Miracle-dz/UniFAR-FTUs huggingface dataset:
SIGGRAPH: G: Enabling Reflective & Refractive Depth Representation in Computer-Generated Holography

1 PROBLEM & MOTIVATION Computer-Generated Holography (CGH) is a technique for the reconstruction and display of three-dimensional imagery through diffraction and interference of light. Holograms are generated digitally by calculating light propagation, and displayed on devices called Spatial Light Modulators (SLMs). When illuminated by coherent laser light, holograms then replay a full 3D scene. Recently, holography has received significant attention from industrial and academic communities, with neural holography [Peng et al. 2020] [Shi et al. 2021] and numerous other techniques [Sahin et al. 2020]. Applications of holography include Augmented/Virtual Reality [Widjanarko et al. 2020], Head-Up Displays, and larger display devices [An et al. 2020]. CGH offers “the most complete and visually satisfying 2D record of a 3D scene we know how to make”[Benton and Bove 2008], and is of particular interest as it allows a realisation of the progress towards realism in computer graphics to be translated into realistic 3D viewing. In the real world, objects can be viewed in reflections (such as in mirrors) and through refractions (such as through glass or water); the depth at which these objects come into focus is defined by the focal power of the material in question. When rendering convincing imagery in computer graphics, realistic representation of these materials is essential to the realism of the final image. These material representations do not pose an issue for rendering for 2D display, as only the pixel intensities are required and focus is predetermined by a depth of field routine in the renderer, or by post processing. Doing this post processing requires the same depth data of the scene as in image/layer-based CGH, where z-depth values are used that correspond to the focus distance of objects. While this technique works well for the first object hit by the raytracer, it is unable to accurately encode the depth at which virtual objects appear after reflection or refraction. It is hence necessary, in order to create perceptually correct scenes, for the renderer to pass multiple depth values into the pipeline to allow the hologram generation engine to ensure realistic representation of these reflections and refractions.
Decision Trees for Tactic Prediction in Coq ∗

We present ongoing work of comparing several different decision tree learning methods on predicting tactics for proof states in Coq [5] by grasping knowledge from preceding humanwritten proofs. The work is based on Tactician[1], a plugin enabling proof automation for Coq. The authors use Tactician to extract features from the abstract syntax trees of proof states in the form of term walks of length one and two. We apply Tactician to record all the proof states (253, 538) and respective tactics in the Coq standard library and randomly choose 1% (2, 530) as the evaluation data. Three algorithms are implemented: random forests and gradient boosted trees working on binary learning with negative examples and multilabel regression. Finally, we compare the results of the decision tree models and the Tactician’s original method, k-nearest neighbors (k-NN).
Evaluation of Antioxidant and Antibacterial Activities of the Polysaccharides from Mycelium and the Culture Medium of Pleurotus Eryngii Strain UN-1

: Pleurotus eryngii was one of the most precious and ordinary edible mushrooms, and its polysaccharides were the major active substances. In this study, P. eryngii strain UN-1 was cultured in a liquid medium at 25℃ under a shaking of 80 rpm for 7 days. Two crude polysaccharides named CPN and CPNM were obtained from the mycelium of P. eryngii UN-1 and its broth culture medium, respectively. After partial purification by cellulose DEAE-52 column chromatography and Sephadex G-100 gel-filtration, two fractions (PNP-1 and PNP-2) from CPN and one (PNMP-1) from CPNM were eluted and subjected to physicochemical properties, antioxidant, and antibacterial activities, in addition, the crude polysaccharides. The in vitro antioxidant assay revealed that all samples showed moderate scavenging capacities on DPPH radical (6.31-80.92%), ABTS radical (9.33-67.26%), and hydroxyl radical (11.21-79.53%) at different concentrations (0-2000 μg/mL), and PNP-2 exhibited the highest scavenging activity for all tested free radicals. Moreover, the antibacterial activity of the most active fraction (PNP-2) showed a significant effect against Escherichia coli, Bacillus Subtillis, Salmonella enterica, and Staphylococcus aureus subsp. Aureus strains with Minimum Inhibitory Concentration (MIC) values (2.5, 5, 2.5 and 5 mg/mL, respectively). Notably, the UV-vis Spectrophotometer confirmed that multiple active known compounds such as uremic acid were detected in all tested fractions, which confirmed the antioxidant and antimicrobial activities obtained in this study. Conclusively, the polysaccharides obtained from P. eryngii UN-1 have the potential to act as a functional food ingredient or a preventive drug against human pathogenic bacteria.
Multiview Concept Bottleneck Models Applied to Diagnosing Pediatric Appendicitis

