Miracle-dz/UniFAR-FTUs huggingface dataset:
BYU ScholarsArchive BYU ScholarsArchive Satisficing negotiations Satisficing negotiations

—Negotiation procedures that are founded on the doc- trine of individual rationality, where each participant is committed to maximizing its own satisfaction, are limited in their ability to accommodate the interests of others, and therefore, may unneces-sarily constrain the negotiability of a decision maker, particularly in cooperative environments. Satisﬁcing game theory provides a distinct alternative to the hyperrationality of conventional rational choice by waiving reliance on the individual rationality premise and offering an approach to negotiatory decision making that is based on a well-deﬁned mathematical notion of satisﬁcing, or being good enough, that permits the modeling of complex interrela- tionships between agents. This approach provides a mechanism to compute the attitude, or degree of conﬂict or contentedness, of the negotiators. Examples illustrate both single-round and multiround satisﬁcing negotiation protocols.
Improving Language Model Predictions via Prompts Enriched with Knowledge Graphs

Despite advances in deep learning and knowledge graphs (KGs), using language models for natural language understanding and question answering remains a challenging task. Pre-trained language models (PLMs) have shown to be able to leverage contextual information, to complete cloze prompts, next sentence completion and question answering tasks in various domains. Unlike structured data querying in e.g. KGs, mapping an input question to data that may or may not be stored by the language model is not a simple task. Recent studies have highlighted the improvements that can be made to the quality of information retrieved from PLMs by adding auxiliary data to otherwise naive prompts. In this paper, we explore the effects of enriching prompts with additional contextual information leveraged from the Wikidata KG on language model performance. Specifically, we compare the performance of naive vs. KG-engineered cloze prompts for entity genre classification in the movie domain. Selecting a broad range of commonly available Wikidata properties, we show that enrichment of cloze-style prompts with Wikidata information can result in a significantly higher recall for the investigated BERT and RoBERTa large PLMs. However, it is also apparent that the optimum level of data enrichment differs between models.
Horloge atomique à piégeage cohérent de population du césium en cellule : limitations à la stabilité de fréquence

Ce memoire porte sur l’etude de la stabilite de frequence d’une horloge atomique a piegeage coherent de population. Le cadre de cette etude est d’une part d’approfondir la connaissance du piegeage coherent de population en cellule de vapeur et d’autre part de construire un prototype d’horloge demontrant une stabilite de frequence a l’etat de l’art des meilleures horloges compactes de laboratoire. Grâce a une interrogation impulsionnelle et un schema d’excitation en polarisations lineaires et orthogonales, cette horloge presenterait une stabilite de frequence relative nettement inferieure a 10^-13 a 1 s si elle etait limitee par un bruit fondamental tel que le bruit de photon. Apres une presentation du montage experimental, la premiere partie de ce memoire est consacree a l’etude des differentes sources de bruit limitant la stabilite de frequence court-terme. Le soin particulier donne a la modelisation, a la caracterisation experimentale et a la reduction des transferts de bruit de frequence de l’oscillateur local (effet Dick) et du bruit d’intensite du laser en bruit de frequence de l’horloge, a permis de mesurer une stabilite de frequence au niveau de 3.2x10^-13 a 1 s. Dans un deuxieme temps une etude theorique et experimentale du deplacement de frequence micro-onde en fonction de la puissance laser est presentee. Au-dela de la mise en evidence du caractere cle de la deformation de la raie dans l’explication de ce deplacement, elle a pose les bases de la derniere partie de ce memoire qui propose une methode d’insensibilisation du deplacement de frequence aux fluctuations de puissance.
Deep Learning Methods for 3D Garment Digitization

