Miracle-dz/UniFAR-FTUs huggingface dataset:
Reliable Architecture-Oblivious Error Detection Schemes for Secure Cryptographic GCM Structures

To augment the confidentiality property provided by block ciphers with authentication, the Galois Counter Mode (GCM) has been standardized by the National Institute of Standards and Technology. The GCM is used as an add-on to 128-bit block ciphers, such as the Advanced Encryption Standard (AES), SMS4, or Camellia, to verify the integrity of data. Prior works on the error detection of the GCM either use linear codes to protect the GCM architectures or are based on AES–GCM architectures, confining the mechanisms to the AES block cipher. Although such structures are efficient, they are not only confined to specific architectures of the GCM but might also not fully take advantage of the parallel architectures of the GCM. Moreover, linear codes have been shown to be potentially ineffective with respect to biased faults. In this paper, we propose algorithm-oblivious constructions through recomputing with swapped ciphertext and additional authenticated blocks, which can be applied to the GCM architectures using different finite field multipliers in $GF(2^{128})$. Such obliviousness for the proposed constructions used in the GCM gives freedom to the designers. We present the results of error simulations and application-specific integrated circuit implementations to demonstrate the utility of the presented schemes. Based on the overhead/degradation tolerance for implementation/performance metrics, one can fine-tune the proposed method to achieve more reliable architectures for the GCM.
Two Types of Physical Inconsistency to Avoid with Univariate Quantile Mapping: A Case Study over North America Concerning Relative Humidity and Its Parent Variables

AbstractUnivariate quantile mapping (QM), a technique often used to statistically postprocess climate simulations, may generate physical inconsistency. This issue is investigated here by classifying physical inconsistency into two types. Type I refers to the attribution of an impossible value to a single variable, and type II refers to the breaking of a fixed intervariable relationship. Here QM is applied to relative humidity (RH) and its parent variables, namely, temperature, pressure, and specific humidity. Twelve sites representing various climate types across North America are investigated. Time series from an ensemble of ten 3-hourly simulations are postprocessed, with the CFSR reanalysis used as the reference product. For type I, results indicate that direct postprocessing of RH generates supersaturation values (>100%) at relatively small frequencies of occurrence. Generated supersaturation amplitudes exceed observed values in fog and clouds. Supersaturation values are generally more frequent and hi.
Low-dose lipopolysaccharide inducing continuous and obvious increase in urinary protein in hyperglycemic rats and the underlying mechanism

Proteinuria is an important hallmark of diabetic nephropathy models, however it takes a long time for the proteinuria and is not stable. Therefore, low-dose lipopolysaccharide (LPS) was investigated in this work to induce rapid and stable proteinuria in hyperglycemic rats and the underlying mechanism was studied. Hyperglycemia rats was induced by high-fat feeding combined with intraperitoneal injection of streptozotocin (STZ). After 21 days, the model rats received a subinjury dose of 0.8 mg / kg LPS intraperitoneally (i.p.). We detected related biochemical indexes at different time periods after LPS injection and examined the expression of glomerular podocyte-associated proteins. Simultaneously, we measured expression of inflammatory factors, apoptotic proteins and albumin (ALB) in the renal cortex and renal medulla, respectively. PAS (Periodic Acid Schiff) staining was used to observe renal pathology. After LPS injection, urinary microalbumin (umALB) increased significantly and lasted longer. The expression of Nephrin, Podocin and necroptosis factor kappa B (NF-κB) in rennal cortex and Interleukin 18 (IL-18), Caspase-1, NF-κB and ALB in the renal medulla was significantly changed. Pathologically, the glomerular basement membrane was observed to be significantly thickened, the renal tubules were dilated, and the epithelial cells fell off in a circle. LPS promoted the continuous increase in urinary microalbumin in hyperglycemic rats, which was related to the damage to the glomerular basement membrane and renal tubular epithelial cells and to the inflammatory reaction in the kidney involved in NF-κB signaling, and this pathological damage can help to establish a stable model of diabetic nephropathy with increased proteinuria.
Optically read displacement detection using phase-modulated diffraction gratings with reduced zeroth-order reflections

