Miracle-dz/UniFAR-FTUs huggingface dataset:
Advancing multiscale structural mapping of the brain through fluorescence imaging and analysis across length scales

Brain function emerges from hierarchical neuronal structure that spans orders of magnitude in length scale, from the nanometre-scale organization of synaptic proteins to the macroscopic wiring of neuronal circuits. Because the synaptic electrochemical signal transmission that drives brain function ultimately relies on the organization of neuronal circuits, understanding brain function requires an understanding of the principles that determine hierarchical neuronal structure in living or intact organisms. Recent advances in fluorescence imaging now enable quantitative characterization of neuronal structure across length scales, ranging from single-molecule localization using super-resolution imaging to whole-brain imaging using light-sheet microscopy on cleared samples. These tools, together with correlative electron microscopy and magnetic resonance imaging at the nanoscopic and macroscopic scales, respectively, now facilitate our ability to probe brain structure across its full range of length scales with cellular and molecular specificity. As these imaging datasets become increasingly accessible to researchers, novel statistical and computational frameworks will play an increasing role in efforts to relate hierarchical brain structure to its function. In this perspective, we discuss several prominent experimental advances that are ushering in a new era of quantitative fluorescence-based imaging in neuroscience along with novel computational and statistical strategies that are helping to distil our understanding of complex brain structure.
Human Guanylate Binding Proteins Potentiate the Anti-Chlamydia Effects of Interferon-γ

Chlamydiae are obligate intracellular pathogens that are sensitive to pro-inflammatory cytokine interferon-γ. IFN-γ-inducible murine p47 GTPases have been demonstrated to function in resistance to chlamydia infection in vivo and in vitro. Because the human genome does not encode IFN-γ-inducible homologues of these proteins, the significance of the p47 GTPase findings to chlamydia pathogenesis in humans is unclear. Here we report a pair of IFN-γ-inducible proteins, the human guanylate binding proteins (hGBPs) 1 and 2 that potentiate the anti-chlamydial properties of IFN-γ. hGBP1 and 2 localize to the inclusion membrane, and their anti-chlamydial functions required the GTPase domain. Alone, hGBP1 or 2 have mild, but statistically significant and reproducible negative effects on the growth of Chlamydia trachomatis, whilst having potent anti-chlamydial activity in conjunction with treatment with a sub-inhibitory concentration of IFN-γ. Thus, hGBPs appear to potentiate the anti-chlamydial effects of IFN-γ. Indeed, depletion of hGBP1 and 2 in cells treated with IFN-γ led to an increase in inclusion size, indicative of better growth. Interestingly, chlamydia species/strains harboring the full-length version of the putative cytotoxin gene, which has been suggested to confer resistance to IFN-γ was not affected by hGBP overexpression. These findings identify the guanylate binding proteins as potentiators of IFN-γ inhibition of C. trachomatis growth, and may be the targets of the chlamydial cytotoxin.
An approach to energy-efficient virtual network embeddings

Network Virtualization is recognized as a key technology for the Future Internet. Energy-efficiency is one of the main challenges in future networking environments. Most algorithms for mapping virtual resources to substrate resources however do not consider energy as a factor for the mapping. In order to evaluate the energy-efficiency of such a mapping, an energy model and appropriate energy-aware metrics are needed. This paper discusses how an algorithm can be modified to take energy-efficiency into account. The modified algorithm is then evaluated, showing that energy-efficiency can be increased with only a minor impact on embedding quality regarding other metrics.
Model integration in the development of embedded control systems - a characterization of current research efforts

The design of advanced embedded control systems requires a systematic approach in handling their increasing complexity and in particular integration of the different aspects and parts of a product worked on by different experts. Several variants of model-based approaches are today advocated to facilitate systems integration. This paper describes a number of representative efforts that address multiple concerns or views including modeling languages such as AADL and EAST-ADL as well as model integration environments such as GeneralStore, ToolNet, and Fujaba. We present a characterization of the approaches and thereby highlight their commonalities and differences regarding basic integration mechanisms and engineering support. We conclude with a prospect for future work.
Local Narratives on the Adoption of Mango Integrated Crop Management Technologies in Samal Island, Philippines

The adoption of agricultural technologies is imperative in improving the performance of the local agriculture sector in the Philippines. Numerous technology-based development projects have been implemented across the country. The Mango ICM project was one of these interventions. It was carried out in the Island Garden of Samal, Davao del Norte (IGaCoS) with the objective of supporting the local mango industry through the promotion of environmentally sustainable technologies. Years since project completion, challenges have been raised in relation to technology adoption. To understand the adoption dynamics in IGaCoS, this study dissects the complex nature of the Mango ICM technologies and the perception and reception of the local producers towards them. This study is grounded on the narratives gathered through a series of in-depth interviews with key informants and local mango producers. Results show that although the potential benefits of the extended technologies were recognized, the existing local labor and market arrangements created barriers to technology adoption. The nature of technology, market arrangement, and financial constraints were the identified reasons for the non-adoption of the local mango producers
Diseño de antenas directivas de banda ancha a frecuencias de microondas

