Coherent Data Research Articles

Where’s the data to support educators’ data use for instructional practice?

ABSTRACT Data use has gained policy traction at the federal, state, and local levels in the United States and internationally, and is now embedded in teacher, principal, and district leader standards in the U.S. However, many decisions implemented in policy and practice are being made on insufficient evidence and assume a relatively straightforward, intuitive, and coherent data use process in which educators have access to data; the data are appropriate for the task at hand; and that they have the skills to retrieve, analyze, and respond appropriately to directly or indirectly change instruction for the better. Yet, research indicates that in actuality the practice of educator data use is complicated and heavily influenced by both organizational and individual factors such as school leaders’ influence on teachers’ data use, and teachers’ beliefs about, capacity for, and use of data for instructional decisions. Because we and many others in the field of education have come to see the potential value and utility of data use by educators, we offer the five recommendations to improve educators’ data use for instructional practice.

Hardware Trojan Threats to Cache Coherence in Modern 2.5D Chiplet Systems

As industry moves toward chiplet-based designs, the insertion of hardware Trojans poses a significant threat to the security of these systems. These systems rely heavily on cache coherence for coherent data communication, making coherence an attractive target. Critically, unlike prior work, which focuses only on malicious packet modifications, a Trojan attack that exploits coherence can modify data in memory that was never touched and is not owned by the chiplet which contains the Trojan. Further, the Trojan need not even be physically between the victim and the memory controller to attack the victim's memory transactions. Here, we explore the fundamental attack vectors possible in chiplet-based systems and provide an example Trojan implementation capable of directly modifying victim data in memory. This work aims to highlight the need for developing mechanisms that can protect and secure the coherence scheme from these forms of attacks.

Coherent Wireless Link at 300 GHz With 160 Gbit/s Enabled by a Photonic Transmitter

The increasing demand for high-capacity wireless communication requires data links at millimeter waves and terahertz frequencies, respectively. At those frequencies, electronic and photonic technologies compete to prove powerful transmitters and receivers. In this work, we demonstrate a wireless link at 300 GHz using a fiber-coupled PIN photodiode as the transmitter. Thus, the whole emitter side is based on components and techniques from standard fiber-optical communication, which inherently enable broadband data channels. We investigated two antenna designs with amplitude modulated and coherent data signals. Despite similar characteristics in terms of output power and carrier bandwidth, the quality of the data signals differed significantly. In addition, we found that the bit-error ratio (BER) scales non-monotonically with the optical input power of the photodiode, which is proportional to the terahertz output power. Depending on the modulation format and the symbol rate, we identified the optimal driving conditions of the photodiode. For amplitude modulation at 5 Gbit/s, we achieved error-free transmission with a BER of 7.5 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−13</sup> . QPSK modulation was error-free up to 64 Gbit/s. The highest line rate of 160 Gbit/s was achieved with 32QAM modulation. This corresponds to 133 Gbit/s net data rate after forward-error correction with 20% overhead. The highest spectral efficiency was achieved with 64QAM at 8 GBaud, i.e., 48 Gbit/s line rate. The presented results highlight the high bandwidth of photonic wireless THz links. Furthermore, the carefully analysis helps to improve the quality of future wireless links in the 300 GHz band.

A Study of the Determinance of the Type of Personality in Albanian Individual Investor Decision-Making

Traditionally, classical finance theories have argued that investors are rational and not influenced by human factors when making financial decisions. Recent developments in the field of finance, such as the anomalies that occurred and occasional financial crises took place, raised skepticism among researchers changing their approach towards traditional theories, as these theories failed to explain or predict unexpected developments in the markets, thus not supporting the unrealistic assumption of rational man (homo economicus). The research work for this new field of finance belongs to the recent decades. More specifically, there are quite a few studies in Albania due to the presence of an underdeveloped financial market. In the multitude of different factors, which influence the financial behavior of the investor, most of the research in the field of financial behavior is dedicated to the study of psychological biases. The topic of this study focuses on the impact of the personality type of individual investors on their decisions to invest in financial assets offered in Albania. The study is composed in the same logic line as that of the purpose and the research question raised. Quantitative strategy is used to answer the research question and draw conclusions. Descriptive and regression analysis was used through R-programme to identify the significance of the type of personality in Albanian individual investor behavior. We use the questionnaire as an instrument to collect data. Big Five Personality Model is chosen as the measurement scale. Only coherent data that remained after the reliability test (Cronbach Alpha), will be further used in regression statistical analysis to examine their impact on investor behavior. The analysis shows that the type of personality affects individual investment decisions in financial assets. More specifically Extraversion, Conscientiousness, and Neuroticism affect the amount of money invested in the asset. 'Openness' and 'Neuroticism' affect the level of certainty investors perceive for the investment made in financial assets.