The reconstruction of 3D objects from monocular images is an active field of research in 3D computer vision which is further boosted by advancements in deep learning. In context of human body, modeling realistic 3D virtual avatars from 2D images is a recent trend, thanks to the advent of AR/VR & metaverse. The problem is challenging, owing to non-rigid nature of human body, especially because of the garments. Various attempts have been made to solve the problem, at least for relatively tighter clothing styles, but loose clothing styles still pose a huge challenge. This problem has also sparked quite an interest in the fashion e-commerce domain, where the objective is to model the 3D garments, independent from the underlying body, in order to enable intriguing applications like virtual try-on systems. 3D garment digitization has been garnering a lot of interest in the past few years, as the demand for online window-shopping and other e-commerce activities has increased in the recent years, where the unfortunate crisis of COVID-19 plays a huge role. Though the problem of 3D digitization of garments seems intriguing, solving it is not as straightforward as it looks. There are existing works out there in the field, majority of which are deep learning based solutions. Most of these methods rely on predefined garment templates which makes the task of texture synthesis easier, but restrict the usage to a fixed number of garment styles for which templates are available. Additionally, these methods do not deal with issues like complex poses and self-occlusions which are very common under in-the-wild assumption. Template-free methods are also explored which enables modeling arbitrary clothing styles, however, they lack texture information which is essential for high-quality photorealistic appearance. The thesis aims to resolve aforementioned issues by providing novel solutions. The main objective is 3D digitization of garments from a monocular RGB image of a person wearing the garment, both in template-based and template-free settings. Initially, we address challenges in existing state-of-the-art template-based methods. We aim to handle complex human poses, occlusions etc. by proposing to use a robust keypoint regressor which estimates keypoints on input monocular image. These keypoints define thin-plate-spline (TPS) based warping of texture from input image to the UV space of a predefined template. Then, we utilize a deep inpainting network to handle missing texture information. In order to train these neural networks, we curate a synthetic dataset of garments with varying textures, draped on 3D human characters in various complex poses. This dataset helps in robust training and generalization to real images. We achieve state-of-the-art results for specific clothing styles (e.g. t-shirt and trouser). However, template-based
An OS-agnostic Approach to Memory Forensics

—The analysis of memory dumps presents unique challenges, as operating systems use a variety of (often un-documented) ways to represent data in memory. To solve this problem, forensics tools maintain collections of models that precisely describe the kernel data structures used by a handful of operating systems. However, these models cannot be generalized and developing new models may require a very long and tedious reverse engineering effort for closed source systems. In the last years, the tremendous increase in the number of IoT devices, smart-home appliances and cloud-hosted VMs resulted in a growing number of OSs which are not supported by current forensics tools. The way we have been doing memory forensics until today, based on handwritten models and rules, cannot simply keep pace with this variety of systems. To overcome this problem, in this paper we introduce the new concept of OS-agnostic memory forensics , which is based on techniques that can recover certain forensics information without any knowledge of the internals of the underlying OS. Our approach allows to automatically identify different types of data structures by using only their topological constraints and then supports two modes of investigation. In the ﬁrst, it allows to traverse the recovered structures by starting from predetermined seeds , i.e., pieces of forensics-relevant information (such as a process name or an IP address) that an analyst knows a priori or that can be easily identiﬁed in the dump. Our experiments show that even a single seed can be sufﬁcient to recover the entire list of processes and other important forensics data structures in dumps obtained from 14 different OSs, without any knowledge of the underlying kernels. In the second mode of operation, our system requires no seed but instead uses a set of heuristics to rank all memory data structures and present to the analysts only the most ‘promising’ ones. Even in this case, our experiments show that an analyst can use our approach to easily identify forensics-relevant structured information in a truly OS-agnostic scenario.
Effect of mixotrophy on lipid content and fatty acids methyl esters pro�le by Chlorella zo�ngiensis grown in media containing sugar cane molasses

The effect of mixotrophy on lipid content and fatty acids methyl ester (FAME) profile 2 by Chlorella zofingiensis is investigated in this work. For this purpose, growth media 3 containing specific concentrations of sugar cane molasses, are used to sustain 4 microalgae growth. Lipids have been extracted from microalgae and then 5 characterized. Specifically, all FAMEs have been quantitatively and qualitatively 6 analyzed in order to improve biodiesel properties. Results showed that using specific 7 concentrations of molasses the total lipid content increased up to 20% compared to 8 the control. FAME profile revealed a 97% composition in C16-C18 where unsaturated 9 fatty acids reached a high portion (77%) when using 2 g L -1 molasses. Main 10 characteristics of biodiesel obtainable from the algal lipids are also evaluated. Based on 11 the biomass and lipid productivity achieved during the experiments as well as on the 12 compliance of the corresponding biodiesel characteristics with its international 13 standards, it can be stated that molasses waste is a viable option as a cheap medium for 14 the cultivation of Chlorella zofingiensis . 15 16
The APOGEE-2 Survey of the Orion Star-forming Complex. I. Target Selection and Validation with Early Observations