A new type of antenna is simulated and described using the properties of waves in the range 3-7 GHz. It consists of placing metal rings spaced a certain distance for varying the refractive index of the metal so that it behaves like the lens, design and simulation is to many layers, considering the first layer metal rings uncut, the second and third metal layer cut rings, the simulation is performed using the software CST laboratories ITEAM group of electromagnetic radiation. Autor: Daniel Antonio Santillan Haro, email: dasan4@teleco.upv. es Director 1: Miguel Ferrando Bataller, email: mferrand@dcom.upv. es Fecha de entrega: 11-07-16 Diseño de antenas directivas de banda ancha a frecuencias de microondas 3
A theory of the learnable

Humans appear to be able to learn new concepts without needing to be programmed explicitly in any conventional sense. In this paper we regard learning as the phenomenon of knowledge acquisition in the absence of explicit programming. We give a precise methodology for studying this phenomenon from a computational viewpoint. It consists of choosing an appropriate information gathering mechanism, the learning protocol, and exploring the class of concepts that can be learned using it in a reasonable (polynomial) number of steps. Although inherent algorithmic complexity appears to set serious limits to the range of concepts that can be learned, we show that there are some important nontrivial classes of propositional concepts that can be learned in a realistic sense.
Neural Network Methods for Boundary Value Problems Defined in Arbitrarily Shaped Domains

Partial differential equations (PDEs) with Dirichlet boundary conditions defined on boundaries with simple geometry have been succesfuly treated using sigmoidal multilayer perceptrons in previous works. This article deals with the case of complex boundary geometry, where the boundary is determined by a number of points that belong to it and are closely located, so as to offer a reasonable representation. Two networks are employed: a multilayer perceptron and a radial basis function network. The later is used to account for the satisfaction of the boundary conditions. The method has been successfuly tested on two-dimensional and three-dimensional PDEs and has yielded accurate solutions.
Deciphering Glioblastoma: Fundamental and Novel Insights into the Biology and Therapeutic Strategies of Gliomas

Gliomas constitute a diverse and complex array of tumors within the central nervous system (CNS), characterized by a wide range of prognostic outcomes and responses to therapeutic interventions. This literature review endeavors to conduct a thorough investigation of gliomas, with a particular emphasis on glioblastoma (GBM), beginning with their classification and epidemiological characteristics, evaluating their relative importance within the CNS tumor spectrum. We examine the immunological context of gliomas, unveiling the intricate immune environment and its ramifications for disease progression and therapeutic strategies. Moreover, we accentuate critical developments in understanding tumor behavior, focusing on recent research breakthroughs in treatment responses and the elucidation of cellular signaling pathways. Analyzing the most novel transcriptomic studies, we investigate the variations in gene expression patterns in glioma cells, assessing the prognostic and therapeutic implications of these genetic alterations. Furthermore, the role of epigenetic modifications in the pathogenesis of gliomas is underscored, suggesting that such changes are fundamental to tumor evolution and possible therapeutic advancements. In the end, this comparative oncological analysis situates GBM within the wider context of neoplasms, delineating both distinct and shared characteristics with other types of tumors.
Using the DIFF Command for Natural Language Processing

Diff is a software program that detects differences between two data sets and is useful in natural language processing. This paper shows several examples of the application of diff. They include the detection of differences between two different datasets, extraction of rewriting rules, merging of two different datasets, and the optimal matching of two different data sets. Since diff comes with any standard UNIX system, it is readily available and very easy to use. Our studies showed that diff is a practical tool for research into natural language processing.
A NEW ALTERNATIVE OF IMPROVING WATER QUALITY CONSUMPTION INDICATORS USING CURRENT STATISTICAL APPROACH SIX SIGMA (6σ)

The concern for quality assurance and improvement of water intended for technological and human consumption is a very topical issue at the state level to any organization, regardless of the activity profile and thus guarantees quality compliance (assurance), performance, competitiveness and organizational profitability. This paper addresses the need to improve water quality indicators of consumption through “Six Sigma”, a statistical method which is based on reducing non-conformities in specified limits and to ensure maximum effectiveness, equivalent to yield 3.4 defects per million opportunities.
Pre-Symptomatic Prediction of Plant Drought Stress Using Dirichlet-Aggregation Regression on Hyperspectral Images

