Miracle-dz/UniFAR-FTUs huggingface dataset:
Hidden loss: A qualitative explorative study of children living with a parent with acquired brain injury

Abstract Primary objective: The purpose of this study was to listen to and learn from children showing high levels of post-traumatic stress symptoms after parental acquired brain injury (ABI), in order to achieve an in-depth understanding of the difficulties the children face in their everyday lives and identify possible trauma-related feelings and relational losses. Design: The study was qualitative, using a phenomenological approach. Methods and procedure: Fourteen children between 7–14 years of age were interviewed at home using a semi-structured interview guide. Siblings were also invited to participate. Results: All children were affected by their parents’ ABI and the altered family situation. The children’s expressions led the authors to identify six themes, including fear of losing the parent, distress and estrangement, chores and responsibilities, hidden loss, coping and support. The main finding indicates that the children experienced numerous losses, many of which were often suppressed or neglected by the children to protect the ill parents. Conclusions: The findings indicated that the children seemed to make a special effort to hide their feelings of loss and grief in order to protect the ill parent. These findings contribute to a deeper understanding of the traumatic process of parental ABI that some children experience and emphasize the importance of family-centred interventions that include the children.
A Branch and Bound Algorithm for the Critical Grid Coverage Problem in Wireless Sensor Networks

We aim to cover a grid fully by deploying the necessary wireless sensors while maintaining connectivity between the deployed sensors and a base station (the sink). The problem is NP-Complete as it can be reduced to a 2-dimensional critical coverage problem, which is an NP-Complete problem. We develop a branch and bound (B&B) algorithm to solve the problem optimally. We verify by computational experiments that the proposed B&B algorithm is more efficient, in terms of computation time, than the integer linear programming model developed by Rebai et al. (2013), for the same problem.
Evaluation of carbon sequestration service of forests - A Russian case-study

Prerequisites of a system methodology of evaluation of carbon sequestration service of forests (CSS) inter alia include: 1) need of assessment of the CSS in biophysical terms, in form of the Full Verified Carbon Account (FCA); 2) an ultimate proxy indicator of the FCA is Net Ecosystem Carbon Budget of forest ecosystems (NECB); 3) need of explicit spatio-temporal distribution of the service (in biophysical and economic terms) and estimation of uncertainties; 4) taken into account that the FCA is a fuzzy (underspecified) system, NECB and its major components are assessed by complimentary use of major methods of carbon accounting (landscape-ecosystem approach; process-based models; eddy covariance; and inverse modelling) with following harmonizing and mutual constraints of the independent estimates. Economic evaluation is provided based on quantitative models of ecosystem services, i.e. ecological production functions, and potential cost under different assumptions. This methodology has been realized for Russian forests for 2007-2009. The NECB was estimated based on an Integrated Land Information System, a multi-layer GIS, where the forest mask was developed at a spatial resolution of 1km by an aggregation of 12 recent remote sensing products, geographically weighted regression and crowdsourcing. Because interactions between ES are different (from synergetic to neutral to competitive to exclusive), economic evaluation of an individual service may not be directly used in integrated assessment of all services within the multipurpose paradigm of forest management. We reconsider the most complete Russian classification of forest ecosystem functions (totally of 75) within 4 classes of ES (provisioning, regulated, cultural, and supporting) and developed a matrix of interactions between CSS and other services that allows to define the range of economic estimates of the CSS under different prices for sequestered carbon and different regimes of forest management.
Myeloid-Derived Suppressor Cells Contribute to Staphylococcus aureus Orthopedic Biofilm Infection

Myeloid-derived suppressor cells (MDSCs) are a heterogeneous population of immature monocytes and granulocytes that are potent inhibitors of T cell activation. A role for MDSCs in bacterial infections has only recently emerged, and nothing is known about MDSC function in the context of Staphylococcus aureus infection. Because S. aureus biofilms are capable of subverting immune-mediated clearance, we examined whether MDSCs could play a role in this process. CD11b+Gr-1+ MDSCs represented the main cellular infiltrate during S. aureus orthopedic biofilm infection, accounting for >75% of the CD45+ population. Biofilm-associated MDSCs inhibited T cell proliferation and cytokine production, which correlated with a paucity of T cell infiltrates at the infection site. Analysis of FACS-purified MDSCs recovered from S. aureus biofilms revealed increased arginase-1, inducible NO synthase, and IL-10 expression, key mediators of MDSC suppressive activity. Targeted depletion of MDSCs and neutrophils using the mAb 1A8 (anti-Ly6G) improved bacterial clearance by enhancing the intrinsic proinflammatory attributes of infiltrating monocytes and macrophages. Furthermore, the ability of monocytes/macrophages to promote biofilm clearance in the absence of MDSC action was revealed with RB6-C85 (anti–Gr-1 or anti-Ly6G/Ly6C) administration, which resulted in significantly increased S. aureus burdens both locally and in the periphery, because effector Ly 6C monocytes and, by extension, mature macrophages were also depleted. Collectively, these results demonstrate that MDSCs are key contributors to the chronicity of S. aureus biofilm infection, as their immunosuppressive function prevents monocyte/macrophage proinflammatory activity, which facilitates biofilm persistence.
Requirements for labelling forest polygons in an object-based image analysis classification