The Orion Star-forming Complex (OSFC) is a central target for the APOGEE-2 Young Cluster Survey. Existing membership catalogs span limited portions of the OSFC, reflecting the difficulty of selecting targets homogeneously across this extended, highly structured region. We have used data from wide-field photometric surveys to produce a less biased parent sample of young stellar objects (YSOs) with infrared (IR) excesses indicative of warm circumstellar material or photometric variability at optical wavelengths across the full 420 square degree extent of the OSFC. When restricted to YSO candidates with H < 12.4, to ensure S/N ∼ 100 for a six-visit source, this uniformly selected sample includes 1307 IR excess sources selected using criteria vetted by Koenig & Liesawitz (2014) and 990 optical variables identified in the Pan-STARRS1 3π survey: 319 sources exhibit both optical variability and evidence of circumstellar disks through IR excess. Objects from this uniformly selected sample received the highest priority for targeting, but required fewer than half of the fibers on each APOGEE-2 plate. We filled the remaining fibers with previously confirmed and new color–magnitude selected candidate OSFC members. Radial velocity measurements from APOGEE-1 and new APOGEE-2 observations taken in the survey’s first year indicate that ∼90% of the uniformly selected targets have radial velocities consistent with Orion membership. The APOGEE-2 Orion survey will include >1100 bona fide YSOs whose uniform selection function will provide a robust sample for comparative analyses of the stellar populations and properties across all sub-regions of Orion.
Integration of Digital Signal Processing Block in SymbiFlow FPGA Toolchain for Artix-7 Devices

v TABLE OF CONTENTS . vi LIST OF TABLES . viii LIST OF FIGURES . ix CHAPTER 1 INTRODUCTION . 1 1.1 Xilinx Vivado . 3 1.2 SymbiFlow Toolchain . 3 1.3 DSP Blocks . 4 1.4 Thesis Outline . 7 CHAPTER 2 SYMBIFLOW . 8 2.1 Yosys . 9 2.2 VPR / Genfasm . 9 2.3 Project X-Ray . 10 2.4 Using SymbiFlow . 11 2.5 State of DSP Block Usage in SymbiFlow . 13 CHAPTER 3 ARCHITECTURE DEFINITIONS AND GENFASM . 15 3.1 SymbiFlow Architecture Definitions . 15 3.1.1 Architecture Primitives . 15 3.1.2 Generating Routing Graph and Architecture File . 17 3.1.3 Developing A Basic DSP48E1 Primitive . 17 3.2 2x2 bit Multiplier Design Under Test (DUT) . 19 3.2.1 Symmetric Flow through SymbiFlow and Vivado . 19 3.2.2 Differences between SymbiFlow and Vivado FASM files . 21 CHAPTER 4 – COMPLETE SYMBIFLOW DSP BITSTREAM . 24 4.1 Diagnosing DSP Support Points . 24 4.2 Investigating the Vivado Routing Resources GUI . 24 4.3 Yosys DSP Information into VPR . 30 4.4 Developing DSP48E1 Primitive . 32
Amyloid-beta peptide induces oligodendrocyte death by activating Amyloid-beta peptide induces oligodendrocyte death by activating the neutral sphingomyelinase-ceramide pathway the neutral sphingomyelinase-ceramide pathway

myloid- (cid:2) peptide (A (cid:2) ) accumulation in senile plaques, a pathological hallmark of Alzheimer’s disease (AD), has been implicated in neuronal degeneration. We have recently demonstrated that A (cid:2) induced oligodendrocyte (OLG) apoptosis, suggesting a role in white matter pathology in AD. Here, we explore the molecular mechanisms involved in A (cid:2) -induced OLG death, examining the potential role of ceramide, a known apoptogenic mediator. Both A (cid:2) and ceramide induced OLG death. In addition, A (cid:2) activated neutral sphingomyelinase (nSMase), but not acidic sphingomyelinase, resulting in increased ceramide generation. Blocking ceramide degradation with A N -oleoyl-ethanolamine exacerbated A (cid:2) cytotoxicity; and addition of bacterial sphingomyelinase (mimicking cellular nSMase activity) induced OLG death. Furthermore, nSMase inhibition by 3- O -methyl-sphingomyelin or by gene knockdown using antisense oligonucleotides attenuated A (cid:2) -induced OLG death. Glutathione (GSH) precursors inhibited A (cid:2) activation of nSMase and prevented OLG death, whereas GSH depletors increased nSMase activity and A (cid:2) -induced death. These results suggest that A (cid:2) induces OLG death by activating the nSMase–ceramide cascade via an oxidative mechanism.
Intrinsic Defect Properties in Halide Double Perovskites for Optoelectronic Applications

