Miracle-dz/UniFAR-FTUs huggingface dataset:
Capturing the Context of Maternal Deaths from Verbal Autopsies: A Reliability Study of the Maternal Data Extraction Tool (M-DET)

Background The availability of quality data to inform policy is essential to reduce maternal deaths. To characterize maternal deaths in settings without complete vital registration systems, we designed and assessed the inter-rater reliability of a tool to systematically extract data and characterize the events that precede a nationally representative sample of maternal deaths in India. Method/Principal Findings Of 1017 nationally representative pregnancy-related deaths, which occurred between 2001 and 2003, we randomly selected 105 reports. Two independent coders used the maternal data extraction tool (questions with coding guidelines) to collect information on antenatal care access, final pregnancy outcome; planned place of birth and care provider; community consultation, transport, admission, hospital referral; and verification of cause of death assignment. Kappa estimated inter-rater agreement was calculated and classified as poor (K≤0.4), moderate (K = 0.4-≤0.6), substantial (K = 0.6-≤0.8) and high (K>0.8) using the criteria from Landis & Koch. The data extraction tool had high agreement for gestational age, pregnancy outcome, transport, death en route and admission to hospital; substantial agreement for receipt of antenatal care, planned place of birth, readmission and referral to higher level hospital, and whether or not death occurred in the intrapartum period; moderate to substantial agreement for classification of deaths as direct or indirect obstetric deaths or incidental deaths; moderate agreement for classification of community healthcare consultation and total number of healthcare contacts; and poor agreement for the classification of deaths as sudden deaths and other/unknown cause of death. The ability of the tool to identify the most-responsible-person in labour varied from moderate agreement to high agreement. Conclusions This data extraction tool achieved good inter-rater reliability and can be used to collect data on events surrounding maternal deaths and for verification/improvement of underlying cause of death.
Midwives' Experiences of Working with Highly Anxious Childbearing Women

Anxiety is a normal human phenomenon. It is fundamental to our survival as a species, allowing us to adjust and plan for the future and prompts us to seek help and security from others. High levels of anxiety during childbearing are associated with poor fetal development, behavioural/emotional problems in children and adolescents, prolonged labours, increased obstetric intervention, impaired lactogenesis and bonding problems. Working with highly anxious childbearing women can be a challenging experience for independent lead maternity care midwives. This qualitative investigation guided by the principles of feminist research examined four independent midwives experiences of working with highly anxious childbearing women. Data were collected by interview, and thematic analysis found three themes that encapsulated the experience. The resultant themes were of: 1) challenging partnerships, 2) making a difference and 3) realising own limitations. The midwives, while very committed to their highly anxious clients, experienced considerable stress while endeavouring to provide effective care. This stress is of concern to midwives and midwifery as it makes midwives vulnerable to burnout. Given the damage that high levels of unchecked anxiety have on childbearing women and their families, midwifery has to look for safe and effective ways to work with these women. Recommendations for practice are based around negotiating boundaries to the midwife-client relationship, increased help and support for midwives, especially clinical supervision, better midwifery education, and continuous professional development in relation to maternal mental health, and properly resourced and funded maternal mental health services.
Documentary With Ephemeral Media: Curation Practices in Online Social Spaces

New hardware such as mobile handheld devices and digital cameras; new online social venues such as social networking, microblogging, and online photo sharing sites; and new infrastructures such as the global positioning system are beginning to establish new practices—what the author refers to as “sociolocative”—that combine data about a physical location, such as a geotag, with a virtual social act. This research investigates the phenomenon of documentary broadcasting, whereby individuals curate lasting descriptions and commentaries about a location for a public audience, often using the photo sharing site, Flickr. Unlike many photographs shared online, the subject of a documentary post is always a place and not the activities nor identity of the broadcaster himself or herself. When presented together as curated narratives, posted images transform Flickr into a virtual public “gallery space” that captures, presents, and preserves aspects of a place that may last longer than the physical location itself.
Melanopsin-dependent light avoidance in neonatal mice

Melanopsin-expressing, intrinsically photosensitive retinal ganglion cells (ipRGCs) form a light-sensitive system separate from rods and cones. Direct light stimulation of ipRGCs can regulate many nonimage-forming visual functions such as photoentrainment of circadian rhythms and pupil responses, and can intensify migraine headache in adults. In mice, ipRGCs are light responsive as early as the day of birth. In contrast, their eyelids do not open until 12–13 d after birth (P12–13), and light signaling from rods and cones does not begin until approximately P10. No physiological or behavioral function is established for ipRGCs in neonates before the onset of rod and cone signaling. Here we report that mouse pups as young as P6 will completely turn away from a light. Light-induced responses of ipRGCs could be readily recorded in retinas of pups younger than P9, and we found no evidence for rod- and cone-mediated visual signaling to the RGCs of these younger mice. These results confirm that negative phototaxis is evident before the onset of rod- and cone-mediated visual signaling, and well before the onset of image-forming vision. Negative phototaxis was absent in mice lacking melanopsin. We conclude that light activation of melanopsin ipRGCs is necessary and sufficient for negative phototaxis. These results strongly suggest that light activation of ipRGCs may regulate physiological functions such as sleep/wake cycles in preterm and neonatal infants.
A predictive interface based on virtual and augmented reality for task specification in a Web telerobotic system

