Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of restricting environmental range of data to project current and future species distributions

We examine the consequences of restricting the range of environmental conditions over which niche-based models are developed to project potential future distributions of three selected European tree species to assess first, the importance of removing absences beyond species known distributions (‘‘naughty noughts’’) and second the importance of capturing the full environmental range of species. We found that restricting the environmental range of data strongly influenced the estimation of response curves, especially towards upper and lower ends of environmental ranges. This induces changes in the probability values towards upper and lower environmental boundaries, leading to more conservative scenarios in terms of changes in distribution projections. Using restricted data analogous to not capturing the fun species’ environmental range, reduces strongly the combinations of environmental conditions under which the models are calibrated, and reduces the applicability of the models for predictive purposes. This may generate unpredictable effects on the tails of the species response curves, yielding spurious projections into the future provided that probability of occurrence is not set to zero outside the environmental limits of the species. Indeed, as the restricted data does not capture the whole of the response curve, projections of future species distributions based of ecological niche modelling may be only valid if niche models are able to approach the complete response curve of environmental predictors.
The Effect of Hydrophilic Ionic Liquids 1-Ethyl-3-Methylimidazolium Lactate and Choline Lactate on Lipid Vesicle Fusion

Ionic liquids (ILs) are room-temperature molten salts that have applications in both physical sciences and more recently in the purification of proteins and lipids, gene transfection and sample preparation for electron microscopy (EM) studies. Transfection of genes into cells requires membrane fusion between the cell membrane and the transfection reagent, thus, ILs may be induce a membrane fusion event. To clarify the behavior of ILs with cell membranes the effect of ILs on model membranes, i.e., liposomes, were investigated. We used two standard ILs, 1-ethyl-3-methylimidazolium lactate ([EMI][Lac]) and choline lactate ([Ch][Lac]), and focused on whether these ILs can induce lipid vesicle fusion. Fluorescence resonance energy transfer and dynamic light scattering were employed to determine whether the ILs induced vesicle fusion. Vesicle solutions at low IL concentrations showed negligible fusion when compared with the controls in the absence of ILs. At concentrations of 30% (v/v), both types of ILs induced vesicle fusion up to 1.3 and 1.6 times the fluorescence intensity of the control in the presence of [Ch][Lac] and [EMI][Lac], respectively. This is the first demonstration that [EMI][Lac] and [Ch][Lac] induce vesicle fusion at high IL concentrations and this observation should have a significant influence on basic biophysical studies. Conversely, the ability to avoid vesicle fusion at low IL concentrations is clearly advantageous for EM studies of lipid samples and cells. This new information describing IL-lipid membrane interactions should impact EM observations examining cell morphology.
The Impact of Migration on HIV-1 Transmission in South Africa: A Study of Migrant and Nonmigrant Men and Their Partners

Background To investigate the association between migration and HIV infection among migrant and nonmigrant men and their rural partners. Goal The goal was to determine risk factors for HIV-1 infection in South Africa. Study Design This was a cross-sectional study of 196 migrant men and 130 of their rural partners, as well as 64 nonmigrant men and 98 rural women whose partners are nonmigrant. Male migrants were recruited at work in two urban centers, 100 km and 700 km from their rural homes. Rural partners were traced and invited to participate. Nonmigrant couples were recruited for comparison. The study involved administration of a detailed questionnaire and blood collection for HIV testing. Results Testing showed that 25.9% of migrant men and 12.7% of nonmigrant men were infected with HIV (P = 0.029; odds ratio = 2.4; 95% CI = 1.1–5.3). In multivariate analysis, main risk factors for male HIV infection were being a migrant, ever having used a condom, and having lived in four or more places during a lifetime. Being the partner of a migrant was not a significant risk factor for HIV infection among women; significant risk factors were reporting more than one current regular partner, being younger than 35 years, and having STD symptoms during the previous 4 months. Conclusion Migration is an independent risk factor for HIV infection among men. Workplace interventions are urgently needed to prevent further infections. High rates of HIV were found among rural women, and the migration status of the regular partner was not a major risk factor for HIV. Rural women lack access to appropriate prevention interventions, regardless of their partners’ migration status.
Evaluation of the MOZAIC Capacitive Hygrometer during the airborne field study CIRRUS-III