Pre-symptomatic drought stress prediction is of great relevance in precision plant protection, ultimately helping to meet the challenge of "How to feed a hungry world? ". Unfortunately, it also presents unique computational problems in scale and interpretability: it is a temporal, large-scale prediction task, e.g., when monitoring plants over time using hyperspectral imaging, and features are `things' with a `biological' meaning and interpretation and not just mathematical abstractions computable for any data. In this paper we propose Dirichlet-aggregation regression (DAR) to meet the challenge. DAR represents all data by means of convex combinations of only few extreme ones computable in linear time and easy to interpret.Then, it puts a Gaussian process prior on the Dirichlet distributions induced on the simplex spanned by the extremes. The prior can be a function of any observed meta feature such as time, location, type of fertilization, and plant species. We evaluated DAR on two hyperspectral image series of plants over time with about 2 (resp. 5.8) Billion matrix entries. The results demonstrate that DAR can be learned efficiently and predicts stress well before it becomes visible to the human eye.
Shake to the Beat: Exploring the Seismic Signals and Stadium Response of Concerts and Music Fans

Large music festivals and stadium concerts are known to produce unique vibration signals that resemble harmonic tremor, particularly at frequencies around 1–10 Hz. This study investigates the seismic signals of a Taylor Swift concert performed on 5 August 2023 (UTC) as part of a series at SoFi Stadium in Inglewood, California, with an audience of ∼70,000. Signals were recorded on regional seismic network stations located within ∼9 km of the stadium, as well as on strong-motion sensors placed near and inside the stadium prior to the concert series. We automatically identified the seismic signals from spectrograms using a Hough transform approach and characterized their start times, durations, frequency content, particle motions, radiated energy, and equivalent magnitudes. These characteristics allowed us to associate the signals with individual songs and explore the nature of the seismic source. The signal frequencies matched the song beat rates well, whereas the signal and song durations were less similar. Radiated energy was determined to be a more physically relevant measure of strength than magnitude, given the tremor-like nature of the signals. The structural response of the stadium showed nearly equal shaking intensities in the vertical and horizontal directions at frequencies that match the seismic signals recorded outside the stadium. In addition, we conducted a brief experiment to further evaluate whether the harmonic tremor signals could be generated by the speaker system and instruments, audience motions, or something else. All evidence considered, we interpret the signal source as primarily crowd motion in response to the music. The particle motions of the strongest harmonics are consistent with Rayleigh waves influenced by scattered body waves and likely reflect how the crowd is moving. Results from three other musical performances at SoFi in summer 2023 were similar, although differences in the signals may relate to the musical genre and variations in audience motions.
Single Dose Intravenous Paracetamol versus Placebo in Postorthognathic Surgery Pain: A Randomized Clinical Trial

Background The postorthognathic surgery patients experienced moderate to severe pain and could be at risk for opioid-related side effects. The aim of this study was to evaluate the efficacy of a single dose of intravenous paracetamol to control postorthognathic surgery pain and reduce opioid consumption. Methods The patients were randomized into two groups. The study group received intravenous paracetamol and the control group received a placebo immediately postoperation. The visual analogue pain scale (VAS) at 1-, 4-, 8-, 12-, 16-, 20-, and 24 -h postoperatively, morphine consumption, side effects from morphine, and patient satisfaction were analyzed. Results Sixty-two patients (thirty-one patients in each group) were included. The postoperative VAS in the study group was significantly lower than those in the control group (p value <0.001) at all time points. The total postoperative morphine consumption in the study group (45.1 ± 21.2 mcg/kg) was significantly lower compared with the control group (136.5 ± 49.9 mcg/kg) (p value <0.001). Patient satisfaction was significantly higher in the study group (4.7 ± 0.5 out of 5 points) than in the control group (4.1 ± 0.7 out of 5 points) (p value <0.001). The incidence of nausea and vomiting was significantly lower in the study group compared with the control group (p value <0.001 and 0.002, respectively). Conclusion A single dose of intravenous paracetamol as part of multimodal analgesia was effective for postorthognathic surgery pain. It provided significant benefits to patients, including reduced pain scores, decreased opioid consumption, reduced nausea and vomiting, and improved satisfaction. This trial is registered with TCTR20210908002.
Benchmarking classification techniques using the Opportunity human activity dataset

Human activity recognition is a thriving research field. There are lots of studies in different sub-areas of activity recognition proposing different methods. However, unlike other applications, there is lack of established benchmarking problems for activity recognition. Typically, each research group tests and reports the performance of their algorithms on their own datasets using experimental setups specially conceived for that specific purpose. In this work, we introduce a versatile human activity dataset conceived to fill that void. We illustrate its use by presenting comparative results of different classification techniques, and discuss about several metrics that can be used to assess their performance. Being an initial benchmarking, we expect that the possibility to replicate and outperform the presented results will contribute to further advances in state-of-the-art methods.
A COMPARATIVE STUDY OF LAND SURFACE TEMPERATURE WITH DIFFERENT INDICES ON HETEROGENEOUS LAND COVER USING LANDSAT 8 DATA