A very interesting robotics area is the high-level tasks' specification, and the way a user-robot interface can facilitate programming complex actions to be executed on real environments. This paper shows a novel contribution in the user-robot interaction domain, and particularly in the web robotics field. The user, who is in the control loop, is able to specify the robot actions over a simulated scenario (running off-line), assisted with 3D virtual and augmented reality. Then, once the task is defined, it can be easily executed over the real scenario (running online). To get its main goal (i.e. task specification) working in real life scenarios, the system incorporates automatic object recognition and visually-guided grasping among others capabilities.
Social Representational Correlates of Attitudes Toward Peace and War: A Cross-Cultural Analysis in the United States and Denmark

This research aimed at examining the possibility that certain social representations of peace and war are, more than others, (in)compatible with support for warfare. It also aimed at investigating the weight of political culture on the realization of this possibility. Using the framework of social representations theory (Moscovici, 1961/2008), this study surveyed undergraduate students from 3 universities located in 2 countries: the United States and Denmark. Analyses conducted at the cultural and individual levels (Leung, 1989) show that the notions of peace as social transformation and of war as direct and indirect violence tend to be more prevalent among anti-war supporters and Danish participants, and indicate that the values and ideas of peace and war that are most incompatible with support of warfare are equality, fear, and poverty. Results are discussed with respect to their theoretical contribution and policy implications.
The Tumor Suppressor Maspin Mediates E2F1-Induced Sensitivity of Cancer Cells to Chemotherapy

The E2F1 transcription factor is a critical downstream target of the tumor suppressor RB. When activated, E2F1 can induce cell proliferation and/or apoptosis. In addition, E2F1 overexpression sensitizes cancer cells to chemotherapeutic drugs. In a screen for genes that are regulated synergistically by E2F1 and chemotherapy in cancer cells, we identified the proapoptotic tumor suppressor gene maspin (mammary serine protease inhibitor) as a novel E2F1-regulated gene. In line with being an E2F-regulated gene, maspin expression is inhibited by short hairpin RNA directed against E2F1 and increases upon activation of endogenous E2F. Furthermore, maspin mRNA and protein levels are elevated upon activation of exogenous E2F1. Importantly, we show that E2F1-mediated upregulation of maspin is enhanced by chemotherapeutic drugs, and inhibition of maspin expression significantly impairs the ability of E2F1 to promote chemotherapy-induced apoptosis. Summarily, our data indicate that maspin is an important effector of E2F1-induced chemosensitization. Mol Cancer Res; 8(3); 363–72
Learning embeddings for indexing, retrieval, and classification, with applications to object and shape recognition in image databases

Nearest neighbor retrieval is the task of identifying, given a database of objects and a query object, the objects in the database that are the most similar to the query. Retrieving nearest neighbors is a necessary component of many practical applications, in fields as diverse as computer vision, pattern recognition, multimedia databases, bioinformatics, and computer networks. This thesis proposes new methods for improving the efficiency and accuracy of nearest neighbor retrieval and classification in spaces with computationally expensive distance measures. The first contribution of this thesis is the BoostMap algorithm for embedding arbitrary spaces into a vector space with a computationally efficient distance measure. Using this approach, an approximate set of nearest neighbors can be retrieved efficiently---often orders of magnitude faster than retrieval using the exact distance measure in the original space. In BoostMap, embedding construction is treated as a machine learning problem. The learning-based formulation leads to an algorithm that directly maximizes the amount of nearest neighbor structure preserved by the embedding, without making any assumptions about the underlying geometry of the original space. The second contribution consists of extending BoostMap to produce, together with the embedding, a query-sensitive distance measure for the target space of the embedding. In high-dimensional spaces, query-sensitive distance measures allow for automatic selection of the dimensions that are the most informative for each specific query object. The third contribution is a method for speeding up nearest neighbor classification by combining multiple embedding-based nearest neighbor classifiers in a cascade structure. In cascade-based classification, computationally efficient classifiers are used to quickly classify easy cases, and classifiers that are more computationally expensive and also more accurate are only applied to objects that are harder to classify. The proposed methods are evaluated experimentally in several different applications: hand shape recognition, off-line character recognition, online character recognition, and efficient retrieval of time series. In all datasets, the proposed methods lead to significant improvements in accuracy and efficiency compared to existing state-of-the-art methods.
A Parallel Implementation of a Fluid Flow Simulation using Smoothed Particle Hydrodynamics

