Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of multi-level spatial data reveals strong synchrony in seasonal influenza epidemics across Norway, Sweden, and Denmark

Population structure, spatial diffusion, and climatic conditions mediate the spatiotemporal spread of seasonal influenza in temperate regions. However, much of our knowledge of these dynamics stems from a few well-studied countries, such as the United States (US), and the extent to which this applies in different demographic and climatic environments is not fully understood. Using novel data from Norway, Sweden, and Denmark, we applied wavelet analysis and non-parametric spatial statistics to explore the spatiotemporal dynamics of influenza transmission at regional and international scales. We found the timing and amplitude of epidemics were highly synchronized both within and between countries, despite the geographical isolation of many areas in our study. Within Norway, this synchrony was most strongly modulated by population size, confirming previous findings that hierarchical spread between larger populations underlies seasonal influenza dynamics at regional levels. However, we found no such association when comparing across countries, suggesting that other factors become important at the international scale. Finally, to frame our results within a wider global context, we compared our findings from Norway to those from the US. After correcting for differences in geographic scale, we unexpectedly found higher levels of synchrony in Norway, despite its smaller population size. We hypothesize that this greater synchrony may be driven by more favorable and spatially uniform climatic conditions, although there are other likely factors we were unable to consider (such as reduced variation in school term times and differences in population movements). Overall, our results highlight the importance of comparing influenza spread at different spatial scales and across diverse geographic regions in order to better understand the complex mechanisms underlying disease dynamics.
Deep GMRT radio observations and a multi-wavelength study of the region around HESS J1858+020

Context. There are a number of very high energy sources in the Galaxy that remain unidentified. Multi-wavelength and variability studies, and catalogue searches, are powerful tools to identify the physical counterpart, given the uncertainty in the source location and extension. Aims. This work carries out a thorough multi-wavelength study of the unidentified, very high energy source HESS J1858+020 and its environs. Methods. We have performed Giant Metrewave Radio Telescope observations at 610 MHz and 1.4 GHz to obtain a deep, low-frequency radio image of the region surrounding HESS J1858+020. We analysed archival radio, infrared, and X-ray data as well. This observational information, combined with molecular data, catalogue sources, and a nearby Fermi gamma-ray detection of unidentified origin, are combined to explore possible counterparts to the very high energy source. Results. We provide with a deep radio image of a supernova remnant that might be related to the GeV and TeV emission in the region. We confirm the presence of an H ii region next to the supernova remnant and coincident with molecular emission. A potential region of star formation is also identified. We identify several radio and X-ray sources in the surroundings. Some of these sources are known planetary nebulae, whereas others may be non-thermal extended emitters and embedded young stellar objects. Three old, background Galactic pulsars also neighbour HESS J1858+020 along the line of sight. Conclusions. The region surrounding HESS J1858+020 is rich in molecular structures and non-thermal objects that may potentially be linked to this unidentified very high energy source. In particular, a supernova remnant interacting with nearby molecular clouds may be a good candidate, but a star forming region, or a non-thermal radio source of yet unclear nature, may also be behind the gamma-ray source. The neighbouring pulsars, despite being old and distant, cannot be discarded as candidates. Further observational studies are needed, however, to narrow the search for a counterpart to the HESS source.
Value chain analysis Methodologies in the context of environment and trade research

This paper gives an overview of different methodologies related to value chain analysis in the context of environment and trade research. Four major fields of methodologies are identified: Accounting of input-output flows, general computable equilibrium models, econometrics, and global commodity chain analysis. Accounting of flows includes different physical (e.g. life cycle assessment) and monetary (e.g. social accounting matrix) accounting frameworks providing the foundation for computable general equilibrium models. Econometric value chain analysis is widespread in the field of impact assessment of value chains. It can be applied to analyze the effects of standards (e.g. food, social, and environmental) as well as transaction costs on the income of households (micro level) or on trade volumes of countries (macro level). Global commodity chain analysis aims to identify and measure the balance of power between the participating actors.
Wave Theory of Information

Understand the relationship between information theory and the physics of wave propagation with this expert guide. Balancing fundamental theory with engineering applications, it describes the mechanism and limits for the representation and communication of information using electromagnetic waves. Information-theoretic laws relating functional approximation and quantum uncertainty principles to entropy, capacity, mutual information, rate–distortion, and degrees of freedom of bandlimited radiation are derived and explained. Both stochastic and deterministic approaches are explored, and applications for remote sensing and signal reconstruction, wireless communication, and networks of multiple transmitters and receivers are reviewed. With end-of-chapter exercises and suggestions for further reading enabling in-depth understanding of key concepts, it is the ideal resource for researchers and graduate students in electrical engineering, physics, and applied mathematics looking for a fresh perspective on information theory.
Dynamic Changes between Two LHCX-Related Energy Quenching Sites Control Diatom Photoacclimation1