A Reference Section Through Fast‐Spread Lower Oceanic Crust, Wadi Gideah, Samail Ophiolite (Sultanate of Oman): Whole Rock Geochemistry

AbstractDue to its inaccessibility, no complete and coherent data set exists for the composition of modern fast‐spreading oceanic crust. We sampled outcrops through 6,500 m of fossil oceanic crust in the Oman Ophiolite (Wadi Gideah Transect) that is regarded as best analogue of fast‐spreading crust on land. Here we report a complete set of whole‐rock major and trace element data displaying systematic and contrasting compositional trends in lower and upper gabbros being correlated with stratigraphic depth. A significant discontinuity in crystallization regime is observed at ∼3,525 m above the mantle‐crust boundary: gabbros below ∼3,525 m have in general very low incompatible element mass fractions which develop upwards in a barely noticeable way to more differentiated compositions while Mg# decreases. More pronounced trends indicating progressive fractionation of ascending melts can be observed for incompatible elements and their element ratios as a consequence of in situ crystallization. Locally, more variable compositions within narrow depth intervals testify for advanced differentiation in situ within individual sills. Gabbros above ∼3,525 m become significantly more evolved and show considerable variations in composition. Fractional crystallization and mixing processes in a transient axial melt lens control the composition of isotropic “varitextured” gabbros and sheeted dike basalts where fractionation of high field strength elemental ratios is minor. New average compositions of fast‐spread (paleo) oceanic crust are reported for major and 38 trace elements. Comparison with new data from Wadi Khafifah close to Wadi Gideah suggests robustness of crustal accretion processes in both space and time.

Probing light mediators and (g − 2)μ through detection of coherent elastic neutrino nucleus scattering at COHERENT

We present the constraints on the parameters of several light boson mediator models obtained from the analysis of the current data of the COHERENT CEνNS experiment. We consider a variety of vector boson mediator models: the so-called universal, the B − L and other anomaly-free U(1)′ gauge models with direct couplings of the new vector boson with neutrinos and quarks, and the anomaly-free Le− Lμ, Le− Lτ, and Lμ− Lτ gauge models where the coupling of the new vector boson with the quarks is generated by kinetic mixing with the photon at the one-loop level. We consider also a model with a new light scalar boson mediator that is assumed, for simplicity, to have universal coupling with quarks and leptons. Since the COHERENT CEνNS data are well-fitted with the cross section predicted by the Standard Model, the analysis of the data yields constraints for the mass and coupling of the new boson mediator that depend on the charges of quarks and neutrinos in each model under consideration. We compare these constraints with the limits obtained in other experiments and with the values that can explain the muon g − 2 anomaly in the models where the muon couples to the new boson mediator.

Multiband Silicon Photonic ePIC Coherent Receiver for 64 GBd QPSK

Multiband coherent communication is being handled as a promising candidate to address the increasing demand for higher data rates and capacity. At the same time, coherent communication is expected to enter the data center domain in the near future. With coherent data links in both, data- and telecom, spanning multiple optical bands, novel approaches to coherent transceiver design and traffic engineering will become a necessity. In this work, we present a monolithically integrated silicon photonic coherent receiver for O- and C-band. The receiver features a 2 × 2 multi-mode interference coupler network as 90 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> hybrid optimized for 1430 nm (E-band). The total power consumption is 460 mW at a footprint of approximately 6 mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula> , and an opto-electrical bandwidth of 33 GHz. 64 GBd operation is demonstrated in O- and C-band, which is competitive to the state-of-the-art for silicon photonic coherent receiver in the C-band, and the highest symbol rate to date for O-band coherent communication.