The reaction of fluid or gas flowing around an obstacle is a common engineering problem. Computer simulations are often used to measure and visualize the physical processes involved. In this report, we will discuss a parallel implementation of a simulation using the Smooth Particle Hydrodynamics (SPH) approach to fluid flow. We will discuss the design decisions made during development, problems encountered during implementation, and parallel performance issues. Section 2 will introduce the fluid flow problem, the SPH technique, and our project motivations. Section 3 will discuss our first O(N 2) serial version of the simulator. Section 4
The cognitive power meter: Looking beyond the smart meter

The smart meter is often heralded as the key component supporting energy displays that can notify home occupants of their energy usage. But, a smart meter is only a digital power meter with enhanced communications capabilities - it is not actually smart. We need to look beyond the smart meter and define what intelligence is needed to actually make a meter smart. One area with promise is load disaggregation. Load disaggregation can be used to determine what loads contributing to the consumption reading at the smart meter. A smart meter incorporating load disaggregation intelligence can be seen as going beyond the traditional smart meter - what we call a cognitive power meter (c-meter). However, using load disaggregation, in its current form, is not feasible. We critically review the requirements for a c-meter and provide insights as to how load disaggregation research needs to change to make the c-meters a reality.
Elotuzumab: a novel immune-stimulating therapy to treat multiple myeloma

ABSTRACT Introduction: Multiple myeloma (MM), constantly remains debilitating disease, consequently leading to death. Clinical trials involving drugs with different mechanisms of action, carry the expectancy for improvement of treatment outcomes. The results of the currently published studies on the monoclonal antibodies, in particular elotuzumab confirm previous expectations of improving treatment outcomes of such therapy in MM patients. Areas covered: This humanized monoclonal antibody targeting surface glycoprotein CS1, expressed commonly on plasma cells and certain cells of the immune system, stimulates the immune system to fight against MM cells. Elotuzumab in the combination with len/dex has been approved by the FDA for treatment of relapsed/refractory MM patients who have received one to three prior therapies. Expert commentary: This review summarizes the chemistry, mechanism of action and preclinical and clinical studies, pharmacodynamics, pharmacokinetics, safety and toxicity of elotuzumab in terms of MM treatment and its potential application in the future.
Noninvasive genetic tracking of the endangered Pyrenean brown bear population

Pyrenean brown bears Ursus arctos are threatened with extinction. Management efforts to preserve this population require a comprehensive knowledge of the number and sex of the remaining individuals and their respective home ranges. This goal has been achieved using a combination of noninvasive genetic sampling of hair and faeces collected in the field and corresponding track size data. Genotypic data were collected at 24 micrdsatellite loci using a rigorous multiple‐tubes approach to avoid genotyping errors associated with low quantities of DNA. Based on field and genetic data, the Pyrenean population was shown to be composed at least of one yearling, three adult males, and one adult female. These data indicate that extinction of the Pyrenean brown bear population is imminent without population augmentation. To preserve the remaining Pyrenean gene pool and increase genetic diversity, we suggest that managers consider population augmentation using only females. This study demonstrates that comprehensive knowledge of endangered small populations of mammals can be obtained using noninvasive genetic sampling.
The effect of sertraline add-on to brief dynamic psychotherapy for the treatment of postpartum depression: a randomized, double-blind, placebo-controlled study.

OBJECTIVE The efficacy of antidepressants in the treatment of mild-to-moderate postpartum depression and the possible advantage of the combination of an antidepressant and psychotherapy have not been adequately studied. We hypothesized that psychotherapy and concurrent antidepressant treatment would be more effective than psychotherapy alone in the treatment of postpartum depression. METHOD Women diagnosed with mild-to-moderate severity postpartum depression according to DSM-IV-TR criteria were enrolled in an 8-week, randomized, double-blind, placebo-controlled study. Participants received 12 sessions of focused brief dynamic psychotherapy (BDP) concurrently with 8-week sertraline or placebo treatment, followed by a 4-week open phase. Primary outcomes were depression scores measured by the Montgomery-Asberg Depression Rating Scale (MADRS) and remission rates. The study was conducted in a referral center from May 2008 to September 2010. RESULTS Forty of 42 women randomized into the study entered the intent-to-treat analysis. A significant time effect for the MADRS was observed (F4,35 = 21.3, P < .0001); however, no time-by-group effect was found for any outcome measure. Response rates were 70% and 55% for the drug and placebo groups, respectively, and remission rates were 65% and 50%, respectively, with no significant difference between groups. CONCLUSION While both treatment groups improved significantly, the results of the present study did not demonstrate a significant benefit for sertraline over placebo as an add-on treatment to focused BDP in mild-to-moderate postpartum depression. Because of the study's small sample, the results cannot be viewed as definitive, and a much larger study is needed to confirm these results. Furthermore, the promising potential of focused BDP as an intervention in this population should be studied under controlled conditions. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01028482.
Oxygen uptake rates and liver‐specific functions of hepatocyte and 3T3 fibroblast co‐cultures