Multiple LHCX-related quenching sites control short- and long-term high-light acclimation in the marine diatom Phaeodactylum tricornutum. Marine diatoms are prominent phytoplankton organisms that perform photosynthesis in extremely variable environments. Diatoms possess a strong ability to dissipate excess absorbed energy as heat via nonphotochemical quenching (NPQ). This process relies on changes in carotenoid pigment composition (xanthophyll cycle) and on specific members of the light-harvesting complex family specialized in photoprotection (LHCXs), which potentially act as NPQ effectors. However, the link between light stress, NPQ, and the existence of different LHCX isoforms is not understood in these organisms. Using picosecond fluorescence analysis, we observed two types of NPQ in the pennate diatom Phaeodactylum tricornutum that were dependent on light conditions. Short exposure of low-light-acclimated cells to high light triggers the onset of energy quenching close to the core of photosystem II, while prolonged light stress activates NPQ in the antenna. Biochemical analysis indicated a link between the changes in the NPQ site/mechanism and the induction of different LHCX isoforms, which accumulate either in the antenna complexes or in the core complex. By comparing the responses of wild-type cells and transgenic lines with a reduced expression of the major LHCX isoform, LHCX1, we conclude that core complex-associated NPQ is more effective in photoprotection than is the antenna complex. Overall, our data clarify the complex molecular scenario of light responses in diatoms and provide a rationale for the existence of a degenerate family of LHCX proteins in these algae.
HSP‐enriched properties of extracellular vesicles involve survival of metastatic oral cancer cells

Cancer cells often secrete extracellular vesicles (EVs) that carry heat shock proteins (HSPs) with roles in tumor progression. Oral squamous cell carcinoma (OSCC) belongs to head and neck cancers (HNC) whose lymph‐node‐metastases often lead to poor prognosis. We have examined the EV proteome of OSCC cells and found abundant secretion of HSP90‐enriched EVs in lymph‐node‐metastatic OSCC cells. Double knockdown of HSP90α and HSP90β, using small interfering RNA significantly reduced the survival of the metastatic OSCC cells, although single knockdown of each HSP90 was ineffective. Elevated expression of these HSP90 family members was found to correlate with poor prognosis of HNC cases. Thus, elevated HSP90 levels in secreted vesicles are potential prognostic biomarkers and therapeutic targets in metastatic OSCC.
Toll-like receptors 2 and 4 modulate intestinal IL-10 differently in ileum and colon

Background Inflammatory bowel diseases are consequence of an intestinal homeostasis breakdown in which innate immune dysregulation is implicated. Toll-like receptor (TLR)2 and TLR4 are immune recognition receptors expressed in the intestinal epithelium, the first physical-physiological barrier for microorganisms, to inform the host of the presence of Gram-positive and Gram-negative organisms. Interleukin (IL)-10 is an essential anti-inflammatory cytokine that contributes to maintenance of intestinal homeostasis. Aim Our main aim was to investigate intestinal IL-10 synthesis and release, and whether TLR2 and TLR4 are determinants of IL-10 expression in the intestinal tract. Methods We used Caco-2 cell line as an enterocyte-like cell model, and also ileum and colon from mice deficient in TLR2, TLR4 or TLR2/4 to test the involvement of TLR signaling. Results Intestinal epithelial cells are able to synthesize and release IL-10 and their expression is increased after TLR2 or TLR4 activation. IL-10 regulation seems to be tissue specific, with IL-10 expression in the ileum regulated by a compensation between TLR2 and TLR4 expression, whereas in the colon, TLR2 and TLR4 affect IL-10 expression independently. Conclusions Intestinal epithelial cells could release IL-10 in response to TLR activation, playing an intestinal tissue-dependent and critical intestinal immune role.
Assessment of thyroid cancer risk associated with radiation dose from personal diagnostic examinations in a cohort study of US radiologic technologists, followed 1983–2014