The ability to spatially quantify changes in the landscape and create land-cover maps is one of the most powerful uses of remote sensing. Recent advances in object-based image analysis (OBIA) have also improved classification techniques for developing land-cover maps. However, when using an OBIA technique, collecting ground data to label reference units may not be straightforward, since these segments generally contain a variable number of pixels as well as a variety of pixel values, which may reflect variation in land-cover composition. Accurate classification of reference units can be particularly difficult in forested land-cover types, since these classes can be quite variable on the ground. This study evaluates how many prism sample locations are needed to attain an acceptable level of accuracy within forested reference units in southeastern New Hampshire (NH). Typical forest inventory guidelines suggest at least 10 prism samples per stand, depending on the stand area and stand type. However, because OBIA segments group pixels based on the variance of the pixels, fewer prism samples may be necessary in a segment to properly estimate the stand composition. A bootstrapping statistical technique was used to find the necessary number of prism samples to limit the variance associated with estimating the species composition of a segment. Allowing for the lowest acceptable variance, a maximum of only six prism samples was necessary to label forested reference units. All polygons needed at least two prism samples for classification. †Present address: School of Forestry and Environmental Studies, Yale University, New Haven, CT, USA Present address: Math and Science Division, Babson College, Babson Park, MA, USA.
Effects of Vestibular Rehabilitation Therapy on Postural Control and Quality of Life in Patients after a Surgical Microvascular Decompression of the Cochleo-Vestibular Nerve

Introduction: The purpose of this study was to evaluate the effectiveness of a vestibular rehabilitation therapy (VRT) on the static and dynamic postural control and on the quality of life in patients after a surgical microvascular decompression of the cochleo-vestibular nerve. Method: Eight patients with a neurovascular conflict were submitted to a surgical microvascular decompression at the Hospital (France). Four patients (G1 group) benefited from VRT whereas four other patients (G2 group) returned to their daily life functions and professional activities without VRT. VRT combined exercises on both rotary chair and dynamic post-urography platform and started 7 days after surgery. Evaluation of the postural performance with (EO) and without vision (EC) and during optokinetic stimulation, was carried out in the two groups before (REF), seven days (DAYS 7) and two months (DAYS 67) after the surgery. Questionnaires on the quality of life (SF-36) were administered on DAYS 67 in both groups. Results: The statistical test performed on the posturography data collected under static and dynamic conditions did not show any significant differences between the two groups in EO, EC and during optokinetic stimulation before surgery and on DAYS 7. By contrast, the postural performance in static and dynamic conditions was significantly improved (p<0.05) in the patients who benefited from the VRT with (EO) and without (EC) vision on DAYS 67. Maintaining balance on an unstable platform with optokinetic stimulation was impossible on DAYS 67 for the patients without VRT whereas the patients with VRT succeeded in this more challenging condition. The SF-36 questionnaire was also better in the patients who benefited from the VRT compared to the patients without VRT. Conclusion: This pilot study shows that VRT improves significantly the postural control and the quality of life as well after surgical microvascular decompression. This conclusion must be confirmed on a larger group of patients.
Parvovirus gene regulation.

Introduction. The parvoviruses are among the smallest of the DNA animal viruses (Siegl et al., 1985). The genome is a linear single-stranded DNA of approximately 5 kb which is encapsidated in a naked icosahedral virion 20 to 26 nm in diameter. There are two or three capsid proteins which have overlapping amino acid sequences; the larger species have additional amino acids at the NH2 termini. The family Parvoviridae contains three genera. One, the densoviruses, contains viruses which have been isolated from several species of butterflies and moths. The other two genera, the parvoviruses and the dependoviruses (adeno-associated viruses), contain viruses which infect a broad range of vertebrates. Because our knowledge of the molecular biology of replication is significantly greater for the latter two genera, this review will concentrate on the regulation of gene expression in the parvoviruses and the dependoviruses.
Community Partnerships for Older Adults: A Case Study