Displacement detection using optical interferometric techniques allows for low minimum detectable displacements which are unmatched by other displacement measurement methods as device sizes are scaled down. The use of diffractive optical elements as beam splitters has proven an effective way to realize miniature and robust optical interferometers. Diffraction gratings commonly used in such applications, however, can generate a zeroth-order reflected beam, which results in reduced sensor performance, packaging limitations, and laser instability. A diffraction grating concept has been designed, fabricated, and tested, which has the effect of reducing the zeroth-order component by imparting a half-wavelength phase shift to a portion of the reflected light. The design criteria for zeroth-order beam elimination are illustrated using a simple model based on phasor arithmetic. The microfabrication process used to prototype gratings is presented, and experimental measurements collected from the prototype are repo.
A smoothed EM approach to indirect estimation problems, with particular reference to stereology and emission tomography

There are many practical problems where the observed data are not drawn directly from the density g of real interest, but rather from another distribution derived from g by the application of an integral operator. The estimation of g then entails both statistical and numerical difficulties. A natural statistical approach is by maximum likelihood, conveniently implemented using the EM algorithm, but this provides unsatisfactory reconstructions of g. In this paper, we modify the maximum likelihood-EM approach by introducing a simple smoothing step at each EM iteration. In our experience, this algorithm converges in relatively few iterations to good estimates of g that do not depend on the choice of starting configuration. Some theoretical background is given that relates this smoothed EM algorithm to a maximum penalized likelihood approach. Two applications are considered in detail. The first is the classical stereology problem of determining particle size distributions from data collected on a plane section through a composite medium. The second concerns the recovery of the structure of a section of the human body from external observations obtained by positron emission tomography; for this problem, we also suggest several technical improvements on existing methodology.
Picosecond Fresnel transmission electron microscopy

We report the demonstration of picosecond Fresnel imaging with an ultrafast transmission electron microscope (UEM). By operating with a low instrument repetition rate (5 kHz) and without objective-lens excitation, the picosecond demagnetization of an FePt film, via in situ, femtosecond laser excitation, is directly imaged. The dynamics are quantified and monitored as a time-dependent change in the degree of electron coherence within the magnetic domain walls. The relative coherence of conventional (thermionic) Fresnel transmission electron microscopy is also directly compared to that of Fresnel UEM through the domain-wall size. Further, the robustness and reversibility of the domain-wall dynamics are illustrated by repeating the picosecond image scans at defocus values having the same magnitude but different signs (e.g., +25 mm vs. −25 mm). Control experiments and approaches to identifying and isolating systematic errors and sources of artifacts are also described. This work, and continued future developm.
Étude asymptotique de certaines partitions dans certains semi-groupes

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Putting pronoun resolution in context : the role of syntax, semantics, and pragmatics in pronoun interpretation

Cette these etudie les mecanismes qui influencent la resolution de pronoms dans des contextes ambigus. Nous proposons une analyse detaillee de la structure discursive ou la dependance pronominale a ete etablie, qui explique pourquoi le role des facteurs jouant un role dans ce processus varie en fonction du contexte. Nous soutenons que l'unite discursive (UD) est le domaine optimal pour l'etude de la resolution de pronoms. Nous proposons une definition 'relationnelle' de l'UD selon laquelle la configuration des UD de la phrase depend du contenu syntactique, semantique et pragmatique de la proposition subordonnee et de la relation entre celle-ci et la proposition principale. Nous etudions deux types de subordonnees adverbiales : les non-relationnelles (temporelles), qui, selon nous, constituent une seule UD avec la proposition principale, et les relationnelles (causales), qui constituent une ud independante de la proposition principale. Nous soutenons que la configuration des UD de la phrase influence l'interpretation de pronoms et que les facteurs jouant un role dans ce processus ont un poids different selon qu'ils se trouvent dans une UD ou au travers de deux UD. Nous defendons la these selon laquelle la resolution de pronoms est fortement basee sur le principe de coherence discursive : la resolution des pronoms est guidee soit par le maintien (intra-UD), soit par l'etablissement de la coherence (inter-UD). Nous testons ces hypotheses avec une serie d'experiences etudiant le role de la fonction grammaticale de l'antecedent, de son statut informationnel et des relations de coherence entre deux propositions dans le contexte d'une ou deux UD, en anglais, espagnol et francais.
TOX2 coordinates with TET2 to positively regulate central memory differentiation in human CAR T cells

