The various systems analyzed differed from each other in terms of Km values for NTPs, absolute Vmax values and Ki values for nucleoside 5′‐[β,γ‐imido]triphosphates. Our data show that altered membrane NTPase activity is a biochemical hallmark of HPRT deficiency, but species and cell‐type differences have to be considered. Thus, future studies on biochemical changes in LND should be conducted in parallel in several HPRT‐deficient systems.
Multi-Scale Computational Models for Electrical Brain Stimulation

Electrical brain stimulation (EBS) is an appealing method to treat neurological disorders. To achieve optimal stimulation effects and a better understanding of the underlying brain mechanisms, neuroscientists have proposed computational modeling studies for a decade. Recently, multi-scale models that combine a volume conductor head model and multi-compartmental models of cortical neurons have been developed to predict stimulation effects on the macroscopic and microscopic levels more precisely. As the need for better computational models continues to increase, we overview here recent multi-scale modeling studies; we focused on approaches that coupled a simplified or high-resolution volume conductor head model and multi-compartmental models of cortical neurons, and constructed realistic fiber models using diffusion tensor imaging (DTI). Further implications for achieving better precision in estimating cellular responses are discussed.
Ethical pathways to informed consent when collecting information from children in research

Aim: This study’s purpose is to determine what themes patients with Cerebral Palsy (CP) rate most highly for importance in their quality of life. Additionally, we aim to determine and compare the parent’s perception of quality of life measures for their child with CP. Methods: Thirty one patients with CP and their guardians were administered a 50 item questionnaire. Results: When comparing the quality of life ratings of patients with CP to parents, five measures were statistically significant. Patients thought that playing video games (p=0.039), using the TV (p=0.004) and how their physical disability affects their appearance in comparison to their peers (p=0.018) were more important than their parents did. Parents thought their child’s future financial independence (p=0.017) and access to healthcare (p=0.008) were more important than their adolescent children did. Interpretation: Parents can accurately predict a few of the quality of life measures important to their child such as eating and drinking independently and going to school. However, disparities exist in many psycho-social domains. A better understanding of the importance of quality of life themes for patients with CP is important because it helps to direct care that can both take advantage of and improve what our patients feel is most important.
Relations of incumbent affect-related personality traits with incumbent and objective measures of characteristics of jobs

The present study examined the possibility that individuals with certain personality traits tend to be found in certain types of jobs. Specifically, we examined correlations between two personality traits, anxiety and optimism, and measures of job characteristics obtained via self-reports and through job analysis. Results showed that those who were high in trait anxiety tended to be in jobs characterized by low autonomy, variety, identity, feedback, significance, and complexity. Conversely, those reporting high levels of optimism tended to be in jobs characterized by high levels of each of these job characteristics. Further research to clarify these findings was suggested.
Software Defined Networking for Flexible and Green Energy Internet

Energy Internet is a vision of future power systems, which will achieve highly efficient interconnection among various types of energy resources, storage, and loads, and enable P2P energy delivery on a large scale. To enhance the flexibility and efficiency of Energy Internet, this article employs the methodology of SDN in Energy Internet and proposes an SDEI architecture. In the SDEI, the control, data, and energy planes are separated. The control plane dynamically reconfigures the data and energy planes and achieves flexible cooperation between them. We then focus on applying an SDN approach to energy router networking, and build a hierarchical energy control architecture that can implement the programmability of energy flow and allow P2P energy delivery from a high-level view. Additionally, we present a case study of future EVs, for which two applications within the SDEI framework are proposed to improve energy efficiency and green energy utilization.
Dynamic control of modeled tonic-clonic seizure states with closed-loop stimulation

