Miracle-dz/UniFAR-FTUs huggingface dataset:
Nanostructures of graphene oxide modified with ZnO: synthesis and photocatalyst evaluation under sunlight

Abstract Multiple nanostructures of graphene oxide (GO) and Zinc oxide (ZnO) have been prepared via alcoholic reduction of GO, where took place the ZnO incorporation with different weight ratios. The X-ray diffraction patterns shown the ZnO anchored between GO sheets consequently produce a significant displacement of the GO characteristic pattern to lowers angles. In addition, the alcoholic reduction process allows generating another Zinc Nanostructure, the presence of Zinc Peroxide (ZnO2) is confirmed by two signals at 37.8° and 43.1° in XRD. The metallic semiconductor anchored is evident in Raman Spectra, because a displacement of D and G band. The ZnO characteristics bands appear in the spectra, however, near to 474 cm−1 a small band is shown, this band indicates the presence of ZnO2, reaffirming the observed in XRD. In thermogravimetric analysis (TGA) the materials (GO, rGO/ZnO) shown similar tendencies, but, in DTG curves is observed different reactions because the species presents in the materials. Bandgap estimation was calculate by Reflectance UV–vis spectroscopy, adjusted by Kubelka-Munk, all rGOZnO material presents visible light activation. By photodegradation of Methylene Blue (MB) under sunlight confirms the Bandgap estimation obtained by Kubelka-Munk. In this work, the alcoholic reduction of GO for metallic semiconductors anchored is a viable method, improving optical and electronic properties of ZnO, allowing these material multiple applications such as optoelectronic, photovoltaic devices and photocatalysis.
FUSION OF HYPERSPECTRAL, MULTISPECTRAL, COLOR AND 3D POINT CLOUD INFORMATION FOR THE SEMANTIC INTERPRETATION OF URBAN ENVIRONMENTS

Abstract. In this paper, we address the semantic interpretation of urban environments on the basis of multi-modal data in the form of RGB color imagery, hyperspectral data and LiDAR data acquired from aerial sensor platforms. We extract radiometric features based on the given RGB color imagery and the given hyperspectral data, and we also consider different transformations to potentially better data representations. For the RGB color imagery, these are achieved via color invariants, normalization procedures or specific assumptions about the scene. For the hyperspectral data, we involve techniques for dimensionality reduction and feature selection as well as a transformation to multispectral Sentinel-2-like data of the same spatial resolution. Furthermore, we extract geometric features describing the local 3D structure from the given LiDAR data. The defined feature sets are provided separately and in different combinations as input to a Random Forest classifier. To assess the potential of the different feature sets and their combination, we present results achieved for the MUUFL Gulfport Hyperspectral and LiDAR Airborne Data Set.
The ISOPHOT Interactive Analysis PIA, a Calibration and Scientic Analysis Tool

ISOPHOT is one of the instruments on board the Infrared Space Observatory (ISO), launched in November 1995 by the European Space Agency. ISOPHOT Interactive Analysis, PIA, is a scientific and calibration data analysis tool for ISOPHOT data reduction. The PIA software was designed both as a tool for use by the instrument team for calibration of the PHT instrument during and after the ISO mission, and as an interactive tool for ISOPHOT data analysis by general observers. It has been jointly developed by the ESA Astrophysics Division (responsible for planning, direction, and execution) and scientific institutes forming the ISOPHOT consortium. PIA is entirely based on the Interactive Data Language IDL (IDL92). All the capabilities of input/output, processing, and visualization can be reached from window menus for all the different ISOPHOT sub-systems, in all levels of data reduction from digital raw data, coming from the ISO telemetry, to the final level of calibrated images, spectra, and multi-filter, multi-aperture photometry. In this article, we describe the structure of the package, putting special emphasis on the internal data organization and management. 1Currently at the ISO Science Operations Centre, Villafranca, Apdo 50727, E-28080 Madrid, Spain 2Now at the Max-Planck Institut für Radioastronomie, Bonn, Germany
Pyrolysis-based separation mechanism for waste crystalline silicon photovoltaic modules by a two-stage heating treatment