Over the past several decades, federal policy has made states and communities increasingly more responsible for providing long-term care for older adults. The Community Partnerships for Older Adults, a national program of The Robert Wood Johnson Foundation, saw this as an opportunity to explore new, sustainable ways to meet current and future needs for community-based long-term care. This initiative focuses on collaborative organizational partnerships, a distinctive philosophy of teaching and learning through the exchange of experience between communities, and program learning focusing on known factors promoting organizational sustainability Using principles that emphasize the development of social capital and collective efficacy, the authors present a case study of the early experiences of this initiative to address the challenges inherent in meeting the growing supportive service needs of older adults. The implications of this multisite community intervention for social work education and practice in aging are discussed.
Impact of Wind Power and Photovoltaic Cell Power on Power System Stability Based on L Index

L index is proposed to assess the impact of wind power and photovoltaic cell power on system stability. L index is a voltage stability index which is based on power flow and can reflect the weak point where wind power and photovoltaic cell are connected to. Because the day trends of the two DGs are different, the impacts of stability are different. The example shows wind power system could cause voltage stability fluctuation. And the photovoltaic cell could enhance stability in strong light and high temperature in daytime.
Non‐ionic surfactant vesicles, niosomes, as a delivery system for the anti‐leishmanial drug, sodium stibogluconate

Liver and serum concentrations of antimony in the mouse have been determined after administration of sodium stibogluconate in the free, liposomal and niosomal form. High liver and low serum values were attained by the use of both vesicular formulations. Niosomal sodium stibogluconate was shown to be more active than free drug against experimental murine visceral leishmaniasis, an effect apparently dependent on maintaining high drug levels in the infected reticuloendothelial system.
Reduced Droop Effect in Nitride Light Emitting Diodes With Taper-Shaped Electron Blocking Layer

A taper-shaped AlGaN electron blocking layer (TEBL) has been designed and incorporated in InGaN/GaN light emitting diodes (LEDs) to promote hole injection and electron confinement under high current injection conditions. Fabricated LEDs with a TEBL exhibit reduced operating voltage, enhanced efficiency as well as alleviated droop effect, compared with those with a conventional bulk AlGaN EBL. The improvement is due to improved electron confinement and hole transportation as well as decreased electrostatic fields in the active region.
Ordinary CLT and WLLN Versions of L = λW

The familiar queueing principle expressed by the formula L = λW Little's law can be interpreted as a relation among strong laws of large numbers SLLNs. Here we prove central-limit-theorem CLT and weak-law-of-large-numbers WLLN versions of L = λW. For example, if the sequence of ordered pairs of interarrival times and waiting times is strictly stationary and satisfies a joint CLT, then the queue-length process also obeys a CLT with a related limiting distribution. In a previous paper we proved a functional-central-limit-theorem version of L = λW, without stationarity, by very different arguments. The two papers highlight the differences between establishing ordinary limit theorems and their functional-limit-theorem counterparts.
Habitat islands, genetic diversity, and gene flow in a Patagonian rodent

The effects of terrestrial habitat islands on gene flow and genetic diversity in animal populations have been predicted and discussed in theoretical terms, but empirical data are needed to test these predictions and provide an understanding of the relationships of life‐history characteristics to genetics of insular species. We studied saxicolous mice (Phyllotis xanthopygus) in Patagonia to explore genetic structure, phylogeography, and gene flow in a species inhabiting natural habitat islands. Phylogeographic analyses based on mtDNA sequences revealed two haplotype clades, which presumably reflect early Pleistocene factors that temporarily separated the mice into two geographically isolated groups. The Río Chubut, which lies within a glacial drainage basin bisecting northern Patagonia, might have affected gene flow in the species. Although we anticipated isolation by distance and founder phenomena associated with habitat islands, in some habitat patches we found evidence of high local genetic diversity. The amount of divergence in the mitochondrial cytochrome b gene (≈ 3.4%) in animals at a single locality could best be explained through a combination of historical factors and metapopulation source–sink theory. Demographic shifts, dispersal, and episodic recolonization are important in the life history and genetic population structure of P. xanthopygus.
VLSI implementation of the SIFT algorithm for pitch detection

Speech voicing classification and pitch detection are fundamental techniques in speech analysis. Voicing information provides valuable insights into the nature of the excitation source used in speech production, and the pitch information is useful to many speech processing applications. In 1972 John Markel developed a technique which combined the benefits of inverse linear predictive (LPC) analysis and simple short-time autocorrelation to extract essential speech parameters. The research resulted in the simplified inverse filter tracking (SIFT) algorithm for voiced/unvoiced classification of speech signals and pitch period determination [JD Markel, 1972]. Up until now this algorithm was available in various software implementations only. This paper describes an alternative real-time CMOS hardware implementation of this algorithm that is small enough to be implemented into a mobile communications device.
A Tutorial on Multi-frame Computational Super-resolution using Statistical Methods