Objective To assess whether personal medical diagnostic procedures over life, but particularly those associated with exposure in adulthood, were associated with increased thyroid cancer risk. Design Participants from the US Radiologic Technologists Study, a large, prospective cohort, were followed from the date of first mailed questionnaire survey completed during 1983–1989 to the earliest date of self-reported diagnosis of thyroid cancer or of any other cancer than non-melanoma skin cancer (NMSC) in any of three subsequent questionnaires up to the last in 2012–2014. Setting US nationwide, occupational cohort. Participants US radiologic technologists with exclusion of: those who reported a previous cancer apart from NMSC on the first questionnaire; those who reported a cancer with an unknown date of diagnosis on any of the questionnaires; and those who did not respond to both the first questionnaire and at least one subsequent questionnaire. Primary outcome measure We used Cox proportional hazards models with age as timescale to compute HRs and 95% CI for thyroid cancer in relation to cumulative 5-year lagged diagnostic thyroid dose. Results There were 414 self-reported thyroid cancers (n=275 papillary) in a cohort of 76 415 persons. Cumulative thyroid dose was non-significantly positively associated with total (excess relative risk/Gy=2.29 (95% CI −0.91 to 7.01, p=0.19)) and papillary thyroid cancer (excess relative risk/Gy=4.15 (95% CI −0.39, 11.27, p=0.08)) risk. These associations were not modified by age at, or time since, exposure and were independent of occupational exposure. Conclusion Our study provides weak evidence that thyroid dose from diagnostic radiation procedures over the whole of life, in particular associated with exposure in adulthood, influences adult thyroid cancer risk.
A Deep Neural Network based Approach for Entity Extraction in Code-Mixed Indian Social Media Text

The rise in accessibility of web to the mass has led to a spurt in the use of social media making it convenient and powerful way to express and exchange information in their own language(s). India, being enormously diversiﬁed country have more than 168 millions users on social media. This diversity is also reﬂected in their scripts where a majority of users often switch between their native languages to be more expressive. These linguistic variations make automatic entity extraction both a necessary and a challenging problem. In this paper, we report our work for entity extraction in a code-mixed environment. Our proposed approach is based on the popular deep neural network based Gated Recurrent Unit (GRU) archirecture that automatically discovers the higher level features from the text. We do not make use of any handcrafted features or rules, and therefore our proposed model is quite generic in nature. Our experiments on two benchmark datasets of English-Hindi and English-Tamil language pairs show the F-scores of 66 . 04% and 53 . 85% , respectively.
Simulating Fundamental Analysis of a Firm Using a VECX Model

The study aims at simulating and forecasting a company’s stock returns and prices by a fundamentalist analysis process based on a Vector Error Correction with Exogenous Variables (VECX) econometric model. To achieve this, we selected relevant fundamentalist indicators and specified a model capable of simulating a fundamentalist analysis of a Brazilian publicly listed company, Sadia S/A. The VECX model statistical validation was carried out by performing unit root tests, cointegration tests, Granger causality tests, correlation analysis, impulse-response functions, and variance decomposition. Data taken from the firm’s financial statements were used to compute seven fundamentalist indicators, which were defined as the model’s endogenous variables. The exogenous variables included in the model are the Brazilian Stock Market (Bovespa) Index return, the Brazilian GDP, the Brazilian basic interest rate (Selic), the US$/BRL exchange rate, and the international price of commodities poultry and corn. The final version of the estimated model takes into account cointegration relationships among the endogenous variables. Based on this model, the Company’s ex-post forecasts of the fundamentalist indicators were obtained, as well as its stock return and price forecasts. The results show that the simulation by a VECX econometric model is robust as seen by the quality of the forecasts obtained. Finally, a prognostic fundamental analysis was carried out based on the forecasts.
The Impact of Activity Based Working (ABW) on Workplace Activity, Eating Behaviours, Productivity, and Satisfaction

The redesign of the physical workplace according to activity-based working (ABW) principles has potential to influence employee health and workplace outcomes. This natural experiment examined changes in accelerometer-derived workplace activity, self-reported eating behaviours, productivity, workplace satisfaction before (March to November 2014) and six to nine months after moving to an ABW workplace compared to a comparison workplace (n = 146 at baseline (56% ABW, aged 40.1 ± 8.5 years, 72% female). Interviews were also conducted with 21 ABW participants. Between- and within-group differences were examined and mixed model analysis examined intervention effects over time. Effect sizes were calculated on change scores (Cohen’s d). Although not statistically significant, ABW participants had meaningful improvements in workday sedentary time, light-, and moderate-to-vigorous intensity physical activity, job satisfaction and relationship with co-workers (d = 0.379–0.577), and small declines in productivity (d = 0.278). There were significant, meaningful, and beneficial intervention effects on perceived organisational support for being active in the workplace, frequency of eating lunch with colleagues, and satisfaction with the physical environment in ABW compared to comparison participants (d = 0.501–0.839). Qualitative data suggested that ABW employees associated ABW with greater opportunities for movement and collaboration, but had mixed views on the impact on productivity. Future research with larger samples and over longer follow-up periods is warranted.
Energy-Efficient Sensor Censoring for Compressive Distributed Sparse Signal Recovery