Heating treatment is the mainstream method to separate the modules in the waste photovoltaic (PV) module recycling process, which has not been studied thoroughly. In the present study, a two-stage heating treatment was conducted to separate the waste crystalline silicon solar panels. The TPT backing material could be recovered integrally by heating at 150 °C for 5 min, which was conducive to further recycling and regeneration. The poly(ethylene-co-vinyl) acetate (EVA) binder was removed by the pyrolysis process at the temperature of 500 °C; acetic acid and several hydrocarbon compounds were the main products of the pyrolysis process. Analysis showed that the pyrolysis of the EVA binder could be divided into two stages: deacetylation process (acetic acid formation) and long chain scission with radical reactions (hydrocarbon formation). Furthermore, the pyrolysis kinetics and pyrolysis mechanisms were studied based on the experimental data and sufficient theoretical foundation. Acetic acid was generated by the deacetylation process through a six-member cyclic transition state, and several hydrocarbon compounds were generated through a series of long chain scissions, free radical migrations and Diels–Alder cycloadditions. In this study, undamaged TPT backing materials, glass and silicon wafers were obtained, which could be recycled by further treatment. This study could perfect the process of waste crystalline silicon solar panel recycling and provide a fundamental basis for recycling the waste crystalline silicon solar panels in an environmentally friendly and efficient manner.
Discovering Precise Temporal Patterns in Large-Scale Neural Recordings through Robust and Interpretable Time Warping

Though the temporal precision of neural computation has been studied intensively, a data-driven determination of this precision remains a fundamental challenge. Reproducible spike time patterns may be obscured on single trials by uncontrolled temporal variability in behavior and cognition, or may not even be time locked to measurable signatures in either behavior or local field potentials (LFP). To overcome these challenges, we describe a general-purpose time warping framework that reveals precise spike-time patterns in an unsupervised manner, even when spiking is decoupled from behavior or is temporally stretched across single trials. We demonstrate this method across diverse systems: cued reaching in nonhuman primates, motor sequence production in rats, and olfaction in mice. This approach flexibly uncovers diverse dynamical firing patterns, including pulsatile responses to behavioral events, LFP-aligned oscillatory spiking, and even unanticipated patterns, like 7 Hz oscillations in rat motor cortex that are not time-locked to measured behaviors or LFP.
Understanding Humans And Objects Based On Context

Contextual information, such as positions, of each entity of interest, such as human, in a photo or video can provide much information and knowledge about the content of the photo or video in question. In this thesis work, we investigate the benefit of analyzing positions and context under various novel settings. Furthermore, we explore ways of extracting the 3D position information about humans from a single photo. Our work indicates that incorporating the spatiotemporal constraints for moving cars with their natural speed upper bound can greatly improve the driving history reconstruction of the car in question. In addition, knowing the positions of each human relative to one another in a photo is shown to improve the prediction of the age and gender of each. Furthermore, the relative positions of the faces in a group shot can reveal the type of social event under which this shot was taken. We also show how to extract approximate 3D position information about humans based only on a single 2D photo. In conclusion, this thesis affirms the benefits of analyzing positions of objects of interests in various novel settings and opens a vista for further research in the area. This document is dedicated to all Cornell graduate students.
Clinical profile of cases with sino-nasal polyposis at a tertiary care hospital at North Karnataka: a cross-sectional study

Background: Nasal polyps are defined as pearly white, prolapsed, pendunculated oedematous Sino-nasal mucosa. They are unique in their position and their composition. Many hypotheses concerning its pathogenesis have been proposed. But till now there is no clear evidence for any single cause. This study was taken-up to study the clinical profile of cases with sino-nasal polyps.Methods: Cross-sectional descriptive study was conducted in the Department of Otolaryngology at Vijayanagara Institution of Medical Sciences, Bellary, between January 2016 to April 2016 involving 60 patients fulfilling inclusion and exclusion criteria. Pre-tested and edited proforma was used to collect the data. Results: Out of 60 participants, 63.4% were males, mean age was 29.5 years. Ethmoidal polyp (63.4%) was the most common polyp followed by antrochoanal polyp (33.4%). Ethmoidal polyp was most commonly observed 31-40 years age while antrochoanal polyp was observed in 11-20 years age. Ethmoidal polyp and antrochoanal polyp were observed more commonly in males and females respectively. The most common presenting symptoms were nasal obstruction and nasal discharge.Conclusions: Ethmoidal polyps are the most commonly observed sino-nasal polyps followed by antrochoanal polyp. Ethmoidal polyp was more commonly observed in adult age group while antrochoanal polyp was observed in children. The most common presenting symptoms were nasal obstruction and nasal discharge.
Thermodynamics of computing with circuits

