Miracle-dz/UniFAR-FTUs huggingface dataset:
Coupling non-linear optical spectroscopy and surface chemistry: Towards new insights in atmospheric chemistry and aerosols

For decades, the observation of atmospheric processes in general and ice nucleation in particular bridged the scales from macroscopic to microscopic levels. They delivered a wide variety of results in cloud microphysics, particularly concerning the ice nucleation ability of atmospheric aerosol particles [1]. The surface properties of an ice-nucleating particle (INP) play a major role in its ice nucleation ability. This role is not well explored in terms of water/INP-surface molecular-level interactions. For example, we found recently that surface-charge induced templating hampers ice nucleation [2]. Aging of an INP in a cloud may change its surface properties and hence its ice nucleation efficiency. To improve our understanding of heterogeneous ice nucleation, we combine chemical and optical surface techniques to probe the change in surface properties of an INP and the corresponding water structuring on it, respectively. The presentation will show the different scenarios after aging of an INP in a cloud and the impact on its ice nucleation ability.
S100 Calcium-Binding Protein B and Glial Fibrillary Acidic Protein in Patients with Mild Traumatic Brain Injury

Objective: To examine the GFAP and S100B ability in prevention unnecessary brain Computed tomography (CT) scan in mild traumatic brain injury (mTBI) and compare them with the single extremity fracture in orthopedic patients. Methods: In this prospective cohort study, two orthopedics patients’ groups and mTBI patients were studied to assess the biomarkers’ ability in prevention unnecessary brain CT scan at the emergency setting. There were 40 orthopedics’ patients with single extremity fracture and 41 mTBI patients. Brain CT scans were done for all mTBI patients. Results: Brain CT scans showed no intracranial traumatic lesions. The median levels for S100B in the mTBI group was 14.8 (4.4-335.9) ng/L, and in orthopedic patients’ group was 13.3 (5-353.10) ng/L. Statistically significant differences were observed between both groups in S100B levels (p=0.006). The median Glial Fibrillary Acidic Protein (GFAP) levels in the mTBI patients’ group were 600 (400-16300) and in the orthopedic patients’ groups was 60 ng/L (300-14900). Statistically significant differences were observed between groups in GFAP (p=0.041). Conclusion: Our results showed that S100B and GFAP serum levels were significantly higher in patients with mTBI than in patients with a single limb fracture.
Molecular Motor or Molecular Clock: A Question of Load

The output of a motor is work, while the output of a clock is information. Here it is discussed how a molecular motor can produce both, work and information, depending on the load. If the ratio of the backward and forward stepping rates of a molecular motor increases exponentially with load, the change in free energy per step can be used to produce only work (at stall force) or only timing information (at zero force), or anything in between.
Viscoelastic Analysis of High Strain Composites for Deployable Structures in Space Applications

Thin-ply composite laminates capable of enduring high strains are currently under investigation for compliant deployable spacecraft structures. Deployable structures such as booms fabricated from these materials can be flattened and coiled to high curvatures, achieving a compact configuration for stowage. Once in orbit, they are released with minimal actuation for deployment, allowing the operational geometry to be recovered. Previous studies have shown that the viscoelastic properties of the composite epoxy matrix can negatively impact final shape accuracy due to stress relaxation during stowage. In addition, since the strain energy stored is relied upon for deployment, considerable relaxation can potentially result in deployment stall. Stress relaxation in composites and the aforementioned effects it can have on deployment have not been analyzed sufficiently for space applications. The objective of this thesis is to investigate the moment relaxation and curvature recovery behavior of thin-ply composite laminates through a combination of analytical, numerical, and experimental approaches. The viscoelastic Kirchhoff plate model that serves as the theoretical basis of the analyses is first presented. An analytical solution for the recovery of a composite plate after stowage is derived. The numerical integration of the viscoelastic plate constitutive equations and its implementation as a user-defined subroutine in finite element programs is then described. The subroutine allows relaxation of 3D thin-shell structures to be modeled, and is applied to simulate stowage and recovery of a thin-ply composite currently of interest for solar sailing applications. The subroutine is then compared with results obtained from experiments for a thin-ply composite for bending relaxation and curvature creep recovery after being unloaded.
Transformer-Based Deep Siamese Network for At-Scale Product Matching and One-Shot Hierarchy Classification

