Miracle-dz/UniFAR-FTUs huggingface dataset:
Beyond Mitigation : Potential Options for Counter-Balancing the Climatic and Environmental Consequences of the Rising Concentrations of Greenhouse Gases

Global climate change is occurring at an accelerating pace, and the global greenhouse gas (GHG) emissions that are forcing climate change continue to increase. Given the present pace of international actions, it seems unlikely that atmospheric composition can be stabilized at a level that will avoid"dangerous anthropogenic interference"with the climate system, as called for in the UN Framework Convention on Climate Change. Complicating the situation, as GHG emissions are reduced, reductions in the offsetting cooling influence of sulfate aerosols will create an additional warming influence, making an early transition to climate stabilization difficult. With significant reductions in emissions (mitigation) likely to take decades, and with the impacts of projected climate change-even with proactive adaptation-likely to be quite severe over the coming decades, additional actions to offset global warming and other impacts have been proposed as important complementary measures. Although a number of possible geoengineering approaches have been proposed, each has costs and side effects that must be balanced against the expected benefits of reduced climate impacts. However, substantial new research is needed before comparison of the relative benefits and risks of intervening is possible. A first step in determining whether geoengineering is likely to be a useful option is the initiation of research on four interventions to limit the increasing serious impacts: limiting ocean acidification by increasing the removal of carbon dioxide from the atmosphere and upper ocean; limiting the increasing intensity of tropical cyclones; limiting the warming of the Arctic and associated sea level rise; and sustaining or enhancing the existing sulfate cooling influence. In addition, in depth consideration is needed regarding the governance structure for an international geoengineering decision-making framework in the event that geoengineering becomes essential.
Precision requirements for space-based XCO2 data

Precision requirements are determined for space-based column-averaged CO_2 dry air mole fraction (X_(CO)_2) data. These requirements result from an assessment of spatial and temporal gradients in (X_(CO)_2) the relationship between (X_(CO)_2) precision and surface CO_2 flux uncertainties inferred from inversions of the (X_(CO)_2) data, and the effects of (X_(CO)_2) biases on the fidelity of CO_2 flux inversions. Observational system simulation experiments and synthesis inversion modeling demonstrate that the Orbiting Carbon Observatory mission design and sampling strategy provide the means to achieve these (X_(CO)_2) data precision requirements.
DIBER: protein, DNA or both?

The program DIBER (an acronym for DNA and FIBER) requires only native diffraction data to predict whether a crystal contains protein, B-form DNA or both. In standalone mode, the classification is based on the cube root of the reciprocal unit-cell volume and the largest local average of diffraction intensities at 3.4 A resolution. In combined mode, the Phaser rotation-function score (for the 3.4 A shell and a canonical B-DNA search model) is also taken into account. In standalone (combined) mode, DIBER classifies 87.4 +/- 0.2% (90.2 +/- 0.3%) of protein, 69.1 +/- 0.3% (78.8 +/- 0.3%) of protein-DNA and 92.7 +/- 0.2% (90.0 +/- 0.2%) of DNA crystals correctly. Reliable predictions with a correct classification rate above 80% are possible for 36.8 +/- 1.0% (60.2 +/- 0.4%) of the protein, 43.6 +/- 0.5% (59.8 +/- 0.3%) of the protein-DNA and 83.3 +/- 0.3% (82.6 +/- 0.4%) of the DNA structures. Surprisingly, selective use of the diffraction data in the 3.4 A shell improves the overall success rate of the combined-mode classification. An open-source CCP4/CCP4i-compatible version of DIBER is available from the authors' website at http://www.iimcb. gov.pl/diber and is subject to the GNU Public License.
Proof and other Dilemmas: What Will Count as Mathematics in 2100?

From the Editors In this chapter, Keith Devlin examines how our concept of mathematics has changed over the centuries and suggests a direction it may grow over this next century. He anticipates the focus of mathematics continuing to shift from science and engineering towards the humanities and social sciences. As a result, students who are more people-oriented may be increasingly attracted to mathematics. Of course, as our idea of mathematics changes, our approach to mathematics courses will have to change correspondingly . Keith Devlin is a scholar with broad interests, and a penchant for trying to communicate mathematics to a broad audience. He is a Senior Researcher at, and Executive Director of, the Center for the Study of Language and Information, as well as a Consulting Professor of Mathematics at Stanford University (www.stanford.edu/~kdevlin/). He is a co-founder of the Stanford Media X research network, which provides an industry portal to Stanford departments and centers which study people and technology—from engineering and computer science to psychology, linguistics, education, and art. He is also a co-founder of the university's H-STAR (Human Sciences and Technology Advanced Research) institute (a new Stanford interdisciplinary research center focusing on people and technology—how people use technology, how to better design technology to make it more usable, how technology affects people's lives, and the innovative use of technologies). He is a World Economic Forum Fellow and a Fellow of the American Association for the Advancement of Science. His current research is focused on the use of different media to teach and communicate mathematics to diverse audiences. He also works on the design of information/reasoning systems for intelligence analysis .
Model and Implement an Agent Oriented E-Learning System