Arguably, interpretability is one of the guiding principles behind the development of machine-learning-based healthcare decision support tools and computer-aided diagnosis systems. There has been a renewed interest in interpretable classification based on high-level concepts, including, among other model classes, the re-exploration of concept bottleneck models. By their nature, medical diagnosis, patient management, and monitoring require the assessment of multiple views and modalities to form a holistic representation of the patient’s state. For instance, in ultrasound imaging, a region of interest might be registered from multiple views that are informative about different sets of clinically relevant features. Motivated by this, we extend the classical concept bottleneck model to the multiview classification setting by representation fusion across the views. We apply our multiview concept bottleneck model to the dataset of ultrasound images acquired from a cohort of pediatric patients with suspected appendicitis to predict the disease. The results suggest that auxiliary supervision from the concepts and aggregation across multiple views help develop more accurate and interpretable classifiers.
Automatic Classification of Audio Uroflowmetry with a Smartwatch

Prior work has shown the classification of voiding dysfunctions from uroflowmeter data using machine learning. We present the use of smartwatch audio, collected through the UroSound platform, in order to automatically classify voiding signals as normal or abnormal, using classical machine learning techniques. We train several classification models using classical machine learning and report a maximal test accuracy of 86.16% using an ensemble method classifier. Clinical relevance- This classification task has the potential to be part of an essential toolkit for urology telemedicine. It is especially useful in areas that lack proper medical infrastructure but still host ubiquitous audio capture devices such as smartphones and smartwatches.
TrustedGateway: TEE-Assisted Routing and Firewall Enforcement Using ARM TrustZone

Gateway routers are at the heart of every network infrastructure, interconnecting subnetworks and enforcing access control policies using firewalls. However, their central position makes them high-value targets for network compromises. Typically, gateways are erroneously assumed to be hardened against software vulnerabilities (“bastion host”). In fact, though, they inherit the attack surface of their underlying commodity OSes which together with the wealth of auxiliary services available on both consumer and enterprise gateways—web and VoIP, file sharing, remote logins, monitoring, etc.—undermines this belief. This is underlined by a plethora of recent CVEs for commodity OSes and services of popular routers which resulted in authentication bypass or remote code execution thus enabling attackers full control over their security policies. We present TrustedGateway (TruGW), a new gateway architecture, which isolates “core” networking features—routing and firewall—from error-prone auxiliary services and gateway OSes. TruGW leverages a TEE-assisted design to protect the network path and policies while staying compatible with commodity gateway platforms. TruGW uses ARM TrustZone to protect the NIC and traffic processing from a fully-compromised gateway and permits policy updates only by trusted remote administrators. That way, TruGW can readily guarantee the secure enforcement of trusted policies on commodity gateways. TruGW’s small attack surface is a key enabler to regain trust in core network infrastructures.
Toward Carbon-Aware Networking

Data transmission tends to be neglected when considering the carbon efficiency of systems, even though the electricity usage of data networks as a whole is as large, or larger, than that of data centers. Accounting for carbon cost of the movement of data is hard, and is often assumed to be the responsibility of the receiver or an intermediate provider. To be able to account for the carbon footprint of networks, mutually agreed metrics are required, covering the end-to-end environmental cost of data transmission and up-the-stack network software costs of data processing, rather than merely the independent network devices. Beyond discussing the considerations for defining these metrics, this paper suggests building upon existing practices, such as network telemetry, programmable network elements and cost-aware routing to enable carbon-intelligent networking, a concept that goes beyond network energy efficiency and considers the impact of energy decarbonization on the routing and scheduling of data transmission.
Plush: A Write-Optimized Persistent Log-Structured Hash-Table

