Miracle-dz/UniFAR-FTUs huggingface dataset:
The Trophy Hunting of African Lions: Scale, Current Management Practices and Factors Undermining Sustainability

The trophy hunting of lions Panthera leo is contentious due to uncertainty concerning conservation impacts and because of highly polarised opinions about the practice. African lions are hunted across at least ∼558,000 km2, which comprises 27–32% of the lion range in countries where trophy hunting of the species is permitted. Consequently, trophy hunting has potential to impart significant positive or negative impacts on lions. Several studies have demonstrated that excessive trophy harvests have driven lion population declines. There have been several attempts by protectionist non-governmental organisations to reduce or preclude trophy hunting via restrictions on the import and export of lion trophies. We document the management of lion hunting in Africa and highlight challenges which need addressing to achieve sustainability. Problems include: unscientific bases for quota setting; excessive quotas and off-takes in some countries; fixed quotas which encourage over-harvest; and lack of restrictions on the age of lions that can be hunted. Key interventions needed to make lion hunting more sustainable, include implementation of: enforced age restrictions; improved trophy monitoring; adaptive management of quotas and a minimum length of lion hunts of at least 21 days. Some range states have made important steps towards implementing such improved management and off-takes have fallen steeply in recent years. For example age restrictions have been introduced in Tanzania and in Niassa in Mozambique, and are being considered for Benin and Zimbabwe, several states have reduced quotas, and Zimbabwe is implementing trophy monitoring. However, further reforms are needed to ensure sustainability and reduce conservation problems associated with the practice while allowing retention of associated financial incentives for conservation.
Gene Flow Across Genus Barriers – Conjugation of Dinoroseobacter shibae’s 191-kb Killer Plasmid into Phaeobacter inhibens and AHL-mediated Expression of Type IV Secretion Systems

Rhodobacteraceae harbor a conspicuous wealth of extrachromosomal replicons (ECRs) and therefore the exchange of genetic material via horizontal transfer has been supposed to be a major evolutionary driving force. Many plasmids in this group encode type IV secretion systems (T4SS) that are expected to mediate transfer of proteins and/or DNA into host cells, but no experimental evidence of either has yet been provided. Dinoroseobacter shibae, a species of the Roseobacter group within the Rhodobacteraceae family, contains five ECRs that are crucial for anaerobic growth, survival under starvation and the pathogenicity of this model organism. Here we tagged two syntenous but compatible RepABC-type plasmids of 191 and 126-kb size, each encoding a T4SS, with antibiotic resistance genes and demonstrated their conjugational transfer into a distantly related Roseobacter species, namely Phaeobacter inhibens. Pulsed field gel electrophoresis showed transfer of those replicons into the recipient both individually but also together documenting the efficiency of conjugation. We then studied the influence of externally added quorum sensing (QS) signals on the expression of the T4SS located on the sister plasmids. A QS deficient D. shibae null mutant (ΔluxI1) lacking synthesis of N-acyl-homoserine lactones (AHLs) was cultivated with a wide spectrum of chemically diverse long-chain AHLs. All AHLs with lengths of the acid side-chain ≥14 reverted the ΔluxI1 phenotype to wild-type. Expression of the T4SS was induced up to log2 ∼3fold above wild-type level. We hypothesize that conjugation in roseobacters is QS-controlled and that the QS system may detect a wide array of long-chain AHLs at the cell surface.
Two different regulatory T cell populations that promote corneal allograft survival.

PURPOSE To compare and contrast the T regulatory cells (Tregs) induced by anterior chamber (AC) injection of antigen with those induced by orthotopic corneal allografts. METHODS Anterior chamber-associated immune deviation (ACAID) Tregs were induced by injecting C57BL/6 spleen cells into the AC of BALB/c mice. Delayed-type hypersensitivity responses to C57BL/6 alloantigens were evaluated by a conventional ear swelling assay. Corneal allograft Tregs were induced by applying orthotopic C57BL/6 corneal allografts onto BALB/c hosts. The effects of anti-CD25, anti-CD8, anti-interferon-γ (IFN-γ), anti-IL-17A, or cyclophosphamide treatments on corneal allograft survival and ACAID were evaluated. RESULTS Administration of either anti-CD25 or anti-IFN-γ antibodies prevented the expression of ACAID and abolished the immune privilege of corneal allografts. By contrast, in vivo treatment with anti-CD8 antibody abrogated ACAID but had no effect on corneal allograft survival. Further discordance between ACAID and corneal allograft survival emerged in experiments in which the induction of allergic conjunctivitis or the administration of anti-IL-17A abolished the immune privilege of corneal allografts but had no effect on the induction or expression of ACAID. CONCLUSIONS Although orthotopic corneal allografts are strategically located for the induction of ACAID by the sloughing of corneal cells into the AC, the results reported here indicate that the Tregs induced by orthotopic corneal allografts are remarkably different from the Tregs that are induced by AC injection of alloantigen. Although both of these Treg populations promote corneal allograft survival, they display distinctly different phenotypes.
An Entity-Topic Model for Entity Linking