E-learning is nowadays recognized as one of the efficient methods to respond to the requirements of open and distance learning. In the e-learning system, several traditional learning styles should be combined with the learner-centered approach. It needs a good notation to represent the requirements of the e-learning system. This paper propose to use a goal and agent oriented approach (i* framework) to analyze and model early requirements of the e-learning system. Base on this model, a multi-agent system is established using Jadex (Java agent development framework based on BDI) on which a rational agent layer on top of a FIPA-compliant infrastructure is built up. Using the modeling paradigm of the intelligent agents with mental states in Jadex, the e-learning system is constructed and implemented
Pattern recognition using labelled and unlabelled data

This thesis presents the results of a three year investigation into combining labelled and unlabelled data for data classification. In the present world, there are many fields in which the quantity of data available to workers in that field has increased exponentially over the last few years. This has in part been due to improved methods of automatic data capture and in part due to improved electronic communication particularly via the internet. These vast quantities of data require some form of processing in order to transform the data into information. This is often a costly business requiring human (often expert) intervention. Our rationale for this investigation is that we wish to augment the information provided by the human experts with data which has not been processed by human experts. The actual method we investigate is classification using both processed (labelled) and unprocessed (unlabelled) data in order to reduce the requirement for human intervention. In Chapter 2 of the thesis we review several aspects of this problem as it features in the current literature. We discuss • Classification versus clustering • Error estimation training, testing and validation data. • Generalisation • Existing methods for combining labelled and unlabelled data • Combining classifiers • Artificial neural networks • The sufficient level of labelled samples for a classification task. • Active selection
MprAB Is a Stress-Responsive Two-Component System That Directly Regulates Expression of Sigma Factors SigB and SigE in Mycobacterium tuberculosis

ABSTRACT The genetic mechanisms mediating the adaptation of Mycobacterium tuberculosis within the host are poorly understood. The best-characterized regulatory systems in this organism include sigma factors and two-component signal transduction systems. mprAB is a two-component system required by M. tuberculosis for growth in vivo during the persistent stage of infection. In this report, we demonstrate that MprAB is stress responsive and regulates the expression of numerous stress-responsive genes in M. tuberculosis. With DNA microarrays and quantitative real-time reverse transcription-PCR, genes regulated by MprA in M. tuberculosis that included two stress-responsive sigma factors were identified. Response regulator MprA bound to conserved motifs in the upstream regions of both sigB and sigE in vitro and regulated the in vivo expression of sigB and sigE in M. tuberculosis. In addition, mprA itself was induced following exposure to stress, establishing a direct role for this regulatory system in stress response pathways of M. tuberculosis. Induction of mprA and sigE by MprA in response to stress was mediated through the cognate sensor kinase MprB and required expression of the extracytoplasmic loop domain. These results provide the first evidence that recognition of and adaptation to specific stress in M. tuberculosis are mediated through activation of a two-component signal transduction system that directly regulates the expression of stress-responsive determinants.
Improved bounded-real-lemma representation and H∞ control of systems with polytopic uncertainties

This brief concerns the problem of the bounded-real- lemma (BRL) representation and control of linear systems with real convex polytopic uncertainties. In order to use a param- eter-dependent Lyapunov function for a system with polytopic un- certainties, the derivative term for the state, which is in the deriva- tive of the Lyapunov function, is reserved; and free weighting ma- trices are used to express the relationship between the terms of the system equation. This yields a new linear-matrix-inequality ap- proach to BRL representation. In addition, this method is extended to the design of a state-feedback controller that solves the con- trol problem. Numerical examples demonstrate that the proposed method is effective and is an improvement over previous ones. Index Terms—Bounded-real-lemma (BRL), control, linear matrix inequality (LMI), parameter-dependent Lyapunov func- tion, polytopic uncertainty.
A block-based combined scheme exploiting sparsity in nonlinear acoustic echo cancellation

Nonlinear acoustic echo cancellation (NAEC) aims at estimating both the acoustic impulse response and the nonlinearities affecting the desired signal. Both the modeling processes show behaviors of sparse nature from an energy point of view. In this paper, we propose an adaptive NAEC algorithm that takes advantage of such sparsity behaviors to improve echo cancellation performance. The proposed scheme is characterized by two block-based adaptive combinations of proportionate adaptive filters, having different strategies, devoted respectively to the estimation of the linear and nonlinear responses. The proposed model is assessed in NAEC problems, where its advantages and effectiveness are shown.
Being Transgender in the Era of Trump: Compassion Should Pick Up Where Science Leaves Off