Chimeric antigen receptor (CAR) T cell therapy is used in treating human hematological malignancies, but its efficacy is limited by T cell exhaustion (TEX). TEX arises at the expense of central memory T cells (TCM), which exhibit robust antitumor efficacy. Reduction of the TET2 gene led to increased TCM differentiation in a patient with leukemia who experienced a complete remission. We show that loss of TET2 led to increased chromatin accessibility at exhaustion regulators TOX and TOX2, plus increased expression of TOX2. Knockdown of TOX increased the percentage of TCM. However, unexpectedly, knockdown of TOX2 decreased TCM percentage and reduced proliferation. Consistently, a TCM gene signature was reduced in the TOX2 knockdown, and TOX2 bound to promoters of numerous TCM genes. Our results thus suggest a role for human TOX2, in contrast to exhaustion regulator TOX, as a potentiator of central memory differentiation of CAR T cells, with plausible utility in CAR T cell cancer therapy via modulated TOX2 expression.
The Fate of Cervical Dysplastic Lesions during Pregnancy and the Impact of the Delivery Mode: A Review

Cervical dysplasia, also referred to as cervical intraepithelial neoplasia (CIN) or squamous intraepithelial lesion (SIL), is the precursor lesion of cervical carcinoma. Therefore, its diagnosis is vital for early detection and inhibiting the development of cervical carcinogenesis. Human papillomavirus (HPV) is the most common aetiology of cervical cancer and this infection mainly affects young women of childbearing age, thus affecting pregnant women as well. It is essential to know how CIN progresses in pregnant patients because the management of pregnant and non-pregnant patients is different (considering the safety of both mother and child in pregnancy). This review intends to highlight the studies which have assessed the rates of progression of CIN diagnosed in pregnancy throughout the antenatal period and the impact of the mode of delivery on CIN outcomes. We searched PubMed/MEDLINE and Google Scholar databases for relevant articles. Many studies indicate that the rate of progression of these lesions is very slow during the tenure of pregnancy; many also report postpartum regression of these lesions. Thus, in most of these patients, management can be safely implemented in the postpartum period while just keeping them under observation in the antenatal period. However, patients with high-grade CIN have a higher chance of developing invasive cancer and, therefore, require careful monitoring. There is a dispute regarding the role of the mode of delivery in determining the fate of cervical dysplasia. While some studies supported vaginal births over caesarean sections, others did not find any difference between the two in defining the outcome of the dysplastic lesions.
The precursory phase of large earthquakes

The existence of an observable precursory phase of slip on the fault before large earthquakes has been debated for decades. Although observations preceding several large earthquakes have been proposed as possible indicators of precursory slip, these observations do not directly precede earthquakes, are not seen before most events, and are also commonly observed without being followed by earthquakes. We conducted a global search for short-term precursory slip in GPS data. We summed the displacements measured by 3026 high-rate GPS time series—projected onto the directions expected from precursory slip at the hypocenter—during 48 hours before 90 (moment magnitude ≥7) earthquakes. Our approach reveals a ≈2-hour-long exponential acceleration of slip before the ruptures, suggesting that large earthquakes start with a precursory phase of slip, which improvements in measurement precision and density could more effectively detect and possibly monitor. Description Editor’s summary Unlike some volcanic eruptions, no clear set of precursor signals have been identified for large earthquakes. Bletery and Nocquet analyzed high-rate GPS time series before 90 different earthquakes that were magnitude 7 and above to find a precursor signal (see the Perspective by Bürgmann). They observed a subtle signal that rose from the noise about 2 hours before these major earthquakes occurred. This work may allow fault monitoring for this precursor phase with denser and higher-precision instrumentation. —Brent Grocholski High-time-rate GPS time series have a precursor signal for large earthquake rupture starting approximately 2 hours beforehand.
Fluorochemicals from fluorspar via a phosphate-enabled mechanochemical process that bypasses HF