Entity Linking (EL) has received considerable attention in recent years. Given many name mentions in a document, the goal of EL is to predict their referent entities in a knowledge base. Traditionally, there have been two distinct directions of EL research: one focusing on the effects of mention's context compatibility, assuming that "the referent entity of a mention is reflected by its context"; the other dealing with the effects of document's topic coherence, assuming that "a mention's referent entity should be coherent with the document's main topics". In this paper, we propose a generative model -- called entity-topic model, to effectively join the above two complementary directions together. By jointly modeling and exploiting the context compatibility, the topic coherence and the correlation between them, our model can accurately link all mentions in a document using both the local information (including the words and the mentions in a document) and the global knowledge (including the topic knowledge, the entity context knowledge and the entity name knowledge). Experimental results demonstrate the effectiveness of the proposed model.
Explicit Coherence Enhancing Filter With Spatial Adaptive Elliptical Kernel

The goal of this letter is to provide an elliptical filter to improve image coherence for the task of image smoothing and inpainting. The kernel of this filter is adaptively weighted and its shape is determined by local coherence estimation. The long axis of its ellipse is the same as the coherence direction and we put more weight there to enhance coherence. Compared with the related anisotropic partial differential equations (PDEs) or wavelet shrinkage methods, the proposed filter is extremely simple, instinctive and easy to code. Numerical examples and comparisons illustrate clearly the good performance of the proposed filter.
Alleviating overfitting for polysemous words for word representation estimation using lexicons

Though there are some works on improving distributed word representations using lexicons, the improper over-fitting of the words that have multiple meanings is a remaining issue deteriorating the learning when lexicons are used, which needs to be solved. An alternative method is to allocate a vector per sense instead of a vector per word. However, the word representations estimated in the former way are not as easy to use as the latter one. Our previous work uses a probabilistic method to alleviate the overfitting, but it is not robust with a small corpus. In this paper, we propose a new neural network to estimate distributed word representations using a lexicon and a corpus. We add a lexicon layer in the continuous bag-of-words model and a threshold node after the output of the lexicon layer. The threshold rejects the unreliable outputs of the lexicon layer that are less likely to be the same with their inputs. In this way, it alleviates the overfitting of the polysemous words. The proposed neural network can be trained using negative sampling, which maximizing the log probabilities of target words given the context words, by distinguishing the target words from random noises. We compare the proposed neural network with the continuous bag-of-words model, the other works improving it, and the previous works estimating distributed word representations using both a lexicon and a corpus. The experimental results show that the proposed neural network is more efficient and balanced for both semantic tasks and syntactic tasks than the previous works, and robust to the size of the corpus.
How to make large touch screens usable while driving

Large touch screens are recently appearing in the automotive market, yet their usability while driving is still controversial. Flat screens do not provide haptic guidance and thus require visual attention to locate interactive elements that are displayed. Thus, we need to think about new concepts to minimize the visual attention needed for interaction, to keep the driver's focus on the road and ensure safety. In this paper, we explore three different approaches. The first one is designed to make use of proprioception. The second approach incorporates physical handles to ease orientation on a large flat surface. In the third approach, directional touch gestures are applied. We describe the results of a comparative study that investigates the required visual attention as well as task performance and perceived usability, in comparison to a state-of-the-art multifunctional controller. We found that direct touch buttons provide the best results regarding task completion time, but with a size of about 6x8 cm, they were not yet large enough for blind interaction. Physical elements in and around the screen space were regarded useful to ease orientation. With touch gestures, participants were able to reduce visual attention to a lower level than with the remote controller. Considering our findings, we argue that there are ways to make large screens more appropriate for in-car usage and thus harness the advantages they provide in other aspects.
Inward rectifier potassium channels in the rat middle cerebral artery.