In a divisive time, few issues are more polarizing than how Americans treat transgender (“trans”) individuals. Trans individuals make up 0.6% of Americans, or 1.4 million people. As states have passed conflicting legislation, some protecting trans individuals and others limiting access, the conversation has become increasingly polarized. Adding to this discourse is the recalibration of protections for trans individuals by the Trump Administration. Recently, the larger debate over the status and protections of trans individuals has focused on whether being trans has any biological or genetic basis. A 2016 review article published by a pair of professors associated with Johns Hopkins University brought this question to center stage. The author’s essentially claim that there is no biological or genetic basis for being trans and thus they caution against any treatment for trans individuals. This controversial stance drew forceful criticism from the scientific community and advocates. At the same time, the paper has been used by legislators and the media to discredit the needs and experiences of trans individuals. This Essay provides a brief overview of the debate, including a brief synopsis of the current status of science surrounding being trans. While the science is not settled, what is clear is that trans individuals face dramatically heightened rates of suicide, psychological distress, and other challenges. Most concerning, the suicide attempt rates for trans individuals have been reported as high as 41%--significantly outstripping the general population, which historically has hovered around 5%. Even at the lower end of estimates, the fact of the matter is that we are dealing with a public health crisis. This Essay argues that the disagreement about biological explanations for being transgender misses the most critical point: trans individuals experience enormous psychological distress across their lives. An appropriate response to the difficulties facing trans persons should not become mired down in a scientific debate about causation. Compassion should guide the discussion.
Resveratrol: from grapevines to mammalian biology

With the rapid advances made over the last two decades in biomedical research, there has been an unprecedented interest in unraveling the magical properties of some commonly used natural products. Consequently, a wide variety of natural products are under scrutiny for their clinical potential, both in terms of disease prevention and treatment. Among the compounds under investigation is a family of polymers given the name viniferin. These compounds elicit strong anti-fungal properties and are therefore included under the broad class of plant antibiotics known as phytoalexins (1). One remarkable compound in this list is resveratrol (RSV), a major active ingredient of stilbene phytoalexins, first isolated from the roots of the oriental medicinal plant Polygonum Capsidatum (Kojo-kon in Japanese) (2). Observations that this compound was an active ingredient of a folk plant known for its remedial effects against a host of human afflictions (2, 3) and that it was synthesized by leaf tissue in response to fungal infection of grapevines (Vitis vinifera) (4) provided the impetus for the increase in activity surrounding RSV in the field of biomedical research. The relatively high concentration of RSV in wine (5) and its documented cardioprotective effect (6) form the basis for the so-called “French paradox” (7). Most of the initial work on RSV was centered around its effects on metabolic pathways regulating cardiovascular biology, such as lipid metabolism and platelet function; however, since the reported cancer chemopreventive activity of RSV in animal models of carcinogenesis (8), recent investigations have been directed at understanding the molecular mechanism(s) of its diverse biological effects. As a result, the positive or negative effects of RSV on some important physiological pathways have been proposed as possible mechanisms for its observed cancer chemopreventive, cardioprotective, and neuroprotective activities. These include suppression of cellular proliferation via inhibition of key steps in the signal transduction pathways (9–12) and cyclin-dependent kinases (cdks) (13), promotion of cellular differentiation (14), scavenging/suppression of intracellular reactive oxygen intermediates (ROI) (15), induction of apoptotic cell death through activation of mitochondria-dependent or -independent pathways (16–18), anti-inflammatory activity via down-regulation of proinflammatory cytokines (19, 20), and inhibition of androgen receptor function and estrogenic activity (21, 22). This review is intended to provide the reader with an appreciation of the diverse biological effects of this remarkable compound, which could have tremendous potential as a chemopreventive and/or chemotherapeutic agent in clinical medicine.
Momentary Improvement of Hand Sensation by Excluding

"Momentary improvement of hand sensibility by excluding vision" Access to the published version may require journal subscription. Abstract Purpose: The aim of this study was to investigate the effects of visual input on the results in a sensory testing procedure. Method: In 66 healthy persons sensory testing was done in a counterbalanced setting 1) with open eyes, and 2) blindfolded. The tested hand was placed behind a screen. Testing for tactile discrimination (2pd) and touch thresholds (Semmes-Weinstein monofilaments) was performed on the index finger of the dominant hand. Wilcoxon signed-rank test was used for the statistical analysis. Result: Two-point discrimination was significantly improved when the test was performed blindfolded compared with open eyes. Touch thresholds – a less complex task – showed no difference. Conclusion: This study demonstrated that removal of all visual input during sensibility testing results in improved test results compared to sensibility testing with visual input (opened eyes but the hand out of sight). The mechanism behind the improvement is likely rapid changes in the brain. Manipulation of visual input during sensibility testing, especially when performing tests that include an element of interpretation, influences the test result. These results highlight the importance of standardized procedures in sensibility testing.
4 + 4 Fingers Manipulating Virtual Objects in Mixed-Reality Environment