Bounds on new physics with data of the Dresden-II reactor experiment and COHERENT

Coherent elastic neutrino-nucleus scattering was first experimentally established five years ago by the COHERENT experiment using neutrinos from the spallation neutron source at Oak Ridge National Laboratory. The first evidence of observation of coherent elastic neutrino-nucleus scattering with reactor antineutrinos has now been reported by the Dresden-II reactor experiment, using a germanium detector. In this paper, we present constraints on a variety of beyond the Standard Model scenarios using the new Dresden-II data. In particular, we explore the constraints imposed on neutrino non-standard interactions, neutrino magnetic moments, and several models with light scalar or light vector mediators. We also quantify the impact of their combination with COHERENT (CsI and Ar) data. In doing so, we highlight the synergies between spallation neutron source and nuclear reactor experiments regarding beyond the Standard Model searches, as well as the advantages of combining data obtained with different nuclear targets. We also study the possible signal from beyond the Standard Model scenarios due to elastic scattering off electrons (which would pass selection cuts of the COHERENT CsI and the Dresden-II experiments) and find more stringent constraints in certain parts of the parameter space than those obtained considering coherent elastic neutrino-nucleus scattering.

The Role of Public Health Emergency Management in Biodefense: A COVID-19 Case Study.

The emergence of the COVID-19 pandemic has had significant impact on human lives as well as economic and social stability. The United States has a complicated history with biosecurity as policy making, biodefense activities, and government transparency have historically been in contention. The terror attacks of September 11, 2001 uncovered various weaknesses in the national public health infrastructure that have persisted into the current pandemic. This study explores the biodefense and public health preparedness landscape for trends in federal support and capacity building. It also investigates the applicability of public health emergency management principles to the biodefense structure. A mixed method was utilized in this study to investigate the qualitative and quantitative factors of the research inquiry. Braun and Clarke's six phase framework for thematic analysis will assist with defining the important information from a review of the literature. The concurrent triangulation design permits that use of qualitative and quantitative data to more accurately define and analyze the relationship among the variables of interest. The results included the identification of 8 common themes of failure during the COVID-19 response: (1) accountable leadership, (2) statutory authorities and policies, (3) inter-agency coordination, (4) coherent data system for situational awareness, (5) strategic national stockpile and supply chain, (6) testing and surveillance, (7) health care system surge capacity and resilience, and (8) federal funds and the role of public health emergency management in the evolving landscape of biothreats, both intentional and natural. To counter the increasing biothreats, the United States must invest in revamping the biodefense infrastructure to mimic and support public health emergency preparedness initiatives which will increase our resilience to various biothreats.

Prognostic Role of Residual Thrombus Burden Following Thrombectomy: Insights From the TOTAL Trial.

It is unclear whether more effective forms of thrombus removal than current aspiration catheters would lead to improved outcomes. We sought to evaluate the prognostic role of residual thrombus burden (rTB), after manual thrombectomy, in patients undergoing primary percutaneous coronary intervention with routine manual thrombectomy in the TOTAL trial (Thrombectomy Versus PCI Alone). This is a single-arm analysis of patients from the TOTAL trial who underwent routine manual aspiration thrombectomy. The rTB was quantified by an angiographic core laboratory using the Thrombolysis in Myocardial Infarction criteria and validated using existing optical coherent tomography data. Large rTB was defined as grade ≥3. The primary outcome was death from cardiovascular causes, recurrent myocardial infarction, cardiogenic shock, or new or worsening heart failure within 180 days. Of 5033 patients randomized to routine thrombectomy, 2869 patients had quantifiable rTB (1014 [35%] had large rTB). Patients with large rTB were more likely to have hypertension, previous percutaneous coronary intervention, myocardial infarction, or Killip class III on presentation but less likely to have Killip class I. The primary outcome occurred more frequently in patients with large rTB, even after adjustment for known risk predictors (8.6% versus 4.6%; adjusted hazard ratio, 1.83 [95% CI, 1.34-2.48]). These patients also had a higher risk of cardiovascular death (adjusted hazard ratio, 1.83 [95% CI, 1.13-2.95]), cardiogenic shock (adjusted hazard ratio, 2.02 [95% CI, 1.08-3.76]), and heart failure (adjusted hazard ratio, 1.74 [95% CI, 1.02-2.96]) but not myocardial infarction or stroke. Large rTB is a common finding in primary percutaneous coronary intervention and is associated with increased risk of adverse cardiovascular outcomes, including cardiovascular death. Future technologies offering better thrombus removal than current devices may decrease or even eliminate the risk associated with rTB. This, potentially, can turn into a strategic option to be studied in clinical trials. URL: https://www. gov; Unique identifier: NCT01149044.