The term super-resolution is used to describe methods aimed at recovering detail information of an imaged scene that would otherwise be lost during the normal imaging process. Here we discuss only digital cameras that process light reflected by the objects constituting a scene. A digital camera, consisting of optics a digital imaging sensor and signal processing hardware is able to capture a digital image of a scene. For digital cameras, resolution has to do with both the number of imaging elements per unit sensor area – which translates into the number of pixels per unit image area – as well as the information content of the digital image. Intuitively speaking, increasing the information content is directly related to increasing the number of pixels per unit area in the digital image such as to properly render the enlarged information content according to the Shannon sampling theorem. This tutorial is concerned with increasing the level of detail (i.e., information content) in a digital image by means of statistical processing algorithms starting from a set of several (usually) alias-afflicted images of the same scene, acquired from slightly different positions. Such techniques fall in the category of multi-frame computational super-resolution. We start be describing the maximum likelihood (ML) solution to this problem and then show how a maximum a posteriori (MAP) approach can improve upon the ML solution. We will discuss several solution strategies relying on such principles and point to their advantages and disadvantages. We conclude with a short overview of alternative super-resolution approaches.
The Interaction Effect of Perioperative Cotreatment with Dextromethorphan and Intravenous Lidocaine on Pain Relief and Recovery of Bowel Function After Laparoscopic Cholecystectomy

Both dextromethorphan (DM) and IV lidocaine improve postoperative pain relief. In the present study, we evaluated the interaction of DM and IV lidocaine on pain management after laparoscopic cholecystectomy (LC). One-hundred ASA physical status I or II patients scheduled for LC were randomized into four equal groups to receive either: (a) chlorpheniramine maleate (CPM) intramuscular injection (IM) 20 mg and IV normal saline (N/S) (group C); (b) DM 40 mg IM and IV N/S (group DM); (c) CPM 20 mg IM and IV lidocaine 3 mg · kg−1 · h−1 (group L); or (d) DM 40 mg IM and IV lidocaine (group DM+L). All treatments were administered 30 min before skin incision. Analgesic effects were evaluated using visual analog scale pain scores at rest and during coughing, time to meperidine request, total meperidine consumption, and the time to first passage of flatus after surgery. Patients of the DM+L group exhibited the best pain relief and fastest recovery of bowel function among groups. Patients in the DM and L groups had significantly better pain relief than those in the C group. The results showed an additional effect on pain relief and a synergistic effect on recovery of bowel function when DM was combined with IV lidocaine after LC.
Graph regularized seismic dictionary learning

We propose a new regularization method for sparse representation and denoising of seismic data. Our approach is particularly based on two ingredients, a sparse data representation in a learned dictionary and a similarity measure for image patches that is evaluated using the Laplacian matrix of a graph. Dictionary learning (DL) methods aim to find a data-dependent basis or a frame that admits a sparse data representation while capturing the characteristics of the given data. We propose two algorithms for dictionary learning based on clustering and singular value decomposition (SVD), called first and second dictionary construction (FDC and SDC). Besides employing an adapted dictionary we also consider a similarity measure for the local geometric structures of the seismic data using the Laplacian matrix of a graph. The proposed method achieves better denoising performance than existing denoising methods, both in terms of peak signal-to-noise ratio values and visual estimation of weak-even preservation. Comparisons of experimental results on field data using traditional FX deconvolution (FX-Decon), a prediction process in frequency-space domain, and curvelet thresholding methods are also provided. Department of Mathematics and Institute of Geophysics, Harbin Institute of Technology, Harbin, China, lina.liu@mathematik.uni-goettingen.de Department of Mathematics and Institute of Geophysics, Harbin Institute of Technology, Harbin, China, jma@hit.edu. cn Institute for Numerical and Applied Mathematics, University of Göttingen, Göttingen, Germany, plonka@math.uni-goettingen.de
A Community Mental Health Approach in Identifying People at Risk of Poor Mental Health: A Case Study in Hong Kong

People with mental health needs are often reluctant to seek help due to inaccessibility to service and also stigmatization, especially in Chinese societies. However, professional effort to identify the high-risk people is inadequate. In this paper the authors described a five-year community-based outreaching project, which aimed at identifying the high-risk groups in seven deprived and low-income communities territory wide and linking them up with mental health and social services. We assessed the project outcome by analysing the data (total number = 2181 participants) gathered on-site using the 20-item Centre for Epidemiological Studies Depression Scale (CES-D). The results of our analysis have shown that the project had successfully identified the high-risk groups (20.6%), with the following profile: the unemployed, housewife, the widowed and divorced and people with low education. They were referred to different services. The results of the post-intervention have indicated improved mental well-being of the participants who had received the services referred (n = 43). Our positive experience has confirmed the need of social workers to take an active role to reach out the unreachable, rather than be passive waiting them to come in.