In the current digital world, improving user-product interaction is more important than ever for both consumers and merchants. In this paper, we present a Transformer-based deep Siamese network for product matching and one-shot product taxonomy classification: We begin by using textual descriptions of products as input data to train the Siamese network initialized using a Microsoft DeBERTa[1] pre-trained model. During training, the network minimizes the distance between similar pairs of products while pushing dissimilar pairs away from each other, and by doing so it learns to map products with similar descriptions to nearby locations in an embedding space, thereby creating "clusters" of similar products. Once trained, the model can output the contextual embeddings for any given product description. We then use these product embeddings as inputs to a downstream one-shot hierarchical classification task in order to predict the product’s taxonomy. For all existing products, the label (the product taxonomy) is based on the product internal catalog. Finally, we design and conduct multiple experiments to validate and verify this approach.
24 MORAL ROBOTS

To many, one of the most distinguishing human features is morality—that is, the capacity to perceive actions as moral or immoral and respond to them in very particular ways, such as by praising or blaming actors, demanding justifications, or accepting an apology. Members of a community are expected to abide by the moral norms and values of the community, and they pass on the knowledge of these norms through observed practices and explicit instruction. In addition, modern societies have made those norms explicit through philosophical reflection and formalized laws, thereby offering ethical foundations for their members to live by. We will thus use the term “moral” (e.g., in “moral processing” or “moral competence”) to refer to those aspects of the human cognitive system that are involved in the representation and processing of norms, values, and virtues. Morality, in this sense, is a natural phenomenon of social groups in their daily lives, a phenomenon that can be studied with empirical scientific methods. The scientific study of these phenomena is now typically called moral psychology. We reserve the term “ethical” for normative discussions and debates about abstract principles (e.g., the doctrine of double effect), theological origins of values, or the difference between ethical theories (e.g., Kantian, utilitarian). Ethics is then more of a philosophical, normative discipline. Consequently, it is possible for an agent to engage in moral decision making (i.e., involving ordinary moral information processing) but to perform an act that is considered unethical within some normative (theological or philosophical) system; conversely, it is possible for an agent to act in conformity with ethical principles even if the decision to act was not guided by the person’s moral processing of those abstract principles but, say, by imitation. This distinction helps distinguish two sets of questions that arise when considering the behavior of nonhuman agents, such as robots. One set of scholarly questions concerns the robot’s functional capacities and computational processes that mimic or adapt to human moral processing. This endeavor falls squarely within cognitive science, integrating, in particular, behavioral research and theorizing with computational modeling and engineering. Another set of scholarly questions concerns the ethical standards that robots should adhere to, the abstract principles (if any) the robots should implement, the ethical value of building morally competent robots in the first place, and so on. This endeavor falls into the domain of ethics as a normative discipline, typically conducted by philosophers or theologians.
Developing an Artificial Neural Network Algorithmic Trading System

The project proposes a type of Artificial Neural Network (ANN) known as Long Short Term Memory (LSTM) to predict the prices for a portfolio of best stocks from five different sectors since election. The current price, technical and fundamental indicators will be learned to predict the next day’s price. The LSTM model will modulate and internally optimize the prices based on certain rules. By comparing the actual and predicted prices, the network provides trading signals which will then be used to back-test the data on a reliable platform. Later, we compare the back-testing results to measure the performance and risk metrics for two types of investors – risk-averse and risk-seeking. The main purpose of this project is to develop a system which either performs on par or outperforms the market.
Comprehensive control of voltage loss enables 11.7% efficient solid-state dye-sensitized solar cells

The relatively large voltage loss (Vloss) in excitonic type solar cells severely limits their power conversion efficiencies (PCEs). Here, we report a comprehensive control of Vloss through efficacious engineering of the sensitizer and redox mediator, making a breakthrough in the PCE of dye-sensitized solar cells (DSSCs). The targeted down-regulation of Vloss is successfully realized by three valid channels: (i) reducing the driving force of electron injection through dye molecular engineering, (ii) decreasing the dye regeneration overpotential through redox mediator engineering, and (iii) suppressing interfacial electron recombination. Significantly, the “trade-off” effect between the dye optical band gap and the open-circuit voltage (VOC) is minimized to a great extent, achieving a distinct enhancement in photovoltaic performance (PCE > 11.5% with VOC up to 1.1 V) for liquid junction cells. The solidification of the best-performing device leads to a PCE of 11.7%, which is so far the highest efficiency obtained for solid-state DSSCs. Our work inspires further development in highly efficient excitonic solar cells by comprehensive control of Vloss.
6 Carbon Pricing Overlaps and Formal Collaboration