Seizure control using deep brain stimulation (DBS) provides an alternative therapy to patients with intractable and drug resistant epilepsy. This paper presents novel DBS stimulus protocols to disrupt seizures. Two protocols are presented: open-loop stimulation and a closed-loop feedback system utilizing measured firing rates to adjust stimulus frequency. Stimulation suppression is demonstrated in a computational model using 3000 excitatory Morris–Lecar (M–L) model neurons connected with depressing synapses. Cells are connected using second order network topology (SONET) to simulate network topologies measured in cortical networks. The network spontaneously switches from tonic to clonic as synaptic strengths and tonic input to the neurons decreases. To this model we add periodic stimulation pulses to simulate DBS. Periodic forcing can synchronize or desynchronize an oscillating population of neurons, depending on the stimulus frequency and amplitude. Therefore, it is possible to either extend or truncate the tonic or clonic phases of the seizure. Stimuli applied at the firing rate of the neuron generally synchronize the population while stimuli slightly slower than the firing rate prevent synchronization. We present an adaptive stimulation algorithm that measures the firing rate of a neuron and adjusts the stimulus to maintain a relative stimulus frequency to firing frequency and demonstrate it in a computational model of a tonic-clonic seizure. This adaptive algorithm can affect the duration of the tonic phase using much smaller stimulus amplitudes than the open-loop control.
Towards physics-based DTCO for performance of advanced technology nodes

We present a case study which shows the path towards design-technology co-optimization (DTCO) based on physical device modeling as opposed to simulation based on empirical mobility models. This allows for more accurate and robust predictions of device performance, and allows to assess novel process options found in 7 nm and 5 nm technology nodes. A more than ten-fold increase in computational efficiency brings turn-around times down sufficiently to make physical models suitable for the DTCO process.
The Rat Homolog of the Schizophrenia Susceptibility Gene ZNF804A Is Highly Expressed during Brain Development, Particularly in Growth Cones

A single nucleotide polymorphism in the ZNF804A gene, rs1344706, is associated with schizophrenia. The polymorphism has been suggested to alter fetal expression of ZNF804A. It has also been reported to be associated with altered cortical functioning and neural connectivity in the brain. Since developmental mechanisms are suggested in the pathophysiology for schizophrenia, expression of Zfp804A, the rat homolog of ZNF804A, was investigated in the developing rat brain. We found that expression of Zfp804A in most brain regions is developmentally regulated and peaks around birth, where after it decreases towards adult levels. This time point is developmentally the equivalent to the second trimester of fetal development in humans. An exception to this expression pattern is the hippocampus where the expression of Zfp804A appears to increase again in the adult brain. Using laser capture and quantitative PCR we found that Zfp804A mRNA expression in the adult rat hippocampus is highest in the CA1 sub region, where the overall firing rates of neurons is higher than in the CA3 region. In cultured cortical neurons Zfp804A mRNA expression peaked at day 4 and then decreased. The ZFP804A protein expression was therefore investigated with immunochemistry in such cultures. Interestingly, before day 4, the protein is mostly found in the perinuclear region of the cell but at day 4, ZFP804A was instead found throughout the cell and particularly in the growth cones. In conclusion we demonstrate that Zfp804A increases in the rat brain at the time of birth, coinciding with neuronal differentiation. We also show that ZFP804A is localized to growth cones of growing neurites. These data implicate ZFP804A in growth cone function and neurite elongation. The polymorphism rs1344706 lowers expression of ZNF804A during prenatal brain development. This may affect ZNF804A’s role in cone function and neurite elongation leading to synaptic deficits and altered neural connectivity.
Updating the Pre/Post Plane in MonetDB/XQuery

We outline an e‐cient ACID-compliant mechanism for structural inserts and deletes in relational XML document storage that uses a region based pre/size/level encoding (equivalent to the pre/post encoding). Updates to such node-numbering schemes are considered prohibitive (i.e. physical cost linear to document size), because structural updates cause shifts in all pre-numbers after the update point, and require updates of the size of all ancestors, such that the root of the tree becomes a locking bottleneck. We show how such locking can be avoided by updating the size of ancestors using deltaincrements, which are transaction-commutative operations. We also reduce the physical cost to the minimum (i.e. linear to update volume) by carefully exploiting the virtual column feature of MonetDB to store pre numbers (virtual columns are never materialized, and thus need not be updated). In our evaluation, we show the overhead of the update-feature in MonetDB/XQuery in terms of added XMark evaluation cost to stay within an acceptable limit (<30% on average).
Scalable Object Retrieval with Compact Image Representation from Generic Object Regions