This paper describes the construction of a prototype system that allows the user to manipulate virtual objects in a mixed-reality environment. The user can perceive haptic sensations at his or her fingertips and see a virtual world with a live image of his or her hands manipulating the virtual objects. The difficulty of constructing such a visual presentation is the problem of merging the real image with correct geometrical occlusion with images of virtual objects in the simulated virtual world. In this paper, a method of solving registration of real and virtual images to produce mixedreality scenes is proposed. We have combined this method with our haptic interface device, SPIDAR-8, to construct a system that integrates these realities by using the sense of touch and vision of real images in the virtual world that can be realized during the manipulation of virtual objects. The implemented results are shown and remaining problems are discussed.
Bipolar seesaw in the northeastern tropical Atlantic during Heinrich stadials

Two SST records based on Mg/Ca of G. ruber (pink) from the continental slope off West Africa at 15°N and 12°N shed new light on the thermal bipolar seesaw pattern in the northeastern tropical Atlantic during periods of reduced Atlantic Meridional Overturning Circulation (AMOC) associated with Heinrich stadials H1 to H6. The two records indicate that the latitudinal position of the bipolar seesaw's zero‐anomaly line, between cooling in the North and warming in the South, gradually shifted southward from H6 to H1. A conceptual model is presented that aims to provide a physically consistent mechanism for the southward migration of the seesaw's fulcrum. The conceptual model suggests latitudinal movements of the Intertropical Convergence Zone, driven by a combination of orbital‐forced changes in the meridional temperature gradient within the realm of the Hadley cell and the expansion of the Northern Hemisphere cryosphere, as a major factor.
Outdated CSIT can achieve full DoF in heterogeneous parallel channels

We consider communication over heterogeneous parallel channels, where a transmitter is connected to two users via two parallel channels: (1) a MISO broadcast channel (BC), and (2) a noiseless rate-limited multicast channel. We characterize the optimal degrees of freedom (DoF) region of this setting when the transmitter has delayed channel state information (CSIT) regarding the MISO BC. Our results show that jointly coding over the two channels can strictly outperform simple channel aggregation (or channel separation) and can even achieve the same performance as with instantaneous CSIT when the CSIT on the MISO BC is completely stale; this occurs when the multicast rate of the second channel is larger than a certain threshold, in the DoF sense. The main idea to achieve full DoF with completely stale CSIT is to send information over the MISO BC at a rate above its capacity and use the second channel to send additional side information to allow for reliable decoding at both receivers.
Open-vocabulary Object Retrieval

—In this paper, we address the problem of retrieving objects based on open-vocabulary natural language queries: Given a phrase describing a speciﬁc object, e.g., “the corn ﬂakes box”, the task is to ﬁnd the best match in a set of images containing candidate objects. When naming objects, humans tend to use natural language with rich semantics, including basic-level categories, ﬁne-grained categories, and instance-level concepts such as brand names. Existing approaches to large-scale object recognition fail in this scenario, as they expect queries that map directly to a ﬁxed set of pre-trained visual categories, e.g. ImageNet synset tags. We address this limitation by introducing a novel object retrieval method. Given a candidate object image, we ﬁrst map it to a set of words that are likely to describe it, using several learned image-to-text projections. We also propose a method for handling open-vocabularies, i.e., words not contained in the training data. We then compare the natural language query to the sets of words predicted for each candidate and select the best match. Our method can combine category-and instance-level semantics in a common representation. We present extensive experimental results on several datasets using both instance-level and category-level matching and show that our approach can accurately retrieve objects based on extremely varied open-vocabulary queries. The source code of our approach will be publicly available together with pre-trained models at http://openvoc.berkeleyvision. org and could be directly used for robotics applications.
Expert-Guided Contrastive Opinion Summarization for Controversial Issues

This paper presents a new model for the task of contrastive opinion summarization (COS) particularly for controversial issues. Traditional COS methods, which mainly rely on sentence similarity measures are not sufficient for a complex controversial issue. We therefore propose an Expert-Guided Contrastive Opinion Summarization (ECOS) model. Compared to previous methods, our model can (1) integrate expert opinions with ordinary opinions from social media and (2) better align the contrastive arguments under the guidance of expert prior opinion. We create a new data set about a complex social issue with "sufficient" controversy and experimental results on this data show that the proposed model are effective for (1) producing better arguments summary in understanding a controversial issue and (2) generating contrastive sentence pairs.