Exploring SMEFT induced nonstandard interactions: From COHERENT to neutrino oscillations

We investigate the prospects of next-generation neutrino oscillation experiments DUNE, T2HK and JUNO including TAO within Standard Model Effective Field Theory (SMEFT). We also re-interpret COHERENT data in this framework. Considering both charged and neutral current neutrino Non-Standard Interactions (NSIs), we analyse dimension-6 SMEFT operators and derive lower bounds to UV scale $\Lambda$. The most powerful probe is obtained on ${\cal O}_{{ledq}_{1211}}$ with $\Lambda \gtrsim$ 450 TeV due to the electron neutrino sample in T2HK near detector. We find DUNE and JUNO to be complementary to T2HK in exploring different subsets of SMEFT operators at about 25 TeV. We conclude that near detectors play a significant role in each experiment. We also find COHERENT with CsI and LAr targets to be sensitive to new physics up to $\sim$900 GeV.

Bayesian homodyne and heterodyne tomography.

Continuous-variable (CV) photonic states are of increasing interest in quantum information science, bolstered by features such as deterministic resource state generation and error correction via bosonic codes. Data-efficient characterization methods will prove critical in the fine-tuning and maturation of such CV quantum technology. Although Bayesian inference offers appealing properties-including uncertainty quantification and optimality in mean-squared error-Bayesian methods have yet to be demonstrated for the tomography of arbitrary CV states. Here we introduce a complete Bayesian quantum state tomography workflow capable of inferring generic CV states measured by homodyne or heterodyne detection, with no assumption of Gaussianity. As examples, we demonstrate our approach on experimental coherent, thermal, and cat state data, obtaining excellent agreement between our Bayesian estimates and theoretical predictions. Our approach lays the groundwork for Bayesian estimation of highly complex CV quantum states in emerging quantum photonic platforms, such as quantum communications networks and sensors.

Carrier Phase Recovery and Compensation in Analog Signal Processing Based Coherent Receivers

Analog coherent receiver (ACR) is an attractive alternative to ADC+DSP based coherent receiver for reducing the complexity and power consumption in near-future high-capacity coherent data center interconnects (DCIs). Carrier phase recovery and compensation (CPRC), which is one of the major operations in the coherent DCIs, is essential to compensate for the phase and frequency offsets between the lasers and phase noise of lasers. In this work, we present a CPRC architecture for ACR based DCIs. The proposed CPRC approach comprises a dual loop architecture for frequency and phase offset corrections. Detailed design, analysis, effects of non-idealities, and simulation results of the dual loop CPRC are presented. For our analyses, circuit-realizable parameters have been used and the CPRC can be implemented in advanced CMOS/FinFET/SiGe technology nodes. The presented analog CPRC technique, along with lowering the power consumption, reduces the complexity in 200 Gbps/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\lambda$</tex-math></inline-formula> coherent DCIs.