In content-based visual object retrieval, image representation is one of the fundamental issues in improving retrieval performance. Existing works adopt either local SIFT-like features or holistic features, and may suffer sensitivity to noise or poor discrimination power. In this article, we propose a compact representation for scalable object retrieval from few generic object regions. The regions are identified with a general object detector and are described with a fusion of learning-based features and aggregated SIFT features. Further, we compress feature representation in large-scale image retrieval scenarios. We evaluate the performance of the proposed method on two public ground-truth datasets, with promising results. Experimental results on a million-scale image database demonstrate superior retrieval accuracy with efficiency gain in both computation and memory usage.
Sensor fault detection with low computational cost: A proposed neural network-based control scheme

The paper describes a low computational power method for detecting sensor faults. A typical fault detection unit for multiple sensor fault detection with modelbased approaches, requires a bank of estimators. The estimators can be either observer or artificial intelligence based. The proposed control scheme uses an artificial intelligence approach for the development of the fault detection unit abbreviated as `i-FD'. In contrast with the bank-estimators approach the proposed i-FD unit is using only one estimator for multiple sensor fault detection. The efficacy of the scheme is tested on an Electro-Magnetic Suspension (EMS) system and compared with a bank of Kalman estimators in simulation environment.
Impact of Performance Improvement Continuing Medical Education on Cardiometabolic Risk Factor Control: The COSEHC Initiative

Introduction: The Consortium for Southeastern Hypertension Control (COSEHC) implemented a study to assess benefits of a performance improvement continuing medical education (PI CME) activity focused on cardiometabolic risk factor management in primary care patients. Methods: Using the plan‐do‐study‐act (PDSA) model as the foundation, this PI CME activity aimed at improving practice gaps by integrating evidence‐based clinical interventions, physician‐patient education, processes of care, performance metrics, and patient outcomes. The PI CME intervention was implemented in a group of South Carolina physician practices, while a comparable physician practice group served as a control. Performance outcomes at 6 months included changes in patients' cardiometabolic risk factor values and control rates from baseline. We also compared changes in diabetic, African American, the elderly (> 65 years), and female patient subpopulations and in patients with uncontrolled risk factors at baseline. Results: Only women receiving health care by intervention physicians showed a statistical improvement in their cardiometabolic risk factors as evidenced by a −3.0 mg/dL and a −3.5 mg/dL decrease in mean LDL cholesterol and non‐HDL cholesterol, respectively, and a −7.0 mg/dL decrease in LDL cholesterol among females with uncontrolled baseline LDL cholesterol values. No other statistical differences were found. Discussion: These data demonstrate that our PI CME activity is a useful strategy in assisting physicians to improve their management of cardiometabolic control rates in female patients with abnormal cholesterol control. Other studies that extend across longer PI CME PDSA periods may be needed to demonstrate statistical improvements in overall cardiometabolic treatment goals in men, women, and various subpopulations.
Topics in entire functions. Lectures in Kent University

Theorem. This class is closed under differentiation. Proof. Let d = degP . Then degP ′ = d−1, so P ′ has at most d−1 zeros (counting multiplicity). On the other hand, it follows from Rolle’s theorem that P ′ has at least d − 1 real zeros (counting multiplicity! ). So all zeros of P ′ are real. This is a non-trivial proof! We used the following principle: if X ⊂ Y are finite subsets, and cardX ≥ cardY then X = Y . And the degree d, which was used in the proof, is not mentioned in the statement of the theorem.