Digital computers implement computations using circuits, as do many naturally occurring systems (e.g., gene regulatory networks). The topology of any such circuit restricts which variables may be physically coupled during the operation of the circuit. We investigate how such restrictions on the physical coupling affects the thermodynamic costs of running the circuit. To do this we first calculate the minimal additional entropy production that arises when we run a given gate in a circuit. We then build on this calculation, to analyze how the thermodynamic costs of implementing a computation with a full circuit, comprising multiple connected gates, depends on the topology of that circuit. This analysis provides a rich new set of optimization problems that must be addressed by any designer of a circuit, if they wish to minimize thermodynamic costs.
An initial categorization of foundational research in complex technical systems

There has been intense foundational research in complex technical systems (CTSs) over the last half century. These systems are exemplified by advanced mechatronics systems, embedded control systems, real-time systems, agent-based smart systems, distributed software systems, internet of things systems, and cyber-physical systems. The objective of this paper is to offer an initial cataloguing of the various research domains and to identify the major research issues. The paper has an ontological flavour, because it concentrates on what research has been and is being done, rather than on why and how research is done. The underpinning study has been done in three stages: (i) intuition-driven exploration of a reference set of related academic publications, (ii) evidence-based specification of a categorization of the domains and subdomains of research, and (iii) refinement and validation of the proposed classification based on a control set of related academic publications. The proposed reasoning model identifies three categories of research domains. The ‘intellectualizations’ category includes research domains such as: (i) philosophy, (ii) ontology, and (iii) epistemology of CTSs. The research domains included in the ‘realizations’ category are: (iv) methodology, and (v) creation of CTSs. The domains considered in the ‘influences’ category are: (vi) manifestations, and (vii) axiology of CTSs. Based on the proposed reasoning model a landscape of foundational research in CTSs is proposed for public debate. Our follow-up study focuses on the extension of the proposed classification to other families of complex engineered systems such as sociotechnical systems and social ecosystems.
A Theory of Collective Cell Migration and the Design of Stochastic Surveillance Strategies

Author(s): George, Mishel | Advisor(s): Bullo, Francesco; Campas, Otger | Abstract: In nature, complex emergent behavior arises in groups of biological entities often as a result of simple local interactions between neighbors in space or on a network. In such cases, scientific inquiry is typically aimed at inferring these local rules. Conversely, in teams of robots, the goal is to create decentralized control laws which results in efficient global behavior. These behaviors are designed for tasks such as maintaining formation control, performing effective coverage control or persistently monitoring an environment. With this in mind, we consider the following: 1g the emergence of collective cell migration from local contact and mechanical feedback and 2g the design of unpredictable surveillance strategies for teams of robots.Collective cell migration is an essential part of tissue and organ morphogenesis during embryonic development, as well as of various disease processes, such as cancer. The vast majority of theoretical descriptions of collective cell behavior focus on large numbers of cells, but fail to accurately capture the dynamics of small groups of cells. Here we introduce a low-dimensional theoretical description that successfully describes single cell migration, cell collisions, collective dynamics in small groups of cells, and force propagation during sheet expansion, all within a common theoretical framework. We also explain the counter-intuitive observation that pairs of cells repel each other upon collision while they coordinate their motion in larger clusters.Conventional monitoring strategies used by teams of robots are deterministic in nature making it possible for intelligent intruders who study the motion of the patrolling agent to compromise the patrol route. This problem can be solved by designing random walkers on graphs which naturally incorporate unpredictability. Within this framework, we study and provide the first analytic expression for the first meeting time of multiple random walkers, in terms of their transition matrices. We also study two problems related to maximizing unpredictability: given graph and visit frequency constraints, 1g maximize the entropy rate generated by a Markov chain, and 2g maximize the return time entropy associated with the Markov chain, where the return time entropy is the weighted average over all graph nodes of the entropy of the first return times of the Markov chain.
Nest temperatures of the Piai and Sayang Islands green turtle (Chelonia mydas) rookeries, Raja Ampat Papua, Indonesia: Implications for hatchling sex ratios