Lead-free halide double perovskites with the formula of quaternary A$_2^+$B'B'$^{3+}$X$_6^-$ have recently attracted intense interest as alternatives to lead-halide-perovskite-based optoelectronic materials for their non-toxicity and enhanced chemical and thermodynamic stability. However, the understanding of intrinsic defect properties and their effects on carrier transport and Fermi level tuning is still limited. In this paper, we show that, by exploring the phase diagram of a halide double perovskite, one can control the effects of intrinsic defects on carrier trapping and Fermi level pinning. We reveal the ideal growth conditions to grow p-type Cs$_2$AgInCl$_6$ and Cs$_2$AgBiCl$_6$ as well as semi-insulating Cs$_2$AgBiBr$_6$ with low trap density for targeted photovoltaic or visible-light/radiation detection application.
Digital The autism-linked UBE3A T485A mutant E3 ubiquitin ligase The autism-linked UBE3A T485A mutant E3 ubiquitin ligase activates the Wnt/ β -catenin pathway by inhibiting the proteasome activates the Wnt/ -catenin pathway by inhibiting the proteasome

UBE3A is a HECT domain E3 ubiquitin ligase whose dysfunc-tion is linked to autism, Angelman syndrome, and cancer. Recently, we characterized a de novo autism-linked UBE3A mutant (UBE3A T485A ) that disrupts phosphorylation control of UBE3A activity. Through quantitative proteomics and reporter assays, we found that the UBE3A T485A protein ubiquitinates multiple proteasome subunits, reduces proteasome subunit abundance and activity, stabilizes nuclear (cid:2) -catenin, and stimulates canonical Wnt signaling more effectively than wild-type UBE3A. We also found that UBE3A T485A activates Wnt signaling to a greater extent in cells with low levels of ongoing Wnt signaling, suggesting that cells with low basal Wnt activity are particularly vulnerable to UBE3A T485A
Discussion on the paper by Andrieu, Doucet and Holenstein

I offer my thanks to the authors for an inspirational paper. Their approach to constructing extended target distributions is powerful, can be exploited further and applied elsewhere. A key ingredient is the elucidation of the probability model underlying a SMC algorithm and the genealogical tree structures it generates. Two further developments on this theme are described below. Firstly, at the end of one Conditional SMC run in the PG algorithm, the authors suggest sampling K from its full conditional under π , then deterministically tracing back the ancestral lineage of X T , to yield X 1:T := (X B K 1 1 ,X B K 2 2 , . ,X B K T
Hot bubbles of planetary nebulae with hydrogen-deficient winds

Context. The first high-resolution X-ray spectroscopy of a planetary nebula, BD +30° 3639, opened the possibility to study plasma conditions and chemical compositions of X-ray emitting “hot” bubbles of planetary nebulae in much greater detail than before. Aims. We investigate (i) how diagnostic line ratios are influenced by the bubble’s thermal structure and chemical profile, (ii) whether the chemical composition inside the bubble of BD +30° 3639 is consistent with the hydrogen-poor composition of the stellar photosphere and wind, and (iii) whether hydrogen-rich nebular matter has already been added to the bubble of BD +30° 3639 by evaporation. Methods. We applied an analytical, one-dimensional (1D) model for wind-blown bubbles with temperature and density profiles based on self-similar solutions including thermal conduction. We also constructed heat-conduction bubbles with a chemical stratification. The X-ray emission was computed using the well-documented CHIANTI code. These bubble models are used to re-analyse the high-resolution X-ray spectrum from the hot bubble of BD +30° 3639. Results. We found that our 1D heat-conducting bubble models reproduce the observed line ratios much better than plasmas with single electron temperatures. In particular, all the temperature- and abundance-sensitive line ratios are consistent with BD +30° 3639 X-ray observations for (i) an intervening column density of neutral hydrogen, NH = 0.20-0.10+0.05 × 1022cm−2, (ii) a characteristic bubble X-ray temperature of TX = 1.8 ± 0.1 MK together with (iii) a very high neon mass fraction of about 0.05, virtually as high as that of oxygen. For lower values of NH, we cannot exclude the possibility that the hot bubble of BD +30° 3639 contains a small amount of “evaporated” (or mixed) hydrogen-rich nebular matter. Given the possible range of NH, the fraction of evaporated hydrogen-rich matter cannot exceed 3% of the bubble mass. Conclusions. The diffuse X-ray emission from BD +30° 3639 can be well explained by models of wind-blown bubbles with thermal conduction and a chemical composition equal to that of the hydrogen-poor and carbon-, oxygen-, and neon-rich stellar surface.
A Bird's Eye View of the 4th Industrial Revolution Technologies