Abstract. The temperature rise in urban areas has become a major environmental concern. Hence, the study of Land surface temperature (LST) in urban areas is important to understand the behaviour of different land covers on temperature. Relation of LST with different indices is required to study LST in urban areas using satellite data. The present study focuses on the relation of LST with the selected indices based on different land cover using Landsat 8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) data in Varanasi, India. A regression analysis was done between LST and Normalized Difference Vegetation index (NDVI), Normalized Difference Soil Index (NDSI), Normalized Difference Built-up Index (NDBI) and Normalized Difference Water Index (NDWI). The non-linear relations of LST with NDVI and NDWI were observed, whereas NDBI and NDSI were found to show positive linear relation with LST. The correlation of LST with NDSI was found better than NDBI. Further analysis was done by choosing 25 pure pixels from each land cover of water, vegetation, bare soil and urban areas to determine the behaviour of indices on LST for each land cover. The investigation shows that NDSI and NDBI can be effectively used for study of LST in urban areas. However, NDBI can explain urban LST in the better way for the regions without water body.
Emerging Stable Configurations in Cellular Automata

This paper considers how simple and limited entities, such as Cellular Automata (CA), can organize themselves giving rise to stable and complex behaviors. We begin by introducing Cellular Automata, simple discrete computational models useful to describe the evolution of a system following simple rules. Then we propose a possible architecture to implement a class of CA onto a Unix system. In particular, we propose a distributed solution where a number of cooperating processes cooperate in order to evolve the current configuration of the Universe.
Ulcerative Colitis, Seronegative Spondyloarthropathies and Allergic Diseases: the Search for a Link

Background: Allergic diseases and seronegative spondyloarthropathies are frequently observed in ulcerative colitis (UC). In this report we have investigated possible relationships between IgE-mediated allergic disease (AD), allergic contact dermatitis (ACD) and seronegative spondyloarthropathy (SpA) in UC patients at different grades and extensions of mucosa inflammation. Methods: Forty-five UC consecutive outpatients were graded according to clinical, endoscopic and histologic activity scores. SpA was diagnosed according to the European Spondyloarthropathy Study Group criteria. AD was detected by skin prick tests and confirmed by specific provocation tests, while ACD was diagnosed using the European standard series of patch tests. Thirty-seven patients' spouses or partners served as controls. Results: Fourteen patients and 1 control subject showed SpA ( P = 0.001). Diagnosis of rhinitis, conjunctivitis or asthma was made in 19 patients and in 5 controls ( P = 0.004), while ACD was found in 10 and in 4 ( P = 0.17), respectively. In UC, AD coexisted with SpA in 2 cases ( P = 0.01), AD with ACD in 1 case ( P = 0.03) and ACD with SpA in 5 ( P = 0.24). Conclusions: Notwithstanding the high frequency of AD and SpA found in UC, the concurrence of AD with SpA or ACD is an unusual finding, while SpA and ACD may coexist. These data suggest that, in UC, atopy and seronegative arthritis, as well as atopy and delayed-type allergy, are strongly polarized conditions tending to mutual exclusion. In UC, the presence of AD without SpA or ACD, and of SpA or ACD without AD may indicate subgroups of patients in which T-helper-2 cell or T-helper-1 cell responses predominate.
Minimum cuts in near-linear time

We significantly improve known time bounds for solving the minimum cut problem on undirected graphs. We use a "semiduality" between minimum cuts and maximum spanning tree packings combined with our previously developed random sampling techniques. We give a randomized (Monte Carlo) algorithm that finds a minimum cut in an <italic>m</italic>-edge, <italic>n</italic>-vertex graph with high probability in <italic>O</italic>(m log<supscrpt>3</supscrpt> <italic>n</italic>) time. We also give a simpler randomized algorithm that finds <italic>all</italic> minimum cuts with high probability in O(<italic>m</italic> log<supscrpt>3</subscrpt> <italic>n</italic>) time. This variant has an optimal <italic>RNC</italic> parallelization. Both variants improve on the previous best time bound of <italic>O<italic>(<italic>n<italic><supscrpt>2</supscrpt> log<supscrpt>3</supscrpt> <italic>n<italic>). Other applications of the tree-packing approach are new, nearly tight bounds on the number of <italic>near-minimum</italic> cuts a graph may have and a new data structure for representing them in a space-efficient manner.