Persistent memory (PMem) promised DRAM-like performance, byte addressability, and the persistency guarantees of conventional block storage. With the release of Intel Optane DCPMM, those expectations were dampened. While its write latency competes with DRAM, its read latency, write endurance, and especially bandwidth fall behind by up to an order of magnitude. Established PMem index structures mostly focus on lookups and cannot leverage PMem's low write latency. For inserts, DRAM-optimized index structures are still an order of magnitude faster than their PMem counterparts despite the similar write latency. We identify the combination of PMem's low write bandwidth and the existing solutions' high media write amplification as the culprit. We present Plush, a write-optimized, hybrid hash table for PMem with support for variable-length keys and values. It minimizes media write and read amplification while exploiting PMem's unique advantages, namely its low write latency and full bandwidth even for small reads and writes. On a 24-core server with 768 GB of Intel Optane DPCMM, Plush outperforms state-of-the-art PMem-optimized hash tables by up to 2.44X for inserts while only using a tiny amount of DRAM. It achieves this speedup by reducing write amplification by 80%. For lookups, its throughput is similar to that of established PMem-optimized tree-like index structures.
Glycolysis and the Pentose Phosphate Pathway Promote LPS-Induced NOX2 Oxidase- and IFN-β-Dependent Inflammation in Macrophages

Macrophages undergo a metabolic switch from oxidative phosphorylation to glycolysis when exposed to gram-negative bacterial lipopolysaccharide (LPS), which modulates antibacterial host defence mechanisms. Here, we show that LPS treatment of macrophages increased the classical oxidative burst response via the NADPH oxidase (NOX) 2 enzyme, which was blocked by 2-deoxyglucose (2-DG) inhibition of glycolysis. The inhibition of the pentose phosphate pathway with 6-aminonicotinamide (6-AN) also suppressed the LPS-induced increase in NOX2 activity and was associated with a significant reduction in the mRNA expression of NOX2 and its organizer protein p47phox. Notably, the LPS-dependent enhancement in NOX2 oxidase activity was independent of both succinate and mitochondrial reactive oxygen species (ROS) production. LPS also increased type I IFN-β expression, which was suppressed by 2-DG and 6-AN and, therefore, is dependent on glycolysis and the pentose phosphate pathway. The type I IFN-β response to LPS was also inhibited by apocynin pre-treatment, suggesting that NOX2-derived ROS promotes the TLR4-induced response to LPS. Moreover, recombinant IFN-β increased NOX2 oxidase-dependent ROS production, as well as NOX2 and p47phox expression. Our findings identify a previously undescribed molecular mechanism where both glycolysis and the pentose phosphate pathway are required to promote LPS-induced inflammation in macrophages.
Routine Immunohistochemical Analysis of Mismatch Repair Proteins in Colorectal Cancer—A Prospective Analysis