All fluorochemicals—including elemental fluorine and nucleophilic, electrophilic, and radical fluorinating reagents—are prepared from hydrogen fluoride (HF). This highly toxic and corrosive gas is produced by the reaction of acid-grade fluorspar (>97% CaF2) with sulfuric acid under harsh conditions. The use of fluorspar to produce fluorochemicals via a process that bypasses HF is highly desirable but remains an unsolved problem because of the prohibitive insolubility of CaF2. Inspired by calcium phosphate biomineralization, we herein disclose a protocol of treating acid-grade fluorspar with dipotassium hydrogen phosphate (K2HPO4) under mechanochemical conditions. The process affords a solid composed of crystalline K3(HPO4)F and K2−xCay(PO3F)a(PO4)b, which is found suitable for forging sulfur-fluorine and carbon-fluorine bonds. Description Editor’s summary Fluorine occurs naturally as a calcium salt in the highly insoluble mineral fluorspar. For well over 200 years, the first step in accessing fluorinating reagents has been the conversion of fluorspar to perilously toxic and corrosive hydrofluoric acid (HF). Patel et al. now report a safer alternative means of activating fluorspar for downstream fluorination chemistry. Specifically, they enhanced its solubility by grinding it in a ball mill with dipotassium hydrogen phosphate salt. The resultant solid can then be used to form carbon–fluorine and sulfur–fluorine bonds with electrophilic reactants in an alcohol solvent. —Jake S. Yeston A versatile inorganic fluorinating reagent is prepared by mechanochemical activation of fluorspar with a phosphate salt.
Infinitesimal holonomy group structure and geometrization

The role of the infinitesimal holonomy group (IHG) and associated curvature structure equations are considered in connection with programs involving geometrization. We argue that the IHG formalism pro-vides a natural setting for discussions of the geometrization program and gauge formulations of gravity. In particular, we show that by considering the IHG structure of Riemannian curvature the Bianchi identities can be cast into the form of basic gauge field equations for the Riemannian curvature gauge fields. We point out that the underlying fibre bundle structure associated with the IHG formalism is that of the holonomy bundles which are reduced subbundles of the bundle of orthonormal frames. The IHG formalism is illustrated for Einstein vacuum and Einstein-Maxwell space-times, and Einstein-Yang-Mills space-times are briefly discussed.
EXAMINATION OF DIMENSIONALITY AND LATENT TRAIT SCORES ON MIXED-FORMAT TESTS

The aim of the present study is to examine various item types utilized to measure success in mathematics in terms of dimensionality and latent trait scores. The data collection instruments utilized in the present study were the student questionnaires and the mathematics achievement tests developed to measure 4th and 8th grade students’ mathematics success in TIMSS 2015. It is assumed in the current study that two different dimensions are formed: the combination of MC and CR items, forming the “math ability” and the CR items, forming the “CR ability”. To determine the dimensionality of latent trait of math ability, three different IRT models – unidimensional, within-item and between-items – were used. It was found that the within-item model displayed a better fit, when compared to the unidimensional model. Moreover, the within-item dimensional model showed better fit according to AIC and BIC as well. In the unidimensional and within-item models, the talent parameter predictions were similar. While the effect of the variables of sense of school belonging and students’ confidence in mathematics on the primary trait were significant, the home resources for learning variable also had a significant impact within 8th grade.
Enabling enterprise autonomy development with a unified data infrastructure