Big data and artificial intelligence (AI) are at the core of the rapid digitalization of all aspects in our lives, which is referred to as the Digital Transformation, 4th Industrial Revolution, or Industry 4.0. In particular, the term “4th Industrial Revolution (4IR)” proposed by Klaus Schwab, the founder of the World Economic Forum, is widely used in the scientific literature. As significant parts of our work and personal life are now performed non-face-to-face due to the COVID-19 crisis, the development of 4IR technologies has been accelerating. At the same time, it is difficult to understand and digest all the new 4IR technologies that are pouring out every day. With this motivation, we take a bird’s eye view of exploring these technologies and their relationships (Section 2). We then elaborate on the base and core technologies (Sections 3 and 4) and a key application (Section 5).
The two faces of secondary contact on

: Hybridization is thought to have played an important role in shaping the evolutionary history of diverse island taxa. Here, we propose an ecological and evolutionary framework for understanding the causes and consequences of heterospecific mating on islands – with and without hybridization. There are a number of reasons why secondary contact is expected to be unusually frequent on islands and why heterospecific mating may be a frequent result of such secondary contact. An important contributor is the suite of species and community traits that are enriched by the colonization process itself. The consequences of heterospecific mating may depend, to a large degree, on whether one of the species is introduced. Due to generally weak intrinsic reproductive isolation between island endemics, secondary contact will frequently lead to hybrid establishment and interspecific gene flow. By contrast, due to relatively longer divergence times between endemic and introduced taxa, there will typically be strong postzygotic isolation between them, and recurrent mating within zones of secondary contact will often lead instead to local exclusion by reproductive interference. Since recent human activity is bringing many insular endemics into contact with introduced relatives, this latter outcome may be an underappreciated conservation threat.
Laboratory Indicators for Identifying Hand, Foot, and Mouth Disease Severity: A Systematic Review and Meta-Analysis

Objective: The purpose of this study is to study laboratory indicators for the identification of hand, foot, and mouth disease (HFMD) severity. Methods: We searched PubMed, Embase, and the Web of Science for literature that was published before May 2022. The main results are presented as forest plots. Subgroup analyses, sensitivity analyses, and publication bias were also performed. Results: Our study indicated that white blood cells (WBC) (95%CI: 0.205–0.778), blood glucose (95%CI: 0.505–0.778), lymphocytes (95%CI: 0.072–0.239), creatinine (95%CI: 0.024–0.228), interleukin (IL)-2 (95%CI: 0.192–1.642), IL-6 (95%CI: 0.289–0.776), IL-8 (95%CI: 0.499–0.867), IL-10 (95%CI: 0.226–0.930), interferon-γ (IFN-γ) (95%CI: 0.193–2.584), tumor necrosis factor-α (TNF-α) (95%CI: 1.078–2.715), and creatine kinase MB isoenzyme (CK-MB) (95%CI: 0.571–1.459) were associated with an increased risk of HFMD severity, and the results of the sensitivity analysis of these indicators were stable and free of publication bias. Conclusions: Our results suggest that various deleterious immune and metabolic changes can increase the risk of HFMD severity, which can provide a basis for predicting the prognosis and useful evidence for clinicians to manage patients efficiently.