Abstract. The MOZAIC Capacitive Hygrometer (MCH) is usually operated aboard passenger aircraft in the framework of MOZAIC (Measurement of Ozone by Airbus In-Service Aircraft) for measuring atmospheric relative humidity (RH). In order to evaluate the performance of the MCH, the instrument was operated aboard a Learjet 35A research aircraft as part of the CIRRUS-III field study together with a closed-cell Lyman-α fluorescence hygrometer (Fast in situ Stratospheric Hygrometer, or FISH) and an open-path tunable diode laser system (Open-path Julich Stratospheric TDL ExpeRiment, or OJSTER) for water vapour measurement. After reducing the CIRRUS-III data set to data corresponding to MOZAIC aircraft operation conditions, the 1 Hz RH data cross correlation between the MCH and reference instruments FISH (clear sky) and OJSTER (in-cirrus) yielded a remarkably good agreement of R2 = 0.92 and slope m = 1.02 and provided a MCH uncertainty of 5% RH. Probability distribution functions of RH deduced from the MCH and reference instruments agreed well between 10 and 70% RH with respect to liquid water in the ambient temperature range of ca. −70 to −40 °C. The use of MCH data is limited to sensor temperatures above the calibration limit of Tsensor = −40 °C (corresponds to ambient temperature of Tambient = −70 °C at typical cruising speed of long-haul passenger aircraft). Good performance of the MCH for clear sky as well as for in-cirrus conditions demonstrated the sensor robustness also for operation inside ice clouds.
Comparison of a single‐channel EEG sleep study to polysomnography

An accurate home sleep study to assess electroencephalography (EEG)‐based sleep stages and EEG power would be advantageous for both clinical and research purposes, such as for longitudinal studies measuring changes in sleep stages over time. The purpose of this study was to compare sleep scoring of a single‐channel EEG recorded simultaneously on the forehead against attended polysomnography. Participants were recruited from both a clinical sleep centre and a longitudinal research study investigating cognitively normal ageing and Alzheimer's disease. Analysis for overall epoch‐by‐epoch agreement found strong and substantial agreement between the single‐channel EEG compared to polysomnography (κ = 0.67). Slow wave activity in the frontal regions was also similar when comparing the single‐channel EEG device to polysomnography. As expected, Stage N1 showed poor agreement (sensitivity 0.2) due to lack of occipital electrodes. Other sleep parameters, such as sleep latency and rapid eye movement (REM) onset latency, had decreased agreement. Participants with disrupted sleep consolidation, such as from obstructive sleep apnea, also had poor agreement. We suspect that disagreement in sleep parameters between the single‐channel EEG and polysomnography is due partially to altered waveform morphology and/or poorer signal quality in the single‐channel derivation. Our results show that single‐channel EEG provides comparable results to polysomnography in assessing REM, combined Stages N2 and N3 sleep and several other parameters, including frontal slow wave activity. The data establish that single‐channel EEG can be a useful research tool.
c7E3Fab Reduces Postischemic Leukocyte-Thrombocyte Interaction Mediated by Fibrinogen: Implications for Myocardial Reperfusion Injury