Simple Summary Recognition of a hereditary colorectal cancer (CRC) syndrome is crucial. Our aim was to assess the value of routine immunohistochemistry screening for mismatch repair proteins deficiency in CRC patients under 70 years-old. In our cohort, this inclusive strategy allowed the identification of Lynch Syndrome patients that could otherwise be missed using a restrictive approach that relies only on Amsterdam and Bethesda criteria. This study strengthens current recommendations and highlights the role of universal CRC screening for MMR protein status. Abstract Recognition of a hereditary colorectal cancer (CRC) syndrome is crucial and Lynch Syndrome (LS) is the most frequent immunohistochemistry (IHC)—screening for mismatch repair proteins (MMR) deficiency in CRC is therefore advocated. An unicentric cohort study was conducted in a central Oncological Hospital to assess its results. All patients under 70 years-old admitted between July 2017–June 2019 and submitted to surgery for CRC were included. Of 275 patients, 56.0% were male, median age 61.0 (IQR:54.5–65.0), with synchronous tumors in six. Histology revealed high grade adenocarcinoma in 8.4%; mucinous and/or signet ring differentiation in 11.3%; and lymphocytic infiltration in 29.8%. Amsterdam (AC) and Bethesda (BC) Criteria were fulfilled in 11 and 74 patients, respectively. IHC revealed loss of expression of MMR proteins in 24 (8.7%), mostly MLH1 and PMS2 (n = 15) and PMS2 (n = 4). Among these, no patients fulfilled AC and 13 fulfilled BC. BRAF mutation or MLH1 promoter hypermethylation was found in four patients with MLH1 loss of expression. Genetic diagnosis was performed in 51 patients, 11 of them with altered IHC. LS was diagnosed in four, and BC was present in three. One patient would not have been diagnosed without routine IHC screening. These results strengthen the important role of IHC screening for MMR proteins loss of expression in CRC.
Introduction to Fourier Analysis on Euclidean Spaces.

The authors present a unified treatment of basic topics that arise in Fourier analysis. Their intention is to illustrate the role played by the structure of Euclidean spaces, particularly the action of translations, dilatations, and rotations, and to motivate the study of harmonic analysis on more general spaces having an analogous structure, e.g., symmetric spaces.
PRELIMINARY RESULTS REGARDING THE TOTAL SUGAR CONTENT OF BLUEBERRY GENITORS AND HYBRID PROGENIES

Blueberry belongs to the Vaccinium Genus, Ericaceae Family, Ericales Order. The highbush blueberry (Vaccinium corymbosum L.) is classified as a commercially-grown berry. Blueberries are appreciated for their taste, nutritional value, and both pharmacological properties and biologically active functions. This study objective was to determine the total sugar content in frozen fruits of the highbush blueberry genotypes used as genitors ('Simultan', 'Delicia', 'Duke', 'Azur', 'Northblue', '4/6', '6/38') and 88 hybrid progenies 'Simultan x Duke', 'Simultan x Northblue', 'Azur x 6/38', 'Azur x 4/6', 'Delicia x Duke', 'Delicia x Northblue'. The total sugar content of frozen fruits was analyzed by the phenol-sulfuric acid method. The results showed that the total sugar content of the genitors varied between 2.83 and 3.81 g glucose/100 g. The fruits of 'Simultan' cv. had the highest total sugar content (3.81 g glucose/100 g). The highest total sugar content, 5.486 g glucose/100 g, was found in a 'Simultan × Duke' hybrids.
Do bankrupt firms recognize publicly available bad news in a timely fashion?

PurposeThe purpose of this paper is to examine whether managers of bankrupt firms are more or less conditionally conservative in their financial reporting relative to non-bankrupt firms. The study further examines the cross-sectional differences in conditional conservatism among bankrupt and non-bankrupt firms.Design/methodology/approachThe study employs a sample of US firms to investigate conditional conservatism in firms that experience financial distress and go bankrupt relative to non-stressed non-bankrupt firms. The study also uses switching regression models to identify the drivers of the cross-sectional difference in conditional conservatism among bankrupt and non-bankrupt firms.FindingsEmpirical results show that bankrupt firms are timelier in recognizing bad news than good news when compared to non-bankrupt firms. The higher level of conditional conservatism in bankrupt firms is mainly driven by their higher levels of leverage and tax-reduction incentives. The cross-sectional analyses show that these results largely hold for more leveraged firms and firms with higher tax costs. Taken together, these results suggest that the conservative tendency of managers of bankrupt firms can stem from the agency problem between lenders and managers and from tax-decreasing motivations.Originality/valueThe novelty of the authors’ research stands in studying the drivers of the cross-sectional differences in conditional conservatism between bankrupt and non-bankrupt firms and specifically, the demonstration that taxation also induces conditional conservatism in the setting of ex post bankrupt firms.
Research on Application of Naive Bayes Algorithm Based on Attribute Correlation to Unmanned Driving Ethical Dilemma