Data is the cornerstone of Artificial Intelligence (AI) and Machine Learning (ML) systems. As the Department of Defense (DoD) leverages AI/ML to develop, test, and deploy autonomous vehicle capabilities, management of autonomy data will become increasingly important. Modern sensors on autonomous vehicles generate an enormous amount of data, and making this data available for further research presents a significant challenge. Moving such large volumes of data from a field environment to a centralized, cloud-based data lake is not straightforward, nor necessarily efficient for data of unknown enterprise utility. As a result, much of DoD’s autonomy data remains siloed in geographically or logically separated on-premises and cloud-based data stores in mixed formats. Organizations within DoD’s modernization enterprise require a mature data infrastructure to store, discover, share, and collaborate upon datasets, models, and other artifacts efficiently. In this paper, we examine the characteristics a data infrastructure must exhibit to meet the needs of the DoD for autonomy research. These characteristics are identified through a review of existing solutions, use cases, and current industry best practices. On the basis of this review, we propose a set of requirements for DoD’s data infrastructure for autonomous systems research. Moreover, an analysis of the viability of various options, including centralized and decentralized architectures, is provided through the lens of DoD data requirements and unique organizational constraints. While data infrastructure for autonomy is our primary concern, the requirements and design we propose generalize to other AI tasks that are of interest to DoD.
Unsupervised training dataset curation for deep-neural-net RF signal classification

We consider the problem of unsupervised (blind) evaluation and assessment of the quality of data used for deep neural network (DNN) RF signal classification. When neural networks train on noisy or mislabeled data, they often (over-) fit to the noise measurements and faulty labels, which leads to significant performance degradation. Also, DNNs are vulnerable to adversarial attacks, which can considerably reduce their classification performance, with extremely small perturbations of their input. In this paper, we consider a new method based on L1-norm principal-component analysis (PCA) to improve the quality of labeled wireless datasets that are used for training a convolutional neural network (CNN), and a deep residual network (ResNet) for RF signal classification. Experiments with data generated for eleven classes of digital and analog modulated signals show that L1-norm tensor conformity curation of the data identifies and removes from the training dataset inappropriate class instances that appear due to mislabeling and universal black-box adversarial attacks and drastically improves/restores the classification accuracy of the identified deep neural network architectures.
Did the Dependent Coverage Mandate Reduce Crime?

The Affordable Care Act’s dependent coverage mandate (DCM) induced approximately 2 million young adults to join parental employer-sponsored health insurance plans. This study is the first to explore the impact of the DCM on crime, a potentially important externality. Using data from the National Incident-Based Reporting System, we find that the DCM induced a 2–5 percent reduction in property crime incidents involving young adult arrestees ages 22–25 relative to those ages 27–29. This finding is supported by supplemental analysis using data from the Uniform Crime Reports. An examination of the underlying mechanisms suggests that declines in large out-of-pocket expenditures for health care, increased educational attainment, and increases in cohabitation of parents and adult children may explain these declines in crime. Back-of-the-envelope calculations suggest that the DCM generated approximately $371–$512 million in annual social benefits from crime reduction among young adults.
Crisis, Ethics, Reliability & a measurement.network: Reflections on Active Network Measurements in Academia

Network measurements are a necessary component of assessing real-world protocol use to inform the development of new and improvement of old protocols and standards. However, especially active measurements, i.e., measurements in which probes are sent to remote devices to illicit a response, face ethical challenges, are difficult to execute reliably, and may cause unintended harm. In this paper, we reflect on the connection between the Internet's growing complexity, the practicalities of academic research, and the likelyhood of reliability issues and unintended harm occurring in active measurements. We argue that communal infrastructure providing measurement services to the academic community could be a path forward to improve reliability and accessibility, while reducing the potential for unintended harm, and enabling PhD students to more easily draw from the experience of industry professionals.