Reperfusion injury after coronary occlusion is in part mediated by leukocyte activation and adhesion. Platelets may interact with polymorphonuclear granulocytes (PMNs), causing aggravated reperfusion injury. We studied whether c7E3Fab, a chimeric Fab fragment blocking platelet glycoprotein (GP) IIb/IIIa, decreases PMN-platelet–dependent myocardial dysfunction after ischemia. Isolated guinea pig hearts (n=5 per group) perfused at a constant flow of 5 mL/min were subjected to ischemia (15 minutes, 37°C) and reperfusion. Human PMNs (10×106 cells, 3 mL), platelets (400×106, 3 mL), and fibrinogen (1 mg/mL) were infused for 3 minutes after 2 minutes of reperfusion, with or without c7E3Fab. Flow cytometry detected GPIIb/IIIa (platelets) and MAC-1 (aM&bgr;2, PMNs) as well as coaggregates of both in the effluent, whereas double-fluorescence microscopy visualized intracoronary PMN-platelet coaggregates. Postischemic recovery of pressure-volume work (12–cm H2O preload and 60–mm Hg afterload) was defined as the ratio of postischemic to preischemic external heart work (mean±SEM). c7E3Fab reduced platelet GPIIb/IIIa detection to 10% of controls, blocked a transcoronary MAC-1 increase (+25% without versus −23% with c7E3Fab), and inhibited PMN-platelet coaggregation in the effluent (49±12% without versus 17±2% with c7E3Fab) as well as in the hearts themselves (5.0±0.7/cm2 without versus 1.2±0.3/cm2 surface area with c7E3Fab). Postischemic recovery of external heart work (83±5% in cell-free hearts) declined to 46±4% after postischemic PMN-platelet infusion, but not in the presence of c7E3Fab (74±11%) or LPM19c (71±6%). We conclude that c7E3Fab inhibits formation of PMN-platelet aggregates during myocardial reperfusion, an effect that protects against PMN-platelet–dependent stunning.
Expressive uses of the countertransference : Notes to the patient from oneself

Expressive Uses of the Countertransference—Notes to the Patient from Oneself Christopher Bollas, Ph.D. AN ANALYST'S COUNTERTRANSFERENCE IS A CONTINUOUS internal response to the presence of an analysand that necessitates a different kind of attentiveness of the analyst's part from that which he gives the patient. Although many patients create through the transference an environment that is favorable to the analyst's good enough state of mind, we are more mindful these days of those patients who represent their existence through the other's moods and thoughts, and, such a countertransference will compel the analyst to take himself as the object of interest, insight, and quite possibly of "cure". Like many clinicians these days I entertain the possibility that for differing reasons and in varied ways analysands recreate their infantile life in the transference in such a determined and unconsciously accomplished way that the analyst is compelled to relive elements of this infantile history through his countertransference. Patients may enact fragments of a parent inviting us unconsciously to learn though experience how it felt to be the child of such a parent, and ironically, they may almost violently hyperbolize that
Pytheas: Enabling Data-Driven Quality of Experience Optimization Using Group-Based Exploration-Exploitation

Content providers are increasingly using data-driven mechanisms to optimize quality of experience (QoE). Many existing approaches formulate this process as a prediction problem of learning optimal decisions (e.g., server, bitrate, relay) based on observed QoE of recent sessions. While prediction-based mechanisms have shown promising QoE improvements, they are necessarily incomplete as they: (1) suffer from many known biases (e.g., incomplete visibility) and (2) cannot respond to sudden changes (e.g., load changes). Drawing a parallel from machine learning, we argue that data-driven QoE optimization should instead be cast as a real-time exploration and exploitation (E2) process rather than as a prediction problem. Adopting E2 in network applications, however, introduces key architectural (e.g., how to update decisions in real time with fresh data) and algorithmic (e.g., capturing complex interactions between session features vs. QoE) challenges. We present Pytheas, a framework which addresses these challenges using a group-based E2 mechanism. The insight is that application sessions sharing the same features (e.g., IP prefix, location) can be grouped so that we can run E2 algorithms at a per-group granularity. This naturally captures the complex interactions and is amenable to realtime control with fresh measurements. Using an end-to-end implementation and a proof-of-concept deployment in CloudLab, we show that Pytheas improves video QoE over a state-of-the-art prediction-based system by up to 31% on average and 78% on 90th percentile of persession QoE.
Performance Evaluation of the Becton Dickinson FACSPresto™ Near-Patient CD4 Instrument in a Laboratory and Typical Field Clinic Setting in South Africa