At present, unmanned driving technology has made great progress, while those research on its related ethical issues, laws, and traffic regulations are relatively lagging. In particular, it is still a problem how unmanned vehicles make a decision when they encounter ethical dilemmas where traffic collision is inevitable. So it must hinder the application and development of unmanned driving technology. Firstly, 1048575 survey data collected by Moral Machine online experiment platform is analyzed to calculate the prior probability that the straight being protector or sacrificer in ethical dilemmas with single feature. Then, 116 multifeature ethical dilemmas are designed and surveyed. The collected survey data are analyzed to determine decision-making for these ethical dilemmas by adopting the majority principle and to calculate correlation coefficient between attributes, then an improved Naive Bayes algorithm based on attribute correlation (ACNB) is established to solve the problem of unmanned driving decision in multifeature ethical dilemmas. Furthermore, these ethical dilemmas are used to test and verify traditional NB, ADOE, WADOE, CFWNB, and ACNB, respectively. According to the posterior probability that the straight being protector or sacrificer in those ethical dilemmas, classification and decision are made in these ethical dilemmas. Then, the decisions based on these algorithms are compared with human decisions to judge whether these decisions are right. The test results show that ACNB and CFWNB are more consistent with human decisions than other algorithms, and ACNB is more conductive to improve unmanned vehicle’s decision robustness than NB. Therefore, applying ACNB to unmanned vehicles has a good role, which will provide a new research point for unmanned driving ethical decision and a few references for formulating and updating traffic laws and regulations related to unmanned driving technology for traffic regulation authorities.
Probability of Belonging to a Language

Probability of Belonging to a Language Kevin M. B. Cook Department of Computer Science, BYU Master of Science Conventional language models estimate the probability that a word sequence within a chosen language will occur. By contrast, the purpose of our work is to estimate the probability that the word sequence belongs to the chosen language. The language of interest in our research is comprehensible well-formed English. We explain how conventional language models assume what we refer to as a degree of generalization, the extent to which a model generalizes from a given sequence. We explain why such an assumption may hinder estimation of the probability that a sequence belongs. We show that the probability that a word sequence belongs to a chosen language (represented by a given sequence) can be estimated by avoiding an assumed degree of generalization, and we introduce two methods for doing so: Minimal Number of Segments (MINS) and Segment Selection. We demonstrate that in some cases both MINS and Segment Selection perform better at distinguishing sequences that belong from those that do not than any other method we tested, including Good-Turing, interpolated modified Kneser-Ney, and the Sequence Memoizer.
The Role of Inflammasomes in Mediating Urological Disease: A Short Literature Review

Abstract Inflammasome dysfunction may be responsible for underlying inflammatory diseases, which include renal and urological pathologies. Five inflammasomes have been described, including nucleotide-binding domain leucine-rich repeat (NLR), NL pyrin domain containing receptor 1(NLPR1), NLRP3, NLR and caspase recruitment domain containing receptor 4 (NLRC4), and the AIM2-like receptor. The purpose of this study was to review literature sources regarding how innate immunity and inflammasomes contribute to urologic disease and infection. A literature search of PubMed/MEDLINE, EMBASE and Google Scholar articles. Articles were selected for review if their content included (1) inflammasomes and (2) urology in the adult population. The initiation of specific cytokine cascades, which include IL-1β and IL-18, appear responsible for a repertoire of urologic pathologies. Inflammation mediates a wide range of uropathies (urologic disorders and infections) which are found in the bladder, prostate, or kidney and inflammasomes appear to be particularly responsible for urological and renal pathologies. Understanding the role of inflammasomes in urologic disorders can help improve treatment and overall quality of life in patients with these disorders.