Inward rectifier K+ channels (Kirs) were studied in the isolated perfused rat middle cerebral artery (MCA). The addition of 15 mM K+ (KCl) to the extraluminal bath dilated the MCAs. These dilations were blocked by selective inhibitors for the Kirs (40 μM BaCl2 or 40 mM CsCl) but not selective inhibitors for other K+channels (glibenclamide, tetraethylammonium, or 4-aminopyridine). Neither removal of the endothelium nor treatment with the nitric oxide synthase inhibitor ( N G-nitro-l-arginine methyl ester, 10 μM) affected the K+-induced dilation. The addition of BaCl2 to resting MCAs produced a dose-dependent constriction of 8-12%, indicating that, during resting conditions, Kirs aid in setting or determining the resting tone. The magnitude of the dilations produced by the addition of K+ or constrictions produced by BaCl2 were independent of pressure over a range of 40-100 mmHg. We conclude that Kirs, which produce a dilation when activated, exist on the vascular smooth muscle of the rat MCA. These Kirs aid in determining the resting tone of the vessel, and their function is independent of pressure over physiological pressure ranges.
An automation system for industrial 3-D laser digitizing

An architecture and prototype implementation of an automation system for industrial 3D digitization is described. Facilities for automated view planning, collision avoidance and 3D data management are combined with a graphical user interface to give the operator control of an integrated virtual digitizing environment. Primary objectives for the design are to increase the speed of practical digitizing tasks, while ensuring that requirements on sampling density and uniformity are respected. An important design principle is that repetitive and well defined procedures are managed by the system, while the operator is encouraged to influence digitizing strategy at a high level. The prototype implementation using Hymarc's Hyscan 45C laser digitizer is described, and early experimental results are reported.
Observations on the Evolution of Neural Networks for the Control of a Simulated Quadruped Robot

This study used a genetic algorithm to evolve neural network controllers for the walking behavior of a quadrupedal robot. A 3D physics simulator (Breve by Jon Klein, using the ODE for physics simulation) is used to simulate the action of a quadruped creature in a 3D world. A variety of neural network architectures are experimented with, using a genetic algorithm to evolve walking behaviors that are rewarded with a fitness proportional to the horizontal distance traversed in a particular direction in a set time-period. Several different experiments test the effects of varying the neural network architecture, the friction of the ground, the pitch of the ground, and the strength of the creature’s muscles. This paper demonstrates that the evolutionary system developed in this research is robust to a wide range of these variables, producing impressive walkers across a broad spectrum of physical and neurological circumstances.
Effects of elevated ground-level ozone on nitrogen acquisition of mature European beech (Fagus sylvatica) and Norway spruce (Picea abies) trees

Chronically elevated ground-level ozone (O3) concentrations are known to affect tree growth and may alter nutrient supply. Using the stable isotope 15N as tracer, the nitrogen(N)-uptake and allocation was studied in ca. 60 yr old beech (Fagus sylvatica) and spruce (Picea abies) that were exposed to twice-ambient O3 concentrations over 7 years. A slight reduction in N acquisition was evident in both species along with a slight increase in N demand (particularly in spruce). The reduction in N uptake was stronger in beech than in spruce and was correlated to the reduced transpiration. Changes in resource allocation were contrasting in beech and spruce: Increased allocation of new N to roots and mycorrhizae in beech as a possible compensation for reduction in tree growth; conversely, increased allocation of new N to the shoot, particularly foliage, in spruce, indicating stress-induced promotion of above-ground growth and defence at the expense of lower investment in roots. The effects may, in the long term, limit stand productivity thereby increasing the soil N pool and, as consequence, leaching.
A braille writing training device with voice feedback

A device incorporating both voice feedback and tactile sensation has been developed to help blind children practice the use of a Braille stylus. A microcomputer and voice-synthesis LSI are used to give voice feedback, and a switch under each hole representing a Braille dot is used to give tactile feedback when the stylus is inserted in a hole. A switch is pressed by the user to hear the voice feedback. A one-cell prototype was used to gather feedback from potential users. Four improvements were identified from this feedback and applied to a six-cell version of the device. Testing of the six-cell device by six school children revealed that, although the device received positive scores for four aspects, further improvements are necessary.
Stopped Sum Models for Citation Data