Background The BD-FACSPresto™ CD4 is a new, point-of-care (POC) instrument utilising finger-stick capillary blood sampling. This study evaluated its performance against predicate CD4 testing in South Africa. Methods Phase-I testing: HIV+ patient samples (n = 214) were analysed on the Presto™ under ideal laboratory conditions using venous blood. During Phase-II, 135 patients were capillary-bled for CD4 testing on FACSPresto™, performed according to manufacturer instruction. Comparative statistical analyses against predicate PLG/CD4 method and industry standards were done using GraphPad Prism 6. It included Bland-Altman with 95% limits of agreement (LOA) and percentage similarity with coefficient of variation (%CV) analyses for absolute CD4 count (cells/μl) and CD4 percentage of lymphocytes (CD4%). Results In Phase-I, 179/217 samples yielded reportable results with Presto™ using venous blood filled cartridges. Compared to predicate, a mean bias of 40.4±45.8 (LOA of -49.2 to 130.2) and %similarity (%CV) of 106.1%±7.75 (7.3%) was noted for CD4 absolute counts. In Phase-2 field study, 118/135 capillary-bled Presto™ samples resulted CD4 parameters. Compared to predicate, a mean bias of 50.2±92.8 (LOA of -131.7 to 232) with %similarity (%CV) 105%±10.8 (10.3%), and 2.87±2.7 (LOA of -8.2 to 2.5) with similarity of 94.7±6.5% (6.83%) noted for absolute CD4 and CD4% respectively. No significant clinical differences were indicated for either parameter using two sampling methods. Conclusion The Presto™ produced remarkable precision to predicate methods, irrespective of venous or capillary blood sampling. A consistent, clinically insignificant over-estimation (5–7%) of counts against PLG/CD4 and equivalency to FACSCount™ was noted. Further field studies are awaited to confirm longer-term use.
Bisulfighter: accurate detection of methylated cytosines and differentially methylated regions

Analysis of bisulfite sequencing data usually requires two tasks: to call methylated cytosines (mCs) in a sample, and to detect differentially methylated regions (DMRs) between paired samples. Although numerous tools have been proposed for mC calling, methods for DMR detection have been largely limited. Here, we present Bisulfighter, a new software package for detecting mCs and DMRs from bisulfite sequencing data. Bisulfighter combines the LAST alignment tool for mC calling, and a novel framework for DMR detection based on hidden Markov models (HMMs). Unlike previous attempts that depend on empirical parameters, Bisulfighter can use the expectation-maximization algorithm for HMMs to adjust parameters for each data set. We conduct extensive experiments in which accuracy of mC calling and DMR detection is evaluated on simulated data with various mC contexts, read qualities, sequencing depths and DMR lengths, as well as on real data from a wide range of biological processes. We demonstrate that Bisulfighter consistently achieves better accuracy than other published tools, providing greater sensitivity for mCs with fewer false positives, more precise estimates of mC levels, more exact locations of DMRs and better agreement of DMRs with gene expression and DNase I hypersensitivity. The source code is available at http://epigenome.cbrc. jp/bisulfighter.
Green synthesis of well-defined spherical PbS quantum dots and its potential in biomedical imaging research and biosensing

In this research, we present a facile, effective and green route for the synthesis of well-defined spherical lead sulfide (PbS) quantum dots (QDs) through the reaction between lead nitrate and sodium sulphide by virtue of its strong reduction and selective interaction abilities without using any surfactant, and evaluate its potential for use in biomedical imaging and biosensing applications. The average crystallite size using Scherrer's formula was about 13 nm and the calculated lattice constant using Bragg's equation was 0.5950 nm, which was very close to the value in the standard card JCPDS file No. 5–592, and the crystal structure of PbS QDs was in its cubic phase. The synthesized particles had well-defined spherical morphology, and the photoluminescence (PL) study showed that the emission spectrum was a strong and narrow band with high intensity which confirmed the high-quality luminescence properties of the prepared PbS QDs. A possible formation mechanism of the PbS QDs and its Potential in Biomedical Imaging Research and Biosensing has also been put forward and discussed.
Quantifying infants' statistical word segmentation: a meta-analysis