Tapilatu RF, Ballamu F. 2015. Nest temperatures of the Piai and Sayang Islands green turtle (Chelonia mydas) rookeries, Raja Ampat Papua, Indonesia: Implications for hatchling sex ratios. Biodiversitas 16: 102-107. Sex determination and hatching success in sea turtles is temperature dependent. Warmer sand temperatures may skew sea turtle population sex ratios towards predominantly females and high sand temperatures may also decrease hatching success. Therefore, understanding nest temperatures is important for conservation programs, including the evaluation of the potential impact of global climate change. Nest temperatures were monitored during the 2013 nesting season of the green sea turtle, Chelonia mydas, at Piai and Sayang Islands, Raja Ampat, West Papua, Indonesia. Nest temperatures increased from 29oC early in the incubation to 34-36oC in the middle, before decreasing again. Monitored nest temperatures were similar across all beaches. Nest temperatures increased 2-4oC during the middle third of incubation due to metabolic heating. Hatchling sex ratio inferred from nest temperature profiles indicated a strong female bias. This finding is consistent with the relatively warm thermal profiles of the majority of the nesting beaches. This also included some extremely warm nest temperatures that were associated with lower hatching success. Information from this study provides a foundation for developing conservation strategies for enhancing hatchling production with optimal sex ratios at the most important nesting beaches for the western Pacific green sea turtle. This study is the first comprehensive assessment of sex ratios for green sea turtles in Raja Ampat and represents the initiation of a long-term database that can be used at a local level to develop strategies that could potentially offset the impact of long-term climate change on the western Pacific green sea turtle.Keywords: Chelonia mydas, hatching success, Piai, Sayang, sex determination
Analysing Object-Capability Patterns With Mur'

Object Capability (OCap) patternscan be used to enforcethe principle of least authority. However, despite the popularity and promise of OCap patterns, these patterns have not been sufficiently analyzed or verified. We analyze several OCap patterns using the Mur' verification tool and confirm the utility of our model by finding previously known vulnerabilities. Because these vulnerabilities were not repaired in previous studies, we provide new patterns and verify their correctness, within the accuracy of our model. Considering both distributed system and language-based settings that are designedto supportthe OCap model,we showthat somepatterns that are secure in a language context are vulnerablein a distributed systems context. We further demonstrate implementable attacks on the revocable forwarder and sealer/unsealer patterns, using a (distributed) subset of E and provide code illustrating and implementing repairs.
Behavioral and Neural Signatures of Working Memory in Childhood

Working memory function changes across development and varies across individuals. The patterns of behavior and brain function that track individual differences in working memory during human development, however, are not well understood. Here, we establish associations between working memory, other cognitive abilities, and functional MRI (fMRI) activation in data from over 11,500 9- to 10-year-old children (both sexes) enrolled in the Adolescent Brain Cognitive Development (ABCD) Study, an ongoing longitudinal study in the United States. Behavioral analyses reveal robust relationships between working memory, short-term memory, language skills, and fluid intelligence. Analyses relating out-of-scanner working memory performance to memory-related fMRI activation in an emotional n-back task demonstrate that frontoparietal activity during a working memory challenge indexes working memory performance. This relationship is domain specific, such that fMRI activation related to emotion processing during the emotional n-back task, inhibitory control during a stop-signal task (SST), and reward processing during a monetary incentive delay (MID) task does not track memory abilities. Together, these results inform our understanding of individual differences in working memory in childhood and lay the groundwork for characterizing the ways in which they change across adolescence. SIGNIFICANCE STATEMENT Working memory is a foundational cognitive ability that changes over time and varies across individuals. Here, we analyze data from over 11,500 9- to 10-year-olds to establish relationships between working memory, other cognitive abilities, and frontoparietal brain activity during a working memory challenge, but not during other cognitive challenges. Our results lay the groundwork for assessing longitudinal changes in working memory and predicting later academic and other real-world outcomes.
Words and patterns: lexico-grammatical patterns and semantic relations in domain-specific discourses

The underlying assumption of this study is the understanding of a specialized term as a summary of disciplinary knowledge, formalized at a textual level in the contextual relations which structure disciplinary lexical knowledge and are therefore essential for the successful interpretation of a text. With that aim this paper carries the analysis of the lexico-grammatical patterns which signal the hyponymy and meronymy relations of the term building, a key disciplinary concept in a corpus of construction engineering textbooks, using the WordNet database for reference. The linguistic analysis of the repertoire of lexico-grammatical patterns employed brings to the fore the dual role of hyponymy and meronymy as both semantic and metalinguistic discourse-organizing lexical resources, key in the rhetorical organization of the discourse of this discipline.
Dynamic Optimization through the use of Automatic Runtime Specialization

Profile-driven optimizations and dynamic optimization through specialization have taken optimizations to a new level. By using actual run-time data, optimizers can generate code that is specially tuned for the task at hand. However, most existing compilers that perform these optimizations require separate test runs to gather profile information, and/or user annotations in the code. In this thesis, I describe run-time optimizations that a dynamic compiler can perform automatically — without user annotations — by utilizing real-time performance data. I describe the implementation of the dynamic optimizations in the framework of a Java Virtual Machine and give performance results. Thesis Supervisor: Martin Rinard Title: Assistant Professor