The “Coherent Data Set”: Combining Patient Data and Imaging in a Comprehensive, Synthetic Health Record

The “Coherent Data Set” is a novel synthetic data set that leverages structured data from Synthea™ to create a longitudinal, “coherent” patient-level electronic health record (EHR). Comprised of synthetic patients, the Coherent Data Set is publicly available, reproducible using Synthea™, and free of the privacy risks that arise from using real patient data. The Coherent Data Set provides complex and representative health records that can be leveraged by health IT professionals without the risks associated with de-identified patient data. It includes familial genomes that were created through a simulation of the genetic reproduction process; magnetic resonance imaging (MRI) DICOM files created with a voxel-based computational model; clinical notes in the style of traditional subjective, objective, assessment, and plan notes; and physiological data that leverage existing System Biology Markup Language (SBML) models to capture non-linear changes in patient health metrics. HL7 Fast Healthcare Interoperability Resources (FHIR®) links the data together. The models can generate clinically logical health data, but ensuring clinical validity remains a challenge without comparable data to substantiate results. We believe this data set is the first of its kind and a novel contribution to practical health interoperability efforts.

A robust physics-based method to filter coherent wavepackets from high-speed schlieren images

A complete understanding of jet dynamics is greatly enabled by the accurate separation of acoustically efficient wavepackets from their higher-energy convecting turbulent counterparts. Momentum potential theory (MPT) has proven highly effective in filtering the desired acoustic component irrespective of operating conditions or nozzle complexity. However, MPT is a data-intensive method predicated on the knowledge of fluctuation quantities in the entire flow field; as such, it has to date been applied only to numerically obtained data. This work develops an approach to extend its application to extract coherent wavepacket data from high-speed schlieren images. Pixel intensities from the schlieren image are mapped to a scaled surrogate for the line-of-sight integrated density gradient. The linear relation between the irrotational scalar MPT potential and time derivatives of density fluctuations is then exploited to perform the filtering. The effectiveness of the procedure is demonstrated using experimental as well as numerical schlieren images representing a wide range of imperfectly expanded free and impinging jet configurations. When combined with spectral proper orthogonal decomposition (SPOD), the method yields modes that accurately capture (i) the Mach wave radiation from a military-style jet, (ii) the mode shapes of the feedback tones in an impinging jet and (iii) the screech signature in twin rectangular jets, without recourse to user adjusted parameters. This technique can greatly enhance the use of high-speed diagnostics for real-time monitoring of the near-field acoustic content for potential feedback control. Additionally, the general nature of the approach allows a straightforward application to other flows, such as cavity and airfoil flow-acoustic interactions.

Bringing in the technological, ethical, educational and social-structural for a new education data governance

ABSTRACT The need for a comprehensive education data governance – the regulation of who collects what data, how it is used and why – continues to grow. Technologically, data can be collected by third parties, rendering schools unable to control their use. Legal frameworks partially achieve data governance as businesses continue to exploit existing loopholes. Education data use practices undergo no prior ethical reviews. And at a personal level, students have no agency over these practices. In other words, there is no coherent and meaningful oversight and data governance framework that ensures accountable data use in an increasingly digitalised education sector. In this article, I contextualise the issues arising from education data transactions in one school district in the United States. The case study helps to contextualise what needs governance, who may access education data and how the district governs data use and transactions, emphasising the need for a coherent education data governance but also the limitations of such isolated efforts.

Information system of the university editorial-publishing complex

This article presents the results of designing the structure of the data models necessary for the proper functioning of a database supporting the editorial, proofreading, printing, and publishing activities of an educational organization. The goal of the study is to create a coherent, objective, holistic, and non-redundant data set appropriate to the subject area to support the process of digital transformation of the publishing and publication sphere within an educational organization. The resulting data models reflect the logical structure of databases independent of the choice of a particular database management system. As part of the design, JavaScript Object Notation models and relational data models are developed to create a relational database. The results allow identifying and estimating the resources needed to implement each process, determining all participants affecting the implementation of the relevant processes, and defining the access to resources needed by certain participants in the process.

Adaptative Perturbation Patterns: Realistic Adversarial Learning for Robust Intrusion Detection

Adversarial attacks pose a major threat to machine learning and to the systems that rely on it. In the cybersecurity domain, adversarial cyber-attack examples capable of evading detection are especially concerning. Nonetheless, an example generated for a domain with tabular data must be realistic within that domain. This work establishes the fundamental constraint levels required to achieve realism and introduces the adaptative perturbation pattern method (A2PM) to fulfill these constraints in a gray-box setting. A2PM relies on pattern sequences that are independently adapted to the characteristics of each class to create valid and coherent data perturbations. The proposed method was evaluated in a cybersecurity case study with two scenarios: Enterprise and Internet of Things (IoT) networks. Multilayer perceptron (MLP) and random forest (RF) classifiers were created with regular and adversarial training, using the CIC-IDS2017 and IoT-23 datasets. In each scenario, targeted and untargeted attacks were performed against the classifiers, and the generated examples were compared with the original network traffic flows to assess their realism. The obtained results demonstrate that A2PM provides a scalable generation of realistic adversarial examples, which can be advantageous for both adversarial training and attacks.