To strike a balance between energy efficiency and data quality control, this paper proposes a sensor censoring scheme for distributed sparse signal recovery via compressive-sensing-based wireless sensor networks. In the proposed approach, each sensor node employs a sparse sensing vector with known support for data compression, meanwhile enabling making local inference about the unknown support of the sparse signal vector of interest. This naturally leads to a ternary censoring protocol, whereby each sensor: 1) directly transmits the real-valued compressed data, if the sensing vector support is detected to be overlapped with the signal support; 2) sends a one-bit hard decision if empty support overlap is inferred; and 3) keeps silent if the measurement is judged to be uninformative. Our design then aims at minimizing the error probability that empty support overlap is decided but otherwise is true, subject to the constraints on a tolerable false-alarm probability that non-empty support overlap is decided but otherwise is true, and a target censoring rate. We derive a closed-form formula of the optimal censoring rule; a low complexity implementation using bi-section search is also developed. In addition, the average communication cost is analyzed. To aid global signal reconstruction under the proposed censoring framework, we propose a modified $\ell _{1}$ -minimization based algorithm, which exploits certain sparse nature of the hard decision vector received at the fusion center. Analytic performance guarantees, characterized in terms of the restricted isometry property, are also derived. Computer simulations are used to illustrate the performance of the proposed scheme.
Scaling up site disputes: strategies to redefine ‘local’ in the fight against fracking

ABSTRACT Plans to replace an aging diesel backup energy plant with liquid natural gas (LNG) generators in Whitehorse, Yukon, resulted in a public outcry, involving community meetings, massive petitions, and demonstrations. Are these civil society protests just a case of a local siting dispute – a response to an unwanted industrial site in an urban neighborhood? Here, it is argued that siting debates are not the driver of these campaigns, but instead are harnessed by activists to advance a broader environmental movement. By linking the LNG project to more distant extraction, involving hydraulic fracturing (‘fracking’), movement leaders portray the entire territory as part of the ‘local’ for Whitehorse residents. Movement leaders rely upon two key mechanisms: claiming insider status, and identifying visible symbols. This case reveals the strategic use by environmental movements of local concerns to recruit support for broader campaigns, and the value of local, place-based activism for broader environmental movements.
Fast clustering in linear 1D subspaces: segmentation of microscopic image of unstained specimens

Algorithms for subspace clustering (SC) are effective in terms of the accuracy but exhibit high computational complexity. We propose algorithm for SC of (highly) similar data points drawn from union of linear one-dimensional subspaces that are possibly dependent in the input data space. The algorithm finds a dictionary that represents data in reproducible kernel Hilbert space (RKHS). Afterwards, data are projected into RKHS by using empirical kernel map (EKM). Due to dimensionality expansion effect of the EKM one-dimensional subspaces become independent in RKHS. Segmentation into subspaces is realized by applying the max operator on projected data which yields the computational complexity of the algorithm that is linear in number of data points. We prove that for noise free data proposed approach yields exact clustering into subspaces. We also prove that EKM-based projection yields less correlated data points. Due to nonlinear projection, the proposed method can adopt to linearly nonseparable data points. We demonstrate accuracy and computational efficiency of the proposed algorithm on synthetic dataset as well as on segmentation of the image of unstained specimen in histopathology.
Words and the mind : how words capture human experience

The study of word meanings promises important insights into the nature of the human mind by revealing what people find to be most cognitively significant in their experience. However, as we learn more about the semantics of various languages, we are faced with an interesting problem. Different languages seem to be telling us different stories about the mind. For example, important distinctions made in one language are not necessarily made in others. What are we to make of these cross-linguistic differences? How do they arise? Are they created by purely linguistic processes operating over the course of language evolution? Or do they reflect fundamental differences in thought? In this sea of differences, are there any semantic universals? Which categories might be given by the genes, which by culture, and which by language? And what might the cross-linguistic similarities and differences contribute to our understanding of conceptual and linguistic development? The kinds of mapping principles, structures, and processes that link language and non-linguistic knowledge must accommodate not just one language but the rich diversity that has been uncovered. The integration of knowledge and methodologies necessary for real progress in answering these questions has happened only recently, as experimental approaches have been applied to the cross-linguistic study of word meaning. In Words and the Mind, Barbara Malt and Phillip Wolff present evidence from the leading researchers who are carrying out this empirical work on topics as diverse as spatial relations, events, emotion terms, motion events, objects, body-part terms, causation, color categories, and relational categories. By bringing them together, Malt and Wolff highlight some of the most exciting cross-linguistic and cross-cultural work on the language-thought interface, from a broad array of fields including linguistics, anthropology, cognitive and developmental psychology, and cognitive neuropsychology. Their results provide some answers to these questions and new perspectives on the issues surrounding them.