Putting a price on carbon provides a straightforward instrument for climate policy, but it also has important repercussions for energy use. This is because most emissions covered by carbon pricing and markets stem from industries with high energy use, and because carbon prices suppress the consumption of energy through directing the choice of fuels away from emissions-intensive fuels. A global price on carbon has been touted as the solution to climate change by actors across the political and geographical spectrum, especially economists (Ball 2018). It is no surprise then that the last ten years have seen a surge in international and transnational institutions aimed at promoting carbon pricing and carbon markets. A couple of such institutions have existed since the 1990s (most notably the International Emissions Trading Association, IETA), but most have appeared since 2007 (Sanderink et al. 2016). These institutions have promoted carbon taxes and emissions trading, as well as systems for the offsetting of emissions. More specifically, the general promotion of placing a price on carbon has taken its shape in the form of the setting of standards and commitments, information-sharing and networking, operational activities such as pilot and demonstration projects, and, to a lesser degree, financing. The overall purpose of this chapter is to provide an overview of the existing carbon pricing and trading institutions. Specific attention lies on mapping out their focus areas and points of interaction that shape the roles, areas of specialization, and underlying norms that relate to the pricing of carbon emissions. We illustrate that carbon-pricing institutions constitute a subfield of interconnected and interactive parts, which together perform crucial tasks of carbon taxing, emissions trading, and offsetting; all directed toward promoting wider carbon-pricing efforts. In this, we follow the argument of Sanderink et al. (2016), as well as Zelli et al., and Sanderink et al. in Chapters 2 and 3, that it is instructive to identify the
Stable variety selection over locations and recommendations for rose-scented geranium (Pelargonium graveolens L’ Herit. ex Aiton.)

Abstract Objective: In this study, productivity and essential oil quality of rose-scented geranium (Pelargonium graveolens L’ Herit. ex Aiton.) varieties, namely CIMAP Bio-G-171, CIM-Pawan and Bourbon were assessed and compared in two locations of north India. Methods: A field experiment was conducted to evaluate the productivity, while the chemical composition of the essential oils was assessed by GC-FID and GC-MS. Result: Yields of fresh leaves and essential oil from CIMAP Bio-G-171 were significantly higher (173.64–174.42 q h-1 and 69.93–79.06 l h-1) than those of CIM-Pawan (158.08–160.56 q h-1 and 55.57–64.46 l h-1) and Bourbon (133.34–139.33 q h-1 and 44.19–48.38 l h-1). Major constituents of the oils were citronellol (20.9–39.5%), geraniol (10.9–26.5%), linalool (2.9–14.2%), isomenthone (7.4–9.4%), citronellyl formate (5.5–9.1%) and 10-epi-γ-eudesmol (5.2–9.0%). Conclusion: The essential oil yields and chemical compositions were substantially influenced by variety and location of growing. The variety CIMAP Bio-G-171 showed improvement up to 58.2–63.4% and 22.6–25.8% in essential oil productivity over the existing prevalent varieties, Bourbon and CIM-Pawan, respectively.
Panoramic Learning with A Standardized Machine Learning Formalism

Machine Learning (ML) is about computational methods that enable machines to learn concepts from experiences. In handling a wide variety of experiences ranging from data instances, knowledge, constraints, to rewards, adversaries, and lifelong interplay in an ever-growing spectrum of tasks, contemporary ML/AI research has resulted in a multitude of learning paradigms and methodologies. Despite the continual progresses on all different fronts, the disparate narrowly-focused methods also make standardized, composable, and reusable development of learning solutions difﬁcult, and make it costly if possible to build AI agents that panoramically learn from all types of experiences. This paper presents a standardized ML formalism, in particular a standard equation of the learning objective, that offers a unifying understanding of diverse ML algorithms, making them special cases due to different choices of modeling components. The framework also provides guidance for mechanic design of new ML solutions, and serves as a promising vehicle towards panoramic learning with all experiences.
A Brief Overview of Results about Uniqueness of the Quantization in Cosmology

The purpose of this review is to provide a brief overview of recent conceptual developments regarding possible criteria to guarantee the uniqueness of the quantization in a variety of situations that are found in cosmological systems. These criteria impose certain conditions on the representation of a group of physically relevant linear transformations. Generally, this group contains any existing symmetry of the spatial sections. These symmetries may or may not be sufficient for the purpose of uniqueness and may have to be complemented with other remaining symmetries that affect the time direction or with dynamical transformations that are, in fact, not symmetries. We discuss the extent to which a unitary implementation of the resulting group suffices to fix the quantization—a demand that can be seen as a weaker version of the requirement of invariance. In particular, a strict invariance under certain transformations may eliminate some physically interesting possibilities in the passage to the quantum theory. This is the first review in which this unified perspective is adopted to discuss otherwise different uniqueness criteria proposed either in homogeneous loop quantum cosmology or in the Fock quantization of inhomogeneous cosmologies.
Pt‐Functionalized Nanoporous TiO2 Nanoparticles With Enhanced Gas Sensing Performances Toward Acetone