Numerical evaluation of spin foam amplitudes beyond simplices

We present the first numerical calculation of the 4D Euclidean spin foam vertex amplitude for vertices with hypercubic combinatorics. Concretely, we compute the amplitude for coherent boundary data peaked on cuboid and frustum shapes. We present the numerical algorithms to explicitly compute the vertex amplitude and compare the results in different cases to the semiclassical approximation of the amplitude. Overall we find good qualitative agreement of the amplitudes and evidence of convergence of the asymptotic formula to the full amplitude already at fairly small spins, yet also differences in the frequency of oscillations and a phase shift absent in the 4-simplex case. However, due to rapidly growing numerical costs, we cannot reach sufficiently high spins to prove agreement of both amplitudes. Lastly, this setup allows us to explore nonuniform vertex amplitudes, where some representations are small while others are large; we find indications that scenarios might exist in which the semiclassical amplitude is a valid approximation even if some spins remain small. This suggests that the transition of the quantum to the semiclassical regime (for a single vertex amplitude) is intricate.

VODCA2GPP – a new, global, long-term (1988–2020) gross primary production dataset from microwave remote sensing

Abstract. Long-term global monitoring of terrestrial gross primary production (GPP) is crucial for assessing ecosystem responses to global climate change. In recent decades, great advances have been made in estimating GPP and many global GPP datasets have been published. These datasets are based on observations from optical remote sensing, are upscaled from in situ measurements, or rely on process-based models. Although these approaches are well established within the scientific community, datasets nevertheless differ significantly. Here, we introduce the new VODCA2GPP dataset, which utilizes microwave remote sensing estimates of vegetation optical depth (VOD) to estimate GPP at the global scale for the period 1988–2020. VODCA2GPP applies a previously developed carbon-sink-driven approach (Teubner et al., 2019, 2021) to estimate GPP from the Vegetation Optical Depth Climate Archive (Moesinger et al., 2020; Zotta et al., 2022​​​​​​​), which merges VOD observations from multiple sensors into one long-running, coherent data record. VODCA2GPP was trained and evaluated against FLUXNET in situ observations of GPP and compared against largely independent state-of-the-art GPP datasets from the Moderate Resolution Imaging Spectroradiometer (MODIS), FLUXCOM, and the TRENDY-v7 process-based model ensemble. The site-level evaluation with FLUXNET GPP indicates an overall robust performance of VODCA2GPP with only a small bias and good temporal agreement. The comparisons with MODIS, FLUXCOM, and TRENDY-v7 show that VODCA2GPP exhibits very similar spatial patterns across all biomes but with a consistent positive bias. In terms of temporal dynamics, a high agreement was found for regions outside the humid tropics, with median correlations around 0.75. Concerning anomalies from the long-term climatology, VODCA2GPP correlates well with MODIS and TRENDY-v7 (Pearson's r 0.53 and 0.61) but less well with FLUXCOM (Pearson's r 0.29). A trend analysis for the period 1988–2019 did not exhibit a significant trend in VODCA2GPP at the global scale but rather suggests regionally different long-term changes in GPP. For the shorter overlapping observation period (2003–2015) of VODCA2GPP, MODIS, and the TRENDY-v7 ensemble, significant increases in global GPP were found. VODCA2GPP can complement existing GPP products and is a valuable dataset for the assessment of large-scale and long-term changes in GPP for global vegetation and carbon cycle studies. The VODCA2GPP dataset is available at the TU Data Repository of TU Wien (https://doi.org/10.48436/1k7aj-bdz35, Wild et al., 2021).