Theories of language acquisition and perceptual learning increasingly rely on statistical learning mechanisms. The current meta-analysis aims to clarify the robustness of this capacity in infancy within the word segmentation literature. Our analysis reveals a significant, small effect size for conceptual replications of Saffran, Aslin, & Newport (1996), and a nonsignificant effect across all studies that incorporate transitional probabilities to segment words. In both conceptual replications and the broader literature, however, statistical learning is moderated by whether stimuli are naturally produced or synthesized. These findings invite deeper questions about the complex factors that influence statistical learning, and the role of statistical learning in language acquisition.
Cascade control for nonlinear non-minimum phase system based on backstepping approach and input output linearization

The problem of tracking control of nonlinear systems whose the zero dynamics are unstable is addressed in this paper. It is shown that, using a novel cascade structure where the backstepping approach is given to stabilise the internal dynamics and the standard input output linearization to stabilise the external dynamics. Assuming high-gain feedback for the external dynamics, a stability analysis of the global system is provided based on singular perturbation theory. Simulations of an inverted cart-pendulum illustrate the theoretical results. Keywords— tracking control, Non-minimum phase system, integrator backstepping, input output linearization, singular perturbed system.
Architecture-driven platform independent deterministic replay for distributed hard real-time systems

Distributed hard real-time systems have become a major component of many advanced technical products. Means to ensure their proper quality are thus of paramount importance. To ensure high quality software, besides preventive means also cost-effective techniques for defect removal are important. The later activity in practice includes testing in order to detect failures, subsequent diagnosis in order to pin down the observed failure to a defect, and finally the proper removal of the defect. In this chain of activities, finding the cause of a failure is often a rather difficult and long-winded undertaking. In the domain of embedded real-time systems the problem is even harder than in a standard environment because of the real-time behavior and hardware heterogeneity (development vs. target platform). Both renders the deterministic replay of faulty behavior a hard problem which today can only be addressed when a substantial amount of additional monitoring hardware is added to the system. The paper proposes to minimize the required additional hardware using an architecture-driven approach which exploits the high-level information available at the architectural level in order to achieve platform independent deterministic replay for distributed hard real-time systems at relative low cost.
Learning controllers for human-robot interaction

In order for robots to assist and interact with humans, they must be socially intelligent. Social intelligence is the ability to communicate and understand meaning through social interaction. Artificial intelligence can be broadly described, as an effort to describe and simulate the property of human intelligence inside of a computational model. In most cases, this simulation happens in a vacuum. An agent, such as a robot, maintains a computational model which includes all information required to make decisions. This internal computational representation is what we consider its intellect. Information may enter this model through perception, and be expressed in the form of action. This separation of knowing and doing can be quite effective for representing certain types of intelligence. However it does not lend itself to simulating social cognition. In order to communicate socially, an agent must be able to affect change in the mental representation of other agents, as well as the physical world. However, social interaction and the creation of meaning is inherently different than interactions with the physical world. Because there are no mathematical models which describe how actions and perceptions affect the mental representations of a human, we cannot hope to build an interactive agent by directly simulating this process. For this reason, when building artificial social intelligence, we need to pay attention to prevailing theories on how humans learn. Many popular theories from cognitive science, social psychology and language development suggest that action and perception are not subordinate to mental representations. Instead, mental representations are a result of action and perception that results from an agent's interaction with an environment and other agents. In particular, social learning theory says that the process which allows agents to understand one another happens from the ground up, starting with action and perception, and resulting in the shared mental representations, and understanding of how to affect change in the representations of others. This thesis addresses the problem of building social intelligence into robotic systems using computational learning and adaptive control. We focus on the problem of how to use decision theoretic planning for learning to interact with humans from the bottom up. We first examine the use of affect recognition in designing human-friendly control strategies. Next, we address the problem of defining subjective measures of interactivity by leveraging human expertise. Finally, we define and evaluate a method for participating in the process of socially situated cognition. We emphasize learning to predict and modulate observable responses of the human rather than attempting to directly infer their mental or emotional states. The effectiveness of this method is demonstrated experimentally using custom robotic systems.