A facile hydrothermal method is used to prepare Pt‐functionalized nanoporous TiO2 nanoparticles. These are used as gas‐sensing material in sensors, fabricated according to the indirect heating method. Gas‐sensing performance of the sensors is investigated by testing their gas response to acetone, which exhibits favorable selectivity, good gas response value, fast response/recovery time, low detection concentration and good long‐term stability to acetone. Gas response β was defined as the ratio of Ra/Rg, where Ra and Rg are the resistance values of gas sensor exposed in air and objective gas, respectively. Among all these as‐prepared gas sensors, the 0.5% Pt‐functionalized TiO2 based gas sensor shows the highest gas response value of 29.51–200 ppm acetone at 300 °C, and the gas response value is 5.2 times higher than that (5.67) of pure TiO2 based gas sensor. It also has excellent selectivity to acetone when comparing with toluene, n‐butanol, isopropanol, ethanol, and methanol. The large specific surface area (168.101 m2 g−1) provides enough contacting interface between gas and the as‐prepared materials, then the gas molecules could be broken into CO2 and H2O by the active adsorbed oxygen species. The present results of the Pt‐functionalized TiO2 based gas sensors illustrates their potential application in detecting acetone.
A Light-weight contextual spelling correction model for customizing transducer-based speech recognition systems

It's challenging to customize transducer-based automatic speech recognition (ASR) system with context information which is dynamic and unavailable during model training. In this work, we introduce a light-weight contextual spelling correction model to correct context-related recognition errors in transducer-based ASR systems. We incorporate the context information into the spelling correction model with a shared context encoder and use a filtering algorithm to handle large-size context lists. Experiments show that the model improves baseline ASR model performance with about 50% relative word error rate reduction, which also significantly outperforms the baseline method such as contextual LM biasing. The model also shows excellent performance for out-of-vocabulary terms not seen during training.
A pH-based bio-rheostat: A proof-of-concept

New science and new technology need new materials and new concepts. In this respect, biological matter can play a primary role because it is a material with interesting and innovative features which has found several applications in technology, from highly sensitive sensors for medical treatments to devices for energy harvesting. Furthermore, most of its phenomenology remains unclear thus giving new hints for speculative investigations. In this letter, we explore the possibility to use a well-known photosensitive protein, the Reaction Center of Rhodobacter Sphaeroides, to build up an electrical pH sensor, i.e., a device able to change its resistance depending on the pH of the solution in which it crystalizes. By using a microscopic model successfully tested on analogue proteins, we investigate the electrical response of the Reaction Center single protein under different conditions of applied bias, showing the feasibility of the bio-rheostat hypothesis. As a matter of facts, the calculated resistance of this protein grows of about 100% when going from a pH = 10 to a pH = 6.5. Moreover, calculations of the conductance response in a wide range of applied bias point out interesting deviations from the linear regime. All findings are in qualitative agreement with the known role of pH in biochemical activities of Reaction Center and similar proteins, therefore supporting a proof-ofconcept for the development of new electron devices based on biomaterials.
Velocity transformation for compressible wall-bounded turbulent flows with and without heat transfer

Significance Near a solid wall, the mean velocity of an incompressible fluid is a nearly universal function of the distance from the wall when appropriately transformed (nondimensionalized). For high-speed compressible flows, due to the wall-normal variations of density and viscosity, it has not been established how to transform a dimensional velocity profile into a universal profile. We propose a transformation that is more accurate and more broadly applicable than existing approaches. This improvement results from deploying different physical arguments for the two critical subdomains of a boundary layer. The transformation can be used to extend incompressible turbulence models to compressible turbulent flows, such as those encountered by vehicles for high-speed transportation and planetary reentry. In this work, a transformation, which maps the mean velocity profiles of compressible wall-bounded turbulent flows to the incompressible law of the wall, is proposed. Unlike existing approaches, the proposed transformation successfully collapses, without specific tuning, numerical simulation data from fully developed channel and pipe flows, and boundary layers with or without heat transfer. In all these cases, the transformation is successful across the entire inner layer of the boundary layer (including the viscous sublayer, buffer layer, and logarithmic layer), recovers the asymptotically exact near-wall behavior in the viscous sublayer, and is consistent with the near balance of turbulence production and dissipation in the logarithmic region of the boundary layer. The performance of the transformation is verified for compressible wall-bounded flows with edge Mach numbers ranging from 0 to 15 and friction Reynolds numbers ranging from 200 to 2,000. Based on physical arguments, we show that such a general transformation exists for compressible wall-bounded turbulence regardless of the wall thermal condition.