Bioartificial liver (BAL) devices have been developed to treat patients undergoing acute liver failure. One of the most important parameters to consider in designing these devices is the oxygen consumption rate of the seeded hepatocytes which are known to have oxygen consumption rates 10 times higher than most other cell types. Hepatocytes in various culture configurations have been tested in BAL devices including those formats that involve co‐culture of hepatocytes with other cell types. In this study, we investigated, for the first time, oxygen uptake rates (OUR)s of hepatocytes co‐cultured with 3T3‐J2 fibroblasts at various hepatocyte to fibroblast seeding ratios. OURs were determined by measuring the rate of oxygen disappearance using a ruthenium‐coated optical probe after closing and sealing the culture dish. Albumin and urea production rates were measured to assess hepatocyte function. Lower hepatocyte density co‐cultures demonstrated significantly higher OURs (2 to 3.5‐fold) and liver‐ specific functions (1.6‐fold for albumin and 4.5‐fold for urea production) on a per cell basis than those seeded at higher densities. Increases in OUR correlated well with increased liver‐specific functions. OURs (Vm) were modeled by fitting Michaelis–Menten kinetics and the model predictions closely correlated with the experimental data. This study provides useful information for predicting BAL design parameters that will avoid oxygen limitations, as well as maximize metabolic functions. Biotechnol. Bioeng. 2007;97: 188–199. © 2006 Wiley Periodicals, Inc.
Simultaneous Bayesian Estimation of Excitatory and Inhibitory Synaptic Conductances by Exploiting Multiple Recorded Trials

Advanced statistical methods have enabled trial-by-trial inference of the underlying excitatory and inhibitory synaptic conductances (SCs) of membrane-potential recordings. Simultaneous inference of both excitatory and inhibitory SCs sheds light on the neural circuits underlying the neural activity and advances our understanding of neural information processing. Conventional Bayesian methods can infer excitatory and inhibitory SCs based on a single trial of observed membrane potential. However, if multiple recorded trials are available, this typically leads to suboptimal estimation because they neglect common statistics (of synaptic inputs (SIs)) across trials. Here, we establish a new expectation maximization (EM) algorithm that improves such single-trial Bayesian methods by exploiting multiple recorded trials to extract common SI statistics across the trials. In this paper, the proposed EM algorithm is embedded in parallel Kalman filters or particle filters for multiple recorded trials to integrate their outputs to iteratively update the common SI statistics. These statistics are then used to infer the excitatory and inhibitory SCs of individual trials. We demonstrate the superior performance of multiple-trial Kalman filtering (MtKF) and particle filtering (MtPF) relative to that of the corresponding single-trial methods. While relative estimation error of excitatory and inhibitory SCs is known to depend on the level of current injection into a cell, our numerical simulations using MtKF show that both excitatory and inhibitory SCs are reliably inferred using an optimal level of current injection. Finally, we validate the robustness and applicability of our technique through simulation studies, and we apply MtKF to in vivo data recorded from the rat barrel cortex.
L . Title : Diagrams in contracts : Fostering understanding in global business communication Year : 2017

Research problem: Business-to-business contracts are complex communication artifacts, often considered “legal stuff” and the exclusive domain of lawyers. However, many other stakeholders without a legal background are involved in the negotiation, drafting, approval and implementation of contracts, and their contributions are essential for successful business relationships. How can we ensure that all stakeholders in the global business context – whatever their native language or professional background – easily and accurately understand contract documents? This study suggests that integrating diagrams in contracts can result in faster and more accurate comprehension, for both native and non-native speakers of English. Literature Review: We focused on the following research topics: 1) how to integrate text and visuals in order to create more effective instructions, since we conceptualize contracts as a type of business instructions; 2) cognitive load theory, as it may help explaining why contracts are so hard to understand and why text-visuals integration may ameliorate their understandability; 3) cognitive styles, as individual differences may affect how individuals process verbal and visual information, thus allowing to explore the limitations of our suggested approach; 4) the English lingua franca spoken by business professionals in international settings, their needs and challenges, and how pragmatic approaches are needed to ensure successful communication. Methodology: We conducted an experiment with 122 contract experts from 24 countries. The research participants were asked to complete a series of comprehension tasks on a contract, which was provided in either a traditional, text-only version or in a version that included diagrams as complements to the text. In addition to measuring answering speed and accuracy, we asked the participants to provide information about their educational background, mother tongue, perceived mental effort in task completion, as well as to fill out the