It is important to identify the most appropriate statistical model for citation data in order to maximise the power of future analyses as well as to shed light on the processes that drive citations. This article assesses stopped sum models and compares them with two previously used models, the discretised lognormal and negative binomial distributions using the Akaike Information Criterion (AIC). Based upon data from 20 Scopus categories, some of the stopped sum models had lower AIC values than the discretised lognormal models, which were otherwise the best. However, very large standard errors were produced for some of these stopped sum models, indicating the imprecision of the estimates and the impracticality of the approach. Hence, although stopped sum models show some promise for citation analysis, they are only recommended when they fit better than the alternatives and have manageable standard errors. Nevertheless, their good fit to citation data gives evidence that two different, but related, processes drive citations. Conference Topic Citation and co-citation analysis Introduction Fitting statistical models to citation data is useful both to understand the citation process itself (de Solla Price, 1976) and to identify the factors that affect the citedness of academic papers (Bornmann, Schier, Marx, & Daniel, 2012; Didegah & Thelwall, 2013). For example, negative binomial regression previously has been used to analyse factors underlying patent citations (Maurseth & Verspagen, 2002). The choice of statistical model is not straightforward (Bookstein, 2001), however, because citation data is typically highly skewed (de Solla Price, 1976) with a heavy tail (i.e., with particularly many articles having high citation counts) which makes it difficult to identify and fit the best distribution (Clauset, Shalizi, & Newman, 2009). Nevertheless, it has recently been shown that the distribution of citations to articles from an individual Scopus category and year follows a hooked power law or a discretised lognormal distribution substantially better than a power law (Thelwall & Wilson, 2014a) and that, on this basis, (discretised) ordinary least squares regression on the log of the citation data, after adding 1 to cope with the problem of uncited articles, is applicable and is probably the best available regression method (Thelwall & Wilson, 2014b). It should be noted that although the data is well fitted by the discretised lognormal distribution, it should not be assumed that it was derived from that distribution, as models should not be regarded as literal descriptions of nature (Hesse, 1953). Moreover, it is useful to assess additional statistical models in case a more powerful model can be found as well as to shed light on the processes underlying citation, which are still far from fully understood. This paper investigates stopped sum models for citation data for the first time. These have very different underlying assumptions to the lognormal distribution but can result in similar shaped distributions.
Distributed intelligent management of microgrids using a multi-agent simulation platform

Multi-agent approaches have been widely used to model complex systems of distributed nature with a large amount of interactions between the involved entities. Power systems are a reference case, mainly due to the increasing use of distributed energy sources, largely based on renewable sources, which have potentiated huge changes in the power systems' sector. Dealing with such a large scale integration of intermittent generation sources led to the emergence of several new players, as well as the development of new paradigms, such as the microgrid concept, and the evolution of demand response programs, which potentiate the active participation of consumers. This paper presents a multi-agent based simulation platform which models a microgrid environment, considering several different types of simulated players. These players interact with real physical installations, creating a realistic simulation environment with results that can be observed directly in the reality. A case study is presented considering players' responses to a demand response event, resulting in an intelligent increase of consumption in order to face the wind generation surplus.
A Quantile Regression Approach to Estimating the Distribution of Anesthetic Procedure Time during Induction

Although procedure time analyses are important for operating room management, it is not easy to extract useful information from clinical procedure time data. A novel approach was proposed to analyze procedure time during anesthetic induction. A two-step regression analysis was performed to explore influential factors of anesthetic induction time (AIT). Linear regression with stepwise model selection was used to select significant correlates of AIT and then quantile regression was employed to illustrate the dynamic relationships between AIT and selected variables at distinct quantiles. A total of 1,060 patients were analyzed. The first and second-year residents (R1-R2) required longer AIT than the third and fourth-year residents and attending anesthesiologists (p = 0.006). Factors prolonging AIT included American Society of Anesthesiologist physical status ≧ III, arterial, central venous and epidural catheterization, and use of bronchoscopy. Presence of surgeon before induction would decrease AIT (p < 0.001). Types of surgery also had significant influence on AIT. Quantile regression satisfactorily estimated extra time needed to complete induction for each influential factor at distinct quantiles. Our analysis on AIT demonstrated the benefit of quantile regression analysis to provide more comprehensive view of the relationships between procedure time and related factors. This novel two-step regression approach has potential applications to procedure time analysis in operating room management.
Real-time multiband dynamic compression and noise reduction for binaural hearing aids.

A multi-signal-processor set-up is introduced that is used for real-time implementation of digital hearing aid algorithms that operate on stereophonic (i.e., binaural) input signals and perform signal processing in the frequency domain. A multiband dynamic compression algorithm was implemented which operates in 24 critical band filter channels, allows for interaction between frequency bands and stereo channels, and is fitted to the hearing of the individual patient by a loudness scaling method. In addition, a binaural noise reduction algorithm was implemented that amplifies sound emanating from the front and suppresses lateral noise sources as well as reverberation. These algorithms were optimized with respect to their processing parameters and by minimizing the processing artifacts. Different versions of the algorithms were tested in six listeners with sensorineural hearing impairment using both subjective quality assessment methods and speech intelligibility measurements in different acoustical situations. For most subjects, linear frequency shaping was subjectively assessed to be negative, although it improved speech intelligibility in noise. Additional compression was assessed to be positive and did not deteriorate speech intelligibility as long as the processing parameters were fitted carefully. All noise reduction strategies employed here were subjectively assessed to be positive. Although the suppression of reverberation only slightly improved speech intelligibility, a combination of directional filtering and dereverberation provided a substantial improvement in speech intelligibility for most subjects and for a certain range of signal-to-noise ratios. The real-time implementation was very helpful in optimizing and testing the algorithms, and the overall results indicate that carefully designed and fitted binaural hearing aids might be